A5082106264- Flood Risk Assessment and Management
- Urban Stormwater Management Solutions
- Hydrology and Watershed Management Studies
- Water resources management and optimization
- Water Systems and Optimization
- Soil and Water Nutrient Dynamics
- Water Quality and Pollution Assessment
- Atmospheric and Environmental Gas Dynamics
- Hydrological Forecasting Using AI
- Coal Properties and Utilization
- Climate variability and models
- CO2 Sequestration and Geologic Interactions
- Interdisciplinary Research and Collaboration
- Water Quality and Resources Studies
- Opportunistic and Delay-Tolerant Networks
- Underwater Vehicles and Communication Systems
- Hydrocarbon exploration and reservoir analysis
- Education, Healthcare and Sociology Research
- Hydrology and Drought Analysis
- Water-Energy-Food Nexus Studies
- Groundwater and Isotope Geochemistry
- Sustainability and Climate Change Governance
- Water Quality Monitoring Technologies
- Evacuation and Crowd Dynamics
- Meteorological Phenomena and Simulations
University of Virginia
2017-2024
Engineering Systems (United States)
2019-2023
McCormick (United States)
2017-2019
West Virginia University
2012
Many coastal cities are facing frequent flooding from storm events that made worse by sea level rise and climate change. The groundwater table in these low relief is an important, but often overlooked, factor the recurrent locations face. Infiltration of stormwater water intrusion due to tidal forcing can cause already shallow tables quickly toward land surface. This decreases available storage which increases runoff, system loads, flooding. Groundwater forecasts, could help inform modeling...
Abstract Flooding in coastal cities is increasing due to climate change and sea-level rise, stressing the traditional stormwater systems these communities rely on. Automated real-time control (RTC) of can improve performance, creating policies for smart an active area study. This research explores reinforcement learning (RL) create mitigate flood risk. RL trained using a model hypothetical urban catchments with tidal boundary two retention ponds controllable valves. RL's performance compared...
Flooding in many areas is becoming more prevalent due to factors such as urbanization and climate change, requiring modernization of stormwater infrastructure. Retrofitting standard passive systems with controllable valves/pumps promising, but requires real-time control (RTC). One method automating RTC reinforcement learning (RL), a general technique for sequential optimization uncertain environments. The notion that an RL algorithm can use inputs flood data rainfall forecasts learn policy...
Reinforcement learning agents can learn real-time stormwater system control strategies that balance the competing goals of flood mitigation and sediment capture in urban watersheds.
Coastal cities face recurrent flooding from storm events and rising seas. A contributing factor to in these low relief areas is the groundwater table, which, already relatively shallow, can quickly rise towards land surface during events. This leads increased runoff entering stormwater drainage systems a greater probability of flooding. As such, table forecasts could be an important component real-time flood forecasting systems, but are generally unavailable. Because traditional...
Abstract Climate change poses water resource challenges for many already stressed watersheds throughout the world. One such watershed is Upper Neuse Watershed in North Carolina, which serves as a source large and growing Research Triangle Park region. The aim of this study was to quantify possible changes watershed’s balance due climate change. To do this, we used Soil Water Assessment Tool (SWAT) model forced with different scenarios baseline, mid‐century, end‐century time periods using...
Abstract Improved understanding of the potential regional impacts projected climatic changes on nitrogen yield is needed to inform water resources management throughout United States ( U.S. ). The objective this research look broadly at watersheds in contiguous assess impact precipitation P ) and air temperature T yield. SPAtially Referenced Regression On Watershed attributes model downscaled outputs from 14 general circulation models were used explore Results analysis suggest that will...
Abstract The complexity of water quality trading (WQT) policy can lead to the promulgation regulations that are challenging comply with and enforce. As a result, transaction costs may be high administrators have limited ability monitor program outcomes. These concerns alleviated in part through increased automation compliance procedures. We present case study pilot system designed for Virginia Department Transportation automates streamlines brokering processes nonpoint source WQT program....
Abstract Uncertainty in water quality trading (WQT) markets is frequently cited as a deterrent for participation, with few studies focusing on uncertainty future credit needs. To reduce this uncertainty, we present geographic information system (GIS)‐based methodology estimating an upper bound of needs set spatially referenced planned construction projects over large region. We demonstrate the by applying it to estimate Virginia Department Transportation's (VDOT) 6‐year improvement program....
Climate change and development have increased urban flooding, requiring modernization of stormwater infrastructure. Retrofitting standard passive systems with controllable valves/pumps is promising, but requires real-time control (RTC). One method automating RTC reinforcement learning (RL), a general technique for sequential optimization in uncertain environments. The notion that an RL algorithm can use inputs flood data rainfall forecasts to learn policy controlling the infrastructure...
Compared with capital improvement projects, real-time control of stormwater systems may be a more effective and efficient approach to address the increasing risk flooding in urban areas. One way automate design process policies is through reinforcement learning (RL). Recently, RL methods have been applied small demonstrated better performance over passive simple rule-based strategies. However, it remains unclear how are for larger complex systems. Current RL-based also suffer from poor...
Recent accessibility of affordable sensing technologies, microcontrollers, and wireless communication technology has made it possible for stormwater systems to be retrofitted with an assortment sensors actuators. These smart have enabled the real-time their surrounding environmental dynamics, subsequently, provide basis autonomous adaptive operational control strategies. Additionally, these allow inexpensive minimally-invasive interventions (e.g. hydraulic valve operated by...
<p>Nuisance flooding, which is repetitive flooding caused by both tidal and rainfall-driven events, increasing in frequency severity for many coastal communities. As climate change causes sea level rise more frequent intense storm these nuisance events are producing significant disruptions impacts to The objective of this study improve modeling decision support activities around and, particular, its impact on transportation infrastructure. Our region partner the research City...
Low-lying coastal cities across the world are increasingly seeing flooding due to climate change and accompanying sea-level rise. Many such rely on old passive stormwater infrastructure which cannot cope up with increasing flood risk. One potential solution for addressing is implementing active control strategies in systems. Existing mostly relies rule-based strategies, not sufficient manage Model predictive (MPC) management has received attention this problem. However, building...