United States Department of Agriculture / Forest Service

Rocky Mountain Research Station

Research Paper RMRS-RP-77

September 2009

Three Years of Hillslope 

Sediment Yields Following the 

Valley Complex Fires, 

Western Montana

Peter R. Robichaud

Joseph W. Wagenbrenner

Robert E. Brown

Kevin M. Spigel
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Robichaud, Peter R.; Wagenbrenner, Joseph W.; Brown, Robert E.; Spigel, Kevin M. 

2009. Three years of hillslope sediment yields following the Valley Complex fires, 

western Montana. Res. Pap. RMRS-RP-77. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research Station. 8 p.

Abstract

The 2000 Bitterroot Valley wildfires provided an opportunity to measure post-fire 

effects and recovery rates. We established 24 small (0.01 ha [0.02 acre]) plots in 

four high-severity burn sites. We measured sediment yields at each site with silt 

fences. We also measured rainfall characteristics, soil water repellency, vegetative 

cover, and other site characteristics. The median sediment yield in post-fire year 1 

was 8 Mg ha-1 yr-1 (3.6 ton acre-1 yr-1), and values ranged from 0.3 to 47 Mg ha-1 yr-1

(0.1 to 21 ton acre-1 yr-1). Sediment yields were lower in post-fire years 2 and 3, 

with medians of 2 and 0.3 Mg ha-1 yr-1 (0.9 and 0.1 ton acre-1 yr-1), respectively. 

The high variability in sediment yields was related to 10-minute maximum rainfall 

intensity (I

10), but not to soil water repellency or vegetative cover. The results of this 

study may assist in decisions about post-wildfire land management.

Keywords: erosion, rainfall intensity, soil water repellency, vegetative recovery, 

post-fire

Authors

Peter R. Robichaud is a research engineer with the Air, Watershed, and Aquatic 

Environments Program at the Forestry Sciences Laboratory of the Rocky Mountain 

Research Station (U.S. Department of Agriculture, Forest Service) in Moscow, Idaho.

Joseph W. Wagenbrenner is an engineer with the Air, Watershed, and Aquatic 

Environments Program at the Forestry Sciences Laboratory of the Rocky Mountain 

Research Station (U.S. Department of Agriculture, Forest Service) in Moscow, Idaho.

Robert E. Brown is a hydrologist with the Air, Watershed, and Aquatic 

Environments Program at the Forestry Sciences Laboratory of the Rocky Mountain 

Research Station (U.S. Department of Agriculture, Forest Service) in Moscow, Idaho.

Kevin M. Spigel is an assistant professor of Geoscience at Unity College, in Unity, 

Maine.
Acknowledgments

This work was funded by the U.S. Department of Agriculture and U.S. Department 

of Interior Joint Fire Science Program, and by the U.S. Department of Agriculture 

Forest Service, Rocky Mountain Research Station and Bitterroot National Forest. 

We gratefully acknowledge the many people from the Rocky Mountain Research 

Station and the Bitterroot National Forest who assisted in field data collection.
USDA Forest Service RMRS-RP-77. 2009. 1

Introduction

Wildfires can dramatically affect forested landscapes by removing the canopy and protective forest 

floor components, such as litter and duff. Soil infiltration capacity and structure may also be altered. 

These effects then impact the hydrologic cycle, often producing more frequent and greater quantities of 

overland flow (Robichaud 2000). The increased overland flow also increases sheet, rill, gully, and channel 

erosion rates. Although these effects have long been 

recognized (Hendricks and Johnson 1944), until recently research into the post-fire effects has been 

sparse with large geographic gaps across the western 

United States. Recent research results suggest that 

post-fire erosion rates, as well as recovery of erosion 

rates to pre-fire levels, vary greatly in the diverse ecosystems of the western United States (Robichaud and 

others 2008b).

Research in the western United States has shown 

that post-fire erosion rates can vary by orders of 

magnitude and depend on several factors, including 

burn severity (Benavides-Solorio and MacDonald 

2001, 2005), post-fire rainfall intensity (Inbar and 

others 1998), time since burning (Robichaud and 

Brown 1999; Benavides-Solorio and MacDonald 

2001; Robichaud and others 2008b), and soil 

type (Benavides-Solorio and MacDonald 2005). 

