Water Erosion Prediction Project Model Research Articles

Effects of root traits on soil detachment capacity driven by farmland abandonment

Vegetation restoration significantly affected root traits during farmland abandonment, thereby considerably altering the soil detachment process. However, few studies have investigated the effects of root traits on soil detachment capacity under different ages of farmland abandonment. To examine the effects of root trait changes caused by vegetation restoration on soil detachment capacity by overland flow (Dc) and soil resistance to erosion under different ages of farmland abandonment, flow scouring tests under five shear stress levels (2.80–12.95 Pa) were conducted on 125 undisturbed soil samples collected using an indoor variable slope flume. The results showed that, compared to slope farmland, the root traits of abandoned farmland (5, 12, 24, and 36 years) increased considerably, and the Dc and erodibility decreased by 51.3–93.9 % and 61.8–94.1 %, respectively. The critical shear stress of abandoned farmland gradually increased with the age of farmland abandonment, but remained less than that of slope farmland. Among hydraulic parameters, stream power was the optimal index for predicting Dc, while among root morphological traits, root surface area density (RSAD) was the best indicator for predicting Dc. The median soil particle size (D50) and cohesion are important factors that affect soil detachment. According to the Water Erosion Prediction Project (WEPP) model, Dc can be predicted using the RSAD and soil cohesion (R2 = 0.95, NSE = 0.95). In addition, a new model was established to estimate the soil detachment capacity based on D50 (R2 = 0.97, NSE = 0.97). In the present study, the performance of the model was improved compared with that of previous studies.

Simulation of Long-Term Water Erosion in Rainfed Croplands of Eastern Washington

Highlights Water erosion in the inland Pacific Northwest was modeled with WEPP for the past (1940–1982) and present (1983–2020). Water erosion decreased from past to present in the study watersheds. Major factors are increased adoption of conservation practices and decrease in large precipitation events. Abstract. 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. Keywords: Inland Pacific Northwest, Soil erosion by water, Temporal trend, WEPP.

A Mathematical Method for Estimating the Critical Slope Angle of Sheet Erosion

Estimating the critical slope angle (CSA) for sheet erosion is important for the precision estimation of sheet erosion and the development of erosion control practices. This study developed mathematical equations considering rainfall intensity and soil infiltration to efficiently estimate both instantaneous (at a given instant during rainfall) and cumulative CSAs, while also providing a valuable explanation for the change in CSA. The mathematical equations were consistent with observations from runoff plots (NSE = −1.01) of loess soils from Zhangjiakou (China) and simulation results (NSE = 0.96) from the Water Erosion Prediction Project model for a loam soil in Montana (USA). Estimated instantaneous CSA determined by the mathematical equations increased as the ratio of rainfall intensity to soil infiltration (I/f) increased, resulting in higher observed cumulative CSA after heavy versus normal rainfall events. Heavy rainfall, compacted soil, and varying rainfall duration affected the CSA by changing the I/f ratio. Maximum instantaneous CSA provided a better prediction of changes in soil erosion dynamics than that obtained from CSAs determined by field observations or experimental simulations. The mathematical equations illustrate the underlying physical mechanisms by which rainfall intensity and soil infiltration affect the CSA through changing the shear stress of overland flow. The results of this study provide critical information for guiding the development of effective soil erosion control strategies.

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

AbstractThere 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.

Predicting the interrill erosion rate on hillslopes incorporating soil aggregate stability on the Loess Plateau of China

The Water Erosion Prediction Project (WEPP) model is a physical process-based model that can predict both interrill and rill erosion on hillslopes. The interrill erodibility (Ki) is quantified by the soil particle size distribution, which is a key parameter in WEPP model. However, the important effects of soil structure on soil erodibility are ignored, which seriously affects the prediction accuracy of the model. In this study, simulated rainfall experiments (60, 90, 120 mm h−1) were performed to improve the prediction equation of interrill erosion incorporating the aggregate instability index (As). Rare earth elements (REEs) were employed as tracers to distinguish interrill and rill erosion on slopes in a box (2 m long, 0.5 m wide, 0.4 m deep) with gradients of 10°, 20° and 30°. The Le Bissonnais method was used to determine the soil aggregate stability. The results showed that aggregate stability played a crucial role in interrill erosion under similar runoff rates. The improved equation contains four parameters, As, runoff rate (q), rainfall intensity (I) and slope gradient (Sf), with a coefficient of determination (R2) of 0.81 and model efficiency (ME) of 0.79. This equation exhibits greatly improved efficiency in estimating the interrill erosion rate compared to the WEPP model. Furthermore, a new equation incorporating the As, flow velocity (v), flow depth (h) and hydraulic gradient (J) was developed, with R2 of 0.90 and ME of 0.89. This study provides a deeper understanding of the mechanism of interrill erosion and improves upon the physical process-based soil erosion model.

