Soil Loss Model Research Articles

Comparison of the MUSLE Model and Two Years of Solid Transport Measurement, in the Bouregreg Basin, and Impact on the Sedimentation in the Sidi Mohamed Ben Abdellah Reservoir, Morocco

The evaluation and quantification of solids transport in Morocco often uses the Universal Soil Loss Model (USLE) and the revised version RUSLE, which presents a calibration difficulty. In this study, we apply the MUSLE model to predict solid transport, for the first time on a large river basin in the Kingdom, calibrated by two years of solid transport measurements on four main gauging stations at the entrance of the Sidi Mohamed Ben Abdellah dam. The application of the MUSLE on the basin demonstrated relatively small differences between the measured values and those expected for the calibrated version, these differences are, for the non-calibrated version, +5% and +102% for the years 2016/2017 and 2017/2018 respectively, and between −33% and +34% for the calibrated version. Besides, the measured and modeled volumes that do not exceed 1.78 × 106 m3/year remain well below the dam’s siltation rate of 9.49 × 106 m3/year, which means that only 18% of the dam’s sediment comes from upstream. This seems very low because it is calculated from only two years. The main hypothesis that we can formulate is that the sediments of the dam most probably comes from the erosion of its banks.

Storage Reduction of Mujeb Dam Reservoir in Jordan due to Sedimentation

The flow of water from the watershed upstream of a reservoir is capable of eroding the drainage area and of depositing material either upstream of the reservoir or in the still water of the reservoir causing reservoir sedimentation. The impact of reservoir sedimentation is reducing the storage capacity, decreasing ability to produce hydroelectric power and shortening of the life of the reservoir. In the present work, Al-Mujeb dam has been selected to estimate the quantity of sediment that reaches its reservoir using the modified universal soil loss model (MUSLE). Calibration and verification were carried out using measured data for volumes of runoff and cumulative sediment yields obtained from Eco-Sounder device. The quantities of sediment yield have been predicted for the next decade, when the reservoir storage capacity will be reduced by 23%. Strategies are recommended to update the Eco-Sounder measurements then the prediction process for another decade of time, and to reduce the soil erosion and minimize the sedimentation in the reservoir. Keywords: Sedimentation, Yield, Dams, Reservoir, Erosion, Soil Loss, Storage, Jordan. DOI: 10.7176/JEES/10-6-10 Publication date: June 30 th 2020

Landslide Susceptibility and Soil Loss Estimates for Drift Creek Watershed, Lincoln County, Oregon

ABSTRACTDrift Creek watershed, Lincoln County, Oregon, is a source of drinking water as well as a reproductive habitat for endangered salmon and trout species. Landslides, exacerbated by logging, are suspected as a cause of water quality deterioration in the watershed. To investigate the impact of landslides on water quality, we mapped landslide distribution and susceptibility, determined engineering properties of landslide-prone soil and rock, and estimated soil loss resulting from landslide-derived sediment within 30 m of Strahler third-order-or-higher streams in the watershed. We mapped 570 landslides using LiDAR imaging, orthophotographs, and field observations. We used logistic regression to determine the most significant variables contributing to landslide occurrence and to create a watershed-scale landslide susceptibility map. Siletz River Volcanics and the sedimentary Tyee Formation make up 85 percent of the watershed, with the sedimentary Yamhill and Nestucca formations making up the majority of the rest. Sedimentary rocks dominate in the Upper Drift Creek watershed, and volcanic dominate in the lower portion. The largest landslide deposits and the highest susceptibility occur in the sedimentary rock formations. The Siletz River Volcanics has a larger abundance of landslides than the sedimentary rock formations, but they are smaller in size with lower susceptibility of occurrence. The soil loss model indicates that the average annual soil loss from landslide deposits in the Upper Drift Creek watershed is 65 tons/acre/yr compared to 29 tons/acre/yr in the Lower Drift Creek watershed. The model also indicates that soil loss from areas along roads in the watershed is high.

