Search

Soil erosion is a complex and highly heterogeneous process with a wide range of environmental and economic impacts. Its estimation is particularly challenging and modelling is typically used for erosion estimation over large areas. The aim of this study was to compare the two leading empirical and physical erosion estimation models, i.e. the Revised Universal Soil Loss Equation (RUSLE) and the Water Erosion Prediction Project (WEPP). The models were calibrated and validated using data collected from field experiments conducted in agricultural lands of Mexico. The simulated rainfall experiments involved measuring erosion from field plots subjected to four tillage systems (No crop, Conventional tillage, Conventional tillage + residues, and Handspike) under two antecedent soil moisture conditions (dry and wet). Different calibration approaches based on the factors K and C for RUSLE, and interrill erodibility and hydraulic conductivity in WEPP were tested. The best-performing methods in RUSLE involved measuring the K factor and adopting the recommended C factor by the National Forestry Commission of Mexico. In WEPP, the best results were obtained when interrill erodibility was estimated from experimental measurements. Overall, RUSLE outperformed WEPP in most of the treatments except for CT under WAMC. [ABSTRACT FROM AUTHOR]

The water erosion is a significant environmental issue in arid and semi-arid regions. It leads to soil degradation, reduced agricultural productivity, and desertification. This article used The WEPP, the USLE, and the MUSLE models to estimate the average soil loss in the Yozgat-Kadılı village. Also, The MUSLE model utilized the WEPP model-estimated runoff for soil loss estimation. The USLE model, which estimates soil erosion using six factors (R, K, L, S, P, and C), can be improved by incorporating the Modified Fournier Index (MFI). Results indicated that the MUSLE model (3.66 t/ha) performed well in estimating soil losses close to the observed value (3.15) in the wheat fields between 1986-1996. the MUSLE (5.31 t/ha) and WEPP (5.88 t/ha) models underestimated soil losses to the observed value (8.75 t/ha) in the fallow field for 1986-1996. The WEPP model estimated the highest average soil loss at 5.18 t/ha in a wheat field, while the USLE model yielded the lowest estimate at 1.28 t/ha between 1969 and 2020. The MUSLE model estimated the highest (4.94 t/ha) and The USLE model estimated the lowest (2.53 t/ha) soil loss in the fallow field between 1969-2020. Results also revealed that the WEPP model is needed to calibrate for estimating soil loss in arid and semi-arid regions.

Current watershed-scale, nonpoint source pollution models do not represent the processes and impacts of agricultural best management practices on water quality with sufficient detail. A Water Erosion Prediction Project-Water Quality (WEPP-WQ) model was recently developed which is capable of simulating nonpoint source pollutant transport in nonuniform hillslope conditions such as those with BMPs. However, WEPP-WQ has not been validated for these conditions, and prior validation work only evaluated calibrated performance rather than uncalibrated performance, with the latter being most relevant to model applications. This study evaluated uncalibrated and calibrated model performance in two plot-scale, artificial rainfall studies. 179 observations were compared to corresponding WEPP-WQ simulations of runoff, sediment yield, and soluble and particulate nutrient forms for both nitrogen and phosphorus. Uncalibrated validation results were mixed for the different field conditions, model configurations, and prediction variables. Nash-Sutcliffe Efficiencies for uncalibrated simulations of uniform conditions were generally greater than 0.6 except for soluble nitrogen predictions which were poor. Simulations of nonuniform conditions were generally ‘unsatisfactory’ except for runoff predictions which were quite good (NSE = 0.78). Performance was improved substantially for almost all endpoints with calibration. Some exceptions to this occurred because the objective function for calibration was based on log-space differences so as to more equally-weight calibration of unsaturated conditions that tend to produce lesser runoff volumes and sediment yields. Calibrated results for both uniform and nonuniform conditions were generally ‘satisfactory’ or ‘good’ according to widely accepted model performance criteria.

