Average Soil Loss Research Articles

Assessment of Water-Induced Soil Erosion as a Threat to Natura 2000 Protected Areas in Crete Island, Greece

Water erosion is a major threat to biodiversity, according to the European Commission’s Soil Thematic Strategy, as it negatively affects soil structure, soil fertility and water availability for plants. The island of Crete (Southern Greece) has been characterized as a biodiversity hotspot including several Natura 2000 (N2K)-protected areas. The aim of this study was to model the soil loss rate in Crete regarding species richness, habitat types and their conservation status, as well as the MAES (Mapping and Assessment of Ecosystem and their Services) ecosystem types. To this end, the RUSLE soil erosion prediction model was implemented, using freely available geospatial data and cloud-computing processes. The estimated average soil loss in the study area was 6.15 t ha−1 y−1, while there was no significant difference between the terrestrial N2K (6.06 t ha−1 y−1) and non-N2K (6.19 t ha−1 y−1) areas. Notably, the natural habitats of principal importance for the conservation of biodiversity (referred to as “priority” areas), according to Annex I to Directive 92/43/EEC, are threatened by soil erosion with an estimated mean annual soil loss equal to 8.58 t ha−1 y−1. It is also notable that grasslands, heathland and shrubs and sparsely vegetated areas experienced the highest erosion rates among the identified MAES ecosystem types. The results showed that soil erosion is a serious threat to biodiversity in N2K-protected areas. Therefore, there is a need for systematic spatiotemporal monitoring and the implementation of erosion mitigation measures.

Soil erosion response to land use change in a mountainous rural area of Son La Province of Vietnam.

This study investigated the changes in soil erosion associated with land use change from 2000 to 2020 in a mountainous rural area. Land use change was detected using Landsat images and soil erosion was estimated using the revised universal soil loss equation (RUSLE). The results show that deforestation and fallow cultivation caused substantial soil loss, whereas conversion from uncultivated land to cropland reduced soil erosion. A conversion from 711ha cropland and 234ha forestland to uncultivated land increased the average soil loss from 17 ton·ha-1·year-1 to 42 ton·ha-1·year-1 and the area of eroded soil at the very high level from 276 to 1058ha between 2000 and 2010. In contrast, a wide expansion of cropland from 637ha uncultivated land decreased the average soil loss from 42 ton·ha-1·year-1 to 32 ton·ha-1·year-1 and the area of eroded soil at the very high level from 1058 to 690ha between 2010 and 2020. We suggest management measures such as forest protection, afforestation, reforestation, fruit tree development, and soil erosion control practices in coffee and maize cultivation to reduce soil erosion.

Study of soil erosion by using remote sensing and GIS techniques in Sone command area in Bihar, India

Soil erosion is caused by various reasons, but the land slope and poor land management are the main reasons. Identification of erosion-prone areas is the most important factor for agricultural planning and effective land management. This study includes an estimation of average annual soil loss in the Sone command area in Bihar and the preparation of spatially distributed soil erosion map for different land-use scenarios. The soil in the study area is generally clay loam. A well-known empirical equation i.e. RUSLE (Revised Universal Soil Loss Equation) has been used to estimate parameters and prepare spatially distributed maps. By using remote sensing and GIS techniques different soil loss parameters like rainfall erosivity (R), soil erodibility (K), slope length and steepness factor (LS), cover management factor (C) and conservation practice factor (P) are estimated and spatially distributed map of all these parameters are prepared. Average soil loss in the study area was found in the range 21 to 40 t.ha−1.yr−1 and the maximum value is found to be around 7000 t.ha−1.yr−1. It was also found that areas with high soil erosion rates are very low. Around 46% variation is observed between the maximum and minimum average soil loss rates.

Soil erosion and sediment yield assessment using RUSLE and GIS based approach in a forest watershed in Kandi region of Punjab

The Revised Universal Soil Loss Equation (RUSLE) integrated with the sediment delivery ratio (SDR) model employed in the GIS environment has been used to quantify the soil erosion and sediment yield for a small reservoir (Takarla dam) located in the Kandi region of Punjab, India. The catchment area of Takarla dam is 72.6 ha. The various layers including rainfall erosivity factor, soil erodibility factor, Slope length and steepness factor and crop management factor were prepared in ArcGIS to estimate the average annual soil loss. The SDR for the dam watershed was obtained by employing different empirical equations. The sedimentation rate and sediments collected in the dam was assessed for the last 20 years. The results of the present study revealed that the average annual soil loss varied from 0 to 12.8 t ha-1 year-1 for Takarla dam. The sediments deposited in the dam over 20 years estimated to be 142603.8 tonnes. The results of the present study may provide an insight for policy makers to design and execute the watershed management practices to reduce erosion hazard and sediment accumulation in the reservoirs.

