Sediment Yield and Soil Loss Estimation Using GIS Based Soil Erosion Model: A Case Study in the MAN Catchment, Madhya Pradesh, India (original) (raw)
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Soil erosion is one of the serious issues threatening the environment. This degrading phenomenon deteriorates the soil fertility and drastically affects the agricultural practices. As a consequence, the productivity of soil is affected unquestionably. In this regard, there is a need to take up conservation and management measures which can be applied to check further soil erosion. Even though, soil erosion is a mass process spread across the watershed, it is not economically viable to implement conservation techniques to the entire watershed. However, a method is a prerequisite to identify the most vulnerable areas and quantify the soil erosion. In this context, Revised Universal Soil Loss Equation (RUSLE) has been adopted to estimate soil erosion in the semi-arid Andipatti Watershed of Tamil Nadu, India. This model takes into consideration the parameters including runoff-rainfall erosivity factor (R), soil erodability Factor (K), topographic factor (LS), cropping management factor (C), and support practice factor (P). All these layers are prepared in a geographical information system (GIS) platform using various data sources and data preparation methods. The results of the study indicate that the annual average soil loss within the watershed is about 6 t/ha/yr (metric ton per hectare per year). Higher soil erosion is observed in the landuse classes of gullied wasteland, open scrub forest and degraded plantation. The soil erosion risk is extremely higher on the steep slopes and adjoining foot hills. Based on the average soil erosion values of different landuse classes and characteristics of land, a proposed landuse map was prepared. The estimated soil erosion and the proposed landuse map could be an effective input for drawing sustainable watershed development measures.
SN applied sciences, 2023
Assessment and estimation of soil loss is a fundamental aspect of land and water resource conservation and management practices as it provides necessary information in the course of watershed-level development of a region. The soil loss model of Wischmeier and Smith, popularly known as the Revised Universal Soil Loss Equation, was selected to estimate soil loss in the lower Kulsi river basin due to its simplicity, versatility, and flexibility nature method in the Geographic information system platform. Most original governmental datasets, mainly daily gauge rainfall from 2009 to 2018, satellite images for land use land cover, digital elevation model of Shuttle Radar Topographic Mission for topographic factor, and National Bureau of Soil Survey and Land-use Planning, India soil map were utilized to estimate the average annual soil erosion. The estimated average annual soil erosion ranges from 0.0 to 6.45 thousand t ha −1 y −1 , grouped into low, moderate, high, and very high risk of soil erosion. A basin area of 36.235 km 2 (1.85%) basin area was identified as high to very high zones of soil erosion risk and needed immediate conservation measures to reduce the erosion risk. Article highlights (1) The soil loss estimate is vital for taking appropriate anti-erosion measures and enhancing surface runoff in identifying priority areas. (2) The GIS-based RUSLE model is a simple and widely acceptable soil loss estimating model for the watershed in a tropical monsoon climate. (3) Rainfall erosivity, conservation practice, and topographic factors of the basin contribute more to soil erosion.
A comparative study of soil erosion models based on GIS and remote sensing
ISH Journal of Hydraulic Engineering, 2020
In most of the developing and underdeveloped countries, the demand of crop is not fulfilled because of less production, and it is further decreasing due to soil erosion. The sheet erosion affects the fertility of soil, and due to other erosion like rill and gully erosion, the land area is reduced. The silent hazard namely soil erosion is reducing the crop production and has become one of the alarming problems of the whole world. Advancement of technology and development of various models based on remote sensing and GIS has played a significant role in the estimation of soil erosion in the catchment using various empirical models. Still it is a challenge to apply those models and investigate soil erosion-prone areas and quantify erosion. In this study, Universal Soil Loss Equation (USLE) and the Unit Stream Power based Soil Erosion/Deposition (USPED) models were used to identify soil erosion in the Upper Lake, Bhopal in India. Different factors affecting soil erosion were studied, and maps of soil loss due to USLE and USPED models were generated. The soil loss using USPED model was found to be 764481.5 tonnes/yr, whereas using USLE model it was found to be 711700 tones/yr.
Estimation of soil erosion using Revised Universal Soil Loss Equation and GIS
A comprehensive methodology that integrates Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) techniques were 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 282.2 t/h/yr with a close relation to grassland areas, degraded forests and deciduous forests on the steep side-slopes. 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.
AIMS Geosciences, 2020
Soil erosion is one of the major environmental problems in northeast India, and identifying areas prone to severe erosion loss is therefore very crucial for sustainable management of different land uses. Tuirial river basin, where shifting cultivation is a major land use, is prone to severe soil erosion and land degradation, linked to its fragile geo-morpho-pedological characteristics. Though several models are available to estimate soil erosion the Revised Universal Soil Loss Equation (RUSLE) is more appropriate and practical model that can be applied at a local or regional level. The objective of the study was to estimate annual soil loss in the upper Tuirial river basin by using RUSLE where various parameters such as rainfall erosivity factor (R), soil erodibility factor (K), slope length (L), slope steepness factor (S), crop management factor (C) and practice management factor (P) were taken into consideration. Land use land cover (LULC) derived from Satellite data of Sentinel 2A Digital Elevation Model (DEM) were integrated into the model. Our results revealed that the river basin has an average annual soil loss of 115.4 Mg ha −1 yr −1 , and annual sediments loss to the tune of 6.161 million Mg yr −1 from the basin. About one-fourth (24.78%) of the total basin could be classed as very high to very severe soil erosion prone area that need immediate conservation measures. Besides, the erosional activities were perceived directly proportional with the slope values in the basin. However, regardless of the rugged mountainous terrain of the basin, the unscientific practice of shifting cultivation, associated with high intensity of rainfall is the principal cause of soil erosion. The results of the study is expected to contribute to adaptation of appropriate soil and water conservation measures in the basin 526 AIMS Geosciences Volume 6, Issue 4, 525-544. area, and similar studies may also be extended to other unexplored areas for proper watershed management in state of Mizoram.
