Integration of geospatial technologies with RUSLE for analysis of land use/cover change impact on soil erosion: case study in Rib watershed,north-western highland Ethiopia

In recent times, soil erosion interlocked with land use and land cover (LULC) changes has become one of the most important environmental issues in developing countries. Evaluation of this complex interaction between LULC change and soil erosion is indispensable in land use planning and conservation works. This paper analysed the impact of LULC change on soil erosion in the north-western highland Ethiopia over the period 1986–2016. Rib watershed, the area with dynamic LULC change and severe soil erosion problem, was selected as a case study site. Integrated approach that combined geospatial technologies with revised universal soil loss equation model was utilized to evaluate the spatio-temporal dynamics of soil loss over the study period. Pixel-based overlay of soil erosion intensity maps with LULC maps was carried out to understand the change in soil loss due to LULC change. Results showed that the annual soil loss in the study area varied from 0 to 236.5 t ha^?1 year^?1 (tons per hectare per year) in 1986 and 0–807 t ha^?1 year^?1 in 2016. The average annual soil loss for the entire watershed was estimated about 40 t ha^?1 year^?1 in 1986 comparing with 68 t ha^?1 year^?1 in 2016, a formidable increase. Soil erosion potential that was estimated to exceed the average soil loss tolerance level increased from 34.5% in 1986 to 66.8% in 2016. Expansion of agricultural land at the expense of grassland and shrubland was the most detrimental factor for severe soil erosion in the watershed. The most noticeable change in soil erosion intensity was observed from cropland with mean annual soil loss amount increased to 41.38 t ha^?1 year^?1 in 2016 from 26.60 in 1986. Moreover, the most successive erosion problems were detected in eastern, south-eastern and northern parts of the watershed. Therefore, the results of this study can help identify the soil erosion hot spots and conservation priority areas at local and regional levels.     

Effects of land use changes on soil erosion in a fast developing area

Land use changes extensively affect soil erosion, which is a great environmental concern. To evaluate the effect of land use change on soil erosion in fast economic developing areas, we studied land use changes of Guangdong, China, from 2002 to 2009 using remote sensing and estimated soil erosion using the Universal Soil Loss Equation. We calculated the areas and percentage of each land use type under different erosion intensity and analyzed soil erosion changes caused by transitions of land use types. In addition, the impact of land use change on soil erosion in different river catchments was studied. Our results show that forest and wasteland land conversions induce substantial soil erosion, while transition from wasteland to forest retards soil loss. This suggests that vegetation cover changes significantly influence soil erosion. Any conversion to wasteland causes soil erosion, whereas expansion of forests and orchards mitigates it. The most significant increase in soil erosion from 2002 to 2009 was found in the Beijiang catchment corresponding to the transition from forest/orchard to built-up and wasteland. Soil erosion in the Xijiang catchment accelerated in this period due to the enormous reduction in orchard land. In Hanjiang catchment, erosion was alleviated and vegetation coverage greatly expanded owing to considerable transitions from wasteland and cropland to orchards. Field investigations validated our estimations and proved the applicability of this method. Measures including protecting vegetation, strict control of mining as well as reasonable urban planning should be taken to prevent successive soil erosion.     

Assessment of soil erosion risk using SWAT model

Soil erosion is one of the most serious land degradation problems and the primary environmental issue in Mediterranean regions. Estimation of soil erosion loss in these regions is often difficult due to the complex interplay of many factors such as climate, land uses, topography, and human activities. The purpose of this study is to apply the Soil and Water Assessment Tool (SWAT) model to predict surface runoff generation patterns and soil erosion hazard and to prioritize most degraded sub-catchment in order to adopt the appropriate management intervention. The study area is the Sarrath river catchment (1,491 km²), north of Tunisia. Based on the estimated soil loss rates, the catchment was divided into four priority categories for conservation intervention. Results showed that a larger part of the watershed (90 %) fell under low and moderate soil erosion risk and only 10 % of the watershed was vulnerable to soil erosion with an estimated sediment loss exceeding 10 t?ha^?1?year^?1. Results indicated that spatial differences in erosion rates within the Sarrath catchment are mainly caused by differences in land cover type and gradient slope. Application of the SWAT model demonstrated that the model provides a useful tool to predict surface runoff and soil erosion hazard and can successfully be used for prioritization of vulnerable areas over semi-arid catchments.     

