United States Department of Agriculture

Forest Rocky Mountain General Technical Report

Service Research Station RMRS-GTR-351 July 2016

Ecohydrologic Impacts of Rangeland 

Fire on Runoff and Erosion: A Literature 

Synthesis

Frederick B. Pierson and C. Jason Williams 
Pierson, Frederick B.; Williams, C. Jason. 2016. Ecohydrologic impacts of rangeland 

fire on runoff and erosion: A literature synthesis. Gen. Tech. Rep. RMRS-GTR-351. 

Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research 

Station. 110 p.

Abstract

Fire can dramatically influence rangeland hydrology and erosion by altering ecohydrologic 

relationships. This synthesis presents an ecohydrologic perspective on the effects of fire on 

rangeland runoff and erosion through a review of scientific literature spanning many decades. 

The objectives are: (1) to introduce rangeland hydrology and erosion concepts necessary for 

understanding hydrologic impacts of fire; (2) to describe how climate, vegetation, and soils 

affect rangeland hydrology and erosion; and (3) to use examples from literature to illustrate 

how fire interacts with key ecohydrologic relationships. The synthesis is intended to provide a 

useful reference and conceptual framework for understanding and evaluating impacts of fire 

on rangeland runoff and erosion.

Keywords: ecohydrology, fire effects, infiltration, rangeland hydrology, runoff, soil erosion, 

soil water repellency, ecohydrology resilience, hillslope hydrology, hydrologic response, 

postfire response, soil response

Authors

Frederick B. Pierson is the Research Leader and a Supervisory Research Hydrologist 

and C. Jason Williams is a Research Hydrologist with the Northwest Watershed Research 

Center, USDA Agricultural Research Service, Boise, Idaho. To contact, email F.B. Pierson at, 

fred.pierson@ars.usda.gov.

Acknowledgments

We sincerely thank Thomas Thurow and Bradford Wilcox for their reviews and comments, 

which greatly helped to improve this manuscript. We greatly appreciate the manuscript 

reviews and recommended revisions provided by the Steering Committee for the Great Basin 

Fire Science Exchange, including Mark Brunson, Steve Bunting, Jeanne Chambers, Cheri 

Howell, Elizabeth Leger, Mike Pellant, and Brad Schultz. We also thank Eugénie MontBlanc 

and Lael Gilbert for extensive editing of the manuscript and for editorial improvements to 

the manuscript. This work was supported by the U.S. Department of Agriculture, Agricultural 

Research Service, Northwest Watershed Research Center, the Great Basin Fire Science 

Exchange (funded by the Joint Fire Science Program), and the Sagebrush Steppe 

Treatment Evaluation Project (funded by the Joint Fire Science Program, the Bureau of Land 

Management, and the National Interagency Fire Center). This is Contribution Number 93 of 

the Sagebrush Steppe Treatment Evaluation Project.

Cover Photo. Prescribed fire at the Reynolds Creek Experimental Watershed, Idaho (photo: USDA 

Agricultural Research Service, Northwest Watershed Research Center, Boise, Idaho).

All Rocky Mountain Research Station publications are produced by U.S. government employees and are in the 

public domain and available at no cost. Even though U.S. Forest Service publications are not copyrighted, they are 

formatted according to U.S. Department of Agriculture standards and research findings and formatting cannot be 

altered in reprints. Altering content or formatting, including the cover and title page, is strictly prohibited.
CONVERSION FACTORS

Multiply By To obtain

degree Celsius (°C) 1.8, and then 

add 32 degree Fahrenheit (°F)

millimeter (mm) 3.94 × 10−2 inch (in)

centimeter (cm) 3.94 × 10−1 inch (in)

meter (m) 3.28 feet (ft)

kilometer (km) 6.21 × 10−1 mile (mi)

gram (g) 3.53 × 10−2 ounce (oz)

kilogram (kg) 2.205 pound (lb)

square meter (m2) 10.76 square foot (ft2)

square meter (m2) 2.47 × 10−4 acre (ac)

hectare (ha) 2.47 acre (ac)

square kilometer (km2) 3.86 × 10−1 square mile (mi2)

square kilometer (km2) 247 acre (ac)

cubic meter (m3) 35.3 cubic foot (ft3)

liter (L) 3.53 × 10−2 cubic foot (ft3)

millimeter per hour (mm h−1) 3.94 × 10−2 inch per hour (in h−1)

liter per second (L s−1) 3.53 × 10−2 cubic foot per second (ft3 s−1)

cubic meter per second (m3 s−1) 35.3 cubic foot per second (ft3 s−1)

gram per square meter (g m−2) 4.46 × 10−3 ton per acre (t ac−1)

kilogram per hectare (kg ha−1) 4.46 × 10−4 ton per acre (t ac−1)

megagram (Mg) 1.102 ton (t) 
Contents

Introduction.......................................................................................................................1

Section 1: Hillslope and Watershed Hydrology.............................................................2

The Hydrologic Cycle.....................................................................................................2

Precipitation ...................................................................................................................3

Interception ....................................................................................................................7

Infiltration........................................................................................................................8

Soil Water Storage and Ground Water Recharge ........................................................10

Evapotranspiration .......................................................................................................11

Surface Runoff and Streamflow ...................................................................................12

Water Balance..............................................................................................................14

Section 2: Sediment Detachment, Transport, and Mass Wasting..............................15

Rainsplash and Sheetflow Processes..........................................................................15

Concentrated Flow Processes .....................................................................................17

Gully Erosion Processes ..............................................................................................18

Mass Movement Processes .........................................................................................19

Spatial and Temporal Variations of Processes.............................................................21

Section 3: Climate-Vegetation-Soil-Hydrology Interactions.......................................23

Climate as a Driver of Hydrologic Response ...............................................................23

Vegetation Influences on Water Availability at the Surface and Near-Surface.............26

Interception Effects on Water Availability ...........................................................................26

Canopy Influence on Soil Microclimate, Evapotranspiration, and 

 Antecedent Soil Water ................................................................................................30

Cover Influences on Infiltration, Runoff, and Water Transfer and Storage...................32

Vegetation and Cover Influences on Infiltration and Runoff Generation............................33

Plant Use of Subsurface Water and Its Influence on Runoff..............................................43

Effects of Soil Water Repellency on Runoff Generation ....................................................46

Cover Influences on Sediment Detachment and Transport .........................................50

Surface Protection from Raindrop Detachment .................................................................50

Cover Effects on Sheetflow Erosion...................................................................................51

Cover Effects on Concentrated Flow Erosion ....................................................................51

Section 4: Impacts of Fire on Rangeland Runoff and Erosion...................................53

Fire Behavior and Regimes on Rangelands ................................................................53

Fire Effects that Dictate Hydrologic Response.............................................................54

Reduced Interception and Surface Protection ...................................................................54

Physical, Chemical, and Biological Alteration of Soils .......................................................56

Exacerbation, Alteration, and Formation of Soil Water Repellency....................................57

Fire Effects on Infiltration and Runoff Generation ........................................................61

Rainsplash and Sheetflow Processes................................................................................62

Hillslope- to Watershed-Scale Runoff ................................................................................67

Fire Effects on Soil Erosion by Water...........................................................................69

Rainsplash and Sheetflow Processes................................................................................69

Concentrated Flow Processes ...........................................................................................71

Hillslope- to Watershed-Scale Erosion...............................................................................72

Assessing Postfire Hydrologic Vulnerability and Risk ..................................................75

Determining Site Susceptibility and Hydrologic Recovery ...........................................77

Summary and Conclusions ...........................................................................................79

References ......................................................................................................................80

ii
USDA Forest Service RMRS-GTR-351. 2016. 1

Introduction

Fire initiates disturbances that alter soil properties and the condition and structure of 

vegetation and ground cover (Miller et al. 2013), potentially resulting in amplified runoff 

and soil loss (Shakesby and Doerr 2006; Robichaud et al. 2010; Pierson et al. 2011; 

Williams et al. 2014b). (Note that in this synthesis, citations are listed in chronological order to reflect the progression of knowledge on a given topic.) The hydrologic 

and erosional responses to fire vary with the intensity, severity, and spatial scale of the 

disturbance, the stability and resilience of the affected ecosystem, and the prevailing 

precipitation regime. Our historical understanding of these responses for rangeland ecosystems comes mostly from anecdotal reports and from short-term, small (0.25 to 1 m2) 

field plot studies of hydrologic behavior on gently sloping, semiarid shrub and grassland 

sites (Pierson et al. 2002a).

In recent years, researchers have expanded the inference space by studying wildfire 

and prescribed burning effects on runoff and erosion rates from steeply sloped shrublands 

(Pierson et al. 2001a, 2002b, 2008a,b, 2009), woodlands (Pierson et al. 2013, 2014; 

Williams et al. 2014a), and shrub-forest interface sites (Johansen et al. 2001). These 

studies, however, represent a minor portion of the diverse plant communities and soil 

types that occur on sloping rangelands. Despite these limitations, this review presents 

fire impacts on rangeland hydrology by (1) explaining fundamental hydrologic processes 

necessary for understanding hillslope and watershed runoff and erosion responses; 

(2) describing how climate, vegetation, and landscape properties interact with these 

principal processes to influence hydrologic and erosional behavior; and (3) providing 

examples from literature to illustrate these relationships with respect to fire and postfire 

hydrologic recovery. The hillslope scale is emphasized, given the lack of literature on 

watershed-scale fire effects for rangelands. Our geographic focus is the western United 

States, although we include some literature from other semiarid regions around the globe. 

We include literature from dry forests because of similarities in the postfire runoff and 

erosion processes across the rangeland-dry forest continuum in the Intermountain West 

(Williams et al. 2014b). The goal of this review is to provide the reader a background for 

understanding rangeland hydrology processes and a conceptual framework from which 

to understand how fire affects rangeland hydrology and erosion across a range of site and 

vegetative conditions and across precipitation regimes.
2 USDA Forest Service RMRS-GTR-351. 2016.

Section 1: Hillslope and Watershed Hydrology

The Hydrologic Cycle

The hydrologic cycle (fig. 1) refers to the continuous pathways in which water 

moves in different phases through the atmosphere; on, into, through, and across the 

land surface; to oceans and storage reservoirs; and upwards back into the atmosphere 

(Dunne and Leopold 1978; Branson et al. 1981; Maidment 1993; Hornberger et al. 1998; 

Dingman 2002; Brutsaert 2005). Knowledge of the hydrologic cycle provides a useful 

framework from which to conceptualize and understand vegetation-soil-climatehydrology interactions and to understand how fire and other disturbances influence runoff 

and erosion behavior (Dunne and Leopold 1978). For a particular hillslope or watershed, 

the cycle consists of water inflow, transit and storage, and outflow. Inflow primarily 

occurs as precipitation, overland flow and streamflow from upslope areas, and ground 

water returns from springs and into streambeds and lakebeds. Transit and storage components of water arriving at the land-atmosphere interface include precipitation interception, 

infiltration, and water storage on and underneath the land surface. Outflows include 

gaseous phase losses to the atmosphere through evaporation and transpiration, and liquid 

water losses to plant use, watershed runoff, and deep drainage to aquifers. The remainder 

of this section explains the fundamental components of the hydrologic cycle.

Figure 1—Illustration of generalized hydrologic cycle for a hillslope showing directional inflows (rainfall, 

snowfall, infiltration) and outflows (evapotranspiration, losses to interception, overland flow, deep drainage, 

streamflow, and subsurface flow out).
USDA Forest Service RMRS-GTR-351. 2016. 3

Precipitation

The primary water input to the land-atmosphere interface is precipitation. 

Precipitation forms when warm, moist air at the Earth’s surface rises into the atmosphere 

and cools by adiabatic expansion (Branson et al. 1981; Dingman 2002). During cooling, 

water vapor condenses on small particles of matter, forming water droplets. The droplets 

remain suspended until gravity overcomes the upward force of the rising air mass, resulting in precipitation. Precipitation falls as snow or ice where the air temperature above the 

ground surface is 0 °C; otherwise precipitation falls as rain. Uplifting of warm air occurs 

through either frontal, convective, or orographic lifting, and the lifting process dictates 

the resulting storm type.

Frontal lifting occurs when warm air and cool air masses collide, forcing the warm 

air mass upwards and over the cool air mass. Warm fronts advancing toward cool air 

masses generate prolonged low-intensity (quantity per unit of time), gentle rainfall over 

large land areas, whereas large cold fronts advancing toward large moist warm air masses 

facilitate high-intensity rainfall of shorter duration in a narrow advancing band. Occluded 

fronts occur when a cold air mass overtakes a warm air mass (and collides with another 

cold air mass), resulting in cold air everywhere at the surface and warm air above. The 

rising warm air over the cool air at the surface generates precipitation, commonly at an 

extremely high intensity (Dingman 2002).

Convective lifting is associated with localized heating of surface air. Warm surface 

air becomes buoyant, rises, and expands due to lower atmospheric pressure. The air mass 

cools as it expands and convective clouds form. As the air mass cools, moisture particles 

begin to coalesce therein. Convective lifting is most common during warm moist periods, 

and generates intense rainfall and hailstorms over small areas scattered across the landscape. However, large-scale convective events may occur and, when over a large enough 

area, facilitate flash flood events.

Orographic lifting occurs when a warm air mass is forced upward along the windward side of a topographic barrier (such as a mountain range). Precipitation generated 

from orographic lifting occurs on the windward side of the barrier and usually increases 

with elevation. Rain shadows form on the leeward side of the barrier as the air parcel 

crests and warms, and clouds dissipate. Orographic events are often associated with 

frontal or convective events that encounter a topographic barrier.

Precipitation is measured as a depth over some duration or period of time (daily, 

monthly, seasonally, or annually) and is reported for individual storms as an intensity. 

Precipitation data for towns, watersheds, and other locales are available from areaspecific climate stations, precipitation gauges, and snow surveys with varying periods 

of record (years of data). The various types of precipitation gauges, surveys (fig. 2), and 

methods for extrapolating and applying precipitation data from available sources can be 

found in most hydrology textbooks (see Dunne and Leopold 1978; Branson et al. 1981; 

Dingman 2002; McCuen 2004; Brutsaert 2005). Here we focus our discussion on the 

types of precipitation measurements commonly reported.

Rainfall depth is the quantity of accumulated rainfall (expressed as a length 

measurement such as mm or cm) at a point on the landscape (such as at a rain gauge). 

Rainfall duration is the time period over which a specified event occurred. Rainfall or 

storm intensity is the rainfall rate expressed as depth of accumulation over a specified 
4 USDA Forest Service RMRS-GTR-351. 2016.

interval of time (for example, mm h-1 or cm h-1). Depth and duration variables are often 

expressed together to define a storm event in terms of a depth-duration relationship 

(48 mm during a 45-min interval) or an intensity-duration relationship (64 mm h-1 for 

45 min) and are related to specified recurrence intervals (frequency) or return periods (for 

example, a 100-year event).

A recurrence interval is an estimate of the interval of time between events of a 

certain intensity or size. A recurrence interval is not the actual time between events of 

the specified intensity or size, but rather represents the probability of that event occurring. For example, the 100-year precipitation event has a 1 in 100 chance, or 1 percent 

probability, of occurring each year. Most climate stations report depth-duration and 

intensity-duration relationships in graphical or tabulated form for a range of return interval storms (depth-duration-frequency or intensity-duration-frequency; fig. 3). Average 

annual rainfall is calculated from gauges with long-term records as the total rainfall catch 

Figure 2—(A) Examples of shielded (right) and unshielded (left) dual precipitation gauge system used by 

the USDA Agricultural Research Service, Northwest Watershed Research Center, at the Reynolds Creek 

Experimental Watershed, Idaho, and (B) snow water equivalent measurement along a snow course transect 

of the USDA Natural Resources Conservation Service (photo A: Agricultural Research Service; photo B: Ron 

Nichols, Natural Resources Conservation Service).

Figure 3—Intensity-duration-frequency graphs for (A) climate station 163x20 at 2,170 m elevation in the 

snowfall-dominated Reynolds Creek Experimental Watershed, Idaho, 1963 to 1998 (Hanson and Pierson 

2001) and (B) climate station 02-8619 at 1,400 m elevation, Tombstone, Arizona, near the summer monsoon 

rainfall-dominated Walnut Gulch Experimental Watershed, 1893 to 2000 (Bonnin et al. 2006).
USDA Forest Service RMRS-GTR-351. 2016. 5

for a number of complete years of record divided by the number of years used. Rainfall 

for a given year may be reported as a percentage of the average annual rainfall (for 

example, 120 percent).

Snowfall is most often measured as a storm-specific depth (accumulation) of newly 

fallen snow at a point, snowpack accumulation at the land surface over some duration 

(daily, monthly, seasonally, or annually), or the snow water equivalent (depth) of newly 

fallen snow or the snowpack. In contrast to rainfall, snowfall accumulation stores water 

at the land surface and releases it for other hydrologic processes more gradually than 

rainfall. Hydrologists are most interested in the snow water equivalent (SWE) within 

accumulated snow, as it represents water availability for the hydrologic cycle (fig. 1) (see 

Dingman 2002).

Snow water equivalent is the depth of water that would result from the complete 

melting of the snowpack of a specified area and is a function of the snowpack density 

and depth over the defined area of interest. The quantity and timing of water delivery 

released from the snowpack depend on SWE and the net energy input into the snowpack 

(Dingman 2002). Snowpack melting begins after the snowpack temperature is isothermal 

at 0 °C. Melt water is retained within the snowpack until the water holding capacity is 

exceeded, initiating delivery of snowmelt. Snowmelt (reported as depth of water) refers 

to the amount of liquid water leaving the snowpack during a given time period. Other 

commonly used terms for snow processes include snowpack ablation and water input. 

Ablation (measured as a depth of water) is the total loss of water substance (snowmelt 

and evaporation) from the snowpack in a given time period. Water input is the total liquid 

water (measured as depth of rain and snowmelt) leaving the snowpack during a given 

time period. As with rainfall, SWE and other snow measurements are available from numerous regional and local climate and precipitation stations. Snowstorms are reported in 

terms of recurrence intervals, and snow water equivalent or snow depth may be reported 

as a depth or percentage of average accumulation for various time steps (such as daily, 

monthly, or annually).

The timing, type, and quantity of precipitation falling at the land-atmosphere 

interface are driven mostly by elevation and geography. Rangelands in the northern and 

central United States receive substantially more annual precipitation than rangelands in 

the desert Southwest (figs. 4 and 5) (see also Branson et al. 1981). In addition to annual 

quantity differences, the timing or seasonality of precipitation inputs varies significantly 

across U.S. rangelands (fig. 5). Precipitation inputs on southwestern U.S. rangelands (fig. 

5E and 5F) occur mostly during the summer monsoonal season (up to 60 to 70 percent 

of annual precipitation can occur during July and August) as intense convective thunderstorms (Branson et al. 1981; Osborn 1983a,b; Mendez et al. 2003; Wainwright 2006; 

Goodrich et al. 2008). Most of the annual precipitation in the northwest and north-central 

United States falls November through May and is snowfall-dominated in mountain 

locations and rainfall-dominated in valley locations (figs. 6 and 7) (Branson et al. 1981). 

Rainfall patterns at these locations usually occur as low-intensity, long-duration events, 

in late autumn or winter, and during a 4- to 8-week spring rainy season. Rain-on-snow or 

rain-on-frozen-soil events are common at mountainous locations in early winter and during transitional snow cover periods in spring (Wilcox et al. 1989; Pierson et al. 2001b). 

Mountain and valley locations experience high-intensity convective storms during the 

dry summer months. Annual precipitation is usually greater at higher elevations than on 
6 USDA Forest Service RMRS-GTR-351. 2016.

valley floors due to adiabatic processes (fig. 6) (see Branson et al. 1981; Dingman 2002). 

Precipitation trends are bimodal for some south-central U.S. rangelands (see Romme 

et al. 2009), with peaks occurring in mid-to-late winter and during summer monsoon 

months (during which 30 to 40 percent of annual precipitation occurs; see Bowen 1996). 

Elevational precipitation trends for the central United States are similar to those occurring 

on northwest and north-central U.S. rangelands.

Figure 4—(A) Annual precipitation (PRISM Climate Group 2011) and (B) landcover (U.S. Geological Survey 

2011) for the western United States.

Figure 5—Average monthly precipitation for western U.S. urban centers immediately adjacent to rangelands 

(PRISM Climate Group 2011). Panels A–C are indicative of annual precipitation in the Inland Northwest. 

Panel D is indicative of annual precipitation trends on central U.S. rangelands. Panels E-F demonstrate the 

influence of the monsoonal season (July–August) on rainfall in the desert Southwest.
USDA Forest Service RMRS-GTR-351. 2016. 7

Interception

Precipitation arriving at the land-atmosphere interface either is intercepted by 

vegetation, rocks, or litter debris or falls unimpeded to the soil surface. Intercepted 

precipitation evaporates into the atmosphere (interception loss) or is transferred as 

liquid water to the soil surface as throughfall or stemflow (Thurow et al. 1987; Návar 

and Bryan 1990; Martínez-Meza and Whitford 1996; Whitford et al. 1997; Wainwright 

et al. 1999; Abrahams et al. 2003; Bhark and Small 2003; Carlyle-Moses 2004; Owens 

et al. 2006). Throughfall reaches the ground surface by passing directly through spaces 

Figure 6—Average monthly precipitation for two climate stations (A – Site 076x59, low elevation; B – 163x20, 

high elevation) located in the Reynolds Creek Experimental Watershed, Idaho (Hanson and Pierson 2001). 

Precipitation differences between the two sites are primarily driven by the differences in elevation.

Figure 7—Reynolds Creek Experimental 

Watershed near Boise, Idaho, where 

precipitation is snow dominated in the 

uplands and rainfall dominated in the 

lowlands (photo: USDA Agricultural 

Research Service).
8 USDA Forest Service RMRS-GTR-351. 2016.

within and between canopies, and includes canopy drip. Canopy drip begins once canopy 

liquid water interception and surface evaporation capacities are exceeded. Stemflow is 

precipitation input that reaches the ground surface by running down stems and trunks of 

vegetation. Gross or bulk precipitation is the precipitation measured in the open, or above 

the canopy. The net precipitation is the gross precipitation arriving at the land-atmosphere 

interface minus total interception loss. Intercepted precipitation retained from throughfall 

and stemflow is termed “static canopy storage” (Dunkerley 2000).

Interception is strongly influenced by the precipitation frequency and intensity and 

by the type and structure of the vegetative community (Branson et al. 1981; Owens et 

al. 2006; Dunkerley 2008). Interception losses from a series of small storm and clearing 

events are proportionately greater than those from large, prolonged rainfall events 

(Rowe 1948; Hamilton and Rowe 1949; Owens et al. 2006). Prolonged events saturate 

plant surfaces and the resulting interception rate becomes equal to the evaporation 

rate. Intercepted precipitation is evaporated during clear periods between short events, 

reestablishing a portion of the interception capacity. This results in a large proportion 

of each small storm’s gross precipitation being applied to interception as compared to a 

prolonged or large event. Interception is usually greater from conifer than broad-leaved 

tree species and is greater from trees species than from shrubs and grasses.

Variations in the canopy density of individual plants and the vegetative community 

complicate quantification of interception losses over large scales. Therefore interception 

terms are commonly reported as a depth or volume of water or as the percentage of 

precipitation falling on an individual plant or at a point during the period of interest. 

Interception losses over large areas are determined by spatially aggregating interception 

losses by plant species or area representations (West and Gifford 1976). Dunkerley 

(2000) provides a brief overview of interception terminology, measurement methods, and 

estimation approaches.

Infiltration

The rate at which water infiltrates into the soil profile is influenced by the amount 

and arrival rate of water at the ground surface, the ability of the soil to conduct water into 

and through the soil profile, and the slope, roughness, and chemical characteristics of the 

soil surface (Dunne and Leopold 1978; Knapp 1978; Branson et al. 1981; Selby 1993; 

Hillel 1998; Dingman 2002; Brutsaert 2005). Infiltration is reported on a point scale as 

a rate (depth per unit of time) or the cumulative depth of water (for example mm or cm) 

that infiltrates into the soil profile over some period of time (such as a storm event). For 

rainfall events, water availability is a function of the intensity and duration of the storm 

(water input rate), interception losses, and the ability of the surface to detain or pond 

water (surface detention).

Surface detention is a function of the land surface slope, the roughness or 

microtopography of the soil surface, and the quantity and structure of litter and woody 

debris present. Gentle slopes with rough surfaces and substantial amounts of litter and 

debris generally detain more water on the ground surface than steep slopes that are bare 

or devoid of ground cover. Snowmelt contributions to infiltration are also influenced by 

the water input rate, interception losses, and surface detention. The snowpack generally 
USDA Forest Service RMRS-GTR-351. 2016. 9

provides a more gradual release of water to the ground surface than does rainfall. 

However, rapid releases of water from a snowpack may occur during peak snowmelt or 

rain-on-snow events (Dingman 2002).

Water infiltrates soil mainly due to a negative pressure gradient or suction (matrix 

suction) into the soil matrix and secondarily due to gravity (Knapp 1978; Branson et al. 

1981; Selby 1993; Hillel 1998; Hornberger et al. 1998; Dingman 2002; Brutsaert 2005). 

Matrix suction results from the physical affinity of water to soil-particle surfaces and 

pores, and decreases with increasing soil wetness (Hillel 1998). In general, infiltration 

is high in the early stages of water input into dry soil, then decreases as the surface soil 

becomes increasingly wet, and approaches a relatively steady state (steady state infiltration rate) as soil becomes saturated. Decreased infiltration over time following rainfall 

results mainly from decreased matrix suction with wetting, but also may occur due to 

surface sealing (Assouline 2004) and compaction from raindrop impact or shrink/swell 

soil properties.

Porous or rough surfaces are usually more conductive than uniform surfaces. 

However, high-intensity rainfall can break apart highly conductive porous structure 

or aggregates of surface soils, facilitating infilling of soil pores with fine soil particles 

(Thornes 1980; Selby 1993). Infilling of pores creates a hydrologic barrier. Compaction 

reduces pore size and can also create a hydrologic barrier and reduce the surface soil infiltration capacity. Infiltration capacity refers to the maximum rate that water can enter soil 

in a given condition. Hydrologic barriers may also form from freezing of surface soils or 

swelling of clay soils. Frozen soils near saturation can form “concrete frost” layers with 

very low conductivity (Blackburn and Wood 1990; Blackburn et al. 1990).

Swelling properties of clay soils may decrease the conductivity of pore spaces 

upon wetting, reducing infiltration with increased soil wetness. The presence of organic 

matter can increase or decrease the infiltration capacity. Organic matter is associated 

with greater aggregate stability (Cerdà 1998b), low bulk density, and formation of large 

pores (macropores) or cracks in the soil surface. Aggregate stability and low bulk density 

values facilitate maintenance of large pore voids and macropores that transfer water 

rapidly downward into or laterally through the soil profile. In contrast, organic matter 

may contribute to water-repellent (hydrophobic) conditions, which impede infiltration 

(Meeuwig 1971; DeBano and Rice 1973; Doerr et al. 2000, 2009). The formation of 

water-repellent soils and the effects on infiltration are discussed in more detail in Section 

3, Effects of Soil Water Repellency on Runoff Generation.

Infiltration into wet soils is significantly influenced by the saturated hydraulic 

conductivity of the soil profile (Knapp 1978; Branson et al. 1981; Selby 1993; Hillel 

1998; Dingman 2002). Once the soil profile becomes wet, any further water input is 

partially dependent on the redistribution or downward transmittance (percolation) of 

existing soil water. Hydraulic conductivity (measured as length per unit time) refers to the 

rate at which water is redistributed through the soil profile and is a function of pore space 

connectivity (soil porosity and soil structure) and soil wetness. Hydraulic conductivity increases with increasing soil wetness due to greater connectivity of wet pores (wet 

flowpaths). Under saturated conditions, all pore spaces are filled, and higher conductivity 

occurs where large and continuous pores represent most of the pore volume. For example, 

sandy, coarse-grained soils with extensive large pore connectivity will transmit water 

downward more rapidly under saturated conditions than fine-grained clayey soils with 
10 USDA Forest Service RMRS-GTR-351. 2016.

numerous micropores. Therefore, infiltration rates for wet soil conditions approximate 

saturated hydraulic conductivity and are generally greater for coarse-grained or wellaggregated soils. Saturated hydraulic conductivity commonly decreases with soil depth 

due to decreases in porosity in deeper portions of soil profiles.

Finally, redistribution and, hence, infiltration are also influenced by the structure 

of the soil profile. The presence of an impeding/restrictive layer (layer of low hydraulic 

conductivity) may retard water movement during infiltration. The rate of water movement 

through restrictive layers is reduced relative to the remainder of the soil profile. Impeded 

flow is often overcome through bypass (macropore or preferential) flow. The processes 

and measurement methods for water infiltration and redistribution in unsaturated and 

saturated soils are described in detail by Hillel (1998) and Dingman (2002).

Soil Water Storage and Ground Water Recharge

Some of the water infiltrating the ground surface is retained in the unsaturated zone 

as soil water storage, and some passes through the profile into the saturated zone as deep 

drainage or ground water recharge. The unsaturated zone encompasses the soil water 

or rooting zone, an intermediate zone, and the capillary fringe immediately overlying 

the saturated zone (Hornberger et al. 1998; Dingman 2002). The soil water zone is the 

uppermost portion of the soil profile where soil water is extracted and used by plants or 

evaporated into the atmosphere. The intermediate zone is often referred to as the zone of 

aeration and is the area between the soil water zone and the capillary fringe. Water enters 

the intermediate zone by percolation from above and exits by gravity drainage. Pore 

spaces in the capillary fringe are saturated or are near saturation and pore water is held 

there by capillary forces (Hornberger et al. 1998; Dingman 2002). Generally, less than 1 

percent of water entering the soil profile passes through the soil water and intermediate 

zones into deep storage below the capillary fringe. In this review we restrict our discussion on soil water movement and storage to the unsaturated zone because most surface 

responses are associated with soil water content in the rooting zone of the soil profile. 

Explanations of the soil physics that dictate soil water movement and retention in the 

unsaturated and saturated zones are provided in Kramer and Boyer (1995), Hillel (1998), 

and Dingman (2002).

The water or moisture content of the soil profile dictates water availability for 

plants and biological processes, and is a function of the soil texture and structure (Kramer 

and Boyer 1995). Soil water content at any point in time is measured as volumetric or 

gravimetric water content (see Dingman 2002). Volumetric soil water content is the ratio 

of water volume to soil volume, and gravimetric soil water content is the mass of water 

per unit mass of dry soil. Soil water content between precipitation events or periods is 

referred to as the “antecedent water/moisture content.” The distribution, connectivity, 

and size of the soil voids greatly influence the water content and degree of wetness (the 

ratio of water content to porosity). Water in capillaries or micropores is tightly held to 

soil particles by matrix potential, whereas large and connected pores drain rapidly due 

to gravity (Kramer and Boyer 1995). Excluding evaporative demands, total soil water 

storage (product of volumetric water content and thickness of the layer) results from the 

resolution of the matrix and gravitation forces, and plant water use.
USDA Forest Service RMRS-GTR-351. 2016. 11

Water content available for plants is the difference between the field capacity 

content and permanent wilting point water content (Kramer and Boyer 1995; Dingman 

2002). Field capacity is the water content held against gravity, and refers to the relatively 

stable soil water content at which continued downward drainage is negligible. The permanent wilting point (Kramer and Boyer 1995; Dingman 2002) is the soil water content at 

which water availability is too low to support plant transpiration demands and the point at 

which plants wilt (see Section 1, Evapotranspiration). Field capacity and water retention 

are generally greater for clay soils than for sandy soils and are intermediate for loams. 

Clay soils are compact and cohesive (with numerous micropores) and drain slowly. In 

contrast, sandy soils are noncohesive, have large and connective voids, drain rapidly, and 

possess limited water storage capacity. The presence of organic matter in soils usually 

increases the water storage capacity.

Evapotranspiration

Evapotranspiration is the primary loss mechanism for precipitation inputs in most 

geographic areas of the United States and may constitute 50 to almost 100 percent 

of incoming annual precipitation (see Branson et al. 1981; Kramer and Boyer 1995; 

Hornberger et al. 1998; Dingman 2002; Brutsaert 2005). Evapotranspiration losses arise 

from two primary processes of liquid water conversion to water vapor: evaporation and 

transpiration. Evaporation is the process by which liquid or solid water from ground and 

vegetative surfaces, from rivers and lakes, and from ice and snow is converted to water 

vapor and transferred back into the atmosphere. Evaporation occurs when atmospheric 

vapor pressure is lower than vapor pressure of the evaporative surface. In the most basic 

sense, evaporation is equal to a coefficient for barometric pressure and wind velocity 

multiplied by the difference in maximum vapor pressure at the surface and the vapor 

pressure in the air above the evaporative surface (Dalton’s Law) (see Branson et al. 1981 

and Dingman 2002).

Transpiration is the direct evaporation of liquid water from within the leaves of 

plants. During transpiration, water vapor diffuses to the atmosphere from leaf surfaces, 

forming a water deficit within foliage cells. This deficit is transmitted from foliage via 

water columns within plant xylem tissue through branches, stems, and large roots to 

fine roots, where soil water uptake occurs. Transpiration is a biological evaporative 

process that is influenced by plant leaf, stem, and root structures, water use strategies, 

soil microclimate, water availability, and plant influences on wind and the aboveground 

microclimate (Branson et al. 1981; Kramer and Boyer 1995; Hornberger et al. 1998; 

Dingman 2002).

In order for evapotranspiration to occur there must be (1) a positive net flow of energy to the evaporative or transpiring surface, (2) water available for conversion to water 

vapor, and (3) a flow of vapor away from the surface (see Hornberger et al. 1998 and 

Dingman 2002). The conditions that control the net flow of energy determine the energy 

available for vaporization of liquid or solid water. Energy arrives at a respective surface 

as incoming solar energy and is either reflected or absorbed, depending on the surface 

reflectivity (albedo). Light-colored surfaces like freshly fallen snow have much higher 

albedo than do dark-colored surfaces such as black soil, and reflect much of the arriving 
12 USDA Forest Service RMRS-GTR-351. 2016.

solar energy back into the atmosphere. Some of the arriving energy is consumed to heat 

(sensible heat) the surface and air around it. The evaporation process consumes additional 

energy (latent heat) in the conversion of liquid or solid water to water vapor. Therefore 

the net flow of energy required for evapotranspiration must satisfy energy reflected and 

energy transferred as sensible and latent heat (Kramer and Boyer 1995; Hornberger et al. 

1998; Dingman 2002).

During water-limited conditions, incoming energy is consumed more in the heating 

of the surface and the air than as latent heat for water vaporization. In contrast, in wet 

conditions, evapotranspiration is dictated by the quantity of incoming radiant energy, 

the dryness of the air, and the efficiency of wind to transport water vapor away from the 

surface. Evapotranspiration may be reported as potential or actual evapotranspiration and 

is usually provided as a depth of water at a point per period of time (for example, annual 

evapotranspiration). Potential evapotranspiration is water loss that occurs when a surface 

is fully wet and no soil water deficiencies exist relative to plant water use. Actual evapotranspiration refers to water loss that occurs when water availability is reduced below 

that found for a wet surface. Methods to measure and calculate evapotranspiration, along 

with more detailed explanations of evapotranspiration processes, are found in Kramer and 

Boyer (1995), Hornberger et al. (1998), and Dingman (2002).

Surface Runoff and Streamflow

The mechanisms for surface runoff generation include Hortonian and saturated 

overland flow generation, direct precipitation into stream channels, and ground water 

returns to the land surface or stream channels (Horton 1933; Dunne 1978; Selby 1993; 

Hornberger et al. 1998; Dingman 2002). Hortonian overland flow (Horton 1933) is 

generated when water input on land exceeds the rate at which water can infiltrate the 

soil. Hortonian flow (also called infiltration-excess flow) is most common under intense 

rainfall in sloping semiarid to arid regions (water-limited) or where surface conductivities 

are low. Saturation overland flow (saturation-excess flow) results from continued water 

input at the surface of a saturated soil profile. Ponded and saturated soil surfaces shed 

any additional water inputs from the atmosphere. The hillslope or watershed area (source 

area) contributing to saturated overland flow varies seasonally or during precipitation 

events. Hydrologists commonly refer to this variable zone of saturation overland flow as 

the “variable source area” (see Selby 1993; Hornberger et al. 1998; Dingman 2002).

Infiltration- and saturation-excess overland flows may create sheetflow (interrill) or 

concentrated flow (rills), or a combination thereof, on sloping terrain. Sheetflow refers to 

overland flow as a thin, relatively spatially connected film or sheet on the land surface. 

Concentrated flow is runoff that accumulates or converges into well-defined microchannels or rills. Direct precipitation into stream channels occurs during all precipitation 

events and can contribute significantly to peak and total event streamflows. Subsurface 

return or event flow constitutes only a small portion of event streamflow. However, areas 

of ground water mounding or ridging and hillslopes with extensive macropore networks 

may contribute substantially to runoff generation and streamflow response (Wilcox et al. 

1997; see Dingman 2002).
USDA Forest Service RMRS-GTR-351. 2016. 13

Streamflow is the flow rate or discharge of water (measured as volume per unit 

of time) along a defined natural channel and is partitioned as either base or event flow 

(Dunne and Leopold 1978; Dingman 2002; McCuen 2004). Base flow refers to the 

portion of the streamflow that cannot be attributed to a particular precipitation event and 

is generally assumed to be ground water return flow into stream channels. Base flow 

of a particular stream or drainage network (pattern of streams within a watershed) is 

relatively consistent from year to year and depends mostly on the availability of ground 

water returns. Stream baseflow may be spatially variable where exchanges of surface 

water and ground water facilitate streamflow gains or losses. Event flow is the portion of 

streamflow directly resulting from event effective water input, and may also be referred 

to as storm runoff or storm flow. Effective water input is the water input from a particular 

precipitation event, usually in the form of direct precipitation into streams and Hortonian 

or saturated overland flow. Time variability and space variability in event flow generally 

increase with increasing watershed size due to temporal and spatial variations in precipitation water input, overland flow generation, and streamflow routing.

Watershed or hillslope response to precipitation events is commonly quantified 

graphically and analyzed by using streamflow hydrographs and precipitation hyetographs 

(fig. 8) (Hornberger et al. 1998; Dingman 2002; McCuen 2004). Hydrographs depict 

stream discharge versus time for a point along a stream channel. Hyetographs quantify 

water input (precipitation or snowmelt) at a point versus time and may be shown on a secondary x- and y-axis of a streamflow hydrograph to view respective stream responses to 

water-input events (fig. 8). The shape of the streamflow hydrograph provides qualitative 

and quantitative interpretation of watershed response to varying water input. The event 

response is evident on the hydrograph by an increase in discharge (rising limb) greater 

than base flow, to a peak (peak discharge), followed by a decrease to baseflow (falling 

or recession limb) (fig. 8). Hydrologists are particularly interested in watershed response 

time, time to peak runoff, peak discharge, and cumulative runoff. The response time and 

Figure 8—Example streamflow hydrograph and precipitation hyetograph. Precipitation and streamflow shown 

are from a convective thunderstorm event (~22 mm rainfall during 2 hours) occurring July 21, 1971, in the 

Reynolds Creek Experimental Watershed as recorded at the Tollgate Weir Site 116x83 (USDA Agricultural 

Research Service 2011a). Event and base flow contributions to streamflow are separated by the dashed 

gray line. Arrows and callouts indicate rising limb, peak discharge, and falling limb of the hydrograph as 

responses to the storm event.
14 USDA Forest Service RMRS-GTR-351. 2016.

time to peak refer to the time it takes for runoff to occur and then to peak following water 

input initiation. Peak discharge is the maximum discharge that occurs during a particular 

event. Cumulative runoff is the integration of runoff rates with respect to runoff duration. 

A short response time, a short time to peak runoff, and a steep rising limb indicate rapid 

or flashy watershed response to a water input event.

The overall response to a particular event, and the resultant hydrograph shape, 

depends on the size of the drainage area, soils and geology, slope, and land use/vegetation 

patterns (Dingman 2002; McCuen 2004). Large watersheds commonly exhibit delayed 

responses to precipitation events unless the event is near the stream outlet or occurs over 

a large, contiguous area. Watersheds or hillslopes with low infiltration rates or steep 

slopes, or both, typically have short response times, high peak discharge, and steep rising 

limbs. Runoff response is delayed and discharge is usually low where extensive vegetation and ground cover exist and land use favors water retention. Shorter event and peak 

response times, higher peak discharges, and steepened rising limbs with respect to similar 

rainfall events postdisturbance indicate degraded surface conditions.

An individual hydrograph does not specifically identify the condition eliciting the 

response. However, hydrographs can be compared for similar precipitation events over 

a range of watershed conditions to infer cause-and-effect relationships where supportive 

watershed/hillslope data are available. Infiltration responses to water-input events may 

also be quantified in hydrograph form, as the inverse of the runoff relationships (see 

Meeuwig 1971; Dunne 1978; Selby 1993; Hillel 1998; Hornberger et al. 1998; Dingman 

2002).

Water Balance

The components of the water cycle with respect to a specified watershed and time 

period represent the area water balance (see Branson et al. 1981; Dingman 2002; Wilcox 

et al. 2003b). The generalized water balance is expressed as:

P + Gin – Q – ET – Gout = ΔS (Equation 1)

where P is precipitation, Gin is incoming ground water, Q is streamflow or surface 

runoff, ET is evapotranspiration, Gout is outgoing ground water, and ΔS is the change in 

water storage over the period of interest. Over annual scales, the water balance provides 

an accounting of the annual water budget. For rangeland ecosystems, runoff usually 

amounts to less than 10 percent of the annual water budget (Wilcox et al. 2003b). Nearly 

all of the remainder of precipitation falling on rangelands is lost to evapotranspiration. 

Evapotranspiration may exceed precipitation during dry years. Deep drainage of soil 

water beyond the rooting zone as ground water recharge, Gout, is usually less than a few 

millimeters (Wilcox et al. 2003b). The net change in water storage is generally considered 

to be zero over long time periods (such as several years). Section 3 provides more detail 

on the water budget components with respect to rangeland ecosystems.
USDA Forest Service RMRS-GTR-351. 2016. 15

Section 2: Sediment Detachment, Transport, and Mass 

Wasting

Soil erosion refers to the detachment and transport of soil by raindrop impact, 

running water, wind, ice flows, and other mass-movement processes (Selby 1993). Soil 

detachment is a function of the erosive energy acting on the soil surface and the resistance of the surface to erosion (Thornes 1980; Selby 1993; Toy et al. 2002). In hydrologic 

terms, erosive energy acting on the soil surface (shear stress) results from raindrop impact 

or the flow of water, or a combination of both. The resistance of the surface (critical 

shear stress) is a function of the soil properties, soil cohesiveness, and other surface 

characteristics that define the soil erodibility. Erodibility is defined as the vulnerability of 

a soil in its current condition to erosion by rainfall, runoff, and wind. Detachment occurs 

when the shear stress acting on a soil exceeds the critical shear stress or resistance of the 

soil (Foster and Meyer 1972; Nearing et al. 1999; Kinnell 2005).

As defined, the removal of detached sediment requires entrainment by a transport 

mechanism. Transport may occur by displacement from raindrop impact or entrainment 

into flowing water, or both (Kinnell 1988, 1990, 2005). Transport capacity of flowing water is dependent on the volume of water, mass of solids versus mass of water, energy loss 

as the flow moves downslope, and efficiency of transport (Thornes 1980; Toy et al. 2002; 

Kinnell 2005). In this section we summarize these fundamental sediment detachment and 

transport mechanisms. Our emphasis is on hillslope processes given the context of this review. Julien (1998), Knighton (1998), and McCuen (2004) provide detailed explanations 

of channel or fluvial sediment entrainment, transport, and routing processes beyond the 

scope of this review. Soil erosion through wind, creep, weathering, and other mechanisms 

not directly involving rainfall and flowing water are discussed in Selby (1993), Toy et al. 