WEPPCLIFF: A command-line tool to process climate inputs for soil loss models

WEPPCLIFF: A command-line tool to process climate inputs for soil loss models

WEPPCLIFF: A command-line tool to process climate inputs for soil loss models

WEPPCLIFF: A command-line tool to process climate inputs for soil loss models

Application of airborne LiDAR and GIS in modeling trail erosion along the Appalachian Trail in New Hampshire, USA

Recreational activities can negatively affect protected area landscapes and resources and soil erosion is frequently cited as the most significant long-term impact to recreational trails. This study applied extensive multiple regression modeling of trail soil loss to identify influential factors that managers can manipulate to improve the sustainability of trail design and management. Field measurements assessed soil loss as the mean vertical depth along 135 trail transects across the Appalachian Trail sampled along three 5 km trail segments in New Hampshire’s White Mountains National Forest, chosen due to its exceptionally high use and impact. GIS and LiDAR data were used to create many new variables reflecting terrain characteristics that were expected to influence trail erosion and improve predictive models of trail system soil loss. A variety of terrain and hydrology characteristics were applied to model trail soil loss at three spatial scales: transect, trail corridor, and watershed. The model for each spatial scale and a combined model are presented. The adjusted R2 explaining variation in soil loss is 0.57 using variables from all spatial scales, improving on predictive modeling from earlier studies. Environmental and trail design factors such as slope and watershed flow length were found to be significantly correlated to soil loss and have implications for improved sustainable trail design and management.

Soil Erosion Modelling for Sustainable Environmental Management in Sebeya Catchment, Rwanda

Soil erosion models can be understood as a virtual laboratory that brings together data, observations and knowledge from different fields for sustainable environmental management. The present study was carried out on Sebeya catchment which is located in the Western Province of Rwanda. The main objective of this study was to develop a Universal Soil Loss Equation type of erosion model to be used in predicting soil loss and associated crop yields for sustainable agriculture management in Sebeya catchment at the level of parcels. USLE parameters were determined on each parcel in Sebeya catchment using map overlapping techniques as applied in Geographical Information System (GIS). Applying a combination of 0, 1, 2 and 3 soil erosion control measures on each of 259,673 parcels, the simulated annual soil loss for Sebeya catchment was 849.94; 143.27; 88.64 and 28.59 t/ha/yr respectively. Soil Loss and Crop Yield (SOLCY) model has been developed to predict soil loss and crop yields for each main cultivated crop in Sebeya catchment. A combination of 3 soil erosion control measures such as (bench terrace + mulching + drainage channels) has been found to be the most effective in reducing soil erosion on each parcel with slope range of (16 - 60)%. Farmers and agriculture technicians can use SOLCY model. Finally, researchers should develop similar models on other catchments based on SOLCY model design concept.

Soil erosion characteristics of three-dimensional overburdened stockpiles

Overburdened stockpiles, a kind of typical loose mixture composed of different proportions of soil and gravel that are created by various production and construction projects, are one of the main sources of man-made accelerated erosion. Because of their specific source of production and unique three-dimensional shape, overburdened stockpiles often present a peculiar erosion process given rainfall conditions. To study this erosion process, a stockpile platform device was designed and used to simulate three-dimensional overburdened stockpiles. A series of indoor artificially simulated rainfall experiments at different precipitation intensities were conducted using loessial soil with different gravel contents. The following key results were obtained: (a) the runoff rate and flow velocity had the same trend over time – that is, a rapid increase, followed by a slower increase and stabilization, while the three-dimensional shape resulted in smaller numerical values of the Reynolds number and Froude number than a rectangular slope; (b) the sediment yield increased exponentially in response to the increasing rainfall intensity and decreased with increasing gravel content in a logarithmic manner; and (c) stream power could be the optimal factor describing soil erosion because it produced the strongest correlation and fitting degree for soil detachment rate. These findings improve our understanding of the hydraulic characteristics and erosion processes of overburdened stockpiles and also have implications for predictive soil and water loss models.

