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Quantitative assessment of adaptive measures on optimal water resources allocation by using reliability, resilience, vulnerability indicators

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Abstract

Water resources allocation is facing great challenge, since hydrological series have shown non-stationarity with high uncertainty due to climate change and human activities. Adaptive measures are suggested to respond to the challenge. Aiming at quantitatively assess the impact of adaptive measures on optimal water resources allocation, we proposed a framework based on reliability, resilience and vulnerability indicators. Two representative concentration pathway (RCP) scenarios (RCP2.6 and RCP4.5) of one global climate model were used to project future climate, and the variable infiltration capacity hydrological model was used to simulate streamflow. Three adaptive measures [water saving measure, water transfer project, dynamic control of flood limiting water levels (FLWLs) for reservoir operation] were combined to eight scenarios, then scenarios were applied to the allocation model to get different optimal allocation schemes which were assessed by RRV indicators. The results show that water saving measure decreases the vulnerability by 79 × 106 m3, water transfer project decreases the resilience by 17% in every scenario and dynamic control of FLWLs increases the reliability by 23.53% to the greatest scale. But the impacts of latter two adaptive measures are restricted to the areas which are geographically close to water supply projects. The uneven spatial distribution and decrease of streamflow will increase the risk of water shortage in the future. Optimal water allocation can reduce this risk and make 23 of 28 operational zones stable. Water saving measure is significantly valid in the rest 5 operational zones, but its impact is not positive to all water use sectors. Overall, our study helps understanding the interaction between adaptive measures and water resources system, and making guidelines for effective adaptation planning.

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Acknowledgements

The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (Nos. 51879194, 91647106, 51579183).

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Authors and Affiliations

  1. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China

    Hui Zou, Dedi Liu, Shenglian Guo, Lihua Xiong, Pan Liu, Jiabo Yin, Yujie Zeng, Jiayu Zhang & Youjiang Shen

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  1. Hui Zou
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Zou, H., Liu, D., Guo, S. et al. Quantitative assessment of adaptive measures on optimal water resources allocation by using reliability, resilience, vulnerability indicators. Stoch Environ Res Risk Assess 34, 103–119 (2020). https://doi.org/10.1007/s00477-019-01753-4

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