VARIATION IN THE RELATION OF RAINFALL 

TO RUNOFF FROM RESIDENTIAL LAWNS IN 

MADISON, WISCONSIN, JULY AND AUGUST 

1995

By Andrew D. Legg, Roger T. Bannerman, and John Panuska

U.S. GEOLOGICAL SURVEY 

Water-Resources Investigations Report 96-4194

Prepared in cooperation with the

WISCONSIN DEPARTMENT OF NATURAL RESOURCES

Madison, Wisconsin 

1996
U.S. DEPARTMENT OF THE INTERIOR 

BRUCE BABBITT, Secretary

U.S. GEOLOGICAL SURVEY 

Gordon P. Eaton, Director

For additional information write to:

District Chief 

U.S. Geological Survey 

6417 Normandy Lane 

Madison, Wl 53719

Copies of this report can be purchased from:

U.S. Geological Survey 

Branch of Information Services 

Box 25286 

Denver, CO 80225-0286
CONTENTS

Abstract.................................................................................................................................................................................. 1

Introduction...............................................................................................^^ 1

Purpose and scope........................................................................................................................................................ 2

Site description............................................................................................................................................................ 2

Acknowledgments....................................................................................................................................................... 3

Factors affecting lawn infiltration and runoff........................................................................................................................ 3

Study methods ....................................................................................................................................................................... 3

Data collection................................................................................^^ 3

Data analysis................................................................................................................................................................ 4

Variation in the relation of rainfall to runoff......................................................................................................................... 5

Summary and conclusions..................................................................................................................................................... 10

References cited..................................................................................................................................................................... 11

FIGURES

1. Map showing location of Madison in south-central Wisconsin............................................................................. 2

2-5. Graphs showing:

2. Cumulative rainfall versus runoff coefficients for three locations on the same residential lawn before

and after normalization for equal antecedent soil moisture............................................................................. 7

3. Cumulative rainfall versus runoff coefficients for three different lawns before and after normalization

for equal antecedent soil moisture ................................................................................................................... 7

4. Cumulative rainfall versus runoff coefficients for five different lawn age groups before and after

normalization for equal antecedent soil moisture............................................................................................ 9

5. Runoff coefficients for a single lawn for three different rainfall intensities.......................................................... 10

TABLES

1. Soil characteristics and average Green-Ampt parameters for three locations on a single lawn................................ 6

2. Soil characteristics and average Green-Ampt parameters for three different lawns................................................. 8

3. Soil characteristics and average Green-Ampt parameters for five different age groups........................................... 8

CONVERSION FACTORS

___________Multiply______________By______________To Obtain_______

centimeter (cm) 0.3937 inch

centimeter per hour (cm/hr) 0.3937 inch per hour

gram (g) 2.205 x 10"3 pound

meter (m) 3.281 foot

Degree Celsius (°C) may be converted to degree Fahrenheit (°F) by using the following equation:

°F = 9/5 (°C) + 32.

CONTENTS AND CONVERSION FACTORS
Variation in the Relation of Rainfall to Runoff from 

Residential Lawns in Madison, Wisconsin, July and 

August 1995

By Andrew D. Legg1 , Roger T. Bannerman2, anc/John Panuska2

Abstract

The quality of runoff from residential lawns 

is a concern for municipal stormwater management programs. Land-use based computer models 

are increasingly being used to assess the impact of 

lawn runoff on urban watersheds. To accurately 

model the runoff for residential lawns, the variation in the relation of rainfall to runoff from lawns 

must be understood. The study described in this 

report measures the runoff parameters from 20 residential lawns in Madison, Wisconsin, using a 

rainfall simulator. It was determined that the saturated hydraulic conductivity does not vary significantly within a single residential lawn, but does 

vary significantly from one lawn to another. This 

variation is recognized in the entire rainfall-runoff 

relation from one lawn to another. The age of a 

lawn, or the years since development and turf 

establishment, is used as a surrogate of several 

lawn and soil characteristics to describe the variability in lawn runoff volumes. Runoff volumes 

from newly developed lawns are significantly 

greater than runoff from older lawns. This is an 

important consideration when modeling runoff for 

new developments. For older lawns, the date since 

lawn establishment does not explain the variation 

in the rainfall-runoff relation. In order for simple 

land-use based computer models to adequately 

account for the volume of runoff from pervious 

landscapes, field data from individual lawns would 

be necessary. A more realistic, alternative method 

may be to consider a basin-scale analysis of runoff 

from pervious landscapes.

INTRODUCTION

The residential lawn is a typical landscape in 

many urban watersheds throughout the United States.

