Session 7 | Wednesday, November 10 | 10:30 AM - 12:00 PM EST

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ATTN OFFICIAL JUDGES FOR THE STUDENT PRESENTATION COMPETITION: If you were contacted by the Conference Planning Committee Student Activities Chair, Allison Lewis, remember to use the appropriate evaluation form when scoring student participants. The link and QR code to this form was emailed to you along with your student assignments. To make identifying student participants easier, the green graduation cap  next to a session title includes a student who is participating in the PRESENTATION Competition.

Supply Source and Natural System Sustainability Assessment and Climate Change Adaptation for Water Supply Utilities

Moderator: Jeffrey Geurink

Presenters:

• Jeff Geurink, Tampa Bay Water, "Examining the Impact of Land Use Change on Water Resources Using the Integrated Hydrologic Model"
Land use transitions from grass, forest, and irrigated agriculture to urban have occurred for several decades and are projected to continue in the Tampa Bay, Florida area. One study indicated impervious area within the Tampa Bay watershed increased from 9% to 27% from 1991 to 2002 and was projected to increase to 38% by 2025. Besides land use transitions, many other stresses influence streamflow, springflow, and levels in lakes, wetlands, and the aquifers. Historical variability in rainfall and potential evapotranspiration (ET) and changes in well pumping, land use, and climate contribute to total changes observed and projected for flows and levels. Over the past several decades, sustainability concerns for natural systems in the Tampa Bay area have prompted regulators to impose minimum flows and levels for water bodies. To evaluate sustainability, a major water utility in the region, Tampa Bay Water, had previously investigated the impact of rainfall variability, well pumping, and projected climate change on water resources and was motivated to also examine the impact of land use change on water resources. The Integrated Hydrologic Model (IHM) is a fully-integrated hydrologic model that simulates all surface-water and groundwater processes and their dynamic interactions. It has been demonstrated that a calibrated IHM application for the Tampa Bay region can quantitively partition total change in flows and levels into separate climatic and anthropogenic stresses in a region covered by 25% water and wetlands with more than 50% of the area having near-surface water table. For two river watersheds within the Tampa Bay watershed (study region), landuse change from 1995 to 2010 was dominated by transitions from grass and forested land to the urban sector, which includes transitions to pervious and impervious surface and to water bodies for stormwater management. With respect to the two watershed areas of the study region, grass and forested lands decreased by 25% and 10%, having transitioned to the urban sector with about half of the transitioned area being impervious. Simulated long-term average responses include increased streamflow (12% and 3%) and decreased total ET, groundwater ET, recharge (20% and 8%), and groundwater level.


• Chin Man Mok, GSI Environmental Inc., "Improving Simulated Hydrologic Responses by Bayesian Integration of Radar and Gauged Rainfall Datal"
To support water management decision making, a calibrated application of the Integrated Hydrologic Model (IHM) was developed to simulate the hydrologic responses to rainfall and water supply operations in the Integrated Northern Tampa Bay (INTB) region. Spatial and temporal distributions of rainfall significantly impact surface water processes and the dynamic exchange between groundwater and surface water. More than 10 years ago, the model was initially calibrated using rainfall input derived from historical rain gauge data with Thiessen polygon spatial distribution method. Since rainfall is highly dynamic and spatially varied, rain gauges in some areas are spaced too far apart and do not adequately capture the spatial and temporal distribution of rainfall. They sometimes miss small-scale rainstorms entirely or over-estimate the spatial extent of the measured rainfall event, resulting in apparent “phantom storms” for some streamflow hydrographs simulated by the model. Since 1995, rainfall estimated from Next Generation Radar (NEXRAD) reflectivity data has been available in 15-minute, 2x2-kilometer resolutions. It was found that the estimation of rainfall from radar data is inherently uncertain and biased, tending to be over-estimated at lower rainfall level and under-estimated at higher rainfall level. This paper describes a Bayesian statistical approach to integrate rain gauge and NEXRAD rainfall data to produce a high-resolution representation of rainfall in the INTB region. In this Bayesian framework, the gauged data was used to develop the prior distribution and the radar rainfall uncertainty was used to derive the likelihood function. The resulting Bayesian rainfall accentuates the strengths of rain gauge and radar rainfall data while de-emphasizing their weaknesses. It agrees with the gauged data and is corrected for the radar rainfall biases. The uncertainty associated with the Bayesian rainfall is smaller than the uncertainty associated with gauged data interpolation and the inherent radar rainfall uncertainty. The Bayesian rainfall estimation has generally improved the INTB simulation accuracy. Monte Carlo realizations of future rainfall were also derived using the Bayesian rainfall. These realizations are expected to produce more reliable estimations of future surface water availability and hydrologic responses which can improve future water resources management.


