Estimating Soil Erosion and the Effect of Changing Land Use and Land Cover in the Bringi Catchment’s Devalgam Watershed Using RS and GIS

Abstract

One of the main factors contributing to soil degradation worldwide is soil erosion. The geographical variability of erosion at the Devalgam watershed was evaluated using the Revised Universal Soil Loss Equation (RUSLE) model in a GIS environment. DEM ASTER (30 m × 30 m). The model was fed with annual rainfall data from 1990, 2000, 2010, and 2020 as well as soil and LULC maps. In the Devalgam watershed, the mean annual soil loss ranged from 0 to 127.32, 140.34, 146.49, and 187.23 t/ha/yr for the years 1990, 2000, 2010, and 2020. The mean annual sol loss was calculated to be 16.6, 18.3,19.1, and 22.08 t/ha/yr. According to a zonal statistical analysis of soil erosion for various types of land cover, open forests and barren areas were more likely to experience erosion with the least susceptible to erosion were vegetation, built-up areas, orchards, and agriculture, with estimates of 85.12 and 52.35 t/ha/yr, respectively. According to the current study, managing natural resources is increasingly dependent on the LULC change in the Devalgam Watershed. GIS and remote sensing technologies have shown to be useful tools for analyzing LU/LC changes on a watershed-by-watershed basis. Six LU/LC classes were used to categorize the study area: built-up, barren terrain, vegetation, farmland, woodland, and orchards. and it was discovered that, out of the total area, or 2058.618 hectares, the least area was covered by orchards (0.5%), while the highest area was covered by forest (30.5%), followed by barren ground (25.7%). The examination of the overlay of analysis of the changes from 1990 to 2020 was conducted using LANDSAT-5 1990 over LANDSAT-8 OLI 2020. The findings also indicate that whereas the area under agricultural, built-up areas, barren land, and orchards expanded by 123%, 36.5%, 0.5%, and 36.4%, respectively, the area under forests and vegetation dropped by 17.3% and 48%. With a kappa coefficient of 0.84, 0.71, 0.75, and 0.87, respectively, the overall accuracy for the categorized imageries LANDSAT-5 (1990), LANDSAT-7 (2000), LANDSAT-7 TM (2010), and LANDSAT-8 OLI (2020) was determined to be 86.6%, 76.6%, 80%, and 90%.respectively

Introduction

I. INTRODUCTION

The foundation of production in forestry and agriculture, the source of human nutrition, and an essential part of the environment for humans is soil. Less than 0.3% of human food comes from sources other than the land, accounting for 99.7% of the total. Soil erosion causes the loss of roughly 10 million hectares of agricultural year, which lowers the amount of cropland that can be used to produce food (Pimentel 2006 and Zachar 2011). Thus, the task is to maintain and protect the soil resource bases for future generations in addition to increasing output on a sustainable basis. The soil, climate, and landform conditions, which are further characterized by intrinsic qualities such as agro-ecological contexts, use, and management, determine the boundaries of the land's production capacity. Thus, a thorough analysis of our land resource is required to determine its potential and identify the challenges in maximizing land use in a sustainable manner.

A complicated and natural phenomena known as "soil erosion" happens when fertile surface soil is broken away by wind and water, exposing beneath soil and resulting in sedimentation in reservoirs. Many elements affect it, such as the location of the topographic slope, vegetation, and soil composition, all of which have a big impact on the soil's erosional activity (Mohamadi and Kavain 2015). Globally, soil erosion is a serious issue. Human activity has caused 1,964.4 million hectares (Mha) of land degradation worldwide (Das, 2014). Of this, 548.3 Mha are prone to wind erosion and 1,903 Mha to water erosion. Water erosion has been identified as the primary driver of land degradation caused by anthropogenic activities across 1094 Mha of land worldwide, or 56% of the total.(1991, Oldman et al.)

India loses over 5334 million tonnes of soil annually for a variety of causes.(Pandey and colleagues, 2007; Dhruvanarayan and Babu, 1983)Jammu and Kashmir has 35.86% of its total land degraded, compared to 29% across the nation (ISRO, 2016).Twenty tonnes are lost in the J&K and Ladakh UTs.

II. MATERIALS AND METHODS

A. Study Area

The study area is located in the Anantnag district's southern portion of the Kashmir Valley. The watershed's geographical size is 2058.618 hectares (20.58 Km2). 33?31′ to 33?34′ North latitude and 75?160′ to 75?26′ East longitude correspond to the study area's locations. The Devalgam watershed is situated at a height of 1430-2202 meters (amsl). Forest vegetation dominates the watershed. The location map of area is shown in figure below

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Conclusion

1) The results of this study reveal that rainfall intensity and slope are the most dynamic and most important factors a?ecting surface runo?. 2) The severe and very severe erosion was found to be distributed mainly with in the areas of high slope gradient and also sections of moderate forest (barren lands) LULC class. 3) The Among different LULC, the maximum mean soil loss was found in Barren lands (85.12t/ha/yr), followed by Forest areas (52.35 t/ha/yr), vegetation (15.88 t/ha/yr), agricultural land (9.1 t/ha/yr), orchards (5.66 t/ha/yr), settlements (4.56 t/ha/yr). 4) Upper Sunbrari and Nala Sunbrari areas of watershed were found to be more prone to soil erosion hence; needed an immediate conservation plan. 5) The soil loss estimation for Devalgam watershed was found in increasing order for the year 1990-91(0 -16.6t/ha/yr), 2000-01 (0 -18.3 t/ha/yr), 2010, (0 -19.1t/ha/yr), and 2020(0 -22.08t/ha/yr). 6) With increasing rainfall intensity, in particular, produced the most runoff, soil erosion. Rainfall is thought to be the most significant cause of erosion. 7) The Rainfall erosivity factor also shows an increasing order from year 1990 to 2020, which is the most dynamic cause of soil loss. 8) The conservation strategies recommended include i) contour farming ii) conservation tillage iii) conservation of wastelands to agriculture iv) afforestation under social forestry program and v) putting stop to overgrazing of the pastures. 9) From the results, it is observed that location upper Sunbrari which has the highest K value (0.086); has a low clay content and low organic matter. Location Goi-hard Soyan with the lowest K value (0.038); has a high clay content and high organic matter. Soils with higher K values should have lower clay content and are more prone to erosion.

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Copyright

Copyright © 2024 Dr. Bashir Ahmad Pandit. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.