Ibendahl, Elise

Elise Ibendahl, PE, CFM, PMP, F.ASCE is the Jacobs Global Principal for Flood Modeling and Planning. With over 28 years of experience in water resources engineering and hydraulic modeling, she leads the development of effective strategies and solutions to mitigate the impact of floods on communities and infrastructure. She utilizes advanced modeling techniques, data analysis, and collaborations with multidisciplinary teams to create comprehensive flood studies and mitigation plans, particularly in urban environments and in combined sewer areas. Throughout her career she has performed the roles of project manager and/or subject matter expert for over 100 projects related to water resources and flood risk management and has supported projects in over 15 countries.

Titles from this speaker

An Adaptive Tale: Optimizing Resilient Development

Abstract

The Oxford-Cambridge Arc (OxCam), in the south of England (see Figure 1), is home to 3.7 million people and supports 2 million jobs. It has been identified as an important area of economic growth for the UK, with up to one million new homes expected over the next 30 years, alongside major infrastructure investment. However, there is great uncertainty in the effect of climate change and the shape and scale of development, creating a challenge in understanding how best to investment in flood resilience. The OxCam Flood Risk Investment Study sought to understand the 'optimum' level and timing of investment in the flood protection elements of flood resilience across three major catchments, but crucially doing so in a way that is mindful of future uncertainty and adaptive to different future scenarios. The OxCam Flood Risk Investment Study project used Flood Platform, Jacobs' data storage, management, simulation, optimization, and analysis platform, to automate the process of building 700 flood models, running 45,000 simulations, and completing a comprehensive impact analysis (Figure 2). Using an innovative 'simulation library' of outputs and novel code to interrogate it (Figure 3), 27 possible future scenarios were represented (Figure 4), spanning a range of possible climate change and development scenarios (Figure 5), along with billions of combinations of flood risk interventions (Figure 6). The project included developing a first-of-its-kind 'adaptive optimization', which explored a highly complex decision tree of billions of possible investment paths to identify investment decisions that are robust across futures and identify where and when to invest. The project served an important dual purpose, firstly providing evidence to support the Environment Agency's strategic engagement with stakeholders, and secondly as a pilot study to learn more about bringing the concepts of adaptive planning and economic optimization together at a regional scale. The project also produced a deep well of outputs and addressed the challenge of distilling them into meaningful key messages that provide evidence to support a strategic approach to flood resilience investment in the OxCam. The outputs are supporting the Environment Agency's engagement with a range of stakeholders — from national and local government to housing developers. For example, the project team found that without investment, the number of properties at risk could double between now and 2050 without new investment in flood resilience (Figure 7). This projected outcome is mainly due to flood zones expanding and encompassing existing housing. An average of between £140 and £206 million annual investment (with a benefit-cost ratio of around 5:1) may be needed to manage flood risk to existing properties and future development in the OxCam. The broad range shows how dependent investment is on future changes in risk, particularly how sensitive the area is to climate change. As part of delivering the work, significant advances have been made in the technology platform (Flood Platform), including automated model development, simulation parallelization, post-processing routines, and optimization integration which is already being used and further enhanced for the benefit of other projects. We have learned a great deal about the complexity of representing broad portfolios of interventions (including carbon) and a wide range of impacts in a large-scale analysis (Figure 8), in particular the challenge of bringing together optimization and adaptation by balancing investment needs across multiple futures. This learning is currently being applied by Jacobs to a project being delivered to the UK government (completion in 2025) which is developing long-term investment scenarios, at a national-scale, to provide the evidence base the Government is seeking to set investment levels (budgets) for flood and coastal erosion risk management. This presentation will outline the project background, technical approach and findings, and will explore the transferrable lessons learned about how adaptive planning and technology and data-driven optimization can be brought together to understand future risk and investment.

This paper explores transferrable lessons about how adaptive planning and technology and datadriven optimization enabled understanding of future risk and investment for the Oxford-Cambridge Arc in the UK. Automation supported over 700 flood models, 45,000 simulations, and comprehensive impact analysis. Without flood resilience investment the number of properties at risk could double between now and 2050, and investment would have a benefit-cost ratio of around 5:1.