For several urban watersheds in Wisconsin, turf areas 

account for as much as 65 percent of the entire land 

cover (Bannerman and others, 1996). The quality of 

stormwater that washes off urban watersheds, including residential lawns, is of concern for municipal 

stormwater management programs. The 1987 Amendments to the Clean Water Act have legitimized these 

concerns. The Amendments call for development of 

site-specific municipal stormwater management programs. States are now in the process of developing 

management programs for municipalities with populations of 100,000 or more.

Simple land-use based computer models are 

being used increasingly in the development of stormwater-quality management programs. The Source 

Loading and Management Model (SLAMM) is being 

used by the Wisconsin Department of Natural 

Resources (WDNR) for estimating pollutant loads 

from particular urban land uses. Specifically, SLAMM 

is being used to develop watershed management plans 

and to evaluate best-management practices for urban 

watersheds in Wisconsin (Pitt, 1986). The work on 

which this report is based was performed by the U.S. 

Geological Survey (USGS) in cooperation with the 

WDNR in order to improve the modeling capability of 

SLAMM. SLAMM uses concepts of small-storm 

hydrology and a formulation similar to the rational formula to calculate the volume of runoff from different 

urban land uses. The runoff parameters used in the 

rational formula for residential lawns were developed 

initially for agricultural purposes and are based on 

characteristics of bare, native soils. Typically, during 

lawn establishment native soils are excavated, the construction area may be filled with non-native soils, soils 

are subjected to compaction by construction equipment, and finally grass is established using either seed 

or sod. These lawn establishment methods alter the

^.S. Geological Survey, Madison, Wis.

2Wisconsin Department of Natural Resources, Madison, Wis.

Abstract 1
runoff characteristics of soils; therefore, the use of 

existing runoff parameters may be inaccurate. As also 

recognized by Watschke and others (1989), there is a 

need to develop runoff parameters for lawns to more 

accurately model urban landscapes.

The study described in this report determines 

whether rainfall infiltration into residential lawns can 

be accurately modeled without intensive data collection. To meet the objectives of simple hydrologic computer models, it is most practical for runoff parameters 

to be determined on a regional basis and not be specific 

to individual lawns. Therefore, fundamental to understanding the relation between rainfall and runoff for 

residential lawns is understanding the variability of 

runoff volumes from lawns. Hamilton (1990) and 

Kelling and Peterson (1975) measured infiltration rates 

for lawns and found considerable variation between 

measurements.

Purpose and Scope

This report describes the results of a study of the 

rainfall-runoff relation from 20 residential lawns in 

Madison, Wisconsin, using a portable rainfall simulator. For this study, three hypotheses were tested to 

determine the variation in the relation between rainfall 

and runoff from residential lawns. Hypothesis 1: there 

are no substantial differences in the rainfall-runoff relations within a single lawn. Hypothesis 2: there are substantial differences in the rainfall-runoff relations from 

different lawns. Hypothesis 3: there is a relation 

between the age of a lawn, or the years since development and turf establishment, and the volume of runoff 

from a lawn. The age of a lawn was used as a surrogate 

of several lawn and soil characteristics to describe the 

variability in lawn runoff volumes. After soil grading 

and turf establishment, physical, chemical, and biological processes described in the section "Factors Affecting Lawn Infiltration and Runoff will develop pore 

space and macropores in the soil matrix. It is believed 

that as the lawn ages, soil develops and the runoff from 

a lawn will decrease. This is supported by Partsch and 

others (1993), who recognized some trend towards 

faster infiltration with age after measuring infiltration 

rates on 6- and 12-year old lawns. Although it may be 

an oversimplification of the infiltration process, the age 

of a lawn would be a practical consideration for simple 

land-use based computer models that are limited in 

their accuracy by their broader management objectives.

Finally, the importance of antecedent soil moisture, 

rainfall intensity, and soil texture as they affect the rainfall-runoff relation on residential lawns is discussed.

Site Description

The data for this study were collected from 20 

residential lawns in Madison, Wisconsin (fig. 1). Madison is located in south-central Wisconsin and has a 

northern temperate climate. The seasons in Madison 

were framed by a summer high temperature of 38°C 

and a winter low temperature of -22°C for 1994-95. 

The data were collected during July and August 1995. 

Total rainfall amounts recorded for south-central Wisconsin during July and August were 10.5 and 14.2 cm, 

respectively. These amounts are 109 percent and 140 

percent of the normal for the period of record 1961-95 

(Pamela Naber-Knox, Wisconsin State Climatologist, 

oral commun., 1995). The soils for the study sites were 

mapped by the Soil Conservation Service (Glocker and 

Patzer, 1978) as silt loam of the Dodge, McHenry, and 

St. Charles Series. These series generally consist of 

deep, well-drained soils on glaciated uplands with 

hydraulic conductivity between 1.6 and 5.1 cm/hr.

