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CLIGEN is the only weather generator that generates internal storm patterns, which are required by many agricultural system models such as the Water Erosion Prediction Project (WEPP) model. The lack of correlation between CLIGEN-generated storm variables may limit those models' abilities to predict surface runoff and soil erosion. The objectives of this study were to: (1) test a distribution-free method for inducing desired rank correlation between generated storm variables, and (2) compare WEPP-predicted runoff and soil loss using measured vs. variously generated storm patterns on eight U.S. sites. Four climate files containing four storm patterns (measured, original uncorrelated CLIGEN output, correlated CLIGEN output, and correlated output with exponentially generated storm durations), along with measured soil, slope, and crop management on each site, were used as input to WEPP. The distribution-free approach was simple to use and capable of inducing desired rank correlation between storm depth and duration and consequently between storm depth and relative peak intensity. Original CLIGEN output after inducing desired correlation considerably improved WEPP runoff and soil loss predictions on most sites where strong correlation between storm depth and duration existed. On average, the relative errors averaged over all sites were reduced from 15.0% to 4.6% for runoff prediction and from 11.1% to 1.5% for soil loss prediction. The use of exponentially distributed storm duration, compared with the original CLIGEN output, doubled the overall relative error for soil loss prediction due to the undesirable alteration of relative peak intensity estimates. Overall results indicate that for better runoff and soil loss prediction, correlated CLIGEN output should be used on sites where strong correlation between storm depth and duration exists.

Erosion prediction utilizing digital elevation models (DEMs) is a logical advancement for automating the simula- tion process for models such as the Water Erosion Prediction Project (WEPP). The effects of using different DEM resolutions on watershed simulations and the ability to accurately predict sediment yield and runoff from different rainfall event sizes were studied using three application methods and data from six research watersheds. Simulating watersheds with a range of resolutions can help address the problem of deciding what topographic DEM resolution is ideal for model simulations of the watershed outlet, the end of each hillslope, and along the slope profiles. The three application methods studied here were: (1) HillslopeChanleng, (2) HillslopeCalcleng, and (3) Flowpath. The two Hillslope methods use a representative slope profile to represent each hillslope in the watershed, and the Flowpath method uses all of the individual flowpaths as model input for WEPP simulations. Results show that the Hillslope methods were not significantly influenced by DEM resolutions; however, there was an observable interaction between resolutions and the Flowpath method. Large rainfall events were pre- dicted better than small events, but fine DEM resolutions did not improve predictions of either large or small rainfall events. Using coarse DEM resolutions for the topographic input will not decrease the accuracy of erosion prediction using the WEPP model and the Hillslope methods, unless the coarseness of the DEM compromises the delineation of the watershed or hill- slopes.

The USDA-Water Erosion Prediction Project (WEPP) demonstrates a new generation of water erosion prediction technology for use in soil and water conservation planning and assessment. The WEPP computer model is based on various interacting natural processes in hydrology, plant sciences, soil physics, and erosion mechanics. The model offers several advantages over existing erosion prediction technology and has the capability of accommodating spatial and temporal variability in topography, soil properties, cropping and management, and sediment detachment and deposition. The model has a wider range of applicability as it accounts for most of the variables affecting runoff and erosion processes. However, considerable validation is required to assess the reliability of predictions obtained from the model. Sixteen-hundred plot years of natural runoff plot data were used for verification and validation of WEPP, including most of data used to develop Universal Soil Loss Equation (USLE). WEPP predictions of soil loss from natural runoff plots at 20 different locations were compared to measured data and existing technology (i.e., USLE and RUSLE). WEPP recorded a model efficiency of 0.71 compared to 0.80 and 0.72 for the USLE and RUSLE respectively. While the USLE and RUSLE did exhibit better model efficiency than WEPP this could be attributed to availability of more refined and site specific input parameters for the empirical models.

