APPLICATION OF THE GREEN-AMPT INFILTRATION EQUATION TO WATERSHED MODELING1

ABSTRACT: A computer model was developed, based on the Green-Ampt infiltration equation, to computed rainfall excess for a single precipitation event. The model requires an estimate of parameters related to hydraulic conductivity, wetting front section, and fillable porosity of the soil layers. Values of parameters were estimated from soil textural averages or regression equations based on percent sand, percent clay, and porosity. Average values of effective porosity and wetting front suction were largely acceptable due to the relatively low variability and low model sensitivity to the parameters. Hydraulic conductivity was the most erratic constituent of the loss rate computation due to the high variability and the high sensitivity of the computed infiltration to the parameter. The performance of the Green-Ampt infiltration model was tested through a comparison with the SCS curve number procedure. Seven watersheds and 23 storms with precipitation of one inch or greater were used in the comparison. For storms with less than one inch of rainfall excess, the SCS curve number procedure generally gave the best results; however, for six of the seven storms with precipitation excess greater than one inch, the Green-Ampt procedure delivered better results. In this comparison, both procedures used the same initial abstractions. The separation of rainfall losses into infiltration, interception, and surface retention is, in theory, an accurate method of estimating precipitation excess. In the second phase of the study using nine watersheds and 39 storms, interception and surface retention losses were computed by the Horton equations. Green-Ampt and interception parameters were estimated from value sin the literature, while the surface retention parameter was calibrated so that the computed runoff volumes matched observed volumes. A relationship was found between the surface retention storage capacity and the 15-day antecedent precipitation index, month of year, and precipitation amount.     

PARAMETER UNCERTAINTY IN RAINFALL-RUNOFF MODELING FOR POLDER SYSTEM DESIGN1

ABSTRACT: An approach is developed for incorporating the uncertainty of parameters for estimating runoff in the design of polder systems in ungaged watersheds. Monte Carlo Simulation is used to derive a set of realizations of streamflow hydrographs for a given design rainstorm using the U. S. Soil Conservation Service (SCS) unit hydrograph model. The inverse of the SCS curve number, which is a function of the antecedent runoff condition in the SCS model, is the random input in the Monte Carlo Simulation. Monte Carlo realizations of streamfiow hydrographs are used to simulate the performance of a polder flood protection system. From this simulation the probability of occurrence of flood levels for a particular hydraulic design may be used to evaluate its effectiveness. This approach is demonstrated for the Pluit Polder flood protection system for the City of Jakarta, Indonesia. While the results of the application indicate that uncertainty in the antecedent runoff condition is important, the effects of uncertainty in rainfall data, in additional runoff parameters, such as time to peak, in the hydraulic design, and in the rainfall-runoff model selected should also be considered. Although, the SCS model is limited to agricultural conditions, the approach presented herein may be applied to other flood control systems if appropriate storm runoff models are selected.     

PCN BASED METAL PARTITIONING IN URBAN SNOWMELT,RAINFALL/RUNOFF,AND RIVER FLOW SYSTEMS1

ABSTRACT: Drawing an analogy between the popular Soil Conservation Service curve number (SCS‐CN) method based infiltration and metal sorption processes, a new partitioning curve number (PCN) approach is suggested for partitioning of heavy metals into dissolved and particulate bound forms in urban snowmelt, rainfall/runoff, and river flow environments. The parameters, the potential maximum desorption, ψ, and the PCN analogous to the SCS‐CN parameters S and CN, respectively, are introduced. Under the condition of snowmelt, PCN (or ψ) is found to generally rely on temperature, relative humidity, pH, and chloride content; during a rainstorm, ψ is found to depend on the alkalinity and the pH of the rainwater; and in the river flow situation, PCN is found to generally depend on the temperature, pH, and chloride content. The advantage of using PCN instead of the widely used partitioning parameter, K_d, is found to lie in the PCN's efficacy to distinguish the adsorption (or sorption) behavior of metals in the above snowmelt, rainfall/runoff, and river flow situations, analogous to the hydrological behavior of watersheds.     