Figure 1. Location of Madison in south-central Wisconsin.

2 Variation in the Relation of Rainfall to Runoff from Residential Lawns in Madison, Wisconsin, July and August 1995
Acknowledgments

Thanks are extended to Kevin Silvera and the 

University of Wisconsin Soils Department for use and 

operation of their rainfall simulator. The author also 

thanks Howard Gundlock of the Natural Resources 

Conservation Service for his help with the soil texture 

analysis, and John Panuska and Roger Bannerman of 

the Wisconsin Department of Natural Resources for 

providing insight for this study.

FACTORS AFFECTING LAWN 

INFILTRATION AND RUNOFF

The infiltration rate of turf grass has received 

increasing attention because of the potential for surface 

water-quality-degradation from nutrient and pesticide 

runoff from residential lawns. Effects of turf grass on 

the infiltration process have been investigated in a few 

studies, and many more studies have investigated the 

effects of soil characteristics on the infiltration process.

Hino and Shutto (1987) found that grass-covered 

soil had a higher soil moisture content and moisture 

conductivity than did bare soil. They concluded that 

grass roots transformed the structural characteristics of 

the soil to increase saturated hydraulic conductivity 

from 0.6 cm/hr for bare soil to 10 cm/hr for grass-covered soils. Gross and others (1991) studied lawns established at different seeding rates and suggested that a 

thick, dense and thatchy lawn may absorb and infiltrate 

all rainfall from light to moderate intensities.

Many researchers have demonstrated that antecedent soil moisture is an important factor in producing 

runoff. Tisdall (1951) recognized that as soil antecedent moisture contents increased, infiltration rates 

decreased. Istok and Boersma (1986) concluded that 

antecedent moisture is more important than the magnitude or intensity of rainfall in controlling the occurrence and amount of runoff. Watschke and others 

(1989) observed a seasonal change in runoff volumes 

in response to antecedent moisture conditions affected 

by seasonal changes in water uptake for plant growth.

The volume of pore space in a soil matrix affects 

the hydraulic conductivity of a soil. Pore space, or the 

void space in the soil matrix, is increased as the aggregation of soil mineral particles increases, and that, in 

turn, increases the hydraulic conductivity of the soil. 

The destruction of the natural soil matrix as a consequence of excavation and compaction can, therefore, 

decrease the hydraulic conductivity. The effect on infiltration of soil compaction from lawn construction and 

every-day foot traffic has been studied. Kelling and 

Peterson (1975) observed infiltration rates under simulated rainfall to be highest on lawns with undisturbed 

soil structure. They noticed that infiltration rates were 

affected locally on a lawn by compaction from foot 

traffic and recreational uses. Partsch and others (1993) 

studied bulk densities of established lawns and 

observed that compacting the soil after stripping the 

topsoil creates a limiting layer that reduces the rate at 

which water can infiltrate. Kussow (1994) studied naturally occurring rainfall runoff from compacted and 

noncompacted turf plots. Initial results of this study 

show that soil disturbances, such as those that occur in 

urban settings, increase runoff from turf, but not as 

much as expected.

The volume of pore space in a soil matrix is also 

affected by the presence of macropores. Macropores 

close to the surface of the soil create preferential pathways for infiltrating rainwater. In their review of the 

importance of macropores on water flow in soils, 

Beven and Germann (1982) suggest macropores may 

dominate vertical flow of water through soils. They 

grouped the formation of macropores by the following: 

(1) those formed by soil fauna, including the activities 

of burrowing animals, earthworms, and ants; (2) those 

formed by plant roots; (3) those caused by cracks; (4) 

fissures in the soil matrix from shrinking and swelling 

soils or freeze/thaw cycles; and (5) natural soil pipes, 

formed by the erosive action of subsurface flows. All of 

these types of macropores may be destroyed when a 

lawn is established but will redevelop in a lawn over 

time. Under favorable circumstances, macropore systems can be developed in as little as 1 to 2 years and last 

for considerable time in a stable soil structure (Beven 

and Germann, 1982). Hino and Shutto (1987) found 

that the growth of grass altered the structure of soils 

within 2 months of establishment.

STUDY METHODS

Data Collection

A Modified Purdue Model Sprinkling Infiltrometer as described by Peterson and Bubenzer (1986) was 

used to simulate rainfall in this study. The rainfall simulator was operated at an intensity of 7.1 cm/hr, which 

is approximately equivalent to a 50-year storm in 

southern Wisconsin (Huff and Angel, 1992). It was

FACTORS AFFECTING LAWN INFILTRATION AND RUNOFF 3
necessary to operate the rainfall simulator at this high 

intensity to produce runoff on all of the lawns without 

varying the intensity for a particular measurement. 