Following the Valley Complex fires of 2000 in the 

Bitterroot Valley of Montana, Robichaud and others 

(2008a) measured sediment yields of 9 to 66 Mg ha-1

yr-1 (4 to 30 ton acre-1 yr-1) (median value of 20 Mg 

ha-1 yr-1 [9 ton acre-1 yr-1]) from four untreated burned 

hillslope plots during the first post-fire year. In another study following the Valley Complex wildfires, 

Spigel and Robichaud (2007) used hillslope plots to 

evaluate soil water repellency and first-year erosion 

rates. They reported event sediment yields of 9 to 82 

Mg ha-1 (4 to 37 ton acre-1) for a rain event with a 

greatest 10-minute rainfall intensity (I10) of 78 mm 

hr-1 (3.1 inch hr-1). Both studies found that the erosion rates increased with an increase in I10 (Spigel 

and Robichaud 2007; Robichaud and others 2008a). 

Robichaud and others (2008b) measured post-fire 

erosion rates from small watersheds (1.4 to 13.3 ha 

[3.5 to 33 acre]) established around the western 

United States. At the Bitterroot Valley site (3.6 ha 

[8.9 acre]), post-fire erosion rates were 0.6 Mg ha-1

(0.3 ton acre-1) in the first post-fire year and between 

0.09 and 0.9 Mg ha-1 (0.04 to 0.4 ton acre-1) in postfire years 2 through 4.

Following the 2000 Valley Complex Fires in 

western Montana, Spigel and Robichaud (2007) established hillslope sites to measure post-fire erosion 

rates. The sites were monitored for two additional 

years to determine the magnitude, variability, and 

short-term (1 to 3 years) recovery of post-fire erosion 

rates in the Bitterroot Valley. Analyses of these data 

provide region-specific, post-fire response information to land managers and researchers.

Methods

In 2000, a series of wildfires burned 144,000 ha 

(356,000 acre) of the Bitterroot Valley of western 

Montana, and about a third of this area burned at 

high severity (U.S. Department of Agriculture 2001). 

We studied the southern portion of the burned area 

(figure 1).

Figure 1—Map of study site locations in western Montana.
2 USDA Forest Service RMRS-RP-77. 2009.

Four steep (50 to 62 percent) (table 1), severely 

burned hillslopes located within a 5-km (3.1-mi) 

radius (figure 1) were selected for measurement of 

hillslope sediment production, rainfall, water repellency, vegetative cover, burn severity index, and stand 

density (Spigel 2002). The sites (1 to 4) were located 

in stands of burned ponderosa pine (Pinus ponderosa) 

and Douglas-fir (Pseudotsuga menziesii) with pre-fire 

understory of pinegrass (Calamagrostis rubescens), 

white spiraea (Spiraea betulifolia), and showy aster (Aster spectabilis) (Spigel and Robichaud 2007). 

The soils at sites 1, 3, and 4 were classified as sandyskeletal, mixed, frigid, typic haplustepts derived from 

granitic colluvium; the soil at site 2 was a loamyskeletal, mixed, superactive, frigid, typic argiustoll 

with a parent material of igneous/metasedimentary 

colluvium (Soil Survey Staff 1999) (table 1). Site elevation ranged from 1620 to 1800 m (5300 to 5900 ft) 

and slope aspects were north, east, northeast, or west 

(table 1). The sites were monitored for three post-fire 

years, from 2001 to 2003.

In each site, six plots measuring 5 m (16 ft) along 

the contour and 20 m (66 ft) along the slope gradient were established on planar hillslopes. We installed 

silt fences at the outlet of each plot to capture eroded 

sediment (Robichaud and Brown 2002). Hand-dug 

trenches, approximately 15 cm (6 inch) wide and 

deep, were installed across the top of each plot to 

prevent overland flow from entering the plot from 

above. We removed and weighed sediment after each 

sediment-producing event in post-fire year 1 and after 

three periods of accumulation in each of the second and third post-fire years. We summed sediment 

production rates by calendar year to produce annual 

production rates. We measured soil moisture on a sediment sample from each silt fence from each period 

of accumulation. The moisture content was used to 

calculate the dry sediment mass for each silt fence. 

