GIS integrated RUSLE model-based soil loss estimation and watershed prioritization for land and water conservation aspects

被引:21
作者
Singh, Mahesh Chand [1 ]
Sur, Koyel [2 ]
Al-Ansari, Nadhir [3 ]
Arya, Prashant Kumar [4 ]
Verma, Vipan Kumar [2 ]
Malik, Anurag [5 ]
机构
[1] Punjab Agr Univ, Dept Soil & Water Engn, Ludhiana, Punjab, India
[2] Punjab Remote Sensing Ctr, Ludhiana, Punjab, India
[3] Lulea Univ Technol, Civil Environm & Nat Resources Engn, Lulea, Sweden
[4] Eastern Reg Ctr, Inst Human Dev, Ranchi, India
[5] Punjab Agr Univ, Reg Res Stn, Bathinda, Punjab, India
关键词
banas basin; prioritization; soil loss; RUSLE; GIS; BANAS RIVER-BASIN; CLIMATE-CHANGE; EROSION RISK; RAJASTHAN; USLE; PREDICTION; MANAGEMENT; SECURITY; INDEXES; IMPACT;
D O I
10.3389/fenvs.2023.1136243
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 has become one of the major threats throughout the globe, affecting about 2.6 billion people in more than 100 countries. The highest rate of land degradation is in Asia, followed by Africa and Europe. Climate change coupled with anthropogenic activities have accelerated the rate of land degradation in developing nations. In India, land degradation has affected about 105.48 million hectares. Thus, modeling and mapping soil loss, and assessing the vulnerability threat of the active erosional processes in a region are the major challenges from the land and water conservation aspects. The present study attempted rigorous modeling to estimate soil loss from the Banas Basin of Rajasthan state, India, using GIS-integrated Revised Universal Soil Loss Equation (RUSLE) equation. Priority ranking was computed for different watersheds in terms of the degree of soil loss from their catchments, so that appropriate conservation measures can be implemented. The total area of Banas basin (68,207.82 km(2)) was systematically separated into 25 watersheds ranging in area from 113.0 to 7626.8 km(2). Rainfall dataset of Indian Meteorological Department for 30 years (1990-2020), FAO based Soil map for soil characterization, ALOS PALSAR digital elevation model for topographic assessment, and Sentinal-2 based land use and land cover map were integrated for modeling and mapping soil erosion/loss risk assessment. The total annual soil loss in the Banas basin was recorded as 21,766,048.8 tons. The areas under very low (0-1 t ha(-1) year(-1)), low (1-5 t ha(-1) year(-1)), medium (5-10 t ha(-1) year(-1)), high (10-50 t ha(-1) year(-1)) and extreme (> 50 t ha(-1) year(-1)) soil loss categories were recorded as 24.2, 66.8, 7.3, 0.9, and 0.7%, respectively, whereas the respective average annual soil loss values were obtained as 0.8, 3.0, 6.0, 23.1, and 52.0 t ha(-1) year(-1). The average annual soil loss among different watersheds was recorded in the range of 1.1-84.9 t ha(-1) year(-1), being highest (84.9 t ha(-1) year(-1)) in WS18, followed by WS10 (38.4 t ha(-1) year(-1)), SW25 (34.7 t ha(-1) year(-1)) and WS23 (17.9 t ha(-1) year(-1)), whereas it was lowest for WS8 (1.1 t ha(-1) year(-1)). Thus, WS18 obtained the highest/top priority rank in terms of the average annual soil loss (84.9 t ha(-1) year(-1)) to be considered as the first priority for land and water conservation planning and implementation. The quantitative results of this study would be useful for implementation of land and water conservation measures in the problematic areas of the Banas basin for controlling soil loss through water erosion.
引用
收藏
页数:17
相关论文
共 59 条
  • [1] Modelling soil erosion in a Mediterranean watershed: Comparison between SWAT and AnnAGNPS models
    Abdelwahab, O. M. M.
    Ricci, G. F.
    De Girolamo, A. M.
    Gentile, F.
    [J]. ENVIRONMENTAL RESEARCH, 2018, 166 : 363 - 376
  • [2] A systematic review of soil erosion control practices on the agricultural land in Asia
    Ahmad, Nur Syabeera Begum Nasir
    Mustafa, Firuza Begham
    Yusoff, Safiah Yusmah Muhammad
    Didams, Gideon
    [J]. INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH, 2020, 8 (02) : 103 - 115
  • [3] Assessment of soil erosion risk severity using GIS, remote sensing and RUSLE model in Oued Laou Basin (north Morocco)
    Amellah, Omayma
    el Morabiti, Karim
    [J]. SOIL SCIENCE ANNUAL, 2021, 72 (03)
  • [4] Amsalu T., 2014, Natural Resources, V5, P616, DOI [10.4236/nr.2014.511054, DOI 10.4236/NR.2014.511054]
  • [5] Soil erosion prediction using RUSLE for central Kenyan highland conditions
    Angima, SD
    Stott, DE
    O'Neill, MK
    Ong, CK
    Weesies, GA
    [J]. AGRICULTURE ECOSYSTEMS & ENVIRONMENT, 2003, 97 (1-3) : 295 - 308
  • [6] [Anonymous], 1972, National Engineering Handbook, Section 4, Hydrology
  • [7] BEASLEY DB, 1980, T ASAE, V23, P938, DOI 10.13031/2013.34692
  • [8] Land use and climate change impacts on global soil erosion by water (2015-2070)
    Borrelli, Pasquale
    Robinson, David A.
    Panagos, Panos
    Lugato, Emanuele
    Yang, Jae E.
    Alewell, Christine
    Wuepper, David
    Montanarella, Luca
    Ballabio, Cristiano
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (36) : 21994 - 22001
  • [9] Assessment of the risk of soil erosion using RUSLE method and SWAT model at the M'dez Watershed, Middle Atlas, Morocco.
    Boufala, M'hamed
    El Hmaidf, Abdellah
    Chadli, Khalid
    Essahlaoui, Ali
    El Ouali, Abdelhadi
    Lahjouj, Abdelhakim
    [J]. SEVENTH INTERNATIONAL CONGRESS WATER, WASTE AND ENVIRONMENT (EDE7-2019), 2020, 150
  • [10] Chahar Bhagu R., 2013, World Environmental and Water Resources Congress 2013. Showcasing the Future. Proceedings of the 2013 Congress, P450