Rainfall was simulated on 1-by-l m sections of residential lawn confined by a steel frame. Runoff from the 

simulated rainfall was collected by vacuuming the surface ponded water into a volumetrically calibrated container (Peterson and Bubenzer, 1986). For each 

measurement site, the simulator "rained" for 60 minutes, and runoff volumes were measured every 5 minutes. If runoff did not occur within the first 30 minutes, 

the simulated rainfall was extended to 90 minutes. In 

an attempt to reach saturated soil conditions, at least 

four consistent runoff volumes were measured before 

the rainfall simulator was turned off. The incremental 

runoff data collected was then used to plot cumulative 

runoff curves for this study.

Along with the runoff measurements, surface 

bulk density, antecedent moisture content, and organic 

matter content measurements were made from the surface soils. Soil moisture samples were measured gravimetrically (Gardner, 1986). A 30-cm soil core was 

logged for each site. The soil texture was described 

using hand texturing, and the soil structure was visually 

inspected. The soils were all classified as silt loam with 

varying degrees of structural development.

Turf conditions and maintenance practices were 

noted for residential lawns in the study. All of the runoff measurements were made on turf with a 10-percent 

slope. The turf at each measurement site was mowed to 

the same height prior to the start of simulated rainfall. '

The data for this study were collected according 

to a design appropriate for statistical analysis. The 

study was designed in three parts to test the hypotheses. 

Each part of the study includes measurement sets consisting of four replicates. Different measurement sets 

are the experimental units being compared in the study. 

A replicate is one rainfall-simulator test, with runoff 

data collected as described above.

Part 1: to examine the variation within a single 

lawn

 1 lawn

 3 sets randomly located within lawn

 replicates located side-by-side

Part 2: to examine the runoff variation among

different lawns

 3 lawns

 3 sets one in each lawn

 replicates randomly located within a lawn

Part 3: to examine the runoff variation for lawns of 

different age groups

 20 lawns

 5 sets of 4 lawns each sets represent different 

age groups (the five age-group sets used in this 

study were 1-3, 7-9, 13-16, 41-46, and 65-70 

years old)

 replicates are 1 measurement on each of the 4 

lawns within an age group

Data Analysis

To quantify the variability in the relation of rainfall to runoff, the measurement sets described above 

were compared statistically. The average of four replications for each measurement set were compared by 

analysis of the variance (ANOVA) (Helsel and Hirsch, 

1995) to determine significant differences. Tukey's 

method for multiple comparison was used to compare 

and rank the average values of the different age-group 

sets (Helsel and Hirsch, 1995). For these statistical 

tests, an observed significance level (p- value) less than 

0.05 was considered significantly different. The rainfall-runoff relations for measurement sets were compared graphically by plotting cumulative rainfall 

versus runoff coefficients. Each plot represents the 

average rainfall-runoff relation from four replications. 

The runoff coefficient is the ratio of cumulative runoff 

to cumulative rainfall. By plotting the rainfall-runoff 

relation as the cumulative rainfall versus runoff coefficient, the effects of the variability on the entire runoff 

process are more apparent, although not quantified.

To statistically compare measurement sets, soil 

matrix parameters describing the entire cumulative 

runoff curve were determined from the Green- Ampt 

infiltration model, as modified by Mein and Larson 

(1973). Runoff data collected in the field was used to 

calibrate the Green- Ampt model.

The formulation of the Green- Ampt model used 

in this study was:

where

t is time since rainfall began (hr);

K is saturated hydraulic conductivity (cm/hr);

F is volume of rainfall infiltrated (cm);

4 Variation in the Relation of Rainfall to Runoff from Residential Lawns in Madison, Wisconsin, July and August 1995
Fr is volume of rainfall infiltrated at the time

runoff began (cm);

\j/ is wetting front soil suction head (cm); 

n is available pore space (percent); and 

tr is elapsed time from the beginning of rainfall

to the beginning of runoff (hr).

For this formulation of the Green-Ampt model, t is the 

dependent variable and F is the independent variable. 

Values for t were calculated using parameters determined at each measurement site as follows. K was calculated from the field data by a linear regression 

analysis on the cumulative runoff curve when the soil 

had reached an apparent steady state or saturation. The 

elapsed time from when rainfall begins to the time 

water begins to runoff the soil surface, tr was taken 

directly from the cumulative runoff curve determined 

in the field. The volume of rainfall infiltrated at the 

time runoff began, Fr is equal to the rainfall intensity 

multiplied by tr Available pore space, n, was calculated as (|) - 9j, where (|) is 95 percent of the soil porosity and 9j is the initial soil moisture. The wetting front 

suction parameter (\j/) was not easily determined from 

the measured data. To complete the model \j/ was 

determined using a curve fitting method similar to that 

described by Partsch and others (1993). To obtain \|/, 

the Green-Ampt model was fit to the cumulative runoff field data. A value for \j/ was chosen which resulted 

in the least square difference between t calculated and 

t values from field measurements. Unlike the physically derived parameters tr and K, \\f is empirically calculated. To measure how well the model fit the field 

data, t calculated was correlated to field measured t

r\

values. An R value of 1.0 was a perfect match 

between model and field data.