• Warren Hogg, Tampa Bay Water, "Environmental Recovery in the Northern Tampa Bay Areal"
Palustrine wetlands currently make up over 25 percent of the land surface in the Northern Tampa Bay area. Ground water extraction from public supply wellfields began in this area in 1930 and increased as the local population grew. The rate of ground water extraction from 11 wellfields reached 167 million gallons per day on an annual average basis in early 2001. This high rate of sustained extraction was a contributing factor to low or absent water levels in area wetlands and the transition from wetland toward upland plant species. Elected and regulatory officials in the Tampa Bay area made historic decisions in 1998, recognizing the importance of wetlands and reducing the extraction of ground water from these 11 wellfields to no more than 90 million gallons per day. The agreements allowed us to develop alternative water supply sources, reduce ground water extraction, and meet the growing demand for water in our area. Ground water extraction from these wellfields has been reduced by half, averaging approximately 80 million gallons per day for the past 10 years. Tampa Bay Water recently completed an assessment of environmental recovery at 1,360 wetlands and lakes in this area. A comprehensive assessment of environmental recovery due to the reduced rate of ground water extraction was necessary to renew the operating permit for these wellfields. Numeric metrics of environmental health or recovery were established for wetland types covered by this study and multiple weight-of-evidence analyses were developed. A quantitative assessment of recovery was completed for all sites with long-term water level data and 85% of the lakes and wetlands fully meet their numeric metric of recovery. The remaining sites show substantial water level improvement and most of these sites missed being classified as recovered by less than one foot on a long-term basis. Full hydrologic recovery at many of these remaining wetlands is precluded by new residential development adjacent to the wellfields. Tampa Bay Water has applied to renew the operating permit for these 10 wellfields at the same extraction rate and this assessment of environmental recovery is a critical component of this permit renewal.


• Wendy Graham, Seungwoo Chang, University of Florida; Jeffrey Geurink and Nisai Wanakule, Tampa Bay Water, "Evaluation of impacts of climate change and water use scenarios on hydrology in the Tampa Bay Region"
General circulation models (GCMs) have been widely used to simulate current and future climate at the global scale. However, the development of frameworks to apply GCMs to assess potential climate change impacts on regional hydrologic systems, ability to meet future water demand, and compliance with water resource regulations is more recent. In this study eight GCMs were bias-corrected and downscaled using the bias correction and stochastic analog (BCSA) downscaling method and then used with eight water use scenarios to drive Tampa Bay Water’s Integrated Northern Tampa Bay Model (INTB). Five of eight GCMs projected a decrease in streamflow and groundwater availability in the future regardless of water use scenario. For the business as usual water use scenario all eight GCMs indicated that, even with active water conservation programs, increases in public water demand projected for 2045 could not be met from ground and surface water supplies while achieving current groundwater level and surface water flow regulations. With adoption of 40% wastewater reuse for public supply and active conservation four of the eight GCMs indicate that 2045 public water demand could be met while achieving current environmental regulations; however, drier climates would require a switch from groundwater to surface water use. These results indicate there may be a reduction in future freshwater supply in the Tampa Bay region if environmental regulations intended to protect current aquatic ecosystems do not adapt to the changing climate.

Urban Flooding Open Knowledge Network Part II: Delivering Flood Information to Anyone, Anytime, Anywhere

Moderator: Janet Clements

Presenters:

