Centroidal Voronoi tessellation based methods for optimal rain gauge location prediction

JOURNAL OF HYDROLOGY

卷:584

Article

Di, Zichao (Wendy)¹  Maggioni, Viviana²  Mei, Yiwen²  Vazquez, Marilyn³  Houser, Paul⁴  Emelianenko, Maria⁵ 

[1] Argonne Natl Lab, Math & Comp Sci Div, Lemont, IL 60439 USA

[2] George Mason Univ, Dept Civil Environm & Infrastruct Engn, Fairfax, VA 22030 USA

[3] Ohio State Univ, Math Biosci Inst, Columbus, OH 43210 USA

[4] George Mason Univ, Dept Geog & Geoinformat Sci, Fairfax, VA 22030 USA

[5] George Mason Univ, Dept Math Sci, Fairfax, VA 22030 USA

关键词: Rain gauges;    CVT;    Decorrelation;    Optimal placement;   

DOI  :  10.1016/j.jhydrol.2020.124651

来源: Elsevier

【 摘 要 】

With more satellite and model precipitation data becoming available, new analytical methods are needed that can take advantage of emerging data patterns to make well informed predictions in many hydrological applications. We propose a new strategy where we extract precipitation variability patterns and use correlation map to build the resulting density map that serves as an input to centroidal Voronoi tessellation construction that optimizes placement of precipitation gauges. We provide results of numerical experiments based on the data from the Alto-Adige region in Northern Italy and Oklahoma and compare them against actual gauge locations. This method provides an automated way for choosing new gauge locations and can be generalized to include physical constraints and to tackle other types of resource allocation problems.

【 授权许可】

Free