Repeating the above calculations, the parameters 

tr \j/, and K were determined for each replication of 

each measurement set. The cumulative runoff curve 

then was completely defined by the Green-Ampt 

parameters: tr is the time until runoff occurs, \j/ 

describes how quickly the soil reaches saturation after 

runoff has begun, and K describes the runoff curve at 

saturation. The averages of the Green-Ampt parameters for each measurement set were statistically compared, and the average rainfall-runoff relation was 

drawn for each measurement set.

An attempt was made to use K instead of \j/ as the 

curve fitting parameter in the Green-Ampt model. \j/ 

values were instead calculated based on soil properties

and regression equations formulated by Rawls and 

Brakenseik (1989). This method was not used because 

it resulted in negative Green-Ampt parameters. Other 

researchers have also encountered negative parameters 

when using a least-squared estimation for Green-Ampt 

parameters (Devaurs and Gifford, 1986).

As noted in the literature, runoff volumes are 

dependent on the antecedent soil moisture. The 

observed antecedent soil moisture contents varied substantially during this study, ranging from 8.2 to 43.5 

percent. To account for the varying soil moisture conditions, the runoff data were normalized to an equal soil 

moisture, 9; = 21 percent. This value is the average of 

the field capacity (28.4 percent) and the permanent wilt 

point (13.5 percent) for a silt loam soil (Rawls and others, 1983). The tr parameter was normalized for the 

equal soil moisture conditions by recalculating n at the 

average soil moisture. K and \j/ are a function of the soil 

matrix and not soil moisture; therefore, these parameters did not need adjustment. After being normalized 

for an equal soil moisture, average tr values for each 

measurement set were again statistically compared, 

and normalized rainfall-runoff relations drawn.

VARIATION IN THE RELATION OF 

RAINFALL TO RUNOFF

Rainfall-runoff measurements and turf characteristics were collected from 20 residential lawns to 

compare the variation in residential lawn runoff. Three 

hypothesis concerning the variation of lawn runoff and 

the causes of that variation were tested.

The first hypothesis stated there are no substantial differences in the rainfall-runoff relations within a 

single lawn. For the first part of the study, measurements were made at three different locations within the 

same lawn with four replications per location. Table 1 

lists the soil characteristics, Green-Ampt parameters, 

and p-values for the three different locations.

The model and field data compared very well as 

determined by the R2 correlation coefficients. 

ANOVA's calculated for average K values were not significantly different, which suggests that the soil properties did not vary for the lawn. The mean values of the 

time of ponding, tr for three measurement sets were 

significantly different within the same lawn. Figure 2A 

shows the substantial effect that these differing mean 

values of tr had on the rainfall-runoff relation. There is 

a trend of increasing soil moisture content from 11.5 to 

43.5 percent as tr decreases from 0.72 to 0.2 hour

VARIATION IN THE RELATION OF RAINFALL TO RUNOFF 5
Table 1. Soil characteristics and average Green-Ampt parameters for three locations on a single lawn

[%, percent; g/cm3 , gram per cubic centimeter; K, saturated hydraulic conductivity; cm/hr; centimeter per hour; tp time until runoff; hrs, hours; 

\|f, wetting front suction; cm, centimeter; R2, correlation coefficient; --, not available]

Average Green-Ampt parameters

Soil characteristics

Measurement set

Location 1

Location 2

Location 3

Soil 

moisture 

content 

(%)

11.5

30.0

43.5

Bulk 

density 

(g/cm3)

1.1

1.3

1.2

Organic 

matter 

content 

(%)

9.0

7.0

6.7

Model fit to measured data

K

(cm/hr)

0.52

.59

.77

tr 

(hrs)

0.72

.59

.20

V 

(cm)

58

53

4.3

R2

0.95

.96

.99

Normalized 

for equal soil 

moisture

tr 

(hrs)

0.51

.73

.32

p-values .53 6.6E-04 .12 .08

(table 1). It is believed that the difference between rainfall-runoff curves in figure 2A was the result of the different antecedent soil moisture conditions. The 

literature supports the importance of antecedent soil 

moisture to the infiltration process (Tisdall, 1951; Istok 

and Boers ma, 1986; Watschke and others, 1989). After 

normalizing the measurement sets for an equal antecedent soil moisture value, the mean values of the time 

of ponding, tr are no longer significantly different. In 

spite of the statistics, the rainfall-runoff relations for 

parameters normalized to an equal soil moisture content are quite different as seen in figure 2B. Although 

not statistically different, the difference in the rainfallrunoff relation as drawn would cause large discrepancies in the prediction of runoff.

