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The Upper Mahaweli Catchment (UMC) is a very important watershed in the Central Highlands of Sri Lanka since it contains a series of multipurpose reservoirs. Hence, conservation of soil in the UMC should be given the highest priority to reduce sediment yields in streams and to maintain the storage capacities of hydropower reservoirs. The sediment yields measured in the sub-catchments of the UMC before 1995 have revealed that soil erosion is intense in the contributing catchments and siltation in some reservoirs is at an alarming level. The situation in the Upper Uma Oya, a sub-catchment of the UMC, is the worst, reporting the highest sediment yield measured for any catchment in Sri Lanka. Mahaweli Authority of Sri Lanka had embarked on two soil and water conservation projects in the Upper Uma Oya catchment from 1995 to 2005 together with monitoring of sediment yields in the stream. Sediment yield measurements in this catchment revealed that the wash load in the stream had been reduced by a factor of five after the implementation of conservation programmes in 1995. Our temporal analyses showed that the role of the other key factors that control soil erosion on a hillslope such as erodibility, slope, erosivity and land use cover is minimal to generate a five-fold reduction in the wash load of the stream. Hence, we report that the conservation measures adopted in the critical areas of the Upper Uma Oya have been very successful and had greatly contributed to the reduction of soil erosion. However, even after conservation, soil erosion rates estimated by stream loads are about 10 times higher than the natural background rate. Hence, as shown in other catchments elsewhere in the world, the ongoing rate of soil erosion can be further lowered by strengthening the existing soil and water management practices together with restoration of vegetation on bare lands.

Anthropogenic changes during the past 2000 years in the Teotihuacan Valley imply that intensity of soil degradation varies depending on the land management practices and the intensity of soil use. As a part of a broader effort to reconstruct erosion dynamics in the Teotihuacan Valley through geoarchaeological approaches, our study applies a process-based watershed hydrology and upland erosion model, the Water Erosion Prediction Project (WEPP). The Geo-spatial interface for WEPP (GeoWEPP) was used to characterize locations of soil detachment and sediment deposition predicted in the watershed through time, based on current and reconstructed conditions in the valley. Climate, topography, soil and land use were used as inputs to WEPP to estimate surface runoff and soil loss rates for periods with different environmental and anthropogenic conditions: the Teotihuacan period (1–650 CE), the Aztec period (1325–1521 CE) and for modern times (after 1970 CE). Over a simulated and established timeframe for those periods, surface runoff and rate of soil loss were estimated to be higher during the Aztec period, when the area devoted to agriculture dominated the landscape. Land use change had a major impact on soil erosion. Comparison of the pre-Hispanic periods with current conditions shows that WEPP is useful in showing the roles of management and climate in environmental degradation. The results contribute to the scientific debate about the antiquity and causes of erosion in central Mexico. The research shows that land use is one of the foremost factors affecting soil erosion, both in ancient and modern periods, with particular impact during the Aztec period.

The black soil in Northeastern China is experiencing severe soil erosion. However, spatially distributed erosion models have scarcely been used to identify the sediment source of a catchment as well as its response to the implemented soil conservation measures (ISCMs). In this study, the WaTEM/SEDEM model was selected and calibrated with sediment yields ( SY s) from 25 reservoir catchments in Baiquan County. The validated model was applied to the Shuangyang river catchment to simulate soil erosion, SY and their responses to the ISCMs. The model simulation accuracy was measured by Nash-Sutcliffe efficiency ( NSE ) and relative root mean square error ( RRMSE ). A satisfactory result was obtained with NSE of 0.914 and RRMSE of 0.266, respectively. The ISCMs on the farmlands in Shuangyang river catchment greatly reduced sediment delivery to the rivers. The terraced and contour tillage lands became sediment sink and the up/downslope tillage land had lower erosion risk, resulting from the ISCMs on the upper slopes. However, these measures are not effective enough to comprehensively control soil erosion. The erosion rates in the erosion areas within terrace and contour tillage land were still very high. The large area of up/downslope tillage land and the steep slopes with gradients above 25% still suffered severe soil loss. Comprehensive soil conservation should be urgently applied to reduce soil erosion and sediment delivery to the rivers. This study can help guide effective implementation of soil conservation measures at the catchment scale for the black soil region, Northeastern China.

Forest roads are a concern in management because they represent areas of elevated risks associated with soil erosion and storm runoff connectivity to stream systems. Storm runoff emanating from forest roads and their connectivity to downslope resources can be influenced by a myriad of factors, including storm characteristics, management practices, and the interaction of management practices and successive storm events. Mitigating sediment export and ensuring that storm runoff has negligible impacts on downstream resources requires a more complete understanding of forest road erosion and sediment delivery dynamics. Progress in the area of road and stream connectivity issues hinges on reliable prediction tools to inform broader-scale modeling of watershed-scale effects of forest roads and management practices. In this study, the Water Erosion Prediction Project (WEPP) model was evaluated based on the results from 156 runoff-generating storm events during a continuous five-year study of nine high-elevation road sections in the Appalachian Mountains. The model adequately predicted sediment yield from the road sections with an overall Nash-Sutcliffe model efficiency (E) of 0.76, Willmott refined index of agreement (dr) of 0.56, percent error of 5%, and average storm difference (ASD) of 1.2 kg. In contrast, WEPP predictions of storm runoff were not as good, and the poor agreement was attributed to an inability to determine the source area for runoff from some of the larger runoff events. In general, the WEPP model for these high-elevation sites adequately described the sediment yield for the road sections. Keywords: Forest roads, Long-term simulation, Runoff, Sediment, Water Erosion Modeling, WEPP.