(2002), Ravi et al. (2007), Sankey et al. (2009), and Field et al. (2012).

Rainsplash and Sheetflow Processes

The combined effects of rainsplash and sheetflow/sheetwash processes are termed 

“rainwash” or “interrill” processes (Selby 1993; Toy et al. 2002). Rainwash processes 

often represent the dominant erosion processes where microchannel formation is 

substantially limited by soil aggregation, soil cohesion, and surface protection. Here, we 

describe the two components of rainwash—rainsplash and sheetflow—separately because 

their co-occurrence is dependent on overland flow generation. Rainsplash erosion is 

the transfer of sediment resulting from raindrop impact. The effects of raindrop impact 

include detachment and displacement of soil (see Kinnell 2005), disaggregation of soil 

aggregates, and reduced infiltration due to surface sealing (Moss 1991; Assouline 2004; 

Kinnell 2005). Sediment detachment and transport by rainsplash occurs in a “splashcrown” (fig. 9A) with sediment mass declining exponentially outward from the point of 

impact on flat surfaces (Thornes 1980; Toy et al. 2002; Kinnell 2005). On sloping terrain, 

downslope transport may exceed three times the mass of upslope transport where slopes 

are greater than 10 percent (Thornes 1980).

Raindrop detachment rates are commonly highest within several minutes after the 

onset of rainfall, followed by an exponential decrease to a steady rate; however, rates 
16 USDA Forest Service RMRS-GTR-351. 2016.

may be highest at rainfall onset if the supply of detachable sediment is low (see Parsons 

et al. 1994). The main source of energy in this process is the kinetic energy of rainfall as 

dictated by the raindrop mass and terminal velocity (Gilley and Finkner 1985; Sharma 

et al. 1991; Bryan 2000; Salles and Poesen 2000; Salles et al. 2002). Terminal velocity 

increases with increasing drop size, and drop size generally increases with increasing 

rainfall intensity (Gunn and Kinzer 1949; Salles and Poesen 2000; Salles et al. 2002; Van 

Dijk et al. 2002). Thus, the impact energy of rainfall and sediment detachment generally 

increases with increasing rainfall intensity. However, cumulative sediment detachment 

may be significant from low-intensity storms over long durations.

The decrease in detachment by raindrops during rain events is often associated with 

an increase in the depth of sheetflow (Thornes 1980; Moss and Green 1983; Ferrera and 

Singer 1985; Gilley et al. 1985; Toy et al. 2002). Flow depths equal to the diameter of 

approximately three drops greatly reduce the impact of rainfall (Moss and Green 1983; 

Kinnell 1990, 1991, 1993). The shear stress and additional transport capacity of sheetflow 

may, however, offset the decrease in raindrop impact, resulting in a net increase in total 

sediment production, or yield (Kinnell 2005). In addition to increasing sediment yield, 

drop impact from high-intensity rainfall may break apart soil aggregates and facilitate 

particle sorting by size and infilling of surface pores with fine material. This process, 

referred to as surface sealing (Bradford et al. 1987; Assouline 2004), may create a surface 

crust or compact the surface soil, resulting in reduced infiltration (by a factor of 1 to 

10) and increased runoff and sediment transport by sheetflow. Soils with high clay and 

organic matter content are generally less influenced by raindrop effects than are sandy or 

sandy loam soils, and the net effect may be related to soil bulk density.

Figure 9—Soil erosion by (A) rainsplash, (B) sheetflow, and (C) concentrated flow processes (photo A: USDA 

Natural Resources Conservation Service; photos B and C: USDA Agricultural Research Service, Northwest 

Watershed Research Center).
USDA Forest Service RMRS-GTR-351. 2016. 17

Sheetflow generates shear stress that is minor (about 100-fold less) compared to 

raindrop impact, but it serves as an additive detachment and transport mechanism for 

interrill sediment yield (Thornes 1980; Selby 1993; Toy et al. 2002; Kinnell 2005). 

Sheetflow does not usually occur as a broad flow across a hillslope; rather, it occurs in 

isolated irregular- flow patches of several millimeters depth separated by flow obstacles 

(fig. 9B) (Emmett 1970, 1978). Raindrops falling into shallow flow depths create turbulence and detachment, facilitating sediment entrainment. Soil detachment from sheetflow 

results from drag created by differential shear stress on the upslope and downslope faces 

of the particle, Bernoulli lift in the horizontal direction, and vertical turbulence (see 

Thornes 1980; Kinnell 2005). The amount of sediment and the size of particles entrained 

depend on the flow velocity and turbulence, both of which generally increase with 

increasing slope and flow depth. The rate of transport generally increases with flow depth 

to a maximum of about one to three raindrop diameters (Selby 1993). Entrained particles 

remain in suspension until a deposition velocity occurs (less than 0.015 m s-1). The presence of ice in surface soils may amplify interrill erosion by slightly raising portions of the 

surface soils, making them more susceptible to detachment and entrainment by rainsplash 

and sheetflow processes (Blackburn and Wood 1990; Blackburn et al. 1990).

Concentrated Flow Processes

Sediment yield from concentrated flow (rill) processes is several orders of magnitude greater than that of sheetflow and rainsplash (Thornes 1980; Wainwright et al. 2000; 

Pierson et al. 2008a). Concentrated flow processes may account for 50 to 90 percent 

of total sediment yield on slopes with very little vegetation. Concentrated flowpaths or 

rills are microchannels of several to tens of centimeters in width and several to 300 millimeters in depth that are easily obliterated between storm events. These microchannels 

form when surface roughness elements (microtopography) concentrate sheetflow into 

narrow, deeper flowpaths, increasing the velocity and erosive energy of runoff (fig. 9C) 

(Emmett 1970, 1978). Concentrated flow detachment and incision occur when the 

incoming interrill sediment load is less than the concentrated flow’s transport capacity, 

and the shear stress applied to the soil is greater than soil surface critical shear stress or 

erodibility (Nearing et al. 1989, 1999; Al-Hamdan et al. 2012b). The shear stress applied 

is a function of the density, depth, and velocity of the flowing water, the friction imposed 

by the soil and cover, land surface slope, and acceleration due to gravity (see Toy et al. 

2002; Al-Hamdan et al. 2012a,b, 2013).

Deposition occurs when the flow transport capacity is exceeded. Sediment detachment and transport are commonly highest at the initiation of concentrated flow and 

decrease gradually as more resistive materials are exposed with flowpath incision or 

where sediment supply is limited (Nearing et al. 1997; Wainwright et al. 2000; Pierson et 

al. 2008a; Al-Hamdan et al. 2012b). On freshly exposed surfaces, parallel concentrated 

flowpaths may cross grade or merge by breaking down the divides between microchannels (micropiracy). This process diverts the flow into the deeper, more dominant 

flowpaths and generally increases the spacing of concentrated flowpaths in the downslope 

direction.
18 USDA Forest Service RMRS-GTR-351. 2016.

Gully Erosion Processes

Gullies are recently channelized drainage features that transmit ephemeral flow, 

usually have steep sides and a head scarp (leading upslope area of exposed soil and rock), 

and are more than 30 cm wide and 60 cm deep (see Selby 1993; Toy et al. 2002). These 

erosional features commonly form when a master rill deepens and widens its channel, 

especially where changes in slope or vegetation patterns occur on unconsolidated materials (fig. 10) (Neary et al. 2012). Gullies may also form where debris and mud flows exit 

unstable drainage basins or where large subsurface drainage features collapse. The most 

common cause of gully formation is a loss in surface protection associated with a change 

in the overlying vegetation or soil disturbance.

Gullies forming from rills often have no head scarp, increase in width and depth 

downslope toward a master gully, and end in a deposition zone of coalescing fans at 

the base of toe slopes. Gullies with head scarps maintain the scarp where soils are 

cohesive, but upslope or upstream headcutting occurs if soils are weak (unconsolidated). 

Peak discharges from gullies typically far exceed the peak discharge of the previously 

unchanneled valleys in which they occur. Erosion from gully processes may be severe 

where high-intensity rainfall events occur over poorly vegetated surfaces with weakly 

consolidated or unconsolidated sediments. Gully erosion most commonly occurs in 

pulses, and sediment supply comes mostly from head scarp erosion and bank failures or 

sidewall sloughing (Selby 1993).

Figure 10—Gully erosion on an unprotected soil (photo: Lynn Betts, 

USDA Natural Resources Conservation Service).
USDA Forest Service RMRS-GTR-351. 2016. 19

Mass Movement Processes

Mass movement erosion occurs when the shear stress applied to a body of soil 

material on a slope exceeds the resistance or critical shear stress (shear strength) of the 

material to downslope movement and may result directly or indirectly from a particular 

water input event (see Sidle et al. 1985; Selby 1993). Shear stress is increased by removal 

of lateral soil support, soil profile shifting, overburdening of soils with rain or snow, 

ground vibrations, undercutting of banks or ridges, and increased slope steepness. Shear 

strength is reduced by loosening of soils with soil shifting, increased buoyancy and capillary tension associated with pore water changes, alteration of soil structure, decreased 

root anchoring and elevated water tables due to vegetation alteration, and the presence of 

relict weakness planes (such as faults and joints). Mass soil movement processes include 

creep, falls/topples, slides, and flows. Here, we briefly summarize the common types and 

causes of soil mass movement. Sidle et al. (1985) and Selby (1993) provide extensive 

description and explanation of the types, causes, and occurrences of soil mass movements 

and present approaches to slope stability assessment and analysis.

Soil creep and fall processes generally constitute minor soil loss relative to other 

erosion processes. Creep of soil downslope may occur as individual soil particles (particle 

creep) or en masse (slope creep). Particle creep occurs due to gravity, particle expansion 

and contraction with heating and cooling, and wetting-drying and freeze-thaw processes. 

Slope creep refers to the slow downslope creep of large soil masses and is a function of 

the creep rate and the depth of material in movement. Creep rates usually range between 

0.1 and 15 mm y-1 on well-vegetated slopes, but may be as high as 500 mm y-1 on 

exposed slopes and areas with frequent freeze-thaw cycles (Selby 1993). Falls result from 

the undercutting of slope faces or toe slopes by flowing water or from cliff-top sloughing 

after freeze-thaw or wetting-drying periods. Falls may contribute significantly to the 

downslope transport of rocks, but sediment contributions from this process are generally 

minimal on annual time cycles.

Slides occur on failure planes that are either straight (translational) or curved 

(slumps), and are the most common form of landslide (Sidle et al. 1985; Selby 1993). 

Translational slides are more common than slumps. Translational slides usually occur due 

to reduced soil strength with saturation and they form in long, shallow (1 to 4 m) linear 

features. High-intensity rainfall saturates the soil profile, reducing the soil strength along 

soil material boundaries of different permeability or density. The soil-bedrock interface 

is a common translational failure plane where saturated soils are underlain by shallow 

bedrock. Overburdening, slope steepening, and ground vibrations are also causes of 

translational slides. The rate of movement for translational slides is commonly several 

meters per day. Similar to translational slides, slumps form when overburdening under 

wet conditions weakens the shear strength of the soil. Slumps, however, are rotational or 

curved failure planes, and may initiate long after water input has ceased. They usually occur in cohesive soils derived from soft rocks like shales, mudstones, and overconsolidated 

clays. Downslope progression usually occurs at a rate of a few millimeters per year to 

several meters per day. However, slumps that occur in soils with high water content may 

generate more substantial downslope transfer of sediment and often result in an earthflow 

event at the toe of the failure.
20 USDA Forest Service RMRS-GTR-351. 2016.

Flows are gravity-induced mass movements that are intermediate between sliding 

and water flows. They occur as debris, earth, or mud flow resulting from wet or dry liquefaction of coarse debris, fine-grained soil, or clay soil, respectively (Selby 1993). These 

fast-moving events (a few meters per day to tens of meters per second) are promoted by 

steep slopes, high soil water content, remolding of soil material following other mass 

movement events, presence of soil with low liquid limits (easily liquefied soil), ground 

vibrations, and the occurrence of soils with open fabrics that facilitate soil movement. 

Flows typically occur with abundant wetness, but may also occur as dry rock avalanches 

or rock fragment flows. They often occur subsequent to an upslope slide that contributes 

substantial debris and sediment downslope at a high velocity.

Debris flows (fig. 11) are flow events consisting of large quantities of debris and 

runoff. Debris flows that contain organic matter in large forms, such as trees and logs, 

are referred to as “debris torrents.” Here, we consider the discussion that follows to be 

similar for debris torrents and flows, and thus refer to both simply as “debris flows.” The 

high bulk density and viscosity of debris flows facilitate flow shear strength substantial 

enough to transport large boulders and debris. Debris flows progress downslope with a 

boulder- and debris-laden front followed by slurry and hyperconcentrated flow of coarseand fine-soil materials. Flowpaths can extend for many kilometers and commonly cease 

in low-gradient alluvial fans with boulder levees (see Selby 1993).

Debris flows may occur in 20 to 100 waves during a single event, with thinner fluid 

pulses occurring between waves. These events can occur suddenly and pose significant 

risk to life, property, and resources due to the high-impact force (5 to 100 times that of 

floods) and velocity and the sediment/debris loading possible. For example, an extreme 

rainstorm event in central California in 1982 generated more than 200 mm of rainfall 

over 32 hours, resulting in more than 18,000 slides (see Ellen and Wiezorek 1988). 

Debris flows from the slides damaged at least 100 homes and killed 14 people, of whom 

10 were buried in their homes. The total cost of the damage was estimated at more than 

$280 million. Selby (1993) provides a brief review of this and other catastrophic debris 

Figure 11—Debris flow following a thunderstorm event occurring on 

burned forest land (photo: USDA Forest Service).
USDA Forest Service RMRS-GTR-351. 2016. 21

flow events of similar magnitude. Cannon et al. (1998, 2001a,b, 2008) explain runoffand infiltration-driven triggers for debris flow initiation on burned landscapes and provide 

additional examples of the potential impact of debris flows on values-at-risk.

Earthflows and mudflows are slow- to rapid-moving viscous flows of fine sand, 

clay, and silt particles mixed with water. As with debris flows, they often result from 

upslope slides, particularly slumps. Slumps of wet soil bulging forward often take the 

form of bulbous toes or tongue-like rolls of earth and mud. The downslope movement is 

dependent on the weight of the material, slope steepness, shear strength of the material, 

and pore water pressures. The rate of movement for earthflows usually ranges from less 

than several meters a day to hundreds of meters per hour. Earthflows may affect areas 

from several square meters to hectares, but these impacts may require several years and 

are commonly of minor degree. Mudflows are highly mobile (with velocities of several 

meters per second) and pose greater threat than earthflows to life, property, and resources. 

For example, the volcanic eruption of Mt. Saint Helens in Washington State in 1980 

generated lahar flows (volcanic mudflows) 120 km down the Toutle River and contributed 

more than 50 million m3 of sediment into the Lower Columbia River (Pierson 1986). The 

Mt. Saint Helens event illustrates changes in flow behavior and deposition from mass 

movement initiation to streamflow delivery (see Scott 1988).

Spatial and Temporal Variations of Processes

Sediment detachment and transport may vary dramatically in space and time 

(Thornes 1980; Toy et al. 2002). The spatial scaling of sediment yield is a function of the 

arrangement and connectivity of surface susceptibility, driving forces (such as rainfall 

distribution), and erosion processes occurring within the area of interest (Pierson et al. 

2011; Williams et al. 2016a). Rainsplash and sheetflow processes (fig. 9A and 9B) dominate at the small-plot scale (1 to 2 m2) and erosion highly depends on the susceptibility 

of the soil surface to raindrop impact. Over large-plot scales (tens of square meters), 

sediment yield is more influenced by the fluid-flow entrainment of raindrop- and flowdetached sediment in sheetflow and concentrated flow (fig. 9C) and the connectivity of 

these processes (Williams et al. 2016a).

At the hillslope scale, the landscape often has a heterogeneous arrangement of 

susceptible conditions and driving forces, resulting in a poorly connected spatial organization of processes and erosion (Pierson et al. 1994a,b; Abrahams et al. 1995; Bergkamp 

1998; Puigdefábregas et al. 1998; Reid et al. 1999; Wilcox et al. 2003a; Puigdefábregas 

2005; Williams et al. 2014b). For example, small perturbations on a hillslope may create 

small patches of exposed bare soil highly susceptible to rainsplash erosion. High-intensity 

rainfall on these patches may generate substantial erosion from raindrop impact, but the 

protected surfaces between the perturbations create a disconnect at the larger hillslope 

scale, resulting in minor sediment yield.

The same landscape with uniform disturbance may undergo substantially more 

soil erosion from a similar storm due to an increase in the spatial connectivity of surface 

susceptibility, rainsplash detachment, and formation of well-organized sheetflow or 

concentrated flow (Williams et al. 2016a). At watershed scales, the distribution of rainfall 

or other driving forces is often highly variable, as is erodibility, facilitating even greater 
22 USDA Forest Service RMRS-GTR-351. 2016.

disconnect than observed at hillslope scales. In-channel processes also play a role in sediment delivery over landscape scales. In general, sediment yield per unit area decreases 

with increased spatial area due to the inherent loss in connectivity of processes, susceptibility, and driving forces (Pierson et al. 1994a,b; Wilcox et al. 2003a). The collective 

arrangement creates a spatially dynamic environment of sediment detachment, transport, 

and deposition that is dependent on the respective magnitude and extent of each of these 

components’ influence.

Temporal variability comes from event oscillations, climate variations, and changes 

in land use or disturbance regimes (see Thornes 1980). Short-term variations in erosion 

usually refer to changes occurring during a single storm event or over seasonal to annual 

time scales. During a storm, the most readily available sediment is eroded first, usually 

resulting in an initial pulse of sediment much greater than sediment delivery near the conclusion of the storm (Pierson et al. 2008a; Al-Hamdan et al. 2012b). The availability of 

sediment is a complex dynamic of sediment detachment and transport that, as previously 

mentioned, is highly variable in space. Oscillations in the magnitude and spatial arrangement of driving forces during individual events may create spatially and temporally 

variable sediment sources that further influence the temporal response.

Over seasonal and annual timescales, erosion may be influenced by changes in 

vegetation, soil conditions, animal activity, or climatic factors. Semiarid areas, for example, commonly have low-intensity, long-duration rainfall in winter and high-intensity, 

short-duration rainfall in summer (see Branson et al. 1981). These different climate 

regimes elicit different erosional responses. The seasonal responses are further influenced 

by co-occurring changes in the vegetation cover and soil wetness that may increase or 

decrease site erodibility. For example, denser canopy cover on semiarid rangelands during summer months, as compared to winter months, offers greater surface protection from 

high-intensity rainfall through increased interception. During winter months, low ground 

cover and freeze-thaw soil processes may facilitate reduced infiltration and high erosion 

rates during low-intensity rainfall (Blackburn and Wood 1990; Blackburn et al. 1990; 

Seyfried and Flerchinger 1994; Wilcox 1994).

Over timescales that cover multiple years or longer, erosion is more influenced by 

climatic changes and land-use disturbances. Prolonged drought conditions may limit plant 

growth and recruitment of surface-protecting litter. A series of wet years may stimulate 

canopy and ground cover recruitment. Likewise, effects of land use, disturbance, or 

postdisturbance rehabilitation may take many years or even decades to influence sediment 

yield and may be linked with climatic influences (Allen and Breshears 1998). Finally, all 

temporal responses are strongly linked to the time dependence of spatial links in erosion 

processes or cumulative effects.
USDA Forest Service RMRS-GTR-351. 2016. 23

Section 3: Climate-Vegetation-Soil-Hydrology Interactions

Precipitation processing and the resultant runoff and erosion processes at point to 

landscape scales are a function of climate, vegetation, and soil interactions (Seyfried and 

Wilcox 1995; Puigedfàbregas et al. 1999; Pierson et al. 2002a; Robichaud et al. 2010; 

Pierson et al. 2011; Williams et al. 2014b). Climate acts as a driving force for runoff generation and erosion, whereas vegetation and soil properties act as resistive forces. Climate 

influences the timing, quantity, type, and intensity (erosive energy) of precipitation falling 

at the land-atmosphere interface. Air temperatures and evaporation rates affect available 

water and plant establishment and productivity. Canopy interception controls the amount 

and erosive energy of precipitation passing through to the ground surface, and influences 

the immediate canopy area, climate, and water use. Ground cover, organic matter, 

and soil fauna recruitment are a function of plant productivity and climate, and their 

interactions regulate soil stability and retention. Ground cover reduces the erosive energy 

of raindrops and surface flow, increases aggregate stability, traps and stores sediment, 

mediates infiltration rates, and modifies the soil climate and soil fauna activity. Plant root 

tissues and soil fauna activity influence the soil bulk density and infiltration capacity. 

Organic matter and byproducts of fauna activity may inhibit or facilitate soil wettability. 

Soil development is strongly related to parent materials, erosion processes, climate, and 

the vegetative community. Soil porosity and structure affect infiltration, percolation, and 

throughflow, all of which influence soil water storage and antecedent moisture conditions. 

Soil water storage and climate regulate plant productivity and vegetation recruitment. 

Collectively, these relationships control the spatial and temporal arrangement of runoff 

and erosion processes. In this section, we discuss these relationships in detail with respect 

to runoff and erosion in preparation for assessing hydrologic impacts of fire.

Climate as a Driver of Hydrologic Response

The type, intensity, duration, and timing of a precipitation event greatly influence 

rangeland hydrologic response. Rainfall events in excess of soil infiltration capacity may 

produce substantial runoff, whereas the same quantity of precipitation falling as snow 

may generate little or no event runoff. Snow accumulation on the land surface stores 

precipitation and delays runoff, allowing more time for evaporative losses and infiltration 

(Dingman 2002; McNamara et al. 2005). For rainfall events, the intensity is an important 

measure for predicting rangeland response (Branson et al. 1981). High-intensity storms 

often greatly exceed the infiltration and storage capacity of the land surface and facilitate 

rapid runoff generation and large quantities of streamflow. Runoff from low-intensity 

storms is often minimal as long as the rainfall rate does not significantly exceed the 

infiltration capacity of the soil (Wilcox et al. 2003a). The duration of a storm event 

also influences runoff generation. High-intensity storms over long durations present the 

greatest risk for elevated runoff and erosion, whereas low-intensity events over short 

durations pose lower risks for runoff and soil loss. However, long-duration low-intensity 

events may also generate substantial runoff, especially under saturated soil conditions 

(Castillo et al. 2003; Wilcox et al. 2003a). In general, the risk for high runoff and erosion 
24 USDA Forest Service RMRS-GTR-351. 2016.

is greater the longer the infiltration and storage capacity of the land surface is exceeded. 

The response is amplified with increasing rainfall intensity.

Seasonal variation in runoff behavior from rangelands is related to the prevailing 

precipitation regime. In the mountainous north and central United States, high-elevation 

range sites are mostly snow dominated while low- to mid-elevation sites are rainfall 

dominated with transient winter snowpacks (Branson et al. 1981; Seyfried and Wilcox 

1995). The greatest runoff rates from snow-dominated uplands occur during the spring 

snowmelt/runoff period or during winter rain-on-snow events (fig. 12A, table 1) (Branson 

et al. 1981; Wilcox et al. 1991; Seyfried and Flerchinger 1994; Marks et al. 2001; Pierson 

et al. 2001b). The spring runoff season at these sites begins when air temperatures warm 

above freezing and the precipitation trend shifts from snowfall to rainfall. Large quantities of available water and saturated soil conditions amplify runoff (McNamara et al. 

Figure 12—Mean monthly streamflow, precipitation, and air temperatures for (A) a semiarid, snow-dominated 

drainage in the Reynolds Creek Experimental Watershed, Idaho (USDA Agricultural Research Service 

2011a) and (B) an arid, rainfall-dominated drainage in the Walnut Gulch Experimental Watershed, Arizona 

(USDA Agricultural Research Service 2011b) (photos: Agricultural Research Service).
USDA Forest Service RMRS-GTR-351. 2016. 25

2005; Seyfried et al. 2009). Snowmelt runoff is generated mainly from subsurface return 

flow in or near stream channels rather than sheetflow or concentrated flow (Flerchinger et 

al. 1992; McNamara et al. 2005; Seyfried et al. 2009; Williams et al. 2009).

Runoff at low-to-mid elevations occurs primarily as overland flow due to rainfall 

on shallow snowpacks (less than 30 cm snow) and frozen soils (Johnson and Smith 1978; 

Wilcox et al. 1989; Blackburn and Wood 1990; Blackburn et al. 1990; Wilcox et al. 1991; 

Seyfried and Flerchinger 1994; Seyfried and Wilcox 1995; Marks et al. 2001; Pierson 

et al. 2001b). Runoff during summer months usually results from short-duration, highintensity rainfall in excess of infiltration (Branson et al. 1981; Wilcox et al. 1991; Pierson 

et al. 2001b). For snow-dominated sites and valley locations, infiltration-excess runoff 

from high-intensity storms is often limited to small areas resulting from isolated rainfall 

patterns and heterogeneous soils and canopy/ground cover (Blackburn 1975; Blackburn 

et al. 1992; Pierson et al. 1994a,b).

In the desert southwestern United States, some mountainous locations present 

intermediate precipitation-runoff patterns, in contrast with the purely snow-dominated or 

rainfall-dominated northwest and central U.S. uplands (Wilcox et al. 2003a). Such sites 

exhibit both winter snow-dominated and summer rainfall-dominated precipitation-runoff 

regimes, but the largest runoff events are usually related to intense monsoon summer 

thunderstorms (Wilcox 1994; Breshears et al. 1998; Wilcox et al. 2003a). Valley rangelands in the desert Southwest also experience the greatest catchment runoff (90 percent 

of annual) during the summer monsoon season (fig. 12B, table 1; Osborn and Lane 1969; 

Branson et al. 1981; Osborn and Renard 1988; Wilcox et al. 2003a; Stone et al. 2008). 

Monsoonal storms occur as variable high-intensity (up to 250 mm h-1), short-duration 

(5 to 30 min), and spatially limited (10 to 100 km2) events (Osborn 1964; Branson 

et al. 1981; Osborn 1983a,b; Osborn and Renard 1988; Renard 1988; Renard et al. 

1993; Goodrich et al. 2008). The more intense (more than 100 mm h-1) storms produce 

Table 1—Ten largest peak flows of record measured on the snowfall-dominated Reynolds Creek 

(Outlet Weir, 1963 to 1996), Reynolds Creek Experimental Watershed , Idaho, and rainfalldominated Walnut Gulch (Flume 1, 1953 to 2010), Walnut Gulch Experimental Watershed, Arizona.

Reynolds Creek, Idaho Walnut Gulch, Arizona

(Snowfall dominated, 23,372 ha) (Rainfall dominated, 14,932 ha)

Peak flowa Peak flowb

Date (m3 s-1) Date (m3 s-1)

23 Dec 1964 109.03 17 Aug 1957 318.61

31 Jan 1963 66.02 02 Aug 1957 183.54

15 Feb 1982 58.97 12 Aug 1972 171.52

11 Jan 1979 47.09 11 Aug 2000 147.50

11 Jun 1977 31.70 10 Sep 1967 132.54

28 Jan 1965 31.53 22 Jul 1964 121.48

21 Jan 1969 25.48 22 Aug 1961 111.26

11 Apr 1982 24.40 10 Aug 1971 102.38

27 Jan 1970 20.64 16 Aug 1958 95.93

02 Mar 1972 19.19 09 Sep 1964 89.58 

a Streamflow summaries provided by the USDA Agricultural Research Service, Northwest Watershed Research 

Center (USDA Agricultural Research Service 2011a).

b Streamflow summaries provided by the USDA Agricultural Research Service, Southwest Watershed Research 

Center (USDA Agricultural Research Service 2011b).
26 USDA Forest Service RMRS-GTR-351. 2016.

significant point and hillslope-scale runoff, yielding watershed-scale runoff equivalent to 

several years of normal runoff (Branson et al. 1981; Renard et al. 1993).

Sediment generation from rangelands is often related to the amount of runoff. For 

snow-dominated uplands, peak erosion occurs during snowmelt runoff (Branson et al. 

1981; Pierson et al. 2001b). Streamflow sediment concentrations during snowmelt runoff 

are most influenced by streambank sloughing and streambed-sediment entrainment 

processes, rather than rainsplash and sheetflow. Low- to mid-elevation mountainous sites 

may experience the greatest erosion rates from low-intensity, long-duration rain events 

during freeze-thaw periods (Seyfried and Flerchinger 1994). Freeze-thaw processes 

increase surface erodibility, and, combined with lower vegetation and ground cover 

in winter months, facilitate increased surface erosion from rainsplash and sheetflow 

(Blackburn and Wood 1990; Blackburn et al. 1990; Seyfried and Flerchinger 1994; 

Wilcox 1994).

Summer convective, high-intensity events at snow-dominated sites may generate 

substantial point and hillslope erosion from rainsplash, sheetflow, and concentrated flow. 

Sediment eroded at the point and hillslope scales during these events usually remains 

onsite, stored locally or in ephemeral stream channels, as runoff is commonly too low for 

offsite transport (Slaughter and Pierson 2000). Where summer runoff occurs, sediment 

concentration per unit of runoff is usually several magnitudes greater than during the 

spring runoff period (Johnson and Smith 1978). As with runoff, sediment yield in the 

desert Southwest peaks during the summer monsoon season (Branson et al. 1981; Wilcox 

et al. 1996; Reid et al. 1999; Wilcox et al. 2003a; Nearing et al. 2007). High-intensity 

rainfall during this period magnifies rainsplash, sheetflow, concentrated flow, and flash 

flood erosion, generating most of the annual surface erosion from southwestern U.S. 

rangelands (Branson et al. 1981; Renard et al. 1993).

Vegetation Influences on Water Availability at the Surface 

and Near-Surface

Interception Effects on Water Availability

Canopy and ground cover interception at the land-atmosphere interface primarily influence rangeland hydrology by limiting the amount of water available for infiltration and 

runoff (fig. 13). For low-intensity, short-duration rainfall events, most of the precipitation 

is captured by plant canopies, litter, and other ground cover, and results in evaporative 

losses (Branson et al. 1981; Owens et al. 2006; Dunkerley 2008). High-intensity rainfall 

events usually exceed cover storage capacities, resulting in some precipitation routing by 

throughflow and stemflow processes in addition to the evaporative losses (Thurow et al. 

1987; Návar and Bryan 1990; Martinez-Meza and Whitford 1996; Whitford et al. 1997; 

Wainwright et al. 1999; Dunkerley 2000; Abrahams et al. 2003; Bhark and Small 2003; 

Carlyle-Moses 2004; Owens et al. 2006; Dunkerley 2008). The percentage of event gross 

rainfall captured by cover elements generally decreases as rainfall intensity increases 

(Branson et al. 1981; Carlyle-Moses 2004; Owens et al. 2006). Cumulative interception 

losses over multistorm and annual time periods vary with the frequency and magnitude of 

precipitation events and meteorological conditions (Dunkerley 2008).
USDA Forest Service RMRS-GTR-351. 2016. 27

Interpreting estimates of rainfall interception loss, throughfall, and stemflow from 

literature is confounded by the variability in measurement approaches, reported units, 

and spatial and temporal experimental scales (Dunkerley and Booth 1999; Dunkerley 

2000; Abrahams et al. 2003; Llorens and Domingo 2007; Dunkerley 2008). Estimates 

have been reported from event, seasonal, and annual timescales over varying rainfall 

intensities, storm patterns, and cumulative precipitation (Branson et al. 1981; Dunkerley 

and Booth 1999; Dunkerley 2000; Carlyle-Moses 2004; Llorens and Domingo 2007; 

Dunkerley 2008). Results are commonly expressed as a depth of water or percentage 

of gross precipitation falling on individual plants or over an entire plant community. 

Extrapolation of these results to other like plants and communities is tenuous given 

variability in vegetation and climate characteristics from one rangeland site to another 

(Dunkerley and Booth 1999; Dunkerley 2000, 2008). General estimates suggest tree, 

shrub, and grass foliage can store about 1.3 mm of water (Bonan 2002).

Branson et al. (1981) and others (Rowe 1948; Hamilton and Rowe 1949; Hull and 

Klomp 1974; West and Gifford 1976; Tromble 1983; Thurow et al. 1987; Tromble 1988; 

Návar and Bryan 1990; Martinez-Meza and Whitford 1996; Wood et al. 1998; Dunkerley 

and Booth 1999; Dunkerley 2000; Abrahams et al. 2003; Wilcox et al. 2003b; CarlyleMoses 2004; Owens et al. 2006; Llorens and Domingo 2007; Dunkerley 2008; Taucer et 

al. 2008) provide estimates of event and annual rainfall interception and stemflow for a 

variety of rangeland plants and communities. Here, we summarize these data to provide 

the reader an idea of the general magnitude of precipitation that returns to the atmosphere 

via interception loss. We summarize ranges in the percentage of gross rainfall intercepted 

at the event and longer term (seasonal and annual) timescales by individual cover type 

and by plant community (see table 2). Gross rainfall interception by rangeland individual 

shrubs (Rowe 1948; Hamilton and Rowe 1949; West and Gifford 1976; Branson et al. 

1981; Tromble 1983) and conifer trees (Skau 1964; Slaughter 1997; Owens et al. 2006; 

Taucer et al. 2008) averages from 50 to 60 percent for low-intensity storms to 5 to 35 

percent for high-intensity or large events. Gross rainfall interception by individual shrubs 

over multistorm to annual timescales ranges from 5 to 46 percent (Hull 1972; Hull and 

Klomp 1974; Thurow et al. 1987; Tromble 1988; Návar and Bryan 1990; Martinez-Meza 

Figure 13—Ponding and interception of artificial rainfall applied on (A) a sagebrush site invaded by western 

juniper and (B) the same site 10 years following juniper removal (photos: USDA Agricultural Research 

Service, Northwest Watershed Research Center, adapted from Pierson et al. 2007a).
28 USDA Forest Service RMRS-GTR-351. 2016.

and Whitford 1996; Domingo et al. 1998; Serrato and Diaz 1998), with most reported 

values around 5 to 15 percent.

Shrub- and woodland-community rainfall interception on the annual scale ranges 

between 5 and 25 percent (Rowe 1948; Hamilton and Rowe 1949; Pressland 1973; West 

and Gifford 1976; Tromble 1983; Thurow et al. 1987; Tromble 1988; Dunkerley and 

Booth 1999; Carlyle-Moses 2004). Fewer data are available for herbaceous vegetation 

and litter interception. Clark (1940) measured rainfall interception by native prairie 

grasses in Nebraska, USA, at levels of 29 to more than 80 percent under low-intensity 

artificial rainfall. Thurow et al. (1987) summarized several studies that found grassland 

interception of gross annual rainfall ranges from 13 to 56 percent. Thurow et al. (1987) 

estimated that interception of gross annual rainfall at two Texas grassland sites with 56 

percent (shortgrass) and 62 percent (midgrass) cover was 11 percent and 18 percent, 

respectively. Dunkerley and Booth (1999) reported a 32 percent interception of gross 

annual rainfall by grass in Australia. 

Branson et al. (1981) provides a summary of literature on litter interception with 

estimates of 2 to 17 percent of gross annual rainfall. These estimates are quite variable 

in part because of the methods used to identify when the litter layer stops and the soil 

layer begins. For example, Owens et al. (2006) estimated that 5 percent of gross annual 

rainfall on Ashe juniper (Juniperus ashei Buchholz) trees at a Texas woodland site was 

intercepted by the coarse litter beneath trees, whereas Thurow et al. (1987) determined 

that litter (all dead plant material above the mineral soil) intercepted 20 percent of annual 

rainfall in a live oak (Quercus virginiana Mill.) motte of the Edwards Plateau, Texas. 

Routing of intercepted water as stemflow has been estimated at 5 to 17 percent of gross 

rainfall for individual rangeland conifers (Thurow and Hester 1997; Owens et al. 2006; 

Taucer et al. 2008) and at 3 to 10 percent of gross rainfall for individual shrubs and shrub 

communities (Thurow et al. 1987; Návar and Bryan 1990; Martínez-Meza and Whitford 

1996; Wainwright et al. 1999; Abrahams et al. 2003; Bhark and Small 2003; CarlyleMoses 2004).

Canopy interception of snowfall is generally considered of minor hydrologic importance because most intercepted snow reaches the ground as meltwater or is shed as large 

snow masses (Dingman 2002; Storck et al. 2002). General interception estimates suggest 

trees can store about 3.8 mm of water as snow (Bonan 2002). Literature on snowfall 

canopy interception specific to rangeland plants is extremely limited. The most commonly cited references are Hull (1972) and Hull and Klomp (1974). They found dense 

shrub cover (2.2 plants per m2) intercepted 37 percent of snowfall at an Idaho rangeland 

site.

Table 2—Event and annual interception rates reported in literature for various individual rangeland 

plant and community types (see Branson et al. 1981).

Event interception Annual interception

Cover type as % of gross rainfall as % of gross rainfall

Individual conifer or shrub 50–60 for Low-Intensity 5–50,

5–35 for High Intensity 5–15 more common

Litter 2–20 2–20

Shrub or woodland community 5–50 5–25

Herbaceous community 15–80 10–55
USDA Forest Service RMRS-GTR-351. 2016. 29

Reports of snow interception measurements of conifer species come from 

woodland- and forest-dominated sites. Breshears et al. (1997b) reported that snow accumulation during each of three winter seasons was much greater in areas between tree 

canopies than underneath canopies at a twoneedle pinyon/oneseed juniper (Pinus edulis

Englem./J. monosperma (Engelm.) Sarg.) woodland site in New Mexico. Snow water 

equivalent in the first year of the 3-year study was about 80 percent greater in openings 

between trees than in areas underneath canopies. Schmidt and Gluns (1991) reported 

45 to 50 percent canopy interception of snowfall for three conifer species in a forested 

setting when snow water equivalent was 10 mm and snow specific gravity was 0.06. 

Interception decreased to 10 percent for an equivalent storm with snow specific gravity of 

0.13 (Schmidt and Gluns 1991). In another forested study, Storck et al. (2002) measured 

approximately 60 percent canopy interception of snowfall by four different conifer species, with minimal differences between species.

Whole plant interception of windblown snowfall by rangeland vegetation is paramount in retaining snow against wind scour (Seyfried and Flerchinger 1994; Pomeroy 

and Gray 1995; Seyfried and Wilcox 1995; Flerchinger et al. 1998; Liston and Sturm 

1998; Flerchinger and Cooley 2000; Marks and Winstral 2001; Marks et al. 2001; Sturm 

et al. 2001; Liston et al. 2002; Marks et al. 2002; Winstral and Marks 2002). Wind and 

topography interact to redistribute fallen snow on undulating terrain, while vegetation 

reduces wind velocities and facilitates deposition (Marks et al. 2001; Marks and Winstral 

2001; Marks et al. 2002; Winstral and Marks 2002). Deeper snow accumulations provide 

greater insulation for surface soils and plant productivity and prolong snow-covered 

periods (Sturm et al. 2001; Liston et al. 2002).

The vegetation snow-holding capacity is a function of the vegetation height, density 

of plants, and snowpack conditions (Pomeroy and Gray 1995; Liston and Sturm 1998; 

Sturm et al. 2001). Overall, accumulation of windblown snow is maximized at the height 

of the canopy. Any deposition in excess of canopy height is readily windblown between 

events, potentially transported offsite, or lost to wind-driven sublimation (Sturm et al. 

2001; Liston et al. 2002). Hutchinson (1965) found that a shrub stand 50 cm in height 

stored 25 mm more water than an adjacent area void of shrubs. Flerchinger et al. (1998) 

reported that snow depth at a wind-driven rangeland site in Reynolds Creek Experimental 

Watershed, Idaho, typically varied by plant community from less than 60 cm in low 

sagebrush/grass (Artemisia arbuscula/Poa secunda J. Presl) to 100 cm in mountain big 

sagebrush/snowberry (A. tridentata Nutt. ssp. vaseyana (Rydb.) Beetle/Symphoricarpos

spp.) and 100 to 800 cm in an aspen/willow (Populus tremuloides/Salix spp.) stand. 

Streamflow over a 10-year period at the site highly depended on vegetation retention of 

windblown snow (Flerchinger and Cooley 2000). Numerous other studies have reported 

similar results from water-limited, snow-dominated rangelands, indicating the retention 

of windblown snow is a dominant influence on the timing and quantity of water available 

for infiltration, soil storage, plant use, and streamflow generation (Seyfried and Wilcox 

1995; Flerchinger et al. 1998; Luce et al. 1998; Flerchinger and Cooley 2000; Marks et 

al. 2001; Winstral and Marks 2002; Seyfried et al. 2009; Williams et al. 2009).
30 USDA Forest Service RMRS-GTR-351. 2016.

Canopy Influence on Soil Microclimate, Evapotranspiration, and 

Antecedent Soil Water

In addition to intercepting water, vegetation and litter may further moderate the soil 

microclimate and water availability by shading solar radiation and insulating surface soils 

(Belsky et al. 1989; Pierson and Wight 1991; Joffre and Rambal 1993; Breshears et al. 

1997b, 1998; Domingo et al. 2000; Lebron et al. 2007). The near-surface microclimate 

influences soil evaporation and affects soil moisture regimes (Branson et al. 1981; 

Breshears et al. 1998; Hillel 1998). Pierson and Wight (1991) reported interspace locations (areas between shrub canopies, also called intercanopy) in a sagebrush community 

(A. tridentata Nutt.) had higher (by 5.2 °C) maximum and lower (by 1.5 °C) minimum 

near-surface (0 to 10 cm depth) soil temperatures than coppice locations (areas underneath and immediately adjacent to canopies, also called subcanopy) during the spring 

season. Small grass clumps and moss clumps within interspaces had little influence on 

near-surface soil temperatures. Pierson and Wight (1991) inferred that shrub cover and 

the associated litter mounds (coppices) insulated the soil surface from incoming solar 

radiation during daylight hours and from sensible heat loss at night. Breshears et al. 

(1997b) found that interspaces between tree canopies of a twoneedle pinyon/oneseed 

juniper woodland exhibited greater (40 to 50 percent more) near-surface solar radiation 

than tree coppices, and that preferential shading on the northern side of tree coppices 

significantly reduced near-surface solar radiation. Solar radiation differences between 

coppice and interspaces were much greater during the summer solstice.

Breshears et al. (1997b) also determined that snow water equivalent was greater 

in interspace locations than under tree canopies and that the differential accumulation 

resulted in temporal variability in the spatial arrangement of soil water. Soils underneath 

tree canopies were wetter than interspace soils in early winter following complete melt 

of coppice snowpacks and during the monsoon season immediately after intense runoffgenerating rainfall events. Wetter soil conditions on the edges of coppices compared to 

interspaces following intense rainfall were assumed partially related to lateral redistribution of surface runoff from interspace locations to coppices as runon. Interspace soils 

were wetter, by 3 percent volumetric moisture content, than coppice soils later in the 

winter and in early spring during the interspace snowmelt period. The differential snow 

accumulation and melt patterns, largely related to canopy snow interception, exerted a 

greater influence on the spatial distribution of soil water (canopy versus interspace locations) than did the effects of preferential shading (Breshears et al. 1997b). The primary 

effect of solar radiation on soil moisture patterns was observed within interspace patches; 

north edges with more solar radiation were wetter than south edges during winter and 

spring. Breshears et al. (1997b) attributed within-interspace differences to the canopy drip 

effects (melting snow) on the warmer south side of trees (north edge of interspaces).