The impact of land use and land cover changes on soil erosion in western Iran

Natural Hazards - Analysis of long-term land use and land cover (LULC) changes requires up-to-date remotely sensed data to assess their effects on erosion. This is a particularly important...     

Spatio-temporal changes in rate of soil loss and erosion vulnerability of selected region in the tropical forests of Borneo during last three decades

An attempt has been made to analyze the spatial-temporal characteristics of soil erosion vulnerability and soil loss from the forested region in the north-eastern Borneo, Sarawak, Malaysia during the last three decades (1991–2015) using the revised universal soil loss equation (RUSLE) and geographical information systems (GIS). The components of RUSLE such as rainfall erosivity (R), soil erodibility (K), slope-length and steepness (LS), cover management (C) and conservation practice (P) factors were grouped into two categories by keeping one set as temporally changing and others as static. Among them the R and C factors are calculated for the years 1991, 2001 and 2015 whereas the K and LS factors are considered for the single time frame. Because of the forested nature of the study area, the P factor is kept constant for the whole analysis. The R factor and C factor is shown changes in values and its distribution over the years, which reflected in the final soil loss and erosion vulnerability map as a change in the rate of erosion and spatial domain. The analysis of three time slices has shown that the maximum value of the soil loss per unit area i.e. at erosion hotspots, is relatively similar throughout at around 1636 to 1744 t/ha/y. This is the result of maximum values of R factor and C factor i.e. high rainfall erosivity combined with lack of vegetation cover in those hotspots, which are generally steeply sloping terrain. The reclassification of annual soil loss map into erosion vulnerability zones indicated a major increase in the spatial spread of erosion vulnerability from the year 1991 to 2015 with a significant increase in the high and critical erosion areas from 2.3% (1991) to 31.5% (2015). In 1991, over 84% of the study area was under low erosion vulnerability class but by the year 2015 only 12% was under low erosion vulnerability class. Moreover, a dynamic nature in the erosion pattern was found from the year 1991 to 2015 with more linear areas of land associated with higher rate of soil loss and enhanced erosion vulnerability. The linearity in the spatial pattern is correlated with the development of logging roads and logging activities which has been confirmed by the extraction of exposed areas from satellite images of different years of analysis. The findings of the present study has quantified the changes in vegetation cover from dense, thick tropical forest to open mixed type landscapes which provide less protection against erosion and soil loss during the severe rainfall events which are characteristic of this tropical region.     

Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China

There is no doubt that land cover and climate changes have consequences on landslide activity, but it is still an open issue to assess and quantify their impacts. Wanzhou County in southwest China was selected as the test area to study rainfall-induced shallow landslide susceptibility under the future changes of land use and land cover (LULC) and climate. We used a high-resolution meteorological precipitation dataset and frequency distribution model to analyse the present extreme and antecedent rainfall conditions related to landslide activity. The future climate change factors were obtained from a 4-member multi-model ensemble that was derived from statistically downscaled regional climate simulations. The future LULC maps were simulated by the land change modeller (LCM) integrated into IDRISI Selva software. A total of six scenarios were defined by considering the rainfall (antecedent conditions and extreme events) and LULC changes towards two time periods (mid and late XXI century). A physically-based model was used to assess landslide susceptibility under these different scenarios. The results showed that the magnitude of both antecedent effective recharge and event rainfall in the region will evidently increase in the future. Under the scenario with a return period of 100 years, the antecedent rainfall in summer will increase by up to 63% whereas the event rainfall will increase by up to 54% for the late 21st century. The most considerable changes of LULC will be the increase of forest cover and the decrease of farming land. The magnitude of this change can reach + 22.1% (forest) and –9.2% (farmland) from 2010 until 2100, respectively. We found that the negative impact of climate change on landslide susceptibility is greater than the stabilizing effect of LULC change, leading to an over decrease in stability over the study area. This is one of the first studies across Asia to assess and quantify changes of regional landslide susceptibility under scenarios driven by LULC and climate change. Our results aim to guide land use planning and climate change mitigation considerations to reduce landslide risk.     

