RESUMO
Good water quality is critical to public health and aquatic ecological security of global reservoirs. In stratified reservoirs, increasing near-term management demands foster extremely high monitoring and forecasting needs. In this study, a management assistant for stratified reservoirs (MASR) was developed, including a wave-driven monitoring platform and interpretation platform for multiple reservoir water quality variables. The wave-driven platform can adapt to the characteristics of water level changes and transmit the monitoring data through a mobile network to the reservoir manager, which are processed by the interpretation platform in real time for near-term management. After several months of application, MASR monitored 1237 groups of valid profile water quality data with an acceptable error, which showed a strong capacity for capturing the water quality dynamics in a stratified reservoir. The effective identification of thermal stratification structures and anoxic zones can help managers to design withdrawal schemes for reservoirs. Moreover, the prediction of algae state based on the back propagation (BP) neural network provided the basis for making operation plans to proactively control algae blooms. Our study provides an economical and convenient solution for stratified reservoirs to address near-term management issues.
