Use of the entropy approach in water resource monitoring systems

Effective management of water resources is possible only with an effectively organized monitoring system. After the emergence and development of information theory, the concept of information entropy found its place in the field of the development of water monitoring systems. The purpose of this work is to review research related to the construction of water monitoring systems and networks that applied the entropy theory in the design process. Methodology. Entropy terms used in the construction of water monitoring systems are summarized. Recent applications of the entropy concept for water monitoring system designs classified by precipitation are reviewed; flow and water level; water quality; soil moisture and groundwater. The integrated method of designing multifactorial monitoring systems is also highlighted. Results. The review analyzes studies and their implementation in the design of water monitoring networks based on entropy. The use of various methods of information theory and their adaptation for use in the design of monitoring networks is demonstrated, with the goal of network design methods being the selection of stations that provide the most information for the monitoring network, while being independent of each other. Through extensive testing, information theory has proven to be a reliable tool for evaluating and designing an optimal water monitoring network. Scientific novelty. This review focuses on studies that have applied information theory or information entropy to construct monitoring networks and systems. Information theory was developed by Shannon in the middle of the last century to measure the information content of a data set and was subsequently applied to solving water resources problems. To date, there are no review studies regarding the design of water monitoring networks based on the concept that entropy will be able to characterize the information specific to the monitoring station or monitoring networks. The main goal is to have the maximum amount of information. Practical significance. The optimal design of the monitoring network can be built based on the specified design criteria; however, the practical application of a new optimal monitoring network is rarely evaluated in a hydrological or other model. It is also important to identify the benefits of entropy-based network design to convince decision-makers of the importance of entropy-based approaches. The optimal network can be subjective, based on the choices made during the entropy calculation and the design method chosen, especially when additional objective functions are considered in the design. This applies to the method chosen to construct the optimal monitoring network, whether it is found using an iterative method where one station is added at a time, or a collection of stations that are added simultaneously. Research has also shown that data length, catchment scale, and the order can affect optimal network design. when using discrete entropy, it was shown that the binning method affects the final network design. Therefore, when selecting options based on the intended application of the monitoring network, a clear understanding and further research is needed to provide recommendations specific to water monitoring networks. In particular, more work is needed on the spatial and temporal scaling of the entropy calculation data to provide robust recommendations for decision-makers.