Mathematical Modeling for Decision-Making of Observation Timing and Workload for Cost-Effective River Environmental Management

This is the authors' abstract. We don't add key points for this paper.

River environmental management contains controlling physical and biological processes. Both processes are different phenomena with each other but are in common continuous-time. In general, the physical processes related to river hydraulics can be measured frequently and the continuous-time nature is captured. On the other hand, the biological processes like growth of population and organisms cannot be observed so frequently. Their observation is thus actually discrete-time. Many models for environmental management assume observation of the biological processes to be continuous-time, which is inconsistent with the reality. The objective of this paper is to develop a new model that can harmonize the continuous and discrete natures in management of the biological processes. This is achieved through employing a recent stochastic process formalism. Focusing on algae population management in river environment, we derive the optimality equation to determine the most cost-effective harvesting policy (observation timing and workload) based on discrete observations. A computational example with practical implications is presented focusing on a problem of benthic algae population management in Hii River, Japan.