Modeling of Soil Loss and Identification of Erosion Hot Spot Areas Using RUSLE Integrated with GIS for Appropriate Conservation Practices in Muga Watershed, Highlands of Ethiopia

Over cultivation, deforestation and free grazing are major factors facilitating soil erosion. Nowadays; in lower parts of Muga watershed soil erosion become as a continuous environmental problem. In this study an attempt has been made to modeling soil loss and identify the most erosion sensitive areas by using Revised Universal Soil Loss Equation integrated with GIS and remote sensing techniques for planning appropriate conservation measures in Muga watershed. The annual soil loss amount was estimated by using the Revised Universal Soil Loss Equation (RUSLE). Digital Elevation Model, digital soil map, thirty years rainfall records of six stations, and land cover data (Landsat images) were used to develop RUSLE soil loss variables. The annual soil loss rate from the catchment were estimated by integrating RUSLE parameters using raster calculator tool. The annual soil loss rate varies between 0.02 ton/ha/yr and 41.789 ton/ha/yr. The total annual soil loss in the watershed was 59751.41 tones, of these, 12806.15 tons were lost from 371.19 km 2 , 26562.44 tons from 214.30 km 2 , 15300.94 tons from 50.52 km 2 , 4059.05 tons from 4.61 km 2 , and 1022.83 tons from 0.37 km 2 of land per year. The rate of soil eroion was high in the lower part of the watershed. Slope gradient and length factor was the main factor for soil erosion increment followed by Support Practice (P) factor. As result of soil erosion cross tabulation; steep slopes, Rendzic leptosols and dominantly cultivated areas were detected as very severe erosivity. Therefore, the lower parts of the study needs to undertake effective soil and water conservation practices. Keywords: Soil loss, RUSLE, GIS, Remote sensing, Moga Watershed, Erosion hot spot areas DOI : 10.7176/JEES/9-10-03 Publication date :October 31 st 2019

Optimization of revised universal soil loss equation of ecological forest lands in the hilly areas of the eastern Zhejiang Province

The soil erosion prediction model is an effective means to predict soil erosion and soil and water conservation planning. Based on the analysis of soil erosion law of typical economic forest slopes in the study area, it is of great significance to establish a prediction model for soil loss in typical economic forests in the study area. In this study, five typical economic forest slope runoff plots in the study area were used as research objects. The runoff and sediment data under natural rainfall conditions were used to optimize the universal soil loss equation. The prediction equation for soil and water loss in the hilly areas of the eastern Zhejiang Province was proposed: A= 0.004·R1.594·K·LS·C·P. The Nash efficiency coefficients of the simulation results are above 0.70, and the coefficients of determination are above 0.80.

Global analysis of support practices in USLE-based soil erosion modeling

Support practices (SPs) influence the magnitude of soil loss and can be readily influenced by human interventions to mitigate soil loss. The SPs factor is expressed as the P-factor in the widely used soil erosion model – the universal soil loss equation (USLE) – and its revised version. Although the effects of SPs on soil erosion are well recognized, the quantification of the P-factor for soil loss modeling remains challenging. This limitation of the P-factor particularly restricts the applicability of USLE-based models at large scales. Here, we analyzed the P-factor values in USLE-based models from 196 published articles. The results were as follows: (a) an increasing trend in the number of studies has been observed in recent years, especially at large scales; (b) the P-factor values for paddy fields, orchards, and croplands were 0.16 ± 0.15, 0.47 ± 0.12, and 0.49 ± 0.21, respectively, and in terms of different types of SPs, the P-factor values for terracing, contouring, and strip-cropping were 0.28 ± 0.18, 0.52 ± 0.24, and 0.49 ± 0.28, respectively; (c) various methods have been developed for P-factor qualification, although the methods that consider SP conditions were most frequently used in studies with relatively smaller areas (< 100 km2), suggesting that USLE-based models are in need of improvement via the quantification of the P-factor, particularly with respect to the regional and global scale; and (d) further improvements of the P-factor for soil erosion modeling should concentrate on building P-factor datasets at the regional level according to data on the effectiveness of SPs on soil loss control based on field experiments in published articles, using advanced image processing techniques based on higher-resolution satellite imagery and developing proxy indicators for P-factors at large scales.

