Entropy theory-based criterion for hydrometric network evaluation and design: Maximum information minimum redundancy



[1] Hydrometric information constitutes the fundamental input for planning, design, operation, and management of water resources systems. How to optimally site monitoring gauges such that they are effective and efficient in gathering the hydrometric information or data has received considerable attention. This paper presents a generic approach for the design (or evaluation) of hydrometric networks. First, an entropy theory-based criterion, named as maximum information minimum redundancy (MIMR), is proposed. The MIMR criterion maximizes the joint entropy of stations within the optimal set, and the transinformation between stations within and outside of the optimal set. Meanwhile, it insures that the optimal set contains minimum duplicated information. An easy-to-implement greedy ranking algorithm is developed to accomplish the MIMR selection. Two case studies are presented to illustrate the applicability of MIMR in hydrometric network evaluation and design. We also compare the MIMR selection with another entropy-based approach. Results illustrate that MIMR is apt at finding stations with high information content, and locating independent stations. The proposed approach is suitable for design (or evaluation) of any type of hydrometric network.