Dynamic monitoring of soil erosion in the upper Minjiang catchment using an improved soil loss equation based on remote sensing and geographic information system

2018 ◽  
Vol 29 (3) ◽  
pp. 521-533 ◽  
Author(s):  
Bing Guo ◽  
Guang Yang ◽  
Feifei Zhang ◽  
Fang Han ◽  
Chenggang Liu
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Soil Loss ◽  
Geographic Information ◽  
Dynamic Monitoring ◽  
Soil Loss Equation

scholarly journals Soil erosion estimation using Geographic Information System (GIS) and Revised Universal Soil Loss Equation (RUSLE) in the Siwalik Hills of Nawalparasi, Nepal

2021 ◽  
Author(s):  
Durga Bahadur Tiruwa ◽  
Babu Ram Khanal ◽  
Sushil Lamichhane ◽  
Bharat Sharma Acharya
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Soil Loss ◽  
Geographic Information ◽  
Universal Soil Loss Equation ◽  
Conservation Practices ◽  
Erosion Hotspots ◽  
Soil Loss Equation

Abstract Soil erosion is one of the gravest environmental threats to the mountainous ecosystems of Nepal. Here, we combined a Geographic Information System (GIS) with the Revised Universal Soil Loss Equation (RUSLE) to estimate average annual soil loss, map erosion factors, compare soil erosion risks among different land use types, and identify erosion hotspots and recommend land use management in the Girwari river watershed of the Siwalik Hills. The annual soil loss was estimated using RUSLE factors: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover crops (C), and conservation practices (P), and erosion factors maps were generated using GIS. Results indicate highest total erosion occurring in hill forests (13,374.3 t yr–1) and lowest total erosion occurring in grasslands (2.9 t yr–1). Hill forests showed high to very severe erosion due to steepness of hills, open forest types, and minimal use of conservation practices. Also, erosion hotspots (>15 t ha–1 yr–1) occurred in only 4.2% of the watershed, primarily in steep slopes. Overall, these results provide important guidelines to formulate management plans and informed decisions on soil conservation at local to regional levels. While the study is the first effort to assess soil erosion dynamics in the Girwari river watershed, potential for application in other basins largely exists.

scholarly journals Estimation of Soil Erosion using USLE and GIS

2019 ◽  
Vol 8 (2) ◽  
pp. 3936-3939
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Environmental Problem ◽  
Gis Technique ◽  
Economic Imbalances ◽  
Factor C ◽  
Soil Loss Equation

Soil erosion is one of the most serious environmental problem which must be taken in to consideration to prevent economic imbalances in nature. Soil erosion not only affect the agricultural productivity but also increases level of sedimentation. The study was carried out to determine the soil erosion for the watershed which is located in Godavari middle sub basin, Nanded district, Maharashtra state (India). The universal soil loss equation (USLE) and Geographic information system (GIS) technique was used to determine soil erosion. Present study revealed that, the study area is under moderate erosion with an average soil loss 7.233 tones/ha/yr. Where as minimum and maximum erosion rate observed as 5.39 tones/ha/yr to 10.27 tones/ha/yr respectively. The various maps of USLE factors prepared in QGIS environment. Statistically significant relationship obtained between soil loss and cover management factor (C). It was observed that C factor more influences in soil loss than any other factor.

REVISITING THE METHODOLOGICAL DEVELOPMENT IN SOIL EROSION RESEARCH

Ensemble ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 145-165
Author(s):  
Tanmoy Sarkar ◽  
◽  
Tapas Pal ◽  
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Geographic Information ◽  
Methodological Development ◽  
Advantages And Disadvantages ◽  
The Future ◽  
Soil Erosion By Water

Soil erosion (by water) is a major land degradation process that may threat the Sustainable Development Goals (SDG) by its negative impact on environment and human well-being. Soil erosion research demands scientific methods, tools and techniques to assess soil erosion with more accuracy and reliability. Soil erosion research has had experienced crude field-based techniques in early twentieth century to model-based approaches since the 1970s and very recent machine learning and artificial intelligence models to predict soil erosion susceptibility and risk. The paper aims to review the trend in methodological development in soil erosion by water through time. The brief background of different approaches, their relative advantages and disadvantages are reviewed. Depending on the time of establishment and wide application the approaches are classified and represented as erosion plot/runoff approach, erosion pin technique followed by environmental tracer method and model approach in combination with Remote Sensing (RS) and Geographic Information System (GIS). Recent advancement in artificial intelligence and application of statistical techniques have a great potential to contribute in soil erosion research by identifying various degrees of susceptibility in large scale and also to quantify the erosion rate with high accuracy. The Remote sensing (RS) and Geographic Information System (GIS) contribute to develop regional scale data base with exploration of real time data and spatial analysis. The combination of RS & GIS and process-based models must be more effective than the traditional soil erosion model in the context of prediction with greater reliability and validity. The future research on soil erosion is better to focus on the theoretical analysis and development of erosion prediction model with more quantitative refinement and to model the future.

scholarly journals Remote Sensing and Geographic Information System in Water Erosion Assessment

2020 ◽  
Author(s):  
Nirmal Kumar ◽  
S. K. Singh ◽  
G. P. Obi Reddy ◽  
V. N. Mishra ◽  
R. K. Bajpai
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Spatial Data ◽  
Soil Loss ◽  
Water Erosion ◽  
Geographic Information ◽  
Geographical Information ◽  
Comprehensive Overview

The aim of this review paper is to provide a comprehensive overview of geographical information system and remote sensing–based water erosion assessment. With multispectral and multi-temporal low cost data at various resolutions, remote sensing plays an important role for mapping the distribution and severity of water erosion and for modeling the risk and/or potential of soil loss. The ability of geographic information system to integrate spatial data of different types and sources makes its role unavoidable in water erosion assessment. The role of satellite data in identification of eroded lands and in providing inputs for erosion modeling has been discussed. The role of GIS in mapping eroded lands based on experts’ opinion, in generating spatial data inputs from sources other than remote sensing and in integrating the inputs to model the potential soil loss has been discussed.

scholarly journals Impact of land-use and land-cover change on soil erosion using the RUSLE model and the geographic information system: a case of Temeji watershed, Western Ethiopia

2021 ◽  
Author(s):  
Mitiku Badasa Moisa ◽  
Daniel Assefa Negash ◽  
Biratu Bobo Merga ◽  
Dessalegn Obsi Gemeda
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Land Cover ◽  
Water Conservation ◽  
Soil Loss ◽  
Geographic Information ◽  
Lulc Change ◽  
The Impact

Abstract The impact of land-use land-cover (LULC) change on soil resources is getting global attention. Soil erosion is one of the critical environmental problems worldwide with high severity in developing countries. This study integrates the Revised Universal Soil Loss Equation model with a geographic information system to estimate the impacts of LULC conversion on the mean annual soil loss in the Temeji watershed. In this study, LULC change of Temeji watershed was assessed from 2000 to 2020 by using 2000 Landsat ETM+ and 2020 Landsat OLI/TIRS images and classified using supervised maximum likelihood classification algorithms. Results indicate that the majority of the LULC in the study area is vulnerable to soil erosion. High soil loss is observed when grassland and forest land were converted into cultivated land with a mean soil loss of 88.8 and 86.9 t/ha/year in 2020. Results revealed that about 6,608.5 ha (42.8%) and 8,391.8 ha (54.4%) were categorized under severe classes in 2000 and 2020, respectively. Accordingly, the soil loss severity class is directly correlated with the over-exploitation of forest resources and grasslands for agricultural purposes. These results can be useful for advocacy to enhance local people and stakeholder's participation toward soil and water conservation practices.

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