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The Soil and Water Assessment Tool (SWAT) and the Geographic Water Erosion Prediction Project (Geo-WEPP) were applied to compare modeling of annual runoff and sediment yield in the Agewmariam watershed, eastern Amhara Region, Ethiopia. Spatial and temporal data distributions were required as inputs to run both models. Soil texture and other soil properties were measured in the field and in the laboratory, and soil maps were generated from global digital soil maps. Land use maps were created by manually digitizing Google Earth images. Watersheds were defined using watershed DEMs and gradient maps were created for each runoff event. Runoff samples were collected and analyzed for sediment concentrations in the laboratory; average annual runoff and sediment volumes were estimated using the WEPP and SWAT models. The results were satisfactory compared to the observed values, with R2 values of 0.86 and 0.91 for the SWAT and WEPP models, respectively, and NSE values of 0.54 and 0.71 for the monthly runoff. The estimated annual mean runoff and sediment yield at the watershed outlets were 65.54 mm, 146.14 mm, 43t/ha/yr and 41.7t/ha/yr for the WEPP and SWAT models, respectively. Several sub watersheds were determined to be susceptible to soil erosion and were prioritized, so more attention was given to this area to reduce runoff and soil erosion. Therefore, the SWAT and WEPP models were suitable for estimating annual runoff and sediment volumes. Sediment yields simulated from both models were high and alarming and far exceeded the allowable rate of soil loss. [ABSTRACT FROM AUTHOR]

Water erosion is an ongoing problem in eastern Washington due to its hilly terrain, highly erodible silt loam soils, rain on thawing soil, and the prevalence of conventional tillage. The region is characterized by a Mediterranean-type climate with warm, dry summers and cool, wet winters. Three distinct precipitation zones, with annual totals low (<380 mm), intermediate (380-460 mm), and high (>460 mm), dictate the area's crop rotations. A unique 43-year (1940-1982) dataset of winter erosion measured on multiple agricultural fields in Whitman County, eastern Washington, by Verle Kaiser, a USDA Soil Conservation Service agronomist, showed annual erosion rates averaging 53.8 Mg ha-1, far exceeding the current Natural Resources Conservation Service tolerable limit of 11 Mg ha-1 yr-1 for the soils in the area. Kaiser's field data allowed us to compare the historical field-measured erosion rates with those simulated by the WEPP (Water Erosion Prediction Project) model. Anthropogenic factors, such as tillage and crop rotation, change with time. Conservation tillage, including reduced- and no-till, has been increasingly adopted in eastern Washington since the mid-1980s. The specific objectives of this study were to (1) apply the WEPP model to simulate soil erosion in eastern Washington and evaluate the interactive effects of climate and management, in addition to topography and soil, on water erosion in the study area, and (2) compare the simulation results with Kaiser's historical field dataset and elucidate the long-term soil erosion trend. The WEPPcloud interface was used to delineate a watershed within each precipitation zone of the study area. Climate inputs were divided into two periods: the past (1939-1982) and the present (1983-2020). Erosion has noticeably decreased from the past to the present, with WEPP simulated annual erosion averaging 13.5, 34.5, and 52.6 Mg ha-1 for the past, and 9.5, 14.1, and 15.5 Mg ha-1 for the present, in the selected watersheds in the low-, intermediate-, and high-precipitation zones, respectively. The decreasing trend was primarily due to the increased adoption of conservation tillage and crop rotation, as well as a decrease in the number of high-intensity precipitation events in the present climate. [ABSTRACT FROM AUTHOR]

Water erosion is an ongoing problem in eastern Washington due to its hilly terrain, highly erodible silt loam soils, rain on thawing soil, and the prevalence of conventional tillage. The region is characterized by a Mediterranean-type climate with warm, dry summers and cool, wet winters. Three distinct precipitation zones, with annual totals low (<380 mm), intermediate (380-460 mm), and high (>460 mm), dictate the area's crop rotations. A unique 43-year (1940-1982) dataset of winter erosion measured on multiple agricultural fields in Whitman County, eastern Washington, by Verle Kaiser, a USDA Soil Conservation Service agronomist, showed annual erosion rates averaging 53.8 Mg ha-1, far exceeding the current Natural Resources Conservation Service tolerable limit of 11 Mg ha-1 yr-1 for the soils in the area. Kaiser's field data allowed us to compare the historical field-measured erosion rates with those simulated by the WEPP (Water Erosion Prediction Project) model. Anthropogenic factors, such as tillage and crop rotation, change with time. Conservation tillage, including reduced- and no-till, has been increasingly adopted in eastern Washington since the mid-1980s. The specific objectives of this study were to (1) apply the WEPP model to simulate soil erosion in eastern Washington and evaluate the interactive effects of climate and management, in addition to topography and soil, on water erosion in the study area, and (2) compare the simulation results with Kaiser's historical field dataset and elucidate the long-term soil erosion trend. The WEPPcloud interface was used to delineate a watershed within each precipitation zone of the study area. Climate inputs were divided into two periods: the past (1939-1982) and the present (1983-2020). Erosion has noticeably decreased from the past to the present, with WEPP simulated annual erosion averaging 13.5, 34.5, and 52.6 Mg ha-1 for the past, and 9.5, 14.1, and 15.5 Mg ha-1 for the present, in the selected watersheds in the low-, intermediate-, and high-precipitation zones, respectively. The decreasing trend was primarily due to the increased adoption of conservation tillage and crop rotation, as well as a decrease in the number of high-intensity precipitation events in the present climate. [ABSTRACT FROM AUTHOR]

There is growing interest in studying the impact of alternative agricultural management practices on runoff and soil loss under future climate change scenarios. In order to address this interest, it is important to demonstrate that runoff and soil loss can be accurately simulated under existing climates based on comparisons between modeled and experimental results. This study calibrates and validates the Water Erosion Prediction Project (WEPP) model to quantify the accuracy of predicting growing season runoff and soil erosion in agricultural hillslopes based on comparisons with experimental data from five Minnesota hydrologic unit code 12 watersheds. In order to accurately predict runoff and soil erosion in each watershed, the baseline effective hydraulic conductivity (Kbe), interrill and rill erodibility (EIR and ER), and monthly precipitation standard deviations (Pstdev) were calibrated in WEPP using observed runoff and total suspended solids data from five Minnesota Discovery Farms field sites. Before calibration, Nash–Sutcliffe model efficiency (NSE) and percent bias (PBIAS) values for predicted versus measured monthly average total runoff (Ravg‐T), runoff ratios (RRT), and total soil loss were generally not in acceptable ranges. After calibration, the NSE values showed very good fits between measured and predicted monthly Ravg‐T (0.64–0.98), RRT (0.66–0.93), and soil loss (0.58–0.80). PBIAS values were also within acceptable ranges for Ravg‐T and RRT (±25%) and soil loss (±55%), except for RRT at site BE1. NSE and PBIAS values during validation were within acceptable ranges, except for RRT at site BE1. These findings suggest that the WEPP hillslopes calibrated in this study are sufficiently robust to accurately predict monthly runoff and soil erosion in Minnesota agricultural fields during the growing season. [ABSTRACT FROM AUTHOR]

In the late 1980s, the USDA Agricultural Research Service, along with other federal agencies and multiple universities, collaborated to develop a new physically based soil erosion model, the Water Erosion Prediction Project (WEPP) Model. The WEPP model was intended to replace the Universal Soil Loss Equation and was to include estimates for upland runoff and erosion, sediment delivery to first order channels, and runoff and sediment routing through a downstream channel network. The WEPP technology estimated erosion from raindrop splash and sheet flow (interrill erosion) and concentrated channel flow (rill erosion). To make these erosion estimates, WEPP required new soil erodibility values for interrill erodibility (Ki). rill erodibility (Kr), and critical shear (𝜏𝜏 c) for concentrated flow erosion. The WEPP Core team determined that they needed to estimate these three erodibility values from measurable soil properties for a wide range of soil conditions. To develop relationships between WEPP soil erodibility variables and other soil properties, a field study was carried out using rainfall and runoff simulation to measure the three erodibility values for 36 soils. Sites were identified on croplands from Washington to Georgia and Maine to California, USA for erodibility measurement. Concurrently, the USDA Soil Conservation Service (SCS) carried out detailed soil surveys and laboratory analyses for all sites to provide a large database of soil physical, chemical, and engineering properties. Correlation and regression analyses were carried out to develop relationships between SCS measurable soil properties and WEPP soil erodibility values. This article provides a summary of the field procedures, data analyses, and subsequent predictive equations that were developed. The predictive equations that were finalized in the WEPP User Summary used sand, very fine sand, clay, and organic carbon contents to predict cropland soil erodibility, but the Coefficient of Determination (r²) values were 0.55 or less. More complex predictive equations were developed with soil physical, chemical, mineralogical, and geomorphic properties, with r² values up to 0.81. Most of the better predictive equations included terms for soil texture and clay mineralogy, often with additional chemical properties. A set of simplified erodibility equations using only the readily available properties of soil texture, organic carbon, cation exchange capacity, slope steepness, and taxonomic order were derived for use within the WEPP Model, with r² values greater than 0.5 for all three equations for estimating soil erodibility from measurable soil properties. [ABSTRACT FROM AUTHOR]