Soil erosion is a global environmental problem influenced by both natural and human factors. Modeling provides a quantitative and consistent approach to estimate soil erosion and sediment yield under a wide range of conditions, and is needed to guide the comprehensive control of soil erosion. Over the years various soil erosion models have been developed. The application of these models is dependent on the soil type and climate of the given area because models differ in complexity and input requirements. This paper reviews various soil erosion models and their applications, focusing more on the most widely applied models which are: Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE) and Water Erosion Prediction Project (WEPP). The method used for this research is a review of academic articles, bulletins, conference papers, textbooks, research reports and publicly available materials on soil erosion models and their applications. The results of this study revealed that most soil erosion models have been developed for the assessment of rill and interill erosion at plot or catchment scale on agricultural lands and watersheds in terms of estimating mostly soil loss, sediment yield, erodibility (K) values, rainfall factor (R) factors, runoff rates and forecasts of likely impacts. Again, the study indicated that most previous authors on soil erosion assessment used the empirical models due to their limited data and parameter inputs. Recommendations of this study include: (1) expansion of the USLE and RUSLE models for the simulation of gully erosion and sediment processes; (2) researchers should be encouraged through grants to develop empirical models (that make use of limited data) based on rainfall (R) factor and erodibility (K) factor that provide two opposing forces in soil erosion processes; and (3) management of soil erosion based on the indigenous knowledge of the affected people and land holders.

. Nonpoint-source (NPS) pollutants, especially from agriculture, continue to be a primary source of waterquality degradation problems. Effective land management decisions at the field scale must be made to minimize nutrient losses that could pollute streams. Existing NPS models often cannot directly estimate the impacts of different land management practices or determine the effectiveness of combined best management practices (BMPs) in a distributed way at the farm scale. In many cases, they rely on application of the Universal Soil Loss Equation (USLE) or its improved versions, which represent fields in a lumped fashion and use empirical rather than process-based modeling methodologies. In this study, a coupled Water Erosion Prediction Project and Water Quality (WEPP-WQ) model was completed, updated, improved, and evaluated for simulation of hydrology, soil erosion, and water quality. The WEPP model is a well-established process-based model that simulates runoff and erosion processes from a hillslope. The water quality components are based on those of the Soil and Water Assessment Tool (SWAT). A single overland flow element (OFE) on a hillslope is used to represent a single soil and land use management. The WEPP-WQ model was tested by comparing simulated values from the coupled model with observed nutrient and sediment concentrations in surface runoff following storm events at experimental sites near Waterloo in northeastern Indiana and at the Throckmorton Purdue Agricultural Center in west central Indiana. Time series evaluation of the WEPP-WQ model was performed with observed nutrient and sediment losses from an experimental plot near Tifton, Georgia. The model performed quite well in simulating nutrient losses for single storm events, with R2 greater than 0.8, Nash-Sutcliffe efficiency (NSE) greater than 0.65, and percent bias (PBIAS) less than 31% for runoff, sediment, nitrate nitrogen, total nitrogen, soluble phosphorus, and total phosphorus losses. In predicting time series nutrient loss, the WEPP-WQ model simulated daily nitrate nitrogen losses adequately, with the ratio of the root mean square error to the standard deviation of measured data (RSR) less than 0.7, NSE greater than 0.55, and PBIAS within the range of ±40%. Comparisons between simulated soluble phosphorus, total phosphorus, and literature results were performed due to the absence of an available observational dataset. The WEPP-WQ model with a single OFE in this study provides a basic but important step for the development of WEPP-WQ models with multiple OFEs that can evaluate the effectiveness of BMPs Keywords: Modeling, Nitrogen, Phosphorus, Soil erosion, Water quality, WEPP.

Soil loss due to wind and water erosion degrades the soil on-site and results in environmental problems due to deposition in off-site areas downstream and downwind of the source field. Wind and water erosion may both occur to varying extents particularly in semi-arid environments. Soil conservation strategies require information about the processes of soil redistribution to mitigate its impact. However, very few studies have partitioned soil erosion between contributions of wind and water. We quantified wind and water erosion on six graded terraces under a uniform crop rotation since 1949 and two tillage management practices begun in 1981. Detailed runoff and sediment yield data have been recorded on all the terraces since 1984. We used a stratified random sampling design to collect soil which were then bulked to form six composites for each terrace. From an adjacent undisturbed native prairie, soil cores were collected and composited similarly to provide a reference. The cores were composited by 15 cm layers in the terraces and, in the reference area, the upper 15 cm layer was subdivided into 5 cm layers and all were measured for 137 Cs activity which was converted to 137 Cs inventory. We then employed an established computer model that equates loss of 137 Cs inventory with soil loss and direct measurement of water-borne sediment loss to estimate 30 year mean wind erosion losses on the terraces by tillage type. We found that no-till management reduced total soil loss by one-third compared with stubble mulch tillage, reduced water-borne sediment loss by about the same amount, and that for both tillage systems, wind erosion was responsible for about 75% of the total soil loss.

Vegetative filter strips (VFS) are areas of either planted or indigenous established vegetation designed to improve the quality of surface runoff. They can be incorporated into pastures, grassed waterways, terraces, or cropland to remove sediment, nitrogen, or phosphorus from runoff. However, their trapping efficiencies depend mainly on the sediment characteristics. The finer soil particles pass through the filter more easily and have more surface area, accounting for most of the transported sediment-bound pollutants. Therefore, the objective of this study was to use a modeling approach to develop a Sediment Composition Vegetative Filter Strip (SCVFS) model to predict the clay, silt and sand trapping efficiencies of VFS based on a wide range of soil loss data from Central Chile. The physically based Water Erosion Prediction Project (WEPP) model was implemented using actual soil and climate data from Central Chile to generate a soil loss database for many VFS designs. More than 22,000 erosion events were generated with data from 28 sites. Three nonlinear relationships were developed between clay, silt and sand delivery and VFS length. The clay and silt models provided accurate estimates compared to WEPP for the calibration (R 2 = 0.80–0.87) and validation (R 2 = 0.73–0.80) sites. However, the sand estimates were not correlated to WEPP (R 2 = 0.00–0.18), as the model computes sand using the difference between the total predicted sediments (R 2 = 0.77–0.89) and the clay and silt estimates. Nevertheless, because most of the sediment-bound pollutants move with the finer sediments, this is not a modeling limitation. Compared to other physically based VFS models, the SCVFS model is remarkably easy to use because it only requires the characteristics of the sediment delivery when there is no filter, the rainfall erosivity and the hillslope and filter lengths. Additionally, it can be easily combined with many existing erosion models that provide daily soil loss estimates, making it a flexible VFS design tool. This study provides the detailed methodology to construct this model and discusses its advantages and limitations.