Breshears et al. (1998), working at the same site as Breshears et al. (1997b), found 

that maximum air temperature was as much as 10 °C greater on interspaces than tree 

coppices during late spring through summer and that the associated differences in spatial 

temperature produced differences in soil evaporation. Breshears et al. (1998) determined 

that spatial differences in soil temperature influenced soil evaporation only when soils 

were thawed and were amplified at lower soil water contents (as expressed by soil water 

potential). Joffre and Rambal (1993) reported greater water storage under tree canopies 
USDA Forest Service RMRS-GTR-351. 2016. 31

(with grass) than in unshaded interspaces on three Mediterranean rangeland sites when 

precipitation exceeded mean annual levels. Soil water storage was low in interspace 

and coppice locations when precipitation was limited, resulting in the loss of about 60 

percent and more than 95 percent of precipitation to evapotranspiration in interspaces and 

coppices, respectively. Domingo et al. (2000) found that canopy shading in a semiarid 

Mediterranean shrubland created a milder microclimate in shrub areas and that diurnal 

temperature fluctuations were greater in interspaces. 

The above noted studies indicate that canopy effects on the near-surface microclimate may influence soil water availability, but that the overall impact is highly dependent 

on the quantity of precipitation and other spatial effects (interception, lateral redistribution). Furthermore, microclimate effects may have greater implications for biological 

processes (seed germination and emergence, nutrient and microbial processes) and spatial 

vegetation structure than for direct runoff generation (Pierson and Wight 1991; Ludwig 

and Tongway 1995; Scholes and Archer 1997; Breshears et al. 1998; Breshears and 

Barnes 1999; Reynolds et al. 1999; Belnap et al. 2005; Huxman et al. 2005; Ludwig et al. 

2005; D’Odorico et al. 2007).

The direct effects of evapotranspiration on rangeland runoff generation vary by 

precipitation regime and are usually minor relative to their influence on annual and 

seasonal water balances (Branson et al. 1981). Annual runoff from rangeland sites usually 

represents 0 to 10 percent (but can be as high as 50 percent) of annual precipitation 

depending on the type and structure of the plant community, meteorological patterns, and 

soils/geology (Carlson et al. 1990; Wilcox et al. 1991; Joffre and Rambal 1993; Wilcox 

1994; Weltz and Blackburn 1995; Carlson and Thurow 1996; Wilcox et al. 1996, 1997; 

Flerchinger et al. 1998; Flerchinger and Cooley 2000; Wilcox et al. 2003b, 2006; Nearing 

et al. 2007; Wilcox et al. 2008). Runoff generation from rainfall-dominated rangelands 

primarily occurs as infiltration-excess overland flow and is minimally influenced by 

evapotranspiration demands (Branson et al. 1981; Pierson et al. 2001b; Wilcox et al. 

2003a; Stone et al. 2008). Exceptions occur following multistorm events or prolonged 

low-intensity storms that wet up the near-surface environment, shifting the runoff process 

to saturation excess (Wilcox 1994; Castillo et al. 2003).

Saturation excess runoff is a function of available soil water storage and rainfall 

intensity. Storage capacity is related to antecedent moisture conditions and soil structure 

and depth. Under these conditions, evapotranspiration dictates the storage capacity or 

degree of saturation in the near-surface environment, strongly influencing, along with 

rainfall intensity, the timing and quantity of runoff. Saturation excess overland flow is 

more common at snow-dominated sites, during and immediately after peak snowmelt, 

and therefore, evaporation of water from the snowpack or saturated soils in these settings 

plays an important role in reducing water availability for surface and subsurface flow 

(Seyfried and Flerchinger 1994; Marks et al. 2001; Pierson et al. 2001b; Wilcox et al. 

2003a; McNamara et al. 2005; Seyfried et al. 2009; Williams et al. 2009).

Evapotranspiration demands at snow-dominated sites strongly influence, along 

with seasonal water input, the seasonal duration of ephemeral streamflow (McNamara 

et al. 2005; Williams et al. 2009). Annual actual and potential evapotranspiration, 

inclusive of interception losses, make up more than 90 percent of annual precipitation from rangeland sites, and are limited primarily by the amount of precipitation and 

available soil water (Campbell and Harris 1977; Branson et al. 1981; Carlson et al. 1990; 
32 USDA Forest Service RMRS-GTR-351. 2016.

Weltz and Blackburn 1995; Flerchinger et al. 1996, 1998; Yoder and Nowak 1999b; 

Flerchinger and Cooley 2000; Zhang et al. 2001; Huxman et al. 2005; Wilcox et al. 2006; 

Wilcox and Thurow 2006; Wilcox et al. 2008). Estimates from literature indicate actual 

evapotranspiration from rangeland herbaceous plants, shrubs, trees, and bare soil ranges 

from 60 to 100 percent, 60 to 130 percent, 35 to 120 percent, and 70 to 110 percent of 

annual precipitation, respectively (fig. 14). A review of literature on evapotranspiration 

rates by various rangeland plant communities is provided by Branson et al. (1981). The 

percentage of evapotranspiration occurring as transpiration varies considerably (7 to 80 

percent) between plant communities and depends on the amount and timing of precipitation, available energy, plant growth form, and water availability throughout the rooting 

depth of the soil profile (Reynolds et al. 2000; Wilcox et al. 2003b; Huxman et al. 2005; 

Scott et al. 2006; Stannard and Weltz 2006; Moran et al. 2009). Evaporation from the soil 

surface is dependent on surface soil moisture conditions and available energy, and generally increases with increasing exposure of bare ground (Breshears et al. 1998; Scott et al. 

2006; Moran et al. 2009).

Cover Influences on Infiltration, Runoff, and Water Transfer 

and Storage

The heterogeneous vegetative and ground cover structure and soil characteristics 

across rangeland communities exhibit a high degree of spatial organization and integration relative to water and soil resource recruitment (Tongway et al. 1989; Tongway and 

Ludwig 1990; Pierson et al. 1994b; Dunkerley and Brown 1995; Ludwig et al. 1997; 

Scholes and Archer 1997; Breshears and Barnes 1999; Puigdefábregas et al. 1999; 

Reynolds et al. 1999; Belnap et al. 2005; Ludwig et al. 2005; Puigdefábregas 2005; 

Rango et al. 2006; D’Odorico et al. 2007; Turnbull et al. 2012). The interaction of 

vegetation, ground cover, soil properties, climate, and resultant hydrologic processes 

on water-limited sites creates stable patches of water, nutrient, and soil accumulation 

and retention. Shrub/tree coppices and herbaceous or litter-covered areas create surface 

and subsurface conditions that favor infiltration and soil and nutrient retention, whereas 

bare areas exhibit higher rates of runoff and soil loss (figs. 15 and 16; Blackburn 1975; 

Abrahams et al. 1988; Schlesinger et al. 1990; Seyfried 1991; Blackburn et al. 1992; 

Figure 14—Estimated averages 

and ranges (as maximum 

and minimum) of annual 

evapotranspiration as 

percentage of annual 

precipitation for various 

rangeland plant types as 

reported in literature (Carlson 

et al. 1990; Joffre and Rambal 

1993; Weltz and Blackburn 

1995; Carlson and Thurow 

1996; Flerchinger et al. 1998; 

Yoder and Nowak 1999b; 

Brandes and Wilcox 2000; 

Flerchinger and Cooley 2000).
USDA Forest Service RMRS-GTR-351. 2016. 33

Pierson et al. 1994a,b; Wilcox 1994; Abrahams et al. 1995; Ludwig and Tongway 1995; 

Wilcox and Breshears 1995; Parsons et al. 1996; Schlesinger et al. 1996; Wilcox et al. 

1996; Whitford et al. 1997; Bergkamp 1998; Davenport et al. 1998; Reid et al. 1999; 

Schlesinger et al. 1999, 2000; Dunkerley 2002; Wainwright et al. 2002; Bhark and Small 

2003; Wilcox et al. 2003a,c; Pierson et al. 2010; Turnbull et al. 2010a,b; Pierson et al. 

2011, 2013, 2014; Williams et al. 2014a).

Canopy and ground cover influence the soil microclimate and the recruitment of 

soil microbes and microfauna that aid nutrient recycling and further improve infiltration 

and soil water storage (Pierson and Wight 1991; Blackburn et al. 1992; Breshears et al. 

1997b, 1998; Imeson et al. 1998; Reynolds et al. 1999; Belnap et al. 2005; Ludwig et al. 

2005). Heterogeneous vegetation patterns yield horizontally and vertically differential 

water use and soil water storage (Walter 1971; Belsky et al. 1989; Belsky et al. 1993; 

Joffre and Rambal 1993; Ryel et al. 1996; Breshears et al. 1997a,b, 1998; Breshears and 

Barnes 1999; Reynolds et al. 1999; Ludwig et al. 2005). These surface and subsurface 

interactions, in an undisturbed condition, result in an organized plant community that 

facilitates a positive feedback of biological productivity and hydrologic processes to conserve water, soil, and nutrient resources (Ludwig and Tongway 1995; Ludwig et al. 1997; 

Davenport et al. 1998; Cammeraat and Imeson 1999; Puigdefábregas et al. 1999; Reid 

et al. 1999; Reynolds et al. 1999; Ludwig and Tongway 2000; Ludwig et al. 2000; Pyke 

et al. 2002; Wilcox et al. 2003a; Ludwig et al. 2005; Puigdefábregas 2005; Pierson et al. 

2010). The stability of the system is defined by its resistance to reduction of these capacities and by its resiliency to perturbations (Schlesinger et al. 1990; Ludwig and Tongway 

1995; Ludwig et al. 1997; Ludwig and Tongway 2000; Pyke et al. 2002; Ludwig et al. 

2005; Williams et al. 2014a).

Vegetation and Cover Influences on Infiltration and Runoff Generation

Higher infiltration rates on coppice mounds versus interspaces are attributed to 

deeper surface soil horizons, greater organic matter accumulation and aggregate stability, 

lower bulk density, macropores, canopy interception and stemflow, and surface retention 

of throughflow and runon underneath and immediately adjacent to the canopy area. Litter 

amassment and decomposition underneath shrub and tree canopies (fig. 15) and differential rainsplash contribute to soil, organic matter, and nutrient accumulation (Blackburn 

1975; Blackburn et al. 1992; Parsons et al. 1992; Ludwig and Tongway 1995; Schlesinger 

et al. 1996; Puigdefábregas et al. 1999; Reynolds et al. 1999; Schlesinger et al. 1999; 

Belnap et al. 2005; Ludwig et al. 2005). Litter and organic matter promote aggregate 

stability, macropore formation, and low bulk densities associated with higher infiltration 

rates and retain surface water, prolonging time for infiltration (Meeuwig 1970; Blackburn 

and Skau 1974; Tromble et al. 1974; Roundy et al. 1978; Wood et al. 1978; Wood and 

Blackburn 1981; Beven and Germann 1982; Devaurs and Gifford 1984; Thurow et al. 

1986; Johnson and Gordon 1988; Wilcox et al. 1988; Blackburn et al. 1990; Dunne et al. 

1991; Seyfried 1991; Pierson et al. 1994a,b; Abrahams et al. 1995; Parsons et al. 1996; 

Seyfried and Wilcox 1995; Cerdà 1998b; Wilcox et al. 2003a; Puigdefábregas 2005; 

Pierson et al. 2010, 2013, 2014; Williams et al. 2014a). Soil fauna activity is enhanced 

by the microclimate, moisture regimes, and nutrient availability underneath canopies. 

The associated biological activity further improves soil aggregation, macroporosity, and 
34 USDA Forest Service RMRS-GTR-351. 2016.

infiltration (Cammeraat and Imeson 1998; Imeson et al. 1998; Puigdefábregas et al. 1999; 

Dunkerley 2002; Belnap et al. 2005; Ludwig et al. 2005). Stemflow concentrates water 

input at plant bases, allowing rapid vertical recharge of the soil profile via preferential 

flow along root channels (Thurow et al. 1987; Návar and Bryan 1990; Martinez-Meza 

and Whitford 1996; Newman et al. 1997; Whitford et al. 1997; Devitt and Smith 2002; 

Abrahams et al. 2003; Bhark and Small 2003; Carlyle-Moses 2004; Owens et al. 2006; 

Lebron et al. 2007).

Figure 15—Photographs from a Utah juniper woodland site in Utah, showing (A) general direction for 

overland flow over contiguous bare interspace, (B) interspace concentrated flowpath during artificial rainfall 

simulation, (C) hydrologically stable shrub and (D) tree coppice microsites, (E) moderately stable vegetated 

interspace microsite; and (F) hydrologically unstable bare interspace microsite. High-intensity artificial rainfall 

simulations performed at the site by Pierson et al. (2010) produced 38, 46, 133, and 313 cumulative grams 

of sediment per m2 area from 0.5 m2 plots on the shrub coppice (C), tree coppice (D), and vegetated (E) 

and bare (F) interspaces, respectively (photos: USDA Agricultural Research Service, Northwest Watershed 

Research Center).
USDA Forest Service RMRS-GTR-351. 2016. 35

Plant growth form also influences infiltration processes. Infiltration rates are 

generally higher for bunchgrasses than sod-forming grasses (Wood and Blackburn 1981; 

Knight et al. 1984; Thurow et al. 1986, 1988; Blackburn et al. 1992; Pierson et al. 2002a). 

Greater vegetative biomass and organic matter accumulation on bunchgrasses than 

sodgrasses result in greater rainfall and runoff interception (Knight et al. 1984; Thurow 

et al. 1986, 1988). Additionally, biomass and organic matter accumulations under bunchgrasses most likely favor infiltration-increasing microbial activity (Blackburn et al. 1992). 

Infiltration under shrub canopies is usually greater than under grass canopies (Wood and 

Blackburn 1981, Schlesinger et al. 1999), but the relationship may be reversed depending 

on grass biomass (Wilcox et al. 1988). The overall greater infiltration in canopy patches 

on shrublands and grasslands increases water availability beneath canopies, which in turn 

stimulates biological activity, plant growth, and organic matter and nutrient recruitment. 

This creates a continuous positive feedback (Schlesinger et al. 1990; Belnap et al. 2005; 

Puigdefábregas 2005; D’Odorico et al. 2007).

Interspace areas on rangelands, particularly shrublands, are often associated with 

surface and subsurface characteristics that inhibit infiltration and soil water storage, and 

promote rapid ponding (fig. 13) and runoff initiation. Interspaces occur with various 

amounts of herbaceous cover, or exist as contiguous bare patches (fig. 15; Blackburn et 

al. 1992; Pierson et al. 1994a,b; Abrahams et al. 1995; Seyfried and Wilcox 1995; Wilcox 

and Breshears 1995; Parsons et al. 1996; Reid et al. 1999; Wilcox et al. 2003a). Wellvegetated interspaces may exhibit similar surface characteristics as canopy areas to some 

degree, but usually generate more surface runoff (table 3; Reid et al. 1999; Bhark and 

Small 2003; Wilcox et al. 2003a). On more water-limited or degraded sites, interspaces 

have low plant biomass and organic matter (fig. 15F) and thin surface soil accumulations 

(Blackburn 1975; Abrahams and Parsons 1991a; Abrahams et al. 1995; Parsons et al. 

1996; Wilcox et al. 1996; Pierson et al. 2010). These characteristics result in poor aggregate stability and soil structure, and high bulk densities relative to coppices. They also 

facilitate low infiltration rates (Blackburn and Skau 1974; Blackburn 1975; Roundy et 

al. 1978; Wood et al. 1978; Thurow et al. 1986; Johnson and Gordon 1988; Wilcox et al. 

1988; Blackburn and Wood 1990; Blackburn et al. 1990; Abrahams and Parsons 1991a; 

Seyfried 1991; Blackburn et al. 1992; Pierson et al. 1994a,b; Abrahams et al. 1995; 

Seyfried and Wilcox 1995; Wilcox and Breshears 1995; Abrahams et al. 1996; Parsons 

et al. 1996; Wilcox et al. 1996; Reid et al. 1999; Wilcox et al. 2003a; Pierson et al. 2010, 

2011, 2013, 2014; Williams et al. 2014a). In general, surface characteristics of interspace 

areas are consistently different from coppices throughout the year, but the magnitude of 

the differences and respective influences on infiltration exhibit some seasonality. The 

spatial differences in vegetation cover and surface characteristics exert a greater influence 

than do seasonal differences on infiltration and runoff generation from sparsely covered 

shrublands, whereas seasonal differences in spatially arranged plant biomass might 

be of greater influence on infiltration patterns on well-vegetated grass-dominated sites 

(Blackburn et al. 1992).

Infiltration in interspace locations is strongly influenced by the expanse of bare 

ground, rock cover, or vesicular crusts (Blackburn 1975; Wood et al. 1978; Johnson and 

Gordon 1988; Abrahams and Parsons 1991a; Parsons et al. 1992; Abrahams and Parsons 

1994; Pierson et al. 1994a; Parsons et al. 1996; Reid et al. 1999; Pierson et al. 2010). 

Exposure of bare ground to raindrop impact increases potential for surface sealing or 
36 USDA Forest Service RMRS-GTR-351. 2016. Table 3—Site characteristics, runoff coefficients, and sediment yield reported for rainfall simulation and natural rainfall experiments in the western United States. Craddock and Pearse (1938) Cold desert (Great Basin, Idaho) Bunchgrasses Unb 20.2 30 - 46/60 Artificial - Dry - - ~35 - 1 1 Unb 20.2 30 - 92/30 Artificial - Dry - - ~35 - 1 1 Unb 20.2 40 - 46/60 Artificial - Dry - - ~35 - <1 1 Unb 20.2 40 - 92/30 Artificial - Dry - - ~35 - <1 1 Craddock and Pearse (1938) Cold desert (Great Basin, Idaho) Grassland (Bromus tectorum) Unb 20.2 30 - 46/60 Artificial - Dry - - ~20 - 10 31 Unb 20.2 30 - 92/30 Artificial - Dry - - ~20 - 5 11 Unb 20.2 40 - 46/60 Artificial - Dry - - ~20 - 26 49 Unb 20.2 40 - 92/30 Artificial - Dry - - ~20 - 53 331 Craddock and Pearse (1938) Cold desert (Great Basin, Idaho) Grassland (Lupinus spp./Stipa lettermanii ) Unb 20.2 30 - 46/60 Artificial - Dry - - ~25 - 44 274 Unb 20.2 30 - 92/30 Artificial - Dry - - ~25 - 57 511 Unb 20.2 40 - 46/60 Artificial - Dry - - ~25 - 44 253 Unb 20.2 40 - 92/30 Artificial - Dry - - ~25 - 55 468 Johnson and Gordon (1988) Cold desert (Great Basin, Idaho) Shrub coppice (Artemisia tridentata) Unb ~0.9 6 - 127/30 Artificial - Dry 15 41 85 25 15 5 Interspace Unb ~0.9 6 - 127/30 Artificial - Dry 29 4 71 13 48 39 Johnson and Blackburn (1989)d Cold desert (Great Basin, Idaho) Shrub steppe (A. tridentata) Unb 32.6 10 - 64/60 Artificial - Dry 16 39 84 - 2 5 Unb 32.6 6 - 64/60 Artificial - Dry 19 12 81 - 11 11 Unb 32.6 9 - 64/60 Artificial - Dry 45 16 55 - 17 15 Pierson et al. (1994b) Cold desert (Great Basin, Idaho) Shrub coppice (A. tridentata) Unb ~0.1 7 - 67/60 Artificial - 4 0 100 100 - 3 1 Vegetated interspace Unb ~0.1 7 - 67/60 Artificial - 4 4 - 96 - 23 23 Bare interspace Unb ~0.1 7 - 67/60 Artificial - 2 94 - 6 - 65 381 Reid et al. (1999) Temperate steppe mountains (Pajarito Plateau, New Mexico) Tree coppice (Pinus edulis or Juniperus monosperma) Unb 1.0 6-12 - Variablee Natural - - 0 - 100 - 8e 39e Vegetated interspace Unb ~2 6-12 - Variablee Natural - - 34 - 66 - 25e 298e Bare interspace Unb ~2 6-12 - Variablee Natural - - 84 - 16 - 37e 1,007e Study Climatic region (location) Microsite/ plant community Treatment/ burn severity Plot size (m2) Slope (%) Time postfire (mth) Rain rate (mm h-1) /duration (min) Rain type WDPT (s)a Soil water (%)b/ conditions Bare soil (%) Canopy cover (%) Ground cover (%) Surface roughness (mm) Runoff coef. (%)c Sed. yield (g m-2)
USDA Forest Service RMRS-GTR-351. 2016. 37 Table 3. Continued Study Climatic region (location) Microsite/ plant community Treatment/ burn severity Plot size (m2) Slope (%) Time postfire (mth) Rain rate (mm h-1) /duration (min) Rain type WDPT (s)a Soil water (%)b/ conditions Bare soil (%) Canopy cover (%) Ground cover (%) Surface roughness (mm) Runoff coef. (%)c Sed. yield (g m-2) Benavides- Solorio and MacDonald (2001, 2002)f Temperate steppe mountains (Colorado Front Range, Colorado) Dry forest 

(Pinus ponderosa)

Low-Unb 1.0 20-25 1-3 79/60 Artificial ~65 2 1 - 99 - 55 80

Mod 1.0 20-35 1-3 79/60 Artificial ~50 2 12 - 88 - 58 179

High 1.0 20-45 1-3 79/60 Artificial ~60 2 77 - 23 - 66 1,280

Johansen et al. (2001)

Temperate steppe mountains (Pajarito Plateau, New Mexico)

Dry forest (P. ponderosa) 

Unb 32.5 5 3 60/60g Artificial - ~5 48 52 - 23 36

High 32.5 7 3 60/60g Artificial - ~5 74 26 - 45 912

Pierson et al. (2001a, 2008a) 

Cold desert (Great Basin, Nevada)

Shrub coppice(A. tridentata)

Unb 0.5 30-40 1 85/60 Artificial 200 7 1 100 99 - 30 12

High 0.5 30-40 1 85/60 Artificial 102 1 99 1 1 - 37 41

Interspace

Unb 0.5 30-40 1 85/60 Artificial 220 5 6 74 94 - 49 24

High 0.5 30-40 1 85/60 Artificial 97 1 99 4 1 - 30 21

Pierson et al. (2002b)h

Cold desert (Great Basin, Idaho)

Shrub coppice(A. tridentata)

Unb 0.5 35-60 12 67/60 Artificial - ~14 7 88 93 18 11 2

Mod 0.5 35-60 12 67/60 Artificial - ~5 97 11 3 12 34 30

High 0.5 35-60 12 67/60 Artificial - ~5 98 13 2 12 37 22

Interspace

Unb 0.5 35-60 12 67/60 Artificial - ~14 89 18 12 18 24 4

Mod 0.5 35-60 12 67/60 Artificial - ~5 95 16 5 12 26 12

High 0.5 35-60 12 67/60 Artificial - ~5 99 5 1 10 49 148

O’Dea and Guertin, (2003) 

Hot desert(Sonoran Desert, Arizona)

Grassland

Unb 30 1-3 -i Variable Natural - Dry - 21 - - 6 1,700i

Mod 30 1-3 -

i Variable Natural -

j Dry - 11 - - 6 2,800i

Grassland

Unb 30 1-3 -k Variable Natural - Dry - 37 - - 14 1,800k

Mod 30 1-3 -k Variable Natural -

j Dry - 29 - - 14 2,200k

Pierson et al. (2007a)

Cold desert (Great Basin, Oregon)

Shrub-interspace zone 

Unb 32.5 19 - 55/60 Artificial - - 84 6 16 24 25 118

Shrub-interspace zone – trees removedl

Unb 32.5 19 - 55/60 Artificial - - 64 23 36 36 2 1

Pierson et al. (2007b)m

Cold desert (Great Basin, Idaho)

Grassland (B. tectorum) Unb 32.5 2 - 64/60 Artificial - 4 34 54 66 1 2 1
38 USDA Forest Service RMRS-GTR-351. 2016. Table 3. Continued Study Climatic region (location) Microsite/plant community Treatment/ burn severity Plot size (m2) Slope (%) Time postfire (mth) Rain rate (mm h-1) / duration (min) Rain type WDPT (s)a Soil water (%)b/ conditions Bare soil (%) Canopy cover (%) Ground cover (%) Surface roughness (mm) Runoff coef. (%)c Sed. yield (g m-2) Michaelides et al. (2009) Hot desert (Chihuahuan Desert, New Mexico) Shrub coppice (Larrea tridentata) Unb 1.5 7 - 125/16-30 Artificial - 7 79 65 21 - 55 97 Interspace Unb 1.5 3 - 125/16-30 Artificial - 8 89 1 11 - 49 122 Grassland (Bouteloua eriopoda) Unb 1.5 2 - 125/16-30 Artificial - 12 96 58 4 - 49 89 Pierson et al. (2009) Cold desert (Great Basin, Idaho) Shrub coppice (A. tridentata) Unb 0.5 35-50 1 85/60 Artificial 286 7 2 84 98 34 39 17 Mod-High 0.5 35-50 1 85/60 Artificial 261 3 42 10 58 11 76 183 Interspace Unb 0.5 35-50 1 85/60 Artificial 110 3 25 31 75 18 63 195 Mod-High 0.5 35-50 1 85/60 Artificial 117 4 84 0 16 11 55 705 Shrub-interspace zone Unb 32.5 35-50 1 85/60 Artificial - 2 24 57 76 21 4 8 Mod-High 32.5 35-50 1 85/60 Artificial 208 4 76 0 24 11 27 988 Pierson et al. (2010) Cold desert (Great Basin, Nevada) Shrub-interspace zone (intercanopy) Unb 13 9 - 64/45 Artificial - 6 26n 39 74 17 24 45 Tree coppice (P. monophylla or J. osteosperma) Unb 13 9 - 64/45 Artificial - 11 3 27o 97 20 3 18 Shrub-interspace zone (intercanopy) Unb 13 9 - 102/45 Artificial - wet 26n 39 74 17 47 222 Tree coppice (P. monophylla or J. osteosperma) Unb 13 9 - 102/45 Artificial - wet 3 27o 97 20 5 36 Pierson et al. (2010) Cold desert (Great Basin, Utah) Shrub-interspace zone (intercanopy) Unb 13 14 - 64/45 Artificial - 7 29p 19 71 26 10 37 Tree coppice (J. osteosperma) Unb 13 15 - 64/45 Artificial - 9 8 21o 92 31 2 13 Shrub-interspace zone (intercanopy) Unb 13 14 - 102/45 Artificial - wet 29p 19 71 26 44 296 Tree coppice (J. osteosperma) Unb 13 15 - 102/45 Artificial - wet 8 21o 92 31 10 66
USDA Forest Service RMRS-GTR-351. 2016. 39 Table 3. Continued Study Climatic region (location) Microsite/plant community Treatment/ burn severity Plot size (m2) Slope (%) Time postfire (mth) Rain rate (mm h-1) /duration (min) Rain type WDPT (s)a Soil water (%)b/ conditions Bare soil (%) Canopy cover (%) Ground cover (%) Surface roughness (mm) Runoff coef. (%)c Sed. yield (g m-2) Pierson et al. (2013), Williams et al. (2014a) Cold desert (Great Basin, Idaho) Shrub coppice (Artemisia spp.) Unb 0.5 20 - 102/45 Artificial <5 wet 25 117 75 13 20 6 High 0.5 18 12 102/45 Artificial 11 wet 57 21 43 9 23 143 Interspace Unb 0.5 14 - 102/45 Artificial <5 wet 46q 20 54 9 63 36 High 0.5 16 12 102/45 Artificial <5 wet 49q 21 51 8 51 135 Tree coppice (J. occidentalis) Unb 0.5 21 - 102/45 Artificial 42 wet 0 170 100 12 23 6 High 0.5 17 12 102/45 Artificial 54 wet 50 50 50 8 58 206 Shrub-interspace zone Unb 13 19 - 102/45 Artificial - wet 28r 18 72 16 50 272 High 13 16 12 102/45 Artificial - wet 39r 32 61 17 50 572 Tree coppice (J. occidentalis) Unb 13 16 - 102/45 Artificial - wet 7 260 93 23 13 48 High 13 18 12 102/45 Artificial - wet 25 150 75 21 58 1,083 Pierson et al. (2014) Cold desert (Great Basin, Nevada) Shrub coppice (Artemisia spp.) Unb 0.5 11 - 102/45 Artificial <5 wet 12 93 88 14 4 6 High 0.5 13 10 102/45 Artificial <5 wet 49 53 51 8 10 48 Interspace Unb 0.5 9 - 102/45 Artificial <5 wet 44s 33 56 9 41 23 High 0.5 10 10 102/45 Artificial <5 wet 49s 30 51 8 46 41 Tree coppice (P. monophylla or J. osteosperma) Unb 0.5 12 - 102/45 Artificial 48 wet 0 7t 100 12 0 0 High 0.5 15 10 102/45 Artificial 65 wet 10 4t 91 12 28 46 Pierson et al. (2014) Cold desert (Great Basin, Utah) Shrub coppice (Artemisia spp.) Unb 0.5 17 - 102/45 Artificial <5 wet 18 69 82 13 8 33 High 0.5 16 10 102/45 Artificial <5 wet 44 28 56 11 29 220 Interspace Unb 0.5 19 - 102/45 Artificial <5 wet 52u 19 48 11 56 233 High 0.5 16 10 102/45 Artificial <5 wet 38u 7 62 9 64 351 Tree coppice (J. osteosperma) Unb 0.5 20 - 102/45 Artificial 88 wet 7 22t 93 12 22 98 High 0.5 21 10 102/45 Artificial 125 wet 9 2t 91 12 18 294 a Water drop penetration time (WDPT) is an indicator of strength of soil water repellency as follows: <5 s wettable, 5 to 60 s slightly repellent, 60 to 600 s strongly repellent (Bisdom et al. 1993). b Measured near the soil surface (<5 cm depth). c Runoff coefficient is equal to cumulative runoff divided by cumulative rainfall applied. Value is multiplied by 100 to obtain percentage. d Data shown are for dry run experiments at Coyote Butte, Nancy, and Summit sites, respectively by row. e Runoff and erosion following natural rainfall events were monitored over a 14-month period. f Data presented for Bobcat Fire only. g Rainfall applied for 60 min under dry conditions, followed by 24-h hiatus, 30 min of rainfall, 30-min hiatus, and 30 min rainfall. Total rain applied was 120 mm. (footnotes continued on next page)
40 USDA Forest Service RMRS-GTR-351. 2016. h Data presented from south-facing slopes solely. i Cumulative runoff and sediment yield for period of 1 July 1998 to 1 October 1998 resulting from natural rainfall events (100 mm). Fire was in May 1998. j Informal water drop tests showed no postfire soil water repellency at soil surface (O’Dea and Guertin 2003). k Cumulative runoff and sediment yield for period of 1 July 1999 to 1 October 1999 resulting from natural rainfall events (106 mm). Fire was in May 1998. l J. occidentalis trees removed from site by chainsaw cutting 10 years before rainfall simulation experiments. m This is a multiple year study; means shown for soil, cover, runoff, and sediment yield are average of 3 simulation years. n Bare ground was about 64 percent (38 percent rock cover and 26 percent bare soil). o Trees removed from plot by chainsaw immediately before simulations. p Bare ground was about 79 percent (50 percent rock cover and 29 percent bare soil). q Bare ground was about 90 percent across unburned (42 percent rock cover and 46 percent bare soil) and burned (43 percent rock cover and 49 percent bare soil) plots. r Bare ground was about 88 percent (60 percent rock cover and 28 percent bare soil) for unburned plots and 84 percent (45 percent rock cover and 39 percent bare soil) for burned plots. s Bare ground was about 73 percent (29 percent rock cover and 44 percent bare soil) for unburned and 87 percent for burned (38 percent rock cover and 49 percent bare soil) plots. t Trees removed from plot about 12 months before simulation as part of earlier study (Pierson et al. 2010). u Bare ground ≥90 percent across unburned (38 percent rock cover and 52 percent bare soil) and burned (56 percent rock cover and 38 percent bare soil) plots.
USDA Forest Service RMRS-GTR-351. 2016. 41

development of infiltration-inhibiting surface crusts (Branson et al. 1981; Puigdefábregas 

et al. 1999). Decreasing infiltration and increasing runoff with increasing expanse of 

bare or vesicular surfaces are well documented in literature (Branson and Owen 1970; 

Blackburn et al. 1992; Pierson et al. 1994a; Abrahams et al. 1995; Parsons et al. 1996; 

Wilcox et al. 1996; Schlesinger et al. 1999, 2000; Pierson et al. 2002a, 2007a, 2010, 

2014; Williams et al. 2014a,b). The effects of rock cover (more than 2 mm) depend 

on the size, amount, and embeddedness of the rocks (Wilcox et al. 1988; Poesen et al. 

1990; Poesen and Ingelmo-Sanchez 1992). Infiltration is generally positively correlated 

with rocks lying on top of the soil matrix due to increased surface roughness and greater 

porosity and aggregation around rocks; surface rock extends time to ponding and runoff, 

increasing time for infiltration (Poesen et al. 1990; Abrahams and Parsons 1994; Poesen 

et al. 1994; Valentin 1994; Cerdà 2001; Martínez-Zavala and Jordán 2008). Infiltration 

is negatively correlated with embedded rock cover due to a decrease in nonabsorbing 

area. Wilcox et al. (1988), Abrahams and Parsons (1991a), and Pierson et al. (2010, 

2013) reported negative correlations between rock cover and infiltration in interspace 

areas, but did not explicitly evaluate embeddedness. The studies by Wilcox et al. (1988) 

and Abrahams and Parsons (1991a) indicate interspace areas occurred in swales and 

were more compacted and crusted than coppice areas. Wilcox et al. (1988), Abrahams 

and Parsons (1991a), and Pierson et al. (2010) suggested that the negative correlations 

were not exclusively associated with rock cover; instead, the relationship was due to 

co-occurring low infiltration rates of the bare interspace areas and extensive rock cover. 

Wilcox et al. (1988) further indicated infiltration was negatively correlated with smaller 

size rock cover (2 to 12 mm) and positively correlated with rock cover of intermediate sizes (26 to 150 mm). Tromble et al. (1974) also reported a negative relationship in 

infiltration and small-size rock cover (less than 10 mm). These studies suggest rock cover 

can facilitate infiltration and that negative effects of rock cover on infiltration most likely 

occur when smaller rocks dominate and the rock cover is embedded rather than freely 

lying atop the soil surface (Brakensiek and Rawls 1994).

The vegetation- and soils-driven hydrologic heterogeneity (Puigdefábregas 2005) 

of rangeland ecosystems creates a mosaic of runoff source and sink areas at the hillslope 

scale (figs. 15 and 16) (Schlesinger et al. 1990; Wilcox and Breshears 1995; Schlesinger 

et al. 1996; Bergkamp 1998; Puigdefábregas et al. 1999; Reid et al. 1999; Wilcox et 

al. 2003a; Ludwig et al. 2005; Turnbull et al. 2012; Williams et al. 2014a). The timing 

and quantity of overland flow generation on rangeland sites is strongly correlated to the 

quantity and arrangement of canopy and ground cover and bare interspace (Branson et 

al. 1981). Runoff occurs more rapidly after the onset of rainfall in sparsely vegetated 

interspaces than in vegetated interspace and coppice locations. These relationships, along 

with rainfall distribution, are responsible for spatial variability in runoff generation during intermediate storm events, but may be dampened by high-intensity or long-duration 

rainfall, creating more uniform runoff (Reid et al. 1999; Puigdefábregas 2005).

The hydrologic connectivity and downslope surface hydraulic conductivity dictate 

the progression or decay of surface runoff with increased slope length (Abrahams et 

al. 1991; Dunne et al. 1991; Pierson et al. 1994b; Wilcox 1994; Abrahams et al. 1995; 

Cerdà 1997; Bergkamp 1998; Davenport et al. 1998; Puigdefábregas et al. 1999; Reid 

et al. 1999; Wainwright et al. 2000; Wilcox et al. 2003a; Puigdefábregas 2005). Wellconnected flowpaths develop in consecutive source areas where overland flow is routed 
42 USDA Forest Service RMRS-GTR-351. 2016.

around topographically elevated coppice mounds, grass clumps, or roughness elements 

(fig. 16) (Emmett 1970, 1978; Dunne et al. 1991; Seyfried 1991; Parsons et al. 1992; 

Thornes 1994; Abrahams et al. 1995; Wilcox and Breshears 1995; Parsons et al. 1996; 

Schlesinger et al. 1996, 1999; Wilcox et al. 2003a). Where concentrated, these flowpaths 

transfer large volumes of water laterally at greater overland flow depths and velocities 

than occur in sheetflow processes (Abrahams et al. 1995; Parsons et al. 1996; Pierson et 

al. 2007a). These effects are amplified on steep slopes (Al-Hamdan et al. 2013), although 

infiltration and slope steepness have been shown to have a positive correlation on some 

rangelands (Wilcox et al. 1988). The interception of flowpaths (mostly due to ponding 

behind coppices or topographic features) and subsequent re-infiltration (runon) in coppice 

or vegetated hydrologic sinks are thought to stimulate biological productivity and further 

facilitate coppice-interspace structure (Schlesinger et al. 1990; Joffre and Rambal 1993; 

Dunkerley and Brown 1995; Ludwig and Tongway 1995; Wilcox and Breshears 1995; 

Breshears et al. 1997b; Tongway and Ludwig 1997; Bergkamp 1998; Puigdefábregas 

et al. 1999; Reid et al. 1999; Bhark and Small 2003; Wilcox et al. 2003a; Ludwig et al. 

2005). Abrahams et al. (1995) and Parsons et al. (1996) observed that fine-scale vegetative heterogeneity of a hydrologically stable grassland facilitated runon processes and 

that the coarseness of vegetative structure in a degraded shrubland community amplified 

runoff with increasing slope length (up to 35 m). Reid et al. (1999) estimated that runon 

from bare interspaces (sources) to vegetated interspace areas (sinks) in a hydrologically 

stable twoneedle pinyon/oneseed juniper woodland accounted for 12 percent of precipitation over the course of 77 rainfall events.

These studies illustrate that a coarsely arranged source-sink structure, as observed 

on degraded sites, potentially generates and releases more surface runoff than a finely 

structured source-sink community (Schlesinger et al. 1990; Abrahams et al. 1995; Parsons 

Figure 16—Concentrated flow formed in interspace areas during a high-intensity 

rainfall on a shrub steppe site in the Reynolds Creek Experimental Watershed, 

Idaho. The lack of runoff from shrub microsites clearly demonstrates the commonly 

observed hydrologic stability observed for areas underneath shrub or tree canopies 

on rangeland sites (photo: USDA Agricultural Research Service, Northwest 

Watershed Research Center).
USDA Forest Service RMRS-GTR-351. 2016. 43

et al. 1996; Wilcox et al. 1996; Davenport et al. 1998; Bhark and Small 2003). Studies by 

Abrahams et al. (1995), Parsons et al. (1996), Wainwright et al. (2000), Michaelides et al. 

(2009), and Turnbull et al. (2010b, 2012) provide comparative examples of these relationships for fine (grassland) versus coarsely arranged (shrubland) rangeland communities 

in southern Arizona. Pierson et al. (2010, 2013) and Williams et al. (2014a) present 

examples of similar relationships following conifer encroachment into Great Basin shrub 

steppe.

Plant Use of Subsurface Water and Its Influence on Runoff

A positive feedback exists between subsurface water acquisition, plant community 

structure, and infiltration, and the maintenance of this arrangement (Richards and 

Caldwell 1987; Dawson 1993; Burgess et al. 2001; Ludwig et al. 2003; Ryel et al. 2003, 

2004; Muñoz et al. 2008; Scott et al. 2008). Herbaceous and woody plants differ in their 

ability to obtain the limited soil water on most rangeland sites (Walter 1971; Breshears 

and Barnes 1999; Schenk and Jackson 2002). Rangeland plant community density and 

structure therefore reflect the ability of the plants to obtain and efficiently use available 

soil water (Caldwell 1985; Dawson 1993; Schenk and Jackson 2002). Walter (1971) 

proposed a two-layered model of soil water use in water-limited ecosystems based on 

rooting depth partitioning among herbaceous and woody species. The model suggests 

that herbaceous plants primarily extract soil water from upper soil layers and that woody 

plants have the sole access to deeper soil water.

Subsequent research has shown woody plants vary in the depth at which they 

extract soil water (Peláez et al. 1994; Montaña et al. 1995; Breshears et al. 1997a; Schenk 

and Jackson 2002) and that they are capable of competing laterally with herbaceous 

species for shallow soil water in interspace areas (Caldwell et al. 1985; Ansley et al. 

1991; Peláez et al. 1994; Montaña et al. 1995; Breshears et al. 1997a; Breshears and 

Barnes 1999). Schenk and Jackson (2002) summarized rooting depths for herbaceous and 

woody plants over a wide range of precipitation regimes. They observed that differences 

in rooting depths between herbaceous and woody species tend to decrease with increasing 

precipitation. This suggests that as water becomes limited, a more distinct vertical separation in water use by woody and herbaceous plants emerges (Schenk and Jackson 2002). 

Breshears and Barnes (1999) pointed out that horizontal as well as vertical gradients 

exist due to woody plant lateral acquisition of soil water from interspace areas and that 

decreased near-surface soil water favors woody plant recruitment.

Similar processes for horizontal acquisitions of surface water via preferred infiltration or runon have been proposed to explain maintenance of vegetated islands (Joffre and 

Rambal 1993; Dunkerley and Brown 1995; Wilcox and Breshears 1995; Ludwig et al. 

1997; Bergkamp 1998; Puigdefábregas et al. 1999; Bhark and Small 2003; Wilcox et al. 

2003a; Ludwig et al. 2005) and desertification of water-limited landscapes (Schlesinger 

et al. 1990). Prolonged periods of dry soil conditions coarsen the vegetative structure 

in favor of woody plants and shrub/tree islands whereas wet periods facilitate a more 

vertically and horizontally heterogeneous community of herbaceous and woody plants 

(Schlesinger et al. 1990). Coarsening of the plant community (such as transitions from 

grassland to shrubland and shrubland to woodland) through drought or disturbance commonly increases bare ground area, hydrologic connectivity of runoff source areas, and 
44 USDA Forest Service RMRS-GTR-351. 2016.

surface runoff from point to hillslope scales (Abrahams et al. 1995; Parsons et al. 1996; 

Wilcox et al. 1996; Davenport et al. 1998; Pierson et al. 2010; Turnbull et al. 2010a,b; 

Pierson et al. 2011; Turnbull et al. 2012; Williams et al. 2014a, 2016a).

Plant community structure may also be influenced by plant-specific belowground 

water conservation strategies that vertically redistribute (via hydraulic redistribution) soil 

water (Caldwell et al. 1998; Horton and Hart 1998; Jackson et al. 2000; Meinzer et al. 

2001). Hydraulic redistribution is the passive transfer of soil water through roots upward 

as hydraulic lift (Richards and Caldwell 1987; Dawson 1993; Wan et al. 1993; Emerman 

and Dawson 1996; Caldwell et al. 1998; Horton and Hart 1998; Yoder and Nowak 1999a; 

Mendel et al. 2002; Ludwig et al. 2003; Zou et al. 2005; Muñoz et al. 2008) or downward 

as hydraulic descent (Burgess et al. 1998; Schulze et al. 1998; Smith et al. 1999; Jackson 

et al. 2000; Burgess et al. 2001; Leffler et al. 2002; Ryel et al. 2002; Hultine et al. 

2003a,b; Ryel et al. 2003; Hultine et al. 2004; Ryel et al. 2004; Leffler et al. 2005; Scott 

et al. 2008) from wetter to drier soil layers along a gradient in water potential. Lateral 

redistribution has also been observed (Brooks et al. 2002; Burgess and Bleby 2006), but 

its occurrence is less documented than vertical transfers. Hydraulic lift has been documented in more than 50 woody taxa and herbaceous species (Jackson et al. 2000), but is 

most common in deeper-rooted shrubs and trees. During dry periods, plants undergoing 

hydraulic lift absorb soil water from moist deep soil layers during evening hours when 

transpiration demands are low. The absorbed water is then transferred upwards and 

released via roots to the drier near-surface soil during the night. The released water is 

subsequently reabsorbed during the next day to meet daily transpiration demands.