• Sean McWillie, University of Maine, "What’s Still Working? An Ontology Design Pattern for Modeling Cascading Infrastructure Outages"
At the heart of the ongoing effort to construct a scalable open knowledge network that integrates information about the urban infrastructure with flood forecasts - the Urban Flooding Open Knowledge Network (UF-OKN) - lays a knowledge graphs that pulls in and semantically connects relevant information. So far, this graph has integrated a multitude of spatial information in order to answer questions about what areas of a city and what infrastructure are likely impacted during a flooding event. But in order to provide a more holistic view of flood-related impacts, we also need to provide timely information about secondary, cascading impacts, such as flood damage to a substation causing widespread power outages, including loss of power to, for example, critical water supply and sewer treatment facilities or to traffic control infrastructure. To identify, query and visualize cascading impacts, the connectivity between different kinds of infrastructure needs to be explicitly modeled in the knowledge network. Towards this goal, we present a novel semantic pattern called the “Utility Connection Pattern”. It uses a general class of features-at-risk that includes both utility users (including the kind of utilities they depend on) and providers, distinguishes between different types of utility provides, and allows extensions by type-specific classes of critical utility infrastructure (e.g. power stations, substations, wells, pumps, treatment plants, traffic control features). At the core lies a “Utility Connection” class that saves which providers serve which users, either via direct connections (where known) or via spatially-defined service areas. This patterns has been implemented as an openly available OWL2 ontology design pattern and has been logically verified and validated against sample data and queries. We further demonstrate how this pattern can be used to express increasingly complex queries about cascading features and explore the scalability of these queries when computed over thousands or even millions of features-at-risk.


• Joshua Parisi and M. Sadegh Riasi, University of Cincinnati, "Structural Controllability of Hydrologic Networks During Floods"
Despite local and federal mitigation plans, damages due to inland flooding have been on the rise in the past few decades. In order to prepare for disastrous flooding events, it is essential to understand the control measures needed to contain or limit the extent of damages. From the systems analysis point of view, a system is called controllable if, with a proper choice of inputs, it can be driven from any initial state to any desired state.  Controllability can then readily be interpreted as the ability to control flow levels – a major goal in flood mitigation and management. In our earlier study (Riasi & Yeghiazarian, 2017), we presented the concept of structural controllability for quantitatively characterizing controllability of surface water networks. For this reason, hydrologic networks were represented as a collection of nodes symbolizing junctions, inlets and outlets, and edges (links) symbolizing stream paths. Focusing on nodal dynamics in hydrologic networks, we proposed a set of four metrics (Full controllability, Target control efficiency, control Centrality, and control Profile – FTCP) to determine the structural boundaries of the system’s control space, in other words, the set of outer limits of what is possible. These metrics collectively answer questions such as: How does the structure of a network affect its controllability? How to efficiently control a preselected subset of the network? Which nodes have the highest control power? What types of topological structures dominate controllability? Due to the importance of dynamical processes that occur along the flow conduits (i.e. edges in flooding networks), edge dynamics can highly affect our ability to control such networks. For this reason, in this study we extend our controllability to include edge dynamics, and implement both nodal and edge-based controllability analysis on surface and stormwater flow networks during a flooding event. The objective of this study is twofold: i) understand the difference between node-controllability and edge-controllability for flooding; and ii) develop a framework to understand the impact of individual edges (flow conduits) on the overall controllability of the system. References: Riasi, M. S., & Yeghiazarian, L. (2017). Controllability of Surface Water Networks. WRR, 53(12), 10450–10464. https://doi.org/10.1002/2017WR020861


• Michael Bianchini, Dušan Stipanović, and Ximing Cai, University of Illinois at Urbana-Champaign and Erhu Du, Southern University of Science and Technology, "Hierarchical Framework for Flood Evacuation: Optimization of Evacuation Order Policies with Consideration of Human Behavior"
Negative consequences of flooding disasters in communities can be reduced through preemptive evacuations or by sheltering in place. Government agencies and their constituents are both responsible for selecting appropriate preventative actions for a given storm event. The government monitors storm forecasts and issues evacuation orders to specific neighborhoods (flood zones) over time; residents respond by making an evacuation decision and selecting an evacuation route. In this study, the interacting roles of government and residents are characterized in a hierarchical framework established to minimize negative flood consequences. The framework is comprised of five distinct models: an optimization model, opinion dynamics model (ODM), agent-based traffic model (ABM), storm forecast model, and hydrodynamics model. Evacuation order policies, consisting of suggested (voluntary) and mandatory orders to flood zones over time, are developed by the government to minimize flood-related risks and evacuation-related time costs. Resident evacuation decisions in response to the policies are evaluated in the ODM with consideration of heterogeneous human behaviors and stochastic exchange of information. An ABM developed using the Multi-Agent Transport Simulation (MATSim) software evaluates movement of individuals within a transportation network and flood zone level outcomes. Results for a series of storm and associated flood scenarios are returned to the government optimization model, which selects an improved evacuation order policy. The approach is novel in its inclusion of both an advanced ODM and ABM into an optimization framework for flood evacuation. The City of Wilmington, North Carolina is selected for implementation of the hierarchical model, and optimal evacuation order policies are developed for three historical hurricane events: Florence, Matthew, and Dorian. Sensitivity analyses are performed to assess the suitability of the identified policies when different assumptions about human behaviors and alternative evacuation route options are considered. Future efforts could incorporate evolving storm forecasts to allow real-time recommendations via an online tool for the selection of evacuation order policies and evacuation routes.

