IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i4p421-d536917.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/4/421/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/10/4/421/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Yuanyuan & Bao, Wenkai & Liu, Yansui, 2020. "Scenario simulation of land system change in the Beijing-Tianjin-Hebei region," Land Use Policy, Elsevier, vol. 96(C).
    2. Shan, Nan & Ruan, Xiao-Hong & Xu, Jing & Pan, Zha-Rong, 2014. "Estimating the optimal width of buffer strip for nonpoint source pollution control in the Three Gorges Reservoir Area, China," Ecological Modelling, Elsevier, vol. 276(C), pages 51-63.
    3. Boongaling, Cheamson Garret K. & Faustino-Eslava, Decibel V. & Lansigan, Felino P., 2018. "Modeling land use change impacts on hydrology and the use of landscape metrics as tools for watershed management: The case of an ungauged catchment in the Philippines," Land Use Policy, Elsevier, vol. 72(C), pages 116-128.
    4. Katarzyna Kocur-Bera & Anna Lyjak, 2021. "Analysis of Changes in Agricultural Use of Land After Poland’s Accession to the EU," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 517-533.
    5. Umut Okkan & Umut Kirdemir, 2018. "Investigation of the Behavior of an Agricultural-Operated Dam Reservoir Under RCP Scenarios of AR5-IPCC," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(8), pages 2847-2866, June.
    6. Li Li & Qidi Yu & Ling Gao & Bin Yu & Zhipeng Lu, 2021. "The Effect of Urban Land-Use Change on Runoff Water Quality: A Case Study in Hangzhou City," IJERPH, MDPI, vol. 18(20), pages 1-12, October.
    7. Zhang, Dejian & Chen, Xingwei & Yao, Huaxia & Lin, Bingqing, 2015. "Improved calibration scheme of SWAT by separating wet and dry seasons," Ecological Modelling, Elsevier, vol. 301(C), pages 54-61.
    8. Michel Opelele Omeno & Ying Yu & Wenyi Fan & Tolerant Lubalega & Chen Chen & Claude Kachaka Sudi Kaiko, 2021. "Analysis of the Impact of Land-Use/Land-Cover Change on Land-Surface Temperature in the Villages within the Luki Biosphere Reserve," Sustainability, MDPI, vol. 13(20), pages 1-23, October.
    9. Ramesh P. Rudra & Balew A. Mekonnen & Rituraj Shukla & Narayan Kumar Shrestha & Pradeep K. Goel & Prasad Daggupati & Asim Biswas, 2020. "Currents Status, Challenges, and Future Directions in Identifying Critical Source Areas for Non-Point Source Pollution in Canadian Conditions," Agriculture, MDPI, vol. 10(10), pages 1-25, October.
    10. Han, Yu & Jia, Haifeng, 2017. "Simulating the spatial dynamics of urban growth with an integrated modeling approach: A case study of Foshan, China," Ecological Modelling, Elsevier, vol. 353(C), pages 107-116.
    11. Jing Yang & Feng Shi & Yizhong Sun & Jie Zhu, 2019. "A Cellular Automata Model Constrained by Spatiotemporal Heterogeneity of the Urban Development Strategy for Simulating Land-use Change: A Case Study in Nanjing City, China," Sustainability, MDPI, vol. 11(15), pages 1-19, July.
    12. Li, Sheng & Nadolnyak, Denis & Hartarska, Valentina, 2019. "Agricultural land conversion: Impacts of economic and natural risk factors in a coastal area," Land Use Policy, Elsevier, vol. 80(C), pages 380-390.
    13. Sarah Hasan & Wenzhong Shi & Xiaolin Zhu & Sawaid Abbas & Hafiz Usman Ahmed Khan, 2020. "Future Simulation of Land Use Changes in Rapidly Urbanizing South China Based on Land Change Modeler and Remote Sensing Data," Sustainability, MDPI, vol. 12(11), pages 1-24, May.
    14. Harik, G. & Alameddine, I. & Zurayk, R. & El-Fadel, M., 2023. "Uncertainty in forecasting land cover land use at a watershed scale: Towards enhanced sustainable land management," Ecological Modelling, Elsevier, vol. 486(C).
    15. Zhang, Chunxiao & Chen, Min & Li, Rongrong & Fang, Chaoyang & Lin, Hui, 2016. "What's going on about geo-process modeling in virtual geographic environments (VGEs)," Ecological Modelling, Elsevier, vol. 319(C), pages 147-154.
    16. Xiaoli Hu & Xin Li & Ling Lu, 2018. "Modeling the Land Use Change in an Arid Oasis Constrained by Water Resources and Environmental Policy Change Using Cellular Automata Models," Sustainability, MDPI, vol. 10(8), pages 1-14, August.
    17. Ali Assani & Raphaëlle Landry & Jonathan Daigle & Alain Chalifour, 2011. "Reservoirs Effects on the Interannual Variability of Winter and Spring Streamflow in the St-Maurice River Watershed (Quebec, Canada)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(14), pages 3661-3675, November.
    18. Yu Sun & Susanna Tong & Mao Fang & Y. Yang, 2013. "Exploring the effects of population growth on future land use change in the Las Vegas Wash watershed: an integrated approach of geospatial modeling and analytics," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 15(6), pages 1495-1515, December.
    19. Eren Germeç & Okan Ürker, 2023. "Investigation of a SWAT Model for Environmental Health Management Based on the Water Quality Parameters of a Stream System in Central Anatolia (Türkiye)," Sustainability, MDPI, vol. 15(18), pages 1-16, September.
    20. Theint Thandar Bol & Timothy O. Randhir, 2024. "Predicting Land Use and Land Cover Changes in the Chindwin River Watershed of Myanmar Using Multilayer Perceptron-Artificial Neural Networks," Land, MDPI, vol. 13(8), pages 1-20, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:10:y:2021:i:4:p:421-:d:536917. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.