RETRACTED ARTICLE: Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed,Guizhou Province,China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

A GIS-based soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) (Lebna watershed,Cap Bon,Tunisia)

Natural Hazards - 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...     

Assessment of soil erosion in a tropical mountain river basin of the southern Western Ghats,India using RUSLE and GIS

Revised Universal Soil Loss Equation(RUSLE) model coupled with transport limited sediment delivery(TLSD) function was used to predict the longtime average annual soil loss, and to identify the critical erosion-/deposition-prone areas in a tropical mountain river basin, viz., Muthirapuzha River Basin(MRB; area=271.75 km~2), in the southern Western Ghats, India. Mean gross soil erosion in MRB is 14.36 t ha~(-1) yr~(-1), whereas mean net soil erosion(i.e., gross erosion-deposition) is only 3.60 t ha~(-1) yr~(-1)(i.e., roughly 25% of the gross erosion). Majority of the basin area(~86%) experiences only slight erosion(5 t ha~(-1) yr~(-1)), and nearly 3% of the area functions as depositional environment for the eroded sediments(e.g., the terraces of stream reaches, the gentle plains as well as the foot slopes of the plateau scarps and the terrain with concordant summits). Although mean gross soil erosion rates in the natural vegetation belts are relatively higher, compared to agriculture, settlement/built-up areas and tea plantation, the sediment transport efficiency in agricultural areas and tea plantation is significantly high,reflecting the role of human activities on accelerated soil erosion. In MRB, on a mean basis, 0.42 t of soil organic carbon(SOC) content is being eroded per hectare annually, and SOC loss from the 4th order subbasins shows considerable differences, mainly due to the spatial variability in the gross soil erosion rates among the sub-basins. The quantitative results, on soil erosion and deposition, modelled using RUSLE and TLSD, are expected to be beneficial while formulating comprehensive land management strategies for reducing the extent of soil degradation in tropical mountain river basins.     

Soil erosion assessment and its verification using the Universal Soil Loss Equation and Geographic Information System: a case study at Boun,Korea

This study is aimed at the evaluation of the hazard of soil erosion and its verification at Boun, Korea, using a Geographic Information System (GIS) and remote sensing. Precipitation, topographic, soil, and land use data were collected, processed, and constructed into a spatial database using GIS and remote sensing data. Areas that had suffered soil erosion were analysed and mapped using the Universal Soil Loss Equation (USLE). The factors that influence soil erosion are rainfall erosivitiy (R) from the precipitation database, soil erodibility (K) from the soil database, slope length and steepness (LS) from the topographic database, and crop and management (C) and conservation supporting practices (P) from the land use database. Land use was classified from Landsat Thematic Mapper satellite images. The soil erosion map verified use of the landslide location data. Landslide locations were identified in the Boun area from interpretation of aerial photographs and field surveys.     

贵州省乌江流域土壤侵蚀模拟——基于GIS、RUSLE和ANN技术的研究

本研究在GIS技术支撑下选择RUSLE模型作为基础模型,估算乌江流域20世纪80年代和90年代年均土壤侵蚀量,结合ANN技术,预测2001—2010年乌江流域的土壤侵蚀量,分析了该流域近30年来土壤侵蚀动态变化规律,以期为研究区土壤侵蚀防治工作提供理论依据。研究结果表明:应用RUSLE模型计算乌江流域年均土壤侵蚀模数,计算结果和以往土壤侵蚀调查估计的结果比较吻合,但由于RUSLE模型不计算重力侵蚀,因此计算结果仍与实测输沙模数有所出入。90年代潜在土壤侵蚀模数比80年代高,流域潜在土壤侵蚀呈增加趋势,其中三岔河流域和马蹄河/印江河流域年均潜在土壤侵蚀模数最高。3种主要土地覆被类型中,林地的土壤保持量最大,耕地次之,草地最少,这与非喀斯特地区在水土保持效果上通常林地草地旱地的结论有所不同。通过构建BP神经网络,预测得到乌江流域2001—2010年土壤侵蚀模数,结果显示,21世纪前10年,流域土壤侵蚀模数大幅降低,流域年均土壤侵蚀模数由90年代的23.13 t/(hm2·a)降低为1.01 t/(hm2·a)。三岔河流域的水土流失得到了控制,黔西、金沙、息烽、修文、贵阳、平坝、思南、石阡、沿河和松桃等县市应是"十二五"期间的水土流失重点治理对象。     

Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy)

Soil erosion by water is a serious problem in southern Italy, particularly in Sicily which is one of the Italian administrative regions prone to desertification. Soil erosion not only affects soil quality, in terms of agricultural productivity, but also reduces the availability of water in reservoirs. This study was conducted in the Comunelli catchment in south-central Sicily, to predict potential annual soil loss using the revised universal soil loss equation (RUSLE) and to test the reliability of this methodology to predict reservoirs siltation. The RUSLE factors were calculated for the catchment using survey data and rain gauge measurement data. The R-factor was calculated from daily, monthly and annual precipitation data. The K-factor was calculated from soil samples collected in May and November 2004. The LS topographic factor was calculated from a 20 m digital elevation model. The C- and P-factors, in absence of detailed data, were set to 1. The results were compared with those obtained from another soil loss estimation method based on ¹³⁷Cs and with the soil loss estimated from the sediment volume stored in the Comunelli reservoir between 1968 and 2004.     

Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed,Nan Province,Thailand

Land degradation is still a very common problem in the mountains of Asia because of inappropriate land use practice in steep topography. Many studies have been carried out to map shifting cultivation and areas susceptible to soil erosion. Mostly, estimated soil loss is taken as the basis to classify the level of soil loss susceptibility of area. Factors that influence soil erosion are: rainfall erosivity, soil erodibility, slope length and steepness, crop management and conservation practices. Thus the reliability of estimated soil loss is based on how accurately the different factors were estimated or prepared. As each and every small pixel of our earth surface is different from one area to another, the manner in which the study area was discretized into smaller homogenous sizes and how the most accurate and efficient technique were adopted to estimate the soil loss are very important. The purpose of this study is to produce erosion susceptibility maps for an area that has suffered because of shifting cultivation located in the mountainous regions of Northern Thailand. For this purpose, an integrated approach using RS and GIS-based methods is proposed. Data from the Upper Nam Wa Watershed, a mountainous area of the Northern Thailand were used. An Earth Resources Data Analysis System (ERDAS) imagine image processor has been used for the digital analysis of satellite data and topographical analysis of the contour data for deriving the land use/land cover and the topographical data of the watershed, respectively. ARCInfo and ARCView have been used for carrying out geographical data analysis. The watershed was discretized into hydrologically, topographically, and geographically homogeneous grid cells to capture the watershed heterogeneity. The soil erosion in each cell was calculated using the universal soil loss equation (USLE) by carefully determining its various parameters and classifying the watershed into different levels of soil erosion severity. Results show that during the time of this study most of the areas under shifting cultivation fell in the highest severity class of susceptibility.     

Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India

Drought is a natural phenomenon posing severe implications for soil, groundwater and agricultural yield. It has been recognized as one of the most pervasive global change drivers to affect the soil. Soil being a weakly renewable resource takes a long time to form, but it takes no time to degrade. However, the response of soil to drought conditions as soil loss is not manifested in the existing literature. Thus, this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India. MODIS remote sensing data was utilized for driving drought indices during 2000–2019. Firstly, we constricted Temperature condition index (TCI) and Vegetation Condition Index (VCI) from Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) derived from MODIS data. TCI and VCI were then integrated to determine the Vegetation Health Index (VHI). Revised Universal Soil Loss Equation (RUSLE) was utilized for estimating soil loss. The relationship between drought condition and vegetation was ascertained using the Pearson correlation. Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during 2000–2019. The mean frequency of the drought occurrence was 7.95 months. The average soil erosion in the sub-basin was estimated to be 9.88 t ha^?1 year^?1. A positive relationship was observed between drought indices and soil erosion values (r value being 0.35). However, wide variations were observed in the distribution of spatial correlation. Among various factors, the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin. Thus, the study calls for policy measures to lessen the impact of drought and soil erosion.     

Multi-temporal annual soil loss risk mapping employing Revised Universal Soil Loss Equation (RUSLE) model in Nun Nadi Watershed, Uttrakhand (India)

The present comparative study is multi-temporal in nature. The Revised Universal Soil Loss Equation (RUSLE), remote sensing, and GIS were used to model the soil loss estimation for soil conservation and vegetation rehabilitation in Nun Nadi watershed for the years 2000 and 2009. The estimated mean soil loss for the year 2000 and 2009 is 3,283.11 and 1,419.39 Mg?ha^?1 year^?1, respectively. The study finds that about 80 % area has low or least risk of erosion and about 7 % is exposed to high or very high risk which indicates the improvement in terms of soil loss if we compare the data of both the time periods. The findings show that the rainfall, LULC change, and elevation are the main responsible factors for the soil loss in Nun Nadi watershed. Conservation measures have been adopted; however, the problem still remains serious and demands urgent attention.     

