An algorithm for optimisation of a rain gauge network based on geostatistics and entropy concepts using GIS

Abstract

There is a high level of spatio-temporal variability in rainfall events over a region. Rain gauges provide point measurements that are interpolated to estimate the rainfall in other points of a region or in order to estimate the regional depth of rainfall. Due to limited numbers of rain gauges that can be deployed, it is important to plan for the optimal number and locations of rain gauges in a region. Because of several factors that can affect the optimal number of stations as well as their locations, development of optimisation models for determining the number of rain gauges and their locations within a region is necessary. In this study, an optimisation model for determining the number and location of the rain gauges is proposed. The objectives of the model are maximising the minimum transformation entropy and minimising the rainfall estimation error. To determine the optimal number of new rain gauges, the candidate points, which are those with the maximum variance of Kriging error and the minimum information transformation entropy, are prioritised according to their participation in the transformation. A mountainous sub-basin has been considered as the case study. Applying the proposed approach to the case study, 17 candidate points are determined for deployment of new rain gauges. Finally, 10 of the candidate points are selected to be added to the current rain gauge network. The results of the study show that joint consideration of spatial analysis error and information transformation entropy can highly improve the optimal design of a rain gauge network.