Each dry mass was divided by the plot contributing 

area (0.01 ha [0.02 acre]) to produce a unit-area sediment production rate. Several trenches overfilled with 

runoff and sediment during the study; data 

for each of these occurrences were discarded 

since the plot contributing area for the sediment production was unknown.

Soil water repellency was measured in 

2001 using the water drop penetration time 

(WDPT) test (DeBano 1981) at 32 points just 

outside each plot (to avoid additional surface 

disturbance within the plot). Measurements 

were taken at the mineral surface and at 1 cm 

(0.4 inch) depth increments until water repellency was encountered or to a maximum depth of 

5 cm (2 inch). The degree of soil water repellency 

was calculated using the WDPT test results and the 

following classes: none, 0 to 5 seconds; slight, 6 to 

60 seconds; moderate, 61 to 180 seconds; and severe, 

181 to 300 or more seconds (DeBano 1981). We repeated the WDPT measurements in post-fire year 3 at 

eight points adjacent to each plot. Vegetative cover 

was estimated for each plot using an ocular or grid 

method (Spigel and Robichaud 2007). For the ocular 

method (sites 1, 3, 4 and plots 4 through 6 in site 2 in 

post-fire year 1; all plots in post-fire year 2), each plot 

was visually partitioned into areas of equal vegetative cover, the amount of cover was estimated, and 

the aggregate area-weighted vegetative cover was 

calculated. For the grid method (plots 1 through 3 

in site 2 in post-fire year 1 and all plots in post-fire 

year 3), we laid a 1-m by 1-m (3.3-ft by 3.3-ft) frame 

on the ground surface at a randomly selected location in each plot. We visually estimated the amount 

of vegetative cover within the frame (Chambers and 

Brown 1983).

A tipping-bucket rain gauge was installed at each 

site. Individual rain events were defined by at least 

5 minute duration and were separated by at least 

6 hours with no rainfall. For each rain event, the total 

rainfall, 10-minute maximum rainfall intensity (I10), 

and 30-minute maximum rainfall intensity (I30) were 

calculated. If more than one rain event occurred before sediment could be removed from the silt fences, 

the measured sediment was associated with the storm 

that had the greatest I10.

In all but post-fire year 1, the rain events that occurred between May 1 and October 31 were used to 

compare the total number of rain events to the number of sediment-producing events at site 1. Since rain 

gauges were installed the third week of June 2001, 

rain events were monitored over a shorter time frame 

(26 June through 31 October 2001) in post-fire year 1 

than in other years.

Table 1—Mean slope, elevation, aspect, and soil class for each site.

Site Slope (%) Elevation (m) Aspect Soil class

1 62 1710 NE Haplustepta

2 54 1620 W Argiustollb

3 58 1800 N Haplustepta

4 50 1740 E Haplustepta

a

 Haplustept: sandy-skeletal, mixed, frigid, typic haplustept b

 Argiustoll: loamy-skeletal, mixed, typic, superactive argiustoll
USDA Forest Service RMRS-RP-77. 2009. 3

Although the sites were originally selected and 

stratified by burn severity index and tree density, 

these characteristics varied little among the sites 

(Spigel 2002); for this study we treated the site as a 

fixed effect to reflect the original site selection method. We conducted repeated measures analyses on the 

annual sediment yields and the occurrence of each 

WDPT class. In each model, “plot” was the random 

component and “years since burning” and “site” were 

fixed-effects variables (Littel and others 1996). We 

used an autoregressive covariance structure for the 

sediment yield model since measurements were made 

repeatedly on each plot (Littel and others 1996). The 

occurrence of each WDPT class was defined as the 

ratio of the number of drops that were classified in a 

given water repellency class to the overall number of 

drops for that plot and measurement period. For the 

WDPT model, a binomial distribution was assumed 

and an unstructured covariance structure was selected 

(Littel and others 2006). We made pair-wise comparisons in each of these analyses using least-squares 

means (LSMeans) with a Tukey-Kramer adjustment 

(Littel and others 1996). The annual sediment yields 

were log-transformed to increase normality (Ott 

1993). The significance level was 0.05 for all statistical tests. No statistical analyses were conducted on 

the vegetative cover data because of differences in 

methods among years and sites.