Modeling runoff and soil erosion in a catchment area, using the GIS, in the Himalayan region, India

Remote sensing data and GIS techniques have been used to compute runoff and soil erosion in the catchment area along the NH-1A between Udhampur and Kud covering an area of approximately 181 km². Different thematic layers, for example lithology, a landuse and landcover map, geomorphology, a slope map, and a soil-texture map, were generated from these input data. By use of the US Soil Conservation Service curve number method, estimated runoff potential was classified into five levels—very low, low, moderate, high, and very high. Data integration was performed by use of the weighting rating technique, a conventional qualitative method, to give a runoff potential index value. The runoff potential index values were used to delineate the runoff potential zones, namely low, moderate, high, and very high. Annual spatial soil loss estimation was computed using the Morgan–Morgan–Finney mathematical model in conjunction with remote sensing data and GIS techniques. Greater soil erosion was found to occur in the northwestern part of the catchment area. When average soil loss from the catchment area was calculated it was found that a maximum average soil loss of more than 20 t ha⁻¹ occurred in 31 km² of the catchment area.     

Water-Borne Erosion Estimation Using the Revised Universal Soil Loss Equation (RUSLE) Model Over a Semiarid Watershed: Case Study of Meskiana Catchment,Algerian-Tunisian Border

Geotechnical and Geological Engineering - Soil erosion is one of the major environmental problems in the Middle East and North Africa (MENA) region. Favoured by the harmful effects of climate...     

Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed,northwest Turkey

This study was aimed at predicting soil erosion risk in the Buyukcekmece Lake watershed located in the western part of Istanbul, Turkey, by using Revised Universal Soil Loss Equation (RUSLE) model in a GIS framework. The factors used in RUSLE were computed by using different data obtained or produced from meteorological station, soil surveys, topographic maps, and satellite images. The RUSLE factors were represented by raster layers in a GIS environment and then multiplied together to estimate the soil erosion rate in the study area using spatial analyst tool of ArcGIS 9.3. In the study, soil loss rate below 1 t/ha/year was defined as low erosion, while those >10 t/ha/year were defined as severe erosion. The values between low and severe erosion were further classified as slight, moderate, and high erosion areas. The study provided a reliable prediction of soil erosion rates and delineation of erosion-prone areas within the watershed. As the study revealed, soil erosion risk is low in more than half of the study area (54%) with soil loss <1 t/ha/year. Around one-fifth of the study area (19%) has slight erosion risk with values between 1 and 3 t/ha/year. Only 11% of the study area was found to be under high erosion risk with soil loss between 5 and 10 t/ha/year. The severe erosion risk is seen only in 5% of the study area with soil loss more than 10 t/ha/year. As the study revealed, nearly half of the Buyukcekmece Lake watershed requires implementation of effective soil conservation measures to reduce soil erosion risk.     

Tertiary extension of continental crust and uplift of Psiloritis metamorphic core complex in the central part of the Hellenic Arc (Crete,Greece)

Kinematic analysis of the deformation in central Crete suggests that the structural evolution and exhumation of the high pressure/low temperature (HP/LT) rocks outcropping at the Mount Psiloritis metamorphic core complex are associated with a regional, Miocene, north-south extension and thinning of the continental crust. This tectonic regime developed under bulk coaxial strain conditions, with ductile deformation in the lower and brittle deformation in the upper crust, and followed, on the decompressional path, a north-south compression associated with a HP/LT metamorphism in the lower crust. This compressional event took place during Oligocene—Early Miocene and led to overthickening of the accretionary wedge in the Hellenic Arc. An east-west directed compression accompanied, in the final stages, the Miocene north-south extension of the continental crust.     

Geological mapping and mining prospecting in the Aouli inlier (Eastern Meseta,Morocco) based on remote sensing and geographic information systems (GIS)

Landsat 8 Oli, ASTER, and Sentinel 2A satellite images processing was used to map geological formations, lineaments and hydrothermal alteration minerals in the Aouli inlier, as a case study to illustrate the application of digital images processing and Geographic Information System (GIS) in geological mapping and mining prospecting. Principal Component Analysis (PCA) applied to the Landsat images allowed good lithological discrimination and contributed to the updating of available geological maps. The Automatic lineament extraction from Sentinel images revealed the main tectonic structures affecting Aouli inlier. The ratio bands (b5+b7)/b6 and the false color composite (b4/b6, b2/b1, b3/b2) allowed the hydrothermal alteration minerals mapping from Aster images. Combined with available geological data and field observations, the satellite derived data were integrated and analyzed in a GIS software to establish mining prospecting guides. The results showed that the anomaly zones are intimately linked to NNE –SSW and NW –SE oriented faults and to highly fractured areas developing argillic and Fe rich alterations. Verified via field survey, this approach was successfully applied to the Aouli inlier to rapidly target potential areas to be explored in the tactical phase. This provides a model for future prospecting efforts for similar mineral deposits in other areas.©2022 China Geology Editorial Office.     

