Work

A Multi-Agent and Constraint-Validation Framework for Sustainable Yellow River Water Allocation in Henan Province, China

Year: 2026

Type: article

Abstract: Reliable and sustainable Yellow River water allocation in Henan Province, China, requires the coordinated use of heterogeneous evidence, sequential allocation calculations, operational constraints, and ecological-management requirements. Existing approaches often lack explicit coordination among demand forecasting, supply calibration, intake-gate allocation, and constraint-triggered feedback. This study proposes a constraint-gated multi-agent framework to support regional Yellow River water allocation. The framework integrates multi-source evidence retrieval with a sequential demand–supply–intake computational chain and sustainability-oriented constraint validation. Regional demand is predicted using a quota-prior-guided neural network (QPG-NN) that incorporates quota-derived demand information as both an input feature and a soft consistency constraint. Supply is calibrated using historical trends and demonstrated supply capacity, while intake-gate allocation combines historical trends, recent operational inertia, and regional supply adjustment. Ecological-water satisfaction, regional supply reliability, and sectoral satisfaction balance are embedded as auditable screening criteria. Experiments using 2015–2023 data from 13 prefecture-level regions in the Henan Yellow River supply area showed that QPG-NN achieved a mean RMSE of 0.736 × 108 m3 and an R2 of 0.976. Supply-calibration MAPE decreased from 10.05% to 5.76%, while intake-allocation WAPE decreased from 15.75% to 3.8%. The proposed framework obtained the highest mean expert score of 4.52 among the evaluated methods. In four synthetic drought scenarios, all cases triggered supply recalculation and passed a second constraint-validation evaluation after one automatic recalculation cycle. These results support the framework’s ability to coordinate traceable numerical computation, constraint-triggered feedback, and sustainability-oriented screening within an auditable water-allocation workflow.

Source: Sustainability

DOI: 10.3390/su18178768

Authors: Libo Yang, Ying Cao, Ning Yang, Libo Mao, Xiuyu Zhang

Institution: North China University of Water Resources and Electric Power

Language: English

Topic: Water resources management and optimization

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: gold

Estimated APC paid: $2,896