Estimation of Runoff and Soil Erosion for Vishwamitri River Watershed, Western India Using RS and GIS (original) (raw)
Related papers
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.
International Journal for Scientific Research & Development, 2015
Soil erosion is one of the critical problem occurs in india as well as some developed countries. A large area can prone for soil erosion, which turn, reduces productivity. Soil erosion estimation is very time consuming exercise. Methods such as the Universal Soil loss Equation (USLE) are widely used for the estimation of soil erosion from watershed. This paper deals with the estimation of soil erosion using USLE in a GIS environment and prioritization of watersheds on that basis. Vishwamitri river watershed in Gujarat, India is taken as the study area. Satellite images of IRS-P6 LISS-III have been used. Various thematic maps like Land use, Soil and Slope map were prepared at BISAG. soil erosion of each of the sub watersheds was estimated. The sub watershed was prioritization of watershed. In present Study, all five parameters of USLE like R.K.LS, C,P was estimated. Calculating all five parameters of USLE, it is found that two sub watersheds coded as SW1 & SW2 are subjected to very severe condition which needs to controlling measures. Remaining two sub watersheds coded as SW3 & SW4 are subjected to Moderate condition. The computed Annual Soil loss of study area is 240.27 ton /ha/year
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.
Water resources management, 2008
In the present study, soil erosion assessment of Dikrong river basin of Arunachal Pradesh (India) was carried out. The river basin was divided into 200×200 m grid cells. The Arc Info 7.2 GIS software and RS (ERDAS IMAGINE 8.4 image processing software) provided spatial input data and the USLE was used to predict the spatial distribution of the average annual soil loss on grid basis. The average rainfall erositivity factor (R) for Dikrong river basin was found to be 1,894.6 MJ mm ha −1 h −1 year −1 . The soil erodibility factor (K) with a magnitude of 0.055 t ha h ha −1 MJ −1 mm −1 is the highest, with 0.039 t ha h ha −1 MJ −1 mm −1 is the least for the watershed. The highest and lowest value of slope length factor (LS) is 53.5 and 5.39 respectively for the watershed. The highest and lowest values of crop management factor (C) were found out to be 0.004 and 1.0 respectively for the watershed. The highest and lowest value of conservation factor (P) were found to be 1 and 0.28 respectively for the watershed. The average annual soil loss of the Dikrong river basin is 51 t ha −1 year −1 . About 25.61% of the watershed area is found out to be under slight erosion class. Areas covered by moderate, high, very high, severe and very severe erosion potential zones are 26.51%, 17.87%, 13.74%, 2.39% and 13.88% respectively. Therefore, these areas need immediate attention from soil conservation point of view.
Land and water are the two most valuable and vital resources essentially required not only for sustenance of life but also for the economic and social progress of a region. In India population pressure is increasing over the years which resulted in the scarcity of availability of land and water resources. Industrial expansion is also a need of the time, which requires infrastructural facilities; which intern forms a feed back resulting in further pressure on finite land and water resources. About 53 percent of the total area of India which is 172 m ha suffers from serious soil erosion and other forms of degradation. So, planning and management of land and water resources on a sustained basis without deterioration and with constant increase in productivity is the main stay in the mankind. Planning and management of natural resources requires hydrological data. In India, sediment yield data(hydrological data) are generally not collected for smaller watersheds and it becomes difficult to identify the most vulnerable area for erosion that can be treated on priority basis. In the present study remote sensing and GIS (Geographical Information System) technology were used to generate information regarding factors affecting soil erosion. These factors include soil type, vegetation, topography and various watershed properties such as drainage density, form factor etc. The present study is carried out in Kanhiya nala watershed of Gusuru river which is a tributary of Tons river basin in S.K. Sharma et al 154 Madhya Pradesh, India. The study area is divided into nine sub watersheds and different topology, vegetation, soil and morphology related indices are estimated separately for each sub watersheds. The integrated effect of all the parameter is evaluated to find different areas vulnerable to soil erosion. Two sub watersheds i.e. 1 and 8 were identified as very high susceptible to soil erosion.
