Pixel-Based Soil Loss Estimation and Prioritization of North-Western Himalayan Catchment Based on Revised Universal Soil Loss Equation (RUSLE)

被引:1
作者
Gupta, Shishant [1 ]
Ojha, Chandra Shekhar Prasad [1 ]
Singh, Vijay P. [2 ,3 ]
Adeloye, Adebayo J. [4 ]
Jain, Sanjay K. [5 ]
机构
[1] Indian Inst Technol, Dept Civil Engn, Roorkee 247667, India
[2] Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX 77843 USA
[3] Texas A&M Univ, Dept Civil & Environm Engn, College Stn, TX 77843 USA
[4] Heriot Watt Univ, Inst Infrastruct & Environm, Edinburgh EH14 4AS, Scotland
[5] Natl Inst Hydrol, Water Resources Syst Div, Roorkee 247667, India
关键词
land degradation; soil erosion; RUSLE; Himalayas; remote sensing; GIS; SEDIMENT YIELD; EROSION; GIS; AREA; AMERICA; REGION;
D O I
10.3390/su152015177
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Land degradation is a noteworthy environmental risk causing water quality issues, reservoir siltation, and loss of valuable arable lands, all of which negate sustainable development. Analysis of the effect of land use changes on erosion rate and sediment yield is particularly useful to identify critical areas and define catchment-area treatment plans. This study utilized remote sensing and geographical information system/science (GIS) techniques combined with the Revised Universal Soil Loss Equation (RUSLE) on a pixel basis to estimate soil loss over space and time and prioritized areas for action. The methodology was applied to the Sutlej catchment from the perspective of sedimentation of the Bhakra reservoir, which is leading to the loss of active storage capacity and performance and of the safety and efficiency of many existing hydroelectric projects in the Sutlej and its tributaries that drain the Himalayas. Soil loss estimation using RUSLE was first calibrated using data from three sites, and the calibrated model was then used to estimate catchment soil loss for 21 years (1995-2015). The number of land use/land cover (LULC) classes as 14 and the C factor as 0.63 for agriculture land were optimized using the observed data for the Sutlej catchment. Further, the linkage between soil erosivity and annual precipitation was also established. It was concluded that extensive control treatment would be necessary from the soil and water conservation point of view. Structures like check dams, terraces, bunds, and diversion drains in the upstream can overcome the issue of fragmentation of soil in the Sutlej catchment.
引用
收藏
页数:21
相关论文
共 50 条
  • [21] Estimation of annual average soil loss using the Revised Universal Soil Loss Equation (RUSLE) integrated in a Geographical Information System (GIS) of the Esil River basin (ERB), Kazakhstan
    Mukanov, Yerbolat
    Chen, Yaning
    Baisholanov, Saken
    Amanambu, Amobichukwu Chukwudi
    Issanova, Gulnura
    Abenova, Ainura
    Fang, Gonghuan
    Abayev, Nurlan
    ACTA GEOPHYSICA, 2019, 67 (03) : 921 - 938
  • [22] Estimation of soil erosion in indo-gangetic region using revised universal soil loss equation (RUSLE) model and geospatial technology
    Sunil Kumar
    Dharmendra Singh
    Amit Kumar
    Mukesh Kumar
    Kushal Giri
    Kushala Devi
    Sultan Singh
    Modeling Earth Systems and Environment, 2023, 9 : 1251 - 1273
  • [23] Utilizing the Revised Universal Soil Loss Equation (RUSLE) Technique Comparative Analysis of Soil Erosion Risk in the Geumhogang Riparian Area
    Kim, Jeong-Cheol
    Yoon, Jung-Do
    Park, Jeong-Soo
    Choi, Jong-Yun
    Yoon, Jong-Hak
    KOREAN JOURNAL OF REMOTE SENSING, 2018, 34 (02) : 179 - 190
  • [24] Relationship between drought and soil erosion based on the normalized differential water index (NDWI) and revised universal soil loss equation (RUSLE) model
    Rendana, Muhammad
    Idris, Wan Mohd Razi
    Alia, Febrinasti
    Rahim, Supli Effendi
    Yamin, Muhammad
    Izzudin, Muhammad
    REGIONAL SUSTAINABILITY, 2024, 5 (04)
  • [25] Prioritization of Sub-Watershed Based on Soil Loss Estimation Using RUSLE Model: A Case Study of Digaru Watershed, Assam, India
    Deka, Dhanjit
    Das, Jyoti Prasad
    Hazarika, Madine
    Borah, Debashree
    INTERNATIONAL JOURNAL OF APPLIED GEOSPATIAL RESEARCH, 2024, 15 (01)
  • [26] Predicting soil erosion risk using the revised universal soil loss equation (RUSLE) model and geo-spatial methods
    Naqvi, Syed Ali Asad
    Tariq, Aqil
    Shahzad, Mudsar
    Khalid, Shoaib
    Tariq, Zara
    Salma, Ume
    Haseeb, Muhammad
    Soufan, Walid
    HYDROLOGICAL PROCESSES, 2024, 38 (08)
  • [27] Estimating soil erosion in sub-Saharan Africa based on landscape similarity mapping and using the revised universal soil loss equation (RUSLE)
    Lulseged Tamene
    Quang Bao Le
    Nutrient Cycling in Agroecosystems, 2015, 102 : 17 - 31
  • [28] Assessing hydrological erosion estimation using the Revised Universal Soil Loss Equation (RUSLE) model in Google Earth Engine: a case study of Medjerda River Catchment, Tunisia
    Cherif, Mouna
    Saidi, Salwa
    Ezzine, Ahmed
    Darragi, Fadila
    Homayouni, Saeid
    EURO-MEDITERRANEAN JOURNAL FOR ENVIRONMENTAL INTEGRATION, 2025,
  • [29] Revisiting the questioned reliability of the revised universal soil loss equation (RUSLE) for soil erosion prediction in the tropics
    Akpa, Enya A.
    Obalum, Sunday E.
    Igwe, Charles A.
    SOIL SCIENCE ANNUAL, 2024, 75 (02)
  • [30] Spatial uncertainty in prediction of the topographical factor for the Revised Universal Soil Loss Equation (RUSLE)
    Wang, G
    Fang, S
    Shinkareva, S
    Gertner, G
    Anderson, A
    TRANSACTIONS OF THE ASAE, 2002, 45 (01): : 109 - 118