水力发电学报2026，Vol.45Issue(4)：73-85,13.DOI:10.11660/slfdxb.20260406
耦合气象水文要素的流域极端径流场景优选生成方法
Method of generating extreme runoff scenarios for river basins coupled with meteorological and hydrological elements
摘要
Abstract
Extreme meteorological events have been occurring frequently worldwide,posing dual challenges to renewable energy integration and secure power supply for the grid systems with a high hydropower proportion.To enhance the systems'dynamic responding capability to such extreme events,this study describes a new methodology for generating and selecting the extreme streamflow scenarios of a river basin by coupling its key meteorological and hydrological elements.First,we use sensitivity analysis based on the Shapley additive explanations(SHAP)theory to reveal the critical influence of precipitation,soil moisture content,and air temperature over the basin on its streamflow.Then,an adaptive machine learning framework by coupling meteorological-hydrological elements with the streamflow,is constructed.It uses a Markov Chain Monte Carlo(MCMC)approach to simulate the extreme meteorological-hydrological events,and integrates the historical observational data as inputs to generate an ensemble of the streamflow scenarios.Finally,the scenarios are integrated using an enhanced K-means clustering algorithm,and the dissimilarity between individual scenarios within each cluster to the cluster centroid is calculated by combining with a modified Dynamic Time Warping(DTW)algorithm to select the optimized extreme streamflow scenarios based on the principle of maximum dissimilarity.Our method proves effective and applicable through validation using the streamflow data(1952-2006)from the Wujiang River basin in Southwest China and the corresponding meteorological-hydrological records.关键词
极端径流场景/机器学习算法/马尔科夫链/沙普利加性解释理论Key words
extreme runoff scenarios/machine learning algorithm/Markov chain/Shapley additive explanations theory分类
建筑与水利引用本文复制引用
陈刚,王永灿,杜成锐,罗彬,王亮,杨俊文,聂状..耦合气象水文要素的流域极端径流场景优选生成方法[J].水力发电学报,2026,45(4):73-85,13.基金项目
国网四川省电力公司科技项目(52199723002B) （52199723002B）
