Developing an entropy-based model of spatial information estimation and its application in the design of precipitation gauge networks

摘要: Summary This study proposed a spatial information estimation model for the analysis of precipitation gauge networks, to improve on previous methods based theory. The employs two-dimensional transinformation–distance ( T – D ) relationship in conjunction with multivariate approximation estimate transinformation ungauged locations from existing stations, while taking into consideration influence multiple stations and anisotropy. is used evaluate distribution data characteristics transfer, which are then applied optimization algorithm selection additional station locations. framework was implemented investigate temporal patterns content Shihmen Reservoir watershed. results demonstrate obvious anisotropy associated delivery information. By comparing different cases, it determined that efficiency dominates content, such eccentricity merely supplemental. Efficiency also heavily influenced by scale. For covering long intervals (monthly annual), relatively high, uncertainty or heterogeneity hourly daily time series produces low correlations due inefficient confirmed optimal location new lies close center zones. Additional could considerably; however, margin improvement decreases number stations.