Cyberinfrastructure to Support Flood Modeling from Catchment to Regional Scales

Abstract

Flooding events are projected to increase in frequency and intensity in coming years due to climate change. New tools and approaches are needed to assist decision makers in better understanding and addressing societal impacts due to flooding and how to mitigate these impacts.This research addressed three challenges related to flooding impacts: (i) better understanding how distributed stormwater infrastructure can mitigate flooding in urban catchments, (ii) designing and building spatially-detailed, real-time flood warning systems for emergency management purposes, and (iii) designing and building cyberinfrastructure to support reuse and transparency in both flood modeling and hydrologic modeling more broadly. The goal of this research was to address these challenges by conducting three studies. The second study explored building an automated cloud-based system for forecasting flooded roadway and bridge locations at a regional-scale. Because the study area has very low topographic relief, a two-dimensional (2D), computationally-expensive hydrodynamic model is required. This study demonstrated the ability of using instances in a public cloud with powerful graphical processing units (GPUs) to run a large (average of 4 million nodes) 2D hydrodynamic model in a time frame relevant to real-time emergency management applications. The steps required to build this system were (i) creating an automated workflow for obtaining and processing ii forecast rainfall data, (ii) running the 2D model in the cloud, (iii) using geospatial analysis tools to identify flooded bridges, and (iv) presenting the results online for decision makers. The system automates forecast data access and pre-processing, execution of a high-resolution 2D hydrodynamic model, and map-based visualization of model outputs using Amazon Web Services (AWS).The third study advanced approaches for sharing hydrologic models, such as the models created in this dissertation, through community supported cyberinfrastructure. Sharing models is important for scientific reproducibility, reuse, and fidelity. In this study, the first task was to design a metadata framework for hydrologic models that is flexible and applicable across the wide variety of models used by hydrologists. Then the study demonstrated the utility of this framework for sharing, publishing, and reusing models through an implementation within the HydroShare cyberinfrastructure system.In the first study, the results suggest that rain gardens with 30 cm berm heights and a total area equal to 20% of the impervious surfaces within the watershed should provide sufficient storage to mitigate flooding for rain events up to and including a 10 year return period storm event.The results also suggest approximately 15%, 27%, and 38% of the runoff generated from impervious surfaces should be diverted to the rain gardens to mitigate flooding from 2, 5, and 10 year return period storm events, respectively. Given prior work on the adoption of LID approaches for other watersheds, rain gardens could effectivel...