Soil management in vineyard inter-rows has a great influence on soil hydraulic conductivity and bulk density, and, consequently, on runoff and soil erosion processes at the field scale. The maintenance of bare soil in vineyard inter-rows with tillage, as well as the tractor traffic, are known to expose the soil to compaction, reduction of soil water holding capacity and increase of runoff and erosion. The use of grass cover is one of the most common and effective practices in order to reduce such threats. It is therefore important to relate rainfall characteristics, soil properties and response in terms of runoff and soil erosion, from yearly to seasonal and to single event temporal scales. The objective of this work is to quantify the temporal variability of the effects of two different kind of inter-row management on soil hydrological properties, runoff and erosion in vineyards. For this reason two vineyard field-scale plots in the Alto Monferrato vine-growing area (Piedmont, NW Italy) were monitored in two years. The inter-rows were managed with conventional tillage (CT) and grass cover (GC), respectively. Fifteen series of infiltration tests were carried out during a 2-year period of observation (October 2012 to November 2014). In order to take into account the effect of tractors traffic, the tests were done on the track, and outside the track. Furthermore, a dataset of 29 rainfall-runoff events covering a wide range of topsoil characteristics was collected in the two plots, along with soil water content and runoff discharge monitoring, and determination of sediment yield in case of erosive events. An optical disdrometer installed in the plots provided also 1-min rainfall intensity data. In summer, just one month after tillage, CT soil showed very low hydraulic conductivity, so storms were able to cause Hortonian runoff and soil losses up to 5.7 Mg ha−1. In autumn and winter very high saturation-excess runoff was observed in CT, that reached 83% of the precipitation. Runoff in the grass cover plot was mainly due to saturation of the topsoil, and the annual reduction of runoff in the GC plot was about 63%. Soil erosion up to 1.2 Mg ha−1 in a single event was observed in the GC vineyard in winter. In each year of observation, most of the erosion occurred during a single event, while the total annual erosion was up to 9 times higher in the CT treatment than in the GC.

Efficient mitigation of environmental loads from agricultural fields to surface waters requires sufficient knowledge of dominating erosion processes and sediment transport pathways. Computational models are often applied in sediment load assessments but their structure inherently includes assumptions and uncertainties, which can hinder their predictive and explanatory capabilities. In this study, a 3D dual-permeability model was applied with field-scale data from a high-latitude site to investigate sediment balances and structural uncertainties in sediment transport components. The two-year data encompassed hourly records of water flow and sediment concentration composite samples from tillage layer runoff and drain discharge in two adjacent clayey fields with different slopes (1% and 5%). Three model structures with different assumptions of sediment transport pathways were built to test their performance against the data. The simulations demonstrated how different model structures can reproduce the data with varying results on sediment balance. The varying results revealed the importance of flow, erosion, and sediment transport observations from the fields to improve the simulations. Structural uncertainty analysis revealed uncertainties which parameter sensitivity analysis could not describe. Concentration data was shown to include more information about erosion and sediment transport processes than solely the load data. The results suggest that a major part (48–69%) of the detached particles remained in the field and that lateral subsurface transport contributed to load generation (10–21% of total loads) especially in the steeper field. The results demonstrated that the majority (84–87%) of sediment loads occurred via subsurface drain discharge and groundwater outflow with the slope gradient of 1–5%, which suggests that load mitigation measures should also be directed to decrease loads via subsurface transport pathways. The simulations demonstrated how transport processes were controlled not only by water flow but also by soil structure.

Soil erosion is one of the serious issues threatening the environment. It is a growing problem especially in areas of agricultural activity where soil erosion not only leads to de-creased agricultural productivity but also reduces water availability. This leads to drastic degradation of the agricultural lands. So there is a need to take up conservation and management measures which can be applied to check further soil erosion. Universal Soil Loss Equation (USLE) is the most popular empirically based model used globally for erosion prediction and control. Remote sensing and GIS techniques have become valuable tools for the digitization of the input data and genereation of maps. In the present study, RUSLE model has been adopted to estimate the soil erosion in the Khajuri watershed of Uttar Pradesh, India. This model involves calculation of parameters including runoff-rainfall erosivity factor (R), soil erodability Factor (K), topographic factor (LS), cropping management factor (C), and support practice factor (P). Layer wise thematic maps of each of these factors were generated using GIS platform using various data sources and data preparation methods. The results of the study indicate that the annual average soil loss within the watershed is about t/ha/yr (metric ton per hectare per year).

Soil erosion is an environmental problem that has reached alarming proportions in many parts of South Africa. Understanding the complex interactions between climate, slope and soil factors is important to ensure that soil erosion is controlled and that soil resources are used sustainably. The objectives of the study were to (i) determine soil and slope variables controlling soil erosion in different climatic units and (ii) establish guidelines for the delineation of land with high potential for cropping. The degree of soil erosion was determined from field observation and existing erosion maps. The slope gradient and length were calculated from Digital Elevation Models. Numerical values of soil and slope factors were regressed against the degree of erosion using step-wise regressions. Soils in humid regions were found to be stable, irrespective of parent material, and their stability was controlled by oxides of iron and aluminium, and kaolinite. Dolerite derived soils were the most stable while mudstone and shale derived soils were vulnerable to erosion in arid, semi-arid and subhumid regions. Fine and very fine sand fractions were most important in controlling erosion of soil in arid and semi-arid climate while kaolinite and sesquioxides were more important in subhumid areas. Critical slope limits varied with soil type. Guidelines for the delineation of arable land were formulated which guided the identification of high priority land for crop development.

A plenty of models exist for study of the soil erosion and sediment yield processes. However, these models vary significantly in terms of their capability and complexity, input requirements, representation of processes, spatial and temporal scale accountability, practical applicability, and types of output they provide. The present study reviews 50 physically based soil erosion and sediment yield models with respect to these factors including shortcomings and strengths. The literature generally suggests the use of models like SWAT, WEPP, AGNPS, ANSWERS and SHETRAN for soil erosion and sediment studies. Most of the developed soil erosion and sediment yield models are capable of simulating soil detachment and sediment delivery processes at hillslope scale; a limited development was found in the field of reservoir siltation and channel erosion processes. The study proposes a guideline for selection of an appropriate model to the reader for a given application or case study. The future research suggested to improve the simulation and prediction capability of physically based soil erosion and sediment yield models, and should focus on incorporation of improved global web based weather database, inclusion of sediment associated water quality and gully erosion simulation module, and improvement in reservoir siltation and channel erosion simulation processes.