Soil erosion by water on agricultural hillslopes leads to numerous environmental problems including reservoir sedimentation, loss of agricultural land, declines in drinking water quality, and requires deep understanding of underlying physical processes for better mitigation. It is imperative to accurately predict soil erosion caused by overland flow processes so that soil conservation efforts can be undertaken proactively before large-scale sedimentation problems arise. Soil detachment is often described by the excess shear stress equation that contains two physical soil erodibility parameters, erodibility coefficient, and critical shear stress. These parameters are normally assumed to be constant but can change across varying soil texture classes as well as during surface runoff events due to changes in soil cohesion and potential dependency on soil moisture content. These changes may significantly affect soil erosion rates at the field and watershed scale. In this study, the erodibility parameters of three soil types (sandy loam, clay loam, and silty clay loam) were analyzed using a laboratory mini-Jet Erosion Test (JET) to determine the effect of soil sample infiltration and moisture condition. Results from the experiments depicted a dynamic relationship between the soil erodibility parameters and amount of infiltrated mass of water. Data analysis displayed that for soils of different texture critical shear stress exhibited local minimum with higher values for very dry and saturated soils, while erodibility coefficient tended to increase with the increase of mass of soil water. Utilizing these dynamic soil erodibility parameters did not result in a significant difference in soil erosion rates when compared to using the averaged soil erodibility parameters taken from the experiment but the range of potential erosion rates increases with the increase of applied sheer stress to soil surface. The erosion rates with the experiment-based coefficients were found to be higher than with the baseline WEPP-based coefficients. These results highlight the importance of evaluating the effect of intrastorm dependent factors during surface runoff events, such as antecedent soil moisture content, time to peak from the start of runoff, soil cohesion, etc., on soil erodibility parameters to accurately calculate erosion rates, especially for initially dry soils or during earlier stages of surface runoff when critical shear stresses were highly affected. Further assessment of such factors with JET or other laboratory and field tests is recommended. [ABSTRACT FROM AUTHOR]

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]

The Water Erosion Prediction Project (WEPP) model has been widely used for estimating runoff and soil loss. The evaluation of the latest version (version 2021.133) under a range of environmental conditions can provide confidence to its users. The objectives of this study were to evaluate the WEPP model for runoff and soil loss predictions using 1159 plot years of rainfall-runoff events data from field experimental plots with various climates, soils, topographies, and crops. WEPP runoff and soil loss predictions were compared to the observations before and after input parameter calibration. The results showed good predictions of runoff and soil loss were obtained with both the uncalibrated and calibrated WEPP model for all considered scales with Nash-Sutcliffe model efficiencies (NSE) over 0.4. The calibration of input baseline effective hydraulic conductivity (ke), baseline critical shear stress (τc), baseline rill erodibility (kr), and baseline interrill erodibility (ki) improved WEPP model performance with NSE values of 0.98 and 0.91 for average annual runoff and soil loss predictions, respectively. The WEPP model tended to underestimate the runoff and soil loss for large events with runoff over 100 mm and soil loss over 120 t/ha. Good event runoff and soil loss predictions (NSE ≥0.4) were obtained for the most common cropping/management systems considered, including corn, cotton, tilled fallow, and wheat after calibration. This study illustrates the most recent WEPP model's performance for runoff and soil loss predictions, and provides a comprehensive set of results.

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]

The Water Erosion Prediction Project (WEPP) model code was modified extensively to support the simulation of nonpoint source (NPS) pollutant sourcing and transport in nonuniform hillslopes based on NPS science from the Soil and Water Assessment Tool (SWAT). This was accomplished utilizing WEPP's overland flow element (OFE) in place of SWAT's hydrologic response unit (HRU) construct which enabled more physically plausible routing within a hillslope. In addition, several improvements to the NPS code base were implemented. These include: free-source format, modern-Fortran conventions, minor enhancements to NPS model science, and code refactoring. This manuscript documents all model development activities, presents a comparison of relevant WEPP and WEPP-WQ code bases, and performs a local sensitivity analysis of the final model code for the most important input parameters and processes. Sensitivity results indicated that the model performed as expected according to its design and provided important insights for potential subsequent validation studies.