Modelling and mapping of soil erosion in the north-eastern frontier Himalayan ranges of India using remote sensing and GIS

Soil erosion is a land degradable problem cause by natural resources. In context of North Eastern Himalayan ranges, it is a common soil degradation process due to fragile nature of soil and ecosystem. The aim of this study is to assess the soil erosion of Mahadevpur block, Namsai district of Arunachal Pradesh by RUSLE method using remote sensing and GIS environment. In this study, Sentinel 2 data of the study area was used to prepare land use/land cover (LU/LC) map by visual interpretation technique and ALOS digital elevation model (DEM) was used to develop slope, contour, flow direction and flow accumulation maps. Thematic raster layers of RUSLE factors (R, K, LS, C and P) were computed and used to estimate average annual soil loss by ArcGIS 10.3 software. The results showed that maximum area was (37.10%) under very slight soil loss class (< 5.0 t ha-1 yr-1). However, the extremely severe soil loss(> 80.0 t ha-1 yr-1) was observed in 7.0 % of the study area which was confined to terrain features such as lateral bar, meander scar, point bar, braided bar and channel bar. It was proved that, use of geospatial technologies in combination with RUSLE is a comprehensive approach, which helped in spatial assessment of soil erosion for better resource planning and taking up suitable conservation measures.

Soil erosion assessment in Ethiopia: A review

Soil erosion is a critical problem affecting rural livelihoods in Ethiopia. Large numbers of studies have been undertaken to identify critical areas of soil loss and prioritize conservation options. With the advancement of geospatial analysis techniques, the use of spatially distributed soil erosion assessment options has become increasingly common. The lack of database and documentation related to soil erosion assessment undermines coordination leading to duplication of efforts and in some instances generating contradictory results. The purpose of this study is to (1) review existing knowledge related to the extent and spatial distribution of soil erosion, (2) document the associated methods employed to assess soil erosion, and (3) assess the spatio-temporal dynamics of soil erosion and the determinant factors in Ethiopia. The review shows that there are about 170 peer-reviewed papers published in scientific journals related to soil erosion in Ethiopia. In those scientific articles, 15 different approaches were used to assess soil loss and sediment yield at different scales. Considering the data set, soil loss rate in Ethiopia varies between 0 and 220 t ha^–1 y^–1, and sediment yield ranges between 2 and 70 t ha^–1 y^–1. Based on the database, the national average gross soil erosion rate is estimated to be 38 t ha^–1 y^–1, while the net sediment yield is about 26 t ha^–1 y^–1. Generally, the observed gross soil loss is slightly lower than the mean value from cultivated lands reported in previous estimates (42 t ha^–1 y^–1) by Hurni (1993). The estimate made using the Revised Universal Soil Loss Equation gives the highest soil loss (51 t ha^–1 y^–1), while that based on field-survey approaches gives the lowest (20 t ha^–1 y^–1). The highest average net soil loss rate (40 t ha^–1 y^–1) is obtained using plot-level measurements, while the lowest (18 t ha^–1 y^–1) is obtained using the AGricultural Non-Point Source pollution model. The highest average soil erosion rate is observed in the moist agro-ecological zone (57 ± 7.8 t ha^–1 y^–1), while the lowest is obtained in the submoist (23.6 ± 2.7 t ha^–1 y^–1) following the arid zone (28.8 ± 6.5 t ha^–1 y^–1). The wide range of soil erosion estimates imply spatio-temporal dynamics of soil erosion in the country, which is mainly a reflection of heterogeneity of the various sites, mainly associated with different values of cover and management factors. Such knowledge can enable making informed conservation decisions by focusing on critical hotspots.

