Prediction Project Model Research Articles

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.

Stationary wave biases and their effect on upward troposphere– stratosphere coupling in sub-seasonal prediction models

Abstract. The simulated Northern Hemisphere winter stationary wave (SW) field is investigated in 11 Subseasonal-to-Seasonal (S2S) prediction project models. It is shown that while most models considered can well simulate the stationary wavenumbers 1 and 2 during the first 2 weeks of integration, they diverge from observations following week 3. Those models with a poor resolution in the stratosphere struggle to simulate the waves, in both the troposphere and the stratosphere, even during the first 2 weeks. Focusing on the tropospheric regions where SWs peak in amplitude reveals that the models generally do a better job in simulating the northwestern Pacific stationary trough, while certain models struggle to simulate the stationary ridges in both western North America and the North Atlantic. In addition, a strong relationship is found between regional biases in the stationary height field and model errors in simulated upward propagation of planetary waves into the stratosphere. In the stratosphere, biases are mostly in wave 2 in those models with high stratospheric resolution, whereas in those models with low resolution in the stratosphere, a wave 1 bias is evident, which leads to a strong bias in the stratospheric mean zonal circulation due to the predominance of wave 1 there. Finally, biases in both amplitude and location of mean tropical convection and the subsequent subtropical downwelling are identified as possible contributors to biases in the regional SW field in the troposphere.

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.

WEPPcloud: An online watershed-scale hydrologic modeling tool. Part I. Model description

We developed a new online interface for the Water Erosion Prediction Project (WEPP) model (WEPPcloud) with a framework that allows the incorporation and development of several other models and applications to make hydrologic models more accessible to land managers and facilitate the decision-making process. All inputs to WEPP, such as topography, soils, land use, and weather, are automatically created from publicly available online international databases and converted into input formats readable by the model. The WEPPcloud interface can be applied to forested, cropland, and rangeland conditions, but it is specialized for undisturbed forest conditions, post-wildfire, and pre- and post-wildfire management scenarios such as forest thinning, prescribed fire, or post-wildfire mulching. Users only need a computer or device with a web browser and an internet connection to perform advanced hydrologic simulations. All the model runs are stored remotely on WEPPcloud, which can be accessed by the users at any given time. This modeling tool is presented in two parts: Part I: Model description and parameterization, and Part II: Model performance assessment and applications to forest management and wildfires.

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).

Modeling surface runoff and soil loss response to climate change under GCM ensembles and multiple cropping and tillage systems in Oklahoma

To develop effective conservation practices to respond to future climatic challenges, the effects of various cropping and tillage systems on surface runoff and soil loss need to be evaluated under extensive geographical conditions. This study used a total of 100 climate scenarios generated from 25 downscaled General Circulation Model (GCM) projections under two Representative Concentration Pathways (RCP4.5 and 8.5) during 2021–2050 and 2051–2080. Those 100 future scenarios were combined with 29 cropping and tillage systems to simulate surface runoff, soil erosion, and crop production response to climate change using the Water Erosion Prediction Project (WEPP) model. The results showed that average annual precipitation in central Oklahoma was projected to significantly decrease by 4–6% (p < 0.05) during the two time periods for both RCP scenarios. Mean annual temperatures were projected to significantly increase (p < 0.01) by 1.74 ℃ for RCP4.5 and 1.99 ℃ for RCP8.5 during 2021–2050, and 2.65 ℃ for RCP4.5 and 3.90 ℃ for RCP8.5 during 2051–2080. Annual runoff and soil loss averaged over the two RCPs and all crop types was projected to decrease by approximately 1% and 3%, respectively. Except for cotton, crop yields were predicted to decrease by 10.3%–18.3% during 2021–2080. Simulated annual runoff depth and soil loss separately followed the order of reduced tillage (RT) > delayed tillage (DT) > no-till (NT) > conventional tillage (CT) and RT > CT > DT > NT under future climate scenarios, respectively. If economically feasible, no-till and the crop-alfalfa rotation were the most effective soil conservation method on farmlands to combat projected future erosion due to changing precipitation and temperatures.