Soil erosion by water on agricultural hillslopes leads to numerous environmental problems including reservoir sedimentation, loss of agricultural land, declines in drinking water quality, and requires deep understanding of underlying physical processes for better mitigation. It is imperative to accurately predict soil erosion caused by overland flow processes so that soil conservation efforts can be undertaken proactively before large-scale sedimentation problems arise. Soil detachment is often described by the excess shear stress equation that contains two physical soil erodibility parameters, erodibility coefficient, and critical shear stress. These parameters are normally assumed to be constant but can change across varying soil texture classes as well as during surface runoff events due to changes in soil cohesion and potential dependency on soil moisture content. These changes may significantly affect soil erosion rates at the field and watershed scale. In this study, the erodibility parameters of three soil types (sandy loam, clay loam, and silty clay loam) were analyzed using a laboratory mini-Jet Erosion Test (JET) to determine the effect of soil sample infiltration and moisture condition. Results from the experiments depicted a dynamic relationship between the soil erodibility parameters and amount of infiltrated mass of water. Data analysis displayed that for soils of different texture critical shear stress exhibited local minimum with higher values for very dry and saturated soils, while erodibility coefficient tended to increase with the increase of mass of soil water. Utilizing these dynamic soil erodibility parameters did not result in a significant difference in soil erosion rates when compared to using the averaged soil erodibility parameters taken from the experiment but the range of potential erosion rates increases with the increase of applied sheer stress to soil surface. The erosion rates with the experiment-based coefficients were found to be higher than with the baseline WEPP-based coefficients. These results highlight the importance of evaluating the effect of intrastorm dependent factors during surface runoff events, such as antecedent soil moisture content, time to peak from the start of runoff, soil cohesion, etc., on soil erodibility parameters to accurately calculate erosion rates, especially for initially dry soils or during earlier stages of surface runoff when critical shear stresses were highly affected. Further assessment of such factors with JET or other laboratory and field tests is recommended.

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Forest roads, haul roads, and especially skid trails have been associated with sedimentation and soil erosion risk. Despite the widespread small shovel harvesting system on steep terrains in South Korea, the subsequent risks of deep (rut depth >5 cm) and compact disturbances, and erosion rates in skid trails are largely unknown. Therefore, the main objectives of this study were to compare the soil erosion rate in each skid trail and predict the total soil erosion rate in a small shovel harvesting area. The soil erosion rate was measured at the plot scale (5 × 3 m) in different skid trail parts (bladed skid trail by small-shovel loader passage, BT; and compacted skid trail CT by carrier passage with construction by a small-shovel loader) using a silt fence experiment. In addition, we investigated the applicability of the Water Erosion Prediction Project (WEPP) model to each disturbance. Among all disturbances, the highest erosion rate (average value of 9.13 ± 0.96 kg m−2 4 months−1) was because of CT. The model predictions were over- and under-estimated and showed particularly poor performance where uncovered soil was exposed (less than 1%) to high machine traffic frequency and excavation. Further, the annual soil erosion rates ranged from 11.59 to 28.94 ton ha−1 year−1. The results suggested that the WEPP model could partially validate the soil erosion results, and further research is still required to improve the accuracy of the model.

Evaluation of prediction models is crucial to achieving valid information on erosion processes and their management choices. WEPP model efficiency in predicting ephemeral gully (EG) erosion was recently tested and compared with both EGEM and empirical models. The models abilities to predict EG erosion were validated using measured estimates at the 6 eroding locations around Mubi area in Northeast Nigeria between April 2008 and October 2009. Each location consisted of 3 watersheds where data on soils, climate, slope, management practices, EG shapes and dimensions were collected. Data on relevant soil properties were collected in the field and then analyzed in laboratory. The mass of soil loss (MSL) predicted by empirical, EGEM and WEPP models were compared with the measured using paired T-test, regression graphs (r2-values), error analysis, and analysis of variance (ANOVA) in a completely randomized design. The EG erosion losses varied significantly (P ≤ 0.05) between sites and years. No significant (P ≤ 0.05) differences were observed between measured and the empirically predicted aggregate MSL. The measured aggregate MSL strongly correlated with those predicted by empirical (r2 = 0.67), than with EGEM (r2 = 0.57), and WEPP (r2 = 0.53) models. Slight over and under-prediction instances against the measured erosion were noted with all the models. The WEPP model was found to slightly over-predict MSL when compared to either the empirical or EGEM model. The prediction quality of the models was generally impressive. Future works should focus more on local inputs such as climate, plants, management, and tillage data for use with WEPP.