Burgess et al. (1998) demonstrated that the reverse of hydraulic lift also occurs. 

They found that as soils wet up following the dry season, the roots of silkoak (Grevillea 

robusta A. Cunn. ex R. Br.) and river redgum (Eucalyptus camaldulensis Dehnh.) 

redistributed soil water from the wetter near-surface to drier soil pockets at depth. They 

termed the process hydraulic redistribution. In other studies, Ryel et al. (2003, 2004) discovered that pulse rain events in a stand of big sagebrush (A. tridentata Nutt.) delivered 

rain at different depths (downward distribution) simultaneously rather than sequentially 

from upper to lower soil layers. This process might be expected with macropore or preferential flow; however, the arrival times at the different depths were simultaneous over 

a few days rather than hours as commonly reported for macropore and other preferred 

flowpaths. Hydraulic descent has also been reported for other water-limited plants including a cheatgrass (Bromus tectorum L.) monoculture in Utah, (Leffler et al. 2005), velvet 

mesquite (Prosopis velutina Woot.) in southern Arizona (Hultine et al. 2004, Scott et al. 

2008), Utah juniper (J. osteosperma (Torr.) Little) in northern Utah (Leffler et al. 2002), 

and Arizona walnut (Juglans major Torr.) in southeastern Arizona (Hultine et al. 2003a).

The decreased water stress associated with hydraulic redistribution provides dryland 

vegetation numerous ecological benefits thought to increase ecosystem primary productivity. These include enhanced water-use efficiency and transpiration (Richards and 

Caldwell 1987; Caldwell and Richards 1989; Dawson 1993, 1996; Emerman and Dawson 

1996; Caldwell et al. 1998; Brooks et al. 2002; Ryel et al. 2002; Hultine et al. 2004; Ryel 

et al. 2004; Muñoz et al. 2008; Scott et al. 2008), greater fine-root longevity (Richards 

and Caldwell 1987; Dawson 1993; Meinzer et al. 2004), increased microbial activity and 

nutrient acquisition (Caldwell et al. 1998; Dawson 1993, 1996; McCulley et al. 2004), 

prolonged symbiotic mychorrizal associations during drought (Richards and Caldwell 
USDA Forest Service RMRS-GTR-351. 2016. 45

1987; Caldwell et al. 1998; Horton and Hart 1998; Querejeta et al. 2003, 2007), reduced 

carbon consumption (Dawson 1993; Caldwell et al. 1998), extension of the growing 

season (Ryel et al. 2004; Muñoz et al. 2008; Scott et al. 2008), and decreased competition 

for limited water resources (Smith et al. 1999). The primary benefit is, of course, water 

conservation.

Few long-term assessments of the ecosystem benefits associated with hydraulic 

redistribution exist (Scott et al. 2008). In a 2-year study, Scott et al. (2008) found that 

velvet mesquite on a southern Arizona rangeland redistributed soil water from the 

near surface to deep soil locations throughout the year, including the dormant season. 

Downward redistributed winter-season precipitation allowed trees to transpire more 

during the dry pre-monsoon period. Hydraulic descent of monsoonal summer rainfall 

extended the growing season and allowed for greater photosynthesis and plant productivity during the seasonal drought. Similar results were reported in another study of velvet 

mesquite in southeastern Arizona (Hultine et al. 2004).

Plants neighboring hydraulic-lifting species may benefit from soil water redistribution as well (Caldwell and Richards 1989; Dawson 1993; Yoder and Nowak 1999a; Smith 

et al. 1999, Brooks et al. 2002; Leffler et al. 2005; Zou et al. 2005), but these benefits 

are probably limited by plant competition and the dry surface soil moisture conditions 

in which hydraulic lifting occurs (Caldwell et al. 1998; Ludwig et al. 2004; Muñoz et al. 

2008). Dawson (1993) reported that hydraulic lift by sugar maple (Acer saccharum) in 

a mesic forest influenced soil moisture conditions up to 5 m from the tree base. Within 

this distance, plants neighboring sugar maple used 3 to 60 percent of the lifted water. 

Neighboring plants that used a high percentage of lifted water exhibited increased 

water-use efficiency and greater aboveground growth (Dawson 1993). Yoder and Nowak 

(1999a) suggested that hydraulic lift by Mojave yucca (Yucca schidigera) plants in the 

water-limited Mojave Desert (located in parts of California, Nevada, Utah, and Arizona), 

provided daytime near-surface soil water for neighboring creosote (Larrea tridentata), 

rough joinfir (Ephedra nevadensis), burrobush (Ambrosia dumosa), pale desert-thorn 

(Lycium pallidum), and Indian ricegrass (Achnatherum hymenoides) plants. All six species exhibited hydraulic lift, but only Mojave yucca (a crassulacean acid metabolism, or 

CAM, species) lifted water during daytime hours and transpired at night.

Such benefits are not always observed for neighboring plants (Caldwell et al. 1998; 

Brooks et al. 2002; Ludwig et al. 2004; Muñoz et al. 2008). In an east African savanna, 

Ludwig et al. (2004) determined that any benefit of hydraulic lift by umbrella thorn 

(Acacia tortilis) observed for neighboring plants was overwhelmed by near-surface 

competition with the water-lifting trees. Ludwig et al. (2004) suggested that the trees 

outcompeted the grasses for lifted water and that grasses were then limited by the lack 

of additional water availability under the more xeric conditions relative to those in the 

Dawson (1993) study. Muñoz et al. (2008) also reported that near-surface water use by 

xeric community shrubs hydraulically lifting soil water mitigated potential losses to 

neighboring plants. Ishikawa and Bledsoe (2000) reported that hydraulic lifting by blue 

oak (Q. douglasii) occurred too late in the growing season for neighboring grasses to 

benefit.

Plants in dry climates with shallow and fibrous roots generally complete seasonal 

physiological processes during periods of high near-surface soil water content. As the 

near-surface environment dries out, shallow-rooted species die off and competition for 
46 USDA Forest Service RMRS-GTR-351. 2016.

near-surface resources is reduced. Deep-rooted species delaying hydraulic lift to the nearsurface can then extend the growing season and, by wetting the near-surface, improve 

near-surface nutrient acquisition during periods of the year when competition is low 

(Caldwell et al. 1998). Benefits to neighboring plants then appear to vary with precipitation regime, type of plant community, and the timing of hydraulic redistribution.

The volume of water redistributed is largely a function of available soil water 

and the daily evapotranspiration requirements. In a semiarid climate, Ryel et al. (2003) 

estimated that 74 percent of precipitation from a 36 mm event and 100 percent of 

precipitation from small (less than 8 mm) rainfall events that infiltrated 30 to 150 cm into 

the soil profile resulted from hydraulic redistribution by big sagebrush roots. Richards 

and Caldwell (1987) reported mountain big sagebrush (A. tridentata Nutt. ssp. vaseyana

(Rydb.) Beetle) hydraulically lifted one-third of its daily evapotranspiration demand. 

Caldwell and Richards (1989) found that artificial suppression of hydraulic lift reduced 

mountain big sagebrush daily transpiration by 25 to 50 percent. Hultine et al. (2003a) 

reported daily hydraulic descent amounted to 10 to 60 percent of daily transpiration for 

Arizona walnut. Hultine et al. (2004) estimated that diurnal hydraulic descent rates of 

velvet mesquite during the winter dormant season were 70 percent of that during the 

growing season following monsoon rainfall.

Leffler et al. (2005) found that about 6 percent of soil water at 10 to 20 cm depth 

underneath a cheatgrass monoculture was hydraulically lifted by cheatgrass during 

flowering and seed set. In the same study, senesced cheatgrass in a greenhouse-stored 

pot lifted 17 percent of soil water measured in an upper soil layer. Brooks et al. (2002) 

determined 28 to 35 percent of water removed daily from the upper 2 m of the soil profile 

in coniferous forests of moist Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco) in 

Washington and dry ponderosa pine (Pinus ponderosa Dougl. ex Laws) in Oregon, was 

replaced by nocturnal hydraulic redistribution. In a mesic climate, Emerman and Dawson 

(1996) found that an individual sugar maple tree was capable of lifting 100 L day-1 and 

that hydraulic lift provided 25 percent of tree daily water use. Dawson (1996) reported 

sugar maple was capable of lifting 25 percent of daily transpiration demand. The studies 

cited above are only a sample from literature to demonstrate that hydraulic redistribution 

occurs across a range of plant communities (herbaceous and woody) and climate regimes 

and may have a substantial impact on ecosystem water balances (Meinzer et al. 2001). 

Hydraulic redistribution may account for as much as 70 percent of daily transpiration; 

however, most values are in the 20 to 35 percent range depending on plant type, antecedent moisture conditions, time of year, and evapotranspiration demand.

Effects of Soil Water Repellency on Runoff Generation

Soil water repellency is a naturally occurring soil condition that inhibits infiltration. 

Its occurrence has been well documented on shrubland, chaparral, woodland, and semiarid forest ecosystems (Meeuwig 1971; Scholl 1971, 1975; DeBano 1981, 1991; Doerr 

et al. 1996, 2000; Jaramillo et al. 2000; DeBano 2001; Huffman et al. 2001; Hubbert et 

al. 2006; Lebron et al. 2007; Verheijen and Cammeraat 2007; Woods et al. 2007; Madsen 

et al. 2008; Pierson et al. 2008b; Doerr et al. 2009; Pierson et al. 2009, 2010; Robinson 

et al. 2010; Bodí et al. 2013; Pierson et al. 2013, 2014; Williams et al. 2014a). Waterrepellent soils form by the coating of particles with hydrophobic compounds leached 
USDA Forest Service RMRS-GTR-351. 2016. 47

from organic matter accumulations, microbial by-products, or fungal growth under litter 

and duff (Savage et al. 1972; Imeson et al. 1992; Bisdom et al. 1993; Doerr et al. 2000). 

The strength of soil water repellency and its influence on infiltration are a function of the 

quantity and type of overlying vegetation, soil texture, and soil water content (Burcar 

et al. 1994; Dekker and Ritsema 1994; Bauters et al. 2000; Doerr and Thomas 2000; 

Shakesby et al. 2000; Dekker et al. 2001; Huffman et al. 2001; MacDonald and Huffman 

2004; Verheijen and Cammeraat 2007; Madsen et al. 2008; Pierson et al. 2008b, 2009, 

2010). The type and quantity of vegetation dictate the amount and type of hydrophobic 

compounds potentially available. Coarse-textured soils generally are more susceptible 

to soil water repellency than fine-textured soils due to their greater particle surface area 

(DeBano 1991, Bisdom et al. 1993, Huffman et al. 2001); however, recent research has 

demonstrated that strong soil water repellency can occur in fine-textured soils (Doerr et 

al. 2000, 2006, 2009). Doerr et al. (2000, 2009) provide a review of occurrence, causes, 

hydrologic and erosional effects, and measurement methods of soil water repellency.

The strength and persistence of soil water repellency is highly variable in time 

and space (DeBano 1971; Witter et al. 1991; Shakesby et al. 1993; Dekker and Ritsema 

1994; Doerr and Thomas 2000; Dekker et al. 2001; Huffman et al. 2001; MacDonald 

and Huffman 2004; Leighton-Boyce et al. 2005; Verheijen and Cammeraat 2007; Woods 

et al. 2007; Madsen et al. 2008; Pierson et al. 2008b, 2009, 2010). Soil water repellency 

for a particular soil may be present under dry conditions, decrease with soil wetting, and 

reappear with soil drying (Shakesby et al. 1993; Doerr et al. 2000). Dekker et al. (2001) 

demonstrated that critical soil-water thresholds demarcate wettable and water-repellent 

soil conditions. Doerr et al. (2009) suggest from literature that the critical threshold 

ranges from 5 percent for organic dune sands to more than 30 percent for fine-textured 

soils. Huffman et al. (2001) reported that water repellency in sandy loam soils at 

semiarid-forested sites in Colorado became wettable at soil water contents of 12 to 25 

percent. Doerr and Thomas (2000) reported that temporal variability in soil water repellency was associated with seasonal rainfall patterns, biological productivity, and wetting 

and drying regimes. Pierson et al. (2008b, 2009) found that soil water repellency and the 

magnitude of its influence on infiltration and runoff exhibited significant annual variability at multiple steeply sloped mountain big sagebrush sites in the Inland Northwest, 

but the study did not explicitly track soil moisture patterns (fig. 17).

In addition to temporal variance, the strength of soil water repellency may be 

spatially variable (horizontally and vertically), owing to its presence mostly under 

or immediately adjacent to canopy- and litter-covered areas and spatial soil-moisture 

gradients (Imeson et al. 1992; Ritsema and Dekker 1994; Dekker et al. 2001; Verheijen 

and Cammeraat 2007; Woods et al. 2007; Madsen et al. 2008; Pierson et al. 2008b, 2009, 

2010, 2013, 2014; Williams et al. 2014a). On unburned sites, soil water repellency is 

commonly stronger at the soil surface and degrades with depth below the mineral surface 

(Huffman et al. 2001; Leighton-Boyce et al. 2007; Pierson et al. 2008b, 2009, 2010). The 

effects of fire on the occurrence and hydrologic impacts of soil water repellency are discussed in Section 4, Exacerbation, Alteration, and Formation of Soil Water Repellency.

Soil water repellency facilitates runoff initiation either by inhibiting infiltration at 

the surface (infiltration-excess runoff) or causing saturation of a shallow soil layer (saturation-excess runoff) immediately overlying a water-repellent zone (Doerr et al. 2000). 

In either case, runoff initiation may occur rapidly, but infiltration generally increases as 
48 USDA Forest Service RMRS-GTR-351. 2016.

soils become wet (Letey et al. 1962; Meeuwig 1971; Burch et al. 1989; DeBano 2000; 

Robichaud 2000; Pierson et al. 2008b, 2009). Increasing infiltration rates over time 

(minutes to hours) occurs due to (1) a gradual decrease in repellency with wetting, or (2) 

lateral and vertical water transfer through preferential infiltration and flow via macropores 

or breaks in the repellent layer (Meeuwig 1971; DeBano 1981; Burch et al. 1989; 

Imeson et al. 1992; Hendrickx et al. 1993; Ritsema et al. 1993; Dekker and Ritsema 

1994; Ritsema and Dekker 1994, 1995; Dekker and Ritsema 1995, 1996; Ritsema and 

Dekker 1996; Ritsema et al. 1997, 1998a, 1998b; Doerr et al. 2000; Jaramillo et al. 2000; 

Leighton-Boyce et al. 2007; Pierson et al. 2008b). Vegetation and ground cover store 

intercepted rainfall, as well as slow and retain overland flow, allowing more time for 

infiltration and soil wetting (Meeuwig 1971; Leighton-Boyce et al. 2007; Pierson et al. 

2008a, 2009, 2010, 2013; Williams et al. 2014a). Vegetation and ground cover also promote macropore development along root channels, animal burrows, and other soil voids 

(Belnap et al. 2005; Ludwig et al. 2005). Preferential flow into macropores bypasses 

water-repellent layers to wettable soil within the root zone (Meeuwig 1971; DeBano 

1981; Burch et al. 1989; Imeson et al. 1992; Hendrickx et al. 1993; Ritsema et al. 1993; 

Dekker and Ritsema 1994; Ritsema and Dekker 1994, 1995; Dekker and Ritsema 1996; 

Ritsema et al. 1998a, 1998b; Doerr et al. 2000; Jaramillo et al. 2000; Leighton-Boyce et 

al. 2007; Pierson et al. 2008b; Robinson et al. 2010). In some cases, the vertical bypass 

of water through repellent zones via macropores leaves a dry layer at the soil surface and 

wet conditions in the root zone (Meeuwig 1971; Burch et al. 1989; Imeson et al. 1992). 

The overall effect of preferential flow depends on the extensiveness of the macropore 

network and the strength of soil water repellency.

The efficacy of naturally occurring soil water repellency on infiltration can be significant at point scales, but quantification of the impacts over larger scales is confounded 

by spatial variability in hydrophobicity and cover as well as soil properties (Imeson et al. 

1992; Doerr et al. 2000; Shakesby et al. 2000; Doerr and Moody 2004; Leighton-Boyce 

Figure 17—Temporal variability of soil water repellency (measured by using water drop penetration time, 

WDPT) effects on infiltration of artificial rainfall into unburned, coarse-textured soils at two sagebrush sites: 

(A) Denio Fire (wildfire), Pine Mountain Range, Nevada, (Pierson et al. 2008a) and (B) Breaks Prescribed 

Fire, Reynolds Creek Experimental Watershed, Idaho (Pierson et al. 2009). WDPT is an indicator of strength 

of soil water repellency as follows: <5 s wettable, 5 to 60 s slightly repellent, 60 to 600 s strongly repellent 

(Bisdom et al. 1993).
USDA Forest Service RMRS-GTR-351. 2016. 49

et al. 2007; Pierson et al. 2009). DeBano (1971) found that horizontal infiltration was 

25 times faster in a soil under wettable conditions as compared to a similar soil under 

hydrophobic conditions. Leighton-Boyce et al. (2007) determined that runoff from smallplot (0.36 m2) rainfall simulations was 16 times higher under water-repellent conditions 

than when the same soils were wettable. Madsen et al. (2008) found that pre-wetting 

water-repellent surface soils underneath Utah juniper and twoneedle pinyon litter yielded 

hydraulic conductivities (as measured by an infiltrometer) 6 to more than 30 times greater 

than under water-repellent conditions. Madsen et al. (2008) observed (without taking 

specific measurements) that tree coppices retained surface water and routed it laterally 

toward preferential wet spots under the tree canopy.

Vertical preferential flow along wet spots has been referred to as fingered flow 

(Ritsema and Dekker 1994; Dekker and Ritsema 1995; Ritsema et al. 1997). Dekker and 

Ritsema (1996) reported that fingered flow into dry, strongly water-repellent conditions 

generated significant differences up to nearly 30 percent volumetric moisture content 

between closely spaced samples of fine-textured soils. In multiyear rainfall simulation 

studies of two steeply sloping mountain big sagebrush sites in Nevada and Idaho, Pierson 

et al. (2001a, 2008a,b, 2009) found that minimum- and steady-state infiltration rates 

(0.5 m2 rainfall simulation plots) on unburned shrub coppices increased 25 to 65 percent 

after a between-years decrease in soil water repellency strength by 55 to 75 percent. 

Minimum- and steady-state infiltration rates on unburned interspaces in the studies by 

Pierson et al. (2001a, 2008a) increased by 65 and 55 percent, respectively, after a 55 

percent between-years decrease in soil water repellency strength. Pierson et al. (2009) 

reported that threefold stronger soil water repellency on shrub coppice than interspace 

plots resulted in 31 mm and 49 mm of runoff from shrub coppices and interspaces, 

respectively. The contradiction in runoff rates with strength was attributed to interception, 

surface retention, and preferential flow (inferred) associated with greater canopy and 

ground cover on coppices. Soil moisture and cover conditions for respective coppice and 

interspace areas were similar for the unburned condition throughout the Pierson et al. 

(2001a, 2008a,b, 2009) studies. Clearly, soil water repellency can significantly reduce 

infiltration rates over small scales, but the heterogeneity of soil and cover conditions on 

undisturbed sites and preferential flowpaths most likely subdue the effects at hillslope 

and catchment scales (Meeuwig 1971; Burch et al. 1989; Imeson et al. 1992; Doerr et 

al. 2000; Shakesby et al. 2000; Doerr and Moody 2004; Verheijen and Cammeraat 2007; 

Pierson et al. 2009).

Soil water repellency may provide water conservation and increased plant productivity for some woody species and may indirectly mitigate runoff generation (Doerr et 

al. 2000; Jaramillo et al. 2000; Lebron et al. 2007; Madsen et al. 2008; Robinson et al. 

2010). Imeson et al. (1992) suggested that preferential flow to deep storage beneath the 

surface water-repellent layer trapped soil water and prevented it from evaporation and 

upward capillary transfer. Lebron et al. (2007) and Madsen et al. (2008) observed (in 

field observations) that surface water on water-repellent soils under Utah juniper and 

twoneedle pinyon was routed to preferential wet spots. They postulated that these locations provide fingered flow through the water-repellent layer to deep soil storage. Roundy 

et al. (1978) hypothesized similar behavior to explain rapid infiltration of simulated 

rainfall into water-repellent soils of Utah juniper. Other researchers have proposed 

soil water repellency as a routing mechanism to preferential flowpaths and deep soil 
50 USDA Forest Service RMRS-GTR-351. 2016.

recharge (see Doerr et al. 2000; Lebron et al. 2007). The recharge of deeper soil layers 

through preferential flow indirectly influences runoff behavior through increased plant 

productivity (Ryel et al. 2003). Water availability deep in the soil profile favors woody 

plant recruitment and facilitates a coppice/interspace structure (Breshears and Barnes 

1999). Increased plant productivity through greater water availability and transpiration 

rates (Ryel et al. 2003) recruits surface plant and litter biomass associated with higher 

infiltration rates (Ludwig et al. 1997; Wilcox et al. 2003a, Huxman et al. 2005; Ludwig et 

al. 2005). Therefore, surface flow routing by soil water repellency may function similar 

to the lateral surface transfers of overland flow (runon) in maintaining shrub, grass, and 

tree islands of higher biological activity and water retention (Schlesinger et al. 1990; 

Joffre and Rambal 1993; Pierson et al. 1994a,b; Dunkerley and Brown 1995; Ludwig and 

Tongway 1995; Seyfried and Wilcox 1995; Wilcox and Breshears 1995; Breshears et al. 

1997b; Tongway and Ludwig 1997; Bergkamp 1998; Puigdefábregas et al. 1999; Reid et 

al. 1999; Bhark and Small 2003; Wilcox et al. 2003a; Huxman et al. 2005; Ludwig et al. 

2005; Robinson et al. 2010).

Cover Influences on Sediment Detachment and Transport

Surface Protection from Raindrop Detachment

The primary effects of cover on rainsplash erosion are dissipation of rainfall energy, 

direct prevention of rainfall contact with the soil surface, and soil stabilization. Recall 

that for sediment detachment to occur the erosive energy (shear stress) applied to the 

soil surface must exceed the detachment resistance of soil (critical shear stress or shear 

strength) (Foster and Meyer 1972; Sharma et al. 1991; Nearing et al. 1999; Kinnell 2005). 

Canopy and ground cover dissipate the erosive energy of rainfall via interception, thereby 

reducing the shear stress applied to the soil surface (Al-Hamdan et al. 2013). Recent studies have estimated that rangeland canopy and ground cover can reduce rainfall erosivity 

approximately 50 percent (Martinez-Mena et al. 1999; Wainwright et al. 1999). Plants 

and organic material also contribute to the soil shear strength by anchoring soils and 

promoting aggregate stability (Blackburn 1975; Pierson et al. 1994a,b; Cammeraat and 

Imeson 1998; Cerdà 1998b; Puigdefábregas et al. 1999; Pierson et al. 2010, 2013, 2014; 

Williams et al. 2014a). The surface protection and soil stabilization by cover elements 

(figs. 15C and 15D) are paramount in minimizing erosion given that raindrop impact is 

the primary sediment contributor to shallow overland flow (Young and Wiersma 1973; 

Wainwright et al. 2000; Kinnell 2005). Cover may significantly reduce soil loss even 

where surface runoff is substantial (for example during intense rainfall or water-repellent 

soil conditions) (Pierson et al. 2009, 2010).

Rainsplash erosion rates are seldom quantified separately from overall interrill 

erosion rates in rangeland field studies. Parsons et al. (1992, 1994) found the rainsplash 

erosion rate on Arizona rangelands was 0.01 to 0.04 g m-2 min-1 on grassland (73 to 

86 mm h-1 intensity) and 0.34 g m-2 min-1 on shrubland (145 mm h-1 intensity) during artificial rainfall experiments (see Wainwright et al. 2000). Rainsplash during the shrubland 

experiments eroded about 1.6 times more sediment from areas between plant canopies 

than from areas underneath plant canopies (Parsons et al. 1992). The Parsons et al. (1992, 

1994) and Wainwright et al. (1999) studies demonstrate the potential influence of cover 
USDA Forest Service RMRS-GTR-351. 2016. 51

on rainsplash erosion; however, the net effects vary with soil properties (see Bryan 2000; 

Kinnell 2005), cover amount/type (Gabet and Dunne 2003), and rainfall characteristics 

(Bryan 2000; Salles and Poesen 2000; Salles et al. 2000).

Cover Effects on Sheetflow Erosion

Canopy and ground cover reduce sheetflow erosion by controlling the water available for sediment transport and by recruiting surface roughness elements that disperse 

overland flow (Emmett 1970, 1978; Branson et al. 1981; Thurow et al. 1986; Seyfried 

1991; Abrahams et al. 1995; Wainwright et al. 2000; Pierson et al. 2002b, 2010, 2013; 

Williams et al. 2014a, 2015). Shallow sheetflow (fig. 9B) has little erosive energy, but 

is the primary transport mechanism for soil detached by raindrops or by other pre-event 

processes (such as freeze-thaw or weather) (Kinnell 1990, 2005). Progressively deeper 

flowpaths dampen the erosive energy of raindrops (Moss and Green 1983; Kinnell 1990, 

1991, 1993), but may exert enough shear stress on the soil surface to detach and entrain 

soil (Foster and Meyer 1972; Kinnell 2005). Collectively, rainsplash and sheetflow are 

primary conduits for hillslope sediment delivery except where concentrated flow (fig. 9C) 

or rills occur (Kinnell 2005). Higher infiltration rates and rainfall interception associated 

with cover elements reduce water availability for transport of eroded material (Blackburn 

1975; Branson et al. 1981; Abrahams et al. 1991; Blackburn et al. 1992; Pierson et al. 

1994a,b; Abrahams et al. 1995; Reid et al. 1999; Wainwright et al. 2000; Pierson et al. 

2008a, 2009, 2010; Williams et al. 2014a). Vegetation, litter, and rocks promote surface 

roughness, which dissipates the velocity and energy of runoff where it does occur 

(Emmett 1970, 1978; Seyfried 1991; Abrahams and Parsons 1994; Abrahams et al. 1995; 

Parsons et al. 1996; Wainwright et al. 2000; Pierson et al. 2002b, 2007a; Al-Hamdan et al. 

2012a, 2013). Reduced flow velocities have lower detachment and allow surface runoff 

to disperse and sediment to fall out of suspension. Ponding behind shrub mounds, grass 

clumps, and litter dams further dissipates rainsplash and facilitates deposition of sediment 

delivered from upslope runoff (Emmett 1970, 1978; Seyfried 1991). Within-event soil 

loss from well-vegetated areas is generally 2- to 10-fold less than that from sparsely covered or bare interspaces (table 3), but differences can exceed three orders of magnitude 

(Pierson et al. 1994b). Actual differences vary with cover, soil, rainfall, and topography 

characteristics. The net effect of cover on interrill processes can reduce rangeland withinstorm soil loss 8- to 10-fold across the plant (less than 1 m2) to patch (tens of square 

meters) scales (Pierson et al. 1994b, 2009) and, where cover exceeds 50 to 60 percent, 

results in minor hillslope soil loss (Gifford 1985; Pierson et al. 1994b, 2008a, 2009, 2010, 

2013; Williams et al. 2014a).

Cover Effects on Concentrated Flow Erosion

The effects of cover elements on concentrated flow erosion (fig. 9C) are similar to 

those in sheetflow erosion. The main effects are reduced runoff discharge, flow velocity, 

and sediment detachment (Emmett 1970, 1978; Branson et al. 1981; Thurow et al. 1986; 

Seyfried 1991; Abrahams et al. 1995; Wainwright et al. 2000; Pierson et al. 2007a, 2008a, 

2009; Al-Hamdan et al. 2012a,b, 2013; Williams et al. 2014a). Vegetation and ground 

cover reduce water available for concentrated flow formation and thereby decrease 
52 USDA Forest Service RMRS-GTR-351. 2016.

concentrated flow discharge (Pierson et al. 2007a, 2008a, 2009). Soil detachment by 

concentrated flow is well correlated with flow velocity (Pierson et al. 2008a, 2009) and 

discharge (Nearing et al. 1997, 1999; Govers et al. 2007; Al-Hamdan et al. 2012b), and 

flow velocity is strongly related to discharge (Govers 1992; Nearing et al. 1997, 1999; 

Giménez and Govers 2001; Govers et al. 2007; Al-Hamdan et al. 2012a). Grass clumps, 

plant bases, coppice mounds (fig. 16), and litter dams create topographic highs that may 

concentrate flow where runoff occurs, but concentrated flowpaths on well vegetated/

covered sites generally flow a short distance and disperse (Emmett 1970, 1978; Seyfried 

1991; Parsons et al. 1996; Bryan 2000; Wainwright et al. 2000).

The erosive energy and transport capacity of concentrated flow are greatly 

reduced when flow intersects ground cover elements (Al-Hamdan et al. 2012a,b, 2013). 

Roughness created by ground cover counteracts flow energy by amplifying hydraulic 

friction until the flow submerges the ground cover (Emmett 1970, 1978; Abrahams and 

Parsons 1991b; Abrahams and Parsons 1994; Abrahams et al. 1994, 1995; Parsons et al. 

1996; Nearing et al. 1997; Wainwright et al. 2000). Studies from a western juniper (J. 

occidentalis Hook.) woodland (Pierson et al. 2007a) and a mountain big sagebrush rangeland (Pierson et al. 2009) reported concentrated flow velocities that were 1.5- (woodland 

interspaces) to more than 2-fold (recently burned mountain big sagebrush) greater on 

degraded hillslopes with 80 percent bare ground than on adjacent hillslopes with 60 

percent and 20 percent bare ground, respectively. Sediment yield from concentrated flow 

processes was fourfold (Pierson et al. 2009) to eightfold (Pierson et al. 2007a) greater 

from the degraded sagebrush and woodland slopes. Sediment transported by concentrated 

flow where it does occur on well-vegetated sites often forms miniature alluvial fans adjacent to vegetative clumps (Emmett 1970, 1978; Seyfried 1991). These features indicate 

that concentrated flow does redistribute surface soil from bare areas to vegetated zones 

on healthy rangelands, but hillslope soil loss from this process is minor under such conditions (Pierson et al. 2007a, 2009). In contrast, concentrated flow becomes the dominant 

erosion mechanism on degraded rangelands where ground cover is sparse (Moffet et al. 

2007; Pierson et al. 2008a, 2009, 2011, 2013; Williams et al. 2014a,b).
USDA Forest Service RMRS-GTR-351. 2016. 53

Section 4: Impacts of Fire on Rangeland Runoff and 

Erosion

Fire Behavior and Regimes on Rangelands

The environmental effects of a particular fire or series of fires are often placed in the 

context of fire behavior, intensity, severity, and regime (DeBano et al. 1998; Shakesby 

and Doerr 2006; Brooks 2008; Keeley 2009). Terms explaining these relationships are 

frequently used inconsistently (Lentile et al. 2006; Keeley 2009), especially among 

nonfire-specific disciplines like hydrology. Therefore, we present a brief summary of the 

fire terms used here to discuss fire effects on rangeland hydrology. Fires are categorized 

as ground, surface, or crown type, and each is associated with a particular behavior 

(DeBano et al. 1998; Shakesby and Doerr 2006; Brooks 2008). Fire behavior refers to the 

rate of spread, residence time, and flame dimensions, and is related to fuel, weather, and 

topographic conditions at the time of burning (DeBano et al. 1998, Brooks 2008). Ground 

fires are mostly flame-free and burn slowly through duff or decayed organic matter on 

the soil surface. Surface fires burn rapidly and consume litter, woody dead material at 

or near the surface, herbaceous fuels, shrubs, and small trees. Crown fires burn rapidly 

through canopies of trees and tall shrubs, leaving most of the stem and land surface fuels 

unburned. An individual fire may comprise one or more of these three primary fire types 

(see DeBano et al. 1998).

The term “fire regime” refers to the pattern of repeated burning within a large spatial 

expanse (landscape scale) over long time periods and is defined by a characteristic combination of fire type, frequency, intensity, severity, size, and seasonality (Brooks 2008; 

Baker 2009). Fire frequency is the number of fires that occur over a specified period of 

time for a particular area, and may be expressed as a return interval/cycle or the length of 

time necessary for the area of interest to burn. Seasonality is the period of the year when 

fires are most likely to occur. Fire intensity refers to the amount of heat released. Severity 

is the degree of impact to soils or vegetation, or to both (see Keeley 2009).

Fire behavior, intensity, and severity are affected by the vertical and horizontal continuity and density of fuels. Fuels, as with fire types, are commonly divided vertically into 

layers termed “ground” (duff, roots, and buried or partially buried woody dead materials), 

“surface” (litter, herbaceous plants, and low shrubs), and “canopy” (tall shrubs and trees) 

fuels (DeBano et al. 1998). Extensive horizontal continuity of surface fuels, canopy fuels, 

or both, facilitates large fires, especially under dry and windy conditions. Breaks in fuel 

continuity retard fire progression. Rangeland fuels usually have low horizontal continuity 

of surface and canopy fuels—except on more productive sites or following long fire-free 

periods (Brooks 2008; Keane et al. 2008). The spread of fire from surface fuels to the 

canopy often requires ladder fuels (horizontally connected heterogeneous vertical continuity). Fire intensity is largely dictated by the amount or density of fuel, or both. Fuel 

density (amount of fuel per unit volume of space) influences combustion and the duration 

of burning. Loosely packed fuels provide sufficient air supply for higher combustion and 

rapid rates of spread relative to densely packed fuels (DeBano et al. 1998; Baker 2009). 

Fuel moisture conditions and temperature also influence fire intensity by regulating 
54 USDA Forest Service RMRS-GTR-351. 2016.

flammability and combustion. Dry, hot fuels exhibit higher flammability, combustion, and 

rates of spread than moist, cool fuels (DeBano et al. 1998; Baker 2009).

The variable most commonly referenced in assessing fire impacts on hydrology 

is severity (Pierson et al. 2001a, 2002b; Lewis et al. 2006; Shakesby and Doerr 2006; 

Pierson et al. 2008a, 2009; Parsons et al. 2010; Pierson et al. 2014; Williams et al. 

2014a,b), although it is not quantified consistently (Keeley 2009). In general, fire severity 

is a function of fire intensity and residence time (DeBano et al. 1998). Numerous severity 

classification systems exist, but three classes are common: low, moderate, and high 

severity (DeBano et al. 1998; Baker 2009; Parsons et al. 2010). Low-severity fires cause 

low soil heating (100 to 250 °C), light charring or minor reduction of litter, and virtually 

no consumption (but some charring) of duff. Moderate-severity fires char the ground 

surface without visible alteration of the mineral soil surface, leave behind some gray- to 

black-colored ash, consume litter and most woody debris (except logs), and have surface 

temperatures (up to 1 cm depth) of 300 to 400 °C. High-severity fires produce surface 

temperatures in excess of 500 °C, create deep ground charring where duff is completely 

consumed, visibly affect the upper mineral soil layer (leaving it reddish in color), and 

result in white ash from consumption of grasses, litter, and most shrub stems.

Wells et al. (1979) extended severity classification over large expanses based on 

total area burned at low, moderate, or high intensities. They suggested the following 

framework: (1) low-severity burn (less than 2 percent severely burned, less than 

15 percent moderately burned, remainder is unburned or burned at low severity); 

(2) moderate-severity burn (less than 10 percent severely burned, more than 15 percent 

burned moderately, remainder unburned or burned at low severity); and (3) high-severity 

burn (more than 10 percent with patches of high burn severity, more than 80 percent 

moderate to severely burned, remainder burned at low severity). Brown (2000) categorized fire regimes loosely related to recurring uniformity of fire severity over a specified 

area of interest. The categories are: (1) stand-replacement regime (lethal burning of 80 

percent or more of dominant vegetation), (2) understory fire regime (generally nonlethal 

to dominant vegetation), and (3) mixed-severity fire regime (recurring fire produces 

variable response in time and space, from nonlethal understory to stand-replacement fire). 

The uniform fine fuels on most grassland communities produce a stand-replacement fire 

regime (DeBano et al. 1998; Rice et al. 2008). These fires may be of high intensity, but 

generally cause only minor surface soil heating (100 to 400 °C) (Wright and Bailey 1982) 

due to the lack of woody fuels and low residence times (DeBano et al. 1998). In contrast, 

shrubland ecosystems may exhibit a mixed-severity or stand-replacement fire regime 

(Rice et al. 2008) and yield soil surface temperatures of 260 to 700 °C (Wright and Bailey 

1982). Parsons et al. (2010) provide guidance on field mapping of burn severity.

Fire Effects that Dictate Hydrologic Response

Reduced Interception and Surface Protection

Consumption of canopy and ground cover by fire reduces interception capacity and 

surface water retention and thus increases the quantity and intensity of water input at the 

soil surface and the flow volume and velocity across it (DeBano et al. 1998; Shakesby 

and Doerr 2006). The amount of additional water input made available by burning 
USDA Forest Service RMRS-GTR-351. 2016. 55

is dependent on the interception and storage capacity of the postburn cover. General 

estimates suggest that the quantity of interception by unburned rangeland trees, shrubs, 

and grasses approximates 1 to 2 mm of rainfall per storm (Bonan 2002) depending on the 

cover biomass, rainfall intensity and duration, cover moisture content, and the vertical 

and horizontal arrangements of cover elements (see Section 3, Vegetation and Cover 

Influences on Infiltration and Runoff Generation).

The conversion of interception loss (table 2) and stemflow rates to rainfall arrival at 

the soil surface is nearly 100 percent where severe burning uniformly removes all canopy 

and ground cover elements (fig. 18). Postfire reductions in raindrop dissipation (increases 

Figure 18—(A) Postfire landscape (3 months after wildfire) at the Denio Fire, Pine Mountain Range, Nevada, 

and cover removal by fire for (B) shrub coppice and (C) vegetated interspace experimental plots (0.5 m2) 

(photos: USDA Agricultural Research Service, Northwest Watershed Research Center).
56 USDA Forest Service RMRS-GTR-351. 2016.

in drop intensity) are as important as the increases in the quantity of water (Shakesby 

and Doerr 2006). Raindrop energy dictates splash sediment detachment under disturbed 

conditions whereas the quantity of overland flow and the downslope velocity govern flow 

detachment and transport capacity (Pierson et al. 2008a, 2009; Al-Hamdan et al. 2012b). 

Greater raindrop impact after canopy and ground cover removal results in increased soil 

detachment from rainsplash processes (Shakesby and Doerr 2006; Pierson et al. 2001a, 

2002b, 2008a, 2009, 2013, 2014; Williams et al. 2014a, 2016a). Reductions in ground 

cover (decreased surface roughness) abate surface retention of overland flow, allowing 

flow to concentrate and move downslope with greater velocity, erosive energy, and 

transport capacity (Shakesby and Doerr 2006; Pierson et al. 2008a, 2009; Al-Hamdan et 

al. 2012a,b, 2013; Pierson et al. 2013; Williams et al. 2014a, 2016a). The potential overall 

effect is a decrease in the time to runoff generation and an increase in cumulative runoff 

and sediment yield over the duration of a storm event.

In snow-dominated environments, removal of vegetation by fire may alter snow accumulation, the timing of runoff initiation, cessation, and peak flow within the year, and 

the amount of snowmelt runoff. Burning may also result in increased surface temperatures and snowmelt rates due to greater incoming solar radiation postburn (Tiedemann et 

al. 1979). Any reduction in vegetation, therefore, reduces snow accumulation and water 

availability for biological processes and streamflow generation. Reduced snow retention 

also potentially alters runoff characteristics from summer thunderstorms on water-limited 

sites by inhibiting vegetation production and ground cover recruitment. Where snow does 

accumulate, runoff responses to mid-winter rain-on-snow events may be substantial after 

burning (see Marks et al. 2001; Pierson et al. 2001b).

Physical, Chemical, and Biological Alteration of Soils

Hydrologically important soil properties (porosity, soil moisture, stability, structure, 

and water repellency) are strongly influenced by vegetation, organic debris, and microorganisms, which can be removed at varying degrees by burning (DeBano et al. 1998; 

Shakesby and Doerr 2006). The magnitude at which these properties are influenced by 

burning depends on the degree of soil heating and the amount of organic matter removed. 

The impact of burning on soils is at a maximum when the entire canopy and all surface 

organics are consumed and the mineral surface is exposed. The primary effect of fire 

relative to organic matter is to expedite the mineralization process. Postfire recovery of 

consumed organic matter may take as long as 5 years on some rangelands (Wright and 

Bailey 1982). Soil organic matter is combusted at temperatures above 200  ̊C and is 

completely consumed at 500  ̊C (DeBano et al. 1998). These temperatures are well within 

the range of surface temperatures commonly reported for grassland and shrubland fires 

(Wright and Bailey 1982; Miller et al. 2013). Subsurface soil temperatures on grasslands 

usually are unaffected by burning, but can range from approximately 100 to 250 °C 

to depths of 5 cm on shrublands (Wright and Bailey 1982; DeBano et al. 1998). The 

combustion of organic matter from surface and subsurface soils can alter soil structure, 

increase bulk density, and decrease porosity (Giovannini and Lucchesi 1997; Giovannini 

et al. 1988; Pierson et al. 2001a,b; Hubbert et al. 2006; Shakesby and Doerr 2006).

Soil stability and aggradation can also be reduced through alteration of soil particles 

during burning (DeBano et al. 1998; Neary et al. 1999; Andreu et al. 2001; Giovannini et 
USDA Forest Service RMRS-GTR-351. 2016. 57

al. 2001; Hubbert et al. 2006; Shakesby and Doerr 2006; Mataix-Solera et al. 2011). Soil 

temperatures between 150 and 400 °C can drive off hydroxyl groups in clays and increase 

erodibility (Giovannini and Lucchesi 1997; DeBano et al. 1998). Collectively, these soil 

alterations inhibit infiltration and promote runoff generation and erosion (Hester et al. 

1997; DeBano et al. 1998; Shakesby and Doerr 2006). Ash at the soil surface may clog 

surface soil pores and further accentuate the runoff response (Campbell et al. 1977; Wells 

et al. 1979; Lavee et al. 1995; Neary et al. 1999), although contrary results have been 

reported recently for the immediate postfire period (Cerdà and Doerr 2008; Woods and 

Balfour 2008; Larsen et al. 2009; Bodí et al. 2012; Ebel et al. 2012).

Burning may reduce the role of invertebrates, microorganisms, and mycorrhizae 

fungi in facilitating infiltration (Ahlgren and Ahlgren 1960; Wright and Bailey 1982; 

DeBano et al. 1998; Shakesby and Doerr 2006). Mycorrhizae and the by-products of soil 

fauna promote soil aggregation. Voids created by fauna movement within the soil profile 

increase porosity. Soil temperatures above 40 to 210 °C are fatal for most fungi and soil 

organisms; organic matter consumption by fire reduces the primary food source for soil 

fauna (Wright and Bailey 1982; DeBano et al. 1998; Mataix-Solera et al. 2009). Recovery 

of soil fauna and fungi may be rapid (Neary et al. 1999) depending on postfire soil microclimate and available nutrients, but can take as much as 3 to 5 years where resources are 

limited (Wright and Bailey 1982). Finally, soil moisture retention, a key component of 

plant and soil fauna productivity in water-limited ecosystems, is also adversely affected 

by the loss of pore structure and surface insulation (against evaporation) by litter (Wright 

and Bailey 1982; DeBano et al. 1998).

Exacerbation, Alteration, and Formation of Soil Water Repellency

Soil heating during burning may enhance, reduce, or create hydrophobic soil conditions (DeBano and Krammes 1966; DeBano et al. 1970; Savage 1974; DeBano et al. 