Examination of the wetting front suction, \j/, 

helps explain the difference in the rainfall-runoff relations for locations within the same lawn. Normalization for equal soil moisture does not equalize the 

rainfall-runoff relations as expected because of the difference in the \j/ values between sites. Although \|/ functions well as a curve fitting parameter to calibrate the 

Green-Ampt model, it has no physical basis. It is possible that the \j/ parameter is compensating for an 

inability of the Green-Ampt model to consider preferential flow paths in the soil matrix (flow through 

macropores). In turfed areas this flow is considered an 

important factor in the infiltration process. The GreenAmpt model is based on flow through a homogenous 

soil matrix and does not consider macropores. By using 

an empirical value for \j/ in the model the effects of 

preferential flow in the field data are compensated for.

It is then difficult to use the model to predict runoff 

based on conditions other than those for which \j/ was 

derived. For this reason, the ability to predict the rainfall-runoff relation for equal initial soil moisture is limited.

To summarize, the runoff data collected within a 

single lawn shows that the hydraulic conductivities do 

not vary significantly. However, the entire rainfall-runoff relation as drawn in figure 2 does change substantially, possibly because of differences in the initial soil 

moisture that could not adequately be compensated for. 

Therefore, the hypothesis that there are no substantial 

differences in the rainfall-runoff relation within a single lawn is rejected.

The second hypothesis is confirmed. There are 

substantial differences in the rainfall-runoff relations 

for different lawns. For this part of the study, runoff 

measurements were made on three different lawns with 

four replications per lawn. Table 2 lists the soil characteristics, Green-Ampt parameters, and p-values for the 

three different treatment means. R2 correlation coefficients indicate an excellent model fit. The hydraulic 

conductivities, K, for the three different lawns are significantly different which suggests that the soil properties vary between lawns. The tr and \|/ values were not 

significantly different before or after normalization for 

an equal antecedent soil moisture content. Figure 3A 

shows the effect of the different hydraulic conductivities on the rainfall-runoff relation between lawns. Normalizing for soil moisture amplified this effect (fig. 

3B). Whether the effects of different antecedent soil 

moisture are adequately compensated for or not in fig6 Variation in the Relation of Rainfall to Runoff from Residential Lawns in Madison, Wisconsin, July and August 1995
0.7 

0.6 

0.5

UJ

£0.4

HJ 

8

It 

o

0.3 

0.2 

0.1

A. ----- Location 1

 - Location 2

 Location 3

12345678 

CUMULATIVE RAINFALL, IN CENTIMETERS

0.7 

0.6

^0.5

3 

I °-4

UJ

8 It °-3

o

<r 0.2 

0.1

A. ----- Lawn 1

 - Lawn 2

 Lawn 3

1 234567 

CUMULATIVE RAINFALL, IN CENTIMETERS

0.7

0.6

0.5

E 0.4

u.0.3 

O

* 0.2

0.1 

0

- - - - Location 1

 - Location 2

 Location 3

1 2345678 

CUMULATIVE RAINFALL, IN CENTIMETERS

0.7 

0.6 

0.5

FT 0.4

0.3

0.2

0.1

0

- - - - Lawn 1

 - Lawn 2

 Lawn 3

1234567 

CUMULATIVE RAINFALL, IN CENTIMETERS

Figure 2. Cumulative rainfall versus runoff coefficients for 

three locations on the same residential lawn before and 

after normalization for equal antecedent soil moisture.

Figure 3. Cumulative rainfall versus runoff coefficients for 

three different lawns (A) before and (B) after normalization 

for equal antecedent soil moisture.

VARIATION IN THE RELATION OF RAINFALL TO RUNOFF
Table 2. Soil characteristics and average Green-Ampt parameters for three different lawns

[%, percent; g/cm3, gram per cubic centimeter; K, saturated hydraulic conductivity; cm/hr; centimeter per hour; tp time until runoff; hrs, hours; 

\)/, wetting front suction; cm, centimeter; R2, correlation coefficient; --, not available]

Average Green-Ampt parameters

Soil characteristics

Measurement set

Lawn 1

Lawn 2

Lawn 3

Soil 

moisture 

content 

(%)

34.9

27.3

13.7

Bulk 

density 

(g/cm3)

1.4

1.4

1.3

Organic 

matter 

content 

(%)