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]

WEPP is a process-based model that estimates runoff and water erosion at slope level, maintaining a soil water balance at daily pace. The objective of this work is to adjust and validate the water balance component of the WEPP model in two watershed management situations (afforestation and natural grassland field) to obtain an adjusted tool that determines runoff and erosion. Soil water content data measured with neutron probe 4 times in the year down to 1.3 m depth during 10 years were used, and were compared with WEPP estimates. The results indicate that the WEPP estimations were not good (Efficiency coefficient (E) = 0.03, -1.29, -0.01, -1.74, 0.17 and -0.08 for the profiles) in high slope (C), average slope (D) and low slope (F), in the Grassland and afforested watershed, respectively, with an E considered insufficient and with periods of over and underestimation water content for both management situations. A better fit was obtained by eliminating the data outside of the calibration line in the profile C, with no improvement for the D and F profiles in both management situations. The results indicate that parameters such as evapotranspiration and WEPP equations must be adjusted to achieve better performance.

The main objective of this study is to predict soil erosion in the Lattakia Governorate (W Syria) using the Water Erosion Prediction Project model (WEPP) and to compare the result with that of the RUSLE. Field survey and data collection were carried out, and 44 soil samples were analyzed. In addition, all the necessary input files were prepared for use in the WEPP model and RUSLE. Results show that more than of 80% of the locations studied experience slight to moderate erosion (less than 5 t/ha/y), whereas the rest of the locations experience severe soil erosion hazard. Moreover, the volume of runoff estimated by the WEPP model is in the range of 51–321 mm, and the R2 between the simulated soil erosion and the predicted runoff reached 0.68. Interestingly, the R2 between the WEPP model and RUSLE is 0.56, which indicates a good correlation between the two models. [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]

Whereas current erosion models are successful in quantitative estimates of soil erosion by water flow, modeling the coevolution of geomorphological features, particularly rill network properties and soil erosion on hillslopes, is still a major challenge. In this study, we propose a rill evolution modeling approach and combine it with a rainfall‐runoff and soil erosion model to simulate the feedback loop of hillslope geomorphic development and soil erosion processes. Rill evolution is mainly characterized by three rill network attributes, rill density, orientation angle, and rill width, all modeled with physical equations. The entire rainfall‐runoff‐erosion and rill evolution model is tested against a set of rill network evolution and soil erosion data from an experimental hillslope subjected to successive rainfall events. The simulated spatial and temporal variations of rill network characteristics and soil erosion agree well with the measured data. The results demonstrate that the three rill network characteristics continually alter the partitioning of interrill and rill flows and affect the interrill and rill flow erosivity and soil erosion, which in turn modify the rill geometry and rill network planform. Comparatively, existing approaches such as Water Erosion Prediction Project (WEPP) that ignore the rill evolution processes largely underestimate the hillslope soil erosion when using time independent model parameters. Moreover, a sensitivity analysis indicates that both the rill evolution and soil erosion processes are sensitive to the rill evolution parameters, rainfall intensity, and slope angle. These results can inform the development of general geomorphic evolution and soil erosion models on evolving rilled hillslopes. Key Points: A set of conceptual equations using flow hydraulic and erosion properties are proposed to simulate evolving rill characteristicsA theoretical framework is presented to simulate coupled rill evolution and soil erosion processesThe coupled model is sensitive to the rill evolution parameters, rainfall intensity, and slope angle [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]