Automated Hydrological Feature Extraction from Digital Terrain Data

Moderator: Alvan Karlin

Presenters:

• Alvan Karlin and Josh Novac, Dewberry, "Extracting Flowline Features from Digital Elevation Models – an Evolutionary Approach"
With the USGS 3D-Elevation Program (3DEP) goal of elevation-mapping the contiguous US to the QL2 specification and Alaska to the QL5 specification, and the 3D Nation initiative focusing on mapping from the tops of mountains to the depths of the ocean, additional attention has been directed toward upgrading the National Hydrography Dataset (NHD) to be more closely matched to the high precision elevation data. Toward this goal, the USGS Lidar Base Specifications 1.3, released in Feb 2018, introduced an “EleHydro” data dictionary as a guide for how breaklines would be compiled. Though not a requirement, the concept was offered as a guide for hydrological breaklines and a roadmap to deriving flowlines from elevation data. Since its initial release, the National Hydrography Dataset (NHD) has been revised and upgraded to reflect higher resolution imagery and topography. Likewise, the EleHydro guidelines have evolved into a “Elevation-Derived Hydrography” (EDH) specification to incorporate the higher precision lidar/IfSAR elevation data into the flowlines and waterbodies of the nation. NHD data are currently being developed with the new EDH specifications under USGS pilot project programs using either QL2 lidar-derived and QL5 IfSAR-derived digital elevation models. Since the early 1990s (Moore, et. al, 1991), numerical models have been developed to automate extracting hydrological features from Digital Elevation Models (DEM). The first models developed used the, now ubiquitous “D8” method of determining flow direction and flow accumulations. As the techniques to develop DEMs evolved, so did the models for extracting the features, including multi-directional flow, an infinite directions flow, and cost-based analysis. New, ancillary DEM-derived surfaces to help interpret terrains, such as Geomorphic Forms (Geomorphons), Topographic Wetness Index, Topographic Position Indexes, Curvature and others have come to be commonplace in flowline extraction workflows. This presentation, (1) discusses the significant differences between several of the publicly available numerical models, (2) compares the currently available techniques for preparing DEM surfaces and feature (flowline) extraction, and (3) explores some of the challenges with using IfSAR-derived DEMs for NHD flowline extraction in Alaska.


• Stephen Aichele, US Geological Survey, "Deriving Hydrography Data from 3D Elevation Program High Resolution Data in Alaska and CONUS: Successes, Issues, and Questions"
The U.S. Geological Survey is leveraging the success of the 3D Elevation Program (3DEP) at acquiring high-resolution elevation data to improve the National Hydrography Dataset (NHD). Specifications for deriving hydrography from elevation data were published in 2019. After a set of pilot projects in Alaska, acquisitions have reached an operational posture, and over 60,000 square miles of updated hydrography data will be produced in Alaska each of the next 7 years. In the conterminous US, pilot projects are underway in Texas, Pennsylvania, and planned in Oregon to better understand issues that will be encountered in moving from research to production. This presentation will provide an overview of the approach to developing the program, describe some of the real-world issues encountered so far in Alaska and the CONUS pilots, and discuss preferences for addressing some of these situations.