RUSLE-based soil erosion assessment and erosion control evaluation in the Kabul Watershed

The development and conservation of water and soil in the Kabul River Basin are critical for ensuring its sustainable economic, social, and environmental progress. Since the watershed drains across the international borders into the Indus River Basin, it is key for both up- and downstream countries to thoroughly plan their resource development and management. Due to relief, soil and climatic conditions, as well as the recent deforestation the Kabul River Basin has been witnessing significant soil erosion by water, indicating the need for analyzing its specifics and deploying proper control measures. This study was carried out using the combination of the Revised Universal Soil Loss Equation (RUSLE) Model and GIS techniques to investigate the gross soil loss rates and their spatial distribution inside the target basin. Thus, the annual average soil loss rate was estimated at 15.1 tons/ha/year, pointing to severe local soil erosion. As to its spatial distribution, according to the study up to 99% of mean annual soil loss rates fell within the tolerable (0-5 tons/acre/year) category. Considering the soil loss rates, local topography, and community-based participatory approaches, the authors recommend conducting a further detailed diagnostic analysis to inform and support subsequent control measures such as deforestation prevention, construction of small check dams, terracing, trenching in hilly areas, revegetation (reforestation) of open- and grasslands, and rainwater harvesting.

МЕТОДИ ДОСЛІДЖЕННЯ ЕРОЗІЙНОЇ ДЕГРАДАЦІЇ ҐРУНТІВ У БРОДІВСЬКОМУ РАЙОНІ

The study of the main factors causing erosive degradation of soils, the study of changes in soils under the influence of water erosion, and the modeling of existing and potential water washout of soil horizons determine the relevance of the conducted research. Analysis of morphologicalfeatures of degraded soils, laboratory analytical studies of their physical and physico-chemical properties, and with the help of GIS tools, modeling of soil washing under the influence of water erosion was carried out. The analysis of studies and publications on the analysis of the main factors that cause erosive degradation of soils, functional analysis and the implementation of modeling of soil washout under the influence of water erosion with the help of GIS tools showed that the issue of changes in background soils under the influence of water erosion and modeling of existing and potential water washout of soil horizons have received little attention in the scientific literature.The purpose of the article is a detailed study of the properties of gray forest, turf-carbonate and meadow soils, as well as the study of erosion processes within the studied territory.Cartographic and descriptive materials of the structure of land use in different years within this model area were studied, which made it possible to analyze the impact of approaches in land use on the intensification of water erosion and the degree of washing. Field and laboratory-analytical studies were conducted to study the morphological, physical, physico-chemical properties of the studied soils. A set of GIS maps has been developed. A 3D terrain model was created to determine the long-term average soil loss due to water erosion under a certain vegetation cover and with a certain tillage system, design and implementation of soil protection measures.For the first time, erosion processes are studied in the territory of the district in a temporal and spatial context. The obtained research results are a significant contribution to the development of the practical foundations of regional soil science. They are proposed to be used for improvement of soil diagnostics and classification; to develop measures to preserve and improve soil fertility; their protection from possible anthropogenic influence.

Landuse and landcover change assessment in the Upper Runde sub-catchment, Zimbabwe and possible impacts on reservoir sedimentation

This work assesses land cover changes on the Upper Runde sub-catchment, Zimbabwe, and associated effects on sedimentation rates and risks. The model was implemented using the common Geographic Information Systems tools. To achieve this objective, mean annual and monthly rainfall, as well as sediment data, were used (December 2016 and April 2017). Land use and land cover changes were assessed using time-series Landsat data acquired between the years 2000 and 2016. The Revised Universal Soil Loss (RUSLE) model was used to model sedimentation rates in the catchment. Land cover results showed that the catchment experienced significant (α = 0.05) changes during the period of monitoring. For example, forests and woodlands decreased by 39% and 23% between 2000 and 2016, respectively. Sedimentation results indicated that the catchment had an average sediment load of 6272 mg/l as compared to the expected maximum of 3000 mg/l. RUSLE soil loss simulation results showed an increase in average soil loss from 1.2 ton/ha/yr. in 2000 to 1.7 ton/ha/yr. in 2016 and an increase in sediment yield by 19.2% from 3476 mg/l in 2000–4144 mg/l in 2016. Overall, the findings of this study demonstrate that the catchment experiences high sedimentation. Therefore, catchment sediment monitoring and soil conservation actions should be a priority.

