The use of spatial empirical models to estimate soil erosion in arid ecosystems

The central objective of this project was to utilize geographical information systems and remote sensing to compare soil erosion models, including Modified Pacific South-west Inter Agency Committee (MPSIAC), Erosion Potential Method (EPM), and Revised Universal Soil Loss Equation (RUSLE), and to determine their applicability for arid regions such as Kuwait. The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the de-militarized zone (DMZ) adjacent to Iraq and has been fenced off to restrict public access since 1994. Results showed that the MPSIAC and EPM models were similar in spatial distribution of erosion, though the MPSIAC had a more realistic spatial distribution of erosion and presented finer level details. The RUSLE presented unrealistic results. We then predicted the amount of soil loss between coastal and desert areas and fenced and unfenced sites for each model. In the MPSIAC and EPM models, soil loss was different between fenced and unfenced sites at the desert areas, which was higher at the unfenced due to the low vegetation cover. The overall results implied that vegetation cover played an important role in reducing soil erosion and that fencing is much more important in the desert ecosystems to protect against human activities such as overgrazing. We conclude that the MPSIAC model is best for predicting soil erosion for arid regions such as Kuwait. We also recommend the integration of field-based experiments with lab-based spatial analysis and modeling in future research.     

Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.     

Use of USLE/GIS Methodology for Predicting Soil Loss in a Semiarid Agricultural Watershed

The Universal Soil Loss Equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices in agricultural watersheds by the effective integration of the GIS-based procedures to estimate the factor values in a grid cell basis. This study was performed in the Kazan Watershed located in the central Anatolia, Turkey, to predict soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Rain erosivity (R), soil erodibility (K), and cover management factor (C) values of the model were calculated from erosivity map, soil map, and land use map of Turkey, respectively. R values were site-specifically corrected using DEM and climatic data. The topographical and hydrological effects on the soil loss were characterized by LS factor evaluated by the flow accumulation tool using DEM and watershed delineation techniques. From resulting soil loss map of the watershed, the magnitude of the soil erosion was estimated in terms of the different soil units and land uses and the most erosion-prone areas where irreversible soil losses occurred were reasonably located in the Kazan watershed. This could be very useful for deciding restoration practices to control the soil erosion of the sites to be severely influenced.     

An assessment to prioritise the critical erosion-prone sub-watersheds for soil conservation in the Gumti basin of Tripura,North-East India

Erosion-induced land degradation problem has emerged as a serious environmental issue across the world. Assessment of this problem through modelling can generate valuable quantitative information for the planners to identify priority areas for proper soil conservation measures. The Gumti River basin of Tripura falls under humid tropical climate and experiences soil erosion for a prolonged period which has turned into a major environmental issue. Increased sediment supply through top soil erosion is one of the major reasons for reduced navigability of this river. Thus, the present study is an attempt to prioritize the sub-watersheds of the Gumti basin by estimating soil loss through the USLE (Universal Soil Loss Equation) model. For that purpose, five parameters of the USLE model were processed, computed and overlaid in a GIS environment. The result shows that potential mean annual soil loss of the Gumti basin ranges between 0.03 and 114.08 t ha^?1 year^?1. The resultant values of soil loss were classified into five categories considering the minimum and maximum values. It has been identified that low, moderate, high, very high and severe soil loss categories occupy 68.71, 8.94, 5.86, 5.02 and 11.47% of the basin respectively. Moreover, it has been recognised that sub-watersheds like SW7, SW8, SW12, SW21, SW24 and SW29 fall under very high priority class for which mitigation measures are essential. Therefore, the present study recommends mitigation measures through terrace cultivation, as an alternative of shifting cultivation in the hilly areas and through construction of check dams at the appropriate sites of the erosion prone sub-watersheds. Moreover, proper afforestation programmes that have been implemented successfully in other parts of Tripura through the Japan International Cooperation Agency, Joint Forest Management, and National Afforestation Programme should be initiated in the highly erosion-prone areas of the Gumti River basin.     

Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China

Soil erosion is a serious environmental problem in Guizhou Province, which is located in the centre of the karst areas of southwestern China. Unfortunately, Guizhou Province suffers from a lack of financial resources to research, monitor and model soil erosion at large watershed. In order to assess the soil erosion risk, soil erosion modeling at the watershed scale are urgently needed to be undertaken. This study integrated the Revised Universal Soil Loss Equation (RUSLE) with a Geographic Information System (GIS) to estimate soil loss and identify the risk erosion areas in the Maotiao River watershed, which is a typical rural watershed in Guizhou Province. All factors used in the RUSLE were calculated for the watershed using local data. It was classified into five categories ranging from minimal risk to extreme erosion risk depending on the calculated soil erosion amount. The soil erosion map was linked to land use, elevation and slope maps to explore the relationship between soil erosion and environmental factors and identify the areas of soil erosion risk. The results can be used to advice the local government in prioritizing the areas of immediate erosion mitigation. The integrated approach allows for relatively easy, fast, and cost-effective estimation of spatially distributed soil erosion. It thus indicates that RUSLE-GIS model is a useful and efficient tool for evaluating and mapping soil erosion risk at a large watershed scale in Guizhou Province.     

Spatial and temporal estimation of soil loss for the sustainable management of a wet semi-arid watershed cluster

The ungauged wet semi-arid watershed cluster, Seethagondi, lies in the Adilabad district of Telangana in India and is prone to severe erosion and water scarcity. The runoff and soil loss data at watershed, catchment, and field level are necessary for planning soil and water conservation interventions. In this study, an attempt was made to develop a spatial soil loss estimation model for Seethagondi cluster using RUSLE coupled with ARCGIS and was used to estimate the soil loss spatially and temporally. The daily rainfall data of Aphrodite for the period from 1951 to 2007 was used, and the annual rainfall varied from 508 to 1351 mm with a mean annual rainfall of 950 mm and a mean erosivity of 6789 MJ mm ha^?1 h^?1 year^?1. Considerable variation in land use land cover especially in crop land and fallow land was observed during normal and drought years, and corresponding variation in the erosivity, C factor, and soil loss was also noted. The mean value of C factor derived from NDVI for crop land was 0.42 and 0.22 in normal year and drought years, respectively. The topography is undulating and major portion of the cluster has slope less than 10°, and 85.3 % of the cluster has soil loss below 20 t ha^?1 year^?1. The soil loss from crop land varied from 2.9 to 3.6 t ha^?1 year^?1 in low rainfall years to 31.8 to 34.7 t ha^?1 year^?1 in high rainfall years with a mean annual soil loss of 12.2 t ha^?1 year^?1. The soil loss from crop land was higher in the month of August with an annual soil loss of 13.1 and 2.9 t ha^?1 year^?1 in normal and drought year, respectively. Based on the soil loss in a normal year, the interventions recommended for 85.3 % of area of the watershed includes agronomic measures such as contour cultivation, graded bunds, strip cropping, mixed cropping, crop rotations, mulching, summer plowing, vegetative bunds, agri-horticultural system, and management practices such as broad bed furrow, raised sunken beds, and harvesting available water using farm ponds and percolation tanks. This methodology can be adopted for estimating the soil loss from similar ungauged watersheds with deficient data and for planning suitable soil and water conservation interventions for the sustainable management of the watersheds.     

Simulation of soil loss processes based on rainfall runoff and the time factor of governance in the Jialing River Watershed,China

Jialing River is the largest tributary in the catchment area of Three Gorges Reservoir, and it is also one of the important areas of sediment yield in the upper reaches of the Yangtze River. In recent years, significant changes of water and sediment characteristics have taken place. The "Long Control" Project implemented since 1989 had greatly changed the surface appearance of the Jialing River Watershed (JRW), and it had made the environments of the watershed sediment yield and sediment transport change significantly. In this research, the Revised Universal Soil Loss Equation was selected and used to predict the annual average amount of soil erosion for the special water and sediment environments in the JRW after the implementation of the "Long Control" Project, and then the rainfall–runoff modulus and the time factor of governance were both considered as dynamic factors, the dynamic sediment transport model was built for soil erosion monitoring and forecasting based on the average sediment yield model. According to the dynamic model, the spatial and temporal distribution of soil erosion amount and sediment transport amount of the JRW from 1990 to 2007 was simulated using geographic information system (GIS) technology and space-grid algorithm. Simulation results showed that the average relative error of sediment transport was less than 10% except for the extreme hydrological year. The relationship between water and sediment from 1990 to 2007 showed that sediment interception effects of the soil and water conservation projects were obvious: the annual average sediment discharge reduced from 145.3 to 35 million tons, the decrement of sediment amount was about 111 million tons, and decreasing amplitude was 76%; the sediment concentration was also decreased from 2.01 to 0.578 kg/m³. These data are of great significance for the prediction and estimation of the future changing trends of sediment storage in the Three Gorges Reservoir and the particulate non-point source pollution load carried by sediment transport from watershed surface.     