Review: Design norms for soil and water conservation structures in the sugar industry of South Africa

This paper contains a critical review of the norms employed in the design of soil and water conservation structures in the South African sugar industry and highlights research needs in order to update them. Sugarcane in South Africa is grown on wide-ranging soils, sometimes in non-ideal climates and on steep topographies where soils are vulnerable to erosion. A consequence of unsustainable soil loss is reduction in field production capacity. Sugarcane fields are protected against erosion through, inter alia, the use of engineered waterways, contour banks and spill-over roads. The South African Sugarcane Research Institute (SASRI), previously known as the South African Sugar Experiment Station (SASEX), developed a nomograph to easily compute the maximum width of field panels based on soil type, tillage method, replant method, surface structures to control runoff, surface cover and slope. This was followed by guidelines and norms for the design of soil and water conservation structures. However, the nomograph was developed based on an acceptable soil loss of 20 t·ha−1·yr−1, yet soil formation rates in South Africa range between 0.25 and 0.38 t·ha−1·yr−1. Comparisons between design norms in the National Soil Conservation Manual and norms used in the sugar industry clearly show discrepancies that need to be investigated. The design of soil conservation structures includes the design of both contour bank spacing and hydraulic capacity. The sustainable soil loss method is recommended in the design of contour spacing and it determines contour spacing based on evaluation of site-specific sheet and rill erosion potential of the planned contour spacing while the hydraulic design employs Manning’s equation. Considering that increases in both design rainfall and design floods are anticipated in South Africa, it is necessary to incorporate these projections in the design of soil and water conservation structures. Many soil loss models exist, of which empirical models are the most robust and provide stable performances. The majority of empirical models are lumped models which estimate average annual soil loss. The Modified Universal Soil Loss Equation (MUSLE) estimates event-based erosion and, given that the majority of soil erosion occurs during a few extreme events annually, the design norms should be updated using the MUSLE.

Prioritization of W. Alarab Sub-Watersheds (North Jordan) for Conservation Measures Using RS, GIS, and Multi-Criteria Analysis

Soil erosion and high sediment flow are of eminent environmental concern in Wadi Alarab catchment, northern Jordan. The objective of this research is to conduct a prioritization scheme using RS, GIS, and multi-criteria analysis approach based on morphometric analysis, land use/land cover (LULC) change analysis, and soil loss modeling based on RUSLE model factors. ASTER GDEM and Arc GIS were utilized to delineate watersheds and extract the drainage networks using the Arc Hydro tool. Five basic morphometric parameters, five linear and five shape parameters, six LULC classes, and five soil erosion risk classes are applied to prioritize 13 sub-watersheds connected to W. Alarab basin. LANDSAT images were subjected to supervised classification (the Maximum Likelihood Method) to determine land use/cover changes and to establish the LULC map/layer. Soil erosion risk classes were estimated using the RULSE model. RULSE factors (R, K, L, S, C, and P) were calculated in a GIS environment, then multiplied together so as to estimate soil loss (ton·ha-1·yr-1) and to establish a soil erosion risk map for the entire watershed and the thirteen sub-watersheds. A GIS-based integration of the three layers compiled for each criterion reveals that six sub-watersheds (1, 5, 8, 9, 10, and 11) are categorized under low priority. Further, three sub-basins (4, 12, and 13) are fall under moderate priority, and four sub-basins (2, 3, 6, and 7) are designated as of high priority. It is obvious that 53.8% of these sub-basins must be prioritized immediately for soil and conservation measures. The validity of the achieved priority classes was tested statistically using Discriminant Analysis (DA), and the results showed that morphometric parameters, LULC analysis, and soil loss are accepted criteria for prioritization. These results are intended to help decision-makers to prepare reliable soil erosion management plans.