Soil erosion not only results in the destruction of land resources and the decline of soil fertility, but also contributes to river channel sedimentation. In order to explore the spatiotemporal evolution of erosion and sediment yield before and after returning farmland in a typical watershed of the hilly and gully region (Chinese Loess Plateau), a distributed-dynamic model of sediment yield based on the Chinese Soil Loss Equation (CSLE) was established and modified to assess the effects of hydrological factors and human activities on erosion and sediment yield between 1995 and 2013. Results indicate that (1) the modified model has the characteristics of a simple algorithm, high accuracy, wide practicability and easy expansion, and can be applied to predict erosion and sediment yield in the study area, (2) soil erosion gradations are closely related to the spatial distribution of rainfall erosivity and land use patterns, and the current soil and water conservation measures are not efficient for high rainfall intensities, and (3) the average sediment yield rate before and after model modification in the most recent 5 years (in addition to 2013) is 4574.62 and 1696.1 Mg km−2, respectively, decreasing by about 35.4 and 78.2 % when compared to the early governance (1995–1998). However, in July 2013 the once-in-a-century storm is the most important reason for maximum sediment yield. Results may provide an effective and scientific basis for soil and water conservation planning and ecological construction of the hilly and gully region, Chinese Loess Plateau.

Soil erosion is a natural process causing grave land degradation problems. In Tunisia, soil erosion represents a serious environmental problem. Both man-made and natural phenomenon is reducing acres of agricultural land. The problem of soil erosion by water is very critical in Lebna watershed. In fact, Lebna is a town in the northeast of Tunisia and it seems high time to protect water and ground resources and to prevent the Lebna dam situated in the downstream from silting. In this context, the application of geographic RUSLE model using the techniques of geographic information system (GIS) and remote sensing has made it possible to assess the estimation of the soil erosion risk at the targeted watershed. This model is composed of several factors associated with climate, topography, soil and vegetation. The spatial distribution of annual average rate of soil loss resulting of this methodology shows an average of 24 ton/ha/year. Consequently, this method based on a combination of RUSLE as erosion model gave very similar results with bathymetric measures performed by Institute of Research for Development. It was about 29 ton/ha/year. Accordingly, Lebna watershed belongs to a zone of rather a steep erosive potential knowing that the maximum acceptable limit value of the erosive potential estimated is 12 ton/ha/year (Roose in Introduction a la gestion conservatoire de l’eau, de la biomasse et de la fertilite des sols (GCES). FAORome, 1994). The results have shown that Lebna watershed has a serious risk on soil erosion on sloping land. The highest values are mainly associated with the steep slopes, poor conservation practices, low vegetation cover and high rainfall. The final soil loss map can be thus a base to plan appropriate strategies for decision-makers to avoid soil erosion risks and consequently to lengthen dam life.

Runoff and sediment flow behaviors from small agricultural watersheds on Alfisols and Vertic Inceptisols, and their implications for the design of a runoff and soil loss monitoring unit are discussed. It was observed that a small segment of runoff hydrograph near peak discharge rate usually accounted for 65–85 percent of total storm soil loss. The runoff and sediment flow behavior recorded on the small agricultural watersheds indicated the need for an integrated digital runoff and soil loss monitoring unit (IDRSMU) to achieve higher accuracy and cost effectiveness. The design, development and testing of an IDRSMU to measure both the runoff and soil loss from small agricultural watersheds is presented. Under the field conditions its accuracy and efficiency for monitoring soil loss from small agricultural watersheds was observed good. Use of this integrated unit, makes the estimation of soil loss easy, rapid and accurate. The designed unit does smart runoff sampling by linking the runoff sampling intervals to the sediment load. This significantly reduces number of samples that needs to be collected, thereby reducing the operational cost, without compromising with the accuracy in estimating soil loss from small agricultural watersheds.

Rainfall erosion is a complex process and good understanding of the mechanisms involved is necessary if inappropriate designs and procedures are not unwittingly used in rainfall erosion experiments. Numerous runoff and soil loss plots of various sizes have been installed in many parts of the world. It is essential that on any eroding surface water flows across the surface without interference from any equipment designed to collect runoff and sediment. Examples of designs that do not conform to this requirement are presented. Because sedimentation occurs in tanks, coarse material needs to be collected and measured separately from fine material which can be subsampled when suspended in the runoff water. Despite attempts to operate in areas where soil properties are uniform, replicates are shown to produce considerable variation in the soil losses produced by the same event. Slope length and gradient influence the type of erosion that occurs on a plot. Slope lengths less than one metre encourage erosion where detachment and transport is controlled by the expenditure of the energy generated by raindrop impact but as slope lengths and gradients increase, detachment by flow may result in the development of rills. Experiments on slopes of one or two metres in length do not provide data that can be used to parameterise models like the USLE that operate on slopes up to 300 m long. Rainfall simulators have been widely used in rainfall erosion experiments on plots shorter than 10 m. Given the fact that raindrop induced bed load transport is stimulated by individual raindrop impacts, spatial variations in raindrop size and impact frequency in artificial rainfall produced by sprays can lead to erroneous results. Similarly, temporal and spatial variations in flow depths in rain-impacted flows on inclined surfaces in experiments leads of variations in erosive stress that are seldom taken into account when analysing the results produced using artificial rainfall. This presents difficulties in respect to apply the results to other situations. The WEPP interrill erosion model was designed to predict soil movement from interrill areas to rills but it is shown that the ranking of soils according to their interrill erodibility varies depending on whether eroding surface is flat plot or on a ridge tillage sideslope.

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.

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.

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.