ISPRS International Journal of Geo-Information
Land degradation caused by soil erosion is considered among the most severe problems of the 21stcentury. It poses serious threats to soil fertility, food availability, human health, and the world ecosystem. The purpose of the study is to make a quantitative mapping of soil loss in the Chitral district, Pakistan. For the estimation of soil loss in the study area, the Revised Universal Soil Loss Equation (RUSLE) model was used in combination with Remote Sensing (RS) and Geographic Information System (GIS). Topographical features of the study area show that the area is more vulnerable to soil loss, having the highest average annual soil loss of 78 ton/ha/year. Maps generated in the study show that the area has the highest sediment yield of 258 tons/ha/year and higher average annual soil loss of 450 tons/ha/year. The very high severity class represents 8%, 16% under high, 21% under moderate, 12% under low, and 13% under very low soil loss in the Chitral district. The above study is help...
Mapping soil erosion in a river basin of madhaya pradesh using remote sensing and gis
For the protection of the land from erosion, it is essential to measure and locate soil loss. Revised Universal Soil Loss Equation, RUSLE, can estimate soil erosion potential on cell-by-cell raster-based GIS data frame. For the present work, Hiran River at Patan, Madhya Pradesh was selected for estimation of soil loss. The study aimed for qualitative assessment of soil erosion prone areas by calculating soil loss using RUSLE. Models, like RUSLE, require less data making soil erosion estimation practicable within larger scales as monthly precipitation data; digital elevation model, soil map, land use and land cover types and slope length and steepness were used to determine the RUSLE values. One of the most important parameters of RUSLE is C factor that represents effects of vegetation and other land covers. Estimating C factor in this study involves the use of Normalized Difference Vegetation Index (NDVI), an indicator which shows vegetation cover, using the regression equation in Spatial Analyst tool of ArcGIS 10.1 software. The Quantitative assessment has effectively been accomplished by calculating rates of soil loss and developing soil loss severity maps of the study areas using soil loss equation model RUSLE. This study has demonstrated GIS as a valuable tool in determining soil erosion and assisting the estimation of soil loss.
Soil erosion is one of the major factors affecting sustainability of agricultural production in watershed. The objective of this paper is to estimate soil loss using the universal soil loss equation (USLE) model and GIS and to suggest soil conservation practices in Moridhal watershed. Soil loss was estimated by USLE. In addition, measurements of randomly selected soil and water conservation structures were done at four physiographic units of watershed. The erodibility of the studied soils was assessed by computing various erodibility indices like clay ratio, silt clay ratio, modified clay ratio, dispersion ratio, erosion ratio and erosion index. The soil loss of watershed was varied from very slight to very severe (range 0.87–67.77 t ha-1 yr-1). Among the physiographic units, the soil loss in the upper piedmont plain area was moderately severe to very severe with a value varying from 19.9–67.8 t ha-1 yr-1. The dispersion ratio of the soils varied from 0.06 to 1.18. It was observed t...
An integrated method has been adopted to estimate soil loss in a plateau and plateau fringe river basin where soil erosion is significant. The integration of Revised Universal Soil Loss Equation model and geographical Information technology has been used for soil loss estimation. In GIS platform, the overlay of rainfall-runoff erosivity factor, soil erodibility factor, slope length factor, slope steepness factor, cover and management factor, support and conservation practices factor results that the high amount of soil loss (more than 100 t ha -1 year -1 ) is significantly low and occupies 0.08% of the entire study area. High soil loss in upstream of the basin has a close relation to LS and K factor and drainage density. As a result of soil loss in the upper catchment areas, reservoir capacity has been depleted both in dead and live storage space. It is concluded that soil erosion has a significant impact on plateau fringe areas and the estimation of soil loss is an essential input for the adoption of proper land use planning and development strategies.
Recent Research in Science and Technology, 2011
In order to assess soil erosion at watershed scale Universal Soil Loss Equation (USLE) erosion model has been used on IEL7 watershed of Lidder Catchment in Himalayan Region. Erosion calculation requires huge amount of information and data, usually coming from different sources and available in different formats and scales. Therefore GIS was used, which helped considerably in organizing the spatial data representing the effects of each factor affecting soil erosion. The factors that most influence soil erosion are linked to topography, vegetation type, soil properties and land use/cover. Average annual soil losses were calculated by multiplying five factors: R; the erosivity factor, K; the soil erodibility factor; LS, the topographic factor; C, the crop management factor and P; the conservation support practice. The annual soil loss predictions range between 0 and 61tons ha -1 . Average soil loss was highest (26 tons ha -1 year -1 ) in agriculture area and lowest soil loss rate was f...