Probabilistic eutrophication risk mapping in response to reservoir remediation

Abstract

Reservoir eutrophication is a critical natural hazard in countries with rapid agricultural and industrial development. To simulate the eutrophication of the Fengshan Reservoir, the algal bloom occurrence patterns in the reservoir were modeled using the Environmental Fluid Dynamics Code (EFDC) for understanding the algal dynamics. The calibration and validation of the EFDC were performed by comparing the model results with field data. The model was calibrated against the hydrodynamic data, including the water level and water temperature, and water quality data from four monitoring stations in the study area. Uncertainty analysis was conducted using a perturbance moment method (PMM) with the EFDC model. Parameter uncertainty was considered in this study. The order of importance of model parameters in terms of their uncertainty contribution to the overall uncertainty of water quality simulations was obtained. The calibrated and validated model was then used to investigate three contaminant remediation scenarios: (a) increasing the water level, (b) dilution, and (c) reaeration. Operational uncertainty was also considered, as there exists variability in the remediation effort and project execution for a complex engineering system like reservoirs. Finally, probabilistic eutrophication risk mapping was established for each remediation effort to facilitate decision-making in eutrophication risk assessment.