Predicting soil erosion by water is an essential natural resource management activity. The Water Erosion Prediction Project (WEPP) model is a process-based continuous simulation tool based on erosion mechanics and channel hydraulics. Due to the extensive data requirements, preparing input parameter settings for WEPP can be time-consuming. A Geospatial Interface for WEPP (GeoWEPP) overcame this major disadvantage but had limitations regarding keeping track of operating systems and proprietary software updates. QGeoWEPP is a newly developed open-source QGIS-based GeoWEPP, offering additional novel user-based customizations of model simulations including validation data sets. QGeoWEPP provides a platform for applying WEPP at the hillslope and watershed scales that integrates the whole model application and validation process. QGeoWEPP allows applying WEPP in any study area worldwide with minimum data limitations and more spatial and temporal capabilities in areas such as soil and water conservation, land management, geohazard assessment due to land use and climate change, and many more. • Open-source, process-based GIS interface to model watershed runoff and erosion. • Provides spatial and temporal validation datasets to customize model interface. • Includes statistical evaluation module to evaluate and validate model outputs. • Enables users to include remote sensing derived land use or land cover changes. • Geohazard assessments of terrain changes based on Digital Elevation Models. [ABSTRACT FROM AUTHOR]

The USDA Water Erosion Prediction Project (WEPP) is a process-based soil erosion prediction model. WEPP uses three soil erodibility parameters: rill erodibility (Kr), interrill erodibility (Ki), and critical hydraulic shear stress (tc). In this study, a new parameterization approach for estimating erodibility was developed for WEPP applications on rangelands. Data from overland flow experiments on disturbed and undisturbed rangelands were used to develop empirical equations to predict rill erodibility variation as a function of vegetation cover and soil texture. Data from rainfall simulation experiments were analyzed by piecewise regression to develop empirical equations for predicting the variability of interrill erodibility before and after disturbance and across a wide range of soil textures as a function of vegetation cover and soil texture. Critical shear values corresponding to the developed rill and interrill erodibility parameters were proposed. Our results show that the new erodibility approach predicts erosion at the plot scale with a satisfactory range of error (PBIAS =35.6 and Nash-Sutcliffe efficiency = 0.49). The new approach was used to provide soil erodibility values for the Erosion Risk Management Tool (ERMiT), which uses WEPP as the runoff and erosion calculation engine. [ABSTRACT FROM AUTHOR]

A strong need exists for tools to assess the efficacy of conservation practices across large regions supporting informed policy decisions that may lead to better soil and water conservation while optimizing agricultural production options. Perennial warm‐season grasses (WSGs) such as switchgrass (Panicum virgatum), can be grown on marginally productive and/or environmentally sensitive lands to meet growing bioenergy demands while reducing water runoff and soil erosion compared to current row crop systems. Quantifying the soil and water conservation effects of WSG when strategically placed on the landscape would help support decisions favoring both economic and environmental benefits. We used the Daily Erosion Project (DEP) to simulate the effects of WSGs on hillslope water runoff and soil loss for 2008–2016 across eight major land resource areas (MLRA) in the Midwest United States. Four different scenarios (baseline or existing conditions and switchgrass grown on slopes ≥3%, ≥6%, and ≥10%) were modeled. Across all hillslope groups replacing row crops with switchgrass reduced yearly water runoff and soil loss by 3.2%–12.1% and 43.7%–95.5% compared with the baseline levels, respectively. Water and soil conservation efficiency (water runoff reductions or soil loss reductions associated with 1% increase in switchgrass coverage) increased with slope as 10% > 6% > 3% for all MLRAs. Switchgrass replacement on slopes ≥10% reduced average soil loss estimates as much as 22.6 Mg ha−1 year−1 for the most erosive MLRA (baseline soil erosion rate of 28.6 Mg ha−1 year−1) and resulted in all MLRA erosion estimates ≤6.0 Mg ha−1 year−1. For soil loss, an apparent interaction existed between slope group and total annual precipitation; as annual precipitation increased, the difference in soil loss between slope groups increased. Soil loss was more sensitive to these factors than was water runoff. Policy supporting a renewable energy industry while strategically improving soil and water resources seems globally advantageous. [ABSTRACT FROM AUTHOR]

Climate change makes it necessary to re-evaluate the erosion potential of forest infrastructure. We used the Forest Service WEPP interfaces (FS WEPP) to compare soil erosion potentials of two competing logging practices in steep terrain in the Northern Black Forest, Germany: (1) Felling with harvesters and logging with forwarders in slope line with optional traction supporting winches. (2) Felling by chainsaw, logging with a cable winch, and further transport of logs via forest dirt roads. After forest harvest we measured erosion, runoff, and DOC concentration in runoff from 50 m sections of two machine tracks, two cable tracks, and a dirt road for 2 years. The erosion measurements were used to validate FS WEPP management options and a regionally adjusted CLIGEN input file. With these parameterizations we compared the erosion potential of the two practices on subcatchment scale by modeling return periods and total sediment export with FS WEPP. Model results show that logging operations with heavy machinery in slope line are less prone to soil erosion than logging operations including winch logging and additional dirt roads. The former produces less sediment in its worst-case configuration than the latter in its most moderate configuration by a factor of two. Model results also show that erosion prevention benefits from long periods of 10 years between two harvests. [ABSTRACT FROM AUTHOR]

Through the indoor runoff tank flushing test, it was found that the sand production efficiency of the Pisha-sandstone firstly increased with the time passed and then decreased and finally stabilized. The peak of sand production occurred in 2~4 min. With the increase of slope, the peak of sediment yield appeared in advance, the sediment concentration increased obviously, between the slopes of 15° and 35° existed a value and near the critical value the sediment yield was higher. The erosion parameters K and the critical shear stress r. under the erosion conditions of the Pisha-sandstone were obtained by the WEPP soil water erosion prediction model. The results show that the erodibility parameters of the Pisha-sandstone are only 0.002 kg / (N • s) at the slope of 5°, which is much smaller than that of other slopes. So when the slope is less than 5° the erosion is difficult to occur, while the erosion parameters of the slope of the Pisha-sandstone of 10°, 15°, 25° and 35° are 0.048 2 kg/(N • s). The prediction model of rill erosion under Pisha-sandstone erosion conditions was established to verify the applicability of the model. [ABSTRACT FROM AUTHOR]

To estimate the impact of highly erosive precipitation on existing and planned forest infrastructure we deem the Forest Service WEPP Interfaces, based on the Water Erosion Prediction Project (WEPP), feasible. As a first step towards testing WEPP and especially the implemented weather generator CLIGEN for conditions in Germany we evaluated the application of CLIGEN to calculate rain erosivities from generated time series. CLIGEN parameters were taken from time series of up to 17 years with 10-minute resolution from three sites in the Northern Black Forest, southwestern Germany. We assessed a rain kinetic energy function for this region from field measurements with a laser disdrometer to compare CLIGEN performance using the local function to using common kinetic energy functions. We showed that running CLIGEN with unaltered input parameters is not suitable to model climatic conditions and erosivity indices in the Northern Black Forest. R-factors from unaltered model runs deviated extremely from observed R-factors, resulting in just one third of observed values. Model performance and parameter uncertainties do not benefit much from the use of a site specific kinetic energy function. Differences in model errors and sensitivities compared to a well-established kinetic energy function remain negligible. However, model output was improved by empirical calibration of input data. Virtual best parameter sets for best model results could be identified. To reproduce observed rain erosivities the input parameters of CLIGEN have to be manipulated to model a precipitation regime where daily precipitation amounts and maximum precipitation intensities are higher at a lower number of rainy days. We also identified the input parameters to which the model is most sensitive to when manipulated, i.e. precipitation amount and frequency, and maximum peak precipitation. These parameters are especially important when implementing future climate change scenarios. [ABSTRACT FROM AUTHOR]

Nonpoint-source (NPS) pollutants, especially from agriculture, continue to be a primary source of water quality degradation problems. Effective land management decisions at the field scale must be made to minimize nutrient losses that could pollute streams. Existing NPS models often cannot directly estimate the impacts of different land management practices or determine the effectiveness of combined best management practices (BMPs) in a distributed way at the farm scale. In many cases, they rely on application of the Universal Soil Loss Equation (USLE) or its improved versions, which represent fields in a lumped fashion and use empirical rather than process-based modeling methodologies. In this study, a coupled Water Erosion Prediction Project and Water Quality (WEPP-WQ) model was completed, updated, improved, and evaluated for simulation of hydrology, soil erosion, and water quality. The WEPP model is a well-established process-based model that simulates runoff and erosion processes from a hillslope. The water quality components are based on those of the Soil and Water Assessment Tool (SWAT). A single overland flow element (OFE) on a hillslope is used to represent a single soil and land use management. The WEPP-WQ model was tested by comparing simulated values from the coupled model with observed nutrient and sediment concentrations in surface runoff following storm events at experimental sites near Waterloo in northeastern Indiana and at the Throckmorton Purdue Agricultural Center in west central Indiana. Time series evaluation of the WEPP-WQ model was performed with observed nutrient and sediment losses from an experimental plot near Tifton, Georgia. The model performed quite well in simulating nutrient losses for single storm events, with R2 greater than 0.8, Nash-Sutcliffe efficiency (NSE) greater than 0.65, and percent bias (PBIAS) less than 31% for runoff, sediment, nitrate nitrogen, total nitrogen, soluble phosphorus, and total phosphorus losses. In predicting time series nutrient loss, the WEPPWQ model simulated daily nitrate nitrogen losses adequately, with the ratio of the root mean square error to the standard deviation of measured data (RSR) less than 0.7, NSE greater than 0.55, and PBIAS within the range of ±40%. Comparisons between simulated soluble phosphorus, total phosphorus, and literature results were performed due to the absence of an available observational dataset. The WEPP-WQ model with a single OFE in this study provides a basic but important step for the development of WEPP-WQ models with multiple OFEs that can evaluate the effectiveness of BMPs. [ABSTRACT FROM AUTHOR]

