Water Erosion Prediction Project Research Articles

Modeling Soil Erosion With Evolving Rills on Hillslopes

AbstractWhereas current erosion models are successful in quantitative estimates of soil erosion by water flow, modeling the coevolution of geomorphological features, particularly rill network properties and soil erosion on hillslopes, is still a major challenge. In this study, we propose a rill evolution modeling approach and combine it with a rainfall‐runoff and soil erosion model to simulate the feedback loop of hillslope geomorphic development and soil erosion processes. Rill evolution is mainly characterized by three rill network attributes, rill density, orientation angle, and rill width, all modeled with physical equations. The entire rainfall‐runoff‐erosion and rill evolution model is tested against a set of rill network evolution and soil erosion data from an experimental hillslope subjected to successive rainfall events. The simulated spatial and temporal variations of rill network characteristics and soil erosion agree well with the measured data. The results demonstrate that the three rill network characteristics continually alter the partitioning of interrill and rill flows and affect the interrill and rill flow erosivity and soil erosion, which in turn modify the rill geometry and rill network planform. Comparatively, existing approaches such as Water Erosion Prediction Project (WEPP) that ignore the rill evolution processes largely underestimate the hillslope soil erosion when using time independent model parameters. Moreover, a sensitivity analysis indicates that both the rill evolution and soil erosion processes are sensitive to the rill evolution parameters, rainfall intensity, and slope angle. These results can inform the development of general geomorphic evolution and soil erosion models on evolving rilled hillslopes.

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.

Effects of root morphological traits on soil detachment for ten herbaceous species in the Loess Plateau

Plant root systems can greatly reduce soil loss, and their effects on soil erosion differ across species due to their varied root traits. The purpose of this study was to determine the effects of root morphology traits of herbaceous plants on the soil detachment process. Ten herbaceous plants (dominant species) in the Loess Plateau were selected, and 300 undisturbed soil samples (including living roots from the selected herbages) were scoured with flowing water to measure their soil detachment capacities under six levels of shear stress (4.98 to 16.37 Pa). Then, the root traits of each soil sample were measured, and the rill erodibility and critical shear stress were estimated based on the Water Erosion Prediction Project (WEPP) model. The results showed that root morphology traits varied greatly among the ten selected herbages. Accordingly, resulting variations in soil detachment capacity (0.030 to 3.297 kg m−2 s−1), rill erodibility (0.004 to 0.447 s m−1), and critical shear stress (4.73 to 1.13 Pa) were also observed. Plants with fibrous roots were more effective than those with tap roots in reducing soil detachment. Their mean soil detachment capacity and rill erodibility were 93.2% and 93.4% lower, respectively, and their mean critical shear stress was 1.15 times greater than that of the herbaceous plants with tap root systems. Of all the root traits, root surface area density (RSAD) was the primary root trait affecting the soil detachment, and it estimated the soil detachment capacity well (R2 = 0.91, normalized squared error (NSE) = 0.82). Additionally, an equation with few factors (soil aggregate and RSAD) was suggested to simulate the soil detachment capacity when the plant root parameters and soil properties were limited.

WEPP MODEL FOR RILL EROSION ESTIMATION IN A BRAZILIAN SEMIARID WATERSHED

ABSTRACT Soil erosion is a major environmental problem in many parts of the world and represents a serious problem for sustainable agriculture and the environment, with direct and indirect impacts on soil quality and fertility. This study aimed to use the Water Erosion Prediction Project (WEPP) model to estimate rill erosion and determine soil physical and hydraulic properties, which are essential to investigate its performance. To this end, an experiment was carried out in the Exu Creek watershed, in Serra Talhada, semi -arid region of Pernambuco State (Brazil), under increasing flow rates: T1: 5.87 L min-1; T2: 12.10 L min-1; T3: 20.33 L min1; and T4: 27.57 L min-1. Liquid and solid discharges were sampled for determination and characterization of hydraulic parameters in preformed rill flows. Reynolds numbers between 2,019 and 6,929 and Froude numbers below 1 found in this study attest to occurrence of erosive rills. Soil losses due to rill erosion increased as flow rates increased. Rill erodibility was 0.0011 kg N-1 s-1, and critical shear stress (tc) was 1.91 Pa, collapsing rill sidewalls and increasing local uplift, wet perimeter, and rill hydraulic radius.