The world is experiencing serious soil losses. Soil erosion has become an important environmental problem in certain regions and is strongly affected by climate and land use changes. By selecting and reviewing 13 extensively used soil water erosion models (SWEMs) from the published literature, we summarize the current model-based knowledge on how climate factors (e.g., rainfall, freeze-thaw cycles, rainstorms, temperature and atmospheric CO2 concentrations) and land use change impact soil erosion worldwide. This study also provides a critical review of the application of these 13 SWEMs. By comparing model structures, features, prediction accuracies, and erosion processes, we recommend the most suitable SWEMs for different regions of the globe (Asia, Europe, Africa and the America) based on the evaluations of 13 SWEMs. Future soil erosion could be simulated using the RUSLE, LISEM, WEPP v2010.1, SWAT, EPIC, KINEROS and AGNPS models in Asia; the RUSLE, WEPP v2010.1, SWAT, EPIC, WATEM-SEDEM, MEFIDIS, AGNPS and AnnAGNPS models in Europe; the RUSLE, LISEM, SWAT, and AGNPS models in Africa; and the WEPP v2010.1, SWAT, EPIC, KINEROS, AGNPS and AnnAGNPS models in America. Finally, the limitations and challenges of the 13 SWEMs are highlighted.

Made available in DSpace on 2019-10-05T06:22:30Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Spatial assessment of soil erosion is essential for the adaptation of agricultural practices and monitoring of soil losses. In this sense, this study aims to assess the efficiency of magnetic susceptibility (MS) as a predictor of soil erodibility factors (K for USLE model; K-i and K-r for WEPP model) fora detailed mapping of Oxisols with different iron contents in northeastern SAo Paulo State, Brazil. This study was carried out in an area of 380 hectares under sugarcane cultivation in SAo Paulo State. Soil samples were collected in a sampling grid (150) and in a transect (86) and physical and chemical analyses and calculations of the erodibility factors/parameters K, K-i, and K-r were performed. Pedotransfer functions (PTFs) were calibrated using simple linear regression analysis to predict the factors/parameters K and K-i using MS as a predictor variable. The observed values of MS and the predicted values of the factors/parameters K, K-i, and K-r were submitted to geostatistical analysis for constructing maps. Magnetic susceptibility can be used as a predictor of erodibility factors (K for USLE model; K-i and K-r for WEPP model) for Oxisols with total iron content ranging from 1 to 20% Fe2O3, with a precision of up to 60% and an accuracy of up to 85%. The results can guide future studies on water erosion in a tropical environment using magnetic soil data as an environmental covariate in the modeling process for large areas. Univ Fed Piaui, Curso Bacharelado Engn Agron, Campus Prof Cinobelina Elvas,Ave Manoel Gracindo, BR-64900000 Bom Jesus, PI, Brazil Univ Estadual Paulista, Fac Ciencias Agr & Vet, Campus Jaboticabal, BR-14884900 Jaboticabal, SP, Brazil Univ Cordoba, Campus Rabanales,Edificio C4, E-14071 Cordoba, Spain Univ Estadual Paulista, Fac Ciencias Agr & Vet, Campus Jaboticabal, BR-14884900 Jaboticabal, SP, Brazil CAPES: 18732-12-7 FAPESP: 13/25118-4

Post-closure maintenance activities for various inactive copper tailings impoundments owned by BHP in Arizona (USA) require frequent erosion-related inspections and repairs. BHP assessed these recurring costs and post-closure hazards and commissioned a study of alternative methods to design a more robust, erosion-resistant solution. The study combined field erosion testing, 2D and 3D erosion models, and landform design tools in an innovative way that allowed BHP to make an informed decision regarding improvements to the erosional stability of the tailings impoundments. The design team developed 3D surfaces of the linear and curvilinear slope profiles developed from WEPP modelling, and more complex 3D surfaces developed from the GeoFluvTM software. These surfaces were subjected to 3D landform evolution modelling using SIBERIA. Inputs to the SIBERIA model and GeoFluvTM software were informed using data collected during the field studies. Each SIBERIA model iteration provided insight regarding short-term and long-term erosion performance for each 3D surface and cover system. The design team produced initial and sustaining capital cost estimates for the final engineering designs based on this output. This paper details the innovative approach taken to integrate field measures of erodibility, 2D and 3D models, and civil 3D design software to produce defensible long-term closure designs that are material and site specific, and cost-effective.

Many high and steep slopes have been formed by special topographic and geomorphic types and mining activities during the construction of mountain expressways. Severe soil erosion may occur under heavy rainfall conditions and pose a serious threat to road safety and the lives of residents. Therefore, the prediction of soil and water loss on highway slopes is important for the protection of infrastructure and human life. This work studies Xinhe Expressway, which is in the southern edge of Yunnan Guizhou Plateau, as the research area. The revised universal soil loss equation is selected as the prediction model of soil and water loss on slopes. Moreover, geographic information system, remote sensing technology, field survey, runoff plot observation test, cluster analysis, and cokriging are adopted. The partition of the prediction units of soil and water loss on the expressway slope in the mountain area and the spatial distribution model of the linear highway rainfall are studied. In view of the particularity of the expressway slope in the mountain area, the model parameter factor is modified and the risk of soil and water loss along the mountain expressway is simulated and predicted under 20-year and one-year rainfall return periods. The results are as follows. (1) Considering natural watershed as the prediction unit of slope soil erosion can represent the actual situation of soil and water loss of each slope. The spatial location of soil erosion unit is realized, the accuracy of soil and water loss prediction results is improved, and the convenience of data management and maintenance in the later stage is guaranteed. (2) Analysis of the actual observation data show that the overall average absolute error of the monitoring area is 33.24 t · km−2, the overall average relative error is 33.96 %, and the overall root mean square error is between 20.95 and 65.64, all of which are within acceptable limits. The Nash efficiency coefficient is 0.67, thereby showing that the prediction accuracy of the model satisfies the requirements. (3) Under the condition of one-year rainfall, we find through risk classification that the percentage of prediction units with no risk of erosion is 78 % and that with mild soil erosion risk is 15.92 %. Results show that soil erosion risk is low and thereby does not affect road traffic safety. Under the 20-year rainfall condition, the percentage of units with high and extremely high risk is 7.11 %. In these areas, the risk of soil erosion is relatively large and mainly distributed on K109 + 500 − K110 + 500 and K133 − K139 + 800 sections. Even if only part of the sediment is deposited on the road, road safety will be affected. The prediction results can help adjust the layout of water and soil conservation measures in these units. This study provides not only a scientific basis for soil erosion prevention and control in mountain expressways but also a reference for the application of water and soil loss prediction and soil conservation planning.