A WEPP-Water Quality model for simulating nonpoint source pollutants in nonuniform agricultural hillslopes: Model development and sensitivity

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 modelling of burned and mulched soils following a Mediterranean forest wildfire

AbstractSoil erosion modelling applied to burned forests in different global regions can be unreliable because of a lack of verification data. Here, we evaluated the following three erosion models: (1) Water Erosion Prediction Project (WEPP), (2) Morgan‐Morgan‐Finney (MMF) and (3) Universal Soil Loss Equation‐Modified (USLE‐M). Using field plots that were either untreated or mulched with straw, this study involved observations of soil loss at the event scale at a burned pine forest in Central Eastern Spain. The erosion predictions of the three models were analysed for goodness‐of‐fit. Optimization of the MMF model with a new procedure to estimate the C‐factor resulted in a satisfactory erosion prediction capacity in burned plots with or without the mulching treatment. The WEPP model underestimated erosion in the unburned areas and largely overestimated the soil loss in burned areas. The accuracy of soil loss estimation by the USLE‐M model was also poor. Calibration of the curve numbers and C‐factors did not improve the USLE‐M model estimation. Therefore, we conclude that an optimized MMF model was the most accurate way to estimate soil loss and recommend this approach for in Mediterranean burned forests with or without postfire mulching. This study gives land managers insight about the choice of the most suitable model for erosion predictions in burned forests.

Evaluating the applicability of the water erosion prediction project (WEPP) model to runoff and soil loss of sandstone reliefs in the Loess Plateau, China

Soil erosion is one of the most serious environmental issues, especially in vulnerable areas such as the Pisha sandstone regions located in the Loess Plateau (China). In these types of reliefs, long-term studies monitoring runoff and soil loss are scarce, and even more considering the efficiency of different soil management techniques applied to reduce land degradation. In this study, seven years (2014–2020) of in-situ measurements of surface runoff and soil loss for different land uses (forestland, shrubland, grassland, farmland, and bare land) in a Pisha Sandstone environment at the Loess Plateau were conducted. We applied the Water Erosion Prediction Project (WEPP) model combining the large database with the precipitation regimes. Our results showed that runoff volume coming from observed and simulated data exhibited significant differences among them depending on the different vegetation types. Runoff and soil loss were different among diverse land use types as follows: farmland > grassland > shrubland > forestland. After conducting a calibration, we found satisfactorily simulated surface runoff and sediment yield based on precipitation regimes and land uses at sandstone reliefs. Simulation performance of surface runoff was better than sediment yield. The range of standard error of the model simulation for event and annual values of runoff were 4.71 mm and 12.19 mm, respectively. The standard error for event and annual values of soil loss were 4.19 t/hm2 and 21.86 t/hm2. In the calibration group, R2 of runoff and soil loss were 0.92 and 0.86 respectively, while Nash-Sutcliffe coefficient (E) reached 0.90 and 0.85, respectively. In the validation group, the R2 for both runoff and soil loss were 0.82 and 0.56, respectively. Nash-Sutcliffe coefficient (E) were 0.77 and 0.54 for the runoff and sediment yield. We concluded that using a detailed monitoring dataset, the WEPP model could accurately simulate and predict water erosion in the hillslopes of Pisha sandstone area.

Measuring and Modeling Impacts of Gravel Road Design on Sediment Generation in the Southeastern U.S.

