A two-phase copula entropy-based multiobjective optimization approach to hydrometeorological gauge network design

摘要

Highlights?A two-phase copula entropy-based approach is developed for network design.?The copula entropy-based MI estimation method is more effective than JH method.?This two-phase approach is verified by using three model evaluation measures.AbstractHydrometeorological data are needed for obtaining point and areal mean, quantifying the spatial variability of hydrometeorological variables, and calibration and verification of hydrometeorological models. Hydrometeorological networks are utilized to collect such data. Since data collection is expensive, it is essential to design an optimal network based on the minimal number of hydrometeorological stations in order to reduce costs. This study proposes a two-phase copula entropy- based multiobjective optimization approach that includes: (1) copula entropy-based directional information transfer (CDIT) for clustering the potential hydrometeorological gauges into several groups, and (2) multiobjective method for selecting the optimal combination of gauges for regionalize