A comprehensive methodology that integrates Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) techniques was adopted to determine that soil erosion vulnerability of micro-watershed in J&K 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 erodibility (K), slope length and steepness (LS), cover management (C) and conservation Practice (P) factors were computed to determine their effect on average annual soil loss in the area. The resultant map of annual soil erosion shows maximum soil loss of 2.9246 t h Y with a close relation to grass land area, agricultural lands and orchards (with low LS) . The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning management in the environmentally sensitive agricultural areas.
According to recent assessments over 80% of the world’s agricultural land suffers from moderate to sever erosion which included loss of productivity. Because of this and population growth, the global per capita food supply is currently declining. In many areas of the world., on site impacts of increased soil loss are frequently couped with serious off site impacts related to the increased mobilization of sediments and its delivery to rivers. These off site impacts include water pollution, reservoir sedimentation, the degradation of aquatic habitats and the increased cost of water treatment. The limitations of current measurement techniques and models to provide information on the spatial and temporal patterns of soil and water degradation across catchments restrict ability to develop cost effective land management strategies. However, the advent of new techniques of erosion assessment and recent developments in the application of remote sensing and geographic information system (GIS) to the study of erosion and sediment delivery offer considerable potential for meeting these requirements. Since disturbed lands in watersheds are significant source of sediment, a systematic rating of their potential for erosion would be useful in soil conservation planning. Most importantly mapping and assessment of erosion prone areas enhance soil conservation and watershed management. Maps showing the spatial distribution of natural and management plans, allowing identification of preferential areas where action against soil erosion is more urgent or where the remediation effort will have highest revenue. The site is situated at latitude (33.9770-34.0256N) and longitude of (74.6962-74.7246E) which located in the province of Kashmir and covers an area of 4197.80 ha. The region is highly undulating and exhibits a uniform topography, with a mean elevation of 5770 m above msl and general northwest terrain slope. The study area receives an annual average rainfall of 690 mm and exhibits a dry climatic condition. Almost 80% of the area is occupied by agricultural lands and orchids, followed by grasslands, forest plantation. Gynomorphically, the micro watershed is characterized by steep structural hills, denudation hills, grasslands and agricultural lands with thin vegetation. The soil texture is clay followed by clayey with silt.
Determining the intensity, amount and distribution of erosion has a big important environmental management specialists to make an informed decision on the suitable soil and water conservation measures that should be installed in a given area. The Universal Soil Loss Equation (Wischmeier, 1997) or Revised Soil Loss Equation ( Renald et al., 1997) is of ten used to predict rainfall erosion in landscape/ watersheds using GIS
A. Topography and Climate
The general topography of the area is both mountainous and plan. While the southern and south-western parts are mostly hilly and the eastern and northern parts are relatively plain. The average height of the mountains is 1.610 meters. The climate of district Budgam is of temperate type
B. Land use land cover
The land cover is mostly agricultural and horticultural in the watershed. The soil is mostly clayey with good amounts of silt and sand.
C. Agricultural System
The weather conditions in the valley as well as the district being temperate multiple cropping has not been successful. Paddy and maize are the main crops while as pulses and vegetables are also grown in different pockets of the district
D. Data Source
The quantitative evaluation of the soil erosion loss by RUSLE is based on its component factor; such as: rainfall data, digital elevation model (DEM), soil type map, land cover map and satellite map. The use of GIS provides the tools to manage and analyze these data. However, the evaluation of these data is necessary before they are used. The uncertainties regarding data sources may introduce larger uncertainties in soil erosion estimates. Such as data interpolation, conversion, and registration
E. The Digital Elevation Model (DEM)
Digital elevation model (DEM) is digital file consisting of terrain elevations for ground positions at regularly spaced horizontal intervals. In other word, digital elevation model (DEM) data are digital representations of cartographic information. The DEM data files of the study area are available from Environmental Science Division. The DEM data was added to ArcGIS 10.2 to calculate the flow length and slope steepness.
F. Soil Data
The soil data for this study was obtained from the Division of Soil Science. The soil type of the area is mostly clayey.
G. Precipitation Data
The rainfall data used in this study is from the rainfall station at Meteorological Department. In order to increase the accuracy of the result additional rainfall data from different areas, which are not located in the study area but are close enough it, were used.
H. Land use Land Cover.
The role of land use land cover category has been immense particularly in estimating C and P factors of the RUSLE model. Tus their influence on soil loos would be to some Extent decisive, however, slope length and slope gradient have put strong reflection of their pattern at final result of RUSLE model. Usually C and P factors are determined from satellite map. And other necessary information, the value of C and P factors were obtained from the Environmental Science s Division of Skuast-K
After determining the K values the K map can be prepared in Arc GIS software. This can be done by Kriging or IDW (Inverse Distance Weight) interpolation method.
Slope Length and Steepness LS Factor
The slope map can be prepared from the DEM of the area. A flow direction map can be prepared from the slope map and FD map can be used as input for the creation of flow accumulation map. These two raster’s can be used along with the cell size of “30” The resulting raster is LS map of RUSLE eqn..
B. Annual Average Soil Loss
Rainfall erosivity , soil erodibility, slope length and steepness, cover management, and support practice factors are calculated. The RUSLE calculated the annual average soil loss (for the watershed) from the Eq. using the six factors and it is estimated as A=2.9246 Mg per ha per yr (2.9246 mega gram per ha per yr) which is equal to 2.9246 tonnes per ha per yr. The final of this study was compared to results from different watersheds in the area and concluded that overall result of this study is in an acceptable range.
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