Land use land cover dynamics as a function of changing demography and hydrology

This paper describes the spatiotemporal changes pertaining to land use land cover (LULC) and the driving forces behind these changes in Doodhganga watershed of Jhelum Basin. An integrated approach utilizing remote sensing and geographic information system (GIS) was used to extract information pertaining to LULC change. Multi-date LULC maps were generated by analyzing remotely sensed images of three dates which include LandSat TM 1992, LandSat ETM+ 2001 and IRS LISS-III 2005. The LULC information was extracted by adopting on-screen image interpretation technique in a GIS environment at 1:25,000 scale. Based on the analysis, changes were observed in the spatial extent of different LULC types over a period of 13 years. Significant changes were observed in the spatial extent of forest, horticulture, built-up and agriculture. Forest cover in the watershed has decreased by 1.47 %, Agricultural by 0.93 % while as built-up area has increased by 0.92 %. The net decrease in forest cover and agriculture land indicate the anthropogenic interference into surrounding natural ecosystems. From the study it was found that the major driving forces for these changes were population growth and changes in the stream discharge. The changes in the stream discharge were found responsible for the conversion of agricultural land into horticulture, as horticulture has increased by 1.14 % in spatial extent. It has been found that increasing human population together with decreasing stream discharge account for LULC changes in the watershed. Therefore, the existing policy framework needs to focus upon mitigating the impacts of forces responsible for LULC change so as to ensure sustainable development of land resources.     

Estimating of water erosion in semiarid regions using RUSLE equation under GIS environment

Water erosion is one of the main forms of land degradation in Algeria, with a serious repercussion on agricultural productivity. The purpose of this study is to estimate the soil loss of Wadi El-Ham watershed in the center of Algeria, this study aims also to evaluate the effectiveness and reliability of the use of the Revised Universal Soil Loss Equation (RUSLE) under a Geographic Information System in this field. The RUSLE model involves the main factors of erosion phenomena, namely, rain aggressiveness, soil erodibility, topographic factor, land cover index and the anti-erosive practices factor. Using this approach, the specific erosion in Wadi El-Ham watershed is estimated as 5.7 (t/ha/yr) in the entire watershed area. This result is compared to the measured suspended sediment at the Rocade-Sud gauging station situated outlet the watershed. These data consist of 1293 instantaneous measures of the water discharge and the suspended sediment concentration recorded during 21 years. Through this comparison, the used approach of RUSLE under GIS estimates the soil loss in Wadi El-Ham in Hodna region of Algeria with an error of 7.5%. Consequently, the results obtained in cartographic format make it possible to target the areas requiring priority action for a larger scale analysis to find appropriate solutions to combat erosion and to protect the natural environment.     

Effects of historical and projected land use/cover change on runoff and sediment yield in the Netravati river basin,Western Ghats,India

In this study, the effects of changes in historical and projected land use land cover (LULC) on monthly streamflow and sediment yield for the Netravati river basin in the Western Ghats of India are explored using land use maps from six time periods (1972, 1979, 1991, 2000, 2012, and 2030) and the soil and water assessment tool (SWAT). The LULC for 2030 is projected using the land change modeller with the assumption of normal growth. The sensitivity analysis, model calibration, and validation indicated that the SWAT model could reasonably simulate streamflow and sediment yield in the river basin. The results showed that the spatial extent of the LULC classes of urban (1.80–9.96%), agriculture (31.38–55.75%), and water bodies (1.48–2.66%) increased, whereas that of forest (53.04–27.03%), grassland (11.17–4.41%), and bare land (1.09–0.16%) decreased from 1972 to 2030. The streamflow increased steadily (7.88%) with changes in LULC, whereas the average annual sediment yield decreased (0.028%) between 1972 and 1991 and increased later (0.029%) until 2012. However, it may increase by 0.43% from 2012 to 2030. The results indicate that LULC changes in urbanization and agricultural intensification have contributed to the increase in runoff, amounting to 428.65 and 58.67 mm, respectively, and sediment yield, amounting to 348 and 43 ton/km², respectively, in the catchment area from 1972 to 2030. The proposed methodology can be applied to other river basins for which temporal digital LULC maps are available for better water resource management plans.     

