Collaborative allocation of water resources considering ecological marginal benefits in a semiarid and cold region

• Developed coupled natural-society WEP-L model for a semiarid basin water cycle. • Proposed ecological marginal benefit function linking bird abundance and wetland replenishment. • Integrated reservoir-regulated rules into WEP-L for feasible intra-year allocation. • Proposed dynamic water allocation strategies balancing ecology-agriculture across hydrological years. Water resource optimization allocation is essential for maintaining ecological balance, promoting economic development, and ensuring social stability within river basins. However, many existing studies treated ecological water requirements as static baselines in allocation models, failing to address the dynamic utilization of water resources efficiently under varying hydrological conditions. In the Tao’er River Basin, a typical semiarid river basin, the combined effects of climate change and human activities have led to a severe imbalance between water supply and demand, particularly in regard to the competition between ecological water replenishment for the Xianghai Wetland, agricultural irrigation, and social water use. There is an urgent need for optimized water resource allocation to ensure the coordinated and sustainable development of these sectors. In this study, we developed the WEP-L model, a coupled natural–societal system, using various ecohydrological monitoring data to analyze the water supply–demand balance under different hydrological conditions. We proposed an allocation plan that considers ecological marginal benefits, agricultural needs, and water use guarantees: 1.04 × 10 8 m 3 for ecological supplementation and 5.16 × 10 8 m 3 for agricultural water in the flat year, adjusted to 0.94 × 10 8 m 3 and 3.60 × 10 8 m 3 in the dry year, respectively. Furthermore, by incorporating reservoir water supply rules into the WEP-L model, we simulated the feasibility of intra-annual water allocation. The proposed allocation scheme concentrates ecological water in spring during flat years and distributes it at a ratio of 80 % in spring and 20 % in autumn during dry years. This study emphasizes the dynamic adjustment of ecological water resources on the basis of environmental conditions and societal needs, aiming to maximize ecological and social benefits. It provides scientific support for optimizing ecological water allocation and offers practical guidance for wetland conservation, agricultural water management, and water resource policy-making.

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Publication Details

Journal
Ecological Indicators
Published
2025-07-05
DOI
https://doi.org/10.1016/j.ecolind.2025.113836
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Collaborative allocation of water resources considering ecological marginal benefits in a semiarid and cold region

A Yinglan, Yuxing Yan, Baolin Xue, Guoqiang Wang et al.
Ecological Indicators
Water resources management and optimization
article

Collaborative allocation of water resources considering ecological marginal benefits in a semiarid and cold region

A Yinglan, Yuxing Yan, Baolin Xue, Guoqiang Wang, Yuntao Wang, Sixuan Wu, Jin Wu
article en

Abstract

• Developed coupled natural-society WEP-L model for a semiarid basin water cycle. • Proposed ecological marginal benefit function linking bird abundance and wetland replenishment. • Integrated reservoir-regulated rules into WEP-L for feasible intra-year allocation. • Proposed dynamic water allocation strategies balancing ecology-agriculture across hydrological years. Water resource optimization allocation is essential for maintaining ecological balance, promoting economic development, and ensuring social stability within river basins. However, many existing studies treated ecological water requirements as static baselines in allocation models, failing to address the dynamic utilization of water resources efficiently under varying hydrological conditions. In the Tao’er River Basin, a typical semiarid river basin, the combined effects of climate change and human activities have led to a severe imbalance between water supply and demand, particularly in regard to the competition between ecological water replenishment for the Xianghai Wetland, agricultural irrigation, and social water use. There is an urgent need for optimized water resource allocation to ensure the coordinated and sustainable development of these sectors. In this study, we developed the WEP-L model, a coupled natural–societal system, using various ecohydrological monitoring data to analyze the water supply–demand balance under different hydrological conditions. We proposed an allocation plan that considers ecological marginal benefits, agricultural needs, and water use guarantees: 1.04 × 10 8 m 3 for ecological supplementation and 5.16 × 10 8 m 3 for agricultural water in the flat year, adjusted to 0.94 × 10 8 m 3 and 3.60 × 10 8 m 3 in the dry year, respectively. Furthermore, by incorporating reservoir water supply rules into the WEP-L model, we simulated the feasibility of intra-annual water allocation. The proposed allocation scheme concentrates ecological water in spring during flat years and distributes it at a ratio of 80 % in spring and 20 % in autumn during dry years. This study emphasizes the dynamic adjustment of ecological water resources on the basis of environmental conditions and societal needs, aiming to maximize ecological and social benefits. It provides scientific support for optimizing ecological water allocation and offers practical guidance for wetland conservation, agricultural water management, and water resource policy-making.

Ecological IndicatorsVol. 178
Beijing Normal University (CN), China Resources (China) (CN)
National Natural Science Foundation of China, National Outstanding Youth Science Fund Project of National Natural Science Foundation of China, Key Technologies Research and Development Program, National Key Research and Development Program of China
Clean water and sanitation
Openalex Percentile: Top 80%
Water resources management and optimization
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