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.

Soil erosion models, typically applied at basin and watershed scales, are rarely evaluated at agricultural field scales due to the lack of spatially-distributed time series data. A novel unmanned aerial vehicle (UAV) methodology was used to quantify farm-field soil erosion from nine UAV surveys and structure-from-motion (SfM). Using a semi-distributed approach, we evaluated soil erosion estimates from the Universal Soil Loss Equation (USLE) and Water Erosion Prediction Project (WEPP). The annual erosion rate, measured with the UAV methodology, was 18.83 t ha−1 yr−1, with USLE and WEPP predictions of 26.23 t ha−1 yr−1 and 16.41 t ha−1 yr−1, respectively. Modelled annual and sub-annual erosion rates with WEPP were within the upper-limit of predictive accuracy, while the USLE tended to systematically overestimate soil erosion rates. These outcomes have implications on the efficacy of conservation efforts, which is highlighted through a discussion and comparison of different best-management practice applications.

Soil erosion is significantly increased and accelerated by unsustainable agricultural activities, resulting in one of the major threats to soil health and water quality worldwide. Quantifying soil erosion under different conservation practices is important for watershed management and a framework that can capture the spatio-temporal dynamics of soil erosion by water is required. In this paper, a modeling framework that coupled physically based models, Water Erosion Prediction Project (WEPP) and MIKE SHE/MIKE 11, was presented. Daily soil loss at a grid-scale resolution was determined using WEPP and the transport processes were simulated using a generic advection dispersion equation in MIKE SHE/MIKE 11 models. The framework facilitated the physical simulation of sediment production at the field scale and transport processes across the watershed. The coupled model was tested using an intensively managed agricultural watershed in Illinois. The impacts of no-till practice on both sediment production and sediment yield were evaluated using scenario-based simulations with different fractions of no-till and conventional tillage combinations. The results showed that if no-till were implemented for all fields throughout the watershed, 76% and 72% reductions in total soil loss and sediment yield, respectively, can be achieved. In addition, if no-till practice were implemented in the most vulnerable areas to sediment production across the watershed, a 40% no-till implementation can achieve almost the same reduction as 100% no-till implementation. Based on the simulation results, the impacts of no-till practice are more prominent if implemented where it is most needed.

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.

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.

Modeling of ephemeral gully (EG) erosion has lagged that of other soil erosion processes despite its major contribution to watershed sediment losses. Several process and semi-empirical based simulation models have been used to assess the occurrence and location of EGs, magnitude of soil losses from EGs, and degradation, aggradation, and transport of sediment through EGs, but no comprehensive EG model exists. This paper reviews these models and presents a thorough discussion of their background, general formulations, key equations, field assessments, assumptions and limitations. Most current EG models evolved from the original formulations used in CREAMS, with incremental improvements by EGEM, WEPP, AnnAGNPS-REGEM, RUSLER-EphGEE models. These models provide process-based estimation of EG processes and field-scale soil-erosion contributions, but all models, except EphGEE, require users to have a priori knowledge of EG locations and all have significant shortcomings. Several topographic index models are discussed that provide simplistic approaches to locate EGs on the landscape using only topographic features. Process-based threshold index models may provide a more robust simulation of EG location and length, though testing has been limited. EG modeling appears to still be in its infancy, with great opportunities for future research, as discussed herein, to improve the understanding and simulation of EG erosion and transport processes.

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 Koppen-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.

CLIGEN is a stochastic weather generator that has been used as input to WEPP. Normally, USLE based models predict erosion using parameter values that are long-term averages but RUSLE2 has a facility to predict erosion for single storms through user entered data. This enables CLIGEN to be used as a weather generator for RUSLE2 when EI30 values for CLIGEN generated rainfall are determined separately. This can be achieved using daily erosivity density (EI30 per unit quantity of rain) data generated by RUSLE2 for each location or by other methods that have the capacity to determine daily EI30 values independently of RUSLE2. One such method developed by Yu was compared with the RUSLE2 based method in terms of its ability to predict temporal variations in soil loss during the calendar year from bare fallow and cropped areas. The process of determining EI30 values by the Yu method involves generating EI30 values so as to match R-factor values used by RUSLE2. This enables CLIGEN to predict soil loss values that are as useful those generated using RUSLE2 erosivity densities in terms of predicting long-term variations in soil loss during the year. However, CLIGEN does not necessarily produce stochastic rainfall data evenly over decades. Consequently, the process of matching R-factors associated with RUSLE2 with those generated by using CLIGEN should be undertaken using the same time frame as used for obtaining the long-term mean soil loss amounts.

Collapsing gullies involve considerable erosion and extreme landform changes and frequently occur in South China. The amount of rainfall infiltration has a direct influence on the occurrence of collapsing gullies. However, the mechanistic effect of infiltration or rainfall on the development of collapsing gullies still needs to be explored, as it is difficult to spatially describe infiltration amounts of event rainfall using existing models (e.g., SWAT and WEPP). A model based on cellular automata (CA) was developed for the spatial simulation of infiltration amounts after event rainfall by analyzing water allocation within and between the cells of the model. The spatial distributions of infiltration amounts after event rainfalls with differing intensities and durations were then predicted and spatially compared with the distribution of collapsing gullies. The results demonstrate that the model performs with good accuracy, as indicated by the Nash coefficient of 0.63. The variations among different rainfall infiltration amounts demonstrate that both rainfall intensity and duration promote spatial variability in infiltration amounts and reduce regional infiltration efficiency. The spatial comparison between rainfall infiltration amounts and collapsing gullies shows that rainfall infiltration promotes the occurrence of collapsing gullies, but steep topographical conditions are also required to collapse the hillside soil. The comparison also reveals that a lower-intensity rainfall event contributes more to the development of collapsing gullies than a higher-intensity rainfall event, mainly due to the soil absorbing more rainfall under lower intensity, increasing in soil weight to induce collapse. This CA-based model for spatially simulating infiltration amounts provides an improved and effective method for understanding the spatial and temporal variations in rainfall infiltration and to better capture the trends in the occurrence of collapsing gullies from hydrological effects. The model can also be customized for convenient and practical application in other watersheds.