The Water Erosion Prediction Project (WEPP) model was originally developed for hillslope and small watershed applications. Recent improvements to WEPP have led to enhanced computations for deep percolation, subsurface lateral flow, and frozen soil. In addition, the incorporation of channel routing has made the WEPP model well suited for large watersheds with perennial flows. However, WEPP is still limited in modeling forested watersheds where groundwater baseflow is substantial. The objectives of this study were to (1) incorporate nonlinear algorithms into WEPP (v2012.8) for estimating groundwater baseflow, (2) auto-calibrate the current and modified WEPP model using a model-independent parameter estimation tool, and (3) evaluate and compare the performance of the current version of WEPP without baseflow (WEPP-Cur) and the modified WEPP model with baseflow (WEPP-Mod) in simulating the hydrology of a snow-dominated watershed in the U.S. Pacific Northwest. A subwatershed of the Upper Cedar River Watershed in western Washington State was chosen for WEPP application and assessment. Simulations were conducted for two periods: 1997-2003 to calibrate the model and 2004-2011 to assess the model performance. The WEPP-Cur simulations resulted in Nash-Sutcliffe efficiency (NSE) and deviation of runoff volume (Dv) values of 0.55 and 24%, respectively, for the calibration period, and 0.60 and 21%, respectively, for the assessment period. The WEPP-Mod simulated streamflow showed improved agreement with observed streamflow, with NSE and Dv values of 0.76 and 6%, respectively, for the calibration period, and 0.74 and 2%, respectively, for the assessment period. The WEPP-Mod model reproduced hydrograph recessions during the low-flow periods and the general trend of the hydrographs, demonstrating its applicability to a watershed where groundwater baseflow was significant. The incorporation of a baseflow component into WEPP will help forest managers to assess the alterations in hydrological processes and water yield for their forest management practices. [ABSTRACT FROM AUTHOR]

Forest roads are a concern in management because they represent areas of elevated risks associated with soil erosion and storm runoff connectivity to stream systems. Storm runoff emanating from forest roads and their connectivity to downslope resources can be influenced by a myriad of factors, including storm characteristics, management practices, and the interaction of management practices and successive storm events. Mitigating sediment export and ensuring that storm runoff has negligible impacts on downstream resources requires a more complete understanding of forest road erosion and sediment delivery dynamics. Progress in the area of road and stream connectivity issues hinges on reliable prediction tools to inform broader-scale modeling of watershed-scale effects of forest roads and management practices. In this study, the Water Erosion Prediction Project (WEPP) model was evaluated based on the results from 156 runoff-generating storm events during a continuous five-year study of nine high-elevation road sections in the Appalachian Mountains. The model adequately predicted sediment yield from the road sections with an overall Nash-Sutcliffe model efficiency (E) of 0.76, Willmott refined index of agreement (dr) of 0.56, percent error of 5%, and average storm difference (ASD) of 1.2 kg. In contrast, WEPP predictions of storm runoff were not as good, and the poor agreement was attributed to an inability to determine the source area for runoff from some of the larger runoff events. In general, the WEPP model for these highelevation sites adequately described the sediment yield for the road sections. [ABSTRACT FROM AUTHOR]

Modeling soil detachment rates at the regional scale is important for better understanding of the processes of erosion and the development of erosion models. Soil erodibility is an important factor for predicting soil loss, but its direct measurement at the watershed scale is difficult, time-consuming and costly. This study used stepwise multiple-linear regression (MLR) and artificial neural networks (ANNs) to model Water Erosion Prediction Project (WEPP) soil erodibility parameters, including the baseline inter-rill erodibility (K ib ), baseline rill erodibility (K rb ) and critical shear stress (τ cb ) of cropland conditions in calcareous soils of northwest Iran. Simulated inter-rill and rill erosion experiments were conducted at 100 locations with three replications. K ib , K rb and τ cb and basic soil properties were measured at each location. Auxiliary variables related to soil erodibility were derived from a Landsat 7 satellite image and a 30 m × 30 m digital elevation model (DEM). MLR and ANN models were employed to predict K ib , K rb and τ cb using two groups of input variables: i) more easily measurable basic soil properties (pedo-transfer functions (PTFs)) and ii) more easily measurable basic soil properties and auxiliary data (soil spatial prediction functions (SSPFs)). The results indicated that the WEPP models performed poorly in comparison to the derived models. PTFs and SSPFs generated from ANN models provided more reliable predictions than the MLR models. ANN-based SSPF models yielded the best results (with the highest R 2 and lowest RMSE values) for predicting K ib and K rb . ANN-based PTF model performed reasonably well for predicting τ cb . These results show that information from terrain attributes and remote sensing data are potential auxiliary variables for improving prediction of soil erodibility parameters. [ABSTRACT FROM AUTHOR]

Soil erodibility is a key factor for estimating soil erosion using physically based models. In this study, a new parameterization approach for estimating erodibility was developed for the Rangeland Hydrology and Erosion Model (RHEM). The approach uses empirical equations that were developed by applying piecewise regression analysis to predict the differences of erodibility before and after disturbance (i.e., wildfire, prescribed fire, and tree encroachment) and across a wide range of soil textures as a function of vegetation cover and surface slope angle. The approach combines rain splash, sheet flow, and concentrated flow erodibilities into a single parameter for modeling erodibility in most cases. We evaluated the new approach for sites representing different degrees of disturbance associated with burning and tree encroachment. Our results show that the new erodibility approach in RHEM predicts erosion at the plot scale with a satisfactory range of error in all cases. The new approach extends the applications of RHEM to a greater scope of landscapes and soil texture. [ABSTRACT FROM AUTHOR]

Hydrologic models are often used to predict erosion and the influence of land cover changes on sediment detachment within a watershed. One such model, the Water Erosion Prediction Project (WEPP), determines the runoff and sediment yield of a given hillslope using input data including slope, climate, soil, and land management. WEPP accepts user inputs or uses empirical equations to determine two major erodibility parameters within the soil input file: critical shear stress (τc) and the erodibility coefficient (kd). WEPP also uses adjustment coefficients to account for vegetation and seasonal effects on erodibility. This study evaluated soil erodibility parameters under two distinct land covers: native tallgrass prairie and encroaching eastern redcedar (Juniperus virginiana) woodland. The erodibility parameters for each watershed were first estimated using WEPP with rangeland and cropland relationships, using the Rangeland Hydrology and Erosion Model (RHEM), and then determined mechanistically in the field using the Jet Erosion Test (JET). The adjusted kd predicted by WEPP for all watersheds was less than the JET-derived kd by one to two orders of magnitude. The baseline and adjusted τ c from WEPP-cropland were typically within the same order of magnitude as the JET-derived τc. The WEPP erodibility parameters were most directly correlated with the soil texture and were independent of land cover. Alternatively, the JET-derived erodibility parameters were significantly different between the two land covers, with no relationship observed with soil texture. Calibrated WEPP simulations based on the measured runoff response from each watershed did not indicate differences in predicted sediment transport for the various erodibility parameter estimates in the encroached woodland watersheds, but slight differences were observed in the tallgrass prairie watersheds when using the WEPP-estimated rangeland erodibility parameters and the erodibility parameters suggested by RHEM. Note that the differences in predicted sediment yield were functions of the small range in applied shear stress predicted by the model. This study highlighted the use of in situ testing for determining field site erodibility to better incorporate the impacts of land cover on hillslope sediment detachment in hydrologic modeling. [ABSTRACT FROM AUTHOR]

The Universal Soil Loss Equation (USLE) soil erodibility (K) factors for different soils have often been estimated using a soil erodibility nomograph. The USDA-NRCS requested assistance in evaluating nomograph estimates of K for two soils that exhibit very different erodibilities based on field observations and expert opinion. In this study, we used a combination of laboratory measurements and process-based WEPP model simulations to estimate USLE K factors for four soils: a Miami silt loam from Indiana, an Opal clay from South Dakota, a Vergennes silty clay loam from Vermont, and a Mexico silty clay loam from Missouri. Experiments to estimate WEPP erosion parameters included: (1) simulated rainfall experiments to estimate WEPP model interrill erodibility (Ki) and (2) V-shaped mini-flume experiments to estimate WEPP model rill erodibility (Kr) and critical shear stress (τcr). These estimates were made under three soil moisture conditions: initially dry, pre-wetted and then drained, and pre-wetted and saturated. Results showed that for the reference Indiana and Missouri soils, the back-calculated USLE K values from the dry and saturated soils were not significantly different from either the nomograph or RUSLE2 database values. For the South Dakota and Vermont NRCS test soils, the nomograph K was significantly lower than the experimentally derived K for initially dry and saturated soils and was also below the RUSLE2 database value. Saturated/drained soil moisture conditions resulted in the lowest back-calculated USLE K values for all soils. The process-based WEPP model with laboratory measurements of Ki, Kr, and τcr allowed computation of USLE K and provided more conservative estimates of K for the South Dakota clay and Vermont silty clay loam soils. More science-based K values have soil conservation policy implications in that the RUSLE2 database may provide better estimates for K values than use of the nomograph for some soils. [ABSTRACT FROM AUTHOR]