Field experiments were conducted on a loam and a silt loam soil to determine the effect of tillage on soil detachment in concentrated flow channels carrying high discharge rates. Soil detachment rates from tilled channels were an order of magnitude greater than rates from no-till channels. Based on a linear constant-parameter soil detachment model, soil erodibility was seven times greater for tilled soil than for no-till, while critical shear values for no-till were about twice that for tilled soil. The coefficient of determination for the soil detachment models improved when soil erodibility and critical shear were related to field measurements of a soil strength index, measured by a fall cone penetrometer and a vane shear device. The fall cone index resulted in better model fits (greater R2) than the vane shear index for modeling soil erodibility and critical shear. Both linear and exponential equations were used to model soil detachment rates. An exponential equation with detachment related to excess shear, which has both soil erodibility and critical shear as linear functions of soil strength, is the recommended form for modeling soil detachment from high discharge concentrated flow.

Conservation Reserve Program (CRP) areas that are returned to crop production will initially be much less erodible than fields which were farmed using conventional practices. In this study, a rainfall simulator was used to measure runoff and erosion from former CRP areas in Mississippi, Nebraska and South Dakota over approximately a two year period. Soil loss rates measured immediately following tillage on each of the three sites were similar to values obtained on the undisturbed CRP treatments. However, when left in a fallow condition, the erosion-reducing effectiveness of the sod appeared to have lasted less than one year. The rapid increase in soil erodibility following tillage was attributed to a reduction in surface cover and organic material. The WEPP and RUSLE models are currently used extensively in conservation planning and assessment. The experimental data collected in this study were used to derive selected parameter values for use in these models.

The Water Erosion Prediction Project (WEPP) watershed scale model is a continuous simulation tool that extends the capability of the WEPP hillslope model to provide erosion prediction technology for small cropland and rangeland watersheds. The model is based on fundamentals of erosion theory, soil and plant science, channel flow hydraulics, and rainfall-runoff relationships, and contains hillslopes, channels, and impoundments as the primary components. The hillslope and channel components can be further divided into hydrology and erosion components. Channel infiltration is calculated by a Green-Ampt Mein-Larson infiltration equation. A continuous channel water balance is maintained, including calculation of evapotranspiration, soil water percolation, canopy rainfall interception, and surface depressional storage. The channel peak runoff rate is calculated using either a modified Rational equation or the equation used in the CREAMS model. Flow depth and hydraulic shear stress along the channel are computed by regression equations based on a numerical solution of the steady state spatially varied flow equations. Detachment, transport, and deposition within constructed channels or concentrated flow gullies are calculated by a steady state solution to the sediment continuity equation. The impoundment component routes runoff and sediment through several types of impoundment structures, including farm ponds, culverts, filter fences, and check dams. The purpose of this article is to provide an overview of the model conceptual framework and structure. In addition, detailed mathematical representations of the processes simulated by the channel hydrology and erosion components are presented. The processes simulated by the impoundment component are not described in this article, but it does include impoundment effects on watershed model channel peak discharge and time of concentration calculations.

An excess shear sediment detachment relation is commonly used in erosion prediction models. Traditional field methods for calibration of soil-dependent empirical constants are both expensive and conceptually suspect. The subprocesses of sediment detachment and transport cannot be physically separated, therefore they cannot be calibrated independently. Impingement of a clear-water jet on a soil bed produces detachment without transport at the point of maximum scour. In this article, a mathematical description of the impinging jet scour process is used to calibrate an excess shear detachment relation. Four calibration models are developed based on variants of the jet-scour rate equations (differential and integral form, each evaluated using arithmetic and logarithmic values for dependent variables). All models assume detachment is linearly related to excess shear. The validity of this calibration technique has been tested in the laboratory by measuring scour depth versus time for six different soils, all evaluated in a disturbed, saturated condition. A total of 14 replicates on the soils were conducted where hydraulic inputs were varied with replicate. Statistical analyses were used to place confidence limits about the optimal sediment detachment values for each of the four models. Only the arithmetic differential model produced results considerably different than the other three. The integrated log model produced the tightest confidence intervals and this is suggested for further use. The size of the confidence intervals demonstrates the replicability of the technique. The technique produced detachment rate constants that are similar to field calibration studies for soils of similar properties. Critical shear values are an approximate order of magnitude lower, but all soils were evaluated only in the highly erosive, disturbed, unconsolidated, and saturated condition. The technique can be applied to soils in other conditions and it is possible that this discrepancy is due to different soil conditions.

