An innovative mathematical framework for complete three-dimensional drought structures

报告摘要：Drought displays dynamic and uncertain spatiotemporal characteristics, thus it is typically not confined to fixed temporal-spatial boundaries. Existing drought clustering methods often involve spatially clustering drought points or grids into patches, subsequently connected over time to form three-dimensional structures. Despite this process being able to extract three-dimensional drought clusters, it is likely to overlook mild or relatively small, isolated drought patches. To overcome this limitation, this paper presented an effective method (named STDCLUSTER) for identifying drought clusters with complete three-dimensional structures. The method initially employed run theory to extract drought events as“lines”and subsequently clustered these events using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. A case study on the 2006 flash drought in the Yangtze River Basin demonstrated that STD-CLUSTER successfully clustered drought events and ensured the integrity of drought clusters by considering small, isolated, or disconnected patches. Additionally, an in-depth analysis using STD-CLUSTER examined seasonal drought events in China from 1991 to 2022, identifying a total of 35 drought clusters. These clusters began and ended with small-area patches, exhibiting features of expansion, contraction, spread, merging, and splitting over time. Furthermore, seasonal changes significantly influenced the evolution of drought clusters, with affected area and severity increasing in spring and summer and decreasing in autumn and winter. The applicability of the proposed method extends beyond various geographical regions and time scales, providing effective support for comprehensively investigating the spatiotemporal evolution of drought.

报告人简介：张敏，广州大学数学与信息科学学院，副教授。2016年毕业于天津大学，2016-2019年在澳大利亚科廷大学从事博士后研究，主要研究方向为最优化理论、方法及其应用。2019年获得中国科学院百人计划青年项目支持，在中科院新疆生态与地理研究所担任副研究员，2024年获得广州大学“百人计划青年杰出人才”，入职广州大学数学与信息科学学院。近五年开展的研究工作主要围绕优化技术与气候变化及水资源管理相关应用之间的交叉科学问题，部分研究成果发表在SIAM Journal on Optimization, Mathematical Programming, IEEE Transaction on Information Theory，Science of The Total Environment，Journal of Hydrology：Regional Study等期刊，主持国家级、省部级基金项目5项。