Response of Soil Detachment Rate to Sediment Load and Model Examination: A Key Process Simulation of Rill Erosion on Steep Loessial Hillslopes.

The rate of soil detachment by water flow indicates soil erosion intensity directly. The exact relation between soil detachment rate and actual sediment load in water flow, however, is still unclear, and the existing relationships have not been adequately tested. The aims of the present study were to investigate the response of soil detachment rate to sediment load using rill flume data with loessial soil and to quantitatively examine the soil detachment equations in the WEPP and EUROSEM soil erosion models. Six slopes were combined with seven flow discharges to measure detachment rates under seven sediment loads using a rill flume with a soil-feeding hopper. Significant differences were found among the soil detachment rate by different sediment loads in low sediment load levels, but an insensitive response of soil detachment rate to sediment load was found under high levels of sediment load. The soil detachment rate was proved to be negatively linearly correlated with sediment load. The rill detachment equation in the WEPP model predicted the soil detachment rate by rill flow very well under our experiment condition. The soil detachment equation in the EUROSEM model underestimated the detachment rates under controlled conditions, but removing the setting velocity from the equation greatly improved prediction. Further experiments that could reflect the dynamic convective detachment and deposition process need to be conducted to compare with the present examination results and to further understand rill erosion processes.

Spatial-temporal dynamic impact of changes in rainfall erosivity and vegetation coverage on soil erosion in the Eastern Mediterranean.

In Syria, soil erosion (SoEr) by water is one of the major challenges for sustainability. Thus, the main goals of this research were to evaluate the spatial changes of SoEr between 2000 and 2018 in the whole coastal basin (CB) of Syria and to provide a soil water erosion risk map for the study area. For this purpose, monthly rainfall data, the SoilGrids dataset, satellite image derived NDVI layers, and Digital Elevation Model (DEM) were collected. Through the integration of these layers into the Revised Universal Soil Loss Equation (RUSLE), under a Geographic Information System (GIS), soil loss was assessed. Also, the contribution of land cover changes and R factor on SoEr were evaluated. The outcomes of this assessment illustrated that the R factor ranged from 800 to 2600 MJ mm ha-1 h-1 yr-1, while the soil erodibility factor (K factor) ranged from 0.048 to 0.035 ton ha MJ-1 mm-1. The C factor (vegetation coverage) values ranged between 0.07 and 1 with a spatial average value of 0.44 for the 2000-2009 period and 0.39 for the 2010-2018 interval. The output of RUSLE revealed that average annual SoEr was of 21.35 ton ha-1 y-1 (± 38) for 2000-2009 and 22.47 ton ha-1 y-1(± 41.8) for 2010-2018. Interestingly, the increased SoEr caused by the R factor was dominant (34.65%), followed by changes in both C factor and R factor (13.34%). However, decrease of SoEr rates is due to the increase of the C factor accounting for 36.82% of the CB. The outcome of this research can provide constructive spatial insights for rehabilitation plans for the post-war phase of Syria.

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.

WEPPcloud hydrologic and erosion simulation datasets from 28 watersheds in US Pacific Northwest and calibrating model parameters for undisturbed and disturbed forest management conditions.

The WEPPcloud interface is a new online decision-support tool for the Water Erosion Prediction Project (WEPP) model that facilitates data preparation and model runs, and summarizes model outputs into tables and maps that are easily interpretable by users. The interface can be used by land and water managers in United States, Europe, and Australia interested in simulating streamflow, sediment and pollutant loads from both undisturbed and disturbed (e.g. post-wildfire or post-treatment such as thinning or prescribed fires) forested watersheds. This article contains full hydrologic model runs for 28 forested watersheds in the U.S. Pacific Northwest with the WEPPcloud online interface. It also includes links to repositories with the individual model runs, a table containing default model parameters for disturbed conditions, and figures with model outputs as compared to observed data. The data in the repositories include all the raw data input and output from the model as well as the processed data, which can be accessed through tables and shapefiles to provide additional insights into the model outputs. Lastly, the article describes how the data are organized and the content of each folder containing the data. These model runs are useful for anyone interested in modeling forested watersheds with the WEPPcloud interface.

Runoff and soil erosion in the integrated farming systems based on micro-watersheds under projected climate change scenarios and adaptation strategies in the eastern Himalayan mountain ecosystem (India).