Since soil erosion is driven by overland flow, it is fair to expect heterogeneity in erosion and deposition in both space and time. In this study, we develop and evaluate an open-source, spatially-explicit, sediment erosion, deposition and transport module for the distributed hydrological model, GEOtop. The model was applied in Dripsey catchment in Ireland, where it captured the total discharge volume and suspended sediment yield (SSY) with a relative bias ofź-1.2% andź-22.4%, respectively. Simulation results suggest that daily SSY per unit rainfall amount was larger when the top soil was near saturation. Simulated erosion and deposition areas, which varied markedly between events, were also found to be directly influenced by spatial patterns of soil saturation. The distinct influence of soil saturation on erosion, deposition and SSY underscores the role of coupled surface-subsurface hydrologic interactions and a need to represent them in models for capturing fine resolution sediment dynamics. An open-source, spatially-explicit, sediment dynamics model was developed.The model was validated at both plot and catchment scales.Error in runoff estimates influences the accuracy of simulated suspended sediment yield.Daily precipitation intensity did not fully explain the variance in daily SSY.Simulated spatial patterns of erosion/deposition were influenced by surface soil saturation.

All characteristics of vegetation, runoff and sediment from 1960 to 2010 in the Xiliu Gully Watershed, which is a representative watershed in wind-water erosion crisscross region in the upper reaches of the Yellow River of China, have been analyzed in this study. Based on the remote sensing image data, and used multi-spectral interpretation method, the characteristics of vegetation variation in the Xiliu Gully Watershed have been analyzed. And the rules of precipitation, runoff and sediment’s changes have been illuminated by using mathematical statistics method. What′s more, the influence mechanism of vegetation on runoff and sediment has been discussed by using the data obtained from artificial rainfall simulation test. The results showed that the main vegetation type was given priority to low coverage, and the area of the low vegetation coverage type was reducing year by year. On the country, the area of the high vegetation coverage type was gradually increasing. In a word, vegetation conditions had got better improved since 2000 when the watershed management project started. The average annual precipitation of the river basin also got slightly increase in 2000–2010. The average annual runoff reduced by 37.5%, and the average annual sediment reduced by 73.9% in the same period. The results of artificial rainfall simulation tests showed that the improvement of vegetation coverage could increase not only soil infiltration but also vegetation evapotranspiration, and then made the rainfall-induced runoff production decrease. Vegetation root system could increases the resistance ability of soil to erosion, and vegetation aboveground part could reduce raindrop kinetic energy and splash soil erosion. Therefore, with the increase of vegetation coverage, the rainfall-induced sediment could decrease.

The watershed of the Ningxia-Inner Mongolia Reach of the Yellow River (NIMRYR) suffers from soil erosion by wind and water because of the wide distribution of deserts and arsenic sandstones in this region. The sediment generated by erosion fed into the Yellow River directly or by its tributaries, silting up the Yellow River and raising the elevation of the river bed. The silting of the Yellow River result in serious flood disasters in this watershed. Therefore, it is urgent to implement soil conservation projects to control wind and water soil erosion. To reach this objective, understanding the spatial and temporal variations of soil erosion in this watershed is very important. In this study, an assessment of soil erosion risk by wind and water was performed based on soil erosion models. The Integrated Wind Erosion Modeling System (IWEMS) and the Revised Wind Erosion Equation (RWEQ) were used to estimate the wind erosion modulus in this watershed, and the water erosion modulus was estimated by the Revised Universal Soil Loss Equation (RUSLE). The results show that during 2000s, the wind erosion modulus ranged from 0 to 31,440.4 t/km 2 /a, and the water erosion modulus was from 0 to 24,048.5 t/km 2 /a. Moreover, the total soil erosion modulus by wind and water has ranged from 0 to 32,792.7 t/km 2 /a. Due to the influence of regional weather and geomorphology, occurrences of wind and water erosion in this watershed are not identical in their spatial and temporal patterns. Based on the calculated soil erosion modulus, soil erosion risk was assessed according to the “Classification criteria for soil-erosion intensities” (SL190-2007). It was assumed that the areas with erosion intensity higher than slight were at risk of erosion; by this criterion, more than 34% of the total area of the watershed of the NIMRYR would be at erosion risk. Based on this estimation, it was also found that the NIMRYR watershed is not a region of wind–water erosion crisscross and that land-use conversions have a significant impact on soil erosion.

Sediment bodies produced during historical periods of human land use, sometimes referred to as legacy sediment, may be found in various locations within drainage basins, and potentially remobilized by hydrogeomorphic processes accompanying land use change. The amounts and locations of stored legacy sediment can be significant factors in modern drainage basin function and should be accounted for when possible. In this study, late nineteenth-century erosion and sediment storage were investigated and used to construct approximate sediment budgets for two small Blue Ridge Mountain drainage basins in North Carolina (USA). Erosion was quantified using a distributed implementation of the Universal Soil Loss Equation (USLE), and calibrated on the separate bases of soil profile truncation data and recent published rates for long-term erosion in the region. Sediment yield information was reconstructed from pond sediments trapped behind a mill dam. Alluvial sediment storage was quantified using field studies of streambank and floodplain sediment profiles and digital elevation data. Colluvial storage was calculated as a residual in the sediment budget, and further evaluated using soil profile studies of footslope deposits, and soil survey maps. The proportions of erosion accounted for by the different budget terms in the most reliable budget are: 28% sediment yield (i.e., a sediment delivery ratio of 0.28), 69% colluvial storage, and 3% alluvial storage. Blue Ridge basins with low levels of ground disturbance erode like Piedmont basins at high levels of ground disturbance, primarily due to higher slope angles. Sediment delivery ratio is high relative to those given for much larger basins in the adjacent and more frequently studied Piedmont province, and generally in accordance with published sediment delivery curves that reflect higher hydrogeomorphic connectivities within smaller basins. Low values for alluvial storage in Blue Ridge basins may be explained by high sediment transport within steep channels. Colluvial storage values have high uncertainties because of the well known problem of error accumulation in residual budget terms. Field data on colluvial deposits reported here are not sufficient to correct for this problem, and in general, the acquisition of accurate field data on historical colluviation remains an important methodological issue in historical sediment budgeting.