Modeling rainfall influence to soil sediment yield in corn monocropping systems in Claveria, Southern Philippines through Water Erosion Prediction Project (WEPP)

In this study, the Water Erosion Prediction Project (WEPP) was used to model the soil sediment yield in four monocropping systems in Claveria, Misamis Oriental in Southern Philippines, as influenced by rainfall. The rainfall data were analyzed and inputted into the WEPP model, together with the soil, climate, and other relevant data in Claveria. The sensitivity analysis was performed using four corn monocropping systems (CMS), including no-till (NT), light till (LT), medium till (MT), and heavy till (HT), considering rill cover, effective hydraulic conductivities of the soil, increasing annual rainfall, and rainfall-runoff factors. The WEPP model indicated that soil sediment yield is highly sensitive to the type of tillage practice and the increased rainfall in Claveria. Claveria’s average annual rainfall is over 3000 mm with nine rainy months and three dry months. During the 13 years, the annual rainfall increased by 28%, which is equivalent to 68 mm/year. The average annual erosion rates increased by 114%, 85%, and 54% in LT, MT, and HT CMS, respectively. One management option to keep sediment yields to an acceptable level is to shift from HT or MT systems to NT or LT systems, which maintain high levels of residue cover on the soil.

Predicting soil erosion hazard in Lattakia Governorate (W Syria)

The main objective of this study is to predict soil erosion in the Lattakia Governorate (W Syria) using the Water Erosion Prediction Project model (WEPP) and to compare the result with that of the RUSLE. Field survey and data collection were carried out, and 44 soil samples were analyzed. In addition, all the necessary input files were prepared for use in the WEPP model and RUSLE. Results show that more than of 80% of the locations studied experience slight to moderate erosion (less than 5 t/ha/y), whereas the rest of the locations experience severe soil erosion hazard. Moreover, the volume of runoff estimated by the WEPP model is in the range of 51–321 mm, and the R2 between the simulated soil erosion and the predicted runoff reached 0.68. Interestingly, the R2 between the WEPP model and RUSLE is 0.56, which indicates a good correlation between the two models.

Improved interrill erosion prediction by considering the impact of the near-surface hydraulic gradient

The mechanism of the interrill erosion process is still unclear under complex conditions. Spatio-temporal variations of the near-surface hydraulic gradient are a common occurrence; however, few attempts have been made to characterize the near-surface hydraulic gradient for erosion prediction. Therefore, the objective of this study is to determine the influence of exogenic erosional forces (rainfall, overland flow, and seepage) on interrill erosion processes by considering the impact of the near-surface hydraulic gradient. Five near-surface hydraulic gradients (70 % of field capacity, field capacity, saturation, artesian seepage at 0.20 and 0.40 m of the hydrostatic pressure head) were applied in clay loam soil at two representative slope gradients of 8.7 % and 17.6 % under three rainfall intensities of 30, 60, and 90 mm h−1. The results showed that the near-surface hydraulic gradient was the dominant factor in the interrill erosion process in addition to rainfall intensity (I), runoff (Q), and slope gradient (S). There was a significant improvement in the prediction accuracy of the interrill erosion rate when the factor of near-surface hydraulic gradient was introduced into the interrill erosion prediction equation based on the Water Erosion Prediction Project (WEPP) concept (R2 = 0.92, Nash-Sutcliffe simulation efficiency (NSE) = 0.92). The R2 and NSE values were 22.4 %–210.0 % higher than those of existing empirical equations (main parameters: I, I&S, I&Q, I&S&Q). The correlation matrix results indicated that the flow velocity was a key hydraulic parameter for predicting the interrill erosion rate. The interrill erosion rate was predicted well by a simple power function of the flow velocity (R2 = 0.88, NSE = 0.88), although this relationship lacks clear physical meaning. We also found that the interrill erosion rate increased as a power function with the runoff depth, rainfall intensity, hydrostatic pressure head, and slope gradient (R2 = 0.88, NSE = 0.88). Considering the integrated effect of the exogenic erosional dynamics on interrill erosion, a power function that included the physical description of the hydrodynamic parameters, rainfall intensity, and hydrostatic pressure head was used to predict the interrill erosion rate (R2 ≥ 0.85, NSE ≥ 0.86). The results of this research provide new insights into developing process-based and mechanistic models for interrill erosion processes.

