Yu Zhang

University of Texas at Arlington | Associate Professor

Subject Areas: Hydrometeorology, hydrology, water resource management, risk assessment; stochastic modeling

 Recent Activity

ABSTRACT:

In recent years, severe storms and catastrophic flooding along the Gulf Coast has causes water quality issues in bays and estuaries and contributes to hypoxia in the Gulf of Mexico through increased nutrient and sediment loads and suppression of oxygen exchange. These events have shown that stormwater and wastewater infrastructures for many coastal and near-coastal communities are inadequately prepared for the frequency and magnitude of these storms. Infrastructure upgrades are costly to implement and maintain and many smaller urban and rural coastal communities do not have the resources to complete infrastructure upgrades that will enhance their area’s storm resiliency. Texas has been working to implement the Coastal Nonpoint Source (CNPS) Program which includes promoting and facilitating implementation of stormwater best management practices (BMPs) in small urban and urbanizing coastal areas.

This project will use Texas GLO Coastal Management Program (CMP) Cycle 24 funds, in a joint effort between University of Texas at Arlington (UTA) and Lamar University (LU) to produce a decision framework. It provide opportunities for coastal communities to assess their exposure to flooding risk using up-to-date precipitation frequency estimates and determine the most cost-effective measures to implement to address stormwater runoff and downstream water quality issues arising from flood events. The resultant decision support system (DSS) will allow communities to appraise the cost-effectiveness of stormwater best management practices (BMPs), constructed wetlands and detention basins, in mitigating the impacts of flooding on flooding and water quality in the lower Neches River, which is highly vulnerable to flooding. The SWMM-based DSS will be applied to the analysis a set of hypothetical BMP implementations in consultation with the Lower Neches Valley Authority (LNVA) and Jefferson and Orange County Drainage Districts. The analysis will yield a table of the cost of BMP implementation, estimate flood risk reductions and potential improvements to water quality.

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ABSTRACT:

This resource includes in-situ, radar, satellite observations of wind, rainfall along the North Carolina coast, and in particular the areas surrounding Albemarle Sound and Pamlico Sound, which encompasses the downstream estuaries of Chowan River, Pamlico River, and Neuse River, during the hurricanes Florence and Michael. To better analyze extreme events such as hurricanes, scientists acquire hydro-meteorological observations from multiple sources including non-regular sources such as beyond the government-operated weather and hydrological stations data. This project provides observational data for two hurricanes from various resources and stores for further use. Thus, could potentially help scientists to improve weather forecast models for better heavy rainfall forecasts after hurricane landfalls. Improvement of weather forecast models for hurricane landfalls will benefit hurricane preparation especially for the states along the coastlines, leading to reduced damages.

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 Contact

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Resources
All 2
Collection 0
Resource 2
App Connector 0
Resource Resource
Hurricane Florence Inundation/Near Surface Data
Created: Oct. 12, 2019, 4:49 p.m.
Authors: Yu Zhang · Ghazvinian, Mohammadvaghef

ABSTRACT:

This resource includes in-situ, radar, satellite observations of wind, rainfall along the North Carolina coast, and in particular the areas surrounding Albemarle Sound and Pamlico Sound, which encompasses the downstream estuaries of Chowan River, Pamlico River, and Neuse River, during the hurricanes Florence and Michael. To better analyze extreme events such as hurricanes, scientists acquire hydro-meteorological observations from multiple sources including non-regular sources such as beyond the government-operated weather and hydrological stations data. This project provides observational data for two hurricanes from various resources and stores for further use. Thus, could potentially help scientists to improve weather forecast models for better heavy rainfall forecasts after hurricane landfalls. Improvement of weather forecast models for hurricane landfalls will benefit hurricane preparation especially for the states along the coastlines, leading to reduced damages.

Show More
Resource Resource
Assessment of Stormwater Infrastructure for Mitigating Flooding and Non-point Source Pollution
Created: Nov. 30, 2021, 10:45 p.m.
Authors: Zhang, Yu · Farzaneh, Helia · Nabin Basnet · Qin Qian

ABSTRACT:

In recent years, severe storms and catastrophic flooding along the Gulf Coast has causes water quality issues in bays and estuaries and contributes to hypoxia in the Gulf of Mexico through increased nutrient and sediment loads and suppression of oxygen exchange. These events have shown that stormwater and wastewater infrastructures for many coastal and near-coastal communities are inadequately prepared for the frequency and magnitude of these storms. Infrastructure upgrades are costly to implement and maintain and many smaller urban and rural coastal communities do not have the resources to complete infrastructure upgrades that will enhance their area’s storm resiliency. Texas has been working to implement the Coastal Nonpoint Source (CNPS) Program which includes promoting and facilitating implementation of stormwater best management practices (BMPs) in small urban and urbanizing coastal areas.

This project will use Texas GLO Coastal Management Program (CMP) Cycle 24 funds, in a joint effort between University of Texas at Arlington (UTA) and Lamar University (LU) to produce a decision framework. It provide opportunities for coastal communities to assess their exposure to flooding risk using up-to-date precipitation frequency estimates and determine the most cost-effective measures to implement to address stormwater runoff and downstream water quality issues arising from flood events. The resultant decision support system (DSS) will allow communities to appraise the cost-effectiveness of stormwater best management practices (BMPs), constructed wetlands and detention basins, in mitigating the impacts of flooding on flooding and water quality in the lower Neches River, which is highly vulnerable to flooding. The SWMM-based DSS will be applied to the analysis a set of hypothetical BMP implementations in consultation with the Lower Neches Valley Authority (LNVA) and Jefferson and Orange County Drainage Districts. The analysis will yield a table of the cost of BMP implementation, estimate flood risk reductions and potential improvements to water quality.

Show More