Analyzing and modeling of a large river basin dynamics applying integrated cellular automata and Markov model

Historical and exact information about the land use/land cover change is very important for regional sustainable development. The aim of this paper is to determine the rapid changes in land use/land cover (LULC) pattern due to agriculture expansion, environmental calamities such as flood and government policies over Upper Narmada basin, India. Multi-temporal Landsat satellite images for years 1990, 2000, 2010 and 2015 were used to analyze and monitor the changes in LULC with an overall accuracy of more than 85%. Results revealed a potential decrease in natural vegetation (? 9.52%) due to the expansion of settlement (+ 0.52%) and cropland (+ 9.43%) from 1990 to 2015. In the present study, Cellular Automata and Markov (CA–Markov), an integrated tool was used to project the short-term LULC map of year 2030. The projected LULC (2030) indicated the expansion of built-up area along with the cropland and degradation in the vegetation area. The outcomes from the study can help as a guiding tool for protection of natural vegetation and the management of the built-up area. Additionally, it will help in devising the strategies to utilize every bit of land in the study area for decision makers.     

http://www.sciencedirect.com/science/article/pii/S1674987111001034

A comprehensive methodology that integrates Revised Universal Soil Loss Equation（RUSLE） model and Geographic Information System（GIS） techniques was adopted to determine the soil erosion vulnerability of a forested mountainous sub-watershed in Kerala,India.The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster based GIS method.GIS data layers including,rainfall erosivity（R）,soil erodability（K）,slope length and steepness（LS）,cover management （C） and conservation practice（P） factors were computed to determine their effects on average annual soil loss in the area.The resultant map of annual soil erosion shows a maximum soil loss of 17.73 t h^-1 y^-1 with a close relation to grass land areas,degraded forests and deciduous forests on the steep side-slopes（with high LS ）.The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas.     

Modeling soil erosion using RUSLE and GIS in a watershed occupied by rural settlement in the Brazilian Cerrado

The installation of a rural settlement complex in the watershed stream Indaiá has promoted changes in land-use and vegetation cover dynamics; however, the effects of intensive agriculture and cattle farming in rural settlements on soil loss rates are not well known. Predictive models implemented in geographic information systems have proven to be effective tools for estimating erosive processes. The erosion predictive model Revised Universal Soil Loss Equation (RUSLE) is a useful tool for analyzing, establishing and managing soil erosion. RUSLE has been widely used to estimate annual averages of soil loss, by both interrill and rill erosion, worldwide. Therefore, the aim of this work was to estimate the soil loss in the watershed stream Indaiá, using the RUSLE model and geoprocessing techniques. To estimate soil loss, the following factors were spatialized: erosivity (R), erodibility (K), topography (LS), land-use and management (C) and conservation practices (P); the annual soil loss values were calculated using the RUSLE model equation. The estimated value of soil loss in the hydrographic basin ranged from 0 to 4082.16 Mg ha^?1 year^?1 and had an average value of 47.81 Mg ha^?1 year^?1. These results have demonstrated that 68.16 % of the study area showed little or no soil loss based on the Food and Agriculture Organization’s (FAO 1980) classification. When comparing the average value of soil loss obtained using the RUSLE model with the Natural Potential for Erosion, a 16-fold reduction in soil was found, which highlighted the fact that vegetation cover (C factor) has a greater influence than other factors (R, K and LS) on soil loss prediction attenuation. These results lead to the conclusion that soil loss occurs by different methods in each settlement in the basin and that erosive processes modeled by geoprocessing have the potential to contribute to an orderly land management process.     

桂江流域土壤侵蚀估算及其时空特征分析

桂江流域的水土流失现状研究对珠江三角洲的水生态安全有重要的现实意义。采用修正的通用土壤流失方程（RUSLE）估算了桂江流域的土壤侵蚀模数与年侵蚀总量,分析流域内土壤侵蚀的时空分布特征,探讨了影响该区域土壤侵蚀强度的自然与人文因素。结果表明,桂江流域51.8%的地表都在发生不同程度的土壤侵蚀。从全流域平均土壤侵蚀强度来看,属于中度侵蚀。从土壤侵蚀面积来看,约85%的地表处于微度、轻度与中度侵蚀。4-6月的全流域平均土壤侵蚀强度最大,侵蚀总量也是最大的。流域的土壤侵蚀主要发生在高程在30~600m的低山丘陵-高地地貌区内的林地与耕地中。流域内岩溶区的土壤侵蚀强度随着石漠化程度从无到中度逐渐增加,轻、中度石漠化区的土壤侵蚀强度达到强度侵蚀等级。      

RETRACTED ARTICLE: Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed,Guizhou Province,China

Due to the existence of fragile karst geo-ecological environments, such as environments with extremely poor soil cover, low soil-forming velocity, and fragmentized terrain and physiognomy, as well as inappropriate and intensive land use, soil erosion is a serious problem in Guizhou Province, which is located in the centre of the karst areas of southwestern China; evaluation of soil loss and spatial distribution for conservation planning is urgently needed. This study integrated the revised universal soil loss equation (RUSLE) with a GIS to assess soil loss and identify risk erosion areas in the Maotiao River watershed of Guizhou. Current land use/cover and management practices were evaluated to determine their effects on average annual soil loss and future soil conservation practices were discussed. Data used to generate the RUSLE factors included a Landsat Thematic Mapper image (land cover), digitized topographic and soil maps, and precipitation data. The results of the study compare well with the other studies and local data, and provide useful information for decision makers and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a larger watershed scale in Guizhou.     