Spatial and agronomic assessment of water erosion on inland Pacific Northwest cereal grain cropland

The inland Pacific Northwest (PNW) is characterized by high erosion rates attributed to hilly topography, highly erodible silt loam soils, wet winter seasons with frequent freeze-thaw events, and widespread use of conventional tillage practices. Historically, annual water erosion from cropland in the region’s Palouse River basin averaged 20.6 t ha^-1, and more recent rates are 10, 13, and 11 t ha^-1 for the low (&lt;380 mm y^-1), intermediate (380 to 460 mm y^-1), and high (&gt;460 mm y^-1) precipitation zones. Identifying source areas for targeted, effective management requires understanding the factors affecting water erosion, especially how tillage practices and crop rotation interact in various topographic, soil, and climatic settings. The objectives of this study were to (1) understand how hillslope hydrological and water erosion processes are influenced by key environmental factors (soil, climate, and topography) and management practices (tillage and crop rotation), and (2) assess the spatial distribution of soil erosion at the county level and by precipitation zone over the last 30 years. We compiled various combinations of soil, climate, topography, tillage, and crop rotation, and simulated these combinations county by county with the Water Erosion Prediction Project (WEPP) model. Simulated average annual erosion rates were lowest in the low-precipitation zone and highest in the intermediate-precipitation zone, exceeding the USDA Natural Resources Conservation Service tolerable limit (11 t ha^-1) in many cases. Temporally, high precipitation events and fallow periods in the rotation greatly increase erosion. Average annual erosion rates in Whitman County are 13.6, 19.0, and 15.4 t ha^-1 in the three precipitation zones: low (&lt;380 mm y^-1), intermediate (380 to 460 mm y^-1), and high (&gt;460 mm y^-1), respectively. The intermediate-precipitation zone produced a total annual erosion of 4.2 × 10⁶ t, despite having the smallest area. Columbia County has the highest erosion rate with 23.7 t ha^-1 y^-1. Geospatial visualizations of the simulation results reveal critical source areas (“hotspots”) where estimated erosion rates are more than five times the average rates, providing crucial information for, and advancing our understanding of, targeting management and increasing efficiency of conservation practices.

Water quality and forest restoration in the Lake Tahoe basin: impacts of future management options

Land managers in the Lake Tahoe basin are considering increasing the use of prescribed fire and forest thinning to restore conditions that will be more resilient to wildfires. However, such restorative treatments also constitute disturbances that could increase sediment and nutrient loads. We examined whether the water-quality impacts from future treatments are likely to be lower compared to the potential impacts from future wildfires under various climate change scenarios. We applied an online interface for the Water Erosion Prediction Project (WEPP) model in combination with a landscape change model (LANDIS-II) to evaluate the effects of different combinations of thinning and prescribed burning on fine sediment (< 2 mm), very fine sediment (< 16 µm), and phosphorus over time. First, we generated results based on historic weather data for soil disturbance conditions, including: an undisturbed baseline, a uniform thinning treatment; a uniform prescribed fire treatment; and uniform low, moderate, and high wildfire burn severity. Residual ground cover declined in that order, and expected loads of sediment and phosphorus increased. We then combined the estimated loads from hillslopes with projected management-disturbance regimes across each decade of the next century. We found that expected sediment and phosphorus loads were lower under the scenario that emphasized thinning, whereas scenarios that increased prescribed burning resulted in loads that were comparable to scenarios that involved less treatment. These results reflect the finding from the WEPP analysis that prescribed burning is expected to reduce ground cover more than is thinning. Our analysis supports efforts to increase fuel reduction treatments to mitigate future wildfires, but it also suggests that preventative treatments may not avoid a long-term decline in water quality as wildfires increase with climate change.