Soil Loss Estimation within the Nun River Basin using Revised Universal Soil Loss Equation (RUSLE) integrated in Geographic Information Systems (GIS)

River bank erosion can cause undesired river bank expansion, distortion of the river course thereby slowing the river velocity and hindering the water carrying capacity of the river. Slow velocity of the river course can result in fast sediment accretion and accumulation at the bottom of the river. If these trends are not checked, the river may wind down and at best begin to become a delta at its middle course. The focus of this study is to apply GIS and analytical RUSLE equation to estimate soil loss within the Nun Basin.&#x0D; Core sediment samples were collected from relatively undisturbed areas (nine different stations) using Uwitec Triple sediment cutter. The sediment samples were processed in the lab for sediment particle size analysis (PSA) and Pb-210 atmospheric deposition with age using alpha spectrophotometer. Spatial rainfall data of the study location were employed to generate the rainfall erosivity map in order to determine the erosivity factor (R). Particle size distribution analysis was validated using Scanning Electron Micrograph (SEM) and integrated with Geographic Information Systems (GIS) was employed to create the soil erodibility map which was subsequently used to determine the erodibility factor (K). The cover management factor (P) was determined using the land use land cover map and the resulting data were then employed to model the river bank erosion around the study area.&#x0D; Result of the study revealed that the maximum annual average soil loss rate was estimated to be 0.66 tons/ha. /year around the Nun River based on GIS application using the Revised Universal Soil Loss Equation (RUSLE).

Evaluating spatio-temporal soil erosion dynamics in the Winam Gulf catchment, Kenya for enhanced decision making in the land-lake interface

Soil erosion accelerated by poor agricultural practices, land degradation, deprived infrastructure development and other anthropogenic activities has important implications for nutrient cycling, land and lake productivity, loss of livelihoods and ecosystem services, as well as socioeconomic disruption. Enhanced knowledge of dynamic factors influencing soil erosion is critical for policymakers engaged in land use decision-making. This study presents the first spatio-temporal assessment of soil erosion risk modelling in the Winam Gulf, Kenya using the Revised Universal Soil Loss Equation (RUSLE) within a geospatial framework at a monthly resolution between January 2017 and June 2020. Dynamic rainfall erosivity and land cover management factors were derived from existing datasets to determine their effect on average monthly soil loss by water erosion. By assessing soil erosion rates with enhanced temporal resolution, it is possible to provide greater knowledge regarding months that are particularly susceptible to soil erosion and can better inform future strategies for targeted mitigation measures. Whilst the pseudo monthly average soil loss was calculated (0.80 t ha−1 month−1), the application of this value would lead to misrepresentation of monthly soil loss throughout the year. Our results indicate that the highest erosion rates occur between February and April (average 0.95 t ha−1 month−1). In contrast, between May and August, there is a significantly reduced risk (average 0.72 t ha−1 month−1) due to the low rainfall erosivity and increased vegetation cover as a result of the long rainy season. The mean annual gross soil loss by water erosion in the Winam Gulf catchment amounts to 10.71 Mt year−1, with a mean soil loss rate of 9.63 t ha−1 year−1. These findings highlight the need to consider dynamic factors within the RUSLE model and can prove vital for identifying areas of high erosion risk for future targeted investigation and conservation action.

Soil erosion assessment in Northwestern Morocco

In this study, the climate and land use change impact on soil water erosion in Loukkos watershed (northwestern Morocco) was assessed. This watershed is known by its intense agricultural activity and characterized by a Mediterranean climate. In order to quantify soil erosion, RUSLE model was used, combined with remote sensing and GIS technology under current and future climate scenarios predicted by the model CNRM-ALADIN63 for 2025–2055. The precipitation for the future climate period (2025–2055) was downscaled using CMhyd's statistical downscaling model (quantile-quantile).The results showed that the annual soil erosion rate averaged about 3.0 t, with a standard deviation of 6.2. In contrast, soil loss of less than 10 t ha−1 yr−1 occurred in 92% of the watershed. While overall erosion estimates show a medium erosion risk, attention and use of soil conservation practices is suggested for 7.1% of area has experienced soil erosion greater than 10 t ha−1 yr−1. Furthermore, the results revealed that average annual soil loss could increase by 3.9% and 8.4% respectively for medium and high Representative Concentration Pathways (RCP 4.5 and RCP 8.5) compared to the baseline period (1981–2017). Soil erosion assessment and land use change were determined to help implement future conservation measures for decision makers to develop appropriate strategies for long-term planning of water and soil resources, risk mapping and agriculture under various climate change scenarios.