A new modeling platform was developed to simulate spatially distributed sediment production and transport in agricultural landscapes. The sediment production at the grid scale was computed using the stand-alone Water Erosion Prediction Project-Hillslope Erosion code, while an advection-dispersion equation represented sediment transport. The model's performance was tested in the Water Resources and Erosion watersheds at the Oklahoma and Central Plains Agricultural Research Center, El Reno, OK, USA. Results showed that this modeling approach could capture the complex behavior of sediment under different management practices in the watersheds. The modeling framework provides mechanistic processes to simulate the fate and transport of sediment across the watershed at spatio-temporal scales that are useful in assessing the environmental impacts of management schemes. Therefore, this study is expected to help advance the current approaches to estimating soil erosion by bridging scale differences to capture the large-scale effects of small-scale soil erosion processes. • A new modeling framework was developed for estimating soil erosion. • Sediment production is evaluated in fully distributed settings. • Different sizes of sediment are considered in simulations. • The model provides mechanistic processes in simulating sediment transport. • The model is able to capture changes in land and management practices. [ABSTRACT FROM AUTHOR]

Summary Forest managers need methods to evaluate the impacts of management at the watershed scale. The Water Erosion Prediction Project (WEPP) has the ability to model disturbed forested hillslopes, but has difficulty addressing some of the critical processes that are important at a watershed scale, including baseflow and water yield. In order to apply WEPP to forested watersheds, we developed and assessed new approaches for simulating streamflow and sediment transport from large watersheds using WEPP. We created specific algorithms to spatially distribute soil, climate, and management input files for all the subwatersheds within the basin. The model enhancements were tested on five geologically and climatically diverse watersheds in the Lake Tahoe basin, USA. The model was run with minimal calibration to assess WEPP’s ability as a physically-based model to predict streamflow and sediment delivery. The performance of the model was examined against 17 years of observed snow water equivalent depth, streamflow, and sediment load data. Only region-wide baseflow recession parameters related to the geology of the basin were calibrated with observed streamflow data. Close agreement between simulated and observed snow water equivalent, streamflow, and the distribution of fine (<20 μm) and coarse (>20 μm) sediments was achieved at each of the major watersheds located in the high-precipitation regions of the basin. Sediment load was adequately simulated in the drier watersheds; however, annual streamflow was overestimated. With the exception of the drier eastern region, the model demonstrated no loss in accuracy when applied without calibration to multiple watersheds across Lake Tahoe basin demonstrating the utility of the model as a management tool in gauged and ungauged basins. [ABSTRACT FROM AUTHOR]

CLIGEN (CLImate GENerator) is a stochastic weather generator that produces daily estimates of precipitation and individual storm parameters, including time to peak, peak intensity and storm duration. These parameters are typically used as inputs for other models, such as the Water Erosion Prediction Project (WEPP) model. Although CLIGEN has been proven to be effective for predicting daily estimates, some discrepancies have been observed when generating storm parameters, such as the storm duration. Therefore, a study was conducted to evaluate and improve CLIGEN for storm generation. Individual rainfall events were identified from 1-h pluviograph records that were collected from 30 sites in Central Chile. In this study, 415 years of data were used; 18,012 storms were analyzed. In addition, rainfall erosivity was computed for all storms using the prescribed method to compare the energy provided by the measured and generated rainfall events. Using measured rainfall data, a procedure was developed to improve the CLIGEN estimates by calibrating the input parameter that controls the storm durations. This procedure in turn improved the rainfall intensities and erosivities. The model was tested before and after calibration with the measured rainfall data from the 30 sites in both the wet and dry seasons. Based on a monthly rainfall analysis, the results demonstrated that the number of storms and rainfall amounts, which are not affected by the calibration process, were accurately estimated with CLIGEN. However, before the calibration, especially in the wet season, the storm durations and maximum intensities were consistently overestimated and underestimated, respectively, at most of the sites and for most months. Therefore, the annual rainfall erosivities were underestimated with CLIGEN at 19 of the 30 sites. After performing the calibration, the R 2 value for the CLIGEN-generated storm durations increased from 0.41 to 0.65. The maximum intensities also exhibited an improvement; the R 2 value increased from 0.31 to 0.60. Consequently, annual rainfall erosivities were generated with an R 2 value of 0.89; these erosivities were accurately estimated at 29 of the 30 sites. Therefore, this calibration procedure proved to be an effective alternative for generating more reliable storm patterns. This paper explains the procedure in detail and analyzes the parameters related to the individual storm generation process. [ABSTRACT FROM AUTHOR]

[Display omitted] • Storm intensification was incorporated into the downscaling process of GCMs. • Amounts of runoff and soil loss from extreme storm events were assessed. • Crop rotation and no-till would effectively mitigate soil erosion under climate change. • Uncertainty of simulated runoff and soil loss was apportioned. Proper simulation of storm intensification is critical in projecting crop yield, surface runoff, and soil loss under climate change conditions. We developed a total of 100 climate scenarios coupled with storm intensification, which were based on 25 downscaled GCMs (General Circulation Model) projections under RCP4.5 and RCP8.5 (Representative Concentration Pathways) for two time periods of 2021–2050 and 2051–2080. The climate files were applied to a modified WEPP (Water Erosion Prediction Project) model to estimate crop yield, runoff, and soil loss under 29 combinations of cropping and tillage systems. The results showed that future extreme storm events in the study area would significantly increase during 2021–2080 (P < 0.01). However, average monthly precipitation in summer would decrease by 12.5% in June and 10.8% in July, along with an annual precipitation decline of 2.6%, leading to a decrease in crop yield in this rainfed agricultural region. The amount of runoff (soil loss) from extreme storms would account for 45.9 (64.3%) of the total annual runoff (soil loss) when averaged across two time periods and two RCPs. The average annual runoff depth (soil loss amount) from crop rotation or double cropping systems would be 27.6 (78.1%) less than the corresponding values in a continuous monoculture cropping system. No-till and crop rotations with alfalfa are the best agricultural management alternatives to mitigate soil erosion rates under future climate change. The analysis of variance (ANOVA) indicated that the uncertainty contributions of GCMs and cropping and tillage systems reached 45.5% and 30.4% in annual surface runoff prediction (P < 0.001), while cropping and tillage systems (71.7%, P < 0.001) was the major uncertainty source in annual soil loss simulations. This study improved the prediction of crop yield, runoff, and soil loss from various cropping and tillage systems under climate change conditions by integrating storm intensification from multiple GCM ensembles. [ABSTRACT FROM AUTHOR]

Highlights: [•] A new approach was developed to determine sediment transport capacity (Tc ). [•] The GUEST model showed better predictions of Tc than did the WEPP model. [•] Considering F =0.15, the performance of GUEST in predicting Tc was further improved. [ABSTRACT FROM AUTHOR]

Land degradation caused by soil erosion (SE) in forests converted into cropland under climate change, particularly with increased rainfall intensity, is of great concern to the agricultural sustainability of the tropical mountain ecosystem. We evaluated the response of six hilly micro-watersheds (HMW) under different Integrated Farming Systems (IFSs) to SE in multi-model climate change scenarios using the Water Erosion Prediction Project (WEPP) model. The IFSs were forestry (HMW 1), abandoned shifting cultivation (HMW 2), livestock with fodder crops (HMW 3), agroforestry (HMW 4), agri-horti-silvi-pastoral (HMW 5), and horticulture (HMW 6) established on a hilly slope (32.0–53.2%) of the eastern Himalayas (Meghalaya, India). The WEPP model was calibrated and validated with measured runoff and soil loss data of 24 years for each of the six IFSs. The projected annual SE (average) for all HMWs increased in all RCPs. The IFS based on shifting cultivation (HMW 2) was the most vulnerable, with the highest percentage increase in SE (46–235%) compared to the baseline years (1976–2005) under RCP 8.5. The cultivated IFSs (HMW 3 to HMW 6) had 47.8–57.0% less runoff and 39.2–74.6% less soil loss than HMW 2 under RCP 8.5. Of these, HMW 6 followed by HMW 4 and HMW 5 were the most effective at minimizing soil loss. Simulation results showed a reduction in soil loss through adaptive strategies such as mulching with broom grasses, stones, field beans, and the introduction of subsurface drainage. Adoption of IFS based on horticulture and agroforestry with bio-mulching on steep slopes is an effective measure to control soil erosion in the eastern Himalaya (India). • Studied soil erosion (SE) in Integrated Farming Systems (IFS) of Eastern Himalaya. • The WEPP model adequately predicted SE in hilly micro-watershed based IFSs. • Runoff and soil loss, increased in response to CMIP5 climate change projections. • SE increased in shifting cultivation and decreased in horticulture and agroforestry. • Proposed adaptation strategies for reducing SE and making IFS climate resilient. [ABSTRACT FROM AUTHOR]

• Pi-VAT is a post-processing, interactive visualization, and analysis tool. • Simple implementation to facilitate 'what-if' analysis using WEPP and SWAT outputs. • Suitable for assessing areas for targeted management. • Synthesize and visualize multiple watersheds and scenarios. • An approach to address the need for integrating extensive outputs from process-based models into decision support tools. Effective watershed management and protection of water resources from non-point source pollution require identification, prioritization, and targeting of pollutant source areas. Process-based hydrology and water quality models are powerful heuristic tools for land and water resources managers. However, because of their complexity, such models are often under-utilized as management prioritization and planning tools. In this paper, we present a prioritization, interactive visualization, and analysis tool (Pi-VAT) that is programmed to synthesize multi-scenario, multi-watershed outputs from process-based geospatial models. We demonstrate the utility of Pi-VAT to examine simulated hydrologic, sediment, and water quality response at the hillslope/hydrologic response unit (HRU) scale. We apply Pi-VAT to output from multiple watersheds and for multiple management scenarios and treatments from two geospatial models for watershed management: Water Erosion Prediction Project (WEPP) and Soil & Water Assessment Tool (SWAT). Pi-VAT was developed using the Shiny web application framework for the R programming language. In a matter of minutes, Pi-VAT can synthesize overwhelming amounts of output from process-based models into information useful for land and water resources managers. We illustrate the use of Pi-VAT to interactively identify, quantify, and visualize areas that are most susceptible to disturbance under different scenarios and provide a synthesis approach based on land use, soil type, and slope steepness. This approach guides land and water resources managers in prioritizing the areas of the watershed that provide the maximum reduction in pollutant loads while treating the least amount of area. Pi-VAT provides a flexible reactive platform for the development of decision support tools based on process-based models intended for watershed management and research applications. [ABSTRACT FROM AUTHOR]