Temporally downscaling a precipitation intensity factor for soil erosion modeling using the NOAA-ASOS weather station network

Precipitation intensity is an important meteorological input for water erosion and runoff applications. A commonly used intensity factor is maximum 30-min intensity (I30), which represents the sustained intensity of a storm. Determining I30 is challenging for two reasons. First, intensity can vary significantly over time, even within very short durations of 5 min or less. Second, the majority of precipitation data sets are limited by their fixed-interval nature, and I30 may not be constant within fixed measurement intervals. When intensity is simply averaged given the accumulation of a measurement interval, the temporal resolution of the precipitation data set biases the result. Therefore, in this study, bias adjustments were determined for a range of selected temporal resolutions and Köppen-Geiger climate regions in the United States. In this case, the intensity factor was monthly mean maximum 30-minute intensity (MX.5P), 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 obtained by using linear regression of reference MX.5P values derived from breakpoint data against MX.5P values aggregated from the breakpoint data to represent lower temporal resolutions. The resulting slope coefficients were used to determine bias adjustment factors. In addition, multivariate machine learning regression was used to obtain more complex correlations involving a host of predictor variables that may each be determined from daily precipitation statistics and the spatial location of each station. In total, 609 stations and 16 climate classifications were represented in the regressions. Linear regressions for climate classifications gave RMSE for values of MX.5P derived from hourly data ranging from 0.98 to 3.46 mm hr−1 with an average of 2.18 mm hr−1. For daily data, the error range was 2.83–8.44 mm hr−1 with an average of 5.61 mm hr−1. The multivariate regression using machine learning algorithms improved regressions for coarser resolutions, reducing error to the 3–4 mm hr−1 range for downscaled daily values.

Long-term, process-based, continuous simulations for a cluster of six smaller, nested rangeland watersheds near Tombstone, AZ (USA): Establishing a baseline for event-based runoff and sediment yields

Accurately predicting long-term, process-based runoff and sediment yields measured at the outlet of even small watersheds can be challenging. The assessments following careful parameter determination enable establishing a baseline for local land management to assess policy implementations and rehabilitation especially under climate or land use/cover changes. Process-based, continuous models have demonstrated their advantage of representing event-based hydrological responses at smaller spatial and temporal scales. In this study, the Geospatial interface for the Water Erosion Prediction Project (WEPP) is validated for a series six, neighboring, nested subwatersheds (101 to 106) at Lucky Hills, Walnut Gulch Experimental Watershed (WGEW), Tombstone, Arizona (USA). The primary objective of this study is to assess short-term parameterization and long-term verification and simulation validation of GeoWEPP based on 55 years of runoff and sediment yields for six subwatersheds. The effective hydraulic conductivity (Keff) parameter is adjusted based on runoff observed in watershed 101 using a research-grade 1 m-Digital Elevation Model (DEM). The performance of runoff simulated generated by an aggregated 5 m-resolution DEM lead to better results in contrast to using the original 1 m- or aggregated 3 m-resolution. Since there are no sediment yield observations for that watershed, the similar sized, neighboring watershed 102 and a publicly available DEM were used to parameterize critical shear. The short-term verification of Keff as well as the long-term verification of Keff and critical shear stress indicate that both parameters generated based on one subwatershed can be used to accurately predict the runoff in all other watersheds in the study area. However, the results have a tendency to slightly over-estimate runoff, and become more significant with the distance from the rainfall and runoff gauges for the watershed that was used for the Keff parameter estimation. For sediment yields, the results indicate that the short-term parameterization of shear stress based on one watershed can potentially lead to significantly different results for neighboring watersheds. The results are the baseline for spatially distributed shear stress and channel erosion parameter validation and impact assessment for future climate and land use changes.