Land degradation caused by soil erosion (SE) in forests converted into cropland under climate change, particularly with increased rainfall intensity, is of great concern to the agricultural sustainability of the tropical mountain ecosystem. We evaluated the response of six hilly micro-watersheds (HMW) under different Integrated Farming Systems (IFSs) to SE in multi-model climate change scenarios using the Water Erosion Prediction Project (WEPP) model. The IFSs were forestry (HMW1), abandoned shifting cultivation (HMW2), livestock with fodder crops (HMW3), agroforestry (HMW4), agri-horti-silvi-pastoral (HMW5), and horticulture (HMW6) established on a hilly slope (32.0-53.2%) of the eastern Himalayas (Meghalaya, India). The WEPP model was calibrated and validated with measured runoff and soil loss data of 24 years for each of the six IFSs. The projected annual SE (average) for all HMWs increased in all RCPs. The IFS based on shifting cultivation (HMW2) was the most vulnerable, with the highest percentage increase in SE (46-235%) compared to the baseline years (1976-2005) under RCP 8.5. The cultivated IFSs (HMW3 to HMW6) had 47.8-57.0% less runoff and 39.2-74.6% less soil loss than HMW2 under RCP 8.5. Of these, HMW6 followed by HMW4 and HMW5 were the most effective at minimizing soil loss. Simulation results showed a reduction in soil loss through adaptive strategies such as mulching with broom grasses, stones, field beans, and the introduction of subsurface drainage. Adoption of IFS based on horticulture and agroforestry with bio-mulching on steep slopes is an effective measure to control soil erosion in the eastern Himalaya (India).

Assessing the WEPP model performance for predicting daily runoff in three terrestrial ecosystems in western Syria.

Soil erosion is one of the main threats facing the agriculture and natural resources sector all over the world, and the same is true for Syria. Several empirical and physically based tools have been proposed to assess erosion induced soil losses and runoff driving the processes, from plot to regional spatial scales. The main goal of this research is to evaluate the performance of the Water Erosion Prediction Project (WEPP) model in predicting runoff in comparison with field experiments in the Al-Sabahia region of Western Syria in three ecosystems: agricultural lands (AG), burned forest (BF) and forest (FO). To achieve this, field experimental plots (2∗1.65∗0.5 m) were prepared to obtain runoff observation data between September 2012 and December 2013. In addition, the input data (atmospheric forcing, soil, slope, land management) were prepared to run the WEPP model to estimate the runoff. The results indicate that the average observed runoffs in the AG, BF and FO were 12.54 ± 1.17, 4.81 ± 0.97 and 1.72 ± 0.16 mm/event, respectively, while the simulated runoffs in the AG, BF and FO were 15.15 ± 0.89, 9.23 ± 1.48 and 2.61 ± 0.47mm/event, respectively. The statistical evaluation of the model's performance showed an unsatisfactory performance of the WEPP model for predicting the run-offs in the study area. This may be caused by the structural flaws in the model, and/or the insufficient site-specific input parameters. So, to achieve good performance and reliable results of the WEPP model, more observation data is required from different ecosystems in Syria. These findings can provide guidance to planners and environmental engineers for proposing environmental protection and water resources management plans in the Coastal Region in Syria.

PEMIP: Post-fire erosion model inter-comparison project.

Land managers often need to predict watershed-scale erosion rates after disturbance or other land cover changes. This study compared commonly used hillslope erosion models to simulate post-fire sediment yields (SY) at both hillslope and watershed scales within the High Park Fire, Colorado, U.S.A. At hillslope scale, simulated SY from four models- RUSLE, AGWA/KINEROS2, WEPP, and a site-specific regression model-were compared to observed SY at 29 hillslopes. At the watershed scale, RUSLE, AGWA/KINEROS2, and WEPP were applied to simulate spatial patterns of SY for two 14-16 km2 watersheds using different scales (0.5-25 ha) of hillslope discretization. Simulated spatial patterns were compared between models and to densities of channel heads across the watersheds. Three additional erosion algorithms were implemented within a land surface model to evaluate effects of parameter uncertainty. At the hillslope scale, SY was only significantly correlated to observed SY for the empirical model, but at the watershed scale, sediment loads were significantly correlated to observed channel head densities for all models. Watershed sediment load increased with the size of the hillslope sub-units due to the nonlinear effects of hillslope length on simulated erosion. SY's were closest in magnitude to expected watershed-scale SY when models were divided into the smallest hillslopes. These findings demonstrate that current erosion models are fairly consistent at identifying areas with low and high erosion potential, but the wide range of predicted SY and poor fit to observed SY highlight the need for better field observations and model calibration to obtain more accurate simulations.

Modeling forest management effects on water and sediment yield from nested, paired watersheds in the interior Pacific Northwest, USA using WEPP.

The Water Erosion Prediction Project (WEPP) model was applied to seven paired, nested watersheds within the Mica Creek Experimental Watershed located in northern Idaho, USA. The goal was to evaluate the ability of WEPP to simulate the direct and cumulative effects of clear-cutting and partial-cutting (50% canopy removal) on water and sediment yield. WEPP was modified to better represent changes in the Leaf Area Index during post-harvest forest vegetative recovery. Good agreement between simulated and observed streamflow was achieved with minimal to no calibration over a 16-year (1992-2007) period. For the seven watersheds and the entire study period, the overall Nash-Sutcliffe Efficiency (NSE), Kling-Gupta efficiency (KGE), and deviation of runoff volume (DV) between observed and simulated daily streamflow ranged 0.58-0.71, 0.67-0.81, and -4% to 9%, respectively. Good agreement between predicted and observed suspended sediment yield was achieved through the calibration of a single channel critical shear stress parameter. For sediment yield, NSE, KGE, and DV ranged 0.62-0.97, 0.43-0.97, and -2% to 2%, respectively, for the calibration period, and 0.61-0.93, 0.42-0.95, and -24% to 13%, respectively, for the period of model performance assessment. Regression analysis of observed- and WEPP-simulated increase in water and sediment yield following clear-cut treatment was similar; however, the WEPP-simulated increase was lower compared to observations particularly from the partial-cut watershed. The variability in the critical shear parameter for different stream channels in the study watersheds was directly related to the observed mean particle size on the stream bed and suggests that applications of the WEPP model in ungauged basins could potentially set the critical shear parameter based on particle size. Overall, the simulated results demonstrate the potential of WEPP as a modeling tool for forestland watershed management, particularly for estimating the effects of forest harvest on hydrograph fluctuations and consequently, stream sediment transport.