Accurate erosion prediction on rainfed cropland of the Northwestern Wheat and Range Region has been severely hampered by lack of suitable slope length and steepness relationships. Relationships derived from data from the humid regions of the United States over-predicted the effect of slope steepness for the steep slopes commonly cultivated in the Pacific Northwest.

The physically based erosion model developed by the Water Erosion Prediction Project (WEPP) of the USDA requires input data that are not routinely measured or estimated in the field. Low altitude photogrammetry data were collected at 12 rangeland locations to measure surface micro-elevations needed to estimate hydraulic geometries of the flow. The photogrammetry contour data were converted to cross-sections, and used to calculate the hydraulic geometries and flowpath density on each cross section. The erosion prediction segment of the WEPP model was optimized with the photogrammetrically derived parameters used as input. The low-altitude photogrammetry makes the measurement of surface hydraulic properties possible on low-relief rangelands resulting in more accurate soil erosion predictions.

Sensitivity analysis was performed on the hillslope profile erosion model developed by the USDA-Water Erosion Prediction Project. The erosion model calculates soil loss and sediment yield caused by rill and interrill erosion on complex shaped hillslope profiles. Sensitivity analysis of a physically based simulation model is used for assessing the rationality of the model, to provide insight into the overall physical system which the simulation model represents, and to help identify research needs. Changes in predicted soil erosion and sediment yield as a function of changes in soil, plant residue and canopy, hillslope topography, and hydrologic input variables were assessed. Dominant factors related to model response were precipitation, rill erodibility, rill residue cover, and rill hydraulic friction factors. Saturated hydraulic conductivity and interrill erodibility were moderately sensitive parameters. Other factors which had less influence on output were canopy height, interrill cover, soil bulk density, antecedent moisture, peak rainfall intensity, time to pe^ rainfall intensity, rill width and spacing, and sediment characteristics. Slope length, gradient, and slope shape effects on soil loss and sediment delivery were also discussed.

The quality of synthesized daily weather data directly affects the output of hydrological and agricultural response models. The objectives of this study were to evaluate the ability of the CLIGEN model to reproduce daily, monthly, and annual precipitation amounts, extremes, and internal storm patterns (i.e., storm duration, relative peak intensity, and time to peak) and to assess further the impact of generated storm patterns on WEPP runoff and erosion prediction. Four Oklahoma stations with more than 50 years of daily precipitation data and eight other sites across the U.S. with an average record of 10 years of measured storm patterns were used. Mean absolute relative errors for simulating daily, monthly, and annual precipitation across the four Oklahoma stations were 4.7%, 1.7%, and 1.5% for the means and 3.7%, 6.7%, and 15% for the standard deviations, respectively. Mean absolute relative errors for the all–time maxima of daily, monthly, and yearly precipitation were 17.7%, 8.9%, and 6.5%, respectively. Storm pattern generation, especially storm duration, was determined to need improvement for better prediction of runoff and soil erosion. The measured storm patterns showed positive linear correlations between precipitation, duration, and relative peak intensity, but little correlation was shown for generated storm patterns. The CLIGEN–generated durations were generally too long for small storms and too short for large storms. Inaccurate storm pattern generation led to WEPP prediction errors as high as 35% for average annual runoff and 47% for annual sediment yield on the test sites. To improve WEPP runoff and erosion prediction, storm duration generation should be reconsidered, and a distribution–free approach may be used to induce proper correlations between the input storm variables.

