Member $25.00 | Non-Member $125.00
View Important Policies and System Requirements for this course
INSTRUCTORS:
Jay Stone, P.E., BCEE, CFM, CPESC, LEED AP, CWPPP, ESCPC, CESCPP, CPSWQ
Stacie DeSousa
Aditi Bhaskar
Rocky Talchabhadel
S.M.Masud Rana
Course Length: 1 hour
Purpose and Background
This course will only award PDHs for completion.
Technical presentations from the 2024 World Environmental & Water Resources Congress:
New Gray & Green Infrastructure Details & Specifications for Honolulu (10 minutes)
This presentation provides an in-depth exploration of the latest gray and green infrastructure specifications tailored for Honolulu's unique urban environment. It covers innovative stormwater management solutions, addressing challenges like high-intensity storms, sea-level rise, and diverse climate zones across O'ahu. The content highlights the extensive process of updating outdated standards, integrating modern materials, and construction techniques to enhance resilience against coastal conditions. Additionally, the presentation offers detailed plans and specifications, including the development of new green infrastructure designs and the adaptation of traditional infrastructure to contemporary needs.
Denver’s Pluvial Predicament: A Spatiotemporal Analysis of Publicly Reported Street Flooding (11 minutes)
This presentation delves into a spatiotemporal analysis of street flooding incidents in Denver, focusing on publicly reported data from 2000 to 2019. It examines the distinction between fluvial and pluvial flooding, emphasizing the latter's underreported nature due to its occurrence outside traditional floodplains. The analysis employs logistic regression to assess the probability of flood reports based on factors such as rainfall intensity, population density, and urban infrastructure characteristics like stormwater pipe length. The findings underscore the importance of integrating both temporal and spatial variables in flood risk assessment, offering valuable insights into urban flood management strategies.
Harmful Algal Blooms in Bay-Estuary Systems Under Future Climate: The Case of Apalachicola Bay, Florida (16 minutes)
This presentation examines the potential impacts of climate change on harmful algal blooms (HABs) in the Apalachicola Bay, Florida, utilizing a combination of statistical and machine learning models. The analysis focuses on key environmental parameters such as air and water temperatures, pH, dissolved oxygen, and salinity, integrating them with climate projections to predict future chlorophyll A levels. The study highlights the challenges of limited data availability and the complexities in modeling HABs due to their intricate relationships with environmental factors. The findings suggest that under high emission scenarios, there is a significant likelihood of increased frequency and intensity of HABs, particularly during summer months.
Providing Undergraduate Students with Training on Evaluating Climate Change Projections within the Framework of Open-Source Software Infrastructure (12 minutes)
This presentation details a framework for training undergraduate students to evaluate climate change projections using open-source software, specifically through applications built on Google Earth Engine. It involves teaching students to access and analyze vast datasets, such as precipitation and temperature indices, by developing practical skills in coding and data visualization. The training emphasizes understanding the variability and uncertainty in climate models, with practical exercises like mapping and temporal plotting of climate indices. The approach integrates tools like Python and Google Colab, allowing students to independently explore climate data and develop research skills applicable to various hydrological models and environmental studies.
A Greedy Search Algorithm for Closed Valve Analysis in Drinking Water Networks for Real-Time Model Development (16 minutes)
This presentation explores the application of a greedy search algorithm for identifying closed valves in drinking water networks to enhance real-time model development. The algorithm leverages pressure and flow data from SCADA systems to detect potential closed valves that affect the hydraulic performance of the network. By iteratively adjusting nodal demands, pump curves, and conducting network skeletonization, the approach seeks to minimize errors between simulated and actual flow conditions. The methodology is computationally intensive but effective in pinpointing critical closed valve locations, which can lead to improved water quality, energy optimization, and reduced carbon footprints in water distribution systems.
Learning outcomes and session benefits
Upon completion of this course, you will be able to:
- Describe the role of both traditional and innovative infrastructure components in improving stormwater management and overall urban resilience as referenced in the New Gray & Green presentation.
- Discuss the differences between pluvial and fluvial flooding and the implications for urban flood management in Denver.
- List the challenges and complexities in modeling harmful algal blooms, particularly under different climate scenarios.
- Describe the use of open-source software tools, such as Google Earth Engine, for analyzing climate change projections and data visualization.
- Identify the steps involved in using a greedy search algorithm to detect closed valves in drinking water networks.
Assessment of Learning Outcomes
Learning outcomes are assessed and achieved through passing a 10 multiple choice question post-test with at least a 70%.
Who Should Attend?
- Water resource engineers
- Consulting engineers
- Utility Engineers
- Public Agency Engineers
- Utility Directors
How to Earn your PDHs and Receive Your Certificate of Completion
This course is worth 1 PDH. To receive your certificate of completion, you will need to complete a short on-line post-test and receive a passing score of 70% or higher within 365 days of the course.