To develop effective conservation practices to respond to future climatic challenges, the effects of various cropping and tillage systems on surface runoff and soil loss need to be evaluated under extensive geographical conditions. This study used a total of 100 climate scenarios generated from 25 downscaled General Circulation Model (GCM) projections under two Representative Concentration Pathways (RCP4.5 and 8.5) during 2021–2050 and 2051–2080. Those 100 future scenarios were combined with 29 cropping and tillage systems to simulate surface runoff, soil erosion, and crop production response to climate change using the Water Erosion Prediction Project (WEPP) model. The results showed that average annual precipitation in central Oklahoma was projected to significantly decrease by 4–6% (p < 0.05) during the two time periods for both RCP scenarios. Mean annual temperatures were projected to significantly increase (p < 0.01) by 1.74 ℃ for RCP4.5 and 1.99 ℃ for RCP8.5 during 2021–2050, and 2.65 ℃ for RCP4.5 and 3.90 ℃ for RCP8.5 during 2051–2080. Annual runoff and soil loss averaged over the two RCPs and all crop types was projected to decrease by approximately 1% and 3%, respectively. Except for cotton, crop yields were predicted to decrease by 10.3%–18.3% during 2021–2080. Simulated annual runoff depth and soil loss separately followed the order of reduced tillage (RT) > delayed tillage (DT) > no-till (NT) > conventional tillage (CT) and RT > CT > DT > NT under future climate scenarios, respectively. If economically feasible, no-till and the crop-alfalfa rotation were the most effective soil conservation method on farmlands to combat projected future erosion due to changing precipitation and temperatures. • 29 cropping and tillage systems were used to simulate climatic effects on runoff and soil erosion. • 25 GCMs were applied to improve confidence in WEPP simulations with projected climate changes. • No-till was the most effective conservation tillage practice to keep soil loss at a low level. • Crop-alfalfa and wheat-soybean rotations were effective in controlling soil erosion. [ABSTRACT FROM AUTHOR]

The rate of soil erosion from agricultural fields is driven by climate erosivity and by soil erodibility or resistance, commonly represented through the interrill (K i) and rill erodibility (K r), and critical shear stress (τ c) parameters. These parameters are affected by factors showing high variability in time and space, such as soil properties, land use, and management practices. Estimating the site-specific time-varying values for K i , K r , and τ c can require laborious field or laboratory experiments and detailed datasets. The objective of this research was to develop a non-linear regression model for estimating temporal adjustments for K i , K r , and τ c considering different types of crops and management practices. One thousand sampling sites were randomly selected across the Kaskaskia watershed in Illinois, and the needed parameters to develop the regression models were extracted from the two-year simulation results of the Water Erosion Prediction Project (WEPP) model on a daily basis. The predicted values of the regression models showed good agreements with the sample data, with the coefficient of determination (r 2) ranging from 0.62 to 0.98, capturing the spatio-temporal variations of the three variables under different crops and management practices. In addition, daily soil loss estimations using the predicted adjustments showed good agreements with the WEPP simulations, with r 2 ranged from 0.98 to 0.99, confirming their possible use in soil erosion models. This is especially useful as the regression models require only a few explanatory variables, which are available at high resolution across the United States. Therefore, the models will facilitate estimating spatio-temporal variations of interrill and rill erodibility, and critical shear stress and thus a new platform of large-scale soil erosion models can be developed using readily available environmental datasets. • Derived non-linear regression models for erodibility and critical shear stress. • The equations can capture the spatio-temporal variations in topsoil's resistance. • Explanatory variables are readily available at fine resolution. • The regression models can be applied to different crops and tillage practices. • The presented work can facilitate the estimations of soil erosion at larger scales. [ABSTRACT FROM AUTHOR]

Abstract: Modeling soil erosion contributes to the understanding of the erosion processes and needs to predict accurately the erosion rates under different environmental conditions. Few studies have investigated the WEPP's applicability for arid and semi-arid conditions that differ from those where the model was developed. This research was carried out to evaluate and improve the WEPP model for arid and semiarid regions for interrill erosion using a rainfall simulator at plot scale. The results showed that measured interrill erosion rates ranged from 9.3×10−6 to 89.6×10−6 kgm−2 s−1. In comparison, the WEPP-interrill erosion prediction values were on average 14.5 times lower than the measured ones, which can be ascribed to a systematic error. To calibrate the model, two regression equations were presented to estimate baseline interrill erodibility (Kib) and adjusted interrill erodibility (Kiadj). Accordingly, the baseline interrill erodibility was influenced by surface rock cover much more than any other soil property. Also, Kiadj was functioned as sediment concentration and sand percent. Model validation showed that after calibrating Kib and Kiadj, the coefficient of efficiency enhanced to 0.31 and 0.90, respectively. However, the model tended to overestimate the lower erosion rates and to underestimate the higher erosion rates. To modify interrill erodibility and to achieve a process-based parameter, a simple equation was developed based on stream power. The coefficient of efficiency of 0.61 was obtained for the proposed approach. In general, the model predictions enhanced after calibration, but the model tendency to underestimate high erosion rates was observed. One of the reasons for low accuracy of the WEPP was its dependence on soil empirical parameters used in predicting the sub-model components. The model prediction was found to be improved through process-based calibration of soil parameters. [Copyright &y& Elsevier]

Vertic soils are common in Mediterranean areas, such as in some olive-growing areas in Andalusia in southern Spain. Model calibration can be especially complex in orchards due to the higher spatial variability induced by the tree/lane distribution and the impact of management, and even more in Vertic soils because of the complexity introduced by the cracking/swelling cycles of the soil whose impact can remain for many months. The WEPP model was evaluated using monthly runoff and erosion data collected from an experiment in an olive orchard on a Vertic soil during four hydrological years, comparing three different soil management systems: no tillage with bare soil (NT), conventional tillage (CT), and cover crop (CC). These three systems differed greatly in average annual runoff and soil losses. Satisfactory calibration of the model required characterization of the main hydrological features of the study period (distinguishing "dry" and "wet" years) due to their large impact on the infiltration properties of the soil. The best predictions were obtained for the wet years and NT management. High values of r² and Nash-Sutcliffe model efficiency OVSE) were obtained at a monthly scale under wet conditions. Annual erosion rates were not well predicted, probably due to the difficulties in simulating the spatial complexity of olive orchards and the limitations of WEPP for modeling soil moisture dynamics at different depths derived from the cracking/swelling processes of Vertic soils as well as their impact on erodibility. The presented parameterization constitutes a basic guideline for the application of the WEPP model in olive-growing areas and on Vertic soils. [ABSTRACT FROM AUTHOR]

Tile drainage influences infiltration and surface runoff and is thus an important factor in the erosion process. Tile drainage reduces surface runoff, but questions abound on its influence on sediment transport through its dense network and into the stream network. The impact of subsurface tiling on upland erosion rates in the Le Sueur River watershed, USA, was assessed using the Water Erosion Prediction Project (WEPP) model. Six different scenarios of tile drainage with varying drainage coefficient and management type (no till and autumn mulch-till) were evaluated. The mean annual surface runoff depth, soil loss rate and sediment delivery ratio (SDR) for croplands, based on a 30-year simulation for the watershed with untiled autumn mulch-till (Scenario 1), were estimated to be 83.5 mm, 0.27 kg/m2and 86.7%, respectively; on no-till management systems (Scenario 4), the respective results were 72.3 mm, 0.06 kg/m2and 88.2%. Tile drains reduced surface runoff, soil loss and SDR estimates for Scenario 1 by, on average, 14.5, 8.1 and 7.9%, respectively; and for Scenario 4 by an estimated 31.5, 22.1 and 20.2%, respectively. The impact of tile drains on surface runoff, soil loss and SDR was greater under the no-till management system than under the autumn mulch-till management system. Comparison of WEPP outputs with those of the Soil Water Assessment Tool (SWAT) showed differences between the two methods. EditorZ.W. Kundzewicz CitationMaalim, F.K. and Melesse. A.M., 2013. Modelling impacts of subsurface drainage on surface runoff and sediment yield in the Le Sueur Watershed in Minnesota, USA.Hydrological Sciences Journal, 58 (3), 570–586. [ABSTRACT FROM PUBLISHER]

