Soil Erosion Risk Assessment and Spatial Mapping in Jhagrabaria Watershed, Allahabad, U.P. (India) by Using LANDSAT 7ETM+ Remote Sensing Data, Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS)

Soil erosion is crucial problem in India where more than 70% of land in degraded. This study is to establish conservation priorities of the sub watersheds across the entire terrain, and suggest suitable conservation measures. Soil conservation practices are not only from erosion data both qualitative SES (Soil Erosion Status) model and quantitative MMF (Morgan, Morgan and Finney) model erosion, but we have to consider LCC (Land Capability Classification) and LULC (Land Use Land Cover). Study demonstrated the use of RS (Remote Sensing) and GIS (Geographic Information System) in soil erosion risk assessment by deriving soil and vegetation parameters in the erosion models. Sub-watersheds were prioritized based on average soil loss and the area falls under various erosion risk classes for conservation planning. The annual rate of soil loss based on MMF model was classified into five soil erosion risk classes for soil conservation measures. From 11 sub watersheds, for the first priority of the watershed is catchment with the small area and the steep slope. Recommendation for steep areas (classes VI, VII, and VIII) land use allocation should be made to maintain forest functions.

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Estimation of Soil Loss Using Remote Sensing And GIS-Based Universal Soil Loss Equation In Northern Catchment of Lake Tana Sub-Basin, Upper Blue Nile Basin, Northwest Ethiopia

10.21203/rs.3.rs-78824/v1 ◽

2020 ◽

Author(s):

Veera Narayana Balabathina ◽

Raju RP ◽

Wuletaw Mulualem ◽

Gedefaw Tadele

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Soil Loss ◽

Universal Soil Loss Equation ◽

Lake Tana ◽

Erosion Risk ◽

Priority Areas ◽

Erosion Rates ◽

The Mean ◽

Soil Loss Equation

Abstract Background: Soil erosion, one of the major environmental challenges, is influenced by topography, climate, soil characteristics, and human activities and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. The present study attempts to estimate soil erosion risk in the Northern catchment of Lake Tana basin, situated in northwest part of Ethiopia, with available data through the application of the Universal Soil Loss Equation model integrated with Geographic Information System and remote sensing technologies to identify priority areas for controlling soil erosion. In addition, it analyzes the effect of land use and land cover, topography, erodibility, and drainage density on soil erosion potential of the catchment, and the possible relationships among them. Results: The results show that the mean annual soil loss of catchment is estimated at 37.89 ± 59.2 t ha−1yr−1 with a total annual soil loss of 1,705,370 tons. The topography (LS-factor), followed by the support practice (P-factor) and the soil erodibility (K-factor) were the most sensitive factors affecting soil erosion in the catchment. To identify high priority areas for management, the study area was subdivided into five major sub-basins and further categorized into five erosion classes based on erosion severity. The mean soil erosion rates of the Derma, Megech, Gumara, Garno, and Gabi Kura River sub-basins are 46.8, 40.98, 30.95, 30.04, and 29.66 t ha−1yr−1, respectively. About 58.9% of the area was found in very low erosion risk which extends from 0-1 t ha−1yr−1 and accounted only 1.1% of total soil loss, while 12.4% of the area was found to be under high and extreme erosion risk with erosion rates of 10 t ha−1yr−1 or more that contributes about 82.1% of total soil loss warrant high priority for reducing the risk of soil erosion. Conclusions: This study permits the understanding of the soil erosion process and the various factors that lead to the spatial variability of the risk in the catchment, and thus enhances the effectiveness of proposed conservation strategies for sustainable land management.

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Prioritization of Watershed Using Remote Sensing and Geographic Information System

Sustainability ◽

10.3390/su13169456 ◽

2021 ◽

Vol 13 (16) ◽

pp. 9456

Author(s):

Devendra Kumar ◽

Arvind Dhaloiya ◽

Ajeet Singh Nain ◽

Mahendra Paal Sharma ◽

Amandeep Singh

Keyword(s):

Remote Sensing ◽

Information System ◽

Soil Erosion ◽

Natural Resources ◽

Best Management Practices ◽

Soil Loss ◽

Management Practices ◽

Agricultural Land ◽

Geographical Information ◽

Slope Length

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 & 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.

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GIS and Remote Sensing solution for Dalat city’s soil erosion mapping

Science and Technology Development Journal ◽

10.32508/stdj.v19i2.700 ◽

2016 ◽

Vol 19 (2) ◽

pp. 46-54

Author(s):

Trung Van Le ◽

Hoang Thi Kim Nguyen ◽

Anh Thi Ngoc Nguyen

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Soil Conservation ◽

Soil Loss ◽

Point Of View ◽

Gis And Remote Sensing ◽

Thematic Layers ◽

Erosion Risk ◽

Attribute Data ◽

Soil Loss Equation

This paper introduces the solution for Dalat city’s soil erosion mapping using the integration of GIS, Remote Sensing and the Universal Soil Loss Equation (USLE). Each of the USLE factors with associated attribute data are dicussed and the soil erosion parameters were selected and encoded in a GIS database to produce thematic layers. The result demonstrates the soil erosion map that indicates the potential annual soil loss located in each area of land. This map is used to confirm the severe level of soil erosion risk need immediate attention from soil conservation point of view.

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Analysis of Ownership Data from Consolidated Land Threatened by Water Erosion in the Vlára Basin, Slovakia

Sustainability ◽

10.3390/su13010051 ◽

2020 ◽

Vol 13 (1) ◽

pp. 51

Author(s):

Alexandra Pagáč Mokrá ◽

Jakub Pagáč ◽

Zlatica Muchová ◽

František Petrovič

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Agricultural Land ◽

Water Erosion ◽

Land Consolidation ◽

Land Fragmentation ◽

Erosion Risk ◽

Definition Of ◽

The Relationship ◽

Soil Loss Equation

Water erosion is a phenomenon that significantly damages agricultural land. The current land fragmentation in Slovakia and the complete ambiguity of who owns it leads to a lack of responsibility to care for the land in its current condition, which could affect its sustainability in the future. The reason so much soil has eroded is obvious when looking at current land management, with large fields, a lack of windbreaks between them, and no barriers to prevent soil runoff. Land consolidation might be the solution. This paper seeks to evaluate redistributed land and, based on modeling by the Universal Soil Loss Equation (USLE) method, to assess the degree of soil erosion risk. Ownership data provided information on how many owners and what amount of area to consider, while taking into account new conditions regarding water erosion. The results indicate that 2488 plots of 1607 owners which represent 12% of the model area are still endangered by water erosion, even after the completion of the land consolidation project. The results also presented a way of evaluating the territory and aims to trigger a discussion regarding an unambiguous definition of responsibility in the relationship between owner and user.

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