The response of sediment phosphorus retention and release to reservoir operations: Numerical simulation and surrogate model development

Dam impoundment causes significant phosphorus (P) retention in reservoir sediment. This makes sediment P release a serious water quality threat in areas where external P loads are being controlled. Reservoir operation strategies affect sediment P retention and release through complex influence on hydrodynamic, temperature, algal and sediment conditions. However, the spatiotemporal response of P retention and release to reservoir operations remains unclear. This study uses a high-fidelity hydrodynamic-eutrophication-sediment model to investigate spatiotemporal variation in sediment P retention and release in a large reservoir in China (i.e., the Danjiangkou Reservoir) as well as associated impacts caused by reservoir operations. Modeling results reveal significant sediment P release in the reservoir (5213 tons annually), from June to October in particular. The intermittent increase in submerged soil area surrounding the reservoir is the dominant factor for P release during the initial stage of this period, while an acute decrease in bottom oxygen conditions caused by thermal stratification in the deep-water zone is the dominant factor during the middle and latter stages. Moreover, the inherent complexity of reservoir P cycling along with the large number of state variables limit the usage of high-fidelity P models in optimizing reservoir operations. To resolve this problem, we apply a dynamic artificial neural network (i.e., nonlinear autoregressive network with exogenous inputs) to develop a surrogate model to predict the response of sediment P release to reservoir operations. The surrogate model is successful in predicting the annual time series of P release with a dramatic reduction in computational burden. It can easily be coupled with a reservoir operation optimization model, thereby enabling operators to identify optimal operation rules to support reservoir socioeconomic functions while mitigating the threats from sediment P legacy. (C) 2020 Elsevier Ltd. All rights reserved.