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Study on Ecological Allocation of Mine Water in Mining Area Based on Long-term Rainfall Forecast

Author

Listed:
  • Guan-jun Lei

    (North China University of Water Resources and Electric Power)

  • Chang-shun Liu

    (Water Resources Research Institute, China Institute of Water Resources and Hydropower Research, State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin)

  • Wenchuan Wang

    (North China University of Water Resources and Electric Power)

  • Jun-xian Yin

    (Water Resources Research Institute, China Institute of Water Resources and Hydropower Research, State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin)

  • Hao Wang

    (Water Resources Research Institute, China Institute of Water Resources and Hydropower Research, State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin)

Abstract

Based on the mine water produced by mining, to improve the ecological environment, the optimal allocation of mine water resources is studied. To reduce the uncertainty of the calculation results of ecological water demand, the wolf colony algorithm neural network model is used for long-term rainfall forecast. Combined with the forecast annual rainfall, the ecological water demand is classified and calculated. The results show that the ecological water demand based on rainfall forecast can reduce the allocation of water resources in wet years to ecological, so that the surplus water resources can be used in industries, irrigation, and other aspects that can create economic benefits, and improve the utilization efficiency of water resources. The ecological allocation model of mine water based on long-term rainfall forecast can reduce the uncertainty of regional water resources allocation based on rainfall forecast, which has good guiding significance and practical value for the optimal allocation of water resources in arid and water shortage areas.

Suggested Citation

  • Guan-jun Lei & Chang-shun Liu & Wenchuan Wang & Jun-xian Yin & Hao Wang, 2022. "Study on Ecological Allocation of Mine Water in Mining Area Based on Long-term Rainfall Forecast," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5545-5563, November.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:14:d:10.1007_s11269-022-03311-0
    DOI: 10.1007/s11269-022-03311-0
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    References listed on IDEAS

    as
    1. Kagiso Samuel More & Christian Wolkersdorfer, 2022. "Predicting and Forecasting Mine Water Parameters Using a Hybrid Intelligent System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2813-2826, June.
    2. Wei Li & Jianzhong Zhou & Lu Chen & Kuaile Feng & Hairong Zhang & Changqing Meng & Na Sun, 2019. "Upper and Lower Bound Interval Forecasting Methodology Based on Ideal Boundary and Multiple Linear Regression Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 1203-1215, February.
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