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Impacts of Climate Change and Land Use/Cover Change on Runoff in the Huangfuchuan River Basin

Author

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  • Xin Huang

    (School of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450045, China)

  • Lin Qiu

    (School of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450045, China)

Abstract

Studying the response of runoff to climate change and land use/cover change has guiding significance for watershed land planning, water resource planning, and ecological environment protection. Especially in the Yellow River Basin, which has a variable climate and fragile ecology, such research is more important. This article takes the Huangfuchuan River Basin (HFCRB) in the middle reaches of the Yellow River as the research area, and analyzes the impact of climate change scenarios and land use/cover change scenarios on runoff by constructing a SWAT model. Using CMIP6 GCMs to obtain future climate data and the CA–Markov model to predict future land use data, the two are coupled to estimate the future runoff process in the HFCRB, and the uncertainty of the estimated runoff is decomposed and quantified. The results were as follows: ① The SWAT model has good adaptability in the HFCRB. During the calibrated period and the validation period, R 2 ≥ 0.84, NSE ≥ 0.8, and | PBIAS | ≤ 17.5%, all of which meet the model evaluation criteria. ② There is a negative correlation between temperature and runoff, and a positive correlation between precipitation and runoff. Runoff is more sensitive to temperature rise and precipitation increase. ③ The impact of land use types on runoff is in the order of cultivated land > grassland > forest land. ④ The variation range of runoff under the combined effects of future climate change and LUCC is between that of single climate change or LUCC scenarios. The increase in runoff under SSP126, SSP245, and SSP585 scenarios is 10.57%, 25.55%, and 31.28%, respectively. Precipitation is the main factor affecting the future runoff changes in the HFCRB. Model uncertainty is the main source of uncertainty in runoff prediction.

Suggested Citation

  • Xin Huang & Lin Qiu, 2024. "Impacts of Climate Change and Land Use/Cover Change on Runoff in the Huangfuchuan River Basin," Land, MDPI, vol. 13(12), pages 1-23, November.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:12:p:2048-:d:1532728
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    References listed on IDEAS

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    1. Jinkang Du & Hanyi Rui & Tianhui Zuo & Qian Li & Dapeng Zheng & Ailing Chen & Youpeng Xu & C.-Y. Xu, 2013. "Hydrological Simulation by SWAT Model with Fixed and Varied Parameterization Approaches Under Land Use Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2823-2838, June.
    2. P. C. D. Milly & K. A. Dunne & A. V. Vecchia, 2005. "Global pattern of trends in streamflow and water availability in a changing climate," Nature, Nature, vol. 438(7066), pages 347-350, November.
    3. Aijing Zhang & Chi Zhang & Guobin Fu & Bende Wang & Zhenxin Bao & Hongxing Zheng, 2012. "Assessments of Impacts of Climate Change and Human Activities on Runoff with SWAT for the Huifa River Basin, Northeast China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(8), pages 2199-2217, June.
    4. Cundong Xu & Xiaomeng Hu & Zijin Liu & Xin Wang & Junjiao Tian & Zhihong Zhao, 2023. "Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
    5. Ziqi Yan & Zuhao Zhou & Jiajia Liu & Hao Wang & Dong Li, 2020. "Water use characteristics and impact factors in the Yellow River basin, China," Water International, Taylor & Francis Journals, vol. 45(3), pages 148-168, April.
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