干旱区研究2025，Vol.42Issue(6)：1004-1020,17.DOI:10.13866/j.azr.2025.06.05
水资源承载力评价耦合模型的研究进展与干旱区应用
Research advances and arid zone applications of coupled models for water resources carrying capacity
摘要
Abstract
As the scarcity of global water intensifies,accurate assessments of water resource carrying capacity(WRCC)have become essential for sustainably managing regional water resources and combating the adverse ef-fects of climate change.However,the water resources-ecology-society system is highly complex,involving multi-dimensional interactions anddynamic internal changes that cannot be fully captured by a single evaluation meth-od.This paper reviews the application status and research progress of coupled-model methods for WRCC evalua-tion.A systematic comparative analysis reveals the strengths and limitations of the major evaluation methods—systems analysis,comprehensive evaluation,and machine learning—in WRCC evaluation.Particular attention is devoted to the challenges of these methods in arid regions.The dynamic feedback mechanisms,nonlinear model-ing capabilities,data-driven characteristics,and applicabilities of different methods are analyzed through a hori-zontal comparison study.The review also analyzes the suitabilities and limitations of each method in arid regions and explores the feasibility of coupled models,providing new insights for resolving WRCC issues in these areas.Multimodel integration and data-driven optimization will enhance the generalizability and applicability of models in future,facilitating the transition of water resource management from static evaluation to dynamic simulation and precise prediction.These developments will offer scientific support for sustainable water resource utilization in arid regions and worldwide.关键词
水资源承载力/耦合模型/系统动力学/机器学习/干旱区Key words
water resources carrying capacity/coupling model/system dynamics/machine learning/arid re-gions引用本文复制引用
王艺璇,邓晓红,范慧文青,韩江哲,李宗省..水资源承载力评价耦合模型的研究进展与干旱区应用[J].干旱区研究,2025,42(6):1004-1020,17.基金项目
中国科学院基础与交叉前沿科研先导专项项目(XDB0720303) （XDB0720303）
甘肃省拔尖领军人才项目 （）
中国科学院青年交叉团队项目(JCTD-2022-18) （JCTD-2022-18）
甘肃省科技计划资助-优秀博士生项目(25JRRA533) （25JRRA533）