USING CURVE NUMBERS TO DETERMINE BASELINE VALUES OF GREEN-AMPT EFFECTIVE HYDRAULIC CONDUCTIVITIES1

ABSTRACT: Since the trend in infiltration modeling is currently toward process-based approaches such as the Green-Ampt equation, more emphasis is being placed on methods of determining appropriate parameters for this approach. The SCS curve number method is an accepted and commonly used empirical approach for estimating surface runoff, and is based on numerous data from a variety of sources. The time and expense of calibrating process-based infiltration parameters to measured data are often prohibitive. This study uses curve number predictions of runoff to develop equations to estimate the “baseline” hydraulic conductivities (K_b) for use in the Green-Ampt equation. Curve number predictions of runoff were made for 43 soils. K_b values in the Water Erosion Prediction Project (WEPP) model were then calibrated so that the annual runoff predicted by WEPP was equal to the curve number predictions. These calibrated values were used to derive an equation that estimated K_b based on the percent sand, percent clay, and cation exchange capacity of the soil. Estimated values of K_b from this equation compared favorably with measured values and values calibrated to measured natural runoff plot data. WEPP predictions of runoff using both optimized and estimated values of K_b were compared to curve number predictions of runoff and the measured values. The WEPP predictions using the optimized values of K_b were the best in terms of both average error and model efficiency. WEPP predictions using estimated values of K_b were shown to be superior to predictions obtained from the curve number method. The runoff predictions all tended to be biased high for small events and low for larger events when compared to the measured data. Confidence intervals for runoff predictions on both an annual and event basis were also developed for the WEPP model.     

Peak Runoff Model Comparison on Central Illinois Watersheds1

ABSTRACT: Four peak runoff rate models were tested with 183 gage years of record to determine the model most applicable to small watersheds of mild topography in east-central Illinois. The Cypress Creek, Rational, Chow, and SCS peak runoff models were evaluated for their performance. Statistical analyses indicated the Soil Conservation Service model was most appropriate for the watersheds tested.     

MODELING INFILTRATION WITH VARYING HYDRAULIC CONDUCTWITY UNDER SIMULATED RAINFALL CONDITIONS1

ABSTRACT: Physically-based models are extensively used to simulate the infiltration process under varied field conditions. Most models are based on the deterministic nature of input parameters related to the flow process (such as hydraulic conductivity). These models yield poor predictions of infiltration rates because they do not include the field-scale variations of flow parameters. The paper presents an approach for integrating the field-scale variability of hydraulic conductivity with an infiltration model to simulate infiltration under the rainfall conditions. A model describing the spatial structure of hydraulic conductivity has been developed using stochastic techniques. The stochastic structure of hydraulic conductivity was then incorporated in the Green-Ampt and Mein-Larson infiltration model. The model outputs on the instantaneous infiltration rates and cumulative infiltration were evaluated using the field infiltration data measured under simulated rainfall conditions. The results show that the combined model is capable of rep. resenting the instantaneous infiltration rates and cumulative infiltration of the study soils. The model may, therefore, be used to simulate the rainfall infiltration process for spatially-variable soils under the field conditions.     

PLANNING OF URBAN BEST MANAGEMENT PRACTICES1

ABSTRACT: A “user-friendly” computer program has been developed for application in personal computers for preliminary design, evaluation, and cost effectiveness analysis of various best management practice (BMP) measures to control stormwater quantity and quality. The algorithms utilize the SCS TR-55 method for calculating runoff hydrographs for a single storm event and a first order pollutant washoff equation to generate pollutographs. Sensitivity analyses based on different policy scenarios is performed on a hypothetical watershed for the purpose of illustration. Three types of BMP measures, namely detention ponds (dry, wet, and extended wet ponds), infiltration trenches, and porous pavements are considered. It is found that the extended wet ponds have the best cost effective performance of the measures evaluated.     

Simulating long-term and residual effects of nitrogen fertilization on corn yields, soil carbon sequestration, and soil nitrogen dynamics

Soil carbon sequestration (SCS) has the potential to attenuate increasing atmospheric CO2 and mitigate greenhouse warming. Understanding of this potential can be assisted by the use of simulation models. We evaluated the ability of the EPIC model to simulate corn (Zea mays L.) yields and soil organic carbon (SOC) at Arlington, WI, during 1958-1991. Corn was grown continuously on a Typic Argiudoll with three N levels: LTN1 (control), LTN2 (medium), and LTN3 (high). The LTN2 N rate started at 56 kg ha(-1) (1958), increased to 92 kg ha(-1) (1963), and reached 140 kg ha(-1) (1973). The LTN3 N rate was maintained at twice the LTN2 level. In 1984, each plot was divided into four subplots receiving N at 0, 84, 168, and 252 kg ha(-1). Five treatments were used for model evaluation. Percent errors of mean yield predictions during 1958-1983 decreased as N rate increased (LTN1 = -5.0%, LTN2 = 3.5%, and LTN3 = 1.0%). Percent errors of mean yield predictions during 1985-1991 were larger than during the first period. Simulated and observed mean yields during 1958-1991 were highly correlated (R2 = 0.961, p < 0.01). Simulated SOC agreed well with observed values with percent errors from -5.8 to 0.5% in 1984 and from -5.1 to 0.7% in 1990. EPIC captured the dynamics of SOC, SCS, and microbial biomass. Simulated net N mineralization rates were lower than those from laboratory incubations. Improvements in EPIC's ability to predict annual variability of crop yields may lead to improved estimates of SCS.     