Highlights The erodibility of heavily trafficked gravel roads can be much greater than that of low volume forest roads. Improved designs of heavily trafficked gravel roads can decrease sediment generation by more than 90 percent. The WEPP Model can be successfully parameterized for high traffic gravel roads to reflect the effects of weather, road design, and topography. Abstract. The purposes of this study were to support a watershed modeling analysis by evaluating the ability to the Water Erosion Prediction Project (WEPP) model to estimate sediment generated by high traffic gravel roads, and to determine the erodibility of two designs of high-traffic gravel roads. In many watersheds, the road network can be a major source of sediment. The ability to predict erosion from roads, evaluate the effects of design and management on road sedimentation, and compare sediment from roads to other sources of sediment in the watershed is an ongoing need by watershed managers. The Water Erosion Prediction Project (WEPP) model is a widely used model for predicting sediment from forest roads. There has, however, been little information published on erosion from high traffic gravel roads and WEPP applications to such roads. To evaluate road erosion predictions, a study was conducted incorporating two road designs at Fort Benning, Georgia, U.S. One design followed a common practice of starting with a native material road and adding gravel and grading as required. Erosion and rutting on the road surface were common occurrences on this type of road. The improved design was a “graded aggregate base” design, built with compacted aggregate layers. To evaluate erosion risks for these two road designs, runoff and sediment delivery were measured from ten plots ranging in size from 63 to 150 m2. Runoff depths up to 50 mm occurred from daily rainfall amounts up to nearly 60 mm, with least square mean event runoff values of 6.5 mm from unimproved plots and 14.9 mm from improved road plots. Delivered sediment ranged from zero to 18 Mg ha-1 from individual storms with least square mean amounts of 2.27 Mg ha-1 of sediment delivered from unimproved road plots compared to only 0.026 Mg ha-1 delivered from improved road design plots for a given runoff event. Hydraulic conductivity was found by calibration to be 3.0 mm h-1 for unimproved roads and 1.3 mm h-1 for improved road segments. Rill erodibility was 0.09 s m-1 for unimproved roads and 0.0008 s m-1 for improved roads, values that were greater than had been measured on road erosion studies elsewhere that were typically less than 0.0004 s m-1. The critical shear for the unimproved roads was the minimum that the WEPP model would accept, 0.0001 Pa, but was a more typical value of 1.5 Pa for the improved road segments. When applying the calibrated erodibility values to a validation data set, the Willmott indices of agreement were 0.62 and 0.82 for runoff for unimproved and improved roads, respectively, and 0.67 and 0.66 for sediment delivery from unimproved and improved roads, respectively, indicating good agreement between observed and WEPP-estimated runoff and erosion rates. A sensitivity analysis and calibration analysis found that the WEPP model was not sensitive to interrill erosion for this application. A sensitivity analysis coupled with a WEPP validation analysis showed that WEPP could incorporate weather, topography, soil, and road design features to predict sediment delivery from highly erodible road segments. The study suggests that there is a need for a simulated runoff study to determine high values of rill erodibility more precisely on unimproved high traffic roads, and that there is a need to incorporate more erodible road erodibility values into the online WEPP:Road interface for the WEPP model. The road erosion rates and effectiveness of improved road designs for reducing off-road sediment reported in this study will be useful to managers seeking to quantify and reduce road erosion rates from high-traffic gravel roads in sensitive watersheds. Keywords: Erodibility, Gravel Roads, Soil Erosion, WEPP.

Estimating WEPP Cropland Erodibility Values From Soil Properties

Highlights Very fine sand is the single most important variable for predicting rill and interrill erodibility values. Slope steepness is the most important property for predicting critical shear for rill erosion. Erodibility prediction equations with the best goodness-of-fits have both soil texture and mineralogy terms. Equations to predict erodibility from texture, organic carbon, cation exchange, slope, and taxonomy are proposed. Abstract. 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 (𝜏c) 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. Keywords: Critical Shear, Interrill Erodibility, Rill Erodibility, Soil Properties, WEPP.

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

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.

Scenario analysis of high and steep cutting slopes protection in the loess hilly region: A case study of the Yangjuangou catchment in Yan’an, China

Soil erosion and slope instability restrict the cutting slopes, especially the high and steep slopes of a construction site. It is difficult for present research of observation experiments and investigation to deal with these problems under climate change. Focusing on gully land consolidation in the loess plateau of China, this paper put forward a technical procedure to explore the optimal combination scheme of slope-cutting and vegetation-planting in future climate change. The technical procedure includes scenarios design, model calculation, and scheme optimization. This paper selected a back catchment in Yangjuangou catchment of Yan’an City as a case study and designed 54 combined scenarios consisting of 6 slopes, 3 types of vegetation (including bare land), and 3 climate scenarios. The soil erosion and slope stability under different scenarios were quantified using FLAC/Slope software and Water Erosion Prediction Project (WEPP) model. This paper innovatively designed elasticity indicators to trade off the increase of the flat land area formed by land consolidation and the resulting reduction in slope stability and increase in soil erosion. It is found that the slope of 53° with Caragana microphylla could be the optimal combination scheme considering flat land creating and the safety of slopes. The technical procedure and the resulting parameters could support gully land consolidation in related areas and be referenced by other construction projects.

Adapting the WEPP Hillslope Model and the TLS Technology to Predict Unpaved Road Soil Erosion.