Results and 

Discussion

Significant differences existed in the occurrence 

of “slight” soil water repellency in post-fire year 

1. Otherwise, there were no differences in WDPT 

among the four sites in either post-fire year 1 or 3. In 

post-fire year 1, the occurrence of soil water repellency averaged 17 percent in the top 5 cm (2 inch) across 

all sites (table 2). By post-fire year 3, the occurrence 

decreased, although not significantly, to 7 percent. In 

post-fire year 1, the greatest occurrence of soil water repellency occurred at 1 cm (0.4 inch) (figure 2). 

By post-fire year 3, soil water repellency was much 

less, with the greatest occurrence at 5 cm (2 inch) 

(figure 2). This shows that the fire-induced repellency 

diminished over time, which is consistent with other studies (Doerr and others 2006; MacDonald and 

Huffman 2004; Robichaud and others 2008a). Site 2 

had the lowest occurrence of soil water repellency in 

post-fire year 1 (table 2). This may be related to the 

relatively fine soil texture in this site because post-fire 

water repellency generally increases with increasing 

sand fraction (Huffman and others 2001).

The mean amount of vegetative cover in post-fire 

year 1 (25 percent) increased in year 2 (50 percent) 

and year 3 (56 percent) (figure 3). In post-fire year 

1, sites 1 and 3 contained the least vegetative cover 

(16 percent and 13 percent, respectively), but site 3 

contained the most vegetative cover in post-fire years 

2 and 3 (69 percent and 78 percent, respectively). 

These apparent differences in vegetative cover regeneration may reflect pre-fire differences in vegetation 

type and/or density. Because site 3 had a northern aspect and the largest change in vegetative cover over 

the three post-fire years, it is possible that aspect 

played a role in the vegetative recovery. Site 3 also 

had the largest post-fire mean tree diameter of the 

three sites measured (reported as stand 12 in Spigel 

2002). Site 2, with a northeast aspect, had the second 

greatest vegetative recovery rate (figure 3). The other 

two sites had east or west aspects (table 1) and had 

similar, lower vegetative recovery rates.

Table 2—Mean occurrence of soil water repellency (%) by WDPT test (DeBano 1981). Data were summed over 

depths of 0 to 5 cm (0 to 2 inch) for each site in post-fire year 1 (2001) and year 3 (2003). Different letters 

within a column represent significant differences using LSMeans with a Tukey-Kramer adjustment (α = 0.05).

	 Site	 Post-fire year	 None (≤5 s)	 Slight (6-60 s)	 Moderate (61-180 s)a

	 Severe (>180 s)

1 1 76 a 11 abcd 3 10 a

 3 100 a 0 abcde 0 0 a

2 1 90 a 2 e 2 5 a

 3 93 a 4 abcde 0.3 2 a

3 1 78 a 14 b 4 4 a

 3 88 a 10 abcde 3 0.4 a

4 1 86 a 4 cde 3 7 a

 3 92 a 5 abcde 2 1 a

a

 Statistical model results were indeterminate for the moderate group.
4 USDA Forest Service RMRS-RP-77. 2009.

Only a small number of summer (May through 

October) rain events produced sediment. The 

comparison of total number of rain events and 

sediment-producing rain events differed slightly at 

each site; however, data from site 1 adequately represent the general trend. Thus, in site 1 there were 

six sediment-producing rain events out of the 25 that 

occurred during the shortened measurement period of 

post-fire year 1 (26 June through 31 October). Two 

out of 44 rain events produced sediment in post-fire 

year 2, and one out of 39 rain events produced sediment in post-fire year 3. The fact that nearly all the 

hillslope sediment yield came from a small number 

of rain events corroborates other post-fire studies 

(Robichaud and others 2008b).