Predicting Soil Erosion Status of the Düz Creek Watershed in Artvin

Aim of study: Main objective of this research was to predict some of the processes (soil loss, runoff and sediment yield) related to soil erosion with the help of WEPP (Water Erosion Prediction Project) model.
 Area of study: The WEPP model was applied to the Düz Creek Watershed (1059 ha in size). It is a sub-watershed flowing into the greater Çoruh River Basin near the district of Borçka, Artvin.
 Material and methods: As required by the WEPP model, four large-data files of soil, climate, slope and plant cover/management were created for the watershed using the data gathered from in-field samplings (soil), laboratory analyses and GIS (Geographical Information Systems) assessments. For easier run and detailed investigation of soil erosion process of the research area, the studied watershed was divided into eight small hydrological units (SHUs) and the program was run on these SHUs. 
 Main results: At the end of GeoWEPP’s run, the results revealed that a total of about 735 mm annual precipitation was fell within the study area. The model also predicted that there was approximately 207 mm as runoff out of this amount of precipitation, which, in turn, generated an annual total soil loss and sediment amounts as 2815.2 t and 2720.9 t, respectively. In addition, the sediment yield per unit area was estimated to be around 2.57 ton/ha/yr while the sediment delivery ratio (SDR) was found to be as 0.977. Lastly, the model predicted that the particle distribution of eroded sediment were 20%, 25% and 55% of clay, silt and sand, respectively, while the mean organic matter (OM) amount of the lost sediment was about 5% for the studied watershed.
 Highlights: Soil loss and sediment yield can be calculated for large areas in a short time and with little cost.

Climate and land use change effects on soil erosion in two small agricultural catchment systems Fugnitz – Austria, Can Revull – Spain

Soil erosion represents one of the most important processes of land degradation in the world and is considered a serious threat to the provision of food supply, to human health and to terrestrial ecosystems. In Europe, soil erosion by water and tillage is responsible for the loss of fertile topsoil and therefore productive land. Under Global Change scenarios climate and land use are expected to impact soil loss and sediment discharge rates distinctly in contrasting climatic regions, further influenced by tillage practices. Soil erosion modeling is a valuable tool to estimate future changes and elucidate opportunities to mitigate future threats to soil loss and crop yield, ultimately leading to the development of Best Management Practices (BMPs). In this study, future change of soil erosion processes under the IPCC Representative Concentration Pathways RCP2.6 and RCP6.0, as well as a conventional tillage (CT) and a reduced tillage (RT) practice are investigated in two small agricultural catchments in Europe under contrasting climate; Can Revull in Spain and Fugnitz in Austria. We applied GeoWEPP, the Geospatial Interface for the Water Erosion Prediction Project, to model these two agricultural catchments at a fine spatial resolution. We demonstrate that tillage practice, precipitation and runoff are driving factors for soil erosion at both locations. Furthermore, we illustrate that tillage practices have a greater effect on soil erosion than climate change scenarios. RT could reduce soil erosion by more than 75% compared to CT practices. Under RCP6.0, future changes in runoff, hillslope soil loss and sediment discharge would be greater compared to RCP2.6, with different responses depending on the investigated climatic region. Linking soil erosion models on a fine spatial scale and with different management practices to downscaled global circulation models, can provide valuable input for the development of future BMPs to reduce soil loss in agricultural landscapes.

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.

Assessing applicability of the WEPP hillslope model to steep landscapes in the northern Loess Plateau of China