In cold regions, frozen soil has a significant influence on runoff and water erosion. In the U.S. Inland Pacific Northwest, major erosion events typically occur during winter as frozen soil thaws and exhibits low cohesion. Previous applications of the WEPP (Water Erosion Prediction Project) model to a continuous bare tilled fallow (CBF) runoff plot at the Palouse Conservation Field Station (PCFS) in southeastern Washington State showed that WEPP reproduced the occurrence of the large erosion events, but the amount of sediment yield was either under- or overestimated. The inability of WEPP to reproduce the magnitude of field-observed erosion events at the PCFS suggests the need for an examination of the dynamic changes in soil erosion properties and for improving the representation of such dynamics. The objective of this study was to evaluate the seasonal changes of rill erosion parameters for two CBF runoff plots at the PCFS. Field-observed runoff and erosion events during 1984-1990 were used to estimate WEPP hydraulic and erosion parameters, including soil effective hydraulic conductivity, critical shear stress (τc), and rill erodibility (Kr). The parameters for each event were best-fitted using WEPP single-event simulations to reproduce the observed runoff and sediment yield on both plots. The results suggest that the adjustment factors for τc and Kr of frozen and thawing soils in the WEPP model could be modified to better describe the changes of these parameters in winter. [ABSTRACT FROM AUTHOR]

The assessment of water yield from hillslopes into streams is critical in managing water supply and aquatic habitat. Streamflow is typically composed of surface runoff, subsurface lateral flow, and groundwater baseflow; baseflow sustains the stream during the dry season. The Water Erosion Prediction Project (WEPP) model simulates surface runoff, subsurface lateral flow, soil water, and deep percolation. However, to adequately simulate hydrologic conditions with significant quantities of groundwater flow into streams, a baseflow component for WEPP is needed. The objectives of this study were (1) to simulate streamflow in the Priest River Experimental Forest in the U.S. Pacific Northwest using the WEPP model and a baseflow routine, and (2) to compare the performance of the WEPP model with and without including the baseflow using observed streamflow data. The baseflow was determined using a linear reservoir model. The WEPP-simulated and observed stream/lows were in reasonable agreement when baseflow was considered, with an overall Nash-Sutcliffe efficiency (NSE) of 0.67 and deviation of runoff volume (Dv) of 7%. In contrast, the WEPP simulations without including baseflow resulted in an overall NSE of 0.57 and Dv of 47%. On average, the simulated baseflow accounted for 43% of the streamflow and 12%, of precipitation annually. Integration of WEPP with a baseflow routine improved the model's applicability to watersheds where groundwater contributes to streamflow. [ABSTRACT FROM AUTHOR]

At the hillslope profile and/or field scale, a simple Windows graphical user interface (GUI) is available to easily specify the slope, soil, and management inputs for application of the USDA Water Erosion Prediction Project (WEPP) model. Likewise, basic small watershed configurations of a few hillslopes and channels can be created and simulated with this GUI. However, as the catchment size increases, the complexity of developing and organizing all WEPP model inputs greatly increases due to the multitude of potential variations in topography, soils, and land management practices. For these types of situations, numerical approaches and special user interfaces have been developed to allow for easier WEPP model setup, utilizing either publicly available or user-specific geospatial information, e.g., digital elevation models (DEMs), geographic information system (GIS) soil data layers, and GIS land use/land cover data layers. We utilize the Topographic Parameterization (TOPAZ) digital landscape analysis tool for channel, watershed, and sub-catchment delineation and to derive slope inputs for each of the subcatchment hillslope profiles and channels. A user has the option of specifying a single soil and land management for each subcatchment or utilizing the information in soils and land use/land cover GIS data layers to automatically assign those values for each grid cell. Once WEPP model runs are completed, the output data are analyzed, results interpreted, and maps of spatial soil loss and sediment yields are generated and visualized in a GIS. These procedures have been used within a number of GIS platforms including GeoWEPP, an ArcView/ArcGIS extension that was the first geospatial interface to be developed in 2001. GeoWEPP allows experienced GIS users the ability to import and utilize their own detailed DEM, soil, and/or land use/land cover information or to access publicly available spatial datasets. A web-based GIS system that used MapServer web GIS software for handling and displaying the spatial data and model results was initially released in 2004. Most recently, Google Maps and OpenLayers technologies have been integrated into the web WEPP GIS software to provide significant enhancements. This article discusses in detail the logic and procedures for developing the WEPP model inputs, the various WEPP GIS interfaces, and provides example real-world geospatial WEPP applications. Further work is ongoing in order to expand these tools to allow users to customize their own inputs via the internet and to link the desktop GeoWEPP with the web-based GIS system. [ABSTRACT FROM AUTHOR]

Abstract: Mara River basin is an internationally acclaimed and ecologically significant basin in the Lake Victoria basin. The recent trend in major land use change in the upstream (forest-to-agriculture conversion) has been the major driver for the current hydrologic alterations. Recent hydrologic data and observations show a reduction in dry season flow, increase in peak flows during wet seasons and an increase in sediment load. This has led to the need for more observation and modeling to understand the impacts of the various land use changes on the sediment and runoff characteristics of the watershed. Two physically based models (Erosion 3D and Water Erosion Prediction Project (WEPP)) were applied to predict the watershed scale sediment and runoff response. Watershed scale modeling results show that sediment yield and runoff vary by slope, land use and soil type. The spatial sediment budget also shows the variability in the erosion and deposition of sediment in the basin. Average simulated erosion in cultivated land was about 120t/ha/yr and the lowest simulated erosion rate was on bush lands and grasslands, which may indicate change in land use has significant impact on soil erosion in the Mara River basin. It was shown that both WEPP and EROSION 3D models are useful tools for watershed scale application and estimation of runoff and sediment yield. [Copyright &y& Elsevier]

The Water Erosion Prediction Project (WEPP) model is a process-based, continuous simulation, distributed parameter, hydrologic and soil erosion prediction system. It has been developed over the past 25 years to allow for easy application to a large number of land management scenarios. Most general or field agency users of WEPP rely upon existing or special databases and/or interfaces that have been developed, tested, and verified by others. This article describes WEPP model calibration and validation procedures, under ideal situations (where all necessary input data and runoff/sediment observations are available) as well as under more typical and less ideal conditions. Two case study applications of the model from the literature are highlighted and discussed in detail as examples of single storm hillslope profile and continuous simulation watershed applications. Current and future development efforts on WEPP are also described. [ABSTRACT FROM AUTHOR]

Abstract: The need for more agricultural areas stemming from population pressure has been contributing to the increased forest and grassland-to-agricultural areas conversion in recent years in the upper Mara River Basin, Kenya. The deforestation of the Mau forest and settlement on hydrological sensitive areas of the watershed along with poor soil and water conservation practices have caused the high level of soil erosion and water quality deterioration. The various efforts to curve down this problem necessitate the knowledge of the rate of erosion, surface runoff as a function of the physical and hydrometeorological characteristics of the watershed. In support of this effort, a study was conducted to evaluate the effects of three land-use/land cover practices on runoff and sediment yield using runoff plots and two models: Water Erosion Prediction Project (WEPP) and Erosion 3D. In order to accomplish these objectives, runoff plots were established at three sites: Amala upstream; Amala downstream and Nyangores watersheds. In all of the three watersheds, three land uses (cropland, grassland and bare land) with similar slope steepness and soil types were considered. Using the data collected from the runoff plots, the WEPP and Erosion 3D models were evaluated. The plot scale research results indicated that erosion was high in all of the sites on cultivated lands. The highest total sediment yield over the study period was observed on cultivated land (162.38g/m2) in the Nyangores watershed; and the lowest sediment yield (29.95g/m2) was observed on grassland at Amala downstream site. The model evaluation indicated that both of the models perform well in estimation of runoff, however, the WEPP model performs better than Erosion 3D in estimation of soil erosion. [Copyright &y& Elsevier]

Forested areas disturbed by access roads produce large amounts of sediment. One method to predict erosion and, hence, manage forest roads is the use of physically based soil erosion models. A perceived advantage of a physically based model is that it can be parameterized at one location and applied at another location with similar soil texture or geological parent material. To test this perception, a two-part study was conducted to compare soil erosion model predictions using parent material/soil texture-based parameters to predictions using site-specific parameters. The first step was to determine site-specific erosion parameters using rainfall simulation. The second step was to compare erosion model results for a typical road network using the two parameter sets. Lake Tahoe was chosen for the study because it had parent materials similar to sites where parameterization had been performed. The coefficient of variation in runoff and sediment mass from the Lake Tahoe rainfall simulations varied from 8% to 36%. These values, although smaller than those reported from natural rainfall studies, are an indication of the inherent variability of erosion measurements. Effective hydraulic conductivity determined by rainfall simulation for a granitic parent material at Lake Tahoe was greater than that for the similar parent material. A volcanic parent material from Lake Tahoe also had higher effective hydraulic conductivity than that for another volcanic parent material. Soil interrill erodibility values for granitic parent material were similar, while values for volcanic parent material were slightly greater for the Lake Tahoe soil. Only the effective hydraulic conductivity of the granitic parent material was statistically different at the 95% confidence level from the parent material/soil texture-based values. Process-based WEPP model predictions of runoff from a typical Lake Tahoe road network were 82% and 73% less for granitic and volcanic soils, respectively, when using the site-specific Lake Tahoe values compared to similar parent material values. Corresponding differences between sediment yields were 85% and 78% less. Most of the decrease was due to fewer snowmelt runoff events. The inherent variability in soil erosion measurements results in a corresponding variability in erosion model parameters derived from those measurements. As a result, model predictions have an inherent accuracy range. In this Lake Tahoe study, the erosion measurement variability resulted in a WEPP model prediction range of approximately ±75% of the mean for both runoff and sediment mass. [ABSTRACT FROM AUTHOR]