SpeakerIbendahl, Elise

Presentation time

08:30:00

09:00:00

Session time

08:30:00

10:00:00

SessionResilient Development: Insights from Urban and Coastal Areas

Session number512

Session locationRoom 243

TopicAdvanced Level, Stormwater and Green Infrastructure, Sustainability and Climate Change

Author(s)

Ibendahl, Elise, Baldwin, Jennifer, Crowder, Richard, Clarke, Joseph

Author(s)E.M. Ibendahl1, J.D. Baldwin2, R. Crowder3, J. Clarke4

Author affiliation(s)1Jacobs, MO, 2Jacobs Solutions Inc., TN, 3Jacobs, West Yorkshire, 4Jacobs

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Oct 2024

DOI10.2175/193864718825159594

Volume / Issue

Content sourceWEFTEC

Word count7

Description: WEF_2026_collectionsystems_Proceedings

Closing the Loop: AI-Enabled Forecasting, Modeling, and Operations for Urban Flood Resilience

Abstract

Utilities and municipalities are under increasing pressure to make faster, better-informed decisions before, during, and after storm events. Yet in many organizations, rainfall forecasting, system operations, model analysis, and resilience planning still occur in separate workflows. This presentation describes a more connected approach: an AI-enabled operational framework that brings these functions together to support both immediate flood response and longer-term stormwater system improvement. The work centers on urban flooding and sewer system applications, where short lead times, rapidly changing rainfall patterns, and network complexity demand timely and reliable decision support. Digital ecosystems leveraging AI layers that integrate radar-based rainfall ingestion, short-horizon nowcasting, field observations, and physics-based hydrologic and hydraulic models can provide a continuously updated picture of expected system conditions. These tools can be used to translate gridded rainfall into model-ready inputs, accelerate scenario evaluation, and support operational decisions related to conveyance, storage, real-time control, and flood management. A key message of the presentation is that AI delivers the most value when paired with established engineering models and domain expertise. In this setting, machine learning is used to improve rainfall processing, forecast skill, uncertainty characterization, and computational efficiency, while hydraulic models preserve physical realism and operational credibility. The result is a practical workflow that helps teams move from raw data to actionable guidance on the timescales required for urban flood management. The same workflow also supports post-event learning. By comparing forecasts, observations, and modeled system performance, practitioners can identify where predictions were accurate, where system behavior differed from expectations, and how model parameters, operating strategies, or resilience priorities should be updated. This creates a repeatable feedback loop in which each storm improves the next forecast, the next operational response, and the next planning decision.

This paper was presented at the WEF Collection Systems and Stormwater Conference in Portland, OR, July 8-11, 2026.

Presentation time

11:30:00

12:00:00

Session time

10:30:00

12:00:00

SessionRobot Knows Best - AI Takes Over Your System (In a Good Way)

Session locationOregon Convention Center

TopicAI & Intelligent/Smart Systems

Author(s)

Wiesner-Friedman, Corinne, Ibendahl, Elise, Robinson, Paul, Nguyen, Tung, Stochl, Monica

Author(s)C. Wiesner-Friedman1, E. Ibendahl1, P. Robinson1, T. Nguyen1, m. stochl1

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Jul 2026

DOI10.2175/193864718825160271

Volume / Issue

Content sourceCollection Systems and Stormwater Conference

Word count13

Description: Collaborate, Restore, and More Rain: What Multi‑Event Field Data Says About...

Collaborate, Restore, and More Rain: What Multi‑Event Field Data Says About Modern Urban Flood Mitigation