The Water Erosion Prediction Project (WEPP) model has been extensively evaluated at lower slope gradients, but its applicability to steep slopes is not yet known. The objectives of this study were to evaluate the WEPP model’s ability to predict runoff and soil erosion on steep slopes in the hilly-gully region of the Loess Plateau of China, and to provide insights for adapting it for this region. Field runoff and soil loss data collected from six bare slope gradient plots, four bare slope length plots, and four cropped plots at the Ansai experimental station during 1985–1992 were used to calibrate, validate, and evaluate the WEPP hillslope model. Measured rainfall intensity (rainfall break point data) was directly used to minimize climate-induced prediction errors. Overall, the calibrated WEPP model predicted event, annual, and average annual runoff and soil loss for different slope gradients, slope lengths, and cropped conditions reasonably well with model efficiencies (ENS) being greater than 0.5 for most cases, but there is still room for improvement. Specifically, for the slope gradient plots, simulated runoff was somewhat insensitive to slope increases at large slope gradients while measured runoff tended to increase with slope steepness due to a decrease in surface storage capacity; however, simulated average annual soil loss, though satisfactory (ENS = 0.83), was slightly oversensitive to slope increases at large slope gradients. For the slope length plots, simulated average annual soil loss was overly responsive to slope length increases at steep slopes, indicating a potential deficiency in representing slope length influence in the model for large slope gradients. The use of the default 1-m rill spacing might have also affected the sensitivity of WEPP-predicted soil loss to slope gradients and lengths, because rill spacing varies with slope steepness and lengths and WEPP –predicted erosion is sensitive to rill spacing. For the cropped plots, WEPP tended to underpredict runoff and soil loss, indicating that the internal model adjustments of hydraulic conductivity and soil erodibility for the effects of factors like roots and residue need to be reexamined for use on steep slopes.

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.

Combining Soil Erosion Modeling with Connectivity Analyses to Assess Lateral Fine Sediment Input into Agricultural Streams

Soil erosion causes severe on- and off-site effects, including loss of organic matter, reductions in soil depth, sedimentation of reservoirs, eutrophication of water bodies, and clogging and smothering of spawning habitats. The involved sediment source-mobilization-delivery process is complex in space and time, depending on a multiplicity of factors that determine lateral sediment connectivity in catchment systems. Shortcomings of soil erosion models and connectivity approaches call for methodical improvement when it comes to assess lateral sediment connectivity in agricultural catchments. This study aims to (i) apply and evaluate different approaches, i.e., Index of Connectivity (IC), the Geospatial Interface for Water Erosion Prediction Project (GeoWEPP) soil erosion model, field mapping and (ii) test a connectivity-adapted version of GeoWEPP (i.e., “GeoWEPP-C”) in the context of detecting hot-spots for soil erosion and lateral fine sediment entry points to the drainage network in a medium-sized (138 km2) agricultural catchment in Austria, further discussing their applicability in sediment management in agricultural catchments. The results revealed that (a) GeoWEPP is able to detect sub-catchments with high amount of soil erosion/sediment yield that represent manageable units in the context of soil erosion research and catchment management; (b) the combination of GeoWEPP modeling and field-based connectivity mapping is suitable for the delineation of lateral (i.e., field to stream) fine sediment connectivity hotspots; (c) the IC is a useful tool for a rapid Geographic Information System (GIS)-based assessment of structural connectivity. However, the IC showed significant limitations for agricultural catchments and functional aspects of connectivity; (d) the process-based GeoWEPP-C model can be seen as a methodical improvement when it comes to the assessment of lateral sediment connectivity in agricultural catchments.

Modeling Runoff-Formation and Soil Erosion after Pumice Excavation at Forested Andosol-Sites in SW-Germany Using WEPP

This study investigates the effects of pumice excavation on runoff formation and soil erosion processes in a forested catchment in SW-Germany. The underlying questions are, if (a) backfilled soils have different properties concerning runoff generation and erodibility and if (b) clear-cutting prior to excavation triggers runoff and erosion. Four adjacent sub-areas were observed, which represented different pre- and post-excavation-stages. The basis of the investigation was a comprehensive field sampling that delivered the data for physical erosion modeling using the Water Erosion Prediction Project (WEPP). Modeling took place for standardized conditions (uniform slope geometry and/or uniform land management) and for actual slope geometry and land management. The results show that backfilled soils exhibited 53% increase of annual runoff and 70% increase of annual soil loss under standardized conditions. Storm runoff was increased by 6%, while storm soil loss was reduced by 9%. Land management changes also triggered shifts in annual runoff and soil erosion: Clear-cut (+1.796% runoff, +4.205% soil loss) and bare (+5.958% runoff, +21.055% soil loss) surfaces showed the most distinct changes when compared to undisturbed forest. While reforestation largely diminished post-excavation runoff and soil erosion, the standardized results statistically prove that soil erodibility and runoff generation remain increased after backfilling.