In post-fire year 1, the average annual sediment 

yields ranged from 0.3 Mg ha-1 (0.1 ton acre-1) in 

site 3 to 47 Mg ha-1 (21 ton acre-1) in site 2, but the 

variability within site 2 was so high that even this 

seemingly large difference was not statistically significant (table 3). Sediment yields were lower in all sites 

in post-fire year 2, but the decline in sediment yields 

from the first post-fire year was only significant in 

site 3, which had the smallest sediment yields in both 

years. Sediment yields were lower again in post-fire 

year 3 in all sites except site 3, but these year-by-year 

declines were also not significant. Although changes 

in sediment yields between post-fire years 1 and 2 and 

between post-fire years 2 and 3 were not significant, 

there were significant reductions in sediment yield 

between post-fire years 1 and 3 in three of the four 

sites. This suggests some recovery in erosion rates 

occurred in the three post-fire years. The relative rank 

of sediment yields by site was the same in all three 

years; sediment yields were greatest in site 2, followed in declining order by sites 1, 4, and 3.

Despite the finer soil texture and lower occurrence 

of soil water repellency at site 2 (table 2), this site 

Figure 2—Occurrence and degree of soil water repellency by soil depth for post-fire year 1 (2001) and post-fire 

year 3 (2003). Measurements were repeated until water repellency was found or to a depth of 5 cm (2 inch). 

Degree was determined using the WDPT test (DeBano 1981) and the following classes: none, 0 to 5 seconds; 

slight, 6 to 60 seconds; moderate, 61 to 180 seconds; and severe, 181 to 300 seconds. The number of drops 

measured is shown next to each bar.
USDA Forest Service RMRS-RP-77. 2009. 5

produced the greatest sediment yields in the study 

(table 3). This was probably because site 2 experienced the greatest I10 values in the first year (75 mm 

hour-1 [3.0 inch hour-1]) (table 3). Lower rainfall intensities in the other sites generally produced lower 

sediment yields (table 3, figure 4), although none of 

these differences was statistically significant. For example, site 3, which had the lowest sediment yields, 

had the smallest maximum I10 value each year and the 

greatest amount of vegetative cover in post-fire years 

2 and 3. The increase in annual sediment yields with 

increasing maximum I10 values (figure 4) was consistent with other research conducted in this region 

(Robichaud and others 2008a,b).

Although the measured I10 values at site 3 were the 

lowest of all sites for each year, the maximum measured value at this site in post-fire year 1 had a 10-year 

return period and the maximum values in post-fire 

years 2 and 3 had 2-year return periods (Miller and 

others 1973). In some areas of the western United 

States such as central Montana, the Colorado Front 

Range, and eastern California, storms with return 

periods of two or more years produced substantially 

more sediment than those in the current study (see 

Fridley, Hayman, and Cannon sites in Robichaud and 

others 2008b). But comparably sized storms in the 

Bitterroot Valley produced similar sediment yields 

to those in this study (see Valley Complex site in 

Robichaud and others 2008b).

Despite our observations of high vegetative cover 

and low sediment yields in site 3 in post-fire years 

2 and 3, the vegetative cover data do not explain 

the site variability in sediment yields in this study. 

Also, soil water repellency does not correlate with 

the sediment yield data as might be expected. There 

probably were subtle site differences (for example, in 

pre- or post-fire soil condition, rainfall intensity, or nonvegetative and vegetative cover) within and among 

the sites that led to the large variability in sediment 

yields. However, of the measured factors, only increases in I10 resulted in increased sediment yields 

(figure 4). It may be that the impact of the I10 overshadowed the impact of other measured factors.