An optimized method for extracting slope length in RUSLE from raster digital elevation

The Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) have been widely used for predicting average soil loss. Slope length is an important topographical parameter of the L factor in USLE/RUSLE. Among the widely studied GIS procedures for extracting slope length, the distributed watershed erosion slope length (DWESL) based on the unit contributing area estimation method, which considers two-dimensional runoff process and cutoff factors, is a relatively complete model for calculating slope length. Slope length in the DWESL model is primarily calculated using conventional flow direction algorithms such as D8, Dinf, MS and MFD-md. However, DWESL outputs require further improvement due to the errors in the usual estimates of the uphill contributing area and the effective contour length of discrete elements. Combined with a theoretical differential equation of specific catchment area on hillsides, the calculation of the DWESL model was optimized without estimating the uphill contributing area or the effective contour length for each cell. The proposed integration method based on the topographical features slope line, contour curvature and cutoff factors (ITF method) was used to extract slope length from the raster digital elevation. Slope length extracted using the ITF method had the smallest error in verification of mathematical surfaces (average RRMSE = 0.0573), and its spatial distribution was more consistent with the structure of the terrain surface for all test data, relative to the conventional flow direction algorithms in the original DWESL model. The proposed ITF method could provide a reference for predicting soil erosion using the USLE/RUSLE model.

Watershed-based soil erosion and sediment yield modeling in the Rib watershed of the Upper Blue Nile Basin, Ethiopia

Soil erosion is a major environmental problem that degrades topsoil and agricultural land productivity in mountainous areas such as Ethiopia. Soil erosion estimation is critical for the planning of erosion control plans in an agriculture-dependent economy. The current study used the Revised Universal Soil Loss Equation (RUSLE) model to evaluate the spatial distribution of annual soil loss and sediment yield in the Rib watershed. The main factors affecting soil erosion and sediment yield include vegetation cover, topography, soil, and climate. Soil erosion and sediment yield maps should be produced with these elements in account to describe locations with high soil erosion and sediment yield risks and to ensure improved erosion mitigation strategies in watersheds. The five input parameters were rainfall erosivity (R), soil erodibility (K), slope length-steepness (LS), cover-management factor (C), and support practice (P). The RUSLE model, when combined with remote sensing technology, has the ability to provide accurate and low-cost erosion and sediment yield risk maps in the Rib watershed. The estimated average annual soil loss was 25.53 t ha−1 yr−1. The soil loss rate was higher in the steeper and topographically dissected part of the watershed. Sediment delivery ratio ranges between 0 and 0.82. The outcome undoubtedly aids in the identification of priority locations for the adoption of sustainable land management and soil erosion mitigation conservation strategies.

Predicting the Impact of Future Land Use and Climate Change on Potential Soil Erosion Risk in an Urban District of the Harare Metropolitan Province, Zimbabwe

Monitoring urban area expansion through multispectral remotely sensed data and other geomatics techniques is fundamental for sustainable urban planning. Forecasting of future land use land cover (LULC) change for the years 2034 and 2050 was performed using the Cellular Automata Markov model for the current fast-growing Epworth district of the Harare Metropolitan Province, Zimbabwe. The stochastic CA–Markov modelling procedure validation yielded kappa statistics above 80%, ascertaining good agreement. The spatial distribution of the LULC classes CBD/Industrial area, water and irrigated croplands as projected for 2034 and 2050 show slight notable changes. For projected scenarios in 2034 and 2050, low–medium-density residential areas are predicted to increase from 11.1 km2 to 12.3 km2 between 2018 and 2050. Similarly, high-density residential areas are predicted to increase from 18.6 km2 to 22.4 km2 between 2018 and 2050. Assessment of the effects of future climate change on potential soil erosion risk for Epworth district were undertaken by applying the representative concentration pathways (RCP4.5 and RCP8.5) climate scenarios, and model ensemble averages from multiple general circulation models (GCMs) were used to derive the rainfall erosivity factor for the RUSLE model. Average soil loss rates for both climate scenarios, RCP4.5 and RCP8.5, were predicted to be high in 2034 due to the large spatial area extent of croplands and disturbed green spaces exposed to soil erosion processes, therefore increasing potential soil erosion risk, with RCP4.5 having more impact than RCP8.5 due to a higher applied rainfall erosivity. For 2050, the predicted wide area average soil loss rates declined for both climate scenarios RCP4.5 and RCP8.5, following the predicted decline in rainfall erosivity and vulnerable areas that are erodible. Overall, high potential soil erosion risk was predicted along the flanks of the drainage network for both RCP4.5 and RCP8.5 climate scenarios in 2050.