Modeling soil erodibility and critical shear stress parameters for soil loss estimation

The rate of soil erosion from agricultural fields is driven by climate erosivity and by soil erodibility or resistance, commonly represented through the interrill (Ki) and rill erodibility (Kr), and critical shear stress (τc) parameters. These parameters are affected by factors showing high variability in time and space, such as soil properties, land use, and management practices. Estimating the site-specific time-varying values for Ki, Kr, and τc can require laborious field or laboratory experiments and detailed datasets. The objective of this research was to develop a non-linear regression model for estimating temporal adjustments for Ki, Kr, and τc considering different types of crops and management practices. One thousand sampling sites were randomly selected across the Kaskaskia watershed in Illinois, and the needed parameters to develop the regression models were extracted from the two-year simulation results of the Water Erosion Prediction Project (WEPP) model on a daily basis. The predicted values of the regression models showed good agreements with the sample data, with the coefficient of determination (r2) ranging from 0.62 to 0.98, capturing the spatio-temporal variations of the three variables under different crops and management practices. In addition, daily soil loss estimations using the predicted adjustments showed good agreements with the WEPP simulations, with r2 ranged from 0.98 to 0.99, confirming their possible use in soil erosion models. This is especially useful as the regression models require only a few explanatory variables, which are available at high resolution across the United States. Therefore, the models will facilitate estimating spatio-temporal variations of interrill and rill erodibility, and critical shear stress and thus a new platform of large-scale soil erosion models can be developed using readily available environmental datasets.

Evaluation of Costs and Efficiencies of Urban Low Impact Development (LID) Practices on Stormwater Runoff and Soil Erosion in an Urban Watershed Using the Water Erosion Prediction Project (WEPP) Model

Storm events and soil erosion can adversely impact flood control, soil conservation, water quality, the recreation economy, and ecosystem biodiversity in urban systems. Urban Low Impact Development practices (LIDs) can manage stormwater runoff, control soil losses, and improve water quality. The Water Erosion Prediction Project (WEPP) model has been widely applied to assess the responses of hydrology and soil losses to conservation practices in agricultural and forested areas. This research study is the first to calibrate the WEPP model to simulate streamflow discharge in the Brentwood watershed in Austin, Texas and apply the calibrated WEPP model to assess the impacts of LIDs. The costs and impacts of various LID scenarios on annual water balance, and monthly average, and daily runoff volumes, and sediment losses at hillslopes and at the watershed outlet were quantified and compared. The LID scenarios identified that native planting in Critically Eroding Areas (CEAs), native planting in all suitable areas, native planting in CEAs with detention ponds, and native planting in all suitable areas with detention ponds could reduce the predicted average annual stormwater runoff by 20–24% and sediment losses by 86–94% at the watershed outlet, and reduce the average annual soil loss rates on hillslope profiles in sub-watersheds by 86–87% with the lowest costs (USD 2991/yr–USD 5257/yr). Watershed/field characteristics, locations, areas, costs, and the effectiveness of the LID practices were essential in choosing the LID scenarios. These research results can help guide decision-making on the selection and implementation of the most economical and suitable LID practices to strengthen the climate resilience and environmental sustainability of urban systems.

Improving and calibrating channel erosion simulation in the Water Erosion Prediction Project (WEPP) model

The Water Erosion Prediction Project (WEPP) model has been widely used to assess the impacts of management practices and climate change on runoff and soil loss at both hillslope and watershed scales. However, the representation of channel erosion processes in WEPP has not been changed significantly since it was released. The current (WEPP v2012.8) and previous WEPP versions assume that channel input erodibility parameters are constant through time, which may lead to erroneous channel detachment predictions, especially for cropland with substantial tillage operations. In this research, the temporally constant values of channel erodibility and critical shear stress were replaced by daily updated values, using the same temporal erodibility and critical shear stress adjustments that are applied in hillslope profile simulations for rill detachment. Observed watershed-scale runoff and soil erosion data from six agricultural watersheds were used to calibrate and compare the WEPP model performance in simulating channel runoff volumes and soil losses before and after the modification. The research showed both WEPP v2012.8 and the modified WEPP model (WEPP_CE) could satisfactorily simulate event-based hydrology and soil erosion at the watershed outlets after calibration. The WEPP_CE model with temporally varying channel erodibility and critical shear stress values demonstrated improved representation of the physical processes in channel soil detachment. Continued improvement in the representation of channel erosion processes in WEPP and other process-based models is needed. The improved WEPP model can be used to evaluate the effectiveness of soil conservation practices on hydrology and erosion in further research.