1976; DeBano 1981, 1991; Shakesby et al. 1993; Doerr et al. 1996; DeBano et al. 1998; 

DeBano 2000; Doerr et al. 2000; Robichaud 2000; Shakesby et al. 2000; BenavidesSolorio and MacDonald 2001; Huffman et al. 2001; Doerr et al. 2004; MacDonald and 

Huffman 2004; Doerr et al. 2006; Hubbert et al. 2006; Fox et al. 2007; Pierson et al. 

2008b; Arcenegui et al. 2008; Doerr et al. 2009; Shakesby 2011). The key determinants 

of whether soil water repellency is enhanced, reduced, or created during burning are the 

presence of organic matter and the soil temperature reached during burning (DeBano and 

Krammes 1966; DeBano et al. 1970; Doerr et al. 1996; DeBano et al. 1998; Doerr et al. 

2004, 2009). Naturally occurring soil water repellency (fig. 19) is typically unaltered by 

soil temperatures less than 175 °C (DeBano 1981). Soil temperatures between 175 and 

270 °C enhance “background” water repellency or may form hydrophobic soil conditions 

(DeBano 1981; Doerr et al. 2000, 2009). Water repellency breaks down or is destroyed 

at soil temperatures above 270 to 400 °C (Savage 1974; DeBano et al. 1976; Giovannini 

and Lucchesi 1997; Doerr et al. 2004).

During fires, combustion of organic matter at the soil surface radiates heat downward into the soil profile and vaporizes organic substances. Some of these substances 

are translocated downward along temperature gradients until they cool and condense, 

forming a variable-thickness hydrophobic layer parallel to the soil surface (DeBano 1981; 

Doerr et al. 1996; DeBano et al. 1998; DeBano 2000; Doerr et al. 2000, 2004, 2009). The 
58 USDA Forest Service RMRS-GTR-351. 2016.

depth at which the water-repellent layer occurs is related in part to the degree of heating 

or fire severity (Huffman et al. 2001). Generally, higher surface temperatures, up to that at 

which repellency is destroyed, increase the depth at which soil water repellency is found 

(DeBano et al. 1998). Fire-enhanced or fire-induced soil water repellency is commonly 

found at or within the first 5 cm of the soil surface, and rapidly decreases in strength with 

increasing soil depth (Benavides-Solorio and MacDonald 2001; Huffman et al. 2001; 

MacDonald and Huffman 2004; Benavides-Solorio and MacDonald 2005; Pierson et al. 

2008b, 2009).

The spatial and temporal persistence (figs. 19 and 20) of postburn soil water repellency are highly variable (Imeson et al. 1992; Doerr et al. 2000; Huffman et al. 2001; 

MacDonald and Huffman 2004; Hubbert et al. 2006; Woods et al. 2007; Pierson et al. 

2008b, 2009, 2013; Bodí et al. 2013; Williams et al. 2014b). The strength of postburn 

soil water repellency varies with the spatial continuity of the respective burn. Repellency 

strength is usually positively correlated with burn severity, the amount of organic material 

present during combustion, and the steepness of the downward soil temperature gradient 

during soil heating (DeBano et al. 1998). Steep temperature gradients enhance downward 

translocation (fig. 21). The steepness of the gradient is regulated in part by soil water 

content and its influence on heat transfer. The persistence of fire-induced soil water repellency commonly ranges from less than 1 to 6 years (DeBano et al. 1976; Huffman et al. 

2001; MacDonald and Huffman 2004).

The influence of repellency on infiltration is highly variable over seasonal and 

annual time scales (fig. 22) and is related to variations in soil moisture content (Shakesby 

et al. 1993; Burcar et al. 1994; Dekker and Ritsema 1994; Ritsema and Dekker 1994; 

Dekker and Ritsema 1996; Doerr et al. 2000; Shakesby et al. 2000; Benavides-Solorio 

and MacDonald 2001; Dekker et al. 2001; MacDonald and Huffman 2004; Hubbert et 

Figure 19—Dry soil underneath a 2- to 3-cm thick layer of water repellent soil 

observed immediately after application of 85 mm of rainfall (see Pierson et 

al. 2008b) over a 1-h period following the Breaks Prescribed Fire, Reynolds 

Creek Experimental Watershed, Idaho. Soils were strongly water repellent 

at the mineral soil surface and to a depth of 2 to 3 cm immediately before 

and after the prescribed fire (photo: USDA Agricultural Research Service, 

Northwest Watershed Research Center).
USDA Forest Service RMRS-GTR-351. 2016. 59

Figure 20—Spatial (by microsite) and 

annual variation in soil water repellency 

(measured by water drop penetration 

time, WDPT) measured on unburned 

and burned soils underneath shrubs 

and in interspaces areas at the Upper 

Sheep Creek Prescribed Burn site 

in the Reynolds Creek Experimental 

Watershed. Year 1 and year 2 

measurements are 1 and 2 years 

postfire, respectively. WDPT is an 

indicator of strength of soil water 

repellency as follows: <5 s wettable, 

5 to 60 s slightly repellent, 60 to 600 s 

strongly repellent (Bisdom et al. 1993).

Figure 21—Soil water repellency measured by using the water drop penetration time (WDPT) method on 

unburned and burned areas underneath Utah juniper and pinyon (Marking Corral site) and Utah juniper 

(Onaqui site) (see Pierson et al. 2010, 2014). WDPT is an indicator of strength of soil water repellency 

as follows: <5 s wettable, 5 to 60 s slightly repellent, 60 to 600 s strongly repellent (Bisdom et al. 1993). 

WDPTs at both sites indicate translocation of prefire repellency from the surface to deeper soil layers (~ 2 

to 4 cm) through the first year postfire. The soil water repellency profile 2 years postfire was similar to that 

of prefire conditions with stronger repellency at the mineral soil surface.
60 USDA Forest Service RMRS-GTR-351. 2016.

al. 2006; Pierson et al. 2008b; Bodí et al. 2013) and seasonal wetting and drying trends 

(Doerr and Thomas 2000; Dekker et al. 2001). The overall effect of preexisting or fireinduced soil water repellency is exacerbated by the removal of vegetation and ground 

cover (Benavides-Solorio and MacDonald 2001, 2002; Pierson et al. 2008b, 2009, 2013, 

2014; Williams et al. 2014a). The increased availability of water arriving at the soil 

surface, lack of surface protection, and presence of hydrophobic soil conditions promote 

runoff generation and surface soil erosion by raindrop-induced flow, sheetflow, and 

concentrated flow processes (DeBano and Krammes 1966; DeBano et al. 1979; Morris 

and Moses 1987; Scott and van Wyk 1990; Terry and Shakesby 1993; Inbar et al. 1997; 

DeBano 2000; Shakesby et al. 2000; Benavides-Solorio and MacDonald 2001, 2002, 

2005; Shakesby and Doerr 2006; Pierson et al. 2008b; Larsen et al. 2009; Pierson et al. 

2009, 2014; Williams et al. 2014a,b).

Figure 22—Temporal variability of soil water repellency (measured by using water 

drop penetration time, WDPT) effects on infiltration of artificial rainfall into unburned 

and burned, coarse-textured soils at two sagebrush sites: (A) Denio Wildfire, Pine 

Mountain Range, Nevada (Pierson et al. 2008a) and (B) Breaks Prescribed Fire, 

Reynolds Creek Experimental Watershed, Idaho (Pierson et al. 2009). WDPT is 

an indicator of strength of soil water repellency as follows: <5 s wettable, 5 to 60 s 

slightly repellent, 60 to 600 s strongly repellent (Bisdom et al. 1993).
USDA Forest Service RMRS-GTR-351. 2016. 61

Fire Effects on Infiltration and Runoff Generation

The degree to which fire affects infiltration and runoff processes depends on the 

magnitude of alterations to soil properties, vegetation, and ground cover (DeBano et 

al. 1998; Shakesby and Doerr 2006; Pierson et al. 2011; Williams et al. 2014b, 2016a). 

Runoff generation further depends on water arrival in excess of aboveground storage, 

surface storage, and infiltration. Thus, the rainfall intensity and duration as well as the 

conditions of the vegetative community and ground surface are key determinants of the 

runoff response (Benavides-Solorio and MacDonald 2005; Spigel and Robichaud 2007). 

Hydrologic response is further influenced by topographic attributes such as hillslope 

steepness (Al-Hamdan et al. 2013). The occurrence and hydrologic value of soil fauna, 

organic matter, macropores, and soil structure are closely related to the presence of vegetation and ground cover (Belnap et al. 2005), particularly in water-limited environments 

like rangelands (Ludwig et al. 1997, 2005). Therefore, many assessments of fire effects 

on infiltration and runoff consider alteration of vegetation, ground cover, and surface 

properties solely and exclude investigation of fire effects on soil organisms, macropores, 

and soil organic matter.

Literature clearly indicates that fire influences soil fauna, macropores, and soil 

organic matter (Wright and Bailey 1982; DeBano et al. 1998; Neary et al. 1999; MataixSolera et al. 2009; Certini et al. 2011; Mataix-Solera et al. 2011), but their respective 

alteration and direct relation to postfire hydrologic responses are rarely specifically 

measured or cited. Alteration of canopy, ground cover, and surface soil properties commonly serve as a surrogate for the collective fire impact and exhibit strong correlations 

with postfire hydrologic response (Benavides-Solorio and MacDonald 2001; Johansen et 

al. 2001; Benavides-Solorio and MacDonald 2005; Shakesby and Doerr 2006; Cerdà and 

Doerr 2008; Pierson et al. 2008a, 2009, 2013, 2014; Williams et al. 2014a,b). Vegetation 

and ground cover intercept rainfall and overland flow, surface roughness promotes 

ponding, and surface soil characteristics influence infiltration rates. Ponding delays runoff 

generation and allows water to infiltrate through breaks in hydrophobic soils or through 

macropores created by root channels, organic matter, or soil fauna. Organic matter input 

through plants and soil fauna promotes aggregate stability and infiltration by enhancing 

soil structure. From literature, three primary points emerge relative to these relationships: 

(1) canopy cover and surface protection are paramount in reducing water availability 

for runoff (Cerdà 1998a; Johansen et al. 2001; Pierson et al. 2001a; Benavides-Solorio 

and MacDonald 2005; Pierson et al. 2008a, 2009, 2013; Williams et al. 2014b); (2) the 

effects of decreased surface protection on water availability are markedly influenced 

by soil conditions (such as soil water repellency) that inhibit or promote infiltration 

and storage (Pierson et al. 2001a,b; Shakesby and Doerr 2006; Pierson et al. 2008a,b, 

2009, 2013, 2014; Williams et al. 2014a); and (3) the effects of decreased canopy cover, 

surface protection, or the co-occurrence of these effects, are intensified with increasing 

rainfall intensity (Inbar et al. 1998; Benavides-Solorio and MacDonald 2005; Spigel 

and Robichaud 2007; Larsen et al. 2009; Williams et al. 2014b) and hillslope angle (AlHamdan et al. 2013).
62 USDA Forest Service RMRS-GTR-351. 2016.

Rainsplash and Sheetflow Processes

Over the last decade, a number of researchers have measured fire effects on infiltration and runoff over small-plot scales (0.25 to 1 m2) (table 3) (Cerdà 1998a; Robichaud 

2000; Benavides-Solorio and MacDonald 2001; Pierson et al. 2001a; Benavidez-Solorio 

and MacDonald 2002; Pierson et al. 2002b; Cerdà and Doerr 2005; Groen and Woods 

2008; Pierson et al. 2008a,b; Woods and Balfour 2008; Pierson et al. 2009, 2013, 2014; 

Williams et al. 2014a,b, 2016a). Small-plot sizes limit inferences to rainsplash and 

sheetflow processes solely (Mutchler et al. 1988). These studies have, however, provided 

valuable insight into infiltration and runoff generation for both burned and unburned 

conditions, and elaborate on the magnitude of runoff response to burning. A series of 

rainfall simulation studies on small (0.5 m2) plots (Pierson et al. 2001a, 2002b, 2008a, 

2008b, 2009) (see table 3) on steeply sloped (35 to 60 percent) sagebrush rangelands 

demonstrate the effects of cover removal, surface alteration, and soil water repellency on 

postfire rangeland infiltration and runoff.

Pierson et al. (2002b) (see table 3) investigated the hydrologic effects of moderateand high-severity burning of sagebrush rangelands on north- and south-facing hillslopes 

1 year after the Eighth Street Fire in 1996 near Boise, Idaho. We restrict our discussion of 

the study to the south-facing hillslopes for brevity. Prefire total live and litter masses were 

32,519 kg ha-1 and 14,372 kg ha-1, respectively, on shrub coppices and 519 kg ha-1 and 

1,721 kg ha-1 in interspaces. Moderate- and high-severity burning reduced shrub coppice 

total live and litter mass by nearly 100 percent. Moderate burning of interspaces had no 

effect on total live mass, but reduced litter mass by 90 percent. High-severity burning of 

interspaces reduced total live and litter masses by 74 percent and 96 percent, respectively. 

Percent bare ground (see table 3) increased on shrub coppices from 7 percent prefire to 

nearly 100 percent for the moderate- and high-severity conditions. Interspace bare ground 

was high prefire (89 percent) and increased to nearly 100 percent following the burn. Soil 

organic matter (2 to 6 percent) was nearly equal across all plots and was not affected by 

burning. Near-surface bulk density (0 to 2 cm) was slightly higher on interspace plots 

(1.35 g cm-3) than on coppices (1.21 g cm-3) and was not significantly altered by burning. 

Gravimetric soil-water content ranged from 5 to 14 percent. Surface roughness decreased 

by 30 percent after moderate- and high-severity burning of coppice microsites and by 30 

and 45 percent after moderate- and high-severity burning, respectively, on interspaces.

Runoff in the Pierson et al. (2002b) study was measured during simulation of a 

summer season convective storm with an intensity of 67 mm h-1 and duration of 60 min. 

Runoff coefficients (runoff per unit of applied rainfall) from unburned hillslopes were 

11 percent for coppice areas and 24 percent for interspace areas. Runoff coefficients for 

coppices increased threefold following moderate- and high-severity burning. Runoff 

coefficients for interspaces were nearly equal (24 to 26 percent) for unburned and moderate-severity plots, but increased twofold to nearly 50 percent for high-severity burn plots. 

Greater infiltration and lower runoff on coppices prefire were attributed to interception 

and surface water retention associated with high live canopy and litter biomass. Runoff 

generally increased with the burn severity, potentially owing to enhanced background 

soil water repellency. Soil water repellency was not directly assessed, but the shape of 

the infiltration curves clearly indicates the presence of water repellency (steeply decreasing followed by gradual increase throughout simulation) (fig. 23) (see Meeuwig 1971; 
USDA Forest Service RMRS-GTR-351. 2016. 63

Imeson et al. 1992; Robichaud 2000; Pierson et al. 2001a, 2008b). Postfire increases in 

runoff were also associated with decreasing surface roughness.

A 3-year investigation by Pierson et al. (2001a, 2008a,b) (see table 3, figs. 22A and 

24) measured infiltration and runoff of rainsplash and sheetflow following the Denio Fire 

in 1999 in Nevada. The fire burned steeply sloping (30 to 40 percent) mountain big sagebrush at high severity. A convective-type storm was simulated by applying 85 mm h-1

rainfall intensity for 60 min to plots 0.5 m2 in size. Before the fire, total ground cover was 

nearly 100 percent in shrub coppice and interspace areas. Shrub canopy cover dominated 

in coppice areas whereas grasses dominated interspaces. Canopy cover was consumed 

entirely by the wildfire, and bare ground increased from less than 10 percent to more than 

95 percent. Ground cover recovered to about 60 percent (40 percent bare ground) following the second growing season, but remained significantly different from the unburned 

condition (90 percent). Shrub cover was slow to recover (5 percent after two growing 

seasons) and litter after the second growing season amassed 30 percent coverage.

Surface bulk densities (0 to 4 cm) were not significantly different between prefire 

coppice (0.93 g cm-3) and interspace (0.94 g cm-3) areas in the Pierson et al. (2001, 

2008a,b) studies. Burning increased bulk density (to 1.21 g cm-3) on both microsites, 

presumably by decreasing organic matter content (Pierson et al. 2001a), although organic 

matter was not specifically measured. Soil water repellency was strong on all unburned 

plots the year of the fire and was reduced more than 50 percent by high-severity burning 

on shrub coppice and interspace microsites (Pierson et al. 2008b). Soil water repellency 

across all plots (fig. 22A) decreased by 55 percent from the year of the fire (year 0) to 1 

year postfire (year 1) and then increased across all plots approximately 40 to 50 percent 

from year 1 to year 2 (2 years postfire). Runoff coefficients (table 3) were slightly 

greater, but not significantly different, for burned (37 percent) than unburned (30 percent) 

shrub coppices immediately postfire, and were significantly higher for the unburned (49 

percent) than burned (30 percent) interspaces.

Pierson et al. (2001, 2008a,b) explained that slightly greater runoff and significantly 

lower minimum infiltration on burned coppices resulted from the removal by fire of 

canopy and ground cover over strongly water-repellent soils. Canopy and litter cover 

on unburned coppices mitigated the effects of strong soil water repellency whereas 

the removal of cover accentuated the effects of the persistent, but reduced, soil water 

repellency on burned coppices (Pierson et al. 2008b). The decrease in runoff from 

Figure 23—Infiltration of artificial 

rainfall (67 mm h-1, 60 min) applied 

on burned (coppice – BC, interspace 

– BI) and unburned (coppice – 

UC, interspace – UI) sagebrush 

hillslopes following the Eighth Street 

Wildfire in 1996 near Boise, Idaho. 

Data from Pierson et al. (2002b).
64 USDA Forest Service RMRS-GTR-351. 2016.

interspace areas was associated with removal of water-shedding senescent vegetation 

and fire-reduced strength of soil water repellency. The influence of soil water repellency 

on the overall hydrologic response is shown by nearly equal runoff coefficients (10 to 

20 percent) and significantly reduced strength (by 55 percent) of soil water repellency 

in year 1 across all plots, regardless of differences in canopy and ground cover (Pierson 

et al. 2008a,b). A subsequent significant increase in soil water repellency across all 

plots in year 2 coincided with a twofold to threefold increase in runoff coefficients for 

burned interspaces and all coppices and the reestablishment of differences in minimum 

infiltration between burned and unburned coppices (Pierson et al. 2008a,b). In summary, 

canopy and ground cover removal dictated water availability whereas the strength of soil 

water repellency exerted greater influence on infiltration processes and runoff generation 

(Pierson et al. 2008b).

Pierson et al. (2008b, 2009) (table 3, figs. 22B and 25) measured infiltration and 

runoff from rainfall simulations on small (0.5 m2) plots on burned and unburned mountain big sagebrush rangeland (35 to 50 percent slopes) the year of, and 1 year following 

the Breaks Prescribed Fire in the Reynolds Creek Experimental Watershed near Boise, 

Idaho. A convective storm was simulated by applying 85 mm h-1 over a 60-min duration. 

Figure 24—(A) The Denio Fire (wildfire), 1999, Pine Mountain Range, Nevada, (B) rainfall 

simulations, and (C) 0.5 m plots used in rainfall simulation studies at the site (Pierson et 

al. 2001a, 2008a,b) (photos: USDA Agricultural Research Service, Northwest Watershed 

Research Center).
USDA Forest Service RMRS-GTR-351. 2016. 65

Canopy cover prefire was 84 percent on shrub coppices (almost all as shrub cover) and 

31 percent on interspaces (22 percent grass). Ground cover was composed almost entirely 

of litter and totaled 75 percent for unburned interspaces and 99 percent for unburned 

shrub coppices. The fire reduced canopy cover to 10 percent on coppices and 0 percent 

on interspaces. Litter cover was reduced to 36 percent and 14 percent for coppices and 

interspaces, respectively. After one growing season (year 1), total canopy cover increased 

to 40 percent (29 percent forb, 3 percent grass) on burned coppices and 63 percent 

(40 percent forb, 22 percent grass) on burned interspaces. Total ground cover in year 1 

was 22 percent (15 percent litter) on burned coppices and 32 percent (26 percent litter) on 

burned interspaces.

Bulk densities (0 to 2 cm) in the Pierson et al. (2009) study were equal (1.13 g cm-3) 

on coppice and interspace microsites and were not significantly changed by burning. 

Soil water repellency was strong and nearly equal on coppice microsites for burned and 

unburned conditions the year of the fire (year 0). The strength of soil water repellency 

was 55 to 60 percent less on burned and unburned interspaces than on coppices in year 

0, but was strong. Soil water repellency was greatly reduced (moderately strong) and 

nearly equal across all plots in year 1 (fig. 22B). Canopy and ground cover removal and 

strong soil water repellency on burned coppice plots generated significant decreases in 

infiltration and increases in runoff postfire (Pierson et al. 2009). Minimum infiltration 

decreased 60 percent and runoff doubled on coppice microsites immediately postfire (runoff coefficient of 76 percent). Runoff coefficients were greater for unburned interspaces 

(63 percent) than for coppices (39 percent) even though soil water repellency was twofold 

to threefold greater on coppices. Vegetation and ground cover mitigated soil water repellency on unburned coppices.

The low cover on unburned interspaces and the presence of strong soil water 

repellency facilitated runoff generation. Burning reduced cover on interspace microsites, 

but did not increase runoff generation relative to the unburned condition. A significant decrease (by 70 percent) in soil water repellency on burned and unburned coppices between 

year 0 and year 1 and the nearly uniform moderate soil water repellency across all plots 

resulted in a 75 to 90 percent decrease in cumulative runoff. Runoff coefficients in year 1 

were 8 to 10 percent across all plots regardless of cover. Total ground cover in year 1 was 

significantly less on burned plots (27 percent) than on unburned plots (73 percent) and 

canopy cover was significantly less on burned (40 percent) than unburned (84 percent) 

coppices. As with the Denio Fire study (Pierson et al. 2001a, 2008a,b), cover influenced 

water availability, but the strength of soil water repellency exerted a greater influence 

on infiltration (fig. 22B) and runoff generation (table 3). That is, cover influenced the 

quantity of water available for runoff generation and soil water repellency, and along with 

other soil factors, governed the rate of infiltration for available surface water.

The collective studies by Pierson et al. (2001a, 2002b, 2008a,b, 2009) illustrate the 

complexity of rainfall-runoff processes on burned and unburned rangelands and are supported by other recent woodland and well-cited semiarid forested studies (Cerdà 1998a; 

Benavides-Solorio and MacDonald 2001, 2002; Pierson et al. 2013, 2014; Williams et 

al. 2014a). Recent small-plot scale investigations at a gently sloping western juniper 

woodland in Idaho found that severe burning had minimal effect on runoff from mostly 

bare interspaces and decadent shrub coppices, but fire-induced litter removal on tree coppices increased runoff of simulated rainfall by twofold to threefold 1 and 2 years postfire 
66 USDA Forest Service RMRS-GTR-351. 2016.

(table 3; Pierson et al. 2013; Williams et al. 2014a). The wildfire reduced tree coppice 

litter cover by a factor of eight, from 98 to 12 percent, and soils underneath tree canopies 

were strongly water repellent prefire and postfire. Soils were wettable in interspaces and 

underneath shrubs before and after burning. Pierson et al. (2014) reported contrasting 

fire impacts on runoff responses to simulated high-intensity storms 1 and 2 years after 

low- to moderate-severity prescribed burns on degraded singleleaf pinyon (P. monophylla

Torr. & Frém.)/Utah juniper (Marking Corral site, Nevada) and Utah juniper (Onaqui site, 

Utah) woodlands (table 3). Burning at both sites had minimal impact on runoff generation 

from degraded interspaces (table 3). The prescribed burn at the more degraded woodland, 

Onaqui, did not significantly reduce litter depths over the strongly water-repellent 

soils on tree coppices and resulted in no significant fire effect on runoff generation. In 

contrast, burning at the less degraded site, Marking Corral, reduced tree coppice litter 

depth twofold, from 40 to 23 mm, and increased runoff coefficients from 0 to 15 and 

28 percent for storms of 64 mm h-1 and 102 mm h-1, respectively (Pierson et al. 2014). 

Soil water repellency was strong before and after burning on tree coppices at both sites 

(Pierson et al. 2014). The contrast in runoff responses to burning across the two sites was 

attributed to greater tree litter removal at the Marking Corral site on persistent strongly 

water-repellent soils (Pierson et al. 2014). The lack of fire effects on runoff generation 

from interspaces and shrub coppices at the sites was attributed to the overall degraded 

conditions of interspaces before burning and the minimal impact of the moderate-severity 

fire on ground cover and soil properties underneath shrub canopies (Pierson et al. 2014).

Benavides-Solorio and MacDonald (2001, 2002) (table 3) measured runoff from 

burned and unburned areas of a ponderosa pine forest in the Colorado Front Range, 

Colorado. A simulated convective rainstorm applied 80 mm h-1 of rainfall for 60 min 

to 1.0 m2 plots with unburned and varying burned severity conditions. Although the 

study investigated three fire sites, we focus on the primary site, the Bobcat Fire, because 

only two replicates existed for each burn severity at other sites (Benavides-Solorio 

and MacDonald 2001, 2002). Percent ground cover by burn severity class was 23 

percent high-severity, 88 percent moderate-severity, and 99 percent low-severity and 

unburned conditions. Slopes averaged 22 to 31 percent and soil moisture averaged 1.0 to 

2.0 percent. Runoff coefficients were 66 percent for the high-severity plots, 58 percent 

for moderate-severity plots, and 55 percent for the low-severity and unburned plots. Soils 

were strongly water-repellent near the surface and there was very little variation in the 

strength of soil water repellency with burn severity. Correlations in runoff and soil water 

repellency were not separated for the multiple fires studied, but when all fires were considered, runoff from high-severity plots was well correlated (r2 = 0.81) with the strength 

of natural or fire-enhanced soil water repellency. Runoff was not well correlated with 

percent slope or percent bare ground. Benavides-Solorio and MacDonald (2001, 2002) 

concluded soil water repellency and soil moisture, as a controller of repellency strength, 

were the primary controls on the amount of runoff generated.

Cerdà (1998a) used rainfall simulation to study the hydrologic impacts of burning 

on moderately steep (25 percent) slopes within a Mediterranean scrubland plant community in southeastern Spain. A simulator applied 55 mm h-1 of rainfall to 0.25 m2 plots 7, 

18, 29, and 64 months after a wildfire. The site burned at high intensity, and the fire consumed the entire litter layer. Organic matter, soil porosity, and bulk density were similar 

across all plots. Ash cover postfire was 3 to 5 cm deep and continuous, but was removed 
USDA Forest Service RMRS-GTR-351. 2016. 67

by autumn rains before simulation. Total ground cover was about 31 percent during the 

first year of simulations and was well established (74 percent) within 18 months. Time 

to ponding gradually increased with vegetative recovery from 2 min 17 sec the year of 

the fire to 15 min 35 sec 5.5 years postfire. Time to runoff increased over the same time 

period from 3 min 47 sec to 25 min 30 sec. The runoff coefficient was 45 percent the year 

of the fire, decreased to 14 percent within the first 3 years, and was 6 percent within 5.5 

years postfire. The spatial variability in runoff tracked with spatial variability in vegetative recovery. Cerdà (1998a) found that the relationship between cover and runoff was 

negative and exponential, as reported for erosion by Johansen et al. (2001) and Pierson 

et al. (2008a, 2009). Runoff was greatly diminished when plant cover recovered to 50 to 

60 percent, the third winter following the burn, and approximated that of other, unburned 

Mediterranean scrub 5.5 years postfire.

In another forested study, Woods and Balfour (2008) measured runoff from ash- and 

nonash-covered plots following high-severity wildfire. Rainfall was applied to 0.5 m2

plots at 75 mm h-1 intensity for 1 hour. The study found that the ash layer provided 

1.5 cm of water storage capacity and protected the soil surface from sealing in the immediate postfire period. Time to ponding was 12 min longer and cumulative infiltration was 

2.0 cm greater on ash than on ash-free plots. Nine months after the fire, ash and ash-free 

plots exhibited similar runoff behavior. Similar ash cover and runoff relationships have 

been reported in studies by Cerdà and Doerr (2008), Larsen et al. (2009), and Ebel et al. 

(2012). Larsen et al. (2009) and Onda et al. (2008) indicate, however, that the positive ash 

and infiltration relationships are likely short lived and that soil sealing following winnowing of ash particles may promote runoff, especially where soil water repellency occurs.

Hillslope- to Watershed-Scale Runoff

Fire effects on runoff generation over large-plot (tens of meters) to hillslope scales 

is commonly less than observed at small-plot scales due to spatially variable cover 

and surface soil conditions (Shakesby and Doerr 2006; Pierson et al. 2009, 2011). This 

relationship is illustrated in the aforementioned Pierson et al. (2009) (table 3) study. In 

addition to small plots, the study measured runoff from large plots (32.5 m2) (fig. 25B) 

in burned and unburned shrub steppe. Runoff coefficients from a simulated convective 

storm (85 mm h-1, 60 min) were 27 percent for burned plots and 4 percent for unburned 

plots (table 3). Mean runoff coefficients from the same storm on burned and unburned 

small plots (0.5 m2) were 2- and more than 10-fold greater, respectively, than on the 

large plots (table 3). The decreased runoff from small- to large-plot scales was attributed 

to greater spatial variability in infiltration at the large- versus small-plot scale. Although 

runoff declined with increasing scale, burned large plots still generated nearly sevenfold 

more runoff than unburned large plots. Greater runoff from the burned than unburned 

condition was attributed to the uniform threefold reduction in ground cover, 100 percent 

reduction in canopy cover, persistence of strong soil water repellency after burning, and 

formation of high-velocity concentrated flowpaths on burned plots. These conditions 

created more uniform surface hydrologic connectivity on burned than unburned plots 

(fig. 25A). Runoff coefficients from all plots were positively correlated with soil water 

repellency strength (r2 = 0.56) and percent bare ground (r2 = 0.32). Concentrated flow 

experiments in the same study (fig. 26) found that cumulative runoff from consecutive 
68 USDA Forest Service RMRS-GTR-351. 2016.

12-min releases of 7, 12, 15, and 21 L min-1 of concentrated flow were 406 L on burned 

plots and 144 L on unburned plots. Runoff from small, large, and concentrated-flow 

burned plots was equivalent to that of unburned plots after ground cover recovered to 30 

to 40 percent one growing season postfire. The return to prefire runoff rates was at least 

partially related to a 70 percent reduction in strength (from strong to moderate) of soil 

water repellency.

Figure 25—(A) The Breaks Prescribed Burn, Reynolds Creek Experimental Watershed, Idaho and (B) large-plot (32.5 m2) rainfall simulations 

conducted at the site by Pierson et al. (2009) (photos: USDA Agricultural Research Service, Northwest Watershed Research Center).

Figure 26—Concentrated flow 

experiments conducted by Pierson 

et al. (2009) immediately following 

the Breaks Prescribed Fire, 

Reynolds Creek Experimental 

Watershed, Idaho. Green dye in 

flowpath is a visual tracer used 

to show concentrated flowpath 

formation and direction. Flows 

were released at specified rates 

(7, 12, 15, and 21 L min-1) for 12-

min intervals each (photo: USDA 

Agricultural Research Service, 

Northwest Watershed Research 

Center).
USDA Forest Service RMRS-GTR-351. 2016. 69

In another mountain big sagebrush study, Pierson et al. (2008a) reported a 35-fold 

difference in runoff between high-severity burned (178 L) and unburned (5 L) plots from 

consecutive 12-min concentrated flow releases of 7, 12, and 15 L min-1. Runoff from 

small plots and concentrated flow experiments in that study returned to preburn levels 

after ground cover increased to about 40 percent and 60 percent, respectively, and soil 

water repellency was reduced to moderate levels. At a western juniper woodland in Idaho, 

Pierson et al. (2013) and Williams et al. (2014a) found runoff ratios during simulated 

64 mm h-1 and 102 mm h-1 intensity rainstorms (45 min, 13 m2 plots) on tree coppices 

increased ninefold and fourfold, respectively, 1 year after a high-severity wildfire 

(table 3). The increased runoff from tree coppices following the fire occurred due to a 

threefold reduction of litter cover, a reduction of more than 4 to 5 cm in litter depth, and 

persistence of strongly water-repellent soils postfire (Pierson et al. 2013; Williams et al. 

2014a). Burning had no effect on runoff generation from the degraded intercanopy (more 

than 80 percent bare soil and rock) at the site the first year after burning.

In a semiarid forest setting in New Mexico, Johansen et al. (2001) (table 3) reported 

that runoff from large-plot (32 m2) rainfall simulations on burned and unburned plots was 

positively correlated with percent bare soil (r = 0.76), and that the time to runoff generation was negatively correlated with percent bare soil (r = -0.67). Application of 120 

mm of rainfall over 2 simulation hours generated mean runoff coefficients of 45 and 23 

percent for burned and unburned conditions, respectively (table 3). Mean ground cover 

was 26 percent for burned plots and 52 percent for unburned plots. Soil water repellency 

was highly variable in space and strength and had minimal effect on runoff generation.

Historical hillslope-scale studies from chaparral communities (see review by 

Shakesby and Doerr 2006) are consistent with the semiarid shrub steppe, woodland, and 

forested studies by Pierson et al. (2009, 2013), Williams et al. (2014a), and Johansen et 

al. (2001). The effects of fire on runoff from rangelands at the watershed scale are limited. Overall, at the watershed scale, peak discharge rather than cumulative runoff tends 

to be greater after burning, and is most pronounced after short-duration, high-intensity, 

convective thunderstorms over large expanses of severely burned landscapes (Shakesby 

and Doerr 2006).

Fire Effects on Soil Erosion by Water

Rainsplash and Sheetflow Processes

Higher erosion rates following fire are commonly attributed to decreased aggregate 

stability, increased surface exposure to raindrop impact, reduced energy dissipation of 

overland flow, and greater surface runoff and overland flow velocity. Greater surface 

vulnerability and maximized raindrop energy amplify sediment detachment by rainsplash 

processes. Greater water availability and flow velocity provide more efficient downslope 

transport and overland flow detachment. Reduced aggregate stability, where it occurs, 

magnifies the overall response. The previously mentioned small-plot studies in Nevada 

and Idaho by Pierson et al. (2001a, 2002b, 2008a, 2009, 2013, 2014) and in the Colorado 

Front Range by Benavides-Solorio and MacDonald (2001, 2002) provide estimates 

of postfire erosion increases due to rainsplash and sheetflow processes. Pierson et al. 

(2002b) (table 3) reported that the more than 90 percent reduction in litter biomass and 70 
70 USDA Forest Service RMRS-GTR-351. 2016.

percent mean reduction in total live biomass 1 year after moderate and severe burning of 

south-facing sagebrush hillslopes increased soil erosion by factors of 7 (21 g m-2) and 28 

(85 g m-2), respectively. Soil erosion postfire was most pronounced on severely burned 

interspace plots (148 g m-2) due to a more than 40 percent reduction in surface roughness. 

Erosion from severely burned shrub coppice plots was 22 g m-2. Sediment yield from all 

plots in the study was negatively correlated with litter biomass (r = -0.59), total ground 

cover (r = -0.59), and total canopy cover (r = -0.56).

Pierson et al. (2001a, 2008a) (table 3; fig. 24) measured a threefold increase in 

soil erosion from shrub coppice plots (41 g m-2 burned, 12 g m-2 unburned) after fire 

consumed nearly 100 percent of canopy and ground cover. Similar bare ground postfire 

on burned interspaces generated half the erosion rate that was measured on burned shrub 

coppices and produced similar erosion to prefire conditions. The differing responses 

were attributed to a more erodible surface, slightly greater runoff, and persistent soil 

water repellency on shrub coppices after burning. Erosion 1 year postfire was greatly 

reduced across all plots and was similar for burned and unburned conditions. Two years 

postfire, burned shrub coppices generated 3- to 14-fold more erosion than any other plot, 

burned or unburned. Soil water repellency, time to peak runoff, and minimum infiltration 

were the only other variables that exhibited the same temporal trend, implicating runoff 

generation and continued greater erodibility as the causal factors.

Pierson et al. (2009) found that 90 percent and 40 percent reductions in canopy and 

ground cover increased sediment yield from 17 g m-2 on unburned shrub coppices (80 

to 90 percent cover) to 183 g m-2 postfire. Fire-caused reductions of 100 percent canopy 

and 80 percent ground cover on interspaces (31 percent and 75 percent canopy and 

ground cover prefire) increased sediment yield from 195 g m-2 to 705 g m-2. Fire-induced 

increases in erosion on shrub coppices were attributed to greater runoff postfire whereas 

significantly increased erodibility, rather than runoff, explained the postfire increase in 

erosion from interspaces.

In woodland studies in southwestern Idaho, Pierson et al. (2013) and Williams et 

al. (2014a) reported that reductions of more than 80 percent of litter cover and 4 to 5 cm 

litter depth from tree coppices amplified erosion from small-plot rainfall simulations 

(102 mm h-1, 45 min, 0.5 m2) by 18- to 34-fold the first 2 years after severe wildfire 

(table 3). In the same studies, more than 80 percent reductions in canopy and litter cover 

on shrub coppices increased erosion from simulated storms more than 20-fold 1 year 

postfire. Two years postfire, erosion remained elevated on shrub coppice plots, but the 

difference in erosion between burned and unburned treatments was not significant. Slight 

fire-induced reductions in interspace grass canopy cover (from 15 to 7 percent) at the 

site 1 year postfire resulted in a fourfold increase in small-plot scale erosion from burned 

interspaces. As with shrub coppices, erosion from burned and unburned interspaces was 

not significantly different 2 years postfire.

Pierson et al. (2014) cited site-specific differences in soil erodibility as the primary 

driver for contrasting erosion rates from simulated rainfall at two woodland sites 1 and 2 

years following prescribed fire (table 3). Simulated high-intensity rainfall (102 mm h-1, 

45 min, 0.5 m2) generated amplified soil erosion from tree coppices at the less erodible 

site (46 to 75 g m-2), but the elevated postfire erosion rates were minor relative to those 

of burned tree coppices at the more highly erodible site (242 to 294 g m-2). Runoff rates 

from burned tree coppices were similar for the two sites (table 3).
USDA Forest Service RMRS-GTR-351. 2016. 71

Benavides-Solorio (2001, 2002; table 3) reported that sediment yield from moderate- and high-severity burned semiarid forested areas were 2- and 16-fold higher than 

from plots burned at low severity or unburned. Percent bare soil (table 3) explained 79 

percent of the variability in erosion from all plots, and soil water repellency explained 43 

percent of the variability in erosion from plots burned at high severity.

As with runoff, the postfire erosion response appears closely tied to alteration of 

cover. A secondary contributing factor appears to be soil water repellency, owing to its 

influence on infiltration and on runoff generation. In each of the studies discussed above, 

rainfall intensity was held constant. Runoff and erosion both exhibit some dependence 

on rainfall intensity as a driving force, and responses may be amplified or dampened by 

respective increases or decreases in the rainfall rate (Pierson et al. 2011; Williams et al. 

2014b).

Concentrated Flow Processes

Concentrated flowpaths rarely occur on undisturbed rangelands, but often become 

the dominant conduit for overland flow and sediment transport after burning (Moffet et 

al. 2007; Pierson et al. 2009; Williams et al. 2014b, 2016a). Following burning, greater 

water availability, decreased infiltration, and reduced surface obstructions facilitate 

formation of concentrated flowpaths. These relationships are enhanced on steep slopes 

and where overland flow is promoted by soil water repellency (Shakesby and Doerr 2006; 

Moffet et al. 2007; Pierson et al. 2009; Williams et al. 2014a,b). Concentrated flowpaths 

have greater flow depth, velocity, erosive energy, and transport capacity than sheetflow 

(Moffet et al. 2007; Pierson et al. 2008a, 2009). The velocity and erosive energy are 

a function of the soil grain and form roughness, the eroded flowpath, ground cover, 

hillslope angle, and flow discharge (Moffet et al. 2007; Al-Hamdan et al. 2012a,b, 2013).

Pierson et al. (2008a, 2009) (figs. 24, 25, and 26) measured the velocity of simulated 

concentrated flowpaths under burned and unburned conditions on sagebrush rangelands 

in Idaho and Nevada. In both studies velocity over a range of flow rates was positively 

correlated (r2 = 0.59 to 0.70) with and exponentially related to percent bare ground. 

Velocity decreased non-linearly with decreasing bare ground as vegetation recovered in 

the years after burning. Sharp increases in velocity were observed where bare ground 

exceeded 50 to 60 percent. Pierson et al. (2009) (table 3) measured increasing erosion 

with increasing plot size after burning of sagebrush hillslopes. They attributed the positive relationship to a switch in the dominant erosion process from rainsplash-sheetflow 

to concentrated flow following burning. In the study by Pierson et al. (2009), erosion for 

unburned conditions was greater from small plots (rainsplash-sheetflow) than large plots. 

Following burning, erosion was greater on the larger plots, and the maximum number of 

concentrated flowpaths increased from zero for unburned to five for burned large plots. 

More uniform bare soil conditions, strongly water-repellent soils, and greater hydrologic 

connectivity after fire contributed to rapid (3 min) runoff generation and formation of 

concentrated flow. Erosion increased from 8 g m-2 for unburned conditions to 988 g m-2

postburn (table 3). Large-plot sediment yield remained greater for burned conditions 

until vegetation recovered to nearly 60 percent two growing seasons postfire (fig. 27). No 

concentrated flowpaths were observed in burned plots after the second growing season.
72 USDA Forest Service RMRS-GTR-351. 2016.

Williams et al. (2014a) and Pierson et al. (2013) also reported a shift from rainsplash and sheetflow to concentrated flow as the dominant erosion process occurring on 

13 m2 rainfall simulation plots following burning of a western juniper woodland (table 3). 

Erosion from burned tree coppices increased exponentially with increasing runoff postfire 

due to the formation of high-velocity concentrated flow paths (fig. 28). Pierson et al. 

(2009) used simulated consecutive 12 min concentrated flow releases of 7, 12, 15, and 

21 L min-1 to quantify erosion solely from concentrated flow processes in unburned and 

burned areas of sagebrush rangeland. The cumulative flow releases generated 14,363 g 

of sediment immediately postfire and 2,420 g under unburned conditions prefire. Pierson 

et al. (2008a) conducted the same concentrated flow experiments as Pierson et al. (2009) 

using flow rates of 7, 12, and 15 L min-1 and measured 17,775 g of sediment immediately 

following burning and less than 10 g on unburned plots. In both studies, erosion from the 

respective simulated concentrated flow rates on burned plots approached that of unburned 

plots once ground cover recovered to 60 percent or greater. The large-plot results from 

Pierson et al. (2009, 2013) and Williams et al. (2014a) illustrate the profound influence 

that concentrated flow processes have on postfire erosion (table 3). The simulated concentrated flow experiments (Pierson et al. 2008a, 2009) demonstrate the erosive potential of 

high-velocity concentrated flowpaths on burned rangelands.

Figure 27—Erosion reported as 

sediment per unit of runoff from 

large-plot (32.5 m2) rainfall 

simulations conducted on 

unburned and burned conditions 

at the Breaks Prescribed Fire, 

Reynolds Creek Experimental 

Watershed, Idaho (Pierson et al. 

2009).

Figure 28—Cumulative sediment 

yield versus runoff from rainfall 

simulations (102 mm h-1, 45 min) 

on unburned and burned tree 

coppice and intercanopy (areas 

between tree coppices) plots (13 

m2) in a western juniper woodland 

(Pierson et al. 2013; Williams et al. 

