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“Smart” Stormwater Management

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“Smart” Stormwater Management “Smart” Stormwater Management Structural Practices: The Futuristic Solutions Debabrata Sahoo, PhD, PE, PH Senior Engineer, Woolpert Inc, Columbia, SC North Carolina-American Public Works Association, October 21, 2019 Introduction Current Practices History Future Technologies Case Studies Agenda • Introduction • 5 Ws of SMART Stormwater Management • Current Practices in Stormwater/Flood Control and Mitigation • Issues with water quantity and quality • Stormwater/Flooding: Quality and Quantity • Issues with Stormwater/Flooding • Historical Flooding in South Carolina/North Carolina • Economic Impacts • Technologies to Integrate water, data, sensing and control • Internet of Waters, IoT, Sensors, Wireless Platforms, Machine to Machine Communication, Artificial Intelligence, Machine Learning, Deep Learning, Real-Time Systems, Cloud Computing, Big Data and Analytics • Application of Future Technologies in Stormwater/Flood Mitigation • Smart Stormwater Systems • Flash Flood Forecasting • Storm Sewer Controls • Big Data Analytics • Challenges and Opportunities Introduction Current Practices History Future Technologies Case Studies Current Practices in Stormwater Control and Mitigation • Use of design storms • Design to lower peak flows • Design to empty within 72 Hours • Store runoff for a minimum of 24 hours to get the water quality benefits Introduction Current Practices History Future Technologies Case Studies Current Practices in Stormwater Control and Mitigation Introduction Current Practices History Future Technologies Case Studies Stormwater/Flooding: Quality and Quantity Introduction Current Practices History Future Technologies Case Studies Stormwater/Flooding: Quality and Quantity Introduction Current Practices History Future Technologies Case Studies Stormwater/Flooding: Quality and Quantity Introduction Current Practices History Future Technologies Case Studies Stormwater/Flooding: Quality and Quantity Introduction Current Practices History Future Technologies Case Studies Technologies to Integrate Water, Data, Sensing and control Introduction Current Practices History Future Technologies Case Studies Technologies to Integrate Water, Data, Sensing and control Hurricane Joaquin Columbia, SC Introduction Current Practices History Future Technologies Case Studies Technologies to Integrate Water, Data, Sensing and control Hydrograph 70 60 50 /S Hydrograph 1 3 40 Hydrograph 2 30 Hydrograph 3 Flow, Flow, Ft 20 Hydrograph 4 10 Hydrograph 5 1 0 0 5 10 15 Time, Hours 3 2 Hydrograph 200 180 160 4 140 /S 3 120 5 100 Hydrograph 80 Hpothetical Flooding Flow, Flow, Ft 60 With Smart Systems 40 20 0 0 5 10 15 Time, Hours Hydrograph 200 180 160 140 /S 3 120 100 80 Hydrograph Flow, Ft Flow, 60 40 20 0 0 2 4 6 8 10 12 Time, Hours Columbia, SC Introduction Current Practices History Future Technologies Case Studies Technologies to Integrate Water, Data, Sensing and control Intelligently manage stormwater and flooding using the futuristic technologies Introduction Current Practices History Future Technologies Case Studies Technologies to Integrate Water, Data, Sensing and control • Internet of Things (IoTs): – The interconnection of devices via internet. • Machine to Machine Communication (M2M): – Direct communication between devices using any wired or wireless technologies. • Wireless Platforms: – 1G, 2G, 3G, 4G, 5G the backbone of communication technology. Introduction Current Practices History Future Technologies Case Studies Technologies to Integrate Water, Data, Sensing and control • Cloud Computing: – The practice of using a network of remote servers hosted on the internet to store, manage, and process data • Big Data: – Extremely large datasets – Analyzed computationally to reveal trends, patterns etc. – Relationships to make decisions. • Data Analytics: – It is the science of drawing insights from raw information sources. Introduction Current Practices History Future Technologies Case Studies Technologies to Integrate Water, Data, Sensing and control • Near Real-time Systems: – System that delivers data closer to as and when collected. • Artificial Intelligence: – Intelligence demonstrated by machines. – Mimicking human intelligence and decision making process. • Machine Learning: – Systems that can learn from data/information. – Recalibrate the learning process on their own. • Deep Learning: – Gathers information from a dataset. – Dives deep to understand the pattern. Introduction Current Practices History Future Technologies Case Studies Technologies to Integrate Water, Data, Sensing and control • Internet of Water (IoW): Implementing a network of easily accessible water relevant data. Introduction Current Practices History Future Technologies Case Studies Application of Technologies in Stormwater/Flood Mitigation/Water Quality Improvements • Smart Stormwater Systems • Flood Forecasting and Remediation • Storm Sewer Controls • Big Data Analytics Introduction Current Practices History Future Technologies Case Studies Application of Technologies in Stormwater/Flood Mitigation/Water Quality Improvements Cloud Platform • Rain gauge • Telemetry • Actuated Valves • Dashboard • Level Sensor • CMAC • Water Reuse • Soil Moisture Sensor • Automated Samplers • Precipitation Forecast Introduction Current Practices History Future Technologies Case Studies Application of Technologies in Stormwater/Flood Mitigation/Water Quality Improvements: Increase flood control capacity of a wet pond at Curtiss Field Park, MN • Runoff from a 38-acre watershed. • Large storms results in pond overflows, standing water etc. • The watershed district wanted to eliminate flooding • Installed a 10-foot diameter perforated pipe. • An 8 inch butterfly valve was installed • Increased the storage volume by 58%. Introduction Current Practices History Future Technologies Case Studies Application of Technologies in Stormwater/Flood Mitigation/Water Quality Improvements: The Great Lakes Region CSO issues • City of Ann Arbor faces several CSO issues every year. • Retrofit with a valve controlled remotely • Held back several million gallons of water • Saved the city a few million dollars. • The system used weather forecast information to increase the storage time resulting in better water quality. • The researchers are testing a series of control structures • Retrofit with real-time control system • Ingests weather forecast • Operate in an optimized fashion Introduction Current Practices History Future Technologies Case Studies Application of Technologies in Stormwater/Flood Mitigation/Water Quality Improvements: Gardner Avenue Detention Facility, Kansas City, CSO Issues • About 6.5 billion gallons of overflows each year. • Issued $1 Billion Smart Infrastructure challenge • $1 Billion in savings over the next 10 years. • Installed SMART systems • At an existing 1.1 million-gallon dry detention pond • Reduced flows directly to the city’s combined system. • prevented 98% of the flows in a 9 month study period. Introduction Current Practices History Future Technologies Case Studies Application of Technologies in Stormwater/Flood Mitigation/Water Quality Improvements: Anacostia River Watershed Water Quality Study • Water Quality Issues in the Chesapeake • Requires a reduction in phosphorous and nitrogen. • Several ponds are retrofit – treat it and reduce nutrient and TSS loadings – CMAC • Such systems help in – Estimate accurate load reductions – Obtain credits to comply with the TMDLs. Challenges and Opportunities • Designs and regulations • Funding opportunities • Training and education • Computing and Networking Acknowledgements • http://open-storm.org/ • Dr. Branko Kerkez, Professor, Civil and Environmental Engineering, University of Michigan, Ann Arbor • Hydroinformatics Research Group, University of Virginia • https://optirtc.com/ • Hal Clarkson, Project Director, Woolpert Inc • Trevor Gauron, Project Manager, Woolpert Inc Questions.
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