Water Erosion Prediction Project Model Research Articles

Hydro-geomorphological assessment of culvert vulnerability to flood-induced soil erosion using an ensemble modeling approach

Intense precipitation events pose growing threats to forest infrastructure causing flooding, and soil erosion and deposition, creating bottlenecks at road-stream crossing structures (RSCS). We describe a hillslope-scale ensemble hydro-geomorphological vulnerability assessment integrating geospatial Streambank Erosion Vulnerability Assessment (SBEVA), Modified Revised Soil Loss Equation (MRUSLE), and process-based Water Erosion Prediction Project (WEPP) model into an ensemble hydro-geomorphologic vulnerability index (EHVI) for USDA Forest Service (USFS) managed 194 road-culverts at the Hubbard Brook Experimental Forest (HBR-EF) in New Hampshire, USA. The results revealed that five and one culvert with diameters of 0.46m and 0.61m, respectively, have extreme EHVI values between 4 and 5, and fifteen and three culverts with diameters of 0.46m and 0.61m, respectively, have severe EHVI values between 3 and 4, some of which were previously identified as hydrologically vulnerable (undersized) to floods. This knowledge will inform USFS efforts to improve the resilience of the RSCS and protect aquatic habitats.

Effects of initial soil moisture on rill erodibility and critical shear stress factors in the WEPP model across diverse soil types

Rill erosion, a significant issue in agricultural regions, is intricately linked to initial soil moisture conditions, affecting the development of concentrated flow erosion processes. However, understanding its dynamics amidst varying soil moisture conditions remain challenging. This study aimed to assess the impact of different soil moisture levels on rill erodibility parameters in the Water Erosion Prediction Project (WEPP) model and to evaluate soil cohesion across a spectrum of soils. Through laboratory experiments employing a small V-shaped rill channel, we investigated rill erodibility (Kr) and critical hydraulic shear stress (τcr), under three soil moisture scenarios: initially dry, saturated, and drainage, with incremental surface inflow rates. Additionally, we examined the efficiency of soil cohesion obtained from an Automated Soil Cohesion Measurement Apparatus in predicting Kr and τcr across various soil textures. Our analysis encompassed twenty soils representing nine texture classes, revealing significant correlations between basic soil properties, cohesion parameters, and WEPP model rill erodibility. Notably, initial soil moisture conditions exerted substantial influence on erodibility potentials. Soils with higher silt contents demonstrated better fits in terms of Nash-Sutcliffe model efficiency, particularly under initially dry and saturated conditions. However, predictions for initially drained soils yielded poor fits, emphasizing the intricate interplay between soil properties and hydrological conditions. In conclusion, our findings emphasize the critical role of topsoil water dynamics in rill erodibility. We propose that soil cohesion serves as a valuable predictor, complementing friction forces within the soil and enhancing simulations of rill erodibility under shallow flow conditions in rills, particularly in next-generation process-based modeling approaches.

Post‐Fire Sediment Yield From a Central California Watershed: Field Measurements and Validation of the WEPP Model

AbstractIn a warming climate, an intensifying fire regime and higher likelihood of extreme rain are expected to increase watershed sediment yield in many regions. Understanding regional variability in landscape response to fire and post‐fire rainfall is essential for managing water resources and infrastructure. We measured sediment yield resulting from sequential wildfire and extreme rain and flooding in the upper Carmel River watershed (116 km2), on the central California coast, USA, using changes in sediment volume mapped in a reservoir. We determined that the sediment yield after fire and post‐fire flooding was 854–1,100 t/km2/yr, a factor of 3.5–4.6 greater than the long‐term yield from this watershed and more than an order of magnitude greater than during severe drought conditions. In this first large‐scale field validation test of the WEPPcloud/wepppy framework for the Water Erosion Prediction Project (WEPP) model on a burned landscape, WEPP predicted 81%–106% of the measured sediment yield. These findings will facilitate assessing and predicting future fire effects in steep watersheds with a Mediterranean climate and indicate that the increasingly widespread use of WEPP is appropriate for evaluating post‐fire hillslope erosion even across 100‐km2 scales under conditions without debris flows.

QGeoWEPP: An open-source geospatial interface to enable high-resolution watershed-based soil erosion assessment

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.