Best Management Practices Influence Modeled Erosion Rates at Forest Haul Road Stream Crossings in Virginia

AbstractForestry best management practices (BMPs) reduce sedimentation by minimizing soil erosion and trapping sediment. These practices are particularly important in relation to road construction and use due to the heightened potential for sediment delivery at stream crossings. This study quantifies the implementation and effectiveness of BMPs at 75 randomly selected forest road stream crossings on recent timber harvests in the Mountains, Piedmont, and Coastal Plain regions of Virginia. Road characteristics at stream crossings were used to estimate erosion using the Universal Soil Loss Equation for Forests and the Water Erosion Prediction Project for Roads. Stream crossings were evaluated based on the Virginia Department of Forestry (VDOF) BMP manual guidelines and categorized as BMP−, BMP‐standard, or BMP+ based on the quality of road template, drainage, ground cover, and stream crossing structure. BMP implementation scores were calculated for each stream crossing using VDOF audit questions. Potential erosion effects due to upgrading crossings were estimated by adjusting ground cover percentage and approach length parameters in the erosion models. Results indicate that erosion rates decrease as BMP implementation scores increase (p < 0.05). BMP‐standard and BMP+ ratings made up 83% of crossings sampled, with an average erosion rate of 6.8 Mg/ha/yr. Hypothetical improvements beyond standard BMP recommendations provided minimal additional erosion prevention.

English

In this paper, we evaluated the Water Erosion Prediction Project (WEPP) model using 5-yr monitored runoff and sediment data from three different lands cover treatments in the Loess Plateau of China. The results showed that the WEPP model was able to predict 22 out of 37 recorded runoff producing events, and 20 out of 34 recorded sediment producing events. Prediction of annual runoff is more accurate than the prediction of sediment. The correlation coefficients between the annual monitored and simulated runoff ranged from 0.69 to 0.91, and 0.11 to 0.90 for sediment; for the three treatments (bare, corn and grass), the prediction for the grass plot is better than the other two. Soil moisture and storm intensity appeared to have greater effect on both predictability and accuracy of runoff events and sediment yields. For grass plot, Nash-Sutcliffe coefficient was 0.76 in runoff and 0.56 in sediment. WEPP predictions for the grass plot were in agreement with measured values, but no better than using the averaged measured values for the other two treatments (bare and corn plots). Application of the WEPP model should be decided with precautions in the Loess Plateau area

Analysing the land-use change effects on soil erosion and sediment in the North of Iran; a case study: Talar watershed

This research aims at predicting the future land-use and examining the effects of the land-use changes on the present and future soil erosion and sediment delivery. Then, Land Change Modeler (LCM) and Geo-spatial Water Erosion Prediction Project (GeoWEPP) were applied. Annual suspended sediment derived from sediment rating curves in Talar Watershed, Iran was used to evaluate the GeoWEPP. The predicted sediment load values of 2016 by GeoWEPP in the likely zone of 0.5 for Shirgah-Talar and Valikbon hydrometric stations were achieved respectively as 756094 and 62082.8 ton. Moreover, the mean annual sediment delivery per unit area of 2000, 2010, 2016 and 2030 were calculated respectively as 37.5, 43, 49.4 and 53.2 (t/ha.yr). The reason for the acquired incremental trend of the soil loss and sediment delivery was the land-use change. The results proved the acceptable performance of LCM combined by GeoWEPP to predict the nearby land-use and related sediment delivery.

New approach to estimate the shear stress and the force of raindrops and their effect on erodibility of agricultural soils

The objective of this work was to the study the erosive force of raindrops and the shear stress on the soil erodibility of disturbed and saturated agricultural soil. A mathematical development was used to determine a new approach to the shear stress. The soil erodibility is calculated using the WEPP (water erosion prediction project) model. To realize this work, an experimental study was led in a laboratory using the rainfall simulator. The soil tray used in this study has a length of 2 m, width of 50 cm and a depth of 15 cm and the slope was adjusted with a system. The soils used were sandy and silty agricultural soils. The results show that the relationship between the erosive force of raindrops and the shear stress on the soil erodibility increased respectively as a power and linear function with an important coeffiient of determination. As regards the relationships between soil erodibility and the mean raindrop diameter, the evolution is represented by a power function with high coeffiient of determination.