Use of USLE/GIS technology integrated with geostatistics to assess soil erosion risk in different land uses of Indagi Mountain Pass—Çankırı, Turkey

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 by the effective integration of the GIS-based procedures to estimate the factor values on a grid cell basis. This study was performed for five different lands uses of Indağı Mountain Pass, Cankırı to predict the soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Of the USLE factors, rainfall-runoff erosivity factor (USLE-R) and topographic factor (USLE-LS) were greatly involved in GIS. These were surfaced by correcting USLE-R site-specifically using DEM and climatic data and by evaluating USLE-LS by the flow accumulation tool using DEM and watershed delineation tool to consider the topographical and hydrological effects on the soil loss. The study assessed the soil erodibility factor (USLE-K) by randomly sampled field properties by geostatistical analysis. Crop management factor for different land-use/land cover type and land use (USLE-C) was assigned to the numerical values from crop and flora type, canopy and density of five different land uses, which are plantation, recreational land, cropland, forest and grassland, by means of reclassifying digital land use map available for the site. Support practice factor (USLE-P) was taken as a unit assuming no erosion control practices. USLE/GIS technology together with the geostatistics combined these major erosion factors to predict average soil loss per unit area per unit time. Resulting soil loss map revealed that spatial average soil loss in terms of the land uses were 1.99, 1.29, 1.21, 1.20, 0.89 t ha⁻¹ year⁻¹ for the cropland, grassland, recreation, plantation and forest, respectively. Since the rate of soil formation was expected to be so slow in Central Anatolia of Turkey and any soil loss of more than 1 ton ha⁻¹ year⁻¹ over 50–100 years was considered as irreversible for this region, soil erosion in the Indağı Mountain Pass, to the great extent, attained the irreversible state, and these findings should be very useful to take mitigation measures in the site.     

Impacts of vehicles on natural terrain at seven sites in the San Francisco Bay area

The impacts of off-road vehicles on vegetation and soil were investigated at seven representative sites in the San Francisco Bay area. Plant cover of grass and chaparral (with shrubs to 4 m tall) have been stripped by the two- and four-wheel vehicles in use. Impacts on loamy soils include increased surface strength (as much as 275 bars), increased bulk density (averaging 18%) to depths of 90 cm or more, reduction of soil moisture by an average 43% to 30 cm depths, greatly reduced infiltration, extension of the diurnal temperature range by as much as 12°C, and reduction of organic carbon by an average 33% in exposed soils. Very sandy soils respond similarly to vehicular use except that moisture is increased and surface strength of beach sand is decreased. These physical and chemical impacts reduce the land's capability of restoring its vegetative cover, which in turn adversely affects animal populations. Both the loss of plant cover and the physical changes caused by vehicles promote erosion. Measured soil and substrate losses from vehicular use zones range from 7 to 1180 kg/m². The estimated erosion rate of the Chabot Park site exceeds the rate of erosion considered a serious problem by a factor 30, it exceeds United States Soil Conservation Service tolerance values by a factor of 46, and it exceeds average San Francisco Bay area erosion rates by a factor of 17. The resulting soil losses are effectively permanent. Neither the increased sediment yield nor the increased runoff is accomodated on the sites of use, and both are causing adverse effects to neighboring properties.     

Impact of land use and land cover changes on landscape structure in the dry lands of Southern Africa: a case of the Zambezi Region,Namibia

GeoJournal - The study evaluated patterns of land use and land cover (LULC) change in the Zambezi Region, Namibia between 1984 and 2010 using geospatial tools. Spatio-temporal dynamics of LULC...     