Identification of effective best management practices in sediment yield diminution using GeoWEPP: the Kasilian watershed case study

Identifying areas that are susceptible to soil erosion is crucial for water resource planning and management efforts. Furthermore, modeling has proven helpful in recognizing and monitoring high-risk areas at the watershed scale. The Water Erosion Prediction Project (WEPP) geospatial interface (GeoWEPP) software integrates GIS with the WEPP to analyze the spatial variation in soil loss, and it has been used as a modeling tool to determine the areas that are most prone to soil erosion and to evaluate best management practices for the Kasilian watershed in Iran. As much as 62.4 % of the agronomic land in the Kasilian watershed is affected by a high magnitude of erosion (>5 t/ha). On the basis of this study, by using soybeans, high fertilization levels, and the drill-no-tillage system, reductions of erosion by almost 32.68–34.02 % are perceivable in three critical subwatersheds that are located in the cultivated lands. Also, it is projected that reductions in the production of sediment in the range of about 36.7–47.1 % are achievable by structural management within two critical, upland subwatersheds. So, by utilizing the best management strategies, sediment yield can be lowered and the conservation of soil and water is feasible at the watershed scale. These results objectively indicate that GeoWEPP can be efficaciously used for evaluating effective management practices for developing watershed conservation.     

Assessment and sources of heavy metals in surface sediments of Miyun Reservoir, Beijing

Heavy metals concentrations in surface sediments from Miyun Reservoir were determined to evaluate the pollution and identify the sources. The average content of metals in sediments from Miyun Reservoir followed the order Al>Fe>Ti>Mn>V>Zn>Cr>Ni>Cu>Pb>As>Cd>Hg, and the most mean values were lower than the globe average shale. Heavy metals concentrations at the inflow area of Baihe were higher than those at the inflow area of Chaohe. Heavy metals pollution assessment was carried out by factor enrichment (EF), geoaccumulation index (I _geo), and potential ecological risk (RI). The EF values for all heavy metals except Hg, Cd, and Cr at several sites were lower than 3, suggesting low anthropogenic impact on the metals level. The I _geo values of Pb indicated that half of the sites were unpolluted to moderately polluted and mainly located in the Baihe area of the reservoir. The RI showed that heavy metals of Miyun Reservoir were low potential risk, however, Hg approached or belonged to moderate ecological risk at sites of M5, M7, and M13. Correlation analysis and principal component suggested that Ni, Cu, V, Zn, Mn, Cr, Ti, and Pb were derived from soil erosion in upper reaches of the reservoir, while Fe, Cd, Hg, As, and partial Pb originated from anthropogenic sources, particularly industrial mining and gold tailings.     

An evaluation of grid size uncertainty in empirical soil loss modeling with digital elevation models

This paper presents a study on the effect of topographic variability on grid-based empirical estimation of soil erosion and sediment transport with raster geographic information systems (GIS). An original digital elevation model (DEM) of 10 m resolution for a case watershed is resampled to six realizations of greater grid sizes for a comparative examination. The Universal Soil Loss Equation (USLE) and a distance-based sediment delivery equation are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams, respectively. The results suggest that the selection of the DEM gird size has considerable influence on the soil loss estimation with the empirical models. The estimate of total soil loss from the watershed decreases significantly with the increasing DEM cell size as the spatial variability is reduced by the cell aggregation. The empirical modeling approach is a useful tool for qualitative assessment of soil erosion, provided that spatial variability can be adequately represented by applied DEMs. However, discretion is suggested for its applications to quantitative estimation of soil loss concerning the sensitivity to the grid size selection.