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.

Simulation of wellbore erosion and sand transport in long horizontal wells producing gas at high velocities

Horizontal wells play a crucial role in improving the recovery of hydrocarbons from thin reservoirs. In weakly consolidated formations, these wells may encounter sand production and this may lead to several problems including wellbore instability, production time loss, corrosion and plugging of downhole and surface facilities. Sand production in wellbores can be linked to two physical phenomena. The first is stress concentration along the wellbore causing mechanical instability and localized failure of the rock. The second is related to hydro-mechanical forces that cause internal and surface erosion, triggering the release of particles from rock surface, by the action of drag forces of produced matter. In open hole completions, high-velocity gas flow can trigger the release of particles from rock surface.We present a reservoir-wellbore flow model to simulate high-velocity gas flow in porous media and in open-hole horizontal wells. Since gas wells are associated with high-velocity flows, this study is focused on dry gas production from long open-hole wells, where large sections of wellbore wall are exposed to the stresses caused by the flowing stream of gas. The Forchheimer equation is coupled with conservation of mass to solve for gas flow in the porous media while the Bernoulli's equation is coupled with mass conservation to solve for gas flow in the horizontal wellbore. Computed wellbore velocities are then used to calculate sand erosion using the Water Erosion Prediction Project (WEPP) model. Subsequently, an advection equation is used to model the transport of the eroded sand particles in the wellbore. An example is presented to study how wellbore erosion affects the flow of gas and pressure drop in the horizontal well. The results indicate that the erosion due to high-velocity gas flow in open-hole horizontal wells affects the gas production rate as well as the well flowing pressure.

Temporal Simulation of Sediment Yield Using WEPP Model in Dal Catchment of Temperate Region of Kashmir Valley, India: Case Study

Soil erosion by water is a serious and continuing environmental problem. In the present study the Water Erosion Prediction Project (WEPP) model was used in the Dal catchment to simulate sediment yield. The study was conducted with the objective of calibrating and validating WEPP at the plot scale to examine its suitability for conservation planning. The WEPP model was calibrated using modified input parameters; further, the results were validated using a different data set. The soil erodibility (Kd) and critical shear stress (τc) values vary from 1.70–2.7 and 0.27–0.76 Pa, respectively, for the study area. The average annual sediment yield (hillslope 1 and hillslope 2) was 6.759 t ha−1 as against the measured value of 5.623 t ha−1. The modeled values of sediment yield showed a close agreement with field observed values. The model also produced temporal variations of sediment yield on hillslope areas. The correlation coefficients were found to be 0.93 and 0.945, RMSE were 0.065 and 0.06 t ha−1, and Nash-Sutcliffe efficiency indexes were 0.84 and 0.85 for the validation and calibration periods, respectively. The coefficient of determination (R2) values were found to be 0.89 and 0.90 during calibration and validation of the model, respectively. Results indicated that the WEPP model simulated sediment yield from steep slope conditions and in forest conditions as well. The WEPP model was found to be an effective tool for simulating hydrological and soil erosion processes in watersheds having scarce data.

Sediment fate and transport: Influence of sediment source and rainfall

The capability of hydrologic models to spatially simulate the changes in hydrologic processes, like precipitation, is an important consideration in capturing the impacts of these processes on sediment prediction across the domain. Radar-derived precipitation (RDP) provides an enhanced detail of rainfall characteristics in time and space compared to estimates from rain-gauge precipitation (RGP) commonly used in hydrologic modeling. However, the impacts of these datasets on sediment fate and transport depend on how sediment sources were conceptualized in the model. This paper developed a modeling framework to simulate sediment transport from upland to the stream and to the outlet of the watershed based on a gridded conceptualization and to examine the impacts of RGP and RDP with different types of sediment sources on sediment prediction. The Water Erosion Prediction Project (WEPP) model was used to estimate daily sediment sources in a semi-distributed and fully distributed manner using the hydrologic model, MIKE SHE and MIKE 11. Model comparison was performed in a watershed in Illinois characterized by a dominant agricultural landscape. The results indicated that the use of RDP only ensured better model performance for sediment yield with the fully distributed sediment source. That is, combining both the ability of the RDP to capture the spatial variability of rainfall across the watershed and assessing sediment production at higher resolution improved the accuracy of predictions in sediment yield while decreasing uncertainties associated with sediment simulations. Advancing modeling capabilities will require the development of new modeling platforms that aim to seamlessly integrate large-scale distributed simulations and environmental input data at finer spatial resolutions.