Assessment of land use land cover change impact on hydrological regime of a basin

The sustainability of water resources mainly depends on planning and management of land use; a small change in it may affect water yield largely, as both are linked through relevant hydrological processes, explicitly. However, human activities, especially a significant increase in population, in-migration and accelerated socio-economic activities, are constantly modifying the land use and land cover (LULC) pattern. The impact of such changes in LULC on the hydrological regime of a basin is of widespread concern and a great challenge to the water resource engineers. While studying these impacts, the issue that prevails is the selection of a hydrological model that may be able to accommodate spatial and temporal dynamics of the basin with higher accuracy. Therefore, in the present study, the capabilities of variable infiltration capacity hydrological model to hydrologically simulate the basin under varying LULC scenarios have been investigated. For the present analysis, the Pennar River Basin, Andhra Pradesh, which falls under a water scarce region in India, has been chosen. The water balance components such as runoff potential, evapotranspiration (ET) and baseflow of Pennar Basin have been simulated under different LULC scenarios to study the impact of change on hydrological regime of a basin. Majorly, increase in built-up (13.94% approx.) and decrease in deciduous forest cover (2.44%) are the significant changes observed in the basin during the last three decades. It was found that the impact of LULC change on hydrology is balancing out at basin scale (considering the entire basin, while routing the runoff at the basin outlet). Therefore, an analysis on spatial variation in each of the water balance components considered in the study was done at grid scale. It was observed that the impact of LULC is considerable spatially at grid level, and the maximum increase of 265 mm (1985–2005) and the decrease of 48 mm (1985–1995) in runoff generation at grid were estimated. On the contrary, ET component showed the maximum increase of 400 and decrease of 570 mm under different LULC change scenario. Similarly, in the base flow parameter, an increase of 70 mm and the decrease of 100 mm were observed. It was noticed that the upper basin is showing an increasing trend in almost all hydrological components as compared to the lower basin. Based on this basin scale study, it was concluded that change in the land cover alters the hydrology; however, it needs to be studied at finer spatial scale rather than the entire basin as a whole. The information like the spatial variation in hydrological components may be very useful for local authority and decision-makers to plan mitigation strategies accordingly.     

岩溶地区不同利用方式土壤土力学特性垂直变化特征

以黔中岩溶地区不同利用方式的土壤为研究对象,采用野外调查和室内试验相结合的方法,研究了土壤黏聚力c、内摩擦角φ及紧实度随不同土壤利用方式、不同土层深度的变化特征。结果表明:土壤黏聚力c总体随土层深度不断增大,在0-35 cm内受不同土壤利用方式的影响比较明显;土壤内摩擦角φ在0-50 cm土层内,呈“S”形变化,受母质影响显著,三种不同土壤利用方式总体变化趋势基本一致;林地、灌草地、坡耕地土壤在垂直剖面上都存在着上松下紧的状况,在0-20 cm内,坡耕地土壤紧实度均小于林地和灌草地,20 cm以下坡耕地和灌草地土壤紧实度基本一致,但均大于林地,三者均保持着不断增大的趋势。研究表明:植被生长对于改善土壤力学性能具有一定的影响。因而通过加强植被保护与管理和调整坡耕地利用方式是改善土壤力学性能,防治土壤侵蚀和控制石漠化的主要手段。      

Simulating climate change impact on soil erosion using RUSLE model <Emphasis Type="BoldItalic">−</Emphasis> A case study in a watershed of mid-Himalayan landscape

Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods, 2011–2040, 2041–2070, and 2071–2099, at large scale. Rainfall erosivity (R) was calculated for future periods using the SDSM downscaled precipitation data. ASTER digital elevation model (DEM) and Indian Remote Sensing data – IRS LISS IV satellite data were used to generate the spatial input parameters required by RUSLE model. A digital soil-landscape map was prepared to generate spatially distributed soil erodibility (K) factor map of the watershed. Topographic factors, slope length (L) and steepness (S) were derived from DEM. Normalised difference vegetation index (NDVI) derived from the satellite data was used to represent spatial variation vegetation density and condition under various land use/land cover. This variation was used to represent spatial vegetation cover factor. Analysis revealed that the average annual soil loss may increase by 28.38, 25.64 and 20.33% in the 2020s, 2050s and 2080s, respectively under A2 scenario, while under B2 scenario, it may increase by 27.06, 25.31 and 23.38% in the 2020s, 2050s and 2080s, respectively, from the base period (1985–2013). The study provides a comprehensive understanding of the possible future scenario of soil erosion in the mid-Himalaya for scientists and policy makers.