CLIGEN is a stochastic weather generator that produces continuous daily variables to drive process–based runoff and erosion prediction models such as WEPP. To test CLIGEN’s ability to generate precipitation–related variables, which are particularly important to runoff and erosion prediction, algorithms were developed to compute the R–factor, its monthly distribution, and 10–year storm erosion index (EI) needed to apply the Revised Universal Soil Loss Equation (RUSLE). Measured R–factor and 10–year storm EI for 76 sites in the U.S. were used for calibration, and 89 additional sites were used for validation. It was found that the generated R–factor using CLIGEN is highly correlated with the measured R–factor for the calibration sites (r2 = 0.96), although the generated R–factor is systematically larger than the measured R–factor. The predicted R–factor for validation sites has a model efficiency (Ec) of 0.92 and a root mean squared error of around 600 MJ mm ha–1 h–1 year–1, or 24% of the average R–factor for the 89 sites. In addition, CLIGEN–generated precipitation data can also be used to predict 10–year storm EI (Ec = 0.75) and monthly distribution of rainfall erosivity for a wide range of climate environments (average discrepancy = 2.6%). This represents considerable improvement over existing methods to estimate R–factor and 10–year storm EI for locations with only monthly precipitation data, although the systematic over–estimation of the R–factor using CLIGEN–generated climate data suggests possible inadequacies in the assumed storm patterns in CLIGEN and WEPP.

Potential runoff and erosion is a serious problem for some types of sprinkler irrigation systems, particularly traveling laterals and center pivots on medium– to heavy–textured soils operating on sloping land. Prediction of when runoff might occur is part of the system design process. The USDA–ARS Water Erosion Prediction Project (WEPP) model was tested with 3 years of field data under high–rate sprinklers in southern Idaho. Runoff and soil loss were measured on the upper, middle, and lower portions of a hillslope. The main parameter affecting infiltration and runoff was the effective hydraulic conductivity. Model predictions for average runoff and soil loss were improved when hydraulic conductivity values were adjusted to account for soil variability across the field. Runoff amounts were small, and prediction variability for individual furrows was quite high, but no more than would be expected from previous studies of infiltration variability. Soil loss predictions were unreliable for the small runoff amounts occurring in this study. The most reasonable use of WEPP for sprinkler irrigation would be for estimating when potential runoff might occur under center pivots for different soils, slopes, and crop management practices, and to determine limits on application depths and rates to avoid serious runoff.

The forms of the sediment continuity equation used in process-based erosion prediction models do not allow for direct analytical solution for soil erodibility parameters for the case when performing rills is not practical or desirable. Therefore, erodibility parameters cannot be calculated from rangeland field erosion data using simple regression unless simplifying assumptions are made which may compromise the accuracy of the parameter estimates. This study developed an optimization technique for determining erodibility parameters from rangeland field data for use in a three parameter steady-state erosion model, and evaluated the method's effectiveness. Model response to variation of the erodibility parameters was also evaluated. Estimated erodibility parameter values characterized the measured data adequately. Model response surface shapes did not indicate problems in terms of parameter identifiability, strong interdependence or sensitivity.

Amodel was developed for estimating soil erosion by water on hillslopes for use in new USDA erosion prediction technology. Detachment, transport, and deposition processes were represented. The model uses a steady-state sediment continuity equation for predicting rill and interrill processes. Net detachment in rills is considered to occur when the hydraulic shear stress of flow exceeds the critical shear stress of the soil and when sediment load in a rill is less than the sediment transport capacity. Net deposition is calculated when the sediment load is greater than the transport capacity. Rill detachment rate is dependent upon the ratio of sediment load to transport capacity, rill erodibility, hydraulic shear stress, surface cover, below ground residue, and consolidation. Rill hydraulics are used to calculate shear stresses and a simplified transport equation, calibrated with the Yalin transport equation, is used to compute transport capacity in rills. Interrill erosion is represented as a function of rainfall intensity, residue cover, canopy cover, and interrill soil erodibility. The model has capabilities for estimating spatial distributions of net soil loss and is designed to accommodate spatial variability in topography, surface roughness, soil properties, hydrology, and land use conditions on hillslopes..