Entropy and kriging approach to rainfall network design

Hydrological data are the basic ingredients for planning, constructing, and operating of hydraulic structures. A well-designed rainfall network can accurately provide and reflect the information of rainfall in a catchment. However, in past studies, the required number and optimal location of rain gauge stations have yet to produce a satisfactory result. A more accurate design is required. Hence, in this study, a proposed model composed of kriging and entropy with probability distribution function is introduced to relocate the rainfall network and to obtain the optimal design with the minimum number of rain gauges. The ordinary kriging is used to generate rainfall data of potential locations where rain gauge stations may be installed. The information entropy based on probability is used to measure the uncertainty of rainfall distribution. The probability distribution function will be introduced to fit the statistical characteristics of data of the rain gauges. By calculating the joint entropy and the transferable information, the relocated rain gauges are prioritized and the minimum number and location of the rain gauges in the catchment can be obtained to construct the optimal rainfall network to replace the existing rainfall network.