WOS: 000394371100002 Soil erosion is one of the major threats to the conservation of soil and water resources. For that reason, predictive erosion models are useful tools for evaluating soil erosion and developing soil erosion management plans. For this aim, the revised universal soil loss equation (RUSLE) function is a widely used erosion model. This research integrated the RUSLE with a geographic information system (GIS) to investigate the spatial distribution of annual soil loss potential in the Alaca catchment in north central Black Sea region, Turkey. The rainfall erosivity factor was developed from local annual precipitation data using a modified Fournier index; the topographic factor was developed from a digital elevation model; the land cover factor was generated from satellite imagery and forest inventory maps; and the soil organic carbon level and the erodibility factor were developed from systematically collected soil samples and the application of the geostatistical method, respectively. From the model, more than the half of the total study area as in the very low and low erosion risk classes (0-12 t ha(-1) year(-1)), whereas 4.4 % (723.6 h) of the total area was at high and very high erosion risk (35-150 and >150 t ha(-1) year(-1)), respectively. In addition, soil organic carbon density values were between 0.18 and 4.92 kg m(-2) across the catchment. Moreover, the distribution of soil organic carbon losses was closely correlated with the distribution of soil erosion risk classes in the study area. Soils and topographical properties of the watershed had a greater influence than land use/land-cover type on the magnitude of potential soil and soil organic carbon losses, because the erosivity factor did not change substantially in the study area.

Shrink–swell soils, such as those in a Mediterranean climate regime, can cause changes in terms of hydrological and erosive responses because of the changing soil water storage conditions. Only a limited number of long-term studies have focused on the impacts on both hydrological and erosive responses and their interactions in an agricultural environment. In this context, this study aims to document the dynamics of cracks, runoff and soil erosion within a small Mediterranean cultivated catchment and to quantify the influence of crack processes on the water and sediment supplied to a reservoir located at the catchment outlet using water and sediment measurements at a cultivated field outlet as baseline. Detailed monitoring of the presence of topsoil cracks was conducted within the Kamech catchment (ORE OMERE, Tunisia), and runoff and suspended sediment loads were continuously measured over a long period of time (2005–2012) at the outlets of a field (1.32 ha) and a catchment (263 ha). Analysis of the data showed that topsoil cracks were open approximately half of the year and that the rainfall regime and water table level conditions locally control the seasonal cracking dynamics. Topsoil cracks appeared to seriously affect the generation of runoff and sediment concentrations and, consequently, sediment yields, with similar dynamics observed at the field and catchment outlets. A similar time lag in the seasonality between water and sediment delivery was observed at these two scales: although the runoff rates were globally low during the presence of topsoil cracks, most sediment transport occurred during this period associated with very high sediment concentrations. This study underlines the importance of a good prediction of runoff during the presence of cracks for reservoir siltation considerations. In this context, the prediction of cracking effects on runoff and soil erosion is a key factor for the development of effective soil and water management strategies and downstream reservoir preservation. Copyright © 2016 John Wiley & Sons, Ltd.

Increased sediment loading to reservoirs and, ultimately, to Guanica Bay and reef areas is a significant concern in Puerto Rico. Sediment deposition has significantly reduced storage capacity of reservoirs, and sediment-attached contaminants can stress corals and negatively impact reef health. In this study, we examined sediment yield from an upper mountainous watershed, Yahuecas, contributing sediment to Lago Yahuecas reservoir and eventually Guanica Bay, Puerto Rico, to gain a better understanding on sediment loss. This watershed was chosen because it was the only watershed where runoff was monitored in Guanica Bay basin. The Soil and Water Assessment Tool was calibrated and validated using 4½ years of flow data (07/1980 to 01/1985) from the Yahuecas watershed. Five and a half years of suspended sediment concentration data (04/2000 to 09/2005) from the adjacent Adjuntas watershed were used to calibrate sediment simulation of the model because no sediment data were available for Yahuecas. After calibration and validation, Soil and Water Assessment Tool was used to evaluate temporal-spatial soil erosion and sediment yield and assess factors that impact sediment yield. From 1975 to 2011, approximately 80% of annual sediment yield occurred during the two rainy seasons (February to May and August to November). Heavy rainfall, erodible soils, and steep mountain slopes were the primary causes of sediment yield in the Yahuecas watershed. Land use that reduces the protective forest canopy (like sun-grown coffee farming) can exacerbate soil loss. More sediment per hectare was lost from areas producing coffee than forested or grass-covered areas. Conversion of coffee farming practices from sun-grown to shade-grown will reduce soil erosion and sediment yield.

Those conducting impact studies using natural resource models need to be able to quickly and easily obtain downscaled future climate data from multiple General Circulation Models (GCMs), future scenarios, and timescales for multiple locations. This article describes a method of quickly obtaining future climate data over a wide range of scenarios, GCMs, and timescales from the Intergovernmental Panel on Climate Change AR4 and AR5 model families using the MarkSim DSSAT Weather Generator and a Microsoft Excel VBA Macro, the final result being a properly formatted parameter (.par) file which can be used by CLIGEN (CLImate GENerator) within the Water Erosion Prediction Project (WEPP) model. We developed a fast and simple method to create WEPP climate input files by using software which already exists on most computers that does not require climatological or modeling knowledge to operate. Ultimately, the method was modified to create continuous daily data for use with the Soil and Water Assessment Tool (SWAT) as well. The final product is an automated spreadsheet with a simple user interface which imports, analyzes, and generates climate input files for the WEPP and SWAT models. This article describes the methods, development, and testing of the tool for use with CLIGEN and WEPP model simulations.