Sensitivity of SCS Models to Curve Number Variation1

ABSTRACT: The Soil Conservation Service (SCS) models, including the TR-20 computer program and the simplified methods in TR-55, are widely used in hydrologic design. The runoff curve number (CN), which is an important input parameter to SCS models, is defined in terms of land use tretments, hydrologic, condition, antecedent soil moisture, and soil type. The objective of this study was to evaluate the sensitivity of the SCS models to errors in CN estimates. The results show that the effects of CN variation decrease as the design rainfall depth increases, such as for the larger storm events. The value and use of the sensitivity curves are demonstrated using a comparison of Landsat and conventionally derived curve numbers for three watersheds in Pennsylvania.     

A COMPUTERIZED DATA BASE FOR FLOOD PREDICTION MODELING1

ABSTRACT: A computerized geographic information system (GIS) was created in support of data requirements by a hydrologic model designed to predict the runoff hydrograph from ungaged basins. Some geomorphologic characteristics (i.e., channel lengths) were manually measured from topographic maps, while other parameters such as drainage area and number of channels of a specified order, land use, and soil type were digitized and manipulated through use of the GIS. The model required the generation of an integrated Soil Conservation Service (SCS) curve number for the entire basin. To this end, soil associations and land use (generated from analysis of Landsat satellite data) were merged in the GIS to acquire a map representing SCS runoff curve numbers. The volume of runoff obtained from the Watershed Hydrology Simulation (WAHS) Model using this map was compared to the volume computed by hydrograph separation and found to be accurate within 19 percent error. To quantify the effect of changing land use on basin hydrology, the GIS was used to vary percentages from the drainage area from forest to bare soil. By changing the basin runoff curve numbers, significant changes in peak discharge were noted; however, the time to peak discharge remained essentially independent of change in area of land use. The GIS capability eliminated many of the more traditional manual phases of data input arid manipulation, thereby allowing researchers to concentrate on the development and calibration of the model and the interpretation of presumably more accurate results.     

SPATIAL VARIABILITY OF CONDUCTWITY AS APPLIED TO DISTRIBUTED PARAMETER INFILTRATION MODELS1

ABSTRACT: Two infiltration models, called VVSIM (variable variance stochastic infiltration model) and EVVSIM (enhanced variable variance stochastic infiltration model), are developed in this study. A distributed parameter infiltration model can estimate the amount of infiltration over a field area by computing the infiltration over zones of the field area. Hydraulic conductivity is the most important parameter determining infiltration in simulations by infiltration models. The performance of an infiltration model depends on how well the model accommodates the complicated spatial distribution of hydraulic conductivity. The two proposed models include the effects of spatial correlation of the conductivity distribution. Virtual conductivity fields are generated using the turning bands method. Monte Carlo simulations show that the proposed models give infiltration estimates more accurate than those obtained by the other models employed.     

Use of a geographic information system for storm runoff prediction from small urban watersheds

The use of computer-assisted map analysis techniques for prediction of storm runoff from a small urban watershed in the United States is investigated. An automated procedure for calculating input parameters for the US Soil Conservation Service (SCS) method of predicting storm runoff volume and peak timing is presented. Advanced techniques of spatial analysis are used to characterize spatial coincidence, surface configuration and effective hydrologic distance. A limited verification of the automated procedure indicates that the model reasonably characterizes water flow. A sensitivity analysis of basin disaggregation suggests that the SCS method yields increased volume and peak discharge predictions as the watershed is divided into smaller and smaller subunits. As a means to demonstrate the practical application of the automated procedure, a simulation of the effects on surface runoff for a potential residential development is presented.     

THE IMPACT OF RUNOFF GENERATION MECHANISMS ON THE LOCATION OF CRITICAL SOURCE AREAS1

ABSTRACT: Identifying phosphorus (P) source areas and transport pathways is a key step in decreasing P loading to natural water systems. This study compared the effects of two modeled runoff generation processes ‐ saturation excess and infiltration excess ‐ on total phosphorus (TP) and soluble reactive phosphorus (SRP) concentrations in 10 catchment streams of a Catskill mountain watershed in southeastern New York. The spatial distribution of runoff from forested land and agricultural land was generated for both runoff processes; results of both distributions were consistent with Soil Conservation Service‐Curve Number (SCS‐CN) theory. These spatial runoff distributions were then used to simulate stream concentrations of TP and SRP through a simple equation derived from an observed relation between P concentration and land use; empirical results indicate that TP and SRP concentrations increased with increasing percentage of agricultural land. Simulated TP and SRP stream concentrations predicted for the 10 catchments were strongly affected by the assumed runoff mechanism. The modeled TP and SRP concentrations produced by saturation excess distribution averaged 31 percent higher and 42 percent higher, respectively, than those produced by the infiltration excess distribution. Misrepresenting the primary runoff mechanism could not only produce erroneous concentrations, it could fail to correctly locate critical source areas for implementation of best management practices. Thus, identification of the primary runoff mechanism is critical in selection of appropriate models in the mitigation of nonpoint source pollution. Correct representation of runoff processes is also critical in the future development of biogeochemical transport models, especially those that address nutrient fluxes.     