The ability to predict snow accumulation and melt in complex vegetated terrain is critical for effective water supply, water quality, and forest land management. Accurate numerical simulation of these processes is important for erosion and sedimentation modeling in the mountainous western U.S., where snow processes dominate the winter phase of the hydrologic cycle. This work assessed approaches to adjust meteorological data and canopy parameterizations to improve Water Erosion Prediction Project (WEPP) snowmelt model predictions and to identify areas in which to focus future model development efforts. Four data modification approaches were used that represented a range of operator cost and effort. Approaches included direct application of: (1) nearby climate data, (2) empirically derived precipitation adjustment factors based on snowpack measurements, (3) custom climate data collected at the site of interest, and (4) adjusted canopy cover factors. Site-specific climate and calibrated canopy parameters produced the best simulation of snowcover duration and melt rate but underestimated peak snow water equivalent (SWE) by approximately 1%, 34%, and 40% in clearcut, partially cut, and fully forested sites, respectively. The best simulation produced time to snowpack depletion from peak SWE of 11, 15, and 4.5 days earlier than observed in clearcut, partial cut, and full forest, respectively. Results illustrate the difficulties of simulating snowpack dynamics with WEPP in forested mountainous systems of the interior Pacific Northwest where air temperatures are close to 0°C during snow deposition. Although improvements in simulation accuracy are needed in forests, the proposed methods can improve confidence in WEPP snowpack simulations or be applied to other models to improve predictions in complex snow-dominated systems. [ABSTRACT FROM AUTHOR]

Abstract: Rainfall events on steep hillslopes can cause both soil erosion and shallow landslides. These processes interact with each other and need to be studied in an integrated way to understand hillslope sediment yields. The main aim of this research is to study post-failure sediment yield following landslides that alter local slope gradients. A laboratory flume under a rainfall simulator was used to quantify erosion and shallow landslides in fine-grained silty loess soils. The flume was divided into an upper and a lower section; the slopes of which could be altered. A total of 12 experiments were conducted on slopes ranging from 35° to 47° in the upper and 5° to 10° in the lower flume sections. Shallow landslides were triggered in four of the 12 experiments. Sediment and runoff were collected from the flume outlet every minute during landslides and every 10 min before and after landslides. Changes in the soil slope after landslides occurred were recorded. Results showed that peak sediment yields were related to landslide occurrence and proximity to the outlet. Post-failure reduction in sediment yields was related to the evolution of the hillslope after slope failures. A simple rule-based soil redistribution model of runout distance was validated using the experimental results. The Water Erosion Prediction Project (WEPP) model was used to simulate runoff and soil erosion during pre- and post-failure rainfall events. Predicted runoff rates and sediment yields using WEPP were in good agreement with those measured in both pre- and post-failure events, indicating that the model can be used successfully as part of an integrated approach to modeling sediment yields in landslide-prone landscapes. [Copyright &y& Elsevier]

Soil loss rates on rangelands are considered one of the few quantitative indicators for assessing rangeland health and conservation practice effectiveness. An erosion model to predict soil loss specific for rangeland applications is needed because existing erosion models were developed from croplands where the hydrologic and erosion processes are different, largely due to much higher levels of heterogeneity in soil and plant properties at the plot scale and the consolidated nature of the soils. The Rangeland Hydrology and Erosion Model (RHEM) was designed to fill that need. RHEM is an event-based derivation of the WEPP model made by removing relationships developed specifically for croplands and incorporating new equations derived from rangeland data. RHEM represents erosion processes under disturbed and undisturbed rangeland conditions, it adopts a new splash erosion and thin sheet-flow transport equation developed from rangeland data, and it links the model hydrologic and erosion parameters with rangeland plant communities by providing a new system of parameter estimation equations based on 204 plots at 49 rangeland sites distributed across 15 western U.S. states. RHEM estimates runoff, erosion, and sediment delivery rates and volumes at the spatial scale of the hillslope and the temporal scale of a single rainfall event. Experiments were conducted to generate independent data for model evaluation, and the coefficients of determination (r²) for runoff and erosion predictions were 0.87 and 0.50, respectively, which indicates the ability of RHEM to provide reasonable runoff and soil loss prediction capabilities for rangeland management and research needs. [ABSTRACT FROM AUTHOR]

Severe soil erosion has generally been regarded as a major cause of land degradation in arid and semi arid regions. A quantitative assessment of soil loss intensity is still scanty for developing appropriate soil erosion control measures in these regions. This article used the combined Water Erosion Prediction Project (WEPP) and Geographic Information System (GIS) models to estimate the average soil loss in the Halahijan watershed in Khuzestan Province, one of the priority areas for soil erosion control in Iran. Also, the sediment yield estimated by the WEPP was compared with that estimated by Modified Pacific Southwest Interagency Committee (MPSIAC) model. The MPSIAC model is used to estimate erosion yield and erosion intensity using nine factors consisting of, geological characteristics, soil, climate, runoff, topography, vegetation cover, land use and present soil erosion. Results indicated that the soil loss estimated by the WEPP model ranged from 15.10 to 28.20 Mg ha-1 yr-1 with an average soil loss of 21.8 Mg ha-1 yr-1 in the study area. The soil loss estimated by WEPP model was highly correlated with data estimated by MPSIAC (R² = 0.97). The soil erosion in this region can be attributed to rainfall intensity (which ranged from 16 to 88 mm hr-1), and high surface runoff (which ranged from 48562 to 80963 m³). Results also revealed that the WEPP model is suitable for estimating soil loss in complex watersheds. [ABSTRACT FROM AUTHOR]

Erosion models play an important role in assessing the influence of human activities on the environment. For cold areas, adequate frost simulation is crucial for predicting surface runoff and water erosion. The Water Erosion Prediction Project (WEPP) model is a physically based erosion prediction software program developed by the USDA. One of the major components of WEPP is the simulation of winter processes, which include snow accumulation and melt as well as soil freeze and thaw. WEPP is successfully used in the evaluation of important natural resource issues throughout the U.S. and in a number of other countries. However, previous studies revealed problems in the winter component of the WEPP model, especially the routine for frost simulation. The main purpose of this study was to improve the WEPP model (v2006.5) by changing the soil profile discretization and computation of key thermal and hydraulic parameters in the frost simulation routines so that the model can adequately simulate soil freeze-thaw and winter runoff and erosion. WEPP v2006.5 and the modified version (v2010.1) were applied to experimental plots in Pullman, Washington, and Morris, Minnesota. The simulated snow and frost depths as well as runoff and sediment yield were contrasted and compared with field observations, the results from v2010.1 showed substantial improvement compared to those from v2006.5. [ABSTRACT FROM AUTHOR]

Abstract: Experimental plots were constructed in the Zhangjiachong Watershed of the Three Gorges Reservoir Area to evaluate soil erosion of traditional slope land farming and effects of soil conservation measures. Surface runoff and sediment from the watershed and each plot were collected and measured during 2004–2007. Field investigations indicated that hedgerows were the best for soil erosion control, followed by stone dike terraces and soil dike terraces. The Water Erosion Prediction Project (WEPP) model was used to simulate erosion of annual and rainfall events both at the watershed and plot levels. The low deviation, high coefficient of determination and model efficiency values for the simulations indicated that the WEPP model was a suitable model. The soil erosion rate distribution was modeled to determine where serious erosion would occur during rainfall events in the Zhangjiachong Watershed and so control measures can be taken. [Copyright &y& Elsevier]

Highly weathered Southeastern soils traditionally cropped under conventional tillage systems are drought-prone and susceptible to runoff and soil loss. We quantified differences in infiltration, runoff, soil loss, and interill erodibilities (Ki) for three soils: Compass loamy sand, Decatur silt loam, and Tifton loamy sand managed under conventional- (CT), strip- (ST), and/or no-till (NT) systems with and without a residue cover (rye [Secale cerale L.]) (+C/-C) and with and without paratilling (+P/-P). Duplicate plots (¹ m² [∼10 ft²]) on each tillage treatment received simulated rainfall (50 mm h-1 [2 in hr-1] for two hours). Runoff and sediment yields were continuously measured, and K. values were calculated from measured data. The Water Erosion Prediction Project (WEPP) model was used to extend experimental data to long-term annual trends. For the Compass soil, NT-C plots increased runoff by as much as 43% and sediment yields by as much as 10-fold compared to NT+C plots. The NT+P+C plots decreased runoff by as much as 70% and sediment yields by 24-fold compared to CT-P-C. For the Decatur soil, NT+P plots decreased runoff by as much as 71% and sediment yields by as much as 2.7-fold compared to NT-P plots. The NT+P+C plots decreased runoff by as much as 73°,6 and sediment yields by as thuch as 11.8-fold com- pared to CT-P-C. For the Tifton soil, ST+P+C plots decreased runoff by as much as 44% and sediment yields by as much as 2.7-fold compared to CT-P-C plots. Calculated K values for the Compass, Decatur, and Tifton soils were 0.37, 0.40, and 0.24, respectively. Residue cover decreased effective internill erodibilities (Kieff) values by 11%, 2-fold, and 2.6-fold for the Decatur,Tifton, and Compass soils, respectively; Paratilling decreased Kieff values by 3-fold for the Compass and Decatur soils. The NT and/or ST systems had lower Kieff values than Ki values from corresponding CT-P-C treatments (Compass = 4- to 37-fold; Decatur = 4- to 13-fold;Tifton = 2-fold). Converting from a CT to a NT or ST System reduced predicted runoff (Compass = 1.7-fold;Decatur = 10% to 17%;Tifton = 1.6- to 2.3-fold) and sediment yields (Compass = 10- to 12-fold; Decatur = 6- to 33-fold;Tifton = 7.3- to.12.1-fold).The most benefit of NT or ST, as quantified by the maximum difference in 100-year predicted runoff and sediment yields, was for the Compass (78%) and Tifton (75%) soils for runoff and for the Compass (10.3-fold) and Decatur soils (9.7-fold) for sediment. Conservation tillage systems (NT, ST) coupled with surface residue cover and/or paratilling are effective in reduc- ing runoff and sediment yields from highly-weathered soils by lowering effective Ki values. [ABSTRACT FROM AUTHOR]