An inter-comparison performance assessment of a Brazilian global sub-seasonal prediction model against four sub-seasonal to seasonal (S2S) prediction project models

This paper presents an inter-comparison performance assessment of the newly developed Centre for Weather Forecast and Climate Studies (CPTEC) model (the Brazilian Atmospheric Model version 1.2, BAM-1.2) against four sub-seasonal to seasonal (S2S) prediction project models from: Japan Meteorological Agency (JMA), Environmental and Climate Change Canada (ECCC), European Centre for Medium-range Weather Forecasts (ECMWF) and Australian Bureau of Meteorology (BoM). The inter-comparison was performed using hindcasts of weekly precipitation anomalies and the daily evolution of Madden–Julian Oscillation (MJO) for 12 extended austral summers (November–March, 1999/2000–2010/2011), leading to a verification sample of 120 hindcasts. The deterministic assessment of the prediction of precipitation anomalies revealed ECMWF as the model presenting the highest (smallest) correlation (root mean squared error, RMSE) values among all examined models. JMA ranked as the second best performing model, followed by ECCC, CPTEC and BoM. The probabilistic assessment for the event “positive precipitation anomaly” revealed that ECMWF presented better discrimination, reliability and resolution when compared to CPTEC and BoM. However, these three models produced overconfident probabilistic predictions. For MJO predictions, CPTEC crosses the 0.5 bivariate correlation threshold at around 19 days when using the mean of 4 ensemble members, presenting similar performance to BoM, JMA and ECCC. Overall, CPTEC proved to be competitive compared to the S2S models investigated, but with respect to ECMWF there is scope to improve the prediction system, likely by a combination of including coupling to an interactive ocean, improving resolution and model parameterization schemes, and better methods for ensemble generation.

Temporally downscaling precipitation intensity factors for Köppen climate regions in the United States

Model inputs for prediction of runoff and soil erosion commonly require precipitation intensity information. Intensity is often estimated if precipitation data with high temporal resolution are unavailable. However, when intensity is time-averaged for fixed measurement intervals, estimates become increasingly underestimated with longer intervals due to the assumption that event durations begin and end at specified measurement intervals. In this study, adjustment factors were determined for downscaling the temporal resolution of intensity values derived from selected resolutions within the range of 10 to 1,440 min for Köppen-Geiger climate regions in the United States. In this case, monthly mean maximum 30 min intensity (MX.5P) was downscaled, which is a parameter used to generate stochastic meteorological inputs for models that include the Rangeland Hydrology and Erosion Model (RHEM) and the Water Erosion Prediction Project model (WEPP). The adjustment factors were given by regressions of reference MX.5P values derived from data with 5 min resolution against MX.5P values derived from data with lower temporal resolutions (≥10 min). In addition to using a slope coefficient for intensity in the regression equation, permutations of the equation included use of an elevation coefficient and constants, resulting in four total permutations. For the 143 stations and 17 climate regions analyzed, the four regression equations had roughly equal performance, and all gave statistically significant results. Regressions for adjusting hourly data using only an intensity coefficient in the equation had standard error of the estimate ranging from 1.01 to 2.96 mm h^–1 with an average of 2.04 mm h^–1. When downscaling daily values, the error range was 2.50 to 10.20 mm h^–1 with an average of 5.63 mm h^–1. Average time-to-peak intensity probability distributions for each climate region were also determined. Finally, a stochastic weather generator, CLIGEN, was used to test the effectiveness of applying the climate-based factors as an alternative to using subhourly data.

Performances of the WEPP and WaNuLCAS models on soil erosion simulation in a tropical hillslope, Thailand.

