Prediction of soil erosion risk using earth observation data under recent emission scenarios of CMIP6

被引:17
|
作者
Kumar, Nirmal [1 ]
Singh, Sudhir Kumar [1 ]
Dubey, Amit Kumar [2 ]
Ray, Ram L. [3 ]
Mustak, Sk [4 ]
Rawat, Kishan Singh [5 ]
机构
[1] Univ Allahabad, K Banerjee Ctr Atmospher & Ocean Studies, Prayagraj, Uttar Pradesh, India
[2] Space Applicat Ctr, Land Hydrol Div, Ahmadabad, Gujarat, India
[3] Prairie View A&M Univ, Coll Agr & Human Sci, Prairie View, TX USA
[4] Cent Univ Punjab, Sch Environm & Earth Sci, Dept Geog, Bathinda, Punjab, India
[5] Graph Era Deemed Univ, Civil Engn Dept, Geoinformat, Dehra Dun, Uttarakhand, India
关键词
Shared Socioeconomic Pathways (SSP); rainfall erosivity; Himalayan river; CMIP; 6; earth observation data; LS factor; CLIMATE-CHANGE; SEDIMENT YIELD; WATER EROSION; RUSLE; GIS; MODEL; IMPACT; REGION;
D O I
10.1080/10106049.2021.1973116
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The earth observation data and CMIP6 models were used to predict plausible soil loss from the Ghaghara river basin. The decadal prediction of soil loss (28.64 ton/ha/year) was found high for SSP585 of CanESM5 during 2015-2025. However, the lower value was reported as 21.71 ton/ha/year for SSP245 of MRI-ESM2-0 during 2035-2045. The century level future rainfall erosivity factor was found lowest for SSP245, however highest for SSP585 of Access-ESM1-5, CanESM5, and IPSL-CM6A-LR. The SSP585 (Access-ESM1-5, CanESM5, and IPSL-CM6A-LR) have maximum soil erosion rate as 29.07, 28.03, and 28.0 ton/ha/year, respectively. For the SSP585, increments were observed as 35.93%, 31.04%, and 30%, respectively, compared to the baseline year (2014). Whereas, lowest was reported as 21.7 and 24.9 ton/ha/year and consequently the low increment as 1.31% and 16.55% for both scenarios of MRI-ESM2-0 compared to baseline. We observed that the soil erosion rate is aligned with the predicted rainfall erosivity factor.
引用
收藏
页码:7041 / 7064
页数:24
相关论文
共 40 条
  • [21] Quantifying the Sensitivity of NDVI-Based C Factor Estimation and Potential Soil Erosion Prediction using Spaceborne Earth Observation Data
    Ayalew, Dawit A.
    Deumlich, Detlef
    Sarapatka, Borivoj
    Doktor, Daniel
    REMOTE SENSING, 2020, 12 (07)
  • [22] Ensemble Flood Risk Assessment in the Yangtze River Economic Belt under CMIP6 SSP-RCP Scenarios
    Peng, Lu
    Li, Zhihui
    SUSTAINABILITY, 2021, 13 (21)
  • [23] Flood Risk Assessment for Sustainable Transportation Planning and Development under Climate Change: A GIS-Based Comparative Analysis of CMIP6 Scenarios
    Abuzwidah, Muamer
    Elawady, Ahmed
    Ashour, Ayat Gamal
    Yilmaz, Abdullah Gokhan
    Shanableh, Abdallah
    Zeiada, Waleed
    SUSTAINABILITY, 2024, 16 (14)
  • [24] Evaluation and prediction of future droughts with multi-model ensembling of four models under CMIP6 scenarios over Iraq
    Abduljaleel, Yasir
    Chikabvumbwa, Sylvester Richard
    Ul Haq, Faraz
    THEORETICAL AND APPLIED CLIMATOLOGY, 2024, 155 (01) : 131 - 142
  • [25] Merging and Downscaling Soil Moisture Data From CMIP6 Projections Using Deep Learning Method
    Feng, Donghan
    Wang, Guojie
    Wei, Xikun
    Amankwah, Solomon Obiri Yeboah
    Hu, Yifan
    Luo, Zicong
    Hagan, Daniel Fiifi Tawia
    Ullah, Waheed
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [26] Streamflow projection under CMIP6 climate scenarios using a support vector regression: a case study of the Kurau River Basin of Northern Malaysia
    Nasir, Muhammad Adib Mohd
    Zainuddin, Zaitul Marlizawati
    Harun, Sobri
    Kamal, Md Rowshon
    Ismail, Habibu
    ENVIRONMENTAL EARTH SCIENCES, 2024, 83 (04)
  • [27] Polar amplification comparison among Earth's three poles under different socioeconomic scenarios from CMIP6 surface air temperature
    Xie, Aihong
    Zhu, Jiangping
    Kang, Shichang
    Qin, Xiang
    Xu, Bing
    Wang, Yicheng
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [28] Spatiotemporal patterns and drivers of soil erosion in Yunnan, Southwest China: RULSE assessments for recent 30 years and future predictions based on CMIP6
    Rao, Wenge
    Shen, Zehao
    Duan, Xingwu
    CATENA, 2023, 220
  • [29] Optimized hybrid ensemble technique for CMIP6 wind data projections under different climate-change scenarios. Case study: United Kingdom
    Moradian, Sogol
    Akbari, Milad
    Iglesias, Gregorio
    SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 826
  • [30] EROSION MODELLING IN A MEDITERRANEAN SUBCATCHMENT UNDER CLIMATE CHANGE SCENARIOS USING PAN-EUROPEAN SOIL EROSION RISK ASSESSMENT (PESERA)
    Cilek, A.
    Berberoglu, S.
    Kirkby, M.
    Irvine, B.
    Donmez, C.
    Erdogan, M. A.
    36TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT, 2015, 47 (W3): : 359 - 365