Abstract
A comprehensive assessment of flood hazards will necessitate a step-by-step analysis, starting with hydrometeorological examinations of runoff and flow, followed by an assessment of the vulnerability of those at risk. Although bodies of knowledge about these topics are large, flood risk assessments face data challenges such as climate change, population growth, and shifting land uses. Recent studies have provided comprehensive reviews of advances in the water sciences arena, and in a complementary way, this paper reviews the state of the practice of assessing flood risk, include flood scenarios, hydrometeorology, inundation modeling, flood frequency analysis, interrelationships with water infrastructure, and vulnerability of people and places. The research base for each of these topics is extensive. Some of the tools in these areas, such as hydrologic modeling, have research advances that extend back decades, whereas others, such as numerical weather prediction, have more room to evolve. It’s clear from all studies that data is crucial along the progression from atmospheric conditions to the impact on flood victims. How data are provided and shared and how they are used by stakeholders in flood risk reduction continue to evolve. Improved availability of data and uses of emerging tools of data science and machine learning are needed to assess and mitigate flood risks. Continued the development of key tools is also required, especially to improve the capability to assemble them effectively on user platforms.
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