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Urban water resources allocation and shortage risk mapping with support vector machine method

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  • Qian Zhang
  • Xiujuan Liang
  • Zhang Fang
  • Tao Jiang
  • Yubo Wang
  • Lei Wang

Abstract

The assessment of urban water shortage risk is crucial to the development of management strategies that enable a more systematic allocation of water resources and effectively reduce societal losses. The present work proposes a comprehensive approach to the thorough evaluation of water shortage risk in an urban basin. We focus on a case study in Jilin City, demonstrating the suitability of the proposed method. The development and utilization of hydric resources in Jilin City is both evaluated and simulated using the MIKE BASIN model, involving hydrological data from 1956 to 2010. Furthermore, this investigation provides a comparison between measured and analog quantity results during the period 2001–2010, yielding an acceptable average relative error of 4.478 %. Five indicators, namely, hazard rate, restorability, vulnerability, recurrence period, and risk level are investigated with the purpose of organizing the assessment system prior to mapping the level of water shortage risk with the SVM model. The data calculated from both the MIKE BASIN model and the emergency conditions are used to formulate five indicators of water shortage assessment. Finally, the level of water shortage risk is determined for six sub-basins in Jilin City. Several schemes are capable of improving the water supply and alleviating the shortage conditions. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • Qian Zhang & Xiujuan Liang & Zhang Fang & Tao Jiang & Yubo Wang & Lei Wang, 2016. "Urban water resources allocation and shortage risk mapping with support vector machine method," 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. 81(2), pages 1209-1228, March.
    • Handle: RePEc:spr:nathaz:v:81:y:2016:i:2:p:1209-1228
    DOI: 10.1007/s11069-015-2129-4
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    References listed on IDEAS

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    1. A. Ireson & C. Makropoulos & C. Maksimovic, 2006. "Water Resources Modelling under Data Scarcity: Coupling MIKE BASIN and ASM Groundwater Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(4), pages 567-590, August.
    2. L. Feng & C. Huang, 2008. "A Risk Assessment Model of Water Shortage Based on Information Diffusion Technology and its Application in Analyzing Carrying Capacity of Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(5), pages 621-633, May.
    3. Hamid Safavi & Mahdieh Esmikhani, 2013. "Conjunctive Use of Surface Water and Groundwater: Application of Support Vector Machines (SVMs) and Genetic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2623-2644, May.
    4. Wenquan Gu & Dongguo Shao & Yufang Jiang, 2012. "Risk Evaluation of Water Shortage in Source Area of Middle Route Project for South-to-North Water Transfer in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(12), pages 3479-3493, September.
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    Cited by:

    1. Jenq-Tzong Shiau, 2021. "Analytical Water Shortage Probabilities and Distributions of Various Lead Times for a Water Supply Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3809-3825, September.

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