Modelling Top Soil Erosion Depend on Stand Profile for Anatolian Black Pine (Pinus nigra Arnold. subsp. pallasiana) Plantation in a Semi-Arid Ecosystem in Turkey

This paper researches top-soil loss depends on Anatolian black pine stands by different canopy density. The stand profile is playing an important role on the living and non-living environment in the ecosystem and it affects directly canopy density (CD), leaf area index and silvicultural treatments and indirectly affects the soil properties. Within the scope of the study, three different canopy densities (60%, 80%, 90%) were taken and the stand profiles were determined by an 20x20 meter sample plots representing the stand. All sample plots were selected under the same habitat conditions (Slope: 5%, Aspect: Northwest, Elevation: 1070 m) to estimate top soil loss model. As a result, the amount of top soil loss was determined as 0.052 t/ha/yr in 60% CD, 0.037 t/ha/yr in 80% CD and 0.017 t/ha/yr in 90% CD respectively. In addition, multiple regression model (Linear, R2=0.96) was developed to estimate annual top soil loss depend on DBH (diameter of breast height), and tree height. On the other hand, simple regression model (Quadratic, R2=0.98) using tree height variable was improved. Furthermore, more advanced models can be developed in the future by using the stand parameters in different ecological conditions and slope gradients.

Modeling of water induced surface soil erosion and the potential risk zone prediction in a sub-tropical watershed of Eastern India

Soil is the earth’s fragile skin that anchors all life on earth. Half of the topsoil on the planet has been lost in the last 150 years. Land degradation due to soil loss is one of the major environmental concerns which can be influences by the natural as well as anthropogenic activities. These impacts include compaction, loss of soil structure, nutrient degradation, and soil salinity. The effects of soil erosion go beyond the loss of fertile land. It has led to increased pollution and sedimentation in streams and rivers. And degraded lands are also often less able to hold onto water which can worsen flooding. Revised Universal soil Loss Equation (RUSLE) model and integration with Geographical Information System (GIS) have been taken into consideration for estimating the average annual soil loss in Arkosa watershed. The Overlay Analysis technique have been adopted in RUSLE model for estimating the influences of different factors namely rainfall and runoff erosivity factor (R), soil erodibility factor (K), slope length and steepness factor (LS), cover and management factor (C) and support practice factor (P) etc. The average annual soil loss of Arkosa watershed ranged between 0 to 10 tons/ha/year. Here the combined index method has been adopted to show the impact spatially of combine index of these five factors, i.e., R, K, LS, C and P. Apart from this there are total 29 points have been selected randomly for securing that the present soil loss model sounded with ground reality or not. The actual soil loss and predicted soil loss show the positive relationship with them in an r2 value of 0.882. Besides this the present study provides a reliable prediction for future on potential soil erosion risk zones which ranged between 0 and 16 tons/ha/year. To overcome from extreme or severe soil loss situation suitable soil conservation practices or support practices have to be taken care off for minimizing the erosion of the fertile soil or the top soil for making the region less vulnerable from soil erosion in present rate. Sustainable land use can help to reduce the impact of agriculture and livestock, preventing the soil degradation and erosion and the loss of valuable land to deforestation.

Evaluation of the relationship between soil erosion and landscape metrics across Gorgan Watershed in northern Iran.

