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Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Author

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  • Guangxing Ji

    (College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China
    Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China)

  • Zhizhu Lai

    (Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China)

  • Haibin Xia

    (Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China)

  • Hao Liu

    (Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China)

  • Zheng Wang

    (Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China)

Abstract

The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December.

Suggested Citation

  • Guangxing Ji & Zhizhu Lai & Haibin Xia & Hao Liu & Zheng Wang, 2021. "Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT," Land, MDPI, vol. 10(4), pages 1-19, April.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:4:p:421-:d:536917
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    References listed on IDEAS

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    1. Poerbandono & Miga Julian & Philip Ward, 2014. "Assessment of the effects of climate and land cover changes on river discharge and sediment yield, and an adaptive spatial planning in the Jakarta region," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(2), pages 507-530, September.
    2. Guan, DongJie & Li, HaiFeng & Inohae, Takuro & Su, Weici & Nagaie, Tadashi & Hokao, Kazunori, 2011. "Modeling urban land use change by the integration of cellular automaton and Markov model," Ecological Modelling, Elsevier, vol. 222(20), pages 3761-3772.
    3. Panagopoulos, Y. & Makropoulos, C. & Baltas, E. & Mimikou, M., 2011. "SWAT parameterization for the identification of critical diffuse pollution source areas under data limitations," Ecological Modelling, Elsevier, vol. 222(19), pages 3500-3512.
    4. Lanhai Li & Honggang Xu & Xi Chen & S. Simonovic, 2010. "Streamflow Forecast and Reservoir Operation Performance Assessment Under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(1), pages 83-104, January.
    5. Ike Sari Astuti & Kamalakanta Sahoo & Adam Milewski & Deepak R. Mishra, 2019. "Impact of Land Use Land Cover (LULC) Change on Surface Runoff in an Increasingly Urbanized Tropical Watershed," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(12), pages 4087-4103, September.
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    Citations

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    Cited by:

    1. Guangxing Ji & Leying Wu & Liangdong Wang & Dan Yan & Zhizhu Lai, 2021. "Attribution Analysis of Seasonal Runoff in the Source Region of the Yellow River Using Seasonal Budyko Hypothesis," Land, MDPI, vol. 10(5), pages 1-14, May.
    2. Shuaijun Yue & Guangxing Ji & Junchang Huang & Mingyue Cheng & Yulong Guo & Weiqiang Chen, 2023. "Quantitative Assessment of the Contribution of Climate and Underlying Surface Change to Multiscale Runoff Variation in the Jinsha River Basin, China," Land, MDPI, vol. 12(8), pages 1-16, August.
    3. Guangxing Ji & Junchang Huang & Yulong Guo & Dan Yan, 2022. "Quantitatively Calculating the Contribution of Vegetation Variation to Runoff in the Middle Reaches of Yellow River Using an Adjusted Budyko Formula," Land, MDPI, vol. 11(4), pages 1-12, April.
    4. Swati Maurya & Prashant K. Srivastava & Lu Zhuo & Aradhana Yaduvanshi & R. K. Mall, 2023. "Future Climate Change Impact on the Streamflow of Mahi River Basin Under Different General Circulation Model Scenarios," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2675-2696, May.
    5. Xu Yang & Ruishan Chen & Guangxing Ji & Chao Wang & Yuanda Yang & Jianhua Xu, 2021. "Assessment of Future Water Yield and Water Purification Services in Data Scarce Region of Northwest China," IJERPH, MDPI, vol. 18(17), pages 1-17, August.
    6. Guangxing Ji & Huiyun Song & Hejie Wei & Leying Wu, 2021. "Attribution Analysis of Climate and Anthropic Factors on Runoff and Vegetation Changes in the Source Area of the Yangtze River from 1982 to 2016," Land, MDPI, vol. 10(6), pages 1-13, June.
    7. Qingqing Li & Yanping Cao & Shuling Miao & Xinhe Huang, 2022. "Spatiotemporal Characteristics of Drought and Wet Events and Their Impacts on Agriculture in the Yellow River Basin," Land, MDPI, vol. 11(4), pages 1-20, April.
    8. Mengru Wei & Zhe Yuan & Jijun Xu & Mengqi Shi & Xin Wen, 2022. "Attribution Assessment and Prediction of Runoff Change in the Han River Basin, China," IJERPH, MDPI, vol. 19(4), pages 1-22, February.

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