Information entropy for assisting decision-making for critical events in surface water quality management

The information entropy method, based on mass sampling data processing, has been widely applied in environment monitoring and management. However, previous efforts have been mainly limited to the optimization of stations in discrete space with no association to critical events and their associated temporal scale. In particular, further research on integrating water quality monitoring under critical events (such a spillway accident) and the related cost-benefit analysis of environment management decisions are needed. In this study, we give an entropy-based paradigm of water quality reaction criteria R, which is analogous to the definition of Gibbs free energy (ΔG) in thermodynamics. Then we propose a systematic framework of entropy prisms (HPrisms) with four entropy indexes: dilution index (E), flux index (F), spatial entropy index (G_x) and temporal entropy index (G_t). They describe the pollutants transport process in water bodies from different perspectives, facing different water environmental management decisions. The corresponding reaction criteria of these four entropy indexes for different water quality management scenarios are defined for different spatiotemporal scales where different criteria are applicable. The method has value in emergency monitoring in rivers and lakes, useful for anomaly detection, key point identification and other water environment management scenarios. This study is a generic theoretical framework so far, and we will present specific critical cases for management reaction criteria to find the quantitative relationship between reaction criteria with information entropy indexes.