Soil erosion is one of the most serious environmental threats strongly influenced by the spatial pattern of land uses. This study was designed to evaluate the relevance of land use pattern and soil erosion using landscape metrics across Gorgan Watershed in northern Iran. Therefore, the revised universal soil loss equation was applied to evaluate and model soil loss and sedimentation in the region. Then, soil erosion relationship to land use pattern was analyzed using a variety of metrics including percentage of landscape, number of patches, largest patch index, and landscape shape index. The results revealed that potential of soil loss, sediment retention, and sediment yield for the whole watershed were 6.6, 2.4, and 1.5tha-1year-1, respectively. The quantity of sediment retention was estimated at 4.3, 3.2, 1.0, and 1.2tha-1year-1 in forest, rangelands, agriculture, and built-up areas, respectively. Similarly, sediment yield was 0.6, 1.6, 1.5, and 2.1tha-1year-1, respectively. The results revealed that the soil loss increased with decreasing metrics of forest and rangelands while increasing metrics of built-up regions and agricultural lands accelerated the process. Moreover, we showed that land use type of patches was an important factor on soil erosion, and soil loss was also affected by area, number, shape, and density of landscape patches. Result of this study can facilitate monitoring of erosion-sensitive areas in the watershed which can help managers and decision makers to design more suitable measures for soil conservation.

Predicting soil loss and sediment characteristics at the plot and field scales: Model description and first verifications

Soil loss models are useful tools for making land management decisions to prevent soil and water quality problems. Several soil loss models have been developed, including the process-based Water Erosion Prediction Project (WEPP) model and the empirical Revised Universal Soil Loss Equation (RUSLE). Although process-based models provide accurate soil loss estimates, they are infrequently used for conservation planning because of their complexity and data need. On the other hand, models such as RUSLE cannot predict the soil loss nor the sediment composition associated with individual events, both of which are critical for designing accurate soil and water conservation practices. Therefore, the objective of this study was to develop a model for estimating sediment delivery on an event scale while predicting its clay, silt and sand fractions. For this purpose, the WEPP model was implemented using measured soil and climate data from Central Chile to generate a soil loss database for many hillslope configurations and management practices. More than 200,000 erosion events were generated using data from 83 sites. Using multiple regression analysis, the main variables controlling soil loss were identified, which included rainfall erosivity, soil erodibility, hillslope geometry, antecedent soil moisture and total precipitation. These variables were incorporated into a soil loss model, which was calibrated using data from 32 sites (R2 = 0.81–0.83) and validated for the remaining 51 sites (R2 = 0.66–0.89). The model provided accurate estimates for the clay and silt fractions (R2 = 0.86 and 0.78, respectively) but showed difficulties for predicting the sand fraction (R2 = 0.31). Contour plowing and vegetative filter strip routines were also incorporated into the soil loss model, providing reliable soil loss (R2 = 0.51–0.78), clay (R2 = 0.54–0.75), and silt (R2 = 0.57–0.68) estimates. The developed model is remarkably easy to use and, due to its simplicity, allows incorporating other soil conservation routines, providing a flexible tool for soil conservation planning. This study provides a detailed description and methodology for building such a model and discusses its advantages and limitations.

A simple model for estimating changes in rainfall erosivity caused by variations in rainfall patterns

A major challenge when coupling soil loss models with precipitation forecasts from Global Circulation Models (GCMs) is that their time resolutions do not generally agree. Precipitation forecasts from GCM must be scaled down; however, the distribution of the rainfall intensity, which can affect soil loss as much as precipitation amounts, is usually not considered in this process. Therefore, the objective of this study was to develop a statistical equation for computing event-based rainfall erosivity under changing precipitation patterns using the least amount of information possible. For this purpose, an empirical equation for predicting event-based rainfall erosivity was developed using the product of the total precipitation P and the maximum 0.5-h rainfall intensity, I0.5. This equation was calibrated using measured precipitation data from 28 sites in Central Chile and then tested with simulated data with different rainfall patterns from the CLIGEN (CLImate GENerator) weather generator. More than 53,000 rainfall events were analyzed, where the equation consistently provided R2 values of 0.99 for every dataset used, revealing its robustness when used in potential climate change scenarios in the study site. However, because computing I0.5 requires estimating precipitation at a high time resolution, the relationship was recalibrated and tested using 1 through 24-h maximum rainfall intensities. Using these intensities, the equation provided erosivity estimates with R2 ranging from 0.78 to 0.99, where better results were obtained as the resolution of the data increased. This study provides the methodology for building and testing the proposed equation and discusses its advantages and limitations.

