Calibration, validation, and evaluation of the Water Erosion Prediction Project (WEPP) model for hillslopes with natural runoff plot data

Wang, Shuyuan; McGehee, Ryan P.; Guo, Ten-Huei; Flanagan, D. C.; Engel, Bernard A.

doi:10.1016/j.iswcr.2022.10.004

Cited by 4 publications

(3 citation statements)

References 35 publications

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“…but not at sites DO1 and RO1. The results at sites BE1, GO1, and ST1 agree with the existing literature that K be , E IR , and E R are key parameters for calibrating runoff and soil erosion in WEPP (Abaci & Papanicolaou, 2009;Anache et al, 2018;Flanagan et al, 2012;Pandey et al, 2008;Wachal et al, 2008;Wang et al, 2022). The calibrated predictions at sites DO1 and RO1 also showed that these parameters can improve the predictive ability of WEPP given that there were significant improvements in PBIAS values at both sites and improvements in NSE values at RO1, but they still fell short of the necessary accuracy requirements outlined in Moriasi et al (2007) until additional calibration involving P stdev .…”

Section: Discussionsupporting

confidence: 88%

“…Other studies have also successfully calibrated WEPP using K be , E IR , and E R as well as several other soil and management parameters (Abaci & Papanicolaou, 2009;Anache et al, 2018;Pandey et al, 2008;Wachal et al, 2008;Wang et al, 2022), which further support the results of this study. The most commonly used parameters for calibrating WEPP were K be (Abaci & Papanicolaou, 2009;Anache et al, 2018;Pandey et al, 2008;Wachal et al, 2008;Wang et al, 2022); interrill, rill, or channel erodibility (Abaci & Papanicolaou, 2009;Anache et al, 2018;Pandey et al, 2008;Wachal et al, 2008;Wang et al, 2022); and critical shear stress (Anache et al, 2018;Wachal et al, 2008;Wang et al, 2022). Although the critical shear stress was chosen for calibration in other studies, adjusting it did not significantly improve WEPP's ability to predict measured soil loss at the five Discovery Farm field sites, so it was not included in during calibration.…”

Section: Discussionsupporting

confidence: 86%

“…The findings in Kinnell (2017) also showed that WEPP did not accurately predict observed USLE runoff and soil loss events on four bare fallow plots even after following a calibration procedure consistent with the one outlined in Flanagan et al (2012). Although numerous studies have shown that WEPP can accurately predict observed runoff and soil loss after these parameters are calibrated (Abaci & Papanicolaou, 2009; Anache et al, 2018; Pandey et al, 2008; Wachal et al, 2008; Wang et al, 2022), the findings at sites DO1 and RO1 and in Kinnell (2017) show that such an approach may not always be successful. Given that this approach has been successful in numerous studies while proving to be unsuccessful in several instances, a new calibration approach involving the monthly P stdev in Cligen was used to improve the accuracy of WEPP in predicting monthly R avg‐T , RR T , and soil loss at all five sites in this study.…”

Section: Discussionmentioning

confidence: 99%

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Calibration and validation of hillslope runoff and soil loss outputs from the Water Erosion Prediction Project model in Minnesota agricultural watersheds

Kohrell,

Mulla,

Gelder

2023

J American Water Resour Assoc

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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.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

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Calibration and validation of hillslope runoff and soil loss outputs from the Water Erosion Prediction Project model in Minnesota agricultural watersheds

Kohrell,

Mulla,

Gelder

2023

J American Water Resour Assoc

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Runoff prediction based on the IGWOLSTM model: Achieving accurate flood forecasting and emergency management

Peng,

Lin,

Fan

et al. 2024

Journal of Hydro-environment Research

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Empirical and physical modelling of soil erosion in agricultural hillslopes

Bueno-Hurtado,

Seidou

2024

Journal of Hydrology and Hydromechanics

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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.

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Calibration, validation, and evaluation of the Water Erosion Prediction Project (WEPP) model for hillslopes with natural runoff plot data

Cited by 4 publications

References 35 publications

Calibration and validation of hillslope runoff and soil loss outputs from the Water Erosion Prediction Project model in Minnesota agricultural watersheds

Calibration and validation of hillslope runoff and soil loss outputs from the Water Erosion Prediction Project model in Minnesota agricultural watersheds

Runoff prediction based on the IGWOLSTM model: Achieving accurate flood forecasting and emergency management

Empirical and physical modelling of soil erosion in agricultural hillslopes

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