Summary: There has been an increasing public concern over forest stream pollution by excessive sedimentation due to natural or human disturbances. Adequate erosion simulation tools are needed for sound management of forest resources. The Water Erosion Prediction Project (WEPP) watershed model has proved useful in forest applications where Hortonian flow is the major form of runoff, such as modeling erosion from roads, harvested units, and burned areas by wildfire or prescribed fire. Nevertheless, when used for modeling water flow and sediment discharge from natural forest watersheds where subsurface flow is dominant, WEPP (v2004.7) underestimates these quantities, in particular, the water flow at the watershed outlet. The main goal of this study was to improve the WEPP v2004.7 so that it can be applied to adequately simulate forest watershed hydrology and erosion. The specific objectives were to modify WEPP v2004.7 algorithms and subroutines that improperly represent forest subsurface hydrologic processes; and, to assess the performance of the modified model by applying it to a research forest watershed in the Pacific Northwest, USA. Changes were made in WEPP v2004.7 to better model percolation of soil water and subsurface lateral flow. The modified model, WEPP v2008.9, was applied to the Hermada watershed located in the Boise National Forest, in southern Idaho, USA. The results from v2008.9 and v2004.7 as well as the field observations were compared. For the period of 1995–2000, average annual precipitation for the study area was 954mm. Simulated annual watershed discharge was negligible using WEPP v2004.7, and was 262mm using WEPP v2008.9, agreeable with field-observed 275mm. [Copyright &y& Elsevier]

The quality of spatially and temporally distributed weather information is critical in soil erosion model results because of the primary influence of rainfall on runoff and soil movement. Detailed climate data for the Water Erosion Prediction Project (WEPP) model can be generated by a climate generator (CLIGEN) based on long-term statistical parameters for more than 4,000 locations in the United States. The objectives of this study were to apply CLIGEN and WEPP and examine the effects of changing storm frequency, storm depth, or a combination of the two on predicted rainfall, runoff, and soil loss. Two different sites, Chun-Cheon and Jeon-Ju, were studied and compared for the period 1966 to 2005. Chun-Cheon is located at a higher altitude and is surrounded with forest, while Jeon-Ju is located in the plains. CLIGEN was used to generate 100-year climate sequences with daily climate data e.g., temperature, precipitation, wind, and solar radiation for a representative climate station in the study sites to predict runoff and soil loss with WEPP. Three precipitation change scenarios were examined in this study: (1) adjusting the number of days with rainfall, (2) adjusting the mean amount of rainfall on a wet day, and (3) a combination of 1 and 2. Observed mean annual precipitation at Chun-Cheon (1,305 mm [50.9 in]) was similar to Jeon-Ju (1,291 mm [50.4 ml). CLIGEN simulated mean annual precipitation depths in Chun-Cheon and Jeon-Ju were very close to the observed data. The WEPP model predicted runoff in Jeon- Ju was 48.8% higher than that in Chun-Cheon and estimated soil loss in Chun-Cheon was 55.6% higher than that in Jeon-Ju. Precipitation change scenario 3 that combined changes in precipitation occurrence with changes in rainfall storm depths showed the largest impacts on predicted runoff and soil loss. A combined 20% increase in these precipitation parameters resulted in increases of 44%, 54%, and 52% in generated average annual precipitation, predicted runoff and predicted soil loss, respectively, at Chun-Cheon, while increases at Jeon-Ju were 44%, 60%, and 27%. Increases in rainfall due to future climate change may thus potentially result in substantial and nonlinear increases in runoff and soil loss in Korea. [ABSTRACT FROM AUTHOR]

The recent modification of the Water Erosion Prediction Project (WEPP) model has improved its applicability to hydrology and erosion modeling in forest watersheds. To generate reliable topographic and hydrologic inputs for the WEPP model, carefully selecting digital elevation models (DEMs) with appropriate resolution and accuracy is essential because topography is a major factor controlling water erosion. Light detection and ranging (LIDAR) provides an alternative technology to photogrammetry for generating fine-resolution and high-quality DEMs. In this study, WEPP (v2006.201) was applied to hydrological and erosion simulation for two small forest watersheds in northern Idaho. Data on stream flow and total suspended solids (TSS) in these watersheds were collected and processed. A total of six DEMs from the National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and LIDAR at three resolutions (30 m, 10 m, and 4 m) were obtained and used to calculate topographic parameters as inputs to the WEPP model WEPP-simulated hydrologic and erosion results using the six DEMs were contrasted and then compared with field observations. For the study watersheds, DEMs with different resolutions and sources generated varied topographic and hydrologic attributes, which in turn led to significantly different erosion simulations. WEPP v2006.201 using the 10 m LIDAR DEM (vs. using other DEMs) produced a total amount of as well as seasonal patterns of watershed discharge and sediment yield that were closest to field observations. [ABSTRACT FROM AUTHOR]

[Display omitted] • A theoretical framework was used to explain dynamic scale effect on soil erosion. • Scale effect on soil erosion varies with erosion types, rainfall, and soil properties. • Slope length factor of USLE/RUSLE performs better on rill erosion dominant slopes. The variation of soil erosion across scales remains a controversial issue. A theoretical framework, coupling the normalized Green-Ampt equation for infiltration, 1D kinematic wave model for overland flow, and WEPP erosion modeling approaches for soil erosion, was used to explain and quantify the direct effect of scale on the soil erosion process. The results show that the relation between interrill erosion and slope length accords with a power-law decreasing trend, while the relation of rill erosion versus slope length shows a power-law increasing trend. Moreover, the power-law scaling of interrill erosion becomes more prominent with an increase of rainfall duration and intensity but is nearly independent of the interrill erodibility factor. The rainfall duration, soil type, soil critical shear stress, sediment transport coefficient, and rill erodibility factor substantially influence the magnitude of scale effect on rill erosion, while rainfall intensity, slope gradient, and Manning's roughness have minor effects. It suggests that the scale effect on soil erosion is variable and dynamic for different erosion types, rainfall and soil characteristics, which can explain why the controversial scaling relationships of soil erosion exist in previous studies. The physically based soil erosion model WEPP is compared to the empirical models USLE and RUSLE at various scales. Only when rill erosion plays a dominant role in soil loss do all these models exhibit consistent scale effect on erosion. These results provide insights into the essence of scaling in the hillslope soil erosion process, which are expected to benefit the development of upscaling techniques for the large-scale hydrological, geomorphological, and ecological processes. [ABSTRACT FROM AUTHOR]

Natural gas exploration and production requires land-disturbing construction activities that have the potential to accelerate soil loss due to land cover modifications, increased slopes, and flow concentration. In the U.S., nearly 30,000 new gas wells are drilled each year. Erosion modeling has been successfully used for decades to predict soil loss and conservation effects on agricultural fields, rangelands, and forests, although much less research has been conducted on the application of erosion models for disturbed construction site conditions. The objective of this research was to evaluate Water Erosion Prediction Project (WEPP) runoff and sediment yield predictions relative to measured data from two natural gas well sites (referred to as GW1 and GW2) in north central Texas. Model parameters were adjusted from WEPP default parameters based on available literature and model observations. A low effective hydraulic conductivity value (0. 75 mm h-1) resulted in successful runoff predictions. Agreement between predicted and measured sediment yields was accomplished by increasing rill and interrill erodibility values and decreasing critical shear stress values from default values. WEPP performance was evaluated with the Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE)-observation standard deviation ratio (RSR), and percent bias (PBIAS), as well as modified versions of NSE and RSR that consider uncertainty in measured validation data. For GW1, NSE and RSR evaluation of WEPP performance was considered "good" for runoff (NSE = 0.68 and RSR = 0.56) and "satisfactory" for sediment yield (NSE = 0.63 and RSR = 0.61). For GW2, NSE and RSR values were "very good'for runoff (NSE = 0.76 and RSR = 0.49) but "unsatisfactory" for sediment yield (NSE = 0.32 and RSR = 0.83). Use of modified NSE and RSR to consider measurement uncertainty improved model performance to "very good" for all instances. PBIAS values were relatively low and considered "very good" for GW1 and GW2 runoff and sediment yield predictions. These results demonstrate that WEPP can effectively model runoff and sediment yields from natural gas well sites, thus making it a useful tool for evaluating potential sediment impacts and management alternatives to minimize sediment yields from natural gas well sites. [ABSTRACT FROM AUTHOR]

Digital elevation models (DEMs) vary in resolution and accuracy by the production method. DEMs with different resolutions and accuracies can generate varied topographic and hydrological features, which can in turn affect predictions by soil erosion models, such as the WEPP (Water Erosion Prediction Project) model. This study investigates the effects of DEMs on deriving topographic and hydrological attributes, and on predicting watershed erosion using WEPP v2006.5. Six DEMs at three resolutions from three sources were prepared for two small forested watersheds located in northern Idaho, USA. These DEMs were used to calculate topographic and hydrological parameters that served as inputs to WEPP. The model results of sediment yields and runoffs were compared with field observations. For both watersheds, DEMs with different resolutions and sources generated varied watershed shapes and structures, which in turn led to different extracted hill slope and channel lengths and gradients, and produced substantially different erosion predictions by WEPP. [ABSTRACT FROM AUTHOR]