Soil erodibility by simulated rainfall in Latosols

Determining a soil's resistance to disaggregation and particle transport is a complex factor that depends on the interaction of multiple attributes. Therefore, this study aimed to determine the indirect and direct erodibility of Latosols in the suborders Red, Yellow and Red-Yellow in the state of Alagoas. The soils were identified through the modal profile of the Agroecological Zoning of the State of Alagoas and through surveys of own classification of companies in the sugar and alcohol sector that have identification of areas of occurrence. They were submitted to chemical and physical analysis, by direct methods (aggregate stability and erodibility determination) and indirect (simulated rain) through mathematical models. The soil erodibility factor in interfurrows presented values that varied from 6.01 x 10-6 Kg s-1 m-4 for Yellow Latosol, to 16.65 x 10-6 Kg s-1 m-4 for Red-Yellow Latosol. This variation was also significant within the suborders, with more homogeneous values observed in the Red Latosols suborder. Thus, it is concluded that for the soil erodibility factor for Latosols, it is recommended to use the simulated rainfall methodology, in field or laboratory conditions through the Water Erosion Prediction Project model.

Vegetation pattern and topography determine erosion characteristics in a semi‐arid sandstone hillslope‐gully system

AbstractThe hillslope‐gully system serves as the primary contributor to both runoff and sediment yield. The WEPP (Water Erosion Prediction Project) model is often applied to investigate erosion characteristics at hillslope scale, demonstrating a high level of accuracy in simulating water erosion. In this study, according to in situ field monitoring (2014–2020) at a Pisha sandstone hillslope on the Loess Plateau, China, a total of 50 rainfall events’ data were used as climatic data to calibrate the soil parameters, and 11 different vegetation patterns and four slope gradients of hillslope‐gully systems were installed as inputs for the management and slope data, respectively. In systems A, B, C and D, the hillslope gradients were defined as 5°, 8°, 10° and 12° and the gully gradients as 15°, 20°, 25° and 30°, respectively. The results showed that the steeper the slope, the more severe the erosion. However, there was a critical value for the effect of slope on runoff. When the slope exceeded 8° and the gully exceeded 20°, the runoff no longer increased further and even decreased. The reduction in runoff in hillslope‐gully systems was in the following order (in mm): system D (3.4 ± 0.14) > system C (3.4 ± 0.14) > system B (3.39 ± 0.14) > system A (3.12 ± 0.13). Increasing vegetation cover could reduce erosion. Differences in runoff between vegetation patterns were not significant (p > 0.05) and ranged from 8% to 26%. However, there were significant differences in the sediment yield reduction benefits of different vegetation patterns (p < 0.05), ranging from 17% to 66%. It was observed that vegetation located in the lower slope produced a more pronounced effect in mitigating sediment when the degree of cover was the same. We conclude that implementing watershed management strategies based on the vegetation and topographic attributes of hillslope‐gully systems within the Loess Plateau, especially on Pisha sandstone hillslopes, serves as the fundamental approach to achieving sustainable watershed management.

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.

Corrigendum to “Estimating WEPP Cropland Erodibility Values from Soil Properties”

Highlights Interrill erodibility Ki values presented in Elliot and Flanagan (2023) were incorrect, and correct values are given. Interrill erodibility can be estimated from a soil’s sand, very fine sand, and clay contents. Abstract. In Elliot and Flanagan (2023), the interrill and rill soil erodibility of 36 cropland soils was reported, along with correlations among soil erodibility and other soil properties, and equations to estimate erodibility from readily measured soil properties. Early versions of the Water Erosion Prediction Project (WEPP) model had linked interrill detachment rate to the square of the rainfall intensity and an interrill soil erodibility constant Ki1. By the time the WEPP model was released for general use in 1995, the developers had changed the interrill detachment rate to be a function of the product of rainfall intensity and runoff and a different interrill erodibility constant, Ki2. The interrill erodibilities (Ki2) with this altered relationship were not the same as Ki1 values developed to support earlier releases of the WEPP model. The authors, when reviewing some of the past literature supporting Elliot and Flanagan (2023), had mistakenly reported Ki2 values when the numbers reported were in fact Ki1 values. A closer examination of the entire data set and the identification of a published source for the correct Ki2 values confirmed this mistake. This corrigendum reports the corrected Ki2 values, the correlation of those revised values with other soil properties, and confirmation of a 1995 regression equation relating Ki2 to three readily measured soil properties: sand content, very fine sand content, and clay content. The coefficient of determination for the 1995 regression equation was 0.80. We recommend that all references to Ki2 in Elliot and Flanagan (2023) be changed to Ki1 except the discussion about the findings of Mirzaee and Ghorbani-Dashtaki (2021), discussion about Ki2 in Alberts et al. (1995), and equations 2 and A16. A marked up copy of Elliot and Flanagan (2023) showing these changes can be downloaded from https://www.fs.usda.gov/rm/pubs_journals/2023/rmrs_2023_elliot_w001_corr.pdf. Keywords: Cropland Soils, Interrill Erodibility, Water Erosion Prediction Project.

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.