Water and soil are the foundation of human life. Today, soil erosion is threatening these valuable resources and consequently human life. Therefore, it is necessary to analyze and control of soil erosion. For evaluating the quality and quantity of soil erosion many models have been proposed. In this study, we aim to analyze erosion and sediment production of the Sulachai watershed, using three models of WEPP, EPM and Fournier and GIS technique. In general, in WEPP model, the file related to each of the parameters was made and entered in the software Geo WEPP. In the EPM model, first the map of coefficients was prepared and then with respect to these coefficients, the map of erosion was prepared. Also, in the Fournier model, required parameters were calculated and placed in the relevant place. Finally, the amount of sediment was estimated with the mentioned three methods. The observed sediment content also was obtained by using gradient flow and sediment. WEPP model has three methods which are slope, catchment area and flow-direction. Estimated sediment by each of the above three methods, are 0.213, 0.178 and 0.785 respectively, and also with the EPM and Fournier models, about 0.241 ton/hectares/year. Also the observed sediment amount was estimated 0.241 ton/hectares/year. The results of this research showed that WEPP model has better performance than other two models in estimating erosion and sediment in the Sulachai watershed.

ABSTRACT Models have been used by man for thousands of years to control his environment in a favorable way to better human living conditions. The use of hydrologic models has been a widely effective tool in order to support decision makers dealing with watersheds related to several economic and social activities, like public water supply, energy generation, and water availability for agriculture, among others. The purpose of this review is to briefly discuss some models on soil and water movement on landscapes (RUSLE, WEPP, GeoWEPP, LASH, DHSVM and AnnAGNPS) to provide information about them to help and serve in a proper manner in order to discuss particular problems related to hydrology and soil erosion processes. Models have been changed and evaluated significantly in recent years, highlighting the use of remote sense, GIS and automatic calibration process, allowing them capable of simulating watersheds under a given land-use and climate change effects. However, hydrology models have almost the same physical structure, which is not enough for simulating problems related to the long-term effects of different land-uses. That has been our challenge for next future: to understand entirely the hydrology cycle, having as reference the critical zone, in which the hydrological processes act together from canopy to the bottom of aquifers.

Changes of soil erosion and rainfall have been simulated by using the Water Erosion Prediction Project (WEPP) model between 2016 and 2039 in Lattakia, Syria. This study was conducted in 6 locations that are characterized by two different ecosystems (agricultural, forest). The results show a linear decrease in rainfall amount of about 7.11 mm per year (170 mm for the whole studying period). For the years 2025, 2026 and 2030, three snowy storm events have been predicted, while the year 2030 will record the highest rainfall amount of 1816.1 mm. According to the WEPP model, the average of estimated soil erosion amount in Alhamara has reached 19 t/ha/y for the agricultural system while it is estimated to be 2.03 t/ha/y for the forest system. The general average of soil erosion in the study area (taking into consideration the variety of slope) within the agricultural system has reached 14.086 t/ha/y, which indicates that there will be a dangerous impact of future erosion on the sustainability of natural sources (soil, water) in the study area.

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Erosion prediction models recreate past scenarios, assess future ones, and determine the best explanatory variables of the soil erosion process. They are widely used and contribute valuable data for landscape management. This paper presents an estimation of soil erosion in the Teotihuacan Valley Basin in central Mexico, assessing its response to biophysical and anthropogenic components during 4 periods within the past 2,000 years. The valley has undergone past and recent anthropogenic erosion and, during the past 2 millennia, has experienced a marked variation in precipitation, variations in land use, soil management, and to a lesser extent, variations in soil type. With the use of the Water Erosion Prediction Project model, we estimated how the above‐mentioned parameters affect soil losses under 4 scenarios: (a) humid conditions (900 mm yr−1) during the Teotihuacan Period (1–650 CE), (b) dry conditions (370 mm yr−1) during the Aztec Period (1325–1521 CE), (c) humid conditions (900 mm yr−1) during the Aztec Period, and (d) present conditions (after 1970 CE; 560 mm yr−1). Comparison of scenarios and a principal component analysis of soil loss according biophysical components showed topography to be the most closely related parameter to soil erosion. Land use and soil type also showed a relationship with soil erosion, particularly during the Aztec Period; climate change did not appear to be the most significant factor in soil loss. Estimation of soil erosion by means of models is an inexpensive way to find answers to future challenges concerning soil erosion in a changing environment. [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]