Unpaved road erosion have been recognized as important sediment sources in a watershed. To evaluate where and when road erosion occurs, the soil loss along road segments should be precisely predicted with process-based erosion models. Methods: The hillslope version of the Water Erosion Prediction Project (WEPP) was used to estimate soil loss from 20 typical road segments in the red soil region of South China. Terrestrial laser scanning (TLS)-measured soil losses were used to validate the model simulations. The results showed that the WEPP model could reasonably predict the total soil loss in relatively short (less than 100 m) and gentle (slope gradient lower than 10%) road segments. In contrast, soil loss would be underestimated for long or steep road segments. Detailed outputs along roads revealed that most of the peak soil loss rates were underestimated. It might due to the linear critical shear stress theory in the WEPP model. Additionally, the lack of upstream flow was found to be connected to the relatively low model efficiency. Nevertheless, the WEPP simulation could accurately fit erosion trend and predict the peak soil loss positions along road segments. Conclusions: The WEPP model could be adopted to evaluate the erosion risk of unpaved roads in the red soil region of South China.

Investigation of human-induced land use dynamics in a representative catchment on the Chota Nagpur Plateau, India: A spatiotemporal application of soil erosion modeling with connectivity index studies

The soil erosion and sediment yield on the Chota Nagpur Plateau, India have been greatly affected over the years by ever increasing anthropogenic influences and associated land-use/land-cover (LULC) changes. This study coupled a CA-Markov model with the Geospatial Interface for Water Erosion Prediction Project (GeoWEPP) model along with sediment connectivity index (IC) to estimate the decadal-scale soil erosion and sediment yield changes in a representative catchment of Chota Nagpur Plateau for 2001–2040 period. This LULC- Erosion-IC modeling approach in the Konar catchment has revealed (i) concerning patterns of conversions of bare lands and grasslands to agricultural fields and (ii) dominance of the new agricultural lands in the areas with higher connectivity. Results indicated that around 11 % and 13 % of the total catchment area undergoing agriculture will be in the highly erodible and highly connected category respectively by 2040. The corresponding mean erosion rates showed a significant increase for agricultural lands [from 26 to 35 T/Ha/Y], built up areas [from 43 to 48 T/Ha/Y], and bare lands [from 30 to 36 T/Ha/Y] during the time period of 2001 to 2040. The evaluation of mean connectivity values showed future expansions of forests (through agro-forestry, i.e. ∼2400 ha) with low connectivity by 2040. A strong linkage between increased future sediment yield and changing LULC patterns (around +6 % and +8 % of the built up area and agricultural lands and −5% and −9% of bare lands and grasslands respectively) can be observed by 2040. These changes are directly attributed to the sediment yield in the region with approximately 59 % and 97 % increase during 2001–2020 and 2020–2040 periods respectively. This study provided a good understanding of general trends in erosion and sediment yield in the Chota Nagpur Plateau and the influence of ongoing efforts in agro-forestry components and land use change dynamics.

Investigation of Geomorphometric Parameters to Simplify Water Erosion Modelling (a Case Study: Emamzadeh Watershed, Iran)

In recent decades, water erosion potential has been recognized as a severe threat against soil sustainability and water resources. The present study was conducted to investigate the relation between geomorphometric parameters and soil type to simulate water erosion in the Emamzadeh watershed located in the northeast of Khuzestan Province. The primary and secondary geomorphic parameters, including slope, plan curvature, profile curvature, flow length, flow accumulation, flow direction, and stream power index (SPI) calculated based on the digital elevation model (DEM). The water erosion measured using available data and laboratory analyzes, then it was predicted with water erosion prediction project (WEPP) model. Our results revealed that the measured soil erosion does not show any relation with geomorphic parameters, while some of the geomorphometric parameters depicted a significant relation with WEPP model’s predictions. A model with an excellent explanation coefficient obtained using multivariate linear regression to predict water erosion. The geomorphometric parameters application allows an estimation of erosion based on simple linear models (R 2 : 0.934, sig: 0.000). Moreover, for SPI, the total curvature was -0.794, plan curvature was -0.658, and profile curvature was 0.746. Therefore, there was a relation between curvature and SPI. Our results showed no specific relation between sediment transport index (STI) and water erosion. The low amount of STI represents the sedimentation areas in the watershed. Generally, application of geomorphometric parameters simplify the soil erosion prediction.