Soil erosion assessment for watershed management is a world-wide concern for ecologists and land users. In this study soil erosion was predicted using Universal Soil Loss Equation (USLE) for Katteri watershed in Nilgiris, Tamilnadu. Topographically the study area falls under steep slope and undulating terrain comprising 49% of tea plantation, 23% of horticultural crops, and 24% of forest area. The IRS-IC LISS III satellite imagery was classified and used for preparing the landuse/landcover which estimates cover management factor (C) and the landuse practice factor (P). Using digital elevation model (DEM) as input, the slope length factor (LS) was determined by AML programme. Soil erodibility (K) values were measured for all mapped soil types in the study area. The rainfall erosivity factor (R) was directly computed from rainfall intensities. All the above mentioned USLE factors, with associated attribute data, were digitally encoded in a GIS database and converted into 30 m grid cells. Simultaneous overlaid operation on these five layers produced a resultant layer of soil erosion rate in t ha -1 yr -1 . This research confirms that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in Katteri watershed.
An Estimation of Soil Erosion in Gandamanur Watershed Using Geospatial Technology
2018
Soil erosion is one of the critical environmental problems and a major threat to many natural resources. Stream bank erosion is a kind of water erosion, in which soil is removed by the runoff flowing over the sides of the stream coming from the areas or by undercutting of soil below the water surface from the stream section. Quantitative analysis of soil loss and description of erosion prone areas are essential for conservation programme. The present study focuses on estimation of soil erosion in Gandamanur watershed of Theni District. The soil loss values estimated for Gandamanur watershed ranges from 0 to 219.7 ton/ hec /yr with an average of 2.53 t/ha/yr (metric ton per hectare per year). High soil erosion found in steep slopes and streams. Integrated Remote sensing and GIS technology is applied for prepare various thematic layers of Revised Universal Soil Loss Equation (RUSLE) which is used to estimate the soil erosion at watershed level.
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.
Journal of The Indian Society of Remote Sensing
Soil erosion which occurs at spatially varying rate is a widespread threat to sustainable resource management at watershed scale. Thus estimation of soil loss and identification of critical area for implementation of best management practice is central to success of soil conservation programme. The present study focuses application of most widely used Universal Soil Loss Equation (USLE) to determine soil erosion and prioritization of micro-watersheds of Upper Damodar Valley Catchment (UDVC) of India. Annual average soil loss for the entire basin is 23.17 t/ha/yr; for micro-watersheds. High soil loss is observed in 345 micro-watersheds, medium in 159 micro-watersheds and low soil loss is observed in 201 micro-watersheds. It is found that, out of 705 micro-watersheds of UDVC, 453 micro-watersheds are in agreement with AISLUS suggested priority which is based on observed sediment yield, 116 micro-watersheds under predict and 136 micro-watersheds over predict the priority. Geographic Information System (GIS) is applied to prepare various layers of USLE parameters which interactively estimate soil erosion at micro-watershed level. The main advantage of the GIS methodology is in providing quick information on the estimated value of soil loss for any part of the investigated area.
Soil Erosion Mapping of Katteri Watershed using Universal Soil Loss Equation and GIS
Soil erosion assessment for watershed management is a world-wide concern for ecologist and land users. In this study soil erosion was predicted using Universal Soil Loss Equation (USLE) for Katteri watershed in Nilgiris, Tamilnadu. Topographically the study area falls under steep slope and undulating terrain comprising 49% of tea plantation, 23% of horticultural crops, and 24% of forest area. The IRS-IC LISS III satellite imagery was classified and used for preparing the landuse/landcover which estimates cover management factor (C) and the landuse practice factor (P). Using digital elevation model (DEM) as input, the slope length factor (LS) was determined by AML programme. Soil erodibility (K) values were measured for all mapped soil types in the study area. The rainfall erosivity factor (R) was directly computed from rainfall intensities. All the above mentioned USLE factors, with associated attribute data, were digitally encoded in a GIS database and converted into 30 m grid cells. Simultaneous overlaid operation on these five layers produced a resultant layer of soil erosion rate in t acre -1 yr -1 . This research confirms that remote sensing and GIS provide promising tools for evaluating and mapping soil erosion risk in Katteri watershed.