2014a). 
USDA Forest Service RMRS-GTR-351. 2016. 73

Hillslope- to Watershed-Scale Erosion

Erosion at hillslope to watershed scales is largely dependent on the spatial arrangement of burn severity, bare soil exposure, water-repellent soil conditions, and 

rainfall intensity (Shakesby and Doerr 2006). Very few large-scale erosion studies have 

been completed on burned rangelands. Therefore insight into large-scale fire effects on 

rangeland hydrology comes from studies of dry or semiarid forested sites and the limited 

number of hillslope-scale studies for shrub steppe, woodland, and chaparral communities. 

Benavides-Solorio and MacDonald (2005) used silt fences to measure (see Robichaud 

and Brown 2002) postfire erosion on moderate to steep, semiarid forest slopes (25 to 

45 percent) in the Colorado Front Range for multiple fires of varying ages and severities. Contributing areas for the silt fences ranged from 190 to 6,600 m2 and averaged 

1,250 m2. Over the 2-year study, percent bare soil explained about 64 percent of the variability in soil erosion across all plots (n = 48). Sediment yield decreased exponentially 

with time after burning, and was highest where bare soil was equal to or greater than 60 

percent. After a high-intensity storm, however, extensive concentrated flow networks and 

erosion were observed on slopes with 70 to 85 percent ground cover of tree needles (15 

to 30 percent bare). Benavides-Solorio and MacDonald (2005) attributed the result to the 

high storm erosivity and ground cover type. Soil water repellency was present at least 

at slight strength on most plots and was moderately strong on some of the high-severity 

burns. As a result, soil water repellency was weakly correlated with sediment production 

from all plots (r2 = 0.30), but was more strongly correlated for the high-severity plots 

(r2 = 0.40). About 90 percent of the sediment collected during the study was delivered 

by high-intensity convective storms whereas 10 percent resulted from frontal rainfall 

or snowmelt. Concentrated flow formation played an important role in postfire erosion 

rates, particularly in converging topographic positions. Overall sediment yield was well 

correlated (r2 = 0.77) with a five-parameter empirical model of percent bare soil, rainfall 

erosivity, fire severity, soil water repellency (1 cm depth), and the 84th percentile sediment grain size. Percent bare soil and rainfall erosivity collectively explained 62 percent 

of sediment production variability.

A large-plot (32.5 m2) rainfall simulation study of recently burned and unburned 

rangeland in southwestern Idaho by Pierson et al. (2009) found soil water repellency and 

sediment yield were moderately correlated (r2 = 0.46) whereas runoff coefficients (table 

3) were more strongly correlated with soil water repellency (r2 = 0.56) and weakly correlated with bare ground (r2 = 0.32). Sediment yield and repellency in the Pierson et al. 

(2009) study was positively correlated with runoff coefficients (r2 = 0.83) and with percent bare ground (r2 = 0.76). These correlations suggest that sediment yield in the study 

by Pierson et al. (2009) was dependent on runoff generation and bare soil whereas runoff 

was more dependent on water-repellent soil conditions in bare areas. The low correlation 

in sediment yield and repellency in the Benavides-Solorio and MacDonald (2005) study 

indicates that either the strength of soil water repellency was not significant enough 

to influence erosion or simply other factors like rainfall intensity or topography and 

extensive bare ground exerted more influence on erosion processes. Soil water repellency 

in the contrasting Pierson et al. (2009) research was strong at the soil surface immediately 

postfire and deteriorated to slight by the end of the 3-year study. Soil water repellency 

was much weaker at the sites studied by Benavides-Solorio and MacDonald (2005) and 
74 USDA Forest Service RMRS-GTR-351. 2016.

showed a general decreasing trend through the study. In a gently sloping (5 to 7 percent) 

semiarid forest setting in New Mexico, Johansen et al. (2001) (table 3) found erosion 

from high-severity burned large plots (32.5 m2) was 25-fold greater than measured from 

unburned plots of the same size. Sediment yield was strongly correlated with percent bare 

soil (r = 0.84), and soil water repellency was considered slight. The studies highlighted 

here illustrate the influence of ground cover and bare ground on hillslope-scale postfire 

erosion response over a range of settings and slopes and demonstrate how soil water 

repellency may magnify those effects.

Large-scale alteration of surface roughness, canopy, and ground cover on rangeland 

soils can trigger flash flooding and mass erosion events where superimposed on steeply 

sloping water-repellent hillslopes. These events have received less attention in literature 

for rangelands than for forested settings. One year after the Eighth Street Fire (6,070 ha) 

in 1996 near Boise, Idaho, a 5- to 10-year return period convective storm (~67 mm h-1) 

of 9-min duration on steeply sloped, severely burned sagebrush caused flash flooding 

and mud flows in the city of Boise (Pierson et al. 2002b). Pierson et al. (2002b) (table 3) 

conducted rainfall simulations (67 mm h-1) at the site preceding the storm and determined 

that elevated runoff and erosion rates from small (0.5 m2) rainfall plots were associated 

with extensive bare ground, reduced surface roughness, and soil water repellency. These 

effects were greater for south-facing than north-facing slopes. Runoff occurred within 2 

to 4 min of rainfall in the Pierson et al. (2002b) study. Flooding during the ensuing storm 

was driven by intense rainfall on bare (90 to 100 percent bare ground), water-repellent 

soils with reduced water storage capacity and low surface roughness. Most of the rainfall 

falling on the south-facing slopes ran off, forming concentrated flow networks (Pierson et 

al. 2002b).

Moody and Martin (2001) described a similar response to 100-year rainfall storm 

following the 4,690 ha Buffalo Creek Fire in steep, forested watersheds of the Colorado 

Front Range. More than 60 percent of the burn was high intensity. Within 2 months 

postfire, a high-intensity (90 mm h-1, 1 h) rainstorm caused flash flooding that killed two 

people and discharged enough sediment into the Strontia Springs Reservoir to reduce 

storage capacity by one-third (Agnew et al. 1997; Moody and Martin 2001). Unburned 

hillslopes adjacent to the fire generated very little surface runoff (Elliott and Parker 

2001). Hillslope erosion increased 150- to 240-fold postfire. Nearly 1,500,000 m3 of sediment was generated from interrill, rill, and in-channel processes during the first summer 

after the fire, and an estimated 86 percent of erosion from the first two summers postfire 

was from rill and channel processes (Moody and Martin 2001). Soil water repellency was 

not reported for the Buffalo Creek Fire.

A torrential rainstorm 2 months after the 800 ha South Canyon Fire in Colorado 

generated multiple runoff-triggered debris-flow events that inundated a 13- to 14-ha area 

with about 70,000 m3 of soil and engulfed 30 vehicles on an adjacent highway (Cannon 

et al. 1998, 2001a). The fire occurred on steeply sloping (30 to 70 percent) woodland and 

shrub-dominated hillslopes. Cannon et al. (1998) estimated that rainsplash, sheetflow, 

and concentrated flow processes during the storm removed 15 percent of the mineral soil 

surface to a depth of 4 cm. Amplified runoff and erosion from rainsplash and sheetflow 

on bare soils led to formation of concentrated flow networks and gullies with high erosive 

energy and sediment transport capacity. Erosion per unit of runoff generally increased 

downslope as flow paths incised and widened to 30 to 40 cm (Cannon et al. 2001a). The 
USDA Forest Service RMRS-GTR-351. 2016. 75

examples presented here demonstrate the potential hydrologic responses to high-intensity 

rainfall after large-scale alteration of vegetation and ground surface characteristics. A 

more detailed chronicle of hillslope- and watershed-scale responses to fire in forested and 

chaparral environments can be found in Shakesby and Doerr (2006).

Assessing Postfire Hydrologic Vulnerability and Risk

The overall postfire hydrologic vulnerability of a site is a function of the site 

susceptibility and prevailing climatic regime (fig. 29). Susceptibility is defined by the 

vegetation, soil, and topographic characteristics of the site and is much greater where bare 

ground is extensive on steep slopes with hydrophobic surface soil conditions (Pierson et 

al. 2011; Williams et al. 2014b). In contrast, susceptibility to postfire runoff and erosion is 

low where ground cover exceeds 60 percent (Pierson et al. 2008a, 2009, 2013; Williams 

et al. 2014a). Susceptibility for a specified area varies in both time and space and depends 

on the prefire conditions and the rate of postfire recovery. Hydrologic vulnerability for a 

specified susceptibility can be measured as the hydrologic response (runoff, erosion, or 

both) to different storm events or rainfall intensities (Williams et al. 2014b). Hydrologic 

vulnerability for a given susceptibility then increases with increasing rainfall intensity, 

as shown by the different curves in figure 29. Each curve in the figure represents a hypothetical vulnerability (or hydrologic response) associated with a particular storm intensity 

over a range of susceptibilities, with susceptibilities defined by the site conditions. 

For example, hydrologic vulnerability for a low-intensity storm on highly susceptible 

Figure 29—Conceptual model of hydrologic vulnerability and risk. Hydrologic vulnerability (measured as runoff 

and erosion response, Y-axis) is a function of site susceptibility (X-axis) and the prevailing rainfall intensity 

(indicated by colors). The level of vulnerability dictates the resources at risk. Concentrated flow processes 

dominate the postfire environment where site susceptibility is high (e.g., high bare ground, water-repellent 

soils) or rainfall is of moderate to high intensity. Rainsplash processes prevail where susceptibility is low 

(well-aggregated soils, land surface well protected by litter cover). Rainsplash, sheetflow, and concentrated 

flow processes all contribute to the runoff/erosion response where site susceptibility is indicative of disturbed 

conditions (reduced ground cover and aggregate stability, poor soil structure). The overall hydrologic 

response is amplified with increasing slope steepness. Figure modified from Pierson et al. (2011) and 

Williams et al. (2014b).
76 USDA Forest Service RMRS-GTR-351. 2016.

conditions is quite low. But hydrologic vulnerability is high for at least a moderate-intensity storm falling on a highly susceptible site (such as a site with more than 60 percent 

bare ground and water-repellent soils). The hydrologic vulnerability is then dictated by 

the storm intensity and the conditions in which the storm occurs (susceptibility).

Concentrated flow processes dictate the response when storm intensity and site 

susceptibility are both high postburn. Rainsplash processes dominate and overall vulnerability is minimal where site susceptibilities are low, regardless of the rainfall intensity. A 

combination of rainsplash, sheetflow, and concentrated flow processes may prevail where 

moderate rainfall intensities fall on a moderately susceptibility condition such as on a 

degraded site. The overall hydrologic vulnerability further defines the resource at risk 

(fig. 29) (Williams et al. 2014b). High-intensity rainfall on moderate to highly susceptible 

conditions may cause loss of life (Moody and Martin 2001) or damage to property or infrastructures (Pierson et al. 2002b; Klade 2006; Pierson et al. 2011) due to large flooding 

or debris flow events, or a combination thereof (Cannon et al. 1998, 2001a; Meyer et al. 

2001). Low-intensity storms on highly susceptible conditions may not generate massive 

flooding, but may generate enough soil loss to degrade water quality or negatively affect 

aquatic habitat. In the framework presented (fig. 29), hydrologic vulnerability curves 

can be populated with quantitative data, but the mitigation of risk is value based. Land 

managers must consider what hydrologic vulnerability they are willing to accommodate 

given the potential risks with which it is associated.

Great advances have been made in postfire risk assessment in recent decades 

(Robichaud et al. 2007a,b; Pierson et al. 2011; Williams et al. 2014b; Al-Hamdan et al. 

2015; Williams et al. 2016a,b). The Erosion Risk Management Tool (ERMiT) is one 

recent model developed with a probabilistic framework like the one shown in figure 

29 (Robichaud et al. 2007a,b). Models like ERMiT predict the likelihood of a runoff/

erosion response associated with a given storm as the probability of that storm occurrence 

given a static susceptibility. The probability of a given storm can be determined from 

return interval or intensity/duration/frequency (fig. 3) information for the area of interest. ERMiT and similar models use climate generators to predict storm frequency and 

magnitude from a climate station location identified by the user. This approach allows 

the user to evaluate hydrologic vulnerability in a predictive way and to make mitigation 

decisions based on what may be at risk given a particular storm under a particular set of 

site conditions. For example, simulations for defined postfire conditions may show there 

is a 20 percent likelihood of a particular storm and an associated infrastructure-damaging 

flood event occurring. Managers must then decide whether they are willing to assume that 

type of risk, and if not, what could be used to mitigate the response if the event occurs. 

This, of course, becomes more complicated if a user is interested in predicting potential 

response for varying conditions or hydrologic recovery with time or in landscape space. 

Predictions of this type require the user to run multiple model scenarios, one for each set 

of postfire conditions and the same storm frequencies.

The Rangeland Hydrology and Erosion Model (RHEM) has been developed 

specifically for modeling runoff and erosion from rangelands (Nearing et al. 2011) and is 

applicable for predicting runoff and erosion responses on postfire conditions (Al-Hamdan 

et al. 2015; Williams et al. 2016a,b). The RHEM model includes optional probabilitybased risk assessment output. RHEM model results for different vegetation and ground 

cover conditions (e.g., prefire, immediately postfire, 3 years postfire) can be displayed 
USDA Forest Service RMRS-GTR-351. 2016. 77

simultaneously to assess hydrologic vulnerability across varied surface susceptibility 

(Williams et al. 2016b). In summary, postfire hydrologic vulnerability assessment for 

large areas or over periods of time benefit from incorporating conceptual and mathematical models that consider both the probability of storm occurrences and the likelihood of 

respective storm occurrences over a range of postfire site conditions.

The need to address hydrologic vulnerability and risk mitigation on western rangelands is increasing due to the increased role of wildfire (Pierson et al. 2011; Williams et 

al. 2014b). Annual weed invasion of shrub steppe (Mack 1981; Whisenant 1990; Knapp 

1996) and woodlands (Tausch 1999; Miller et al. 2008; Romme et al. 2009), woodland 

encroachment (Miller and Tausch 2001; Romme et al. 2009), and increasing global 

temperatures (Westerling et al. 2006; Keane et al. 2008) are expected to amplify the 

role of fire on western landscapes (Williams et al. 2014b). Cheatgrass is now the major 

plant constituent on 4 to 7 million of the 18 million ha of shrub steppe in the Great Basin 

(Mack 1981; Knapp 1996). The continuous horizontal fuel structure of cheatgrassinvaded shrubland promotes more frequent and larger-scale wildland fires than reported 

for historical shrub steppe (Whisenant 1990; Peters and Bunting 1994; D’Antonio 2000; 

Brooks and Pyke 2001; Brooks et al. 2004; Keane et al. 2008). Current fire return intervals on many cheatgrass areas are 3 to 15 years (Whisenant 1990; Brooks and Pyke 2001; 

Brooks et al. 2004); historical fire return intervals on Great Basin sagebrush communities 

range from 20 to 100 or more years depending on the productivity of the site (Wright and 

Bailey 1982; Keane et al. 2008). Great Basin rangelands with substantial cheatgrass coverage are 10 to 500 times more likely to burn than pristine shrub-bunchgrass communities 

(Hull 1965), and fire risk is near 100 percent where cheatgrass coverage approaches 50 

percent (Link et al. 2006).

Recent infilling of trees in persistent woodlands and wooded shrublands of the 

Great Basin has also increased the risk of occurrence of large, high-severity fires (Tausch 

1999; Miller and Tausch 2001; Tausch and Hood 2007; Keane et al. 2008; Romme et al. 

2009). Cheatgrass invasion into persistent woodlands and wooded shrublands has further 

increased the horizontal fuel structure and risk of large-scale fires on many wooded sites 

within the Great Basin (Young and Evans 1978; Billings 1994, Tausch 1999; Miller et 

al. 2008). Larger, more frequent, uniform, and intense fires increase the spatial expanse 

and temporal exposure of these landscapes to accelerated runoff and erosion. Greater 

temporal exposure increases both the potential soil loss from low-return interval storms 

(1- to 10-year events) and from more damaging, high-intensity thunderstorm events.

The environmental and ecological implications of altered fire regimes are substantial when one considers the magnitude of cumulative soil loss associated with frequently 

occurring storms or infrequent but extreme events. Risks to property and human life are 

of particular concern at the wildland-urban interface (Craddock 1946; Cannon et al. 1998, 

2001a; Meyer et al. 2001; Moody and Martin 2001; Pierson et al. 2002b; Klade 2006; 

Pierson et al. 2011; Williams et al. 2014b). The economic consequences are significant 

given current U.S. expenditures on postfire risk mitigation (General Accounting Office 

2003).
78 USDA Forest Service RMRS-GTR-351. 2016.

Determining Site Susceptibility and Hydrologic Recovery

Hydrologic susceptibility assessments should include evaluation of those variables 

found to significantly affect rangeland hydrology in the postfire environment (Pierson 

et al. 2011; Williams et al. 2014b). Our research (Pierson et al. 2001a, 2002b, 2008a,b, 

2009, 2013, 2014; Al-Hamdan et al. 2012a,b, 2013; Williams et al. 2014a,b) as well as 

others’ research (Benavides-Solorio and MacDonald 2001; Cannon et al. 1998, 2001a,b; 

Johansen et al. 2001; Moody and Martin 2001; Benavides-Solorio and MacDonald 2002, 

2005; Larsen et al. 2009) indicate these variables include hillslope angle and topography, 

percent bare soil, surface soil erodibility, and soil water repellency. Although the influence of bare soil, erodibility, and soil water repellency are important across a range of 

hillslope gradients, the potential magnitude of the hydrologic response may be much 

greater for steep hillslopes (DeBano et al. 1998). Furthermore, convergent topography 

tends to accentuate concentrated flow (Benavides-Solorio and MacDonald 2005). Results 

from numerous studies indicate both runoff and erosion, more so for the latter, are strongly influenced by the expanse of bare ground (Morris and Moses 1987; Benavides-Solorio 

and MacDonald 2001; Johansen et al. 2001; Pierson et al. 2001a; Benavides-Solorio and 

MacDonald 2002; Pierson et al. 2002b; Benavides-Solorio and MacDonald 2005; Moffet 

et al. 2007; Pierson et al. 2008a,b, 2009; Larsen et al. 2009; Pierson et al. 2013; Williams 

et al. 2014a, 2016a).

For sloping rangelands, a ground cover of 50 to 60 percent is commonly adequate 

to protect the soil surface from amplified runoff and erosion during frequently recurring convective thunderstorm events (Gifford 1985; Pierson et al. 2008a, 2009, 2013; 

Williams et al. 2014a). A greater ground cover may be necessary to protect against larger, 

less frequent, major events (such as a 100-year storm) capable of generating concentrated 

flow (Benavides-Solorio and MacDonald 2005; Pierson et al. 2008a, 2009). The presence 

of strong soil water repellency further inhibits infiltration, and, when combined with 

less than 60 percent ground cover, greatly increases the vulnerability for runoff generation, concentrated flow, and elevated erosion rates (Pierson et al. 2008a,b, 2009, 2013; 

Williams et al. 2014a). The influence of soil water repellency on postfire runoff is well 

documented, but the relationships between spatial and temporal repellency strength and 

the respective hydrologic responses remain largely unknown. Finally, site erodibility 

should be considered (Pierson et al. 2010, 2014). Sites with higher erodibility may 

require greater ground cover protection. The generalities presented here are based on field 

studies, but often one or more variables (such as slope and aspect) were held constant 

during investigations. Therefore, the collective interaction remains largely unevaluated.

Postfire hydrologic recovery assessments are often hampered by the difficulty in 

selecting the appropriate reference condition, temporal fluctuations in climate, spatial 

variability in postfire surface and vegetation characteristics, and the fact that conditions 

required for hydrologic stability differ for runoff versus erosion and for rainsplash/sheetflow versus concentrated flow processes (Pierson et al. 2008a, 2009). Large-scale plant 

community transitions (D’Antonio and Vitousek 1992; Knapp 1996; DiTomaso 2000; 

Brooks and Pyke 2001; Brooks et al. 2004; Rice et al. 2008; Romme et al. 2009) have 

created prefire vegetation and surface characteristics that may differ from those that favor 

water and soil conservation. Therefore, determination of the appropriate reference for 

comparison of postburn runoff and erosion may be difficult.
USDA Forest Service RMRS-GTR-351. 2016. 79

Annual variations in climate influence hydrologically important variables like 

canopy and ground cover, soil erodibility, and soil water repellency. In a 3-year study, 

for example, Pierson et al. (2008a,b; figs. 22 and 24) reported that temporal controls 

on naturally occurring soil water repellency exerted a greater influence on runoff from 

burned and unburned sagebrush hillslopes than did direct fire effects. Soil erosion from 

burned shrub coppices in the study also exhibited significant temporal variability, but the 

study did not determine whether this resulted from temporal variation in infiltration/runoff or erodibility. The study highlighted the need for annual controls and suggested that 

results from single-year studies or those without annual unburned controls may produce 

unreliable evaluations of hydrologic vulnerability.

Potential spatial variability of site characteristics that influence hydrology like 

slope, soil properties, and vegetation should be considered in recovery assessments. For 

example, Pierson et al. (2002b) demonstrated that runoff and erosion were significantly 

greater on south-facing than north-facing slopes 1 year following wildfire in sagebrush. 

These differences greatly influenced hydrologic behavior after an intense, flash floodgenerating storm. Analysis of the north-facing slopes solely would not have captured 

the potential response of the more vulnerable south-facing slopes. Other fire-influenced 

variables like soil water repellency may vary greatly in space depending on variations in 

soil properties and burn characteristics (Woods et al. 2007).

Lastly, postfire recovery periods differ for runoff and erosion and for different 

hydrologic processes. Pierson et al. (2008a, 2009, 2013) as well as others (BenavidesSolorio and MacDonald 2001, 2002) have shown that fire-induced increases in erosion 

are greater than increases in runoff (table 3). Pierson et al. (2008a, 2009) further demonstrated that postfire erosion may take longer than postfire runoff to return to unburned 

levels and that potential erosion from concentrated flow processes may take longer than 

that from rainsplash-sheetflow processes to recover. Therefore, studies that focus on one 

aspect of hydrologic vulnerability (such as runoff) or on one process (such as rainsplash) 

may not accurately evaluate recovery (Pierson et al. 2011). Studies would benefit from 

multiyear assessments with annual controls and evaluation of runoff and erosion over 

multiple scales that encompass rainsplash, sheetflow, and concentrated flow. But such 

all-encompassing studies are often not possible or practical. Investigations that focus on 

a single-scale hydrologic parameter or process should consider the potential error associated with broad inferences of hydrologic recovery.

Summary and Conclusions

Fire is a natural disturbance on western rangelands that can facilitate amplified 

runoff and erosion rates and place natural resources, property, and lives at risk. However, 

the degree to which fire increases runoff and erosion rates and the associated risks is 

highly variable and depends on many factors. Runoff and erosion from rangelands are 

dictated by interactions among climate, vegetation, soils, and topography. Fire alters the 

structure of vegetation and ground cover, and may physically or chemically affect soils. 

Therefore, the magnitude of fire-induced increases in annual or event runoff and erosion 

is fundamentally associated with the degree to which fire reduces vegetation and modifies 
80 USDA Forest Service RMRS-GTR-351. 2016.

soils, and with the local topography and prevailing climate regime (annual scale) or storm 

input (event scale).

In general, fire-induced hydrologic vulnerability and risks are low where burning 

minimally alters vegetation and ground cover or when precipitation input is low. Highintensity rainfall on severely burned and steeply sloping hillslopes presents the highest 

risk for fire-induced increases in runoff and erosion. Plot- to hillslope-scale studies 

presented in this review demonstrate that burning may increase runoff, erosion, or both 

during high-intensity rainfall events by factors of 2 to 40 over small-plot scales and more 

than 100-fold over large-plot to hillslope scales. Anecdotal reports of large-scale flooding 

and debris-flow events from rangelands, woodlands, and semiarid forests, associated with 

high-intensity rainfall following burning, document the potential risk to resources (such 

as water quality and aquatic habitat), property and infrastructure, and human life. Such 

risks are of particular concern for large urban centers along urban-wildland interfaces. It 

is important to note the need for postfire risk assessments to consider risk in a probabilistic framework that examines the likelihood of specified storm events and the potential 

responses for a given set of site conditions or susceptibility. Evaluations of site susceptibility to increased runoff and erosion should focus on the key indicators described in this 

review: expanse of bare ground, degree of soil water repellency, slope/topography, and 

site-specific soil stability/erodibility. Assessments of risk over long-term intervals should 

also evaluate potential changes in site susceptibility associated with prevailing climate 

conditions and plant/cover recruitment.

Lastly, the role of fire is changing on western rangelands. Fires are increasing in 

frequency, duration, and size across much of the western United States. These changes 

potentially increase the overall hydrologic vulnerability of rangelands by spatially and 

temporally increasing surface exposure to runoff and erosion processes. We do not 

yet know the ramifications of repeated burning and the respective runoff/erosion from 

frequently occurring small events or less frequent large events. The materials presented 

in this review do, however, provide a foundation from which hydrologic vulnerability 

assessments can be developed and conceptual and mathematical models can be advanced 

to aid in the management of postfire risk evaluation and assessment.

References

Abrahams, A.D.; Anthony, J.P.; Wainwright, J. 1995. Effects of vegetation change on 

interrill runoff and erosion, Walnut Gulch, Southern Arizona. Geomorphology. 13: 

37‒48.

Abrahams, A.D.; Li, G.; Parsons, A.J. 1996. Rill hydraulics on a semiarid hillslope, 

southern Arizona. Earth Processes and Landforms. 21: 35‒47.

Abrahams, A.D.; Parsons, A.J. 1991a. Relation between infiltration and stone cover on a 

semiarid hillslope, southern Arizona. Journal of Hydrology. 122: 49‒59.

Abrahams, A.D.; Parsons, A.J. 1991b. Resistance to overland flow on desert pavement 

and its implications for sediment transport modeling. Water Resources Research. 27: 

1827‒1836.

Abrahams, A.D.; Parsons, A.J. 1994. Hydraulics of interrill overland flow on stonecovered desert surfaces. Catena. 23: 111‒140.
USDA Forest Service RMRS-GTR-351. 2016. 81

Abrahams, A.D.; Parsons, A.J.; Luk, S.H. 1988. Hydrologic and sediment responses to 

simulated rainfall on desert hillslopes in southern Arizona. Catena. 15: 103‒117.

Abrahams, A.D.; Parsons, A.J.; Luk, S.H. 1991. The effect of spatial variability in 

overland flow on the downslope pattern of soil loss on a semiarid hillslope, southern 

Arizona. Catena. 18: 255‒270.

Abrahams, A.D.; Parsons, A.J.; Wainwright, J. 2003. Disposition of rainwater under 

creosotebush. Hydrological Processes. 17: 2555‒2566.

Agnew, W.; Labn, R.E.; Harding, M.V. 1997. Buffalo Creek, Colorado, fire and flood of 

1996. Land and Water. 41: 27‒29.

Ahlgren, I.F.; Ahlgren, C.E. 1960. Ecological effects of forest fires. Botanical Review. 26: 

483‒533.

Al-Hamdan, O.Z.; Hernandez, M.; Pierson, F.B.; Nearing, M.A.; Williams, C.J.; Stone, 

J.J.; Boll, J.; Weltz, M.A. 2015. Rangeland Hydrology and Erosion Model (RHEM) 

enhancements for applications on disturbed conditions. Hydrological Processes. 29: 

445–457.

Al-Hamdan, O.Z.; Pierson, F.B.; Nearing, M.A.; Stone, J.J.; Williams, C.J.; Moffet, 

C.A.; Kormos, P.R.; Boll, J.; Weltz, M.A. 2012a. Characteristics of concentrated flow 

hydraulics for rangeland ecosystems: Implications for hydrologic modeling. Earth 

Surface Processes and Landforms. 37: 157‒168.

Al-Hamdan, O.Z.; Pierson, F.B.; Nearing, M.A.; Williams, C.J.; Stone, J.J.; Kormos, 

P.R.; Boll, J.; Weltz, M.A. 2012b. Concentrated flow erodibility for physically based 

erosion models: Temporal variability in disturbed and undisturbed rangelands. Water 

Resources Research. 49: art. no. W07504.

Al-Hamdan, O.Z.; Pierson, F.B.; Nearing, M.A.; Williams, C.J.; Stone, J.J.; Kormos, 

P.R.; Boll, J.; Weltz, M.A. 2013. Risk assessment of erosion from concentrated flow on 

rangelands using overland flow distribution and shear stress partitioning. Transactions 

of the American Society of Agricultural and Biological Engineers. 56: 539‒548.

 Allen, C.D.; Breshears, D.D. 1998. Drought-induced shift of a forest-woodland ecotone: 

Rapid landscape response to climate variation. Proceedings of the National Academy 

of Sciences of the United States of America. 95: 14839–14842.

Andreu, V.; Imeson, A.C.; Rubio, J.L. 2001. Temporal changes in soil aggregates and 

water erosion after wildfire in a Mediterranean pine forest. Catena. 44: 69‒84.

Ansley, R.J.; Jacoby, P.W.; Hicks, R.A. 1991. Leaf and whole plant transpiration in 

honey mesquite following severing of lateral roots. Journal of Range Management. 44: 

577‒583.

Arcenegui, V.; Mataix-Solero, J.; Guerrero, C.; Zornoza, R.; Mataix-Beneyto, J.; GarciaOrenes, F. 2008. Immediate effects of wildfires on water repellency and aggregate 

stability in Mediterranean calcareous soils. Catena. 74: 219‒223.

Assouline, S. 2004. Rainfall-induced soil surface sealing: A critical review of 

observations, conceptual models, and solutions. Vadose Zone Journal. 3: 570‒591.

Baker, W.L. 2009. Fire ecology in Rocky Mountain landscapes. Washington, DC: Island 

Press. 632 p.
82 USDA Forest Service RMRS-GTR-351. 2016.

Bauters, T.W.J.; Steenhuis, T.S.; Dicarlo, D.A.; Nieber, J.L.; Dekker, L.W.; Ritsema, 

C.J.; Parlange, J.Y.; Haverkamp, R. 2000. Physics of water repellent soils. Journal of 

Hydrology. 231‒232: 233‒243.

Belnap, J.; Welter, J.R.; Grimm, N.B.; Barger, N.; Ludwig, J.A. 2005. Linkages between 

microbial and hydrologic processes in arid and semiarid watersheds. Ecology. 86: 

298‒307.

Belsky, A.J.; Amundson, R.G.; Duxbury, J.M.; Riha, S.J.; Ali, A.R.; Mwonga, S.M. 1989. 

The effects of trees on their physical, chemical, and biological environments in a semiarid savanna in Kenya. Journal of Applied Ecology. 26: 1005‒1024.

Belsky, A.J.; Mwonga, S.M.; Amundson, R.G.; Duxbury, J.M.; Ali, A.R. 1993. 

Comparative effects of isolated trees on their undercanopy environments in high- and 

low-rainfall savannas. Journal of Applied Ecology. 30: 143‒155.

Benavides-Solorio, J.D.D.; MacDonald, L.H. 2001. Post-fire runoff and erosion from 

simulated rainfall on small plots, Colorado Front Range. Hydrological Processes. 15: 

2931‒2952.

Benavides-Solorio, J.D.D.; MacDonald, L.H. 2002. Erratum: post-fire runoff and erosion 

from simulated rainfall on small plots, Colorado Front Range. Hydrological Processes. 

16: 1131‒1133.

Benavides-Solorio, J.D.D.; MacDonald, L.H. 2005. Measurement and prediction of 

post-fire erosion at the hillslope scale, Colorado Front Range. International Journal of 

Wildland Fire. 14: 457‒474.

Bergkamp, G. 1998. A hierarchical view of the interactions of runoff and infiltration with 

vegetation and microtopography in semiarid shrublands. Catena. 33: 201‒220.

Beven, K.; Germann, P. 1982. Macropores and water flows in soils. Water Resources 

Research. 18: 1311–1325.

Bhark, E.W.; Small, E.E. 2003. Association between plant canopies and the spatial 

patterns of infiltration in shrubland and grassland of the Chihuahuan Desert, New 

Mexico. Ecosystems. 6: 185‒196.

Billings, W.D. 1994. Ecological impacts of cheatgrass and resultant fire on ecosystems 

in the western Great Basin. In: Monsen, S.B.; Kitchen, S.G., comps. Proceedings: 

Ecology and management of annual rangelands; 1992 May 18‒22; Boise, Idaho, USA. 

Gen. Tech. Rep. INT-GTR-313. Ogden, UT: U.S. Department of Agriculture, Forest 

Service, Intermountain Research Station: 22‒30.

Bisdom, E.B.A.; Dekker, L.W.; Schoute, J.F.T. 1993. Water repellency of sieve fractions 

from sandy soils and relationships with organic material and soil structure. Geoderma. 

56: 105‒118.

Blackburn, W.H. 1975. Factors influencing infiltration and sediment production of 

semiarid rangelands in Nevada. Water Resources Research. 11: 929‒937.

Blackburn, W.H.; Pierson, F.B.; Hanson, C.L.; Thurow, T.L.; Hanson, A.L. 1992. The 

spatial and temporal influence of vegetation on surface soil factors in semiarid 

rangelands. Transactions of the American Society of Agricultural Engineers. 35: 

479‒486.
USDA Forest Service RMRS-GTR-351. 2016. 83

Blackburn, W.H.; Pierson, F.B.; Seyfried, M.S. 1990. Spatial and temporal influence of 

soil frost on infiltration and erosion of sagebrush rangelands. Water Resource Bulletin. 

26: 991‒997.

Blackburn, W.H.; Skau, C.M. 1974. Infiltration rates and sediment production of selected 

plant communities in Nevada. Journal of Range Management: 27(6): 476‒480.

Blackburn, W.H.; Wood, M.K. 1990. Influence of soil frost on infiltration of shrub 

coppice dune and dune interspace soils in southeastern Nevada. Great Basin Naturalist. 

50: 41‒46.

Bodí, M.B.; Doerr, S.H.; Cerdà, A.; Mataix-Solera, J. 2012. Hydrological effects of a 

layer of vegetation ash on underlying wettable and water repellent soil. Geoderma. 

191: 14‒23.

Bodí, M.B.; Muñoz-Santa, I.; Armero, C.; Doerr, S.H.; Mataix-Solero, J.; Cerdà, A. 2013. 

Spatial and temporal variations of water repellency and probability of its occurrence in 

calcareous Mediterranean rangeland soils affected by fires. Catena. 108: 14‒25.

Bonan, G. 2002. Ecological climatology: concepts and applications. Cambridge, UK: 

Cambridge University Press. 678 p.

Bonnin, G.M.; Martin, D.; Lin, B.; Parzybok, T.; Yekta, M.; Riley, D. 2006. 

Precipitation—frequency atlas of the United States, NOAA atlas 14, volume 1, 

version 4. Silver Spring, MD: U.S. Department of Commerce, National Oceanic and 

Atmospheric Administration, National Weather Service. 261 p.

Bowen, B. 1996. Rainfall and climate variation over a sloping New Mexico plateau 

during the North American monsoon. Journal of Climate. 9: 3432‒3442.

Bradford, J.M.; Ferris, J.E.; Remley, P.A. 1987. Interrill soil erosion processes: I. Effect 

of surface sealing on infiltration, runoff, and soil splash detachment. Soil Science 

Society of America Journal. 51: 1566‒1571.

Brakensiek, D.L.; Rawls, W.J. 1994. Soil containing rock fragments: Effects on 

infiltration. Catena. 23: 99‒110.

Brandes, D.; Wilcox, B.P. 2000. Evapotranspiration and soil moisture dynamics on 

a semiarid ponderosa pine hillslope. Journal of the American Water Resources 

Association. 36: 965‒974.

Branson, F.A.; Owen, J.B. 1970. Plant cover, runoff, and sediment yield relationships on 

Mancos Shale in western Colorado. Water Resources Research. 6: 783‒790.

Branson, F.A.; Gifford, G.F.; Renard, K.G.; Hadley, R.F. 1981. 2d ed. Rangeland 

hydrology. Range Science Series No. 1. Dubuque, IA: Kendall-Hunt Publishing. 340 p.

Breshears, D.D.; Barnes, F.J. 1999. Interrelationships between plant functional types 

and soil moisture heterogeneity for semiarid landscapes within the grassland/forest 

continuum: A unified conceptual model. Landscape Ecology. 14: 465‒478.

Breshears, D.D.; Myers, O.B.; Johnson, S.R.; Meyer, C.W.; Martens, S.N. 1997a. 

Differential use of spatially heterogeneous soil moisture by two semiarid woody 

species: Pinus edulis and Juniperus monosperma. Journal of Ecology. 85: 289‒299.

Breshears, D.D.; Nyhan, J.W.; Heil, C.E.; Wilcox, B.P. 1998. Effects of woody plants on 

microclimate in a semiarid woodland: soil temperature and evaporation in canopy and 

intercanopy patches. International Journal of Plant Science. 159: 1010‒1017.
84 USDA Forest Service RMRS-GTR-351. 2016.

Breshears, D.D.; Rich, P.M.; Barnes, F.J.; Campbell, K. 1997b. Overstory-imposed 

heterogeneity in solar radiation and soil moisture in a semiarid woodland. Ecological 

Applications. 7: 1201‒1215.

Brooks, J.R.; Meinzer, F.C.; Coulombe, R.; Gregg, J. 2002. Hydraulic redistribution of 

soil water during summer drought in two contrasting Pacific Northwest coniferous 

forests. Tree Physiology. 22: 1107‒1117.

Brooks, M.L. 2008. Plant invasions and fire regimes. In: Zouhar, K.; Smith, J.K.; 

Sutherland, S.; Brooks, M.L., eds. Wildland fire in ecosystems: Fire and nonnative 

invasive plants. Gen. Tech. Rep. RMRS-GTR-42-vol. 6. Ogden, UT: U.S. Department 

of Agriculture, Forest Service, Rocky Mountain Research Station: 33‒45.

Brooks, M.L.; D’Antonio, C.M.; Richardson, D.M.; Grace, J.B.; Keeley, J.E.; DiTomaso, 

J.M.; Hobbs, R.J.; Pellant, M.; Pyke, D. 2004. Effects of invasive alien plants on fire 

regimes. BioScience. 54: 677‒688.

Brooks, M.L.; Pyke, D.A. 2001. Invasive plants and fire in the deserts of North America. 

In: Galley, K.E.M.; Wilson, T.P., eds. Proceedings of the invasive species workshop: 

The role of fire in the control and spread of invasive species. Fire conference 2000: 

The first national congress on fire ecology, prevention, and management. Tall Timbers 

Research Station, Misc. Publ. No. 11: 1‒14.

Brown, J.K. 2000. Introduction and fire regimes. In Brown, J.K.; Smith, J.K., eds. 

Wildland fire in ecosystems: Effects of fire on flora. Gen. Tech. Rep. RMRS-GTR-42-

vol. 2. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain 

Research Station: 1‒8.

Brutsaert, W. 2005. Hydrology, an introduction. New York: Cambridge University Press. 

618 p.

Bryan, R.B. 2000. Soil erodibility and processes of water erosion on hillslope. 

Geomorphology. 32: 385‒415.

Burcar, W.W.; Tyler, S.W.; Johnson, D.W. 1994. Seasonal preferential flow in two Sierra 

Nevada soils under forested and meadow cover. Soil Science Society of America 

Journal. 58: 1555‒1561.

Burch, G.J.; Moore, I.D.; Burns, J. 1989. Soil hydrophobic effects on infiltration and 

catchment runoff. Hydrological Processes. 3: 211‒222.

Burgess, S.S.O.; Adams, M.A.; Turner, N.C.; Ong, C.K. 1998. The redistribution of soil 

water by tree root systems. Oecologia. 115: 306‒311.

Burgess, S.S.O.; Adams, M.A.; Turner, N.C.; White, D.A.; Ong, C.K. 2001. Tree roots: 

Conduits for deep recharge of soil water. Oecologia. 126:158‒165.

Burgess, S.S.O.; Bleby, T.M. 2006. Redistribution of soil water by lateral roots mediated 

by stem tissues. Journal of Experimental Botany. 57: 3283‒3291.

Caldwell, M.M. 1985. Cold deserts. In: Chabot, B.F.; Mooney, H.A., eds. Physiological 

ecology of North American plant communities. New York: Chapman and Hall: 

198‒212.

Caldwell, M.M.; Dawson, T.E.; Richards, J.H. 1998. Hydraulic lift: Consequences of 

water efflux from roots of plants. Oecologia. 113: 151‒161.
USDA Forest Service RMRS-GTR-351. 2016. 85

Caldwell, M.M.; Eissenstat, D.M.; Richards, J.H.; Allen, M.F. 1985. Competition for 

phosphorus: Differential uptake from dual-isotope-labeled soil interspaces between 

shrub and grasses. Science. 229: 384‒386.

Caldwell, M.M.; Richards, J.H. 1989. Hydraulic lift: Water efflux from upper roots 

improves effectiveness of water uptake by deep roots. Oecologia. 79: 1‒5.

Cammeraat, L.H.; Imeson, A.C. 1998. Deriving indicators of soil degradation from soil 

aggregation studies in southeastern Spain and southern France. Geomorphology. 23: 

307‒321.

Cammeraat, L.H.; Imeson, A.C. 1999. The evolution and significance of soil-vegetation 

patterns following land abandonment and fire in Spain. Catena. 37: 107‒127.

Campbell, G.S.; Harris, G.A. 1977. Water relations and water use patterns for Artemisia 

tridentata Nutt. in wet and dry years. Ecology. 58: 652‒659.

Campbell, R.E.; Baker, M.B.; Ffolliot, P.F.; Larson, F.R.; Avery, C.C. 1977. Wildfire 

effects on a ponderosa pine ecosystem: An Arizona case study. Res. Pap. RM-191. Fort 

Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest 

and Range Experimental Station. 12 p.

Cannon, S.H.; Bigio, E.R.; Mine, E. 2001a. A process for fire-related debris flow 

initiation, Cerro Grande fire, New Mexico. Hydrological Processes. 15: 3011‒3023.

Cannon, S.H.; Gartner, J.E.; Wilson, R.C.; Bowers, J.C.; Laber, J.L. 2008. Storm rainfall 

conditions for floods and debris flows from recently burned areas in southwestern 

Colorado and southern California. Geomorphology. 96: 250‒269.

Cannon, S.H.; Kirkham, R.M.; Parise, M. 2001b. Wildfire-related debris-flow initiation 

processes, Storm King Mountain, Colorado. Geomorphology. 39: 171‒188.

Cannon, S.H.; Powers, P.S.; Savage, W.Z. 1998. Fire-related hyperconcentrated 

and debris flows on Storm King Mountain, Glenwood Springs, Colorado, USA. 

Environmental Geology. 35: 210‒218.

Carlson, D.H.; Thurow, T.L. 1996. Comprehensive evaluation of the improved SPUR 

model (SPUR-91). Ecological Modelling. 85: 229‒240.

Carlson, D.H.; Thurow, T.L.; Knight, R.W.; Heitschmidt, R.K. 1990. Effect of honey 

mesquite on the water balance of Texas rolling plains rangeland. Journal of Range 

Management. 43: 491‒496.

Carlyle-Moses, D.E. 2004. Throughfall, stemflow, and canopy interception loss fluxes in 

a semi-arid Sierra Madre Oriental matorral community. Journal of Arid Environments. 

58: 181‒202.

Castillo, V.M.; Gómez-Plaza, A.; Martínez-Mena, M. 2003. The role of antecedent soil 

water content in the runoff response of semiarid catchments: A simulation approach. 

Journal of Hydrology. 284: 114‒130.

Cerdà, A. 1997. The effect of patchy distribution of Stipa tenacissima L. on runoff and 

erosion. Journal of Arid Environments. 36: 37‒51.

Cerdà, A. 1998a. Changes in overland flow and infiltration after a rangeland fire in a 

Mediterranean scrubland. Hydrological Processes. 12: 1031‒1042.
86 USDA Forest Service RMRS-GTR-351. 2016.