Abstract

LEARNING OBJECTIVE This presentation will enable attendees to understand how a large, long‑term urban flood mitigation initiative-exemplified by the Brentwood Bound Project in Brentwood, Missouri-integrates floodplain restoration, green infrastructure, and multi‑functional public amenities to reduce flood risk in a densely developed corridor. Participants will learn how the project's long-term and comprehensive planning, stakeholder coordination, and collaboration with regional sewer and stormwater programs support improved hydraulic performance, increased public safety, and enhanced environmental and recreational outcomes. The session will highlight, using real post-event data, how nature‑based design strategies, infrastructure modifications, and watershed‑scale partnerships translate into measurable reductions in flood elevations and community impacts, as demonstrated through real‑world storm events that tested the system during and after construction. ABSTRACT BACKGROUND Flooding has long severely impacted the City of Brentwood, MO along Deer Creek between Hanley Road and South Brentwood Boulevard, with 26 floods since 1957. The repeated flooding in this landlocked, urban community of ~8,200 residents in the core of the metropolitan St. Louis region has caused significant public safety issues and property damage. The flood mitigation component of Brentwood Bound works alongside the St. Louis Metropolitan Sewer District's Project Clear efforts and includes improvements to Deer Creek that create more flow capacity and restore the natural floodplain along the creek to alleviate frequent widespread flooding in the area with no adverse impacts upstream or downstream of the project area. METHODOLOGY The Brentwood Bound Project is an integrated, comprehensive plan to renew the Manchester Road corridor via three main components: Deer Creek Flood Mitigation, Manchester Road Improvements, and Deer Creek Greenway Connector. The flood mitigation component of Brentwood Bound includes floodplain restoration and mitigation to reduce flood elevations, increase public safety, and provide environmental and recreational amenities. In addition to the flood mitigation improvements, the City of Brentwood is constructing the Deer Creek Greenway Connector (Figure 1), a new park pavilion with amphitheater, retention ponds (Figure 2) and a destination playground. The completed improvements have the potential to connect to more than 28 miles of greenways in the St. Louis region. The flood mitigation project and community amenities are now complete and has been subject to multiple major storm events that previously would have flooded the mitigation area. The historic St. Louis area floods of July/August 2022, with multiple large rain events (including one with over 8' of rain in 6 hours), tested out the project's effectiveness during construction and before all flood mitigation measures were complete. Another storm event, which would have required boat rescues in pre-project conditions, went largely unnoticed just before the flood mitigation project was completed and Brentwood Park opened in the summer of 2023. Figure 3 provides an overview of the hydrologic comparison of the project's effectiveness. This presentation provides a unique look at the full planning, construction, and post-project cycle of a major project that originated in 2011, was completed in 2023, and today is reaping new benefits from enough growth cycles that have allowed native vegetation to meaningfully establish. This presentation will also reflect on the resulting biodiversity and related community impacts observed after only two growing seasons. The Brentwood Bound Project has actively worked with stakeholders and the community over nearly 15 years of project planning, design, and development. The project interfaced with the St. Louis metropolitan area's combined sewer overflow reduction efforts in the Deer Creek watershed, and the project area included coordination with a storage tunnel dropshaft, required a sanitary trunk sewer relocation, and implemented green infrastructure measures in collaboration with the Metropolitan St. Louis Sewer District. The $81M project is funded through a combination of grant funding, partnerships, funding from certificates of participation, and a one-half of 1% economic development sales tax. CONCLUSION The project successfully addresses flooding issues in a regionally collaborative manner with a multi-functional, nature-based approach, shown in Figure 4, which includes: •Elimination of structures and impervious areas over an area of about 14 acres •Over 6,500 feet of creek improvements including floodplain benching and open space creation, retaining walls, storm sewers, and additional drainage elements such as bioretention, permeable pavers, and amended soils •Construction of three large detention basins, integrating water quality improvements and integration of an outdoor amphitheater •Plantings, including trees, shrubs, perennial groundcover, prairie seeding, and ornamental grasses •Replacement of the Breckenridge Industrial Court Bridge.

This paper was presented at WEFTEC 2026 in New Orleans, Louisiana.

Presentation time

08:30:00

08:45:00

Session time

8:30:00

10:00:00

SessionIntegrating Climate Change Resilience into Stormwater and Nutrient Management Strategies

Session locationErnest N. Morial Convention Center

TopicClimate Change Adaptation and Metrics, Resilience, Safety, and Disaster Planning, Stormwater and Green Infrastructure, Watershed Management, Water Quality, and Groundwater

Author(s)

