arXiv subjects

Eduardo M. Mendiondo

Publications and source records attributed to Eduardo M. Mendiondo.

3 recordsLinked to original sources

arXiv2024

Real-time Regulation of Detention Ponds via Feedback Control: Balancing Flood Mitigation and Water Quality

Detention ponds can mitigate flooding and improve water quality by allowing the settlement of pollutants. Typically, they are operated with fully open orifices and weirs (i.e., passive control). Active controls can improve the performance of these systems: orifices can be retrofitted with controlled valves and spillways can have controllable gates. The real-time optimal operation of its hydraulic devices can be achieved with techniques such as Model Predictive Control (MPC). A distributed quasi-2D hydrologic-hydrodynamic coupled with a reservoir flood routing model is developed and integrated with an MPC algorithm to estimate the operation of valves and movable gates. The control optimization problem is adapted to switch from a flood-related algorithm focusing on mitigating floods to a heuristic objective function that aims to increase the detention time when no inflow hydrographs are predicted. The case studies show the potential of applying the methods developed in a catchment in Sao Paulo, Brazil. The performance of MPC compared to alternatives with either fully or partially open valves and gates are tested. Comparisons with HEC-RAS 2D indicate volume and peak flow errors of approximately 1.4% and 0.91% for the watershed module. Simulating two consecutive 10-year storms shows that the MPC strategy can achieve peak flow reductions of 79%. In contrast, passive control has nearly half of the performance. A 1-year continuous simulation results show that the passive scenario with 25% of the valves opened can treat 12% more runoff compared to the developed MPC approach, with an average detention time of approximately 6 hours. For the MPC approach, the average detention time is nearly 14 hours indicating that both control techniques can treat similar volumes; however, the proxy water quality for the MPC approach is enhanced due to the longer detention times.

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arXiv2023

Global Optimization-Based Calibration Algorithm for a 2D Distributed Hydrologic-Hydrodynamic and Water Quality Model

Hydrodynamic models with rain-on-the-grid capabilities are usually computationally expensive. This makes the use of automatic calibration algorithms hard to apply due to the large number of model runs. However, with the recent advances in parallel processing, computational resources, and increasing high-resolution climatologic and GIS data, high-resolution hydrodynamic models can be used for optimization-based calibration. This paper presents a global optimization-based algorithm to calibrate a fully distributed hydrologic-hydrodynamic and water quality model (HydroPol2D) using observed data (i.e., discharge, or pollutant concentration) as input. The algorithm can find a near-optimal set of parameters to explain observed gauged data. The modeling framework presented here, although applied in a poorly-gauged catchment, can be adapted for catchments with more detailed observations. We applied the algorithm in different cases of the V-Tilted Catchment, the Wooden-Board catchment, and in an existing urban catchment with heterogeneous data. The results of automatic calibration indicate $\mathrm{NSE} = 0.99$ for the V-Tilted catchment, $\mathrm{RMSE} = 830~\mathrm{mgL^{-1}}$ for salt concentration pollutographs (i.e., 8.3% of the event mean concentration), and $\mathrm{NSE} = 0.89$ for the urban catchment case study. This paper also explores the issue of equifinality in modeling calibration (EqMC). Equifinality is defined as the set of different parameter combinations that can provide equally good or accepted results, within the physical parameter ranges. EqMC decreases with the number of events and increases with the choice of partially or nonproducing runoff ones. Furthermore, results indicate that providing more accurate parameter ranges based on a priori knowledge of the catchment is fundamental to reduce the chances of finding a set of parameters with equifinality.

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arXiv2022

Flood Risk Mitigation and Valve Control in Stormwater Systems: State-Space Modeling, Control Algorithms, and Case Studies

The increasing access to non-expensive sensors, computing power, and more accurate forecasting of storm events provides unique opportunities to shift flood management practices from static approaches to an optimization-based real-time control (RTC) of urban drainage systems. Recent studies have addressed a plethora of strategies for flood control in stormwater reservoirs; however, advanced control theoretic techniques are not yet fully investigated and applied to these systems. In addition, there is an absence of a coupled integrated control model for systems composed of watersheds, reservoirs, and channels for flood mitigation. To this end, we develop a novel state-space model of hydrologic and hydrodynamic processes in reservoirs and one-dimensional channels. The model is tested under different types of reservoir control strategies based on real-time measurements (reactive control), and based on predictions of the future behavior of the system (predictive control) using rainfall forecastings. We apply the modeling approach in a system composed by a single watershed, reservoir, and a channel connected in series, respectively, for the San Antonio observed rainfall data. Results indicate that for flood mitigation, the predictive control strategy outperforms the reactive controls not only when applied for synthetic design storm events, but also for a continuous simulation. Moreover, the predictive control strategy requires smaller valve operations, while still guaranteeing efficient hydrological performance. From the results, we recommend the use of the model predictive control strategy to control stormwater systems due to the ability to handle different objective functions, which can be altered according to rainfall forecasting and shift the reservoir operation from flood-based control to strategies focused on increasing detention times, depending on the forecasting.

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