Methods in Reclaimed Water Management

Moderator: Shirley Clark

Presenters:

• Dee Korich, City of Tucson/Tucson Water Department, "Tucson's Reclaimed Water System"
Water is Tucson’s most precious natural resource. Today we are more fortunate than many southwestern cities because we have four sources of water: groundwater, Colorado River water, captured rainwater, and recycled water. Recycled water is an important water resource today and for the future. Tucson Water uses some of its recycled water to produce reclaimed water. Reclaimed water is specially treated for irrigation and a variety of other uses but is not treated to be used for drinking and bathing. The nitrogen and phosphorus in reclaimed water provide fertilizer for plants and grass. Tucson Water has the capacity to deliver over 30 million gallons per day (MGD) of reclaimed water through infrastructure that is separate from our drinking water supply system. The reclaimed system includes 173 miles of pipe and 15 million gallons of storage in enclosed reservoirs. Since 1984 Tucson Water has been recycling water for irrigation and other uses. Tucson Water delivers reclaimed water to customers in our service area and neighboring communities including golf courses, parks, schools and more than 700 homes. Using reclaimed water to irrigate plants and landscaping saves more than six billion gallons of drinking water a year – enough to supply more than 60,000 families. Tucson Water maximizes its use of reclaimed water through a complicated system of multiple recharge projects and production wells. Reclaimed water not immediately needed by customers is stored underground for future use and then pumped back into the distribution system when needed. Some reclaimed water is recharged in areas of the basin experiencing significant groundwater declines to boost water levels. Some reclaimed water is delivered to the environment to create wetland and riparian habitats. This presentation will provide an overview of the history of Tucson’s Reclaimed Water System including the recent expansion of the system to recreate a flowing stream in downtown Tucson (the Santa Cruz River Heritage Project) and to boost water levels in a part of town experiencing groundwater declines (the Southeast Houghton Area Recharge Project or SHARP). Future projects will also be discussed, as will some important water quality challenges.


• Allison Lewis, Jacobs, and Rachel Slocumb, City of Ocala, FL, "Reuse, Reduce, Recharge, Restore & Recreate: The Ocala Wetland Recharge Park"
Silver Springs, located in North-Central Florida, is world famous for its crystal-clear waters and is the ecological and economic engine in the area. However, long-term flow and water quality data indicate a significant decline in spring flow and increase in nutrient concentrations which has led to ecological degradation of Silver Springs. The City of Ocala (City), located within the Silver Springs springshed, constructed a treatment wetland designed for groundwater recharge to offset their use of groundwater and nutrient loads to Silver Springs associated with municipal water and wastewater management. This 35-acre groundwater recharge wetland will treat up to 5 million gallons per day of reclaimed water and stormwater to recharge the aquifer; protect water quality; and recover and enhance the flows to Silver Springs. The Silver Springs system is subject to Total Maximum Daily Load regulations for nitrate and has a recovery strategy to help meet its established Minimum Flows and Levels. The Ocala Wetland Recharge Park (Park) project supports both nitrate load reductions and recharge to help augment flows in the springshed. The Park provides a unique opportunity to address environmental challenges through creation of habitat and a public park for the community. The Park has seen over 140 bird species and 35,000 visitors since the first six months of the Park opening. Educational exhibits related to wetland ecology, hydrogeology, and the Park’s connectivity to Florida springs dot the Park along boardwalks, trails, and other park amenities for public education and enjoyment. Based on wetland treatment performance calculations, its estimated that the wetland will remove, per year, up to 29,000 pounds total nitrogen, 23,000 pounds nitrate, and 30,000 pounds total phosphorus. These reductions equate to an annual mass removal of 64%, 95%, and 56% for total nitrogen, nitrate, and total phosphorus, respectively. The natural resource benefits to both water quality and water quantity led this project to be ranked #1 for funding from SJRWMD and secured Springs Funding from FDEP. The Park represents a multi-benefit “natural solution” that should be considered for other similar regions needing to address both water supply and water quality in an innovative way.


• Shirley Clark, Penn State Harrisburg, "Salinity Transport in a Bioretention Basin Due to Winter Storm De-Icing Salt Applications"
The transport of salinity due to deicing salt application was investigated a bioretention basin in the city of Lancaster, Pennsylvania. In the Winter 2020-2021 study period, there were three de-icing salt applications by the City to the nearby roadway and sidewalk. The data analysis indicated snow and cold temperatures did not have a significant effect on the response of salinity levels in the top 8 inches of the bioretention soil, likely due to the lack of a flow of water moving the salt from the roadway/sidewalk into the system. Precipitation in the form of rain had a significant effect on the salinity readings in the soil, and in the presence of de-icing salt loadings, the concentration of salinity in the bioretention soil and basin water was shown to increase substantially. The response time of salinity concentrations in the soil after rain events generally decreased as the rain intensity increased. The lack of transport during snow and freezing rain/sleet and the increased movement during rain events highlights the impact of the rain portion of the mixed events that are common to the mid-Atlantic region. Soil salinity measurements took at least 57 days after the end of the last recorded salt application to decrease to baseline concentrations. This research and analysis spans only from December 2020 to March 2021, but the research is expected to continue as a multi-year project conducted by numerous Penn State faculty and students. The goal is to expand upon the knowledge about the health of urban bioretention systems in the presence of seasonal influences.