Study on the oasis landscape fragmentation in northwestern China by using remote sensing data and GIS: a case study of Jinta oasis

The purpose of this study is to investigate the oasis landscape fragmentation in northwestern China’s arid regions. Landscape maps of Jinta oasis were compiled by using GIS based on Landsat TM data of 1990 and 2000. Landscape indexes for evaluating fragmentation are patch area, patch density, corridor density and split index. Results indicated many difference. First, between the years 1990 and 2000, the landscape fragmentation in Jinta oasis decreased slightly. Second, the area of the matrix decreased at the class level. The landscape fragmentation of the matrix (bare soil) increased as a result of increased influence of human activities on matrix and was opposite to the irrigated farmland whose area is larger and more aggregated in 2000 than in 1990. Third, dense corridor system is one of the most prominent characteristics of the arid regions. It is one of the key factors resulting in the landscape fragmentation; especially the fragmentation within the same patch types. The corridor density of irrigated farmland, residential area and forestland were quite large in Jinta oasis both in 1990 and 2000. The pattern of Jinta oasis is characterized by agricultural oasis embedded in Gobi and in the desert, where the ecosystem was disturbed strongly by the intense human activities.     

Groundwater study using remote sensing and geographic information systems (GIS) in the central highlands of Eritrea

Remote sensing, evaluation of digital elevation models (DEM), geographic information systems (GIS) and fieldwork techniques were combined to study the groundwater conditions in Eritrea. Remote sensing data were interpreted to produce lithological and lineament maps. DEM was used for lineament and geomorphologic mapping. Field studies permitted the study of structures and correlated them with lineament interpretations. Hydrogeological setting of springs and wells were investigated in the field, from well logs and pumping test data. All thematic layers were integrated and analysed in a GIS. Results show that groundwater occurrence is controlled by lithology, structures and landforms. Highest yields occur in basaltic rocks and are due to primary and secondary porosities. High yielding wells and springs are often related to large lineaments, lineament intersections and corresponding structural features. In metamorphic and igneous intrusive rocks with rugged landforms, groundwater occurs mainly in drainage channels with valley fill deposits. Zones of very good groundwater potential are characteristic for basaltic layers overlying lateritized crystalline rocks, flat topography with dense lineaments and structurally controlled drainage channels with valley fill deposits. The overall results demonstrate that the use of remote sensing and GIS provide potentially powerful tools to study groundwater resources and design a suitable exploration plan.An erratum to this article can be found at     

Groundwater study using remote sensing and geographic information systems (GIS) in the central highlands of Eritrea

Remote sensing, evaluation of digital elevation models (DEM), geographic information systems (GIS) and fieldwork techniques were combined to study the groundwater conditions in Eritrea. Remote sensing data were interpreted to produce lithological and lineament maps. DEM was used for lineament and geomorphologic mapping. Field studies permitted the study of structures and correlated them with lineament interpretations. Hydrogeological setting of springs and wells were investigated in the field, from well logs and pumping test data. All thematic layers were integrated and analysed in a GIS. Results show that groundwater occurrence is controlled by lithology, structures and landforms. Highest yields occur in basaltic rocks and are due to primary and secondary porosities. High yielding wells and springs are often related to large lineaments, lineament intersections and corresponding structural features. In metamorphic and igneous intrusive rocks with rugged landforms, groundwater occurs mainly in drainage channels with valley fill deposits. Zones of very good groundwater potential are characteristic for basaltic layers overlying lateritized crystalline rocks, flat topography with dense lineaments and structurally controlled drainage channels with valley fill deposits. The overall results demonstrate that the use of remote sensing and GIS provide potentially powerful tools to study groundwater resources and design a suitable exploration plan.The online version of the original article can be found at     

A methodology using GIS, aerial photos and remote sensing for loss estimation and flood vulnerability analysis in the Supersano-Ruffano-Nociglia Graben, southern Italy

The impact of calamitous meteoric events and their interaction with the geological and geomorphological environment represent a current problem of the Supersano-Ruffano-Nociglia Graben in southern Italy. Indeed, severe floods take place on a frequent basis not only in autumn and winter, but in summer also. These calamities are not only triggered by exceptional events, but are also amplified by peculiar geological and morpho-structural characteristics of the Graben. Flooding often affects vast agricultural areas and consequently, water-scooping machines cannot remove the rainwater. These events cause warnings and emergency states, involving people as well as socio–economic goods. This study represents an application of a vanguard technique for loss estimation and flood vulnerability analysis, integrating a geographic information system (GIS) with aerial photos and remote sensing methods. The analysis results clearly show that the Graben area is potentially at greatest flood vulnerability, while along the Horsts the flood vulnerability is lower.