  Floods in urban areas are becoming more intense due to unplanned urbanization
and more frequent due to climate change. One of the most effective strategies
to alleviate the effects of flooding is the use of flood control reservoirs
such as detention ponds, which attenuate flood waves by storing water and
slowing the release after the storm. Detention ponds can also improve water
quality by allowing the settlement of pollutants inside the reservoir. The
operation of most detention ponds occurs passively, where the outflows are
governed by fixed hydraulic structures such as fully open orifices and weirs.
The operation of detention ponds can be enhanced with active controls: orifices
can be retrofitted with controlled valves, and spillways can have controllable
gates such that their control schedule can be defined in real-time with a model
predictive control (MPC) approach. In this paper, we develop a distributed
quasi-2D hydrologic-hydrodynamic coupled with a reservoir flood routing model
and an optimization approach (MPC) to identify the opening or closing of valves
and movable gates working as spillways. We adapt the optimization problem to
switch from a flood-related cost function to a heuristic function that aims to
increase the detention time when no inflow hydrographs are predicted within a
prediction horizon. The numerical case studies show the potential results of
applying the methods herein developed in a real-world watershed in Sao Paulo,
Brazil. We test the performance of MPC compared to static (i.e., fixed
hydraulic device opening) alternatives with valves either fully or partially
opened. The results indicate that the control algorithm presented in this paper
can achieve greater flood and proxy water quality performance compared to
passive scenarios.