3.5

6.1

6.9

Model fit to measured data

K

(cm/hr)

0.84

5.9

3.5

tr 

(hrs)

0.20

.20

.12

M> 

(cm)

9.2

2.0

.23

R2

1.0

1.0

.99

Normalized

for equal soil 

moisture

tr 

(hrs)

0.32

.19

.12

p-values 2.7E-05 .18 .39 .08

Table 3. Soil characteristics and average Green-Ampt parameters for five different age groups

[%, percent; g/cm3 , gram per cubic centimeter; K, saturated hydraulic conductivity; cm/hr; centimeter per hour; tp time until runoff; hrs, hours; 

\|/, wetting front suction; cm, centimeter; R , correlation coefficient; --, not available]

Average Green-Ampt parameters

Soil characteristics

Years

1-3

7-9

13-18

41^6

65-70

Soil 

moisture 

content 

(%)

24.5

26.7

21.0

14.9

37.5

Bulk 

density 

(g/cm3)

1.6

1.4

1.3

1.4

1.2

Organic 

matter 

content 

(%)

4.8

7.3

6.5

5.5

7.0

Model fit to measured data

K

(cm/hr)

1.1

4.3

4.7

4.3

5.4

tr 

(hrs)

0.18

.25

.41

.13

.12

M> 

(cm)

3.2

11

7.1

.67

.15

R2

1.0

.99

1.0

1.0

1.0

Normalized

for equal soil 

moisture

tr 

(hrs)

0.21

.36

.41

.13

.14

p-values .01 .11 .23 .11

ure 3, the shape of the curve is very different. This supports the results of the statistical analysis that suggest a 

difference in soil properties between different lawns.

Confirmation of the second hypothesis established a significant difference between soil properties 

that control rainfall-runoff relations for different lawns. 

Expanding on this, the third hypothesis states that there 

is a relation between the age of a lawn and the volume 

of runoff from the lawn. This third part of the study 

consisted of the collection of data from lawns in five 

different age groups with four different lawns as replication, for a total of 20 lawns. Table 3 lists the soil characteristics, Green-Ampt parameters, and p-values for 

the five different age groups. The model fit was excelr\

lent with 4 of the 5 age groups having an R value of 

1.0. The hydraulic conductivities for individual age 

groups were compared using Tukey's method for multiple comparison. The results of this test showed significant differences among lawns in the age group 1-3 

years and lawns in the age groups 13-18 years and 65- 

70 years. The differences among age group 1-3 years 

and groups 7-9 years and 41-46 years were close to 

having statistical significance with p-values of 0.066 

and 0.064, respectively. Age groups over 1-3 years had 

no statistical difference when individually compared to 

one another. It was confirmed that the hydraulic conductivity of new lawns, ages 1-3 years, are significantly lower than those for older lawns. Differences

8 Variation in the Relation of Rainfall to Runoff from Residential Lawns in Madison, Wisconsin, July and August 1995
0.7

0.6

I 0.4

0.2

0.1

A. Age Group, in Years

_.._. 1 _ 3

____ 7-9 .''

....... 13-16 y'

_ . - . - 41-46 y 

 65 - 70 /

'/V

I

1234567 

CUMULATIVE RAINFALL, IN CENTIMETERS

0.7 

0.6 

0.5

E 0.4

u.0.3

O

z

^ 0.2

0.1

B. Age Group, in Years

_.._. 1-3

---- 7-9

....... 13-16

_._.- 41-46

 65-70 / 

/

1234567 

CUMULATIVE RAINFALL, IN CENTIMETERS

Figure 4. Cumulative rainfall versus runoff coefficients for 

five different lawn age groups (A) before and (B) after 

normalization for equal antecedent soil moisture.

among the lawns older than the 1-3 year age group 

could not be distinguished. The different hydraulic 

conductivities had a substantial effect on rainfall-runoff relations as shown in figure 4A, which displays the 

highest runoff coefficients with youngest age group.

Normalizing for soil moisture had little effect on 

the rainfall-runoff relations (fig. 4B). As discussed previously, the normalization procedure is limited by the 

empirical nature of \\r. The soil moisture for age-group

treatment 65-70 is 37.5 percent. The effect of normalizing to an average soil moisture of 21 percent may in 

fact be much greater if the \|/ values did not vary considerably.

