Assessment of Stormwater infrastructure for mitigating flooding and non-point source pollution

PROJECT PI

Dr. Qin Qian, Associate Professor, Department of Civil & Environmental Engineering

SHORT DESCRIPTION

Flooding has been the top natural hazards to coastal and inland communities alike in the State of Texas. It is also a major culprit for water quality issues in the estuaries and bays, and it contributes to the hypoxia in the Gulf of Mexico, through enhancing nutrient and sediment loading or simply suppressing the oxygen exchange between salty water and atmosphere. In recent years, indications are that the severe storms and catastrophic flooding along the Gulf Coast have become more frequent. Houston, for example, experiences three extreme floods in the past three consecutively years, namely the Memorial Day flood in May 2015, the Tax Day flood in May 2016, and the Hurricane Harvey in August 2017. The precipitation frequency estimates (PFEs), which serve as the standards for designing stormwater, flood control, and transportation infrastructures, have not been revised for the state of Texas since the 1970s but will be seeing its first update (NOAA Atlas-14) in later 2018. What is obvious from the recent floods is that stormwater and wastewater infrastructures for many coastal and near-coastal communities are inadequately prepared for the frequency and magnitude of storms. Such infrastructure upgrades, though often necessary, are costly to implement and maintain. Of critical need is a comprehensive study that would help the communities assess their exposure to flooding risk using up-to-date precipitation frequency estimates, and to determine the most cost-effective measures to implement that will address both the stormwater runoff and downstream water quality issues arising therefrom.

FULL DESCRIPTION

The proposed project is a joint effort between UT Arlington and Lamar University seeking to answer to this need. In this project, we focus on the Neches River Watershed upstream of I-10. The area is highly vulnerable to flooding: it was almost completely submerged during Hurricane Harvey, and non-point pollution has been a perennial concern over the watershed. Our plan is to establish a SWMM-based modeling system for assessing the severity of stormwater runoff and water quality using the PFEs from NOAA Atlas-14, and on this basis to create a decision support system (DSS) that allows appraisal of cost-effectiveness of future stormwater best management practices (BMPs), in particular detention basins and constructed wetlands. The SWMM and the DSS will be used to perform analysis of a

set of hypothetical implementations BMPs in consultation with Lower Neches Valley Authority (LNVA) and City of Beaumont. The analysis will yield a table of costs of BMP implementation, the reduction in risk of inundation, and improved water quality. The SWMM and DSS configurations and implementations will be shared with stakeholders, including TWDB, TCEQ, LNVA and City of Beaumont, along with the outcomes of the analysis. The data and modeling systems will be also made available to researchers and general public upon request.

Dr. Qin Qian will lead the project research to perform the following tasks:

1. Deploy STORM 3 water quality probe to collect hourly streamflow and water quality data

2. Consult stakeholders in Orange and Jefferson County on possible site settings for constructed wetlands and detention ponds, will include, but not be limited to Lower Neches Valley Authority (LNVA), Drainage Districts, City and County managers and officials.

3. Perform field surveys to assess sites for suitability of constructed wetlands or detention ponds.

4. Develop optimal configurations for constructed wetlands or detention ponds at sites determined to be suitable for development.

5. Present project outcomes to identified stakeholders in Task 2.

6. Prepare lectures for presentation through outreach programs fostered by the College of Engineering (COE) at Lamar University on project outcomes and broadcast conclusions of research to local communities.

FUNDING

Funded by Texas General Land Office, Coastal Management Program (subcontract from UTA), 10/1/2019-03/31/2021.