Effects of Ridge Tillage and Straw Returning on Runoff and Soil Loss under Simulated Rainfall in the Mollisol Region of Northeast China

Ridge tillage and straw returning are tillage practices widely used in the Chinese Mollisol region. However, the effects of ridge tillage combined with straw returning on runoff and soil loss control are still unclear. The objective of this study was to compare the effects of ridge tillage practices (contour ridge (CR)) and longitudinal ridge (LR), straw returning practices (straw on the furrow surface (SS)) and straw below the furrow (SB)), and their interactions on the runoff and soil loss by using simulated rainfall experiment. Two rainfall intensities (45 and 60 mm h−1) were applied to six combinations of ridge tillage and straw returning (contour ridge treatment, contour ridge with straw on the furrow surface treatment, contour ridge with straw below the furrow treatment, longitudinal ridge treatment, longitudinal ridge with straw on the furrow surface treatment, and longitudinal ridge with straw below the furrow treatment) on a 5° slope. The results showed that the phenomenon of ridge failure was common in the treatments with contour ridge. The average runoff rate and soil loss rate after ridge failure for treatments with contour ridge were separated 2.8 and 3.5 times greater than those of before failure at 60 mm h−1. However, the corresponding values were only 68.6% and 43.3% of the average value of longitudinal ridge treatment and longitudinal ridge with straw below the furrow treatment at 60 mm h−1. The water storage capacities of treatments with contour ridge remained constant when the rainfall intensity varied. The water storage capacities of contour ridge with straw on and below the furrow treatments were separate 3.0 and 1.0 mm less than that of contour ridge. However, longitudinal ridge with straw on the furrow surface treatment increased the runoff rate by 7.4% but reduced the soil loss rate by 72.6% when compared with longitudinal ridge treatment and longitudinal ridge with straw below the furrow treatment under the two rainfall intensities. Longitudinal with straw on the furrow surface treatment was more conducive to the stability of ridges, and there was no significant difference in total soil loss between longitudinal ridge with straw on the furrow surface treatment and treatments with contour ridge. This study was based on simulated rainfall conditions, and its adaptability under long-term positioning monitor in the field should be added in future.

Impacts of Land Cover and Greenness Change on Soil Loss and Erosion Risk in Damota Area Districts, Southern Ethiopia

Soil erosion is a key problem in Ethiopia in view of tropical climate, lack of vegetation, and landscape relief. Therefore, soil and water conservation (SWC) measures have been practiced, but their impacts on soil loss have not been estimated adequately. The RUSLE modeling was applied using satellite imageries, ASTER GDEM, rainfall, and soil data to estimate total annual soil loss for a 100 km2 hilly and highly populated area in Ethiopia. Soil loss decreased in the Damota districts from 21 to 13 million tons from 2000 to 2020. Similarly, the average annual soil loss decreased by 36%. Very slight-risk areas (&lt; 5 t ha−1 yr−1) increased from 42.66 to 53.72%, and very high-risk areas (&gt; 50 t ha−1 yr−1) decreased from 12 to 5%. Soil and water conservation measures showed an important implication against soil erosion through improved land cover and landscape greenness. However, still, the rate of soil erosion is high compared to the soil loss tolerance of 1–6 t ha−1 yr−1 for the Ethiopian highlands.