Assessment of landuse change impact on runoff and sediment yield of Patiala-Ki-Rao watershed in Shivalik foot-hills of northwest India.

Landuse change significantly alters the hydrologic characteristics of the land surface within a watershed. In the present study, the impact of landuse change (2006-2016) on runoff and sediment yield has been assessed in Patiala-Ki-Rao watershed (5140 ha) located in Shivalik foot-hills, using remote sensing, geographical information system (GIS), and Water Erosion Prediction Project (WEPP) watershed model. The watershed has seven major landuse classes, namely agriculture, built-up, fallow land, forest, grass land, streams, and water bodies. The landuse change analysis indicated that the area under all the landuses decreased except built-up that increased by 372.27 ha (112.04%). Forest is the most affected landuse among all watershed landuses that shrinked by 194.90 ha followed by agriculture (64.57 ha), grass land (50.81 ha), streams (30.42 ha), fallow land (21.86 ha), and water bodies (9.72 ha). Runoff and sediment yield for the landuse of the years 2006 and 2016 were simulated by the WEPP model using two climate scenarios (2006 and 2016). The simulated runoff, sediment yield, and sediment delivery ratio increased by 18.62%, 48.04%, and 32.23% under Climate-2006 and 26.78%, 30.23%, and 16.09% under Climate-2016 due to change in landuse during a period of 10 years. This clearly indicates that landuse change in 10 years has greatly influenced the hydrology of the watershed and requires urgent land allocation policy in place for sustainable development in the area.

Evaluation of the rusle and disturbed wepp erosion models for predicting soil loss in the first year after wildfire in NW Spain.

Severe fire greatly increases soil erosion rates and overland-flow in forest land. Soil erosion prediction models are essential for estimating fire impacts and planning post-fire emergency responses. We evaluated the performance of a) the Revised Universal Soil Loss Equation (RUSLE), modified by inclusion of an alternative equation for the soil erodibility factor, and b) the Disturbed WEPP model, by comparing the soil loss predicted by the models and the soil loss measured in the first year after wildfire in 44 experimental field plots in NW Spain. The Disturbed WEPP has not previously been validated with field data for use in NW Spain; validation studies are also very scarce in other areas. We found that both models underestimated the erosion rates. The accuracy of the RUSLE model was low, even after inclusion of a modified soil erodibility factor accounting for high contents of soil organic matter. We conclude that neither model is suitable for predicting soil erosion in the first year after fire in NW Spain and suggest that soil burn severity should be given greater weighting in post-fire soil erosion modelling.

Land use and climate change impacts on runoff and soil erosion at the hillslope scale in the Brazilian Cerrado.

Land use and climate change can influence runoff and soil erosion, threatening soil and water conservation in the Cerrado biome in Brazil. The adoption of a process-based model was necessary due to the lack of long-term observed data. Our goals were to calibrate the WEPP (Water Erosion Prediction Project) model for different land uses under subtropical conditions in the Cerrado biome; predict runoff and soil erosion for these different land uses; and simulate runoff and soil erosion considering climate change. We performed the model calibration using a 5-year dataset (2012-2016) of observed runoff and soil loss in four different land uses (wooded Cerrado, tilled fallow without plant cover, pasture, and sugarcane) in experimental plots. Selected soil and management parameters were optimized for each land use during the WEPP model calibration with the existing field data. The simulations were conducted using the calibrated WEPP model components with a 100-year climate dataset created with CLIGEN (weather generator) based on regional climate statistics. We obtained downscaled General Circulation Model (GCM) projections, and runoff and soil loss were predicted with WEPP using future climate scenarios for 2030, 2060, and 2090 considering different Representative Concentration Pathways (RCPs). The WEPP model had an acceptable performance for the subtropical conditions. Land use can influence runoff and soil loss rates in a significant way. Potential climate changes, which indicate the increase of rainfall intensities and depths, may increase the variability and rates of runoff and soil erosion. However, projected climate changes did not significantly affect the runoff and soil erosion for the four analyzed land uses at our location. Finally, the runoff behavior was distinct for each land use, but for soil loss we found similarities between pasture and wooded Cerrado, suggesting that the soil may attain a sustainable level when the land management follows conservation principles.