Ibendahl, Elise

Author(s)E. Ibendahl1

Author affiliation(s)Jacobs, 1

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Sep 2026

DOI10.2175/193864718825160312

Volume / Issue

Content sourceWEFTEC

Word count16

Pixels and Puddles: Decoding, Depicting, and Dashboarding Urban Drainage

Abstract

BACKGROUND Cities are increasingly reacting to larger storm events with higher intensity, frequency, and rainfall volume that exceed sewer system design capacities. Flood protection systems that were designed years ago are overwhelmed, which additionally limit the performance of the sanitary, storm, and combined sewer systems. A Digital OneWater approach uses data that systems have been collecting to provide insights and foresight into how to operate their OneWater system. Using machine learning and artificial intelligence to predict a system's operation based on forecasted rainfall allows the operators to be prepared ahead of the storm to maximize capture and minimize flooding, both overland and in the collection system. Having insights into what operational controls will minimize this flooding/overflow while also showing areas on a live map that will flood/overflow for an upcoming storm is quite powerful. METHODOLOGY This presentation will highlight a case study in Wilmington, DE. Jacobs began operating the City of Wilmington, DE's wastewater treatment system in 2020, which includes its regional wastewater treatment plant (WWTP), 41 combined sewer overflows (CSOs), three wet weather storage facilities, and three major pump stations. In 2020, only 6 out of 41 CSOs had level and/or flow monitoring. To comply with CSO permit requirements to either monitor or inspect all CSOs to prevent dry weather overflows , a four-person crew personally inspects each CSO three days a week. A smart CSO system upgrade added level sensors at the 35 unmonitored CSOs as well as flow meters on two interceptors. The main objective is to have 'eyes on the system' for monitoring, reporting and faster incident response. The four-person crew can transition to proactive maintenance instead of reactive maintenance, reducing the risk of accidents on the road, mental stress, fuel costs, and wear & tear on vehicles. Another objective is to integrate the data stream with WWTP operations and provide predictive analytics that will integrate operations and better manage the system. Once the remote sensors were in place, the data were sent through secure methods to an online dashboard. The dashboard shows the locations and status of the monitors and sensors. Machine learning is performed on the data to provide maintenance alerts. The alerts are configured so that they are site-specific. Our machine learning determines a 'baseline' level in the sewer. Alerts are then provided for baseline threshold exceedance, pre-overflow threshold exceedance, or actual overflow occurrence. Figure 1 shows an overflow occurring alert. In this instance, we received an 'approaching overflow' alert at CSO-4C at just past 5 pm on Monday, August 26th, 2024, followed quickly by an overflow occurring alert. The crew lead was nearby and was dispatched to clear the blockage about an hour after the overflow occurring alert came in. Historically, the crew would have not checked the site until Wednesday morning. Additionally, the forecasted rainfall can be applied into the calibrated hydrologic & hydraulic (H&H) model to make operational decisions ahead of pending rain events. Rainfall forecast data provider is first integrated into the system, and then spatial analysis is performed based on the radar rainfall forecast. With the forecast data integrated into the platform spatially (Figure 2), the hydraulic model for the collection system can be combined with data-driven models to forecast the predicted flows from both the City of Wilmington and the surrounding areas from New Castle County to give a comprehensive flow forecast for the WWTP influents. In Wilmington, the skeletonized SWMM-based H&H model is on the platform and can be run ahead of the storm event to determine what control setpoints will provide the best capture of the wet weather flow (Figure 3). The solution is developed so that many control setpoint combinations can be run in a short amount of time. The setpoints can be reviewed over time as the forecast progresses. With this solution, the setpoints can be varied for a specific rain event. After the storm, the setpoints can then be compared with the baseline to determine how much more flow can be captured by changing the setpoints (Figure 4). CONCLUSION The case study illustrates how application of a digital data system can proactively identify maintenance issues, reduce CSOs. Existing tools, such as the hydraulic model, can be adapted to solutions that increase public safety in advance of urbanized flood events. These systems can be leveraged to integrate more refined urban flood model results from real time model runs, a library flood map catalog, or machine learning environment. Like the current system, various rainfall forecasts can be run in a short amount of time with locations vulnerable to surface flooding and potential inundation risk depicted in the dashboard. The use of near real-time forecast data in an urban data environment allows communities to develop defensible, integrated frameworks for infrastructure resilience and public safety in a changing environment. These frameworks would include operational procedures for utility leaders, public safety teams, and operations staff that issue hyper-local advance notifications of potential flood locations, visualize potential flood impacts for an oncoming storm event, enable proactive emergency response activities such as placement of traffic barriers, and advance planning of potential storm/flood recovery activities.

This paper was presented at the WEF/WEAT Collection Systems and Stormwater Conference, July 15-18, 2025.