The significantly lower hydraulic conductivity 

and high runoff coefficients for lawns in the 1-3 year 

age group are recognized in the bulk density and 

organic matter content data collected from the soil surface. The bulk density for the 1-3 year age group is 

higher than that of any other age group, and the organic 

matter content for the 1-3 year age group is less 

(table 3). Bulk density is a measure of porosity and soil 

structure. Organic matter content is an indication of the 

amount of biological activity, including grass-root 

growth in the top layer of the soil. The trends in bulk 

density and organic matter data from the 1-3 year age 

group to older lawns represent an increase in infiltration. It is generally accepted that development of soil 

structure and macropores increases infiltration. The 

significant decrease in runoff from age group 1-3 years 

to older lawns appears consistent with the findings of 

others. Beven and Germann (1986) and Hino and 

Shutto (1987) both reported the development of preferential flow within 2 years.

To begin to understand the effect of rainfall 

intensity on the runoff from residential lawns, a single 

lawn was tested at varying intensities. The rainfall simulator was run at 3.8,7.1, and 14.0 cm/hr with the same 

antecedent soil moisture conditions. The relation of 

rainfall to runoff at the three different intensities are 

shown in figure 5. Contrary to what might be expected, 

the relations for different intensities are similar. This 

may be a result of a change in the available pore space, 

n. As intensity of rainfall increases surface water ponding on the measurement site is likely to increase. The 

increased pressure head due to ponding may contribute 

to a larger volume of rainfall infiltrating. Data sufficient to quantify this effect were not collected.

Data also were collected from residential lawns 

with sandy soil texture. Preliminary results of these 

tests compare well with hydraulic conductivities collected for silt loam soils. Rainfall simulator measurements on lawns with loamy sand soil for 5-, 15-, and 

70+- year-old lawns had hydraulic conductivities of 

2.6, 3.4, and 5.7 cm/hr, respectively. Similarly, the 

hydraulic conductivities for the silt loam soil increased 

from 1.1 cm/hr for age group 1-3 years to 5.4 cm/hr for 

age group 65-70 years. These preliminary data show 

that changes in soil texture may not be an important

VARIATION IN THE RELATION OF RAINFALL TO RUNOFF
0.7

0.6

0.5

E °-4

uj

8 it 0.3

o

z 

3 OC 0.2

0.1

Rainfall intensity, in 

centimeters per hour

....... 3.8

- - 7.1

 14

4 6 8 10 

RAINFALL, IN CENTIMETERS

Figure 5. Runoff coefficients for a single lawn for three 

different rainfall intensities.

factor contributing to the variation in runoff volumes 

from lawns.

SUMMARY AND CONCLUSIONS

Determining the factors that most affect runoff 

volumes from residential lawns would improve the 

estimation of pollutant loads from urban watersheds. 

Fundamental to determining which factors contribute 

to runoff is quantifying the variation in the rainfall-runoff relation on residential lawns.

In this study, it was determined that the hydraulic 

conductivities do not vary significantly for a single residential lawn. The entire rainfall-runoff relation does 

change substantially, possibly because of differences in 

the initial soil moisture. From one lawn to another lawn 

there is substantial variation in the relation of rainfall to 

runoff. The difference between the hydraulic conductivity of newly established lawns and that of lawns 1-3 

years old and older is statistically significant. Also, 

runoff coefficients for the young lawns are substantially greater than those for older lawns. The variability 

in the rainfall-runoff relation for lawns other than those 

newly developed cannot be explained by the age of a 

lawn. It is concluded that the age of a lawn would only 

be a useful parameter in determining runoff volume 

and pollutant loads from newly established residential 

lawns, those three years old or younger.

The effect of antecedent soil moisture on the 

results of this study is questioned. Because of the

inability of the Green-Ampt model to account for flow 

through macropores, applicability of the soil moisture 

normalization procedure used in this study may be limited. For this reason definitive conclusions are not 

drawn regarding the variation of the runoff process on 

a single lawn. Also for this reason, a trend in decreasing 

runoff for older lawns could not be obviously distinguished.

Preliminary data show variation in rainfall intensity and variation in the soil texture had little effect on 

the runoff volumes. Data collected on residential lawns 

with sandy soil texture demonstrate similar hydraulic 

conductivities as those from silt loam soils. Future 

studies would need to include a variety of soil textures 

and rainfall intensities to substantiate these results.

This study explores the variation in the relation 

of rainfall to runoff from residential lawns. It is concluded that the rainfall-runoff relation varies substantially among different lawns. The age of a lawn, or the 

years since development and turf establishment, is used 

as a surrogate of several lawn and soil characteristics to 

describe this variation. Lawns established within three 

years produce higher runoff volumes than older lawns. 

This is an important consideration when modeling runoff for new developments. For older lawns, the date 

since lawn establishment does not explain the variation 

in the rainfall-runoff relation. In order for simple landuse based computer models to adequately account for 

the volume of runoff from pervious landscapes, field 

data from individual lawns would be necessary. A more 

realistic, alternative method may be to consider a 

basin-scale analysis of runoff from pervious landscapes.

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