Figure 3—Mean vegetative cover by year and site. We used the grid method with half the plots in site 2 in postfire year 1 and all the plots in post-fire year 3. All other data were from ocular estimates.
6 USDA Forest Service RMRS-RP-77. 2009. Table 3—Total rainfall, I10, I30, and mean sediment yields by date and site for rain events that produced sediment. The maximum I10, maximum I30, and total sediment yield are shown for each year and site in the summary line. Different letters in the summary rows represent significant differences in annual site sediment yields among sites and years using LSMeans with a Tukey-Kramer adjustment (a = 0.05). “n/a” indicates data are not available. Standard deviations are shown in parentheses for individual events. ----------Rainfall----------- (mm) ---------------I10--------------- (mm hr-1) --------------I30--------------- (mm hr-1) --------------------------Sediment yield--------------------------- (Mg ha-1) Date Site 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 27 Jun 2001 9.1 n/a n/a n/a 13.7 n/a n/a n/a 6.1 n/a n/a n/a 0.02 (0.03) 0 (0) 0 (0) 0 (0) 14 Jul 2001 17.0 0 0 4.8 24.4 0 0 10.7 12.2 0 0 3.6 0.09 (0.06) 0 (0) 0 (0) 0.01 (0.003) 15 Jul 2001 4.6 20.1 15.2 1.0 16.8 74.7 18.3 3.0 8.6 35.0 10.7 2.0 0.02 (0.01) 26 (17) 0.03 (0.02) 0.01 (0.004) 20 Jul 2001 30.2 13.0 25.9 20.6 73.2 73.2 50.3 64.0 29.5 25.9 23.4 39.1 10 (n/a)a 21 (17) 0.1 (0.2) 6 (4) 29 Jul 2001 29.5 11.1 30.7 34.8 6.1 19.5 6.1 10.7 4.6 11.0 4.6 8.6 0.07 (0.01) 0.3 (0.2) 0.1 (0.1) 0.5 (0.3) 5 Sep 2001 37.8 11.7 32.0 16.5 6.1 4.6 4.6 9.1 4.6 4.1 3.6 5.6 0.06 (0.08) 0 (0) 0.003 (0.006) 0 (0) Post-fire year 1 summary -----Maximum I10 in 2001---- ----Maximum I30 in 2001---- -----------------------Total sediment in 2001---------------------- 73.2 74.7 50.3 64.0 29.5 35.0 23.4 39.1 10 ab 47 acde 0.3 cdf 6.5 abc 7 May 2002 4.1 19.8 2.3 3.0 4.6 n/a 3.0 4.6 3.6 n/a 1.0 3.0 0 (0) 0.3 (0.4) 0 (0) 0 (0) 19 Jul 2002 25.7 n/a 14.7 21.1 65.5 n/a 33.5 86.9 45.7 n/a 25.9 40.6 2 (2) 1 (2) 0.03 (0.03) 0.7 (1) 6 Aug 2002 0 31.0 0 6.8 0 n/a 0 6.1 0 n/a 0 4.6 0 (0) 22 (16) 0 (0) 0 (0) 15 Aug 2002 4.3 0 0 0 25.9 n/a 0 0 8.6 n/a 0 0 1 (2) 0 (0) 0 (0) 0 (0) Post-fire year 2 summary -----Maximum I10 in 2002----- ----Maximum I30 in 2002---- ------------------------Total sediment in 2002------------------------ 65.5 88.4 33.5 86.9 45.7 39.6 25.9 40.6 3 abcd 23 abcde 0.03 eg 0.7 cdef 1 Apr 2003 17.5 n/a 15.5 15.5 21.3 n/a 15.2 19.8 16.8 n/a 14.2 15.2 0.2 (0.1) 0 (0) 0.2 (0.1) 0 (0) 30 May 2003 14.5 n/a 14.0 13.7 44.2 n/a 39.6 44.2 15.7 n/a 13.7 15.2 0.1 (0.1) 1 (1) 0.03 (0.05) 0.2 (0.4) 3 Aug 2003 8.1 45.5 35.8 7.9 27.4 15.2 29.0 12.2 11.7 5.6 12.2 5.6 0 (0) 0.2 (0.1) 0.07 (0.1) 0 (0) 22 Aug 2003 10.7 9.7 9.9 58.9 12.2 9.1 13.7 47.2 6.1 7.6 7.1 20.3 0 (0) 0 (0) 0 (0) 0.06 (0.1) Post-fire year 3 summary -----Maximum I10 in 2003----- ----Maximum I30 in 2003---- ------------------------Total sediment in 2003------------------------ 44.2 15.2 39.6 47.2 16.8 7.6 14.2 20.3 0.3 cdef 1.2 bfg 0.3 cdf 0.3 def a Data obtained from one silt fence; standard deviation could not be calculated.
USDA Forest Service RMRS-RP-77. 2009. 7