Recent soil erosion in the Hongfeng catchment on the Guizhou Plateau, SW China revealed by analysis of reservoir sediments and soil loss modeling

The Guizhou Plateau in SW China is dominated by carbonate rocks and karst landforms. Erosion rates are low, but soils are thin and soil erosion remains a serious problem. Hongfeng Lake is the largest reservoir on the Guizhou Plateau. A 35-cm-long sediment core was retrieved from the reservoir and six soil profiles were sampled in the catchment. 137Cs activity was measured in the core to establish a chronological framework. Sediments and soils were analyzed for particle size, TOC, TN and mineral magnetism. Soil erosion that occurred between 1960 and 2003 was inferred from stratigraphic variations in particle size, TOC, C/N and magnetism of the sediments, aided by similar analyses on soils. Erosion was generally low from 1960 to 1987, but intensified thereafter, until about 1996. Between ca. 1996 and 2003, erosion declined. Land use data were derived from remote sensing images for 1973, 1990, 1993, 1996, 2000, 2003, 2006, 2010 and 2013, and running the Conversion of Land Use and its Effects at Small Region Extent (CLUE-S) model for 1976, 1979, 1982, 1985 and 1988. Precipitation, Digital Elevation Model (DEM) and soil-property data were also collected. Using these data, we determined input variables [rainfall erosivity (R), soil erodibility (K), slope length and gradient (LS), vegetation cover and management (C) and erosion control practices (P) for the Revised Universal Soil Loss Equation (RUSLE) Model]. Annual soil loss (A) was estimated for the Hongfeng Reservoir catchment for each year using the RUSLE model. Annual soil loss for 1973, 1976, 1979, 1982 and 1985 was generally low, with an average of 38.5 t ha−1 a−1. For 1988, 1990, 1993 and 1996, average annual soil loss increased to 57.7 t ha−1 a−1. The average for 2000 and 2003 declined to 46.6 t ha−1 a−1. Variations in the modeled annual soil loss are consistent with what was measured in the sediment record, implying that erosion events were recorded in the sediments despite temporary storage of sediments in the large, relatively flat catchment. Erosion was low and may have declined even more from 2003 to 2013. Despite the temporal variability, erosion was generally more intense in the west and east than in the central part of the catchment. Topography, rainfall and vegetation are the main factors that influenced soil erosion in the catchment.

GIS‐based modelling of soil erosion processes using the modified‐MMF (MMMF) model in a large watershed having vast agro‐climatological differences

AbstractThe present study demonstrates a spatially distributed application of a field‐scale annual soil loss model, the modified‐MMF (MMMF), to a large watershed using hydrological routing techniques, remote sensing data and geospatial technologies. In this study, the MMMF model is implemented after incorporating the corrections suggested in recent literature along with appropriate modifications of the model to suit the agro‐climatological conditions prevailing in most parts of India. Sensitivity analysis carried out through an Average Linear Sensitivity approach indicates that the model outputs are highly sensitive to soil moisture (MS), bulk density (BD), effective hydraulic depth (EHD), ground cover (GC) and settling velocity for clay (VSc). During calibration and validation, the performance evaluation statistics are mostly in the range of very good to satisfactory for both runoff and soil loss at the watershed outlet. Even spatial validation of the results of intermediate processes in the water phase and the sediment phase, although qualitative, seems to be reasonable and rational. Furthermore, the soil erosion severity analysis for different land‐uses existing in the watershed indicates that about 90% of the watershed area, especially that occupied by agricultural lands, is vulnerable to the long‐term effects of soil erosion. Copyright © 2018 John Wiley & Sons, Ltd.