An Integrated Flood Risk Assessment and Mitigation Framework: Middle Cedar River Basin Case Study

Abstract

Property buyout is one of the most frequently preferred flood mitigation applications by decision-makers for long-term risk reduction. Due to its high-level funding requirements as a mitigation solution, it requires extensive benefits and costs analysis for the selected region. Many communities in the State of Iowa experienced flood events (i.e. 1993, 2008, 2014, 2019) which resulted in a heavy economic impact over a couple of decades. Nearly 3,000 property acquisitions have been made between 2007 and 2017 by Iowa Homeland Security and Emergency Management Department (IHSEMD). This study presents a web-based Flood Risk Assessment and Mitigation Environment (FRAME) which provides visual data analytics capabilities to analyze property and community level benefit-cost analysis for property acquisitions. The FRAME allows users to query previous mitigation projects and buyouts that are completed by IHSEMD. A detailed benefit-cost analysis of historical property buyouts and direct losses of existing properties in the Middle Cedar watershed in Iowa is studied using stream gauge data from the United States Geological Survey (USGS). Projected stream gauge datasets which are outputs of two climate scenarios (A1FI-fossil intensive and A2-low emission) are also utilized to assess future avoided losses for acquisitions and possible direct economic losses for existing parcels. Case study results indicate that the average benefit-cost ratio (BCR) for most buyouts in Iowa is around 0.86. In addition, nearly half of the buyouts reached to 4.72 BCR in low emission and 6.3 BCR in fossil intensive climate projections.

A Comprehensive Review of Ontologies in the Hydrology Towards Guiding Next Generation Artificial Intelligence Applications

“…Because they are usually computation-oriented rather than communication-oriented, these systems deliver either static reports or maps and allow little interaction between data and users. Information systems, on the other hand, include web-based management (Xu et al, 2019), visualization, and sharing capabilities (Yildirim and Demir, 2021) for environmental time-series data utilizing web services. Knowledge Management is a set of strategies and practices organizations use to become more systematic about managing intellectual capital -the intangible assets and resources that are not captured by conventional accounting reports, but still contribute to its value and help it achieve competitive advantage (Wallace, 2018).…”

A Systematic Review of Ontology-Based River Streamflow and Flood Data Management Challenges

“…The case study of Cedar River Basin under the property Buyout project used an integrated approach for benefit-cost analysis and flood risk analysis of the property. They consider that streamflow, flood, and environmental conditions for potential property buyout cost benefits and avoid the possible damages in the State of Iowa [31]. Qing et.…”

WaterBench: A Large-scale Benchmark Dataset for Data-Driven Streamflow Forecasting

“…The 1998 Bangladesh flood, the Iowa flood of 2008, and the 2013 North India floods show how catastrophic and both economically and psychologically devastating floods can be for populations in respective regions. In order to maximize the preparedness for floods and minimize their effects after the disaster (Yildirim and Demir, 2021), weather and flood forecasting stands as a perennial research interest for hydrologists and data scientists. Flood forecasting (also known as streamflow prediction or runoff forecasting) is a modeling effort where the water height change of a stream over time is being modeled and forecasted using previous data points for a location or nearby locations with similar characteristics.…”