Abstract: Water runoff and sediment transport from agricultural uplands are substantial threats to water quality and sustained crop production. To improve soil and water resources, farmers, conservationists, and policy‐makers must understand how landforms, soil types, farming practices, and rainfall interact with water runoff and soil erosion processes. To that end, the Iowa Daily Erosion Project (IDEP) was designed and implemented in 2003 to inventory these factors across Iowa in the United States. IDEP utilized the Water Erosion Prediction Project (WEPP) soil erosion model along with radar‐derived precipitation data and government‐provided slope, soil, and management information to produce daily estimates of soil erosion and runoff at the township scale (93 km2 [36 mi2]). Improved national databases and evolving remote sensing technology now permit the derivation of slope, soil, and field‐level management inputs for WEPP. These remotely sensed parameters, along with more detailed meteorological data, now drive daily WEPP hillslope soil erosion and water runoff estimates at the small watershed scale, approximately 90 km2 (35 mi2), across sections of multiple Midwest states. The revisions constitute a substantial improvement as more realistic field conditions are reflected, more detailed weather data are utilized, hill slope sampling density is an order of magnitude greater, and results are aggregated based on surface hydrology enabling further watershed research and analysis. Considering these improvements and the expansion of the project beyond Iowa it was renamed the Daily Erosion Project (DEP). Statistical and comparative evaluations of soil erosion simulations indicate that the sampling density is adequate and the results are defendable. The modeling framework developed is readily adaptable to other regions given suitable inputs. © 2017 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

This study investigates the effects of pumice excavation on runoff formation and soil erosion processes in a forested catchment in SW-Germany. The underlying questions are, if (a) backfilled soils have different properties concerning runoff generation and erodibility and if (b) clear-cutting prior to excavation triggers runoff and erosion. Four adjacent sub-areas were observed, which represented different pre- and post-excavation-stages. The basis of the investigation was a comprehensive field sampling that delivered the data for physical erosion modeling using the Water Erosion Prediction Project (WEPP). Modeling took place for standardized conditions (uniform slope geometry and/or uniform land management) and for actual slope geometry and land management. The results show that backfilled soils exhibited 53% increase of annual runoff and 70% increase of annual soil loss under standardized conditions. Storm runoff was increased by 6%, while storm soil loss was reduced by 9%. Land management changes also triggered shifts in annual runoff and soil erosion: Clear-cut (+1.796% runoff, +4.205% soil loss) and bare (+5.958% runoff, +21.055% soil loss) surfaces showed the most distinct changes when compared to undisturbed forest. While reforestation largely diminished post-excavation runoff and soil erosion, the standardized results statistically prove that soil erodibility and runoff generation remain increased after backfilling.

Ephemeral gully erosion, prevalent on agricultural landscapes of the Great Plains, is recognized as a large source of soil loss and a substantial contributor to the sedimentation of small ponds and large reservoirs. Multi-seasonal field studies can provide needed information on ephemeral gully development and its relationship to physical factors associated with field characteristics, rainfall patterns, runoff hydrograph, and management practices. In this study, an ephemeral gully on a no-till cultivated crop field in central Kansas, U.S., was monitored in 2013 and 2014. Data collection included continuous sub-hourly precipitation, soil moisture, soil temperature, and 15 field surveys of cross-sectional profiles in the headcut and channelized parts of the gully. Rainfall excess from a contributing catchment was calculated with theWater Erosion Prediction Project (WEPP) model for all storm events and validated on channel flow measurements. Twelve significant runoff events with hydraulic shear stresses higher than the critical value were identified to potentially cause soil erosion in three out of fourteen survey periods. Analysis of shear stress imposed by peak channel flow on soil surface, antecedent soil moisture condition, and channel shape at individual events provided the basis on which to extend the definition of the critical shear stress function by incorporating the intra-storm changes in soil moisture content. One potential form of this function was suggested and tested with collected data. Similar field studies in other agriculturally-dominated areas and laboratory experiments can develop datasets for a better understanding of the physical mechanisms associated with ephemeral gully progression. [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]