Non-structural flood mitigation optimization at community scale: Middle Cedar Case Study.

Flooding is the leading natural hazard in Iowa and has resulted in billions of dollars of damage to properties and critical infrastructure over the past couple of decades. Land alterations, urbanization, and changing precipitation regimes increase the magnitude and frequency of flood events. Considering the increasing risk, flood mitigation efforts are significant to reduce future losses. In this study, we present a comprehensive flood mitigation assessment for the cities of Cedar Falls, Cedar Rapids, and Waterloo in Iowa, utilizing various datasets such as property information, flood inundation maps, mitigation costs, and depth-damage functions. The research revealed that flooding has a minimal impact on Waterloo below the 200-year return period flood scenario, but Cedar Falls and Cedar Rapids are significantly vulnerable, requiring more mitigation investments and planning. The study conducted a benefit-cost analysis, indicating that dry floodproofing is the most feasible option to reduce flood impacts in all studied communities. Moreover, the research conducted a climate data-driven analysis, which found that elevating structures significantly increases the number of feasible mitigation options, regardless of various long-term climate projections. The study also analyzed predetermined mitigation budgets, revealing potential avoided losses and benefit-cost ratios for properties with the highest BCRs and prioritizing them to maximize the total benefit to the communities. The study findings offer crucial insights and recommendations to guide decision-makers in the community on prioritizing cost-effective flood mitigation strategies and minimizing flood impact in the studied regions.

Agricultural flood vulnerability assessment and risk quantification in Iowa.

Agricultural lands are often impacted by flooding, which results in economic losses and causes food insecurity across the world. Due to the world's growing population, land-use alteration is frequently practiced meeting global demand. However, land-use changes combined with climate change have resulted in extreme hydrological changes (i.e., flooding and drought) in many areas. The state of Iowa has experienced several flooding events over the last couple of decades (e.g., 1993, 2008, 2014, 2016, 2019). Also, agribusiness is conducted across 85% of the state. In this research, we present a comprehensive assessment for agricultural flood risk in the state of Iowa utilizing most up-to-date flood inundation maps and crop layer raster datasets. The study analyzes the seasonal variation of the statewide agricultural flood risk by focusing on corn, soybean, and alfalfa crops. The results show that over $230 million average annualized losses estimated at statewide considering studied crop types. The crop frequency layers and corn suitability rating datasets are investigated to reveal regions with lower or higher productivity ratings. The study founds nearly half a million acres of cropland is under 2-year return period flood zone. Additionally, a data-driven flood model, Height Above the Nearest Drainage (HAND), is used to analyze performance against the FEMA maps. We found that the HAND flood maps performed with the correlation of 0.93 and 0.94 for 100-year and 500-year flood events regarding to the FEMA maps.

Flood mitigation data analytics and decision support framework: Iowa Middle Cedar Watershed case study.

Flooding is one of the most frequent natural disasters, causing billions of dollars in damage and threatening vulnerable communities worldwide. Although the impact of flooding can never be diminished, minimizing future losses is possible by taking structural or non-structural mitigation actions. Mitigation applications are often costly practices. However, they can be more feasible for long-term planning and protection. On the other hand, selecting a feasible option requires a comprehensive analysis of potential risk and damages and comparing the costs and benefits of different mitigation types. This paper presents a web-based decision support framework called Mitigation and Damage Assessment System (MiDAS) that analyzes flood risk impacts and mitigation strategies at the community and property-level with the goal of informing communities on the consequences of flooding and mitigation alternatives and encouraging them to participate in the community rating system. The framework utilizes regulatory flood inundation maps, damage functions, property information, scenario-based climate projections, and mitigation inputs and guidelines from the Federal Emergency Management Agency (FEMA) and the United States Army Corps of Engineers (USACE). It will help users select the appropriate flood mitigation measures based on various characteristics (e.g., foundation type, occupancy, square footage) and provide cost estimates for implementing measures. The system also provides a decision tree algorithm for analyzing and representing the mitigation decision by reviewing existing guidelines (e.g., FEMA, USACE). We analyzed the community-level mitigation for three major cities in Eastern Iowa (Cedar Falls, Cedar Rapids, and Waterloo) and found certain measures (e.g., wet/dry floodproofing) are cost-effective for community-level mitigation. Implementation of mitigation measures can reduce the property's vulnerability and improve the response to a flooding event.