Cerdà, A. 1998b. Soil aggregate stability under different Mediterranean vegetation types. 

Catena. 32: 73‒86.

Cerdà, A. 2001. Effects of rock fragment cover on soil infiltration, interrill runoff and 

erosion. European Journal of Soil Science. 52: 59‒68.

Cerdà, A.; Doerr, S.H. 2005. Influence of vegetation recovery on soil hydrology and 

erodibility following fire: An 11-year investigation. International Journal of Wildland 

Fire. 14: 423‒437.

Cerdà, A.; Doerr, S.H. 2008. The effects of ash and needle cover on surface runoff and 

erosion in the immediate post-fire period. Catena. 74: 256‒263.

Certini, G.; Nocentini, C.; Knicker, H.; Arfaioli, P.; Rumpel, C. 2011. Wildfire effects on 

soil organic matter quantity and quality in two fire-prone Mediterranean pine forests. 

Geoderma. 167‒168: 148‒155.

Clark, O.R. 1940. Interception of rainfall by prairie grasses, weeds, and certain crop 

plants. Ecological Monographs. 10: 243‒277.

Craddock, G.W. 1946. Salt Lake City flood, 1945. Proceedings of the Utah Academy of 

Sciences, Arts, and Letters. 23: 51‒61.

Craddock, G.W.; Pearse, C.K. 1938. Surface run-off and erosion on granitic mountain 

soils of Idaho as influenced by range cover, soil disturbance, slope, and precipitation 

intensity. Boise, ID: U.S. Department of Agriculture, Forest Service, Intermountain 

Forest and Range Experiment Station. 24 p.

D’Antonio, C.M. 2000. Fire, plant invasions, and global changes. In: Mooney, H.A.; 

Hobbs, R.J., eds. Invasive species in a changing world. Washington, DC: Island Press: 

65‒93.

D’Antonio, C.M.; Vitousek, P.M. 1992. Biological invasions by exotic grasses, the grass/

fire cycle, and global change. Annual Review of Ecology and Systematics. 23: 63‒87.

Davenport, D.W.; Breshears, D.D.; Wilcox, B.P.; Allen, C.D. 1998. Viewpoint: 

Sustainability of piñon-juniper ecosystems—a unifying perspective of soil erosion 

thresholds. Journal of Range Management. 51: 231‒240.

Dawson, T.E. 1993. Hydraulic lift and water use by plants: implications for water 

balance, performance and plant-plant interactions. Oecologia. 95: 565‒574.

Dawson, T.E. 1996. Determining water use by trees and forests from isotopic, energy 

balance and transpiration analyses: The roles of tree size and hydraulic lift. Tree 

Physiology. 16: 263‒272.

DeBano, L.F. 1971. The effect of hydrophobic substances on water movement in soil 

during infiltration. Soil Science Society of America Proceedings. 35: 340‒343.

DeBano, L.F. 1981. Water repellent soils: A state-of-the-art. Gen. Tech. Rep. PSW-46. 

Berkeley, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest 

Research Station. 25 p.

DeBano, L.F. 1991. The effects of fire on soil properties. In: Harvey, A.E.; 

Neuenchwander, L.F., comps. Proceedings—management and productivity of westernmontaine forest soils; 1990 April 10–12; Boise, ID. Gen. Tech. Rep. INT-280. Ogden, 

UT: U.S. Department of Agriculture, Forest Service, Intermountain Research Station: 

151‒156.
USDA Forest Service RMRS-GTR-351. 2016. 87

DeBano, L.F. 2000. The role of fire and soil heating on water repellency in wildland 

environments: A review. Journal of Hydrology. 231‒232: 195‒206.

DeBano, L.F. 2001. Water repellency in soils: a historical review. Journal of Hydrology. 

231‒232: 4‒32.

DeBano, L.F.; Krammes, J.S. 1966. Water repellent soils and their relation to wildfire 

temperatures. International Association of Hydrological Sciences. 2: 14‒19.

DeBano, L.F.; Mann, L.D.; Hamilton, D.A. 1970. Translocation of hydrophobic 

substances into soil by burning organic litter. Proceedings of the Soil Science Society 

of America. 34: 130‒133.

DeBano, L.F.; Neary, D.G.; Ffolliott, P.F. 1998. Fire’s effects on ecosystems. New York: 

John Wiley and Sons, Inc. 352 p.

DeBano, L.F.; Rice, R.M. 1973. Water-repellent soils: Their implications in forestry. 

Journal of Forestry. 71: 220‒223.

DeBano, L.F.; Rice, R.M.; Conrad, C.E. 1979. Soil heating in chaparral fires: Effects 

on soil properties, plant nutrients, erosion, and runoff. PSW-145. Berkeley, CA: U.S. 

Department of Agriculture, Forest Service, Pacific Southwest Research Station. 21 p.

DeBano, L.F.; Savage, S.M.; Hamilton, A.D. 1976. The transfer of heat and hydrophobic 

substances during burning. Proceedings of the Soil Science Society of America. 40: 

779‒782.

Dekker, L.W.; Doerr, S.H.; Oostindie, K.; Ziogas, A.K.; Ritsema, C.J. 2001. Water 

repellency and critical soil water content in a dune sand. Soil Science Society of 

America Journal. 65: 1667‒1674.

Dekker, L.W.; Ritsema, C.J. 1994. How water moves in a water-repellent sandy soil: 1. 

Potential and actual water repellency. Water Resources Research. 30: 2507‒2517.

Dekker, L.W.; Ritsema, C.J. 1995. Fingerlike wetting patterns in two water-repellent 

loam soils. Journal of Environmental Quality. 24: 324‒333.

Dekker, L.W.; Ritsema, C.J. 1996. Preferential flow paths in a water repellent clay soil 

with grass cover. Water Resources Research. 32: 1239‒1294.

Devaurs, M.; Gifford, G.F. 1984. Variability of infiltration within large runoff plots on 

rangelands. Journal of Range Management. 37: 523‒528.

Devitt, D.A.; Smith, S.D. 2002. Root channel macropores enhance downward movement 

of water in a Mojave Desert ecosystem. Journal of Arid Environments. 50: 99‒108.

Dingman, L. 2002. 2d ed. Physical hydrology. Upper Saddle River, NJ: Prentice Hall. 

600 p.

DiTomaso, J.M. 2000. Invasive weeds in rangelands: Species, impacts, and management. 

Weed Science. 48: 255‒265.

D’Odorico, P.; Caylor, K.; Okin, G.S.; Scanlon, T.M. 2007. On soil moisture-vegetation 

feedbacks and their possible effects on the dynamics of dryland ecosystems. Journal of 

Geophysical Research. 112: G04010.
88 USDA Forest Service RMRS-GTR-351. 2016.

Doerr, S.H.; Blake, W.H.; Shakesby, R.A.; Stagnitti, F.; Vuurens, S.H.; Humphreys, G.S.; 

Wallbrink, P. 2004. Heating effects on water repellency in Australian eucalypt forest 

soils and their value in estimating wildfire soil temperatures. International Journal of 

Wildland Fire. 13: 157‒163.

Doerr, S.H.; Moody, J.A. 2004. Hydrological impacts of soil water repellency: On spatial 

and temporal uncertainties. Hydrological Processes. 18: 829‒832.

Doerr, S.H.; Shakesby, R.A.; Blake, W.H.; Chafer, C.; Humphreys, G.S.; Wallbrink, P.J. 

2006. Effects of differing wildfire severities on soil wettability and implications for 

hydrological response. Journal of Hydrology. 319: 295‒311.

Doerr, S.H.; Shakesby, R.A.; MacDonald, L.H. 2009. Soil water repellency: A key 

factor in post-fire erosion. In: Cerdà, A.; Robichaud, P.R., eds. Fire effects on soils 

and restoration strategies. Land Reconstruction and Management Series, Volume 5. 

Enfield, NH: Science Publishers: 197‒224.

Doerr, S.H.; Shakesby, R.A.; Walsh, R.P.D. 1996. Soil water repellency variations with 

depth and particle size fractions in burned and unburned Eucalyptus globulus and 

Pinus pinaster forest terrain in the Agueda basin, Portugal. Catena. 27: 25‒47.

Doerr, S.H.; Shakesby, R.A.; Walsh, R.P.D. 2000. Soil water repellency: Its causes, 

characteristics and hydro-geomorphological significance. Earth-Science Reviews. 51: 

33‒65.

Doerr, S.H.; Thomas, A.D. 2000. The role of soil moisture in controlling water 

repellency: New evidence from forest soils in Portugal. Journal of Hydrology. 

231‒232: 134‒147.

Domingo, F.; Sánchez, G.; Moro, M.J.; Brenner, A.J.; Puigdefábregas, J. 1998. 

Measurement and modeling of rainfall interception by three semi-arid canopies. 

Agricultural and Forest Meteorology. 91: 275‒292.

Domingo, F.; Villagarcía, L.; Brenner, A.J.; Puigdefábregas, J. 2000. Measuring and 

modelling the radiation balance of a heterogeneous shrubland. Plant, Cell and 

Environment. 23: 27‒38.

Dunkerley, D. 2000. Measuring interception loss and canopy storage in dryland 

vegetation: A brief review and evaluation of available research strategies. Hydrological 

Processes. 14: 669‒678.

Dunkerley, D. 2002. Infiltration rates and soil moisture in a groved mulga community 

near Alice Springs, arid central Australia: Evidence for complex internal rainwater 

redistribution in a runoff-runon landscape. Journal of Arid Environments. 51: 199‒219.

Dunkerley, D.L. 2008. Intra-storm evaporation as a component of canopy interception 

loss in dryland shrubs: Observations from Fowlers Gap, Australia. Hydrological 

Processes. 22: 1985‒1995.

Dunkerley, D.L.; Booth, T.L. 1999. Plant canopy interception of rainfall and its 

significance in a banded landscape, arid western New South Wales, Australia. Water 

Resources Research. 35: 1581‒1586.

Dunkerley, D.L.; Brown, K.J. 1995. Runoff and runon areas in a patterned chenopod 

shrubland, arid western New South Wales, Australia: Characteristics and origin. 

Journal of Arid Environments. 30: 41‒55.
USDA Forest Service RMRS-GTR-351. 2016. 89

Dunne, T. 1978. Field studies of hillslope flow processes. In: Kirby, M.J., ed. Hillslope 

hydrology. Norwich, UK: John Wiley and Sons, Ltd.: 227–293.

Dunne, T.; Leopold, L.B. 1978. Water in environmental planning. San Francisco, CA: 

W.H. Freeman and Company. 818 p.

Dunne, T.; Zhang, W.; Aubry, B.F. 1991. Effects of rainfall, vegetation, and 

microtopography on infiltration and runoff. Water Resources Research. 27: 2271‒2285.

Ebel, B.A.; Moody, J.A.; Martin, D.A. 2012. Hydrologic conditions controlling runoff 

generation immediately after wildfire. Water Resources Research. 48: W0352.

Ellen, S.D.; Wieczorek, G.F. 1988. Landslides, floods, and marine effects of the storm 

of January 3–5, 1982, in the San Francisco Bay Region, California. United States 

Geological Survey, Professional Paper 1434, Version 1. 319 p.

Elliott, J.G.; Parker, R.S. 2001. Developing a post-fire flood chronology and recurrence 

probability from alluvial stratigraphy in the Buffalo Creek watershed, Colorado, USA. 

Hydrological Processes. 15: 3039‒3051.

Emerman, S.H.; Dawson, T.E. 1996. Hydraulic lift and its influence on the water content 

of the rhizosphere: An example from sugar maple, Acer saccharum. Oecologia. 108: 

273‒278.

Emmett, W.W. 1970. The hydraulics of overland flow on hillslopes. United States 

Geological Survey, Professional Paper 662A. 66 p.

Emmett, W.W. 1978. Overland flow. In: Kirby, M.J., ed. Hillslope hydrology. Norwich, 

UK: John Wiley and Sons, Ltd.: 145‒176.

Ferrera, A.G.; Singer, M.J. 1985. Energy dissipation for water drop impact into shallow 

pools. Soil Science Society of America Journal. 49: 1537‒1542.

Field, J.P.; Breshears, D.D.; Whicker, J.J.; Zou, C.B. 2012. Sediment capture by 

vegetation patches: Implications for desertification and increased resource 

redistribution. Journal of Geophysical Research G: Biogeosciences. 117. doi: 

10.1029/2011jg001663.

Flerchinger, G.N.; Cooley, K.R. 2000. A ten-year water balance of a mountainous semiarid watershed. Journal of Hydrology. 237: 86‒99.

Flerchinger, G.N.; Cooley, K.R.; Hanson, C.L.; Seyfried, M.S. 1998. A uniform versus 

an aggregated water balance of a semi-arid watershed. Hydrological Processes. 12: 

331‒342.

Flerchinger, G.N.; Cooley, K.R.; Ralston, D.R. 1992. Groundwater response to snowmelt 

in a mountainous watershed. Journal of Hydrology. 133: 293‒311.

Flerchinger, G.N.; Hanson, C.L.; Wight, J.R. 1996. Modeling evapotranspiration and 

surface energy budgets across a watershed. Water Resources Research. 32: 2539‒2548.

Foster, G.R.; Meyer, L.D. 1972. Transport of soil particles by shallow flow. Transactions 

of the American Society of Agricultural Engineers. 15: 99‒102.

Fox, D.M.; Darboux, F.; Carrega, P. 2007. Effects of fire-induced water repellency on soil 

aggregate stability, splash erosion, and saturated hydraulic conductivity for different 

size fractions. Hydrological Processes. 21: 2377‒2384.
90 USDA Forest Service RMRS-GTR-351. 2016.

Gabet, E.J.; Dunne, T. 2003. Sediment detachment by rain power. Water Resources 

Research. 39: ESG11–ESG112.

General Accounting Office. 2003. Wildland fires: Better information needed on 

effectiveness of emergence stabilization and rehabilitation treatments. Rep. GAO-03-

430. Washington, DC: U.S. General Accounting Office. 55 p.

Gifford, G.F. 1985. Cover allocation in rangeland watershed management (a review). 

In: Jones, E.B.; Ward, J.T., eds. Watershed management in the Eighties. New York: 

American Society of Civil Engineers: 23‒31.

Gilley, J.E.; Finkner, S.C. 1985. Estimating soil detachment caused by raindrop impact. 

Transactions of the American Society of Agricultural Engineers. 28: 140‒146.

Gilley, J.E.; Woolhiser, D.A.; McWhorter, D.B. 1985. Interrill soil erosion—Part 

II: testing and use of model equations. Transactions of the American Society of 

Agricultural Engineers. 28: 154‒159.

Giménez, R.; Govers, G. 2001. Interaction between bed roughness and flow hydraulics in 

eroding rills. Water Resources Research. 37: 791‒799.

Giovannini, G.; Lucchesi, S. 1997. Modifications induced in soil physico-chemical 

parameters by experimental fires at different intensities. Soil Science. 162: 479‒486.

Giovannini, G.; Lucchesi, S.; Giachetti, M. 1988. Effect of heating on some physical 

and chemical parameters related to soil aggregation and erodibility. Soil Science. 146: 

255‒261.

Giovannini, G.; Vallejo, R.; Lucchesi, S.; Bautista, S.; Ciompi, S.; Llovet, J. 2001. Effects 

of land use and eventual fire on soil erodibility in dry Mediterranean conditions. Forest 

Ecology and Management. 147: 15‒23.

Goodrich, D.C.; Keefer, T.O.; Unkrich, C.L.; Nichols, M.H.; Osborn, H.B.; Stone, J.J.; 

Smith, J.R. 2008. Long-term precipitation database, Walnut Gulch Experimental 

Watershed, Arizona, United States. Water Resources Research. 44: W05S04.

Govers, G. 1992. Relationship between discharge, velocity and flow area for rills eroding 

loose, non-layered materials. Earth Surface Processes and Landforms. 17: 515‒528.

Govers, G.; Giménez, R.; Van Oost, K. 2007. Rill erosion: Exploring the relationship 

between experiments, modelling and field observations. Earth-Science Reviews. 84: 

87‒102.

Groen, A.H.; Woods, S.W. 2008. Effectiveness of aerial seeding and straw mulch for 

reducing post-wildfire erosion, north-western Montana, USA. International Journal of 

Wildland Fire. 17: 559‒571.

Gunn, R.; Kinzer, G.D. 1949. The terminal velocity of fall from water droplets in 

stagnant air. Journal of Meteorology. 6: 243‒248.

Hamilton, E.L.; Rowe, P.B. 1949. Rainfall interception by chaparral in California. 

Sacramento, CA: California Department of Natural Resources, Division of Forestry, 

with the U.S. Department of Agriculture, Forest Service, Pacific Southwest Forest and 

Range Experiment Station. 43 p.
USDA Forest Service RMRS-GTR-351. 2016. 91

Hanson, C.L.; Pierson, F.B. 2001. Characteristics of extreme precipitation and associated 

streamflow in the Reynolds Creek Experimental Watershed, Idaho. In: Proceedings 

of the 12th Symposium on Global Change Climate Variations; 2001 January 14-19; 

Albuquerque, NM. Boston, MA: American Meteorological Society: J2.13‒J2.16.

Hendrickx, J.M.H.; Dekker, L.W.; Boersma, O.H. 1993. Unstable wetting fronts in water 

repellent field soils. Journal of Environmental Quality. 22: 109‒118.

Hester, J.W.; Thurow, T.L.; Taylor, C.A., Jr. 1997. Hydrologic characteristics of 

vegetation types as affected by prescribed burning. Journal of Range Management. 50: 

199‒204.

Hillel, D. 1998. Environmental soil physics. New York: Academic Press. 771 p.

Hornberger, G.M.; Raffensperger, J.P.; Wiberg, P.L.; Eshleman, K.N. 1998. Elements of 

physical hydrology. Baltimore, MD: John Hopkins University Press. 276 p.

Horton, J.L.; Hart, S.C. 1998. Hydraulic lift: a potentially important ecosystem process. 

Trends in Ecology and Evolution. 13: 232‒235.

Horton, R.E. 1933. The role of infiltration in the hydrologic cycle. Transactions of the 

American Geophysical Union. 14: 446‒460.

Hubbert, K.R.; Preisler, H.K.; Wohlgemuth, P.M.; Graham, R.C.; Narog, M.G. 2006. 

Prescribed burning effects on soil physical properties and soil water repellency in a 

steep chaparral watershed, southern California, USA. Geoderma. 130: 284‒298.

Huffman, E.L.; MacDonald, L.H.; Stednick, J.D. 2001. Strength and persistence of fireinduced hydrophobicity under ponderosa and lodgepole pine, Colorado Front Range. 

Hydrological Processes. 15: 2877‒2892.

Hull, A.C., Jr. 1965. Cheatgrass—a persistent homesteader. In: Proceedings, cheatgrass 

symposium; 1965 July 27-30; Vale, OR. Portland, OR: U.S. Department of the Interior, 

Oregon Bureau of Land Management: 20‒26.

Hull, A.C., Jr. 1972. Rainfall and snowfall interception of big sagebrush. Utah Academy 

of Science, Arts, and Letters. 49: 64.

Hull, A.C., Jr.; Klomp, G.J. 1974. Yield of crested wheatgrass under four densities of 

big sagebrush in southern Idaho. U.S. Department of Agriculture Tech. Bull. 1438. 

Washington, DC: U.S. Department of Agriculture, Agricultural Research Service. 70 p.

Hultine, K.H.; Cable, W.L.; Burgess, S.S.O.; Williams, D.B. 2003a. Hydraulic 

redistribution by deep roots of a Chihuahuan Desert phreatophyte. Tree Physiology. 

23: 353‒360.

Hultine, K.H.; Scott, R.L.; Cable, W.L.; Goodrich, D.C.; Williams, D.G. 2004. Hydraulic 

redistribution by a dominant, warm desert phreatophyte: Seasonal patterns and 

response to precipitation pulses. Functional Ecology. 18: 530‒538.

Hultine, K.H.; Williams, D.G.; Burgess, S.S.O.; Keefer, T.O. 2003b. Contrasting patterns 

of hydraulic redistribution in three desert phreatophytes. Oecologia. 135: 167‒175.

Hutchinson, B.A. 1965. Snow accumulation and disappearance influenced by big 

sagebrush. Res. Note RM-RN-46. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Forest and Range Experiment Station. 7 p.
92 USDA Forest Service RMRS-GTR-351. 2016.

Huxman, T.E.; Wilcox, B.P.; Breshears, D.D.; Scott, R.L.; Snyder, K.A.; Small, E.E.; 

Hultine, K.; Pockman, W.T.; Jackson, R.B. 2005. Ecohydrological implications of 

woody plant encroachment. Ecology. 86: 308‒319.

Imeson, A.C.; Lavee, H.; Calvo, A.; Cerdà, A. 1998. The erosional response of calcareous 

soils along a climatological gradient in southeast Spain. Geomorphology. 24: 3‒16.

Imeson, A.C.; Verstraten, J.M.; van Mulligen, E.J.; Sevink, J. 1992. The effects of fire and 

water repellency on infiltration and runoff under Mediterranean type forest. Catena. 

19: 345‒361.

Inbar, M.; Tamir, M.; Wittenberg, L. 1998. Runoff and erosion processes after a forest fire 

in Mount Carmel, a Mediterranean area. Geomorphology. 24: 17‒33.

Inbar, M.; Wittenberg, L.; Tamir, M. 1997. Soil erosion and forestry management after 

wildfire in a Mediterranean woodland, Mt. Carmel, Israel. International Journal of 

Wildland Fire. 7: 285‒294.

Ishikawa, C.M.; Bledsoe, C.S. 2000. Seasonal and diurnal patterns of soil water potential 

in the rhizospere of blue oaks: Evidence for hydraulic lift. Oecologia. 125: 459‒465.

Jackson, R.B.; Sperry, J.S.; Dawson, T.E. 2000. Root water uptake and transport: Using 

physiological processes in global predictions. Trends in Plant Science. 5: 624‒632.

Jaramillo, D.F.; Dekker, L.W.; Ritsema, C.J.; Hendrickx, J.M.H. 2000. Occurrence of soil 

water repellency in arid and humid climates. Journal of Hydrology. 231‒232: 105‒111.

Joffre, R.; Rambal, S. 1993. How tree cover influences the water balance of 

Mediterranean rangelands. Ecology. 74: 570‒582.

Johansen, M.P.; Hakonson, T.E.; Breshears, D.D. 2001. Post-fire runoff and erosion from 

rainfall simulation: Contrasting forests with shrublands and grasslands. Hydrological 

Processes. 15: 2953‒2965.

Johnson, C.W.; Blackburn, W.H. 1989. Factors contributing to sagebrush rangeland soil 

loss. Transactions of the American Society of Agricultural Engineers. 32: 155‒160.

Johnson, C.W.; Gordon, N.D. 1988. Runoff and erosion from rainfall simulator plots on 

sagebrush rangeland. Transactions of the American Society of Agricultural Engineers. 

31: 421‒427.

Johnson, C.W.; Smith, J.P. 1978. Sediment characteristics and transport from Northwest 

Rangeland Watersheds. Transactions of the American Society of Agricultural 

Engineers. 21: 1157‒1163.

Julien, P.Y. 1998. Erosion and sedimentation. Cambridge, UK: Cambridge University 

Press. 300 p.

Keane, R.E.; Agee, J.K.; Fule, P.; Keeley, J.E.; Key, C.; Kitchen, S.G.; Miller, R.; Schulte, 

L.A. 2008. Ecological effects of large fires on US landscapes: Benefit or catastrophe? 

International Journal of Wildland Fire. 17: 696‒712.

Keeley, J.E. 2009. Fire intensity, fire severity and burn severity: a brief review and 

suggested usage. International Journal of Wildland Fire. 18: 116–126.

Kinnell, P.I.A.1988. The influence of flow discharge on sediment concentrations in 

raindrop induced flow transport. Australian Journal of Soil Research. 26: 575‒582.
USDA Forest Service RMRS-GTR-351. 2016. 93

Kinnell, P.I.A. 1990. The mechanics of raindrop-induced flow transport. Australian 

Journal of Soil Research. 28: 497‒516.

Kinnell, P.I.A. 1991. The effect of flow depth on sediment transport induced by raindrops 

impacting shallow flows. Transactions of the American Society of Agricultural 

Engineers. 34: 161‒168.

Kinnell, P.I.A. 1993. Sediment concentrations resulting from flow depth/drop size 

interactions in shallow overland flow. Transactions of the American Society of 

Agricultural Engineers. 36: 1099‒1103.

Kinnell, P.I.A. 2005. Raindrop-impact-induced erosion processes and prediction: A 

review. Hydrological Processes. 19: 2815‒2844.

Klade, R.J. 2006. Building a research legacy—the Intermountain Station 1911-1997. Gen. 

Tech. Rep. RMRS-GTR-184. Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station. 259 p.

Knapp, B.J. 1978. Infiltration and storage of soil water. In: Kirby, M.J., ed. Hillslope 

hydrology. Norwich, UK: John Wiley and Sons, Ltd.: 43‒72.

Knapp, P.A. 1996. Cheatgrass (Bromus tectorum L.) dominance in the Great Basin desert. 

Global Environmental Change. 6: 37‒52.

Knight, R.W.; Blackburn, W.H.; Merrill, L.B. 1984. Characteristics of oak mottes, 

Edwards Plateau, Texas. Journal of Range Management. 37: 534‒537.

Knighton, D. 1998. Fluvial forms and processes: A new perspective. London, UK: 

Arnold. 400 p.

Kramer, P.J.; Boyer, J.S. 1995. Water relations of plants and soils. London, UK: 

Academic Press. 495 p.

Larsen, I.J.; MacDonald, L.H.; Brown, E.; Rough, D.; Welsh, M.J. 2009. Causes of postfire runoff and erosion: water repellency, cover, or soil sealing. Soil Science Society of 

America Journal. 73: 1393‒1407.

Lavee, H.; Kutiel, P.; Segev, M.; Benyamini, Y. 1995. Effects of surface roughness on 

runoff and erosion in Mediterranean ecosystems: The role of fire. Geomorphology. 11: 

227‒234.

Lebron, I.; Madsen, M.D.; Chandler, D.G.; Robinson, D.A.; Wendroth, O.; Belnap, J. 

2007. Ecohydrological controls on soil moisture and hydraulic conductivity within a 

pinyon-juniper woodland. Water Resources Research. 43: W08422.

Leffler, A.J.; Peek, M.S.; Ryel, R.J.; Ivans, C.Y.; Caldwell, M.M. 2005. Hydraulic 

redistribution through the root systems of senesced plants. Ecology. 86: 633‒642.

Leffler, A.J.; Ryel, R.J.; Hipps, L.; Ivans, S.; Caldwell, M.M. 2002. Carbon acquisition 

and water use in a northern Utah Juniperus osteosperma (Utah juniper) population. 

Tree Physiology. 22: 1221‒1230.

Leighton-Boyce, G.; Doerr, S.H.; Shakesby, R.A.; Walsh, R.P.D. 2007. Quantifying 

the impact of soil water repellency on overland flow generation and erosion: A new 

approach using rainfall simulation and wetting agent on in situ soil. Hydrological 

Processes. 21: 2337‒2345.
94 USDA Forest Service RMRS-GTR-351. 2016.

Leighton-Boyce, G.; Doerr, S.H.; Shakesby, R.A.; Walsh, R.P.D.; Ferreira, A.J.D.; Boulet, 

A.K.; Coelho, C.D.A. 2005. Temporal dynamics of water repellency and soil moisture 

in eucalypt plantations, Portugal. Australian Journal of Soil Research. 43: 269‒280.

Lentile, L.B.; Holden, Z.A.; Smith, A.M.S.; Falkowski, M.J.; Hudak, A.T.; Morgan, P.; 

Lewis, S.A.; Gessler, P.E.; Benson, N.C. 2006. Remote sensing techniques to assess 

active fire characteristics and post-fire effects. International Journal of Wildland Fire. 

15: 319‒345.

Letey, J.; Osborn, J.; Pelishek, R.E. 1962. The influence of the water-solid contact angle 

on water movement in soil. Bulletin International Association Scientific Hydrology. 3: 

75‒81.

Lewis, S.A.; Wu, J.Q.; Robichaud, P.R. 2006. Assessing burn severity and comparing soil 

water repellency, Hayman Fire, Colorado. Hydrological Processes. 20: 1‒16.

Link, S.O.; Keeler, C.W.; Hill, R.W.; Hagen, E. 2006. Bromus tectorum cover mapping 

and fire risk. International Journal of Wildland Fire. 15: 113‒119.

Liston, G.E.; McFadden, J.P.; Sturm, M.; Pielke, R.A., Sr. 2002. Modelled changes in 

arctic tundra snow, energy and moisture fluxes due to increased shrubs. Global Change 

Biology. 8: 17‒32.

Liston, G.E.; Sturm, M. 1998. A snow-transport model for complex terrain. Journal of 

Glaciology. 44: 498‒516.

Johnson, C.W.; Blackburn, W.H. 1989. Factors contributing to sagebrush rangeland soil 

loss. Transactions of the American Society of Agricultural Engineers. 32: 155‒160.

Llorens, P.; Domingo, F. 2007. Rainfall partitioning by vegetation under Mediterranean 

conditions. A review of studies in Europe. Journal of Hydrology. 335: 37‒54.

Luce, C.H.; Tarboton, D.G.; Cooley, K.R. 1998. The influence of the spatial distribution 

of snow basin-average snowmelt. Hydrological Processes. 12: 1671‒1683.

Ludwig, F.; Dawson, T.E.; Kroon, H.; Berendse, F.; Prins, H.H.T. 2003. Hydraulic lift in 

Acacia tortilis on an East African savanna. Oecologia. 134: 293‒300.

Ludwig, F.; Dawson, T.E.; Prins, H.H.T.; Berendse, F.; de Kroon, H. 2004. Below-ground 

competition between trees and grasses may overwhelm the facilitative effects of 

hydraulic lift. Ecology Letters. 7: 623‒631.

Ludwig, J.A.; Tongway, D.J. 1995. Spatial organisation of landscapes and its function in 

semi-arid woodlands, Australia. Landscape Ecology. 10: 51‒63.

Ludwig, J.A.; Tongway, D.J. 2000. Viewing rangelands as landscape systems. In: 

Arnalds, O.; Archer, S., eds. Rangeland desertification. Dordrecht, the Netherlands: 

Kluwer Academic Publishers: 39‒52.

Ludwig, J.A.; Tongway, D.J.; Freudenberger, D.O.; Noble, J.C.; Hodgkinson, K.C. 1997. 

Landscape ecology, function, and management: Principles from Australia’s rangelands. 

Melbourne, Australia: CSIRO Publishing. 158 p.

Ludwig, J.A.; Wiens, J.A.; Tongway, D.J. 2000. A scaling rule for landscape patches and 

how it applies to conserving soil resources in savannas. Ecosystems. 3: 84‒97.
USDA Forest Service RMRS-GTR-351. 2016. 95

Ludwig, J.A.; Wilcox, B.P.; Breshears, D.D.; Tongway, D.J.; Imeson, A.C. 2005. 

Vegetation patches and runoff-erosion as interacting ecohydrological processes in 

semiarid landscapes. Ecology. 86: 288‒297.

MacDonald, L.H.; Huffman, E.L. 2004. Post-fire soil water repellency: Persistence and 

soil moisture thresholds. Soil Science Society of America Journal. 68: 1729‒1734.

Mack, R.N. 1981. Invasion of Bromus tectorum L. into western North America: An 

ecological chronicle. Agro-Ecosystems. 7: 145‒165.

Madsen, M.D.; Chandler, D.G.; Belnap, J. 2008. Spatial gradients in ecohydrological 

properties within a pinyon-juniper ecosystem. Ecohydrology. 43(8): 349‒360.

Maidment, D.R. 1993. Hydrology. In: Maidment, D.R., ed. Handbook of hydrology. New 

York: McGraw-Hill, Inc.: 1.1‒1.3.

Marks, D.; Link, T.; Winstral, A.; Garen, D. 2001. Simulating snowmelt processes during 

rain-on-snow over a semi-arid mountain basin. Annals of Glaciology. 32: 195‒202.

Marks, D.; Winstral, A. 2001. The effect of variable patterns of snow deposition and 

drifting on snowmelt, runoff, and stream discharge in a semi-arid mountain basin. In: 

Proceedings of the Western Snow Conference; 2001 April 1619; Sun Valley, Idaho. 

Western Snow Conference Proceedings 69: 127‒130.

Marks, D.; Winstral, A.; Seyfried, M. 2002. Simulation of terrain and forest shelter effects 

on patterns of snow deposition, snowmelt, and runoff over a semi-arid mountain 

catchment. Hydrological Processes. 16: 3605‒3626.

Martínez-Mena, M.; Alvarez Rogel, J.; Albaladejo, J.; Castillo, V.M. 1999. Influence of 

vegetal cover on sediment size distribution in natural rainfall conditions in a semiarid 

environment. Catena. 38: 175‒190.

Martínez-Meza, E.; Whitford, W.G. 1996. Stemflow, throughflow, and channelization of 

stemflow by roots in three Chihuahuan desert shrubs. Journal of Arid Environments. 

32: 271‒287.

Martínez-Zavala, L.; Jordán, A. 2008. Effect of rock fragment cover on interrill soil 

erosion from bare soils in Western Andalusia, Spain. Soil Use and Management. 

24:108‒117.

Mataix-Solera, J.; Cerdà, A.; Arcenegui, V.; Jordán, A.; Zavala, L.M. 2011. Fire effects on 

soil aggregation: a review. Earth-Science Reviews. 109: 44‒60.

Mataix-Solero, J.; Guerrero, C.; García-Orenes, F.; Bárcenas, G.M.; Pilar Torres, M. 

2009. Forest fire effects on soil microbiology. In: Cerdà, A.; Robichaud, P.R., eds. 

Fire effects on soils and restoration strategies. Land Reconstruction and Management 

Series, Volume 5. Enfield, NH: Science Publishers: 133‒176.

McCuen, R.H. 2004. Hydrologic analysis and design. Upper Saddle River, NJ: PrenticeHall, Inc. 888 p.

McCulley, R.L.; Jobbagy, E.G.; Pockman, W.T.; Jackson, R.B. 2004. Nutrient uptake as a 

contributing explanation for deep rooting in arid and semi-arid ecosystems. Oecologia. 

141: 620‒628.

McNamara, J.P.; Chandler, D.; Seyfried, M.; Achet, S. 2005. Soil moisture states, 

lateral flow, and streamflow generation in a semi-arid, snowmelt-driven catchment. 

Hydrological Processes. 19: 4023‒4038.
96 USDA Forest Service RMRS-GTR-351. 2016.

Meeuwig, R.O. 1970. Infiltration and soil erosion as influenced by vegetation and soil in 

northern Utah. Journal of Range Management. 23: 185‒188.

Meeuwig, R.O. 1971. Infiltration and water repellency in granitic soils. Res. Pap. INT111. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest 

and Range Experiment Station. 20 p.

Meinzer, F.C.; Brooks, J.R.; Bucci, S.; Goldstein, G.; Scholz, F.G.; Warren, J.M. 2004. 

Converging patterns of uptake and hydraulic redistribution of soil water in contrasting 

woody vegetation. Tree Physiology. 24: 919‒928.

Meinzer, F.C.; Clearwater, M.J.; Goldstein, G. 2001. Water transport in trees: Current 

perspectives, new insights and some controversies. Environmental and Experimental 

Botany. 45: 239‒262.

Mendel, M.; Hergarten, S.; Neugebauer, H.J. 2002. On a better understanding of 

hydraulic lift: A numerical study. Water Resources Research. 38: 1183–1192. doi: 

10.1029/2001WR000911.

Mendez, A.; Goodrich, D.D.; Osborn, H.B. 2003. Rainfall point intensities in an air mass 

thunderstorm environment: Walnut Gulch, Arizona. Journal of the American Water 

Resources Association. 39: 611‒621.

Meyer, G.A.; Pierce, J.L.; Wood, S.H.; Jull, A.J.T. 2001. Fire, storms, and erosional 

events in the Idaho batholiths. Hydrological Processes. 15: 3025‒3038.

Michaelides, K.; Lister, D.; Wainwright, J.; Parsons, A.J. 2009. Vegetation controls 

on small-scale runoff and erosion dynamics in a degrading dryland environment. 

Hydrological Processes. 23: 1617‒1630.

Miller, R.F.; Chambers, J.C.; Pyke, D.A.; Pierson, F.B.; Williams, C.J. 2013. A review of 

fire effects on vegetation and soils in the Great Basin Region: Response and ecological 

site characteristics. Gen. Tech. Rep. RMRS-GTR-308. Fort Collins, CO: UT: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station. 126 p.

Miller, R.F.; Tausch, R.J. 2001. The role of fire in juniper and pinyon woodlands: A 

descriptive analysis. In: Galley, K.E.M.; Wilson, T.P., eds. Proceedings of the invasive 

species workshop: The role of fire in the control and spread of invasive species. 

Fire Conference 2000: The first national congress on fire ecology, prevention, and 

management; 2000 November 27–December 1; San Diego, CA. Misc. Publ. No. 11. 

Tallahassee, FL: Tall Timbers Research Station: 15‒30.

Miller, R.F.; Tausch, R.J.; McArthur, E.D.; Johnson, D.J; Sanderson, S.C. 2008. Age 

structure and expansion of piñon-juniper woodlands: A regional perspective in the 

Intermountain West. Res. Pap. RMRS-RP-69. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 15 p.

Moffet, C.A.; Pierson, F.B.; Robichaud, P.R.; Spaeth, K.E.; Hardegree, S.P. 2007. 

Modeling soil erosion on steep sagebrush rangeland before and after prescribed fire. 

Catena. 71: 218‒228.

Montaña, C.; Cavagnaro, B.; Briones, O. 1995. Soil water use by co-existing shrubs and 

grasses in the Southern Chihuahuan Desert, Mexico. Journal of Arid Environments. 

31: 1‒13.
USDA Forest Service RMRS-GTR-351. 2016. 97

Moody, J.A.; Martin, D.A. 2001. Initial hydrologic and geomorphic response following 

a wildfire in the Colorado Front Range. Earth Surface Processes and Landforms. 26: 

1049‒1070.

Moran, M.S.; Scott, R.L.; Keefer, T.O.; Emmerich, W.E.; Hernandez, M.; Nearing, 

G.S.; Paige, G.B.; Cosh, M.H.; O’Neill, P.E. 2009. Partitioning evapotranspiration 

in semiarid grassland and shrubland ecosystems using time series of soil surface 

temperature. Agricultural and Forest Meteorology. 149: 59‒72.

Morris, S.E.; Moses, T.A. 1987. Forest fire and the natural soil erosion regime in the 

Colorado Front Range. Annals—Association of American Geographers. 77: 245‒254.

Moss, A.J. 1991. Rain-impact soil crust: I. Formation on a granite-derived soil. Australian 

Journal of Soil Research. 29: 271‒289.

Moss, A.J.; Green, P. 1983. Movement of solids in air and water by rain drop impact: 

Effects of drop-size and water-depth variations. Australian Journal of Soil Research. 

21: 257‒269.

Muñoz, M.R.; Squeo, F.A.; León, M.F.; Tracol, Y.; Gutiérrez, J.R. 2008. Hydraulic lift in 

three shrub species from the Chilean coastal desert. Journal of Arid Environments. 72: 

624‒632.

Mutchler, C.K.; Murphree, C.E.; McGregor, K.C. 1988. Laboratory and field plots for 

soil erosion studies. In: Lal, R., ed. Soil erosion research methods. Ankeny, IA: Soil 

and Water Conservation Society: 9‒39.

Návar, J.; Bryan, R. 1990. Interception loss and rainfall redistribution by three semi-arid 

growing shrubs in northeastern Mexico. Journal of Hydrology. 115: 51‒63.

Nearing, M.A.; Foster, G.R.; Lane, L.J.; Finkner, S.C. 1989. A process-based soil erosion 

model for USDA Water Erosion Prediction Project technology. Transactions of the 

American Society of Agricultural Engineers. 32: 1587‒1593.

Nearing, M.A.; Nichols, N.H.; Stone, J.J.; Renard, K.G.; Simanton, J.R. 2007. Sediment 

yields from unit-source semiarid watersheds at Walnut Gulch. Water Resources 

Research. 43: W06426.

Nearing, M.A.; Norton, L.D.; Bulgakov, D.A.; Larionov, G.A.; West, L.T.; Dontsova, 

K.M. 1997. Water hydraulics and erosion in eroding rills. Water Resources Research. 

33: 865‒876.

Nearing, M.A.; Simanton, J.R.; Norton, L.D.; Bulygin, S.J.; Stone, J. 1999. Soil erosion 

by surface water flow on a stony, semiarid hillslope. Earth Surface Processes and 

Landforms. 24: 677‒686.

Nearing, M.A.; Wei, H.; Stone, J.J.; Pierson, F.B.; Spaeth, K.E.; Weltz, M.A.; Flanagan, 

D.C.; Hernandez, M. 2011. A rangeland hydrology and erosion model. Transactions of 

the American Society of Agricultural and Biological Engineers. 54: 901‒908.

Neary, D.G.; Klopatek, C.C.; DeBano, L.F.; Ffolliott, P.F. 1999. Fire effects on 

belowground sustainability: A review and synthesis. Forest Ecology and Management. 

122: 51‒71.

Neary, D.G.; Koestner, K.A.; Youberg, A.; Koestner, P.E. 2012. Post-fire rill and gully 

formation, Schultz Fire 2010, Arizona, USA. Geoderma. 191: 97‒104.
98 USDA Forest Service RMRS-GTR-351. 2016.

Newman, B.D.; Campbell, A.R.; Wilcox, B.P. 1997. Tracer-based studies of soil water 

movement in semi-arid forests of New Mexico. Journal of Hydrology. 196: 251‒270.

O’Dea, M.E.; Guertin, D.P. 2003. Prescribed fire effects on erosion parameters in a 

perennial grassland. Journal for Range Management. 56: 27‒32.

Onda, Y.; Dietrich, W.E.; Booker, F. 2008. Evolution of overland flow after a severe 

forest fire, Point Reyes, California. Catena. 72: 13‒20.

Osborn, H.B. 1964. Effect of storm duration on runoff from rangeland watersheds in the 

semiarid southwestern United States. International Association of Scientific Hydrology 

IX. 4: 40–47.

Osborn, H.B. 1983a. Precipitation characteristics affecting hydrological response of 

south-western rangelands. Agricultural Reviews and Manuals, Western Series 34. 

Oakland, CA: U.S. Department of Agriculture, Agricultural Research Service. 55 p.

Osborn, H.B. 1983b. Timing and duration of high rainfall rates in the Southwestern 

United States. Water Resources Research. 19: 1036‒1042.

Osborn, H.B.; Lane, L.J. 1969. Precipitation-runoff relations for very small semiarid 

rangeland watersheds. Water Resources Research. 5: 419‒425.

Osborn, H.B.; Renard, K.G. 1988. Rainfall intensities for Southeastern Arizona. Journal 

of Irrigation and Drainage Engineering. 114: 195‒199.

Owens, M.K.; Lyons, R.K.; Alejandro, C.L. 2006. Rainfall partitioning within semiarid 

juniper communities: Effects of event size and canopy cover. Hydrological Processes. 

20: 3179‒3189.

Parsons, A.; Robichaud, P.R.; Lewis, S.A.; Napper, C.; Clark, J.T. 2010. Field guide for 

mapping post-fire soil burn severity. Gen. Tech. Rep. RMRS-GTR-243. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research 

Station. 49 p.

Parsons, A.J.; Abrahams, A.D.; Simanton, J.R. 1992. Microtopography and soil-surface 

materials on semi-arid piedmont hillslopes, southern Arizona. Journal of Arid 

Environments. 22: 107‒115.

