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The increasing access to inexpensive 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 developed a novel nonlinear state-space model of hydrologic and hydrodynamic processes in watersheds, reservoirs, and one-dimensional channels. The model was tested under different types of reservoir control strategies based on real-time measurements (reactive control) and predictions of the future behavior of the system (predictive control) using rainfall forecastings. We applied the modeling approach in a system composed of a single watershed, reservoir, and channel connected in series for the observed rainfall data in San Antonio. 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 nonlinear model predictive control strategy to control stormwater systems because of 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. [ABSTRACT FROM AUTHOR]

The natural hydrologic flow regime is altered by urbanization, which can be mitigated through best management practices (BMPs) or low impact development (LID). Typically, the effectiveness of different management scenarios is tested by comparing post- and predevelopment instantaneous peak flows. This approach, however, does not capture the extent of hydrologic change and the effect on downstream communities. A new hydrologic sustainability metric is presented here to quantify the impact of urbanization on downstream water bodies on the basis of the inundation dynamics of the flow regime. The hydrologic footprint residence (HFR) is designed to capture both temporal and spatial hydrological changes to an event-based flow regime by calculating the inundated areas and duration of a flood. The HFR is demonstrated for a hypothetical watershed and a watershed on the Texas A&M University Campus, located in College Station, Texas. For the campus watershed, three design storms (2-, 10-, and 100-year) and a set of historical events (during the period 1978-2009) are simulated for various management scenarios, representing predevelopment conditions, development on campus, BMP-based control, and LID-based control. The results indicate that the HFR can better capture alterations to the shape of the hydrograph compared with the use of the peak flow only. [ABSTRACT FROM AUTHOR]