Automated Framework for Flood Modeling and Forecasting using Geospatial Descriptors and the Interconnected Channel and Pond Routing (ICPR) Model

Moderator: Siddharth Saksena

Presenters:

• Peter Singhofen, Streamline Technologies, Inc., "Demonstrating Pilot Applications of the Automated H&H Modeling Framework for Flood Prediction and Forecasting"
This is the 4th presentation of the topical session entitled “An automated framework for flood modeling and forecasting using geospatial descriptors and the Interconnected Channel and Pond Routing (ICPR) model”. Two pilot applications of the automated H&H modeling framework are described including the Neches River Basin (29K sq. km.) in southeast Texas and the Cape Fear River Basin (24K sq. km.) in North Carolina. Model detail, speed of model construction, and accuracy of model results are presented as well as techniques for refining the model in urban settings. Probabilistic and automated real-time flood forecasting approaches, and integration into the Urban Flooding Open Knowledge Network are discussed.


• Sayan Dey, Purdue University, "System for Producing River Network Geometry (SPRING): An Automated Tool for Extracting Geospatial Descriptors for Large-scale Flood Modeling"
Hyper-resolution flood models require detailed topographic datasets such as Digital Elevation Model (DEM) as well as geospatial descriptors representing channel centerline, banks, channel geometry and hydraulics (cross-sections, breaklines). These descriptors are derived from different sources leading to errors such as improper spatial correspondence and incomplete channel representation that can critically hinder accurate flood simulation. To develop large watershed scale flood models with dense drainage network, there is a need for automated generation of high-resolution detailed geospatial descriptors for a river network spanning thousands of kilometers. This study presents an automated framework called System for Producing RIver Network Geometry (SPRING) for creating and updating geospatial descriptors required for large watershed-scale flood modeling. The flexibility of SPRING to incorporate varying level of detail across a river network while requiring minimal user interaction makes it ideally suited for processing large watersheds. The advantages of SPRING are demonstrated across two large watersheds in the United States by rapidly creating integrated flood models from publicly available datasets with minimal user input. Comparison of flood outputs with USGS gauge measurements further validate the performance of proposed framework.


• Frank McKinnie, Streamline Technologies, Inc., "Incorporating National Scale Infrastructure for Automated Generation of H&H Models"
Developing accurate H&H models for large-scale watersheds requires a significant amount of time, effort, and resources to complete, especially when manual methods are used. This presentation describes a suite of custom tools developed in ArcGIS using Python that take advantage of the National Hydrography Dataset (NHD). NHD flowlines and “structure” point locations are converted into a computational framework of nodes and links (nodal network) with variable discretization based on stream order. The tools can also incorporate data from other sources into the nodal network such as Tiger/Lines, the National Inventory of Dams, the National Levee Database, and low water crossing databases. An example will be presented as part of the discussion with an approximate 35,000-node computational network constructed using a 500-meter spacing. The total processing time for the network development is approximately 15-minutes. After the nodal network is developed, tools developed by others in this session are used to center channel links based on available terrain data, develop channel cross sections including bathymetry and roughness characteristics, and create catchment polygons to each node.


• Siddharth Saksena, Virginia Tech University, "Introduction and Significance of an Automated Flood Modeling and Forecasting Framework Using the Interconnected Channel and Pond Routing (ICPR) Model"
As the flood intensity and magnitude is expected to rise from urbanization and climate change, there is a growing need to develop flood prediction and alert systems that can capture the compound nature of extreme events. In this regard, integrated hydrosystem models have shown the ability to capture the mechanistic interplay between watershed processes under different atmospheric conditions. Despite an immense potential, the application of these towards flood prediction remains challenging without compromising on the spatiotemporal scale and resolution, computational efficiency, and local-scale hydrodynamics. This talk will introduce the need for an automated framework for large-scale flood prediction, highlight problems associated with building it, and discuss the overall methodology being implemented to develop this framework using a computationally efficient hybrid design.