Parsons, A.J.; Abrahams, A.D.; Wainwright, J. 1994. Rainsplash and erosion rates in an 

interrill area on semi-arid grassland, Southern Arizona. Catena. 22: 215‒226.

Parsons, A.J.; Abrahams, A.D.; Wainwright, J. 1996. Responses of interrill runoff and 

erosion rates to vegetation change in southern Arizona. Geomorphology. 14: 311‒317.

Peláez, D.V.; Distel, R.A.; Bóo, R.M.; Elia, O.R.; Mayor, M.D. 1994. Water relations 

between shrubs and grasses in semi-arid Argentina. Journal of Arid Environments. 27: 

71‒78.

Peters, E.F.; Bunting, S.C. 1994. Fire conditions pre- and post-occurrence of annual 

grasses on the Snake River Plain. In: Monsen, S.B.; Kitchen, S.G., eds. Proceedings—

ecology and management of annual rangelands. Gen. Tech. Rep. INT-GTR-313. 

Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and 

Range Experiment Station: 31‒36.

Pierson, F.B.; Bates, J.D.; Svejcar, T.J.; Hardegree, S.P. 2007a. Runoff and erosion after 

cutting western juniper. Rangeland Ecology and Management. 60: 285‒292.
USDA Forest Service RMRS-GTR-351. 2016. 99

Pierson, F.B.; Blackburn, W.H.; Van Vactor, S.S. 2007b. Hydrologic impacts of 

mechanical seeding treatments on sagebrush rangelands. Rangeland Ecology and 

Management. 60: 666‒674.

Pierson, F.B.; Blackburn, W.H.; Van Vactor, S.S.; Wood, J.C. 1994a. Partitioning 

small scale spatial variability of runoff and erosion on sagebrush rangelands. Water 

Resources Bulletin. 30: 1081‒1089.

Pierson, F.B.; Carlson, D.H.; Spaeth, K.E. 2002b. Hydrologic impacts of fire on steep 

intermountain sagebrush-steppe rangeland. International Journal of Wildland Fire. 11: 

145‒151.

Pierson, F.B.; Moffet, C.A.; Williams, C.J.; Hardegree, S.P.; Clark, P.E. 2009. Prescribedfire effects on rill and interrill runoff and erosion in a mountainous sagebrush 

landscape. Earth Surface Processes and Landforms. 34: 193‒203.

Pierson, F.B.; Robichaud, P.R.; Moffet, C.A.; Spaeth, K.E.; Hardegree, S.P.; Clark, 

P.E.; Williams, C.J. 2008a. Fire effects on rangeland hydrology and erosion in a steep 

sagebrush-dominated landscape. Hydrological Processes. 22: 2916‒2929.

Pierson, F.B.; Robichaud, P.R.; Moffet, C.A.; Spaeth, K.E.; Williams, C.J.; Hardegree, 

S.P.; Clark, P.E. 2008b. Soil water repellency and infiltration in coarse-textured soils of 

burned and unburned sagebrush ecosystems. Catena. 74: 98‒108.

Pierson, F.B.; Robichaud, P.R.; Spaeth, K.E. 2001a. Spatial and temporal effects of 

wildfire on the hydrology of a steep rangeland watershed. Hydrological Processes. 15: 

2905‒2916.

Pierson, F.B.; Slaughter, C.W.; Cram, Z.K. 2001b. Long-term stream discharge and 

suspended-sediment database, Reynolds Creek Experimental Watershed, Idaho, United 

States. Water Resources Research. 37: 2857‒2861.

Pierson, F.B.; Spaeth, K.E.; Weltz, M.A.; Carlson, D.H. 2002a. Hydrologic response of 

diverse western rangelands. Journal of Range Management. 55: 558‒570.

Pierson, F.B.; Van Vactor, S.S.; Blackburn, W.H.; Wood, J.C. 1994b. Incorporating 

small scale spatial variability into predictions of hydrologic response on sagebrush 

rangelands. In: Blackburn, W.H.; Pierson, F.B.; Schuman, G.E.; Zartman, R., eds. 

Variability in rangeland water erosion processes. Soil Science Society of America 

Special Publication 38. Madison, WI: Soil Science Society of America: 23‒33.

Pierson, F.B.; Wight, J.R. 1991. Variability of near-surface soil temperature on sagebrush 

rangeland. Journal of Range Management. 44: 491‒497.

Pierson, F.B.; Williams, C.J.; Hardegree, S.P.; Clark, P.E.; Kormos, P.R.; Al-Hamdan, 

O.Z. 2013. Hydrologic and erosion responses of sagebrush steppe following juniper 

encroachment, wildfire, and tree-cutting. Rangeland Ecology and Management. 66: 

274‒289.

Pierson, F.B.; Williams, C.J.; Hardegree, S.P.; Weltz, M.A.; Stone, J.J.; Clark, P.E. 2011. 

Fire, plant invasions, and erosion events on western rangelands. Rangeland Ecology 

and Management. 64: 439‒449.

Pierson, F.B.; Williams, C.J.; Kormos, P.R.; Al-Hamdan, O.Z. 2014. Short-term effects 

of tree removal on infiltration, runoff, and erosion in woodland-encroached sagebrush 

steppe. Rangeland Ecology and Management. 67: 522–538.
100 USDA Forest Service RMRS-GTR-351. 2016.

Pierson, F.B.; Williams, C.J.; Kormos, P.R.; Hardegree, S.P.; Clark, P.E.; Rau, B.M. 

2010. Hydrologic vulnerability of sagebrush steppe following pinyon and juniper 

encroachment. Rangeland Ecology and Management. 63: 614‒629.

Pierson, T.C. 1986. Flow behaviour of channelized debris flows, Mount St. Helens, 

Washington. In: Abrahams, A.D., ed. Hillslope processes. Boston, MA: Allen and 

Unwin: 269‒296.

Poesen, J.; Ingelmo-Sanchez, F. 1992. Runoff and sediment yield from topsoils with 

different porosity as affected by rock fragment cover and position. Catena. 19: 

451‒474.

Poesen, J.; Ingelmo-Sanchez, F.; Mücher, H. 1990. The hydrological response of soil 

resources to rainfall as affected by cover and position of rock fragments in the top 

layer. Earth Surface Processes and Landforms. 15: 653‒671.

Poesen, J.W.; Torri, D.; Bunte, K. 1994. Effects of rock fragments on soil erosion by 

water at different spatial scales: A review. Catena. 23: 141‒166.

Pomeroy, J.W.; Gray, D.M. 1995. Snowcover: Accumulation, relocation and 

management. National Hydrology Research Institute Science Report No. 7. Saskatoon, 

Saskatchewan, Canada: National Hydrology Research Institute. 144 p.

Pressland, A.J. 1973. Rainfall partitioning by an arid woodland (Acacia aneura F. Muell.) 

in South-West Queensland. Australian Journal of Botany. 21: 235‒245.

PRISM Climate Group. 2011. PRISM climate data. Corvallis, OR: Oregon State 

University, Northwest Alliance for Computational Science and Engineering. http://

prism.oregonstate.edu [Accessed March 22, 2011].

Puigdefábregas, J. 2005. The role of vegetation patterns in structuring runoff and 

sediment fluxes in drylands. Earth Surface Processes and Landforms. 30: 133‒147.

Puigdefábregas, J.; del Barrio, G.; Boer, M.M.; Gutiérrez, L.; Solé, A. 1998. Differential 

responses of hillslope and channel elements to rainfall events in a semi-arid area. 

Geomorphology. 23(2): 337‒351.

Puigdefábregas, J.; Sole, A.; Gutierrez, L.; del Barrio, G.; Boer, M. 1999. Scales and 

processes of water redistribution in drylands: Results from the Rambla Honda field site 

in southeast Spain. Earth Science Reviews. 48: 37‒70.

Pyke, D.A.; Herrick, J.E.; Shaver, P.; Pellant, M. 2002. Rangeland health attributes and 

indicators for qualitative assessment. Journal of Range Management. 55: 584‒597.

Querejeta, J.I.; Egerton-Warburton, L.M.; Allen, M.F. 2003. Direct nocturnal water 

transfer from oaks to their mycorrhizal symbionts during severe soil drying. 

Oecologia. 134: 55‒64.

Querejeta, J.I.; Egerton-Warburton, L.M.; Allen, M.F. 2007. Hydraulic lift may buffer 

rhizosphere hyphae against the negative effects of severe soil drying in a California 

oak savanna. Soil Biology and Biochemistry. 39: 409‒417.

Rango, A.; Tartowski, S.L.; Laliberte, A.; Wainwright, J.; Parsons, A. 2006. Islands of 

hydrologically enhanced biotic productivity in natural and managed arid ecosystems. 

Journal of Arid Environments. 65: 235‒252.
USDA Forest Service RMRS-GTR-351. 2016. 101

Ravi, S.; D’Odorico, P.; Zobeck, T.M.; Oliver, T.M.; Collins, S.L. 2007. Feedbacks 

between fires and wind erosion in heterogeneous arid lands. Journal of Geophysical 

Research: Biogeosciences. 112: G04007. doi: 10.1029/2007jg000474.

Reid, K.D.; Wilcox, B.P.; Breshears, D.D.; MacDonald, L. 1999. Runoff and erosion in 

a piñon-juniper woodland: Influence of vegetation patches. Soil Science Society of 

America Journal. 63: 1869‒1879.

Renard, K.G. 1988. Water resources of small impoundments in dry regions. In: Thames, 

J.L.; Ziebell, C.D., eds. Small water impoundments in semiarid regions. Albuquerque, 

NM: University of New Mexico Press: 1–20.

Renard, K.G.; Lane, L.J.; Simanton, J.R.; Emmerich, W.E.; Stone, J.J.; Weltz, M.A.; 

Goodrich, D.C.; Yakowitz, D.S. 1993. Agricultural impacts in an arid environment: 

Walnut Gulch case study. Hydrological Science and Technology. 9: 145‒190.

Reynolds, J.F.; Kemp, P.R.; Tenhunen, J.D. 2000. Effects of long-term rainfall variability 

on evapotranspiration and soil water distribution in the Chihuahuan Desert: A 

modeling analysis. Plant Ecology. 150: 145‒159.

Reynolds, J.F.; Virginia, R.A.; Kemp, P.R.; De Soyza, A.G.; Tremmel, D.C. 1999. Impact 

of drought on desert shrubs: Effects of seasonality and degree of resource island 

development. Ecological Monographs. 69(1): 69‒106.

Rice, P.M.; McPherson, G.R.; Rew, L.J. 2008. Fire and nonnative invasive plants in the 

Interior West Bioregion. In: Zouhar, K.; Smith, J.K.; Sutherland, S.; Brooks, M.L., 

eds. Wildland fire in ecosystems: Fire and nonnative invasive plants. Gen. Tech. Rep. 

RMRS-GTR-42-vol. 6. Ogden, UT: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station: 141‒171.

Richards, J.H.; Caldwell, M.M. 1987. Hydraulic lift: Substantial nocturnal water transport 

between soil layers by Artemisia tridentata roots. Oecologia. 73: 486‒489.

Ritsema, C.J.; Dekker, L.W. 1994. How water moves in a water repellent sandy soil. 2. 

Dynamics of fingered flow. Water Resources Research. 30: 2519‒2531.

Ritsema, C.J.; Dekker, L.W. 1995. Distribution flow: A general process in the top layer of 

water repellent soils. Water Resources Research. 31: 1187‒1200.

Ritsema, C.J.; Dekker, L.W. 1996. Water repellency and its role in forming preferred flow 

paths in soils. Australian Journal of Soil Research. 34: 475‒487.

Ritsema, C.J.; Dekker, L.W.; Hendrickx, J.M.H.; Hamminga, W. 1993. Preferential flow 

mechanism in a water repellent sandy soil. Water Resources Research. 29: 2183‒2193.

Ritsema, C.J.; Dekker, L.W.; van den Elsen, E.G.M.; Oostindiel, K.; Steenhuis, T.S.; 

Nieber, J.L. 1997. Recurring fingered flow pathways in a water repellent sandy field 

soil. Hydrology and Earth System Sciences. 1: 777‒786.

Ritsema, C.J.; Nieber, J.L.; Dekker, L.W.; Steenhuis, T.S. 1998a. Modeling and field 

evidence of finger formation and finger recurrence in a water repellent sandy soil. 

Water Resources Research. 34(4): 555‒567.

Ritsema, C.J.; Nieber, J.L.; Dekker, L.W.; Steenhuis, T.S. 1998b. Stable or unstable 

wetting fronts in water repellent soils—effect of antecedent soil moisture content. Soil 

and Tillage Research. 47: 111‒123.
102 USDA Forest Service RMRS-GTR-351. 2016.

Robichaud, P.R. 2000. Fire effects on infiltration rates after prescribed fire in northern 

Rocky Mountain forests, USA. Journal of Hydrology. 231‒232: 220‒229.

Robichaud, P.R.; Ashmun, L.E.; Sims, B.D. 2010. Post-fire treatment effectiveness for 

hillslope stabilization. Gen. Tech. Rep. RMRS-GTR-240. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station. 62 p.

Robichaud, P.R.; Brown, R.E. 2002. Silt fences: An economical technique for measuring 

hillslope soil erosion. Gen. Tech. Rep. RMRS-GTR-94. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky Mountain Research Station. 24 p.

Robichaud, P.R.; Elliot, W.J.; Pierson, F.B.; Hall, D.E.; Moffet, C.A. 2007a. Predicting 

postfire erosion and mitigation effectiveness with a web-based probabilistic erosion 

model. Catena. 71: 229‒241.

Robichaud, P.R.; Elliot, W.J.; Pierson, F.B.; Hall, D.E.; Moffet, C.A.; Ashmun, L.E. 

2007b. Erosion Risk Management Tool (ERMiT) user manual (version 2006.01.18). 

Gen. Tech. Rep. RMRS-GTR-188. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station. 24 p.

Robinson, D.A.; Lebron, I.; Ryel, R.J.; Jones, S.B. 2010. Soil water repellency: A method 

of soil moisture sequestration in pinyon-juniper woodland. Soil Science Society of 

America Journal. 74: 624‒634.

Romme, W.H.; Allen, C.D.; Bailey, J.D.; Baker, W.L.; Bestelmeyer, B.T.; Brown, P.M.; 

Eisenhart, K.S.; Floyd, M.L.; Huffman, D.W.; Jacobs, B.F.; Miller, R.F.; Muldavin, 

E.H.; Swetnam, T.W.; Tausch, R.J.; Weisberg, P.J. 2009. Historical and modern 

disturbance regimes, stand structures, and landscape dynamics in piñon-juniper 

vegetation of the western United States. Rangeland Ecology and Management. 62: 

203‒222.

Roundy, B.A.; Blackburn, W.H.; Eckert, R.E., Jr. 1978. Influence of prescribed burning 

on infiltration and sediment production in the pinyon-juniper woodland, Nevada. 

Journal of Range Management. 31: 250–253.

Rowe, P.B. 1948. Influence of woodland chaparral on water and soil in central California. 

[N.p.]: State of California Department of Natural Resources, Division of Forestry, in 

cooperation with the U.S. Department of Agriculture, Forest Service, California Forest 

and Range Experiment Station. 70 p.

Ryel, R.J.; Caldwell, M.M.; Leffler, A.J.; Yoder, C.Y. 2003. Rapid soil moisture recharge 

to depth by roots in a stand of Artemisia tridentata. Ecology. 84: 757‒764.

Ryel, R.J.; Caldwell, M.M.; Manwaring, J.H. 1996. Temporal dynamics of soil spatial 

heterogeneity in sagebrush-wheatgrass steppe during a growing season. Plant and Soil. 

184: 299‒309.

Ryel, R.J.; Caldwell, M.M.; Yoder, C.K.; Or, D.; Leffler, A.J. 2002. Hydraulic 

redistribution in a stand of Artemisia tridentata: Evaluation of benefits to transpiration 

assessed with a simulation model. Oecologia. 130: 173‒184.

Ryel, R.J.; Leffler, A.J.; Peek, M.S.; Ivans, C.Y.; Caldwell, M.M. 2004. Water 

conservation in Artemisia tridentata through redistribution of precipitation. Oecologia. 

141: 335‒345.
USDA Forest Service RMRS-GTR-351. 2016. 103

Salles, C.; Poesen, J. 2000. Rain properties controlling soil splash detachment. 

Hydrological Processes. 14: 271‒282.

Salles, C.; Poesen, J.; Govers, G. 2000. Statistical and physical analysis of soil 

detachment by raindrop impact: Rain erosivity indices and threshold energy. Water 

Resources Research. 36: 2721‒2729.

Salles, C.; Poesen, J.; Sempere-Torres, D. 2002. Kinetic energy of rain and its functional 

relationship with intensity. Journal of Hydrology. 257: 256‒270.

Sankey, J.B.; Germino, M.J.; Glenn, N.F. 2009. Aeolian sediment transport following 

wildfire in sagebrush steppe. Journal of Arid Environments. 73: 912‒919.

Savage, S.M. 1974. Mechanism of fire-induced water repellency in soils. Proceedings of 

the Soil Science Society of America. 38: 652‒657.

Savage, S.M.; Osborn, J.; Letey, J.; Helton, C. 1972. Substances contributing to fire 

induced water repellency in soils. Soil Science Society of America Proceedings. 36: 

674‒678.

Schenk, H.J.; Jackson, R.B. 2002. Rooting depths, lateral root spreads and below-ground/

above-ground allometries of plants in water-limited ecosystems. Journal of Ecology. 

90: 480‒494.

Schlesinger, W.H.; Abrahams, A.D.; Parsons, A.J.; Wainwright, J. 1999. Nutrient losses 

in runoff from grassland and shrubland habitats in Southern New Mexico: I. Rainfall 

simulation experiments. Biogeochemistry. 45: 21‒34.

Schlesinger, W.H.; Raikes, J.A.; Hartley, A.E.; Cross, A.F. 1996. On the spatial pattern of 

soil nutrients in desert ecosystems. Ecology. 77: 364‒374.

Schlesinger, W.H.; Reynolds, J.F.; Cunningham, G.L.; Huenneke, L.F.; Jarrell, W.M.; 

Virginia, R.A.; Whitford, W.G. 1990. Biological feedbacks in global desertification. 

Science. 247: 1043‒1048.

Schlesinger, W.H.; Ward, T.J.; Anderson, J. 2000. Nutrient losses in runoff from grassland 

and shrubland habitats in southern New Mexico: II. Field plots. Biogeochemistry. 49: 

69‒86.

Schmidt, R.A.; Gluns, D.R. 1991. Snowfall interception on branches of three conifer 

species. Canadian Journal of Forest Research. 21: 1262‒1269.

Scholes, R.J.; Archer, S.R. 1997. Tree-grass interactions in savannas. Annual Review of 

Ecology and Systematics. 28: 517‒544.

Scholl, D.G. 1971. Soil wettability in Utah juniper stands. Soil Science Society of 

America Proceedings. 35(2): 344‒345.

Scholl, D.G. 1975. Soil wettability and fire in Arizona chaparral. Soil Science Society of 

America Proceedings. 39: 356‒361.

Schulze, E.-D.; Caldwell, M.M.; Canadell, J.; Mooney, H.A.; Jackson, R.B.; Parson, D.; 

Scholes, R.; Sala, O.E.; Trimborn, P. 1998. Downward flux of water through roots 

(i.e., inverse hydraulic lift) in dry Kalahari sands. Oecologia. 115: 460‒462.

Scott, D.F.; Van Wyk, D.B. 1990. The effects of wildfire on soil wettability and 

hydrological behaviour of an afforested catchment. Journal of Hydrology. 121: 

239‒256.
104 USDA Forest Service RMRS-GTR-351. 2016.

Scott, K.M. 1988. Origins, behavior, and sedimentology of lahars and lahar-runout flows 

in the Toutle-Cowlitz River system, Mount St. Helens, Washington. United States 

Geological Survey, Professional Paper 1447-A. 74 p.

Scott, R.L.; Cable, W.L.; Hultine, K.R. 2008. The ecohydrologic significance of hydraulic 

redistribution in a semiarid savanna. Water Resources Research. 44: W02440. doi: 

10.1029/2007WR006149.

Scott, R.L.; Huxman, T.E.; Cable, W.L.; Emmerich, W.E. 2006. Partitioning of 

evapotranspiration and its relation to carbon dioxide exchange in a Chihuahuan Desert 

shrubland. Hydrological Processes. 20: 3227‒3243.

Selby, M.J. 1993. Hillslope materials and processes. New York: Oxford University Press, 

Inc. 480 p.

Serrato, F.B.; Diaz, A.R. 1998. A simple technique for measuring rainfall interception by 

small shrub: “Interception flow collection box.” Hydrological Processes. 12: 471‒481.

Seyfried, M.S. 1991. Infiltration patterns from simulated rainfall on a semiarid rangeland 

soil. Soil Science Society of America Journal. 55: 1726‒1736.

Seyfried, M.S.; Flerchinger, G.N. 1994. Influence of frozen soil on rangeland erosion. In: 

Variability of rangeland water and erosion processes. Special Publ. 38. Madison, WI: 

Soil Science Society of America: 67‒82.

Seyfried, M.S.; Grant, L.E.; Marks, D.; Winstral, A.; McNamara, J. 2009. Simulated 

soil water storage effects on streamflow generation in a mountainous snowmelt 

environment, Idaho, USA. Hydrological Processes. 23: 858‒873.

Seyfried, M.S.; Wilcox, B.P. 1995. Scale and the nature of spatial variability: Field 

examples having implications for hydrologic modeling. Water Resources Research. 31: 

173‒184.

Shakesby, R.A. 2011. Post-wildfire soil erosion in the Mediterranean: Review and future 

research directions. Earth-Science Reviews. 105: 71‒100.

Shakesby, R.A.; Coelho, C.D.A.; Ferreira, A.D.; Terry, J.P.; Walsh, R.P.D. 1993. Wildfire 

impacts on soil erosion and hydrology in wet Mediterranean forests, Portugal. 

International Journal of Wildland Fire. 3: 95‒110.

Shakesby, R.A.; Doerr, S.H. 2006. Wildfire as a hydrological and geomorphological 

agent. Earth-Science Reviews. 74: 269‒307.

Shakesby, R.A.; Doerr, S.H.; Walsh, R.P.D. 2000. The erosional impact of soil 

hydrophobicity: Current problems and future research directions. Journal of 

Hydrology. 231‒232: 178‒191.

Sharma, P.P.; Gupta, S.C.; Rawls, W.J. 1991. Soil detachment by single raindrops of 

varying kinetic energy. Soil Science Society of America Journal. 55: 301‒307.

Sidle, R.C.; Pearce, A.J.; O’Loughlin, C.L. 1985. Hillslope stability and land use. Water 

Resource Monograph Series, Vol. 11. Washington, DC: American Geophysical Union. 

140 p.

Skau, C.M. 1964. Interception, throughfall, and stemflow in Utah and alligator juniper 

cover types in northern Arizona. Forest Science. 10: 283‒287.
USDA Forest Service RMRS-GTR-351. 2016. 105

Slaughter, C.W.; Pierson, F.B. 2000. Sediment yield and hydrology in northwestern 

rangelands. International Journal of Sediment Research. 15: 253‒259.

Slaughter, D.J., Jr. 1997. Throughfall, stemflow, and infiltration rates of Juniperus ashei

on the Edwards Plateau, Texas. Austin, TX: University of Texas. Master’s thesis. 

120 p.

Smith, D.M.; Jackson, N.A.; Roberts, J.M.; Ong, C.K. 1999. Reverse flow in tree roots 

and downward siphoning of water by Grevillea robusta. Functional Ecology. 13: 

256‒264.

Spigel, K.M.; Robichaud, P.R. 2007. First-year post-fire erosion rates in Bitterroot 

National Forest, Montana. Hydrological Processes. 21: 998‒1005.

Stannard, D.I.; Weltz, M.A. 2006. Partitioning evapotranspiration in sparsely vegetated 

rangeland using a portable chamber. Water Resources Research. 42: W02413.

Stone, J.J.; Nichols, M.H.; Goodrich, D.C.; Buono, J. 2008. Long-term runoff database, 

Walnut Gulch, Experimental Watershed, Arizona, United States. Water Resources 

Research. 44: W05S05.

Storck, P.; Lettenmaier, D.P.; Bolton, S.M. 2002. Measurement of snow interception and 

canopy effects on snow accumulation and melt in a mountainous maritime climate, 

Oregon, United States. Water Resources Research. 38: 5‒1 to 5‒16.

Sturm, M.; McFadden, J.P.; Liston, G.E.; Chapin, F.S., III; Racine, C.H.; Holmgren, 

J. 2001. Snow-shrub interactions in arctic tundra: A hypothesis with climatic 

implications. Journal of Climate. 336‒344.

Taucer, P.I.; Munster, C.L.; Wilcox, B.P.; Owens, M.K.; Mohanty, B.P. 2008. Large-scale 

rainfall simulation experiments of juniper rangelands. Transactions of the American 

Society of Agricultural and Biological Engineers. 51: 1951‒1961.

Tausch, R.J. 1999. Historic pinyon and juniper woodland development. In: Monsen, 

S.B.; Stevens, R., comps. Proceedings: Ecology and management of pinyon-juniper 

communities within the Interior West; 1997 September 15‒18; Provo, UT. Proc. 

RMRS-P-9. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky 

Mountain Research Station: 12‒19.

Tausch, R.J.; Hood, S. 2007. Pinyon/juniper woodlands. In Hood, S.M.; Miller, M., eds. 

Fire ecology and management of the major ecosystems of southern Utah. Gen. Tech. 

Rep. RMRS-GTR-202. Fort Collins, CO: U.S. Department of Agriculture, Forest 

Service, Rocky Mountain Research Station: 57‒71.

Terry, J.P.; Shakesby, R.A. 1993. Soil hydrophobicity effects on rainsplash: Simulated 

rainfall and photographic evidence. Earth Surface Processes and Landforms. 18: 

519‒525.

Thornes, J.B. 1980. Erosional processes of running water and their spatial and temporal 

controls: A theoretical viewpoint. In: Kirkby, M.J.; Morgan, R.P.C., eds. Soil erosion. 

Norwich, UK: John Wiley and Sons, Ltd.: 129‒182.

Thornes, J.B. 1994. Catchment and channel hydrology. In: Abrahams, A.D.; Parsons, 

A.J., eds. Geomorphology of desert environments. London, UK: Chapman and Hall: 

257‒287.
106 USDA Forest Service RMRS-GTR-351. 2016.

Thurow, T.L.; Blackburn, W.H.; Taylor, C.A., Jr. 1986. Hydrologic characteristics of 

vegetation types as affected by livestock grazing systems, Edwards Plateau, Texas. 

Journal of Range Management. 39: 505‒509.

Thurow, T.L.; Blackburn, W.H.; Taylor, C.A., Jr. 1988. Infiltration and interrill erosion 

responses to selective livestock grazing strategies, Edwards Plateau, Texas. Journal of 

Range Management. 41: 296‒302.

Thurow, T.L.; Blackburn, W.H.; Warren, S.D.; Taylor, C.A., Jr. 1987. Rainfall interception 

by midgrass, shortgrass, and live oak mottes. Journal of Range Management. 40: 

455‒460.

Thurow, T.L.; Hester, J.W. 1997. How an increase or a reduction in juniper cover alters 

rangeland hydrology. In: 1997 Juniper Symposium; 1997 January 9–10; Texas 

Agricultural Experiment Station, San Angelo, TX. Tech. Report 97-1. College Station, 

TX: Texas A&M University: 9‒22.

Tiedemann, A.R.; Conrad, C.E.; Dieterich, J.H. 1979. Effects of fire on water. A state-ofknowledge review. Gen. Tech. Rep. WO-GTR-10. Washington, DC: U.S. Department 

of Agriculture, Forest Service. 28 p.

Tongway, D.J.; Ludwig, J.A. 1990. Vegetation and soil patterning in semi-arid mulga 

lands of eastern Australia. Australian Journal of Ecology. 15: 23‒34.

Tongway, D.J.; Ludwig, J.A. 1997. The conservation of water and nutrients within 

landscapes. In: Ludwig, J.A.; Tongway, D.J.; Freudenberger, D.O.; Noble, J.C.; 

Hodgkinson, K.C., eds. Landscape ecology, function, and management: Principles 

from Australia’s rangelands. Melbourne, Australia: CSIRO Publishing: 13‒22.

Tongway, D.J.; Ludwig, J.A.; Whitford, W.G. 1989. Mulga log mounds: Fertile patches 

in the semi-arid woodlands of eastern Australia. Australian Journal of Ecology. 14: 

263‒268.

Toy, T.J.; Foster, G.R.; Renard, K.G. 2002. Soil erosion: Processes, prediction, 

measurement, and control. New York: John Wiley and Sons, Inc. 352 p.

Tromble, J.M. 1983. Interception of rainfall by tarbush. Journal of Range Management. 

36: 525‒526.

Tromble, J.M. 1988. Water interception by two arid land shrubs. Journal of Arid 

Environments. 15: 65–70.

Tromble, J.M.; Renard, K.G.; Thatcher, A.P. 1974. Infiltration for three rangeland soil 

vegetation complexes. Journal of Range Management. 27: 318‒321.

Turnbull, L.; Wainwright, J.; Brazier, R.E. 2010a. Changes in hydrology and erosion over 

a transition from grassland to shrubland. Hydrological Processes. 24: 393‒414.

Turnbull, L.; Wainwright, J.; Brazier, R.E.; Bol, R. 2010b. Biotic and abiotic changes in 

ecosystem structure over a shrub-encroachment gradient in the Southwestern USA. 

Ecosystems. 13: 1239‒1255.

Turnbull, L.; Wilcox, B.P.; Belnap, J.; Ravi, S.; D’Odorico, P.; Childers, D.; Gwenzi, 

W.; Okin, G.; Wainwright, J.; Caylor, K.K.; Sankey, T. 2012. Understanding the role 

of ecohydrologic feedbacks in ecosystem state change in drylands. Ecohydrology. 5: 

174‒183.
USDA Forest Service RMRS-GTR-351. 2016. 107

USDA Agricultural Research Service. 2011a. Long-term climate, precipitation, and 

stream discharge-sediment yield databases, Reynolds Creek Experimental Watershed, 

Idaho, United States. ftp://ftp.nwrc.ars.usda.gov/publicdatabase/reynoldscreek/ 

[Accessed March 23, 2011].

USDA Agricultural Research Service. 2011b. Long-term meteorological, precipitation, 

and runoff databases, Walnut Gulch Experimental Watershed, Arizona, United States. 

http://www.tucson.ars.ag.gov/dap/Default.htm [Accessed March 23, 2011].

U.S. Geological Survey. 2011. NLCD land cover 2006. Sioux Falls, SD: U.S. Department 

of the Interior, U.S. Geological Survey. http://www.mrlc.gov/nlcd2006_downloads.php 

[Accessed March 22, 2011].

Valentin, C. 1994. Surface sealing as affected by various rock fragment covers in West 

Africa. Catena. 23: 87‒97.

Van Dijk, A.I.J.M.; Bruijnzeel, L.A.; Rosewell, C.J. 2002. Rainfall intensity-kinetic 

energy relationships: a critical literature appraisal. Journal of Hydrology. 261: 1‒23.

Verheijen, F.G.A.; Cammeraat, L.H. 2007. The association between three dominant shrub 

species and water repellent soils along a range of soil moisture contents in semi-arid 

Spain. Hydrological Processes. 21: 2310‒2316.

Wainwright, J. 2006. Climate and climatological variations. In: Havstad, K.M.; 

Huenneke, L.F.; Schlesinger, W.H.; eds. Structure and function of a Chihuahuan Desert 

ecosystem: The Jornada Basin Long-Term Ecological Research Site. Long Term 

Ecological Research Network Series. New York: Oxford University Press: 44‒80.

Wainwright, J.; Parsons, A.J.; Abrahams, A.D. 1999. Rainfall energy under creosotebush. 

Journal of Arid Environments. 43: 111‒120.

Wainwright, J.; Parsons, A.J.; Abrahams, A.D. 2000. Plot-scale studies of vegetation, 

overland flow and erosion interactions: Case studies from Arizona and New Mexico. 

Hydrological Processes. 14: 2921‒2943.

Wainwright, J.; Parsons, A.J.; Schlesinger, W.H.; Abrahams, A.D. 2002. Hydrologyvegetation interactions in areas of discontinuous flow on a semi-arid bajada, Southern 

New Mexico. Journal of Arid Environments. 51: 319‒338.

Walter, H. 1971. Ecology of tropical and subtropical vegetation. Edinburgh, Scotland: 

Oliver and Boyd. 688 p.

Wan, C.; Sosebee, R.E.; McMichael, B.L. 1993. Does hydraulic lift exist in shallowrooted species? A quantitative examination with a half-shrub Gutierrezia sarothrae. 

Plant and Soil. 153: 11‒17.

Wells, C.G.; Campbell, R.E.; DeBano, L.F.; Lewis, C.E.; Fredrickson, R.L.; Franklin, 

E.C.; Froelich, R.C.; Dunn, P.H.1979. Effects of fire on soil: A state-of-the-knowledge 

review. Gen. Tech. Rep. WO-7. Washington, DC: U.S. Department of Agriculture, 

Forest Service. 34 p.

Weltz, M.A.; Blackburn, W.H. 1995. Water budget for south Texas rangelands. Journal of 

Range Management. 48: 45‒52.

West, N.E.; Gifford, G.F. 1976. Rainfall interception by cool-desert shrubs. Journal of 

Range Management. 29: 171‒172.
108 USDA Forest Service RMRS-GTR-351. 2016.

Westerling, A.L.; Hidalgo, H.G.; Cayan, D.R.; Swetnam, T.W. 2006. Warming and earlier 

spring increase western U.S. forest wildfire activity. Science. 313: 940‒943.

Whisenant, S.G. 1990. Changing fire frequencies on Idaho’s Snake River plains: 

Ecological and management implications. In: McArthur, E.D.; Romney, E.M.; 

Smith, S.D.; Tueller, P.T., comps. Proceedings—symposium on cheatgrass invasion, 

shrub die-off, and other aspects of shrub biology and management. 1989 April 5–7; 

Las Vegas, NV. Gen. Tech. Rep. INT-GTR-276. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Research Station: 4‒10.

Whitford, W.G.; Anderson, J.; Rice, P.M. 1997. Stemflow contribution to the “fertile 

island” effect in creosotebush, Larrea tridentata. Journal of Arid Environments. 35: 

451‒457.

Wilcox, B.P. 1994. Runoff and erosion in intercanopy zones of pinyon-juniper 

woodlands. Journal of Range Management. 47: 285‒295.

Wilcox, B.P.; Breshears, D.D. 1995. Hydrology and ecology of piñon-juniper woodlands: 

Conceptual framework and field studies. In: Shaw, D.W.; Aldon, E.J.; LoSapio, C., eds. 

Desired future conditions for pinyon-juniper ecosystems; 1994 August 8–12; Flagstaff, 

AZ. Gen. Tech. Rep. RM-258. Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Forest and Range Experimental Station: 109‒119.

Wilcox, B.P.; Breshears, D.D.; Allen, C.D. 2003a. Ecohydrology of a resource-conserving 

semiarid woodland: Effects of scale and disturbance. Ecological Monographs. 73: 

223‒239.

Wilcox, B.P.; Breshears, D.D.; Seyfried, M.S. 2003b. Water balance on rangelands. 

Encyclopedia of Water Science. doi: 10.1081/E-EWS 120010097.

Wilcox, B.P.; Breshears, D.D.; Turin, H.J. 2003c. Hydraulic conductivity in a piñonjuniper woodland: Influence of vegetation. Soil Science Society of America Journal. 

67: 1243‒1249.

Wilcox, B.P.; Dowhower, S.L.; Teague, W.R.; Thurow, T.L. 2006. Long-term water 

balance in a semiarid shrubland. Rangeland Ecology and Management. 59: 600‒606.

Wilcox, B.P.; Hanson, C.L.; Wight, J.R.; Blackburn, W.H. 1989. Sagebrush rangeland 

hydrology and evaluation of the SPUR hydrology model. Water Resources Bulletin. 

25: 653‒666.

Wilcox, B.P.; Huang, Y.; Walker, J.W. 2008. Long-term trends in streamflow from 

semiarid rangelands: Uncovering drivers of change. Global Change Biology. 14: 

1676‒1689.

Wilcox, B.P.; Newman, B.D.; Brandes, D.; Davenport, D.W.; Reid, K. 1997. Runoff from 

a semiarid ponderosa pine hillslope in New Mexico. Water Resources Research. 33: 

2301‒2314.

Wilcox, B.P.; Pitlick, J.; Allen, C.D.; Davenport, D.W. 1996. Runoff and erosion from 

a rapidly eroding pinyon-juniper hillslope. In: Anderson, M.G.; Brooks, S.M., eds. 

Advances in hillslope processes, Volume 1. New York: John Wiley and Sons, Ltd.: 

61‒77.
USDA Forest Service RMRS-GTR-351. 2016. 109

Wilcox, B.P.; Seyfried, M.S.; Cooley, K.R.; Hanson, C.H. 1991. Runoff characteristics of 

sagebrush rangelands: Modeling implications. Journal of Soil and Water Conservation. 

46: 153‒158.

Wilcox, B.P.; Thurow, T.L. 2006. Preface: Emerging issues in rangeland ecohydrology. 

Hydrological Processes. 20: 3155‒3157.

Wilcox, B.P.; Wood, M.K.; Tromble, J.M. 1988. Factors influencing infiltrability of 

semiarid mountain slopes. Journal of Range Management. 41: 197‒206.

Williams, C.J.; McNamara, J.P.; Chandler, D.G. 2009. Controls on the temporal and 

spatial variability of soil moisture in a mountainous landscape: The signatures of snow 

and complex terrain. Hydrology and Earth System Science. 13: 1325‒1336.

Williams, C.J.; Pierson, F.B.; Al-Hamdan, O.Z.; Kormos, P.R.; Hardegree, S.P.; Clark, 

P.E. 2014a. Can wildfire serve as an ecohydrologic threshold-reversal mechanism on 

juniper-encroached shrublands. Ecohydrology. 7: 453‒477. doi: 10.1002/eco.1364.

Williams, C.J.; Pierson, F.B.; Robichaud, P.R.; Boll, J. 2014b. Hydrologic and erosion 

responses to wildfire along the rangeland-xeric forest continuum in the western US: A 

review and model of hydrologic vulnerability. International Journal of Wildland Fire. 

23: 155‒172.

Williams, C.J.; Pierson, F.B.; Robichaud, P.R.; Al-Hamdan, O.Z.; Boll, J.; Strand, E.K. 

2016a. Structural and functional connectivity as a driver of hillslope erosion following 

disturbance. International Journal of Wildland Fire. 25(3): 306‒321. doi: 10.1071/

WF14114.

Williams, C.J.; Pierson, F.B.; Spaeth, K.E.; Brown, J.R.; Al-Hamdan, O.Z.; Weltz, M.A.; 

Nearing, M.A.; Herrick, J.E.; Boll, J.; Robichaud, P.R.; Goodrich, D.C.; Heilman, 

P.; Guertin, D.P.; Hernandez, M.; Wei, H.; Hardegree, S.P.; Strand, E.K.; Bates, J.D.; 

Metz, L.J.; Nichols, M.H. 2016b. Incorporating hydrologic data and ecohydrologic 

relationships into Ecological Site Descriptions. Rangeland Ecology and Management. 

69(1): 4‒19.

Winstral, A.; Marks, D. 2002. Simulating wind fields and snow redistribution using 

terrain-based parameters to model snow accumulation and melt over a semi-arid 

mountain catchment. Hydrological Processes. 16: 3585‒3603.

Witter, J.V.; Jungerius, P.D.; ten Harkel, M.J. 1991. Modelling water erosion and the 

impact of water-repellency. Catena. 18: 115‒124.

Wood, M.K.; Blackburn, W.H. 1981. Grazing systems: Their influence on infiltration 

rates in the Rolling Plains of Texas. Journal of Range Management. 34: 331‒335.

Wood, M.K.; Blackburn, W.H.; Eckert, R.E., Jr.; Peterson, F.F. 1978. Interrelations of 

the physical properties of coppice dune and vesicular dune interspace soils with grass 

seedling emergence. Journal of Range Management. 31: 189‒192.

Wood, M.K.; Jones, T.L.; Vera-Cruz, M.T. 1998. Rainfall interception by selected plants 

in the Chihuahuan Desert. Journal of Range Management. 51: 91‒96.

Woods, S.W.; Balfour, V.N. 2008. The effect of ash on runoff and erosion after a severe 

forest wildfire, Montana, USA. International Journal of Wildland Fire. 17: 535‒548.

Woods, S.W.; Birkas, A.; Ahl, R. 2007. Spatial variability of soil hydrophobicity after 

wildfires in Montana and Colorado. Geomorphology. 86: 465‒479.
110 USDA Forest Service RMRS-GTR-351. 2016.

Wright, H.A.; Bailey, A.W. 1982. Fire ecology: United States and Southern Canada. New 

York: Wiley and Sons. 501 p.

Yoder, C.K.; Nowak, R.S. 1999a. Hydraulic lift among native plant species in the Mojave 

Desert. Plant and Soil. 95: 93‒102.

Yoder, C.K.; Nowak, R.S. 1999b. Soil moisture extraction by evergreen and droughtdeciduous shrubs in the Mojave Desert during wet and dry years. Journal of Arid 

Environments. 42: 81‒96.

Young, J.A.; Evans, R.A. 1978. Population dynamics after wildfires in sagebrush 

grasslands. Journal of Range Management. 31: 283‒289.

Young, R.A.; Wiersma, J.L. 1973. The role of rainfall impact in soil detachment and 

transport. Water Resources Research. 9: 1629‒1636.

Zhang, L.; Dawes, W.R.; Walker, G.R. 2001. Response of mean annual evapotranspiration 

to vegetation changes at catchment scale. Water Resources Research. 37: 701‒708.

Zou, C.B.; Barnes, P.W.; Archer, S.; McMurtry, C.R. 2005. Soil moisture redistribution as 

a mechanism of facilitation in savanna tree-shrub clusters. Oecologia. 145: 32‒40.

United States Department of Agriculture

Forest Service

Rocky Mountain Research Station

In accordance with Federal civil rights law and U.S. Department of Agriculture (USDA) civil rights regulations and policies, the USDA, its Agencies, offices, and employees, and institutions participating in or 

administering USDA programs are prohibited from discriminating based on race, color, national origin, 

religion, sex, gender identity (including gender expression), sexual orientation, disability, age, marital status, family/parental status, income derived from a public assistance program, political beliefs, or reprisal 

or retaliation for prior civil rights activity, in any program or activity conducted or funded by USDA (not 

all bases apply to all programs). Remedies and complaint filing deadlines vary by program or incident.

Persons with disabilities who require alternative means of communication for program information (e.g., 

Braille, large print, audiotape, American Sign Language, etc.) should contact the responsible Agency or 

USDA’s TARGET Center at (202) 720-2600 (voice and TTY) or contact USDA through the Federal Relay 

Service at (800) 877-8339. Additionally, program information may be made available in languages other 

than English.

To file a program discrimination complaint, complete the USDA Program Discrimination Complaint 

Form, AD-3027, found online at http://www.ascr.usda.gov/complaint_filing_cust.html and at any USDA 

office or write a letter addressed to USDA and provide in the letter all of the information requested in 

the form. To request a copy of the complaint form, call (866) 632-9992. Submit your completed form or 

letter to USDA by: (1) mail: U.S. Department of Agriculture, Office of the Assistant Secretary for Civil 

Rights, 1400 Independence Avenue, SW, Washington, D.C. 20250-9410; (2) fax: (202) 690-7442; or (3) 

email: program.intake@usda.gov. 

To learn more about RMRS publications or search our online titles:

www.fs.fed.us/rm/publications

www.treesearch.fs.fed.us/