Presentation time

14:30:00

15:00:00

Session time

13:30:00

15:00:00

SessionHarnessing the Cloud for Smarter Water Management

Session number06

Session locationGeorge R. Brown Convention Center, Houston, Texas, USA

TopicArtificial Intelligence, Real-Time Control, Wet Weather

Author(s)

Baldwin, Jennifer, Ibendahl, Elise, Verghis, Athena, Liu, Suibing

Author(s)J. Baldwin1, E. Ibendahl1, A. Verghis1, S. Liu1

Author affiliation(s)Jacobs Solutions, Inc., 1Jacobs, 1Jacobs, 1Jacobs, 1 ,

SourceProceedings of the Water Environment Federation

Document typeConference Paper

PublisherWater Environment Federation

Print publication date Jul 2025

DOI10.2175/193864718825159824

Volume / Issue

Content sourceCollection Systems and Stormwater Conference

Word count10

Present and Future Damage: Quantifying Urban Flood Impacts in Philadelphia

Abstract

Learning Objective: This presentation will include an overview of 1D/2D modeling conducted in key sewersheds across Philadelphia. Decision making required during both sewershed selection and the modeling process will be presented with a focus on optimizing model results and level of effort. Model results and accompanying analysis determining locations of sewer backups, basement flooding, and first floor elevation flooding will be presented in addition to considerations for application of similar programs in other locations. BACKGROUND Water service in Philadelphia began in 1801. The Philadelphia Water Department (PWD) is now tasked with mitigating the risk of its aging infrastructure through evaluation and recommendation of both structural and non-structural solutions. Aging or undersized infrastructure is an increasing concern across many municipalities - and will only accelerate in the future. Targeted flood modeling across their service area is a key pillar of PWD's asset evaluation, risk assessment, and long-term capital planning. 1D/2D modeling has been utilized on an individual sewershed scale to determine urban pluvial flood risk within the city. To date, 6,100 acres across approximately 40,400 acres making up the city's service area have been modeled, with the ultimate goal to model all sewersheds. Sewersheds are prioritized and selected by PWD based on known flooding issues, known upcoming development, or customer complaint logs. OBJECTIVES The ultimate objective of this ongoing project is to determine areas across the city prone to flooding, sewer backups, or basement/first floor elevation flooding. As in all modeling, data quality directly impacts quality of model results. What implications should be considered if input data is outdated or modeling is being conducted in an area of rapid redevelopment and infrastructure changes? What is the best way to leverage existing models (such as existing 1D planning level models) to accelerate creation of flood models? METHODOLOGY Jacobs began supporting PWD with their linear asset management planning program in 2022, though it has evolved over the last several years. Progress includes: - a comparison of a 1D/2D PCSWMM 1D/2D and a 2D only HEC-RAS approach - addition of a basement flood analysis methodology - refinement of model expansion techniques from planning level models to more representative 1D networks - incorporation of climate perturbed rainfall data for 2100 Once a sewershed is selected, an integrated 1D/2D PCSWMM model is built with an approach designed to optimize a variety of considerations including overall level of effort, accuracy, and model run time. PWD's existing 1D network models are utilized with incorporation of 2D terrain, inlet connections, varied rainfall, and expansion of pipe network, and building footprints. Validation of the model is conducted using a historical event time series, documented backflow preventor installations, and problem areas which received flood calls from the public were utilized to confirm areas of flooding. RESULTS AND CONCLUSIONS Final outcomes of this work are flood depths across the modeled area, identified locations of sewer backups and locations of basement and first floor elevations. The following results will be summarized and presented: - Model setup and validation (Figure 1) - Flood model results - Analysis of sewer backups, basement flooding, and first floor elevation flooding (Figures 2 and 3) Once flood modeling is completed, the use and application of model results is just as important as the model build itself. For PWD, these flood model results are utilized to help enforce private development stormwater standards called the Public Health and Safety Release Rate, which dictates that a maximum release rate based on sewer capacity must be used in design in certain watersheds where known flooding occurs.

This paper was presented at the WEF/WEAT Collection Systems and Stormwater Conference, July 15-18, 2025.

Presentation time

16:15:00

16:45:00

Session time

13:30:00

16:45:00

SessionStormwater and Coastal Resilience Modeling

Session number05

Session locationGeorge R. Brown Convention Center, Houston, Texas, USA

TopicClimate Change Adaptation, Flooding, Wet Weather

Author(s)