Investigation of Geomorphometric Parameters to Simplify Water Erosion Modelling (a Case Study: Emamzadeh Watershed, Iran)

In recent decades, water erosion potential has been recognized as a severe threat against soil sustainability and water resources. The present study was conducted to investigate the relation between geomorphometric parameters and soil type to simulate water erosion in the Emamzadeh watershed located in the northeast of Khuzestan Province. The primary and secondary geomorphic parameters, including slope, plan curvature, profile curvature, flow length, flow accumulation, flow direction, and stream power index (SPI) calculated based on the digital elevation model (DEM). The water erosion measured using available data and laboratory analyzes, then it was predicted with water erosion prediction project (WEPP) model. Our results revealed that the measured soil erosion does not show any relation with geomorphic parameters, while some of the geomorphometric parameters depicted a significant relation with WEPP model’s predictions. A model with an excellent explanation coefficient obtained using multivariate linear regression to predict water erosion. The geomorphometric parameters application allows an estimation of erosion based on simple linear models (R 2 : 0.934, sig: 0.000). Moreover, for SPI, the total curvature was -0.794, plan curvature was -0.658, and profile curvature was 0.746. Therefore, there was a relation between curvature and SPI. Our results showed no specific relation between sediment transport index (STI) and water erosion. The low amount of STI represents the sedimentation areas in the watershed. Generally, application of geomorphometric parameters simplify the soil erosion prediction.

Assessment of Soil Erosion Potential From the Disturbed Surface of Skid Trails in Small Shovel Harvesting System

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.

Simulating storm intensification impact on soil erosion and soil hydrology in various cropping and tillage systems under climate change

AbstractStorm intensification in the past half‐century has been documented in the U.S., and the trend will likely become more intense in future. Thus, storm intensification should be considered in impact assessment of climate change on soil erosion. The objective is to simulate how climate change will affect surface runoff, soil erosion, and crop production, using a weather generator‐based downscaling method that explicitly incorporates future storm intensification. A total of 100 climate projections was generated from 25 downscaled General Circulation Models (GCMs) under two emission scenarios for two future periods. The Water Erosion Prediction Project (WEPP) model was run for 29 cropping and tillage systems for Weatherford, Oklahoma, U.S. Compared with baseline, annual precipitation would significantly decrease by 4.6% (P < 0.05) during 2021‐2050 and 5.6% (P < 0.05) during 2051‐2080. Most crop yields would decrease by 10‐18% except cotton. The overall surface runoff (soil loss) averaged over all cropping and tillage systems, 25 GCMs, two emissions and two time periods would decrease by approximate 5.8% (increase by about 2.9%) during 2021‐2080. Soil loss followed the order of reduced till (RT) >conventional till (CT) >delayed till (DT) >no‐till (NT), suggesting no‐till would be a key solution to control soil erosion in future. Evapotranspiration followed the order of CT>NT >DT>RT for both present and future climates. Soil water and deep percolation changed little among tillage practices and climate scenarios. Projected erosion is sensitive to storm intensification, and thus more studies are needed for properly simulating storm intensification in future studies.This article is protected by copyright. All rights reserved.

WEPPcloud: An online watershed-scale hydrologic modeling tool. Part II. Model performance assessment and applications to forest management and wildfires

Suspended sediment and nutrients following forest management activities or wildfires are transported to streams and lakes via surface runoff and are a major threat to water quality. Land and water managers resort to hydrologic models to test hypotheses that can help them make informed decisions to minimize disturbances and protect water resources. We present applications of an online interface, WEPPcloud, for the Water Erosion Prediction Project (WEPP) model as a pre- and post-disturbance management tool to model various gauged and ungauged forested watersheds throughout the western U.S. We compare simulated streamflow, sediment, and phosphorus to observations at USGS gauging stations and assess the accuracy of the online interface with minimal or no calibration. Specifically, we present modeling results from 28 relatively undisturbed forested watersheds in the states of California, Nevada, Oregon, Washington, and Idaho. Across all watersheds, the NSEs based on the daily streamflow values, were in the range of 0.43 to 0.64 indicating satisfactory agreement between modeled and observed values. Similarly, annual average NSE for sediment yield was 0.61, while for phosphorus it was 0.75, 0.71, and 0.66, for total, particulate, and soluble reactive phosphorus, respectively. Additionally, we demonstrate the utility of the WEPPcloud interface as a tool to compare model results for ungauged watersheds from various disturbed conditions including prescribed fire, thinning, and wildfire to undisturbed model results to better understand the effects of forest management and wildfires on water quality and quantity.

Simulating the potential effects of elevated CO2 concentration and temperature coupled with storm intensification on crop yield, surface runoff, and soil loss based on 25 GCMs ensemble: A site-specific case study in Oklahoma

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.