Conclusions

In the four high burn severity sites, the first postfire year erosion rates had a median value of 8 Mg 

ha-1 (3.6 ton acre-1) and ranged from 0.3 to 47 Mg ha-1

(0.1 to 21 ton acre-1). In the second post-fire year, the 

median sediment yield from the four sites was 2 Mg 

ha-1 (0.9 ton acre-1). Although this was a 75 percent 

decline from the first year, this change was not statistically significant because of the high variability in 

sediment yields within and among sites. The median 

sediment yield dropped again in the third post-fire 

year to 0.3 Mg ha-1 (0.1 ton acre-1), which was 85 percent less than the second post-fire year, and was a 

significant decline from the first post-fire year sediment yields in three of the four study sites.

In the first two post-fire years, the annual sediment yields increased with increasing maximum I10. 

Although not rigorously tested, we found no relationship between sediment yield and other measured or 

observed factors, including vegetative cover and soil 

water repellency.

Management 

Implications

Knowledge and prediction of post-fire effects 

influence a myriad of management decisions after wildfire, from immediate stabilization treatment 

prescriptions developed by Burned Area Emergency 

Response (BAER) teams to long-term planning for 

future watershed management and resource use. This 

study corroborates other post-wildfire studies conducted in forested areas of the western United States 

that indicate that rainfall intensity is one of the key 

factors behind post-fire hillslope erosion, and that 

hillslope erosion during the first post-fire year can be 

on the order of 10 Mg ha-1 yr-1 (4 ton acre-1 yr-1).

These results indicate that the erosion risk after a 

wildfire is greatest for the first two post-fire years. 

Also, the magnitude of that risk may be influenced by 

the rainfall intensity and the number of post-fire years. 

However, depending on what lies downstream of the 

burned area, even the erosion rates we measured in 

post-fire year 3 may be well above tolerable levels.

Our data may be useful for predicting wildfire 

effects in western Montana. For example, the site 

characteristics described in this study, such as changes in soil water repellency over time, can be used 

to select appropriate input parameters for post-fire 

hydrologic and/or erosion models. In addition, our 

reported sediment yields can be directly compared 

to model predictions to confirm the validity of those 

predictions before using the models for post-fire treatment decisions.

Because wildfires commonly occur in western 

Montana, land managers must consider the potential 

wildfire effects in any long-range planning process. 

The post-fire responses reported in this study, combined with other regional data, can assist in land 

management decisions such as fuel reduction treatments, fire suppression, and wildland fire use.

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8 USDA Forest Service RMRS-RP-77. 2009.

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Rocky

 Mountain

 Research Station

The Rocky Mountain Research Station develops scientific information 

and technology to improve management, protection, and use of the 

forests and rangelands. Research is designed to meet the needs of 

the National Forest managers, Federal and State agencies, public and 

private organizations, academic institutions, industry, and individuals. 

Studies accelerate solutions to problems involving ecosystems, range, 

forests, water, recreation, fire, resource inventory, land reclamation, 

community sustainability, forest engineering technology, multiple use 

economics, wildlife and fish habitat, and forest insects and diseases. 

Studies are conducted cooperatively, and applications may be found 

worldwide.

Station Headquarters

Rocky Mountain Research Station

240 W Prospect Road

Fort Collins, CO 80526

(970) 498-1100

Research Locations

Reno, Nevada

Albuquerque, New Mexico

Rapid City, South Dakota

Logan, Utah

Ogden, Utah

Provo, Utah

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and where applicable, sex, marital status, familial status, parental status, religion, 

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require alternative means for communication of program information (Braille, 

large print, audiotape, etc.) should contact USDA’s TARGET Center at (202) 

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Director, Office of Civil Rights, 1400 Independence Avenue, S.W., Washington, 

DC 20250-9410, or call (800) 795-3272 (voice) or (202) 720-6382 (TDD). USDA 

is an equal opportunity provider and employer.

Flagstaff, Arizona

Fort Collins, Colorado

Boise, Idaho

Moscow, Idaho

Bozeman, Montana

Missoula, Montana