History and Development of the NRCS Lag Time Equation1

Abstract: Many of the hydrologic methods that are used in engineering practice today resulted from the Spring Flood of 1936, which blanketed the Northeastern portion of the United States. Because of the flood damage that was caused by this rainfall‐snowmelt event, many federal agencies including the U.S. Army Corp of Engineers and the Soil Conservation Service (SCS) implemented the hydrologic theories that were available in the literature at this time and developed hydrologic procedures for design flow estimation. Sherman had recently published his unit hydrograph theory in 1932, and later in 1938 Snyder, who had been charged by the Water Resource Council to develop a synthetic unit hydrograph, published his famous paper. The SCS unit hydrograph theory was developed by Victor Mockus in the late 1950s. Most if not all of the theories at that time reported the rainfall‐runoff process for floods as a surface phenomenon, and as such those theories all required some type of a timing parameter to estimate watershed response time. This article documents the development of the SCS lag equation.     

DEVELOPMENT AND EVALUATION OF A DIMENSIONLESS UNIT HYDROGRAPH1

ABSTRACT: A generalized unit hydrograph method is developed and evaluated for ungaged watersheds. A key component in this method is the value of a dimensionless storage coefficient. Procedures to estimate this coefficient are given using calibrated values from 142 rainfall-runoff events gaged in watershed located mainly in the Eastern US. Only limited success was obtained in predicting this storage coefficient. Thirty-seven, independent rainfall-runoff events were used to test the proposed technique. The generalized unit hydrograph predicted the observed runoff hydrographs fairly well with considerable improvement in accuracy over the SCS dimensionless unit hydrograph. Approximately one-half of test storms had percent errors in predicted peak flow rates that were less than 34 percent compared to percent error of 88 percent with the SCS method.     

REGIONAL RAINFALL INTENSITY-DURATION-FREQUENCY CURVES FOR PENNSYLVANIA1

ABSTRACT: A statistical analysis of all available continuous hourly and 15-minute duration rainfall records for Pennsylvania was performed to develop an updated procedure to estimate design storms. As a resuit of this study, Pennsylvania was divided into five homogeneous rainfall regions and a set of rainfall intensity-duration curves developed for each region, for return periods of 1 to 100 years and durations ranging from 5 minutes to 24 hours. The PDT-IDF curves were judged to be a better representation of Pennsylvania rainfall than the nationwide TP-40 maps, particularly for storm events of 10-years and lower return periods. The average time distribution of 24-hour storms in Pennsylvania was found to be well represented by the SCS Type II distribution. The Corps of Engineers SPS 24-hour distribution was found to differ appreciably from both the SCS Type H and the Pennsylvania 24-hour storm distribution. For storm durations between 15 and 90 minutes the standard Yarnell intensity-duration curves closely resemble Pennsylvania storm distributions.     

The Ability of Urban Residential Lawns to Disconnect Impervious Area from Municipal Sewer Systems1

Abstract: Runoff from urban catchments depends largely on the amount of impervious surface and the connectivity of these surfaces to the storm sewer drainage system. In residential areas, pervious lawns can be used to help manage stormwater runoff by intercepting and infiltrating runoff from impervious surfaces. The goal of this research was to develop and evaluate a simple method for estimating the reduction in stormwater runoff that results when runoff from an impervious surface (e.g., rooftop) is directed onto a pervious surface (e.g., lawn). Fifty‐two stormwater runoff reduction tests were conducted on six residential lawns in Madison, Wisconsin during the summer of 2004. An infiltration‐loss model that requires inputs of steady‐state infiltration rate, abstraction (defined here as surface storage, vegetation interception and cumulative total infiltration minus steady‐state infiltration during the period prior to steady‐state), and inundated area was evaluated using experimental data. The most accurate results were obtained using the observed steady‐state infiltration rates and inundated areas for each test, combined with a constant abstraction for all tests [root mean squared (RMS) difference = 1.0 cm]. A second case utilized lawn‐averaged steady‐state infiltration rates, a regression estimate of inundated area based on flow‐path length, and lawn‐specific abstractions based on infiltration rate (RMS difference = 2.2 cm). In practice, infiltration rates will likely be determined using double‐ring infiltration measurements (RMS difference = 3.1 cm) or soil texture (RMS difference = 5.7 cm). A generalized form of the model is presented and used to estimate annual stormwater runoff volume reductions for Madison. Results indicate the usefulness of urban lawns as a stormwater management practice and could be used to improve urban runoff models that incorporate indirectly connected impervious areas.