Spatial soil loss risk assessment for priority intervention using GIS and remote sensing techniques: A case of Neri Watershed Southwestern Ethiopia

Soil loss by runoff is a severe and continuous ecological problem in Neri watershed. It affects agricultural production, drinking water quality, ecosystem health, and landscape aesthetics. This study was conducted to assess spatial risk of soil by estimating the average annual soil loss, and creating a soil erosion hazard map for this watershed. Revised Universal Soil Loss Equation (RUSLE) model supported by a GIS framework was used. To this end, data for the model parameters were derived from, a digital elevation model (DEM) of (30*30 m), thirty years (1988-2017) rainfall data at rain gauge stations, soil erodibility data from field soil samples, Landsat-8 satellite image for cover management and conservation support practices. Once raster layer of the input parameters created, overlay analysis was carried to assess the spatial distribution of soil loss. The estimated annual soil loss varies from 0 to 465.16 t ha−1 yr−1 with a mean annual soil loss of 9.95 t ha−1 yr−1. The empirical analysis also confirmed that the watershed losses a total of about 463365.46 t of soil annually. Out of the total area; 54.9% of the watershed was categorized below moderate classes and the remaining 45.1% of land area was classified under high to very high classes, which is about several times the maximum tolerable soil loss rate. Based on the classification of soil loss hazard map, six out of eleven Neri sub-watersheds need prior intervention in terms of integrated cover-management and mechanical conservation measures. Furthermore, model results can be refined by analyzing along with sub-watersheds level real time monitoring for conservation practices.

Prioritization of Watershed Using Remote Sensing and Geographic Information System

Soil erosion is becoming a major concern at the watershed scale for the environment, natural resources, and sustainable resource management. Therefore, the estimation of soil loss through this phenomenon and the identification of critical soil erosion-prone areas are considered to be key tasks in the soil conservation programme for the design and implementation of best management practices for specific regions or areas. In the present study, revised universal soil loss equation (RUSLE) modelling is combined with remote sensing (RS) and geographical information system (GIS) techniques and used to predict soil erosion and the prioritization of watersheds in Nainital district Uttarakhand, India. For the estimation of soil loss, different factors, namely, rainfall-runoff erosivity (R) factor, soil erodability (K) factor, slope length steepness (LS) factor, cover management (C) factor, and the erosion control practices (P) factor were computed. The data on various other aspects such as land use/land cover (LU/LC), the digital elevation model (DEM), slope, contours, drainage network, soil texture, organic matter, and rainfall were integrated to prepare a database for the RUSLE equation by employing ENVI &amp; QGIS software. The results showed that a major portion (70.26%) of Nainital district is covered with forest, followed by area under fallow and agricultural land. Annual average soil loss ranged between 20 to 80 t ha−1 yr−1 in the study area. Out of 50 watersheds in the study area, 7 watersheds were given top priority for conserving natural resources, while 11 watersheds, mostly in the east-central part of Nainital, were kept under the next priority category. Only 4 watersheds of the total were given lowest priority. Moreover, it was concluded that major portions of Nainital district were in a severely prone category of soil erosion, and therefore required immediate action plans to check soil erosion and evade the possibility of landslides.

Land Use and Land Cover Changes and Its Impact on Soil Erosion in Stung Sangkae Catchment of Cambodia

Agricultural expansion and urban development without proper soil erosion control measures have become major environmental problems in Cambodia. Due to a high population growth rate and increased economic activities, land use and land cover (LULC) changes will cause environmental disturbances, particularly soil erosion. This research aimed to estimate total amounts of soil loss using the Revised Universal Soil Loss Equation (RUSLE) model within a Geographic Information System (GIS) environment. LULC maps of Japan International Cooperation Agency (JICA) 2002 and Mekong River Commission (MRC) 2015 were used to evaluate the impact of LULC on soil erosion loss in Stung Sangkae catchment. LULC dynamics for the study periods in Stung Sangkae catchment showed that the catchment experienced a rapid conversion of forests to paddy rice fields and other croplands. The results indicated that the average soil loss from the catchment was 3.1 and 7.6 t/ha/y for the 2002 and 2015 periods, respectively. The estimated total soil loss in the 2002 and 2015 periods was 1.9 million t/y and 4.5 million t/y, respectively. The soil erosion was accelerated by steep slopes combined with the high velocity and erosivity of stormwater runoff. The spatial distribution of soil loss showed that the highest value (14.3 to 62.9 t/ha/y) was recorded in the central, southwestern and upland parts of the catchment. It is recommended that priority should be given to erosion hot spot areas, and appropriate soil and water conservation practices should be adopted to restore degraded lands.