Effective soil erosion prediction models and proper conservation practices are important tools to mitigate soil erosion in hillside agricultural areas. The Water Nutrient and Light Capture in Agroforestry Systems (WaNuLCAS) and Water Erosion Prediction Project (WEPP) models are capable tools in soil erosion simulation in the conventional and conservation cropping systems in hillslopes. We calibrated both the models in maize monocropping and simultaneously validated them in maize-chili intercropping with Leucaena hedgerow for nine rainfall events in 2010, with the aim to evaluate their performances in runoff and sediment prediction on a skeleton soil in a hillslope, Western Thailand. The results showed that the calibrated WaNuLCAS model poorly predicts runoff prediction in the validation. In contrast, the calibrated WEPP model had a better performance in runoff prediction in the validation. For sediment prediction, the calibrated WaNuLCAS model predicted sediment yield better than the calibrated WEPP model in the validation because the WEPP model shows more variability of the sediment yield in the calibration (5.84 kg m–2) than the WaNuLCAS (5.18 kg m–2). Thus, the WEPP model was more suitable for runoff prediction than sediment prediction in the monocropping system, whereas the WaNuLCAS model was better suited for sediment yield prediction than runoff prediction, especially in complex intercropping systems.

Improvement of the Water Erosion Prediction Project (WEPP) model for quantifying field scale subsurface drainage discharge

In the poorly drained regions of the world, subsurface drainage systems are required to remove excess water for crop growth. Plastic drains alter a field’s hydrology by lowering the water table, reducing surface ponding, and reducing surface runoff. One significant concern with the use of subsurface drainage systems is adverse environmental effects because of the modification of the soil water dynamics. Some effects include the reduction of ecological services since wetlands change to croplands, water quality concerns, particularly sediment, nitrogen, and phosphorus losses in agricultural subsurface discharge water, as well as changes in the volume and timing of off-site discharges. Hydrological simulation models predict surface and artificial subsurface flow at different scales. Often in these models, Hooghoudt-based expressions are adapted in their internal algorithms. In this study, the Water Erosion Prediction Project (WEPP) model, developed by the United States Department of Agriculture - Agricultural Research Service (USDA-ARS) for soil and water conservation planning activities, was tested and improved to simulate surface and subsurface discharges. The modified WEPP model was tested and validated on an extensive dataset collected at four experimental sites managed by USDA-ARS within the Lake Erie Watershed. Predicted drainage discharges show Nash-Sutcliffe Efficiency (NSE) values ranging from 0.50 to 0.70, and Percent Bias ranging from −30% to +15% at daily and monthly resolutions. Evidence suggests that the WEPP model can be used to produce reliable estimates of subsurface flow with minimum calibration. Future work includes the extension of the model for quantifying subsurface drainage under controlled water table and watershed-scale simulations.

Identification of priority areas for sediment yield reduction by using a GeoWEPP-based prioritization approach

Sedimentation has been causing both onsite and offsite damages around the world. In this context, watershed prioritization allows decision-makers to implement management strategies for reducing sediment yield. So, this study aimed to determine the subwatersheds that produce the maximum amount of sediment for reducing sedimentation in a watershed. We used GeoWEPP, Geo-spatial interface for Water Erosion Prediction Project (WEPP) model, to predict sediment yield in the watershed. In order to run GeoWEPP easily and reliably, the watershed was divided into 85 subwatersheds. Sediment yield was found to be 5.13 tons ha− year−for the whole watershed. In order to produce a sediment risk map in ArcGIS, values from 0 to 1 were assigned to the sediment yield values of each subwatershed by using min-max normalization method. The obtained values were divided into 5 risk classes. According to this map, 42% of the study area was subject to very low sediment risk, while 28%, 12%, 7%, and 11% of it were subject to low, moderate, high, and very high sediment risk. When the sediment yield amount of the risk classes was investigated, very high sediment risk class accounted for 54% of total sediment yield in the watershed. These results revealed that a small part of the watershed contributed a disproportionate amount of the total sediment yield. Consequently, the GeoWEPP-based prioritization approach can help decision-makers design and implement effective soil and water conservation practices to reduce sediment yield in the regions where human and financial resources are limited.