NSF-funded project

Flood Control at Watershed Scale

Project Title: Dynamic management of water storage in watersheds for reducing the magnitude of floods

Funding Agency: U.S. National Science Foundation
Period: August 2018 - July 2022
PI: Arturo S. Leon
Co-PI: Craig Glennie and Steven Pennings


Floods are resulting in more loss of lives and damage to property and crops than any other natural disaster in the United States. Structural measures for flood control, such as levees, are constrained to only a small part of a watershed, and are limited in their capacity and robustness to reduce floods. Communities need flood control solutions that provide more storage in the watershed, are flexible to trends in precipitation and land use changes, and are environmentally sustainable. This project will explore an approach for flood control that is based on the dynamic management of water storage in wetlands across the landscape. The strategy will enable adaptive release of water from wetlands hours or days ahead of rainfall events, thereby maximizing storage capacity while at the same time maintaining or increasing wetland ecological function. Our group is also developing a modular and integrated hardware/software platform for interfacing automated siphons/gates, sensors and sensor control/communication to enable remote operation of multiple gates in wetlands, detention ponds and reservoirs.


The specific objectives of the project are to: (1) determine the ecological consequences of manipulating the hydroperiod (water depth changes over time) for wetland communities typical of Harris County, Houston; (2) create a set of modular active controls for dynamic management of storage in wetlands, and (3) examine how the size of wetlands (area and usable storage) in relation to the watershed area, and the degree of water storage management, impact the magnitude of floods at the watershed-scale. To minimize ecological impacts, constraints on water level reductions will be included in the management strategy.





Examining the impact of wetland area, volume and its location within the watershed on reducing the magnitude of floods

We are investigating how the size of wetlands (area and usable storage in relation to the watershed area) and their location within the watershed impact the magnitude of floods at the watershed-scale. Two distinctive watersheds (The Cypress Creek Watershed and the San Jacinto Galveston Bay Watershed) within the Harris County Flood Control District (Houston), which experience recurrent flooding events, are being used as case studies.




Towards real-time flood control


We are developing a Decision Support System (DSS) that can be used in near-real time for guiding on the optimal water releases from a network of wetlands, detention ponds and other storage systems for mitigating floods. This approach enables adaptive release of water from storage systemes (e.g., wetlands, detention ponds, reservoirs) hours or days ahead of rainfall events, thereby maximizing storage capacity and minimizing flooding. For this approach to be implemented, conventional storage systems such as detention ponds would be retrofitted (e.g., adding large gates) and the gates and siphons of these systems would be remotely controlled in an integrated manner using our decision support system. This decision support system incorporates components of hydrological modeling (HEC-HMS), inundation modeling (HEC-RAS) and genetic algorithm optimization. The automated exchange of data between these models is made via HEC-DSS files. To make possible the remote operation of water releases in wetlands and other storage systems in a relatively inexpensive way, we have developed a modular and integrated hardware/software platform for interfacing automated siphons/gates, sensors and sensor control/communication to enable remote operation of thousands of gates in wetlands, detention ponds and reservoirs. Our current integrated system uses 4G cellular network connection although we could also use direct radio, wireless and/or satellite links.





Project Participants

Arturo S. Leon, PhD, PE

Associate Professor

Associate Professor

Professor

Phd Student

PhD Student

PhD Student

MS Student

Current Research Outcomes:

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