Scalability of CASCADE2001: Gis-Based Flood Risk Screening Tool to Support Watershed Master Planning
DOI:
https://doi.org/10.63002/asrp.28.562Keywords:
Flooding, watershed, drilldown flood modeling, screening tool, risk, infrastructure prioritizationAbstract
Flood risk analysis is the instrument by which floodplain and stormwater utility managers create a sound strategy and adaptation plans to reduce flood potential in their communities. As a result, there is a need to develop a flood risk screening tool to analyze watersheds and find vulnerable areas by leveraging the scientific and technological developments of the last decade to prioritize improvements. Because local municipalities are continuously challenged by the impacts of changes in precipitation and other climatic events, the screening tool needs to be scalable, while providing similar results of spatial inundation extent regardless of the scale. Likewise, the ability to perform this analysis without overwhelming limited modeling budgets is a goal for local governments who may spend large amounts of money on capital in the future to retrofit their stormwater management systems. The present study investigates the scalability of a GIS-based hydrologic-hydraulic model, CASCADE2001, to support development of watershed-based flood protection plans. The comparative analysis of the predicted flood response at three nested levels of scale were applied in south Florida to a 8-digit hydrologic unit code (HUC) level (the Caloosahatchee Watershed), a 12-digit HUC level (the Ninemile Canal Subwatershed within the Caloosahatchee Watershed), and a local municipal level (City of Clewiston, Florida within the Ninemile Canal subwatershed). The findings were that the model was scalable and the infrastructure that mattered with respect to results was driven by the scale.
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Copyright (c) 2024 Tucker Hindle, Frederick Bloetscher, Anthony Abbate, Jeffery Huber, Weibo Liu, Daniel E. Meeroff, Diana Mitsova, S. Nagarajan, Colin Polsky, Hongbo Su, Ramesh Teegavarapu, Zhixiao Xie, Yan Yong, Caiyun Zhang
This work is licensed under a Creative Commons Attribution 4.0 International License.