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Estimating the Soil Erosion Response to Land-Use Change Using GIS-Based RUSLE and Remote Sensing: A Case Study of Heilongjiang Province, China

Author

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  • Nan Jiang

    (Harbin Center for Integrated Natural Resources Survey, China Geological Survey, Harbin 150086, China
    School of Earth Sciences and Resources, China University of Geosciences (Beijing), Beijing 100083, China)

  • Fojun Yao

    (Key Laboratory of Metallogeny and Resources Assessment, Institute of Mineral Resources Chinese Academy of Geological Sciences, Beijing 100037, China)

  • Tao Liu

    (Harbin Center for Integrated Natural Resources Survey, China Geological Survey, Harbin 150086, China)

  • Zhuo Chen

    (Harbin Center for Integrated Natural Resources Survey, China Geological Survey, Harbin 150086, China)

  • Chen Hu

    (Harbin Center for Integrated Natural Resources Survey, China Geological Survey, Harbin 150086, China)

  • Xinxia Geng

    (Key Laboratory of Metallogeny and Resources Assessment, Institute of Mineral Resources Chinese Academy of Geological Sciences, Beijing 100037, China)

Abstract

Understanding soil erosion in the northeastern area of China with black soil is vital for protecting the natural environment and preserving food security. Although spatial and temporal studies of soil erosion have been conducted, further research is needed on the correlation between soil erosion and land use type changes. In this study, the soil erosion modulus is computed using RUSLE. The model that is most suitable to the research area was produced by contrasting three different approaches to estimating the rainfall erosion factor. The RUSLE based on the multi-year continuous high-density hourly average precipitation had the best performance of the bunch, with a MAPE of 15.49%, RMSPE of 7.99%, and R 2 of 0.99. Based on this model, simulated soil erosion trends in the study region from 1980 to 2020 were examined, along with the link between soil erosion and land use change. The results showed that 40.47% of the overall erosion area is made up of cultivated land, and 97.83% of it is low erosion. The most severe soil erosion occurred on unused land, with moderate and above soil erosion occupying 48.93%. Since 2000, there has been an increase in the erosion of soil in the study region, which is primarily spatially represented in the rise in the soil erosion of forests in the central and northern mountainous areas. The study’s findings serve as a guide for land planning and the development of sustainable agriculture.

Suggested Citation

  • Nan Jiang & Fojun Yao & Tao Liu & Zhuo Chen & Chen Hu & Xinxia Geng, 2023. "Estimating the Soil Erosion Response to Land-Use Change Using GIS-Based RUSLE and Remote Sensing: A Case Study of Heilongjiang Province, China," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8004-:d:1146743
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    References listed on IDEAS

    as
    1. Haiyan Fang & Zemeng Fan, 2020. "Assessment of Soil Erosion at Multiple Spatial Scales Following Land Use Changes in 1980–2017 in the Black Soil Region, (NE) China," IJERPH, MDPI, vol. 17(20), pages 1-19, October.
    2. Taoyan Dai & Liquan Wang & Tienan Li & Pengpeng Qiu & Jun Wang, 2022. "Study on the Characteristics of Soil Erosion in the Black Soil Area of Northeast China under Natural Rainfall Conditions: The Case of Sunjiagou Small Watershed," Sustainability, MDPI, vol. 14(14), pages 1-16, July.
    3. Andrea Koch & Alex McBratney & Rattan Lal, 2012. "Put soil security on the global agenda," Nature, Nature, vol. 492(7428), pages 186-186, December.
    4. Qurrat Ulain & Syeda Maria Ali & Ashfaq Ahmad Shah & Kanwar Muhammad Javed Iqbal & Wahid Ullah & Muhammad Atiq Ur Rehman Tariq, 2022. "Identification of Soil Erosion-Based Degraded Land Areas by Employing a Geographic Information System—A Case Study of Pakistan for 1990–2020," Sustainability, MDPI, vol. 14(19), pages 1-12, September.
    5. Stella Margiorou & Aristeidis Kastridis & Marios Sapountzis, 2022. "Pre/Post-Fire Soil Erosion and Evaluation of Check-Dams Effectiveness in Mediterranean Suburban Catchments Based on Field Measurements and Modeling," Land, MDPI, vol. 11(10), pages 1-18, October.
    6. Ranghu Wang & Shuwen Zhang & Jiuchun Yang & Luoman Pu & Chaobin Yang & Lingxue Yu & Liping Chang & Kun Bu, 2016. "Integrated Use of GCM, RS, and GIS for the Assessment of Hillslope and Gully Erosion in the Mushi River Sub-Catchment, Northeast China," Sustainability, MDPI, vol. 8(4), pages 1-20, March.
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    Cited by:

    1. Chenxi Liu & Manyu Dong & Qian Liu & Zhihua Chen & Yulian Wang, 2023. "Spatiotemporal Variability in Rainfall Erosivity and Its Teleconnection with Atmospheric Circulation Indices in China," Sustainability, MDPI, vol. 16(1), pages 1-19, December.

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