{"id":20361,"date":"2024-06-06T14:21:22","date_gmt":"2024-06-06T18:21:22","guid":{"rendered":"https:\/\/engineering.jhu.edu\/magazine-archive\/?p=20361"},"modified":"2024-06-10T14:21:33","modified_gmt":"2024-06-10T18:21:33","slug":"clearer-predictions-for-river-flood-damage","status":"publish","type":"post","link":"https:\/\/engineering.jhu.edu\/magazine-archive\/2024\/06\/clearer-predictions-for-river-flood-damage\/","title":{"rendered":"Clearer Predictions for River Flood Damage"},"content":{"rendered":"\"illustration<\/a>\n

Rivers overflowing their banks have caused property damage and loss of life in Texas, China, and Kenya in recent months, underscoring the increasing perils of climate change.\u00a0<\/span><\/p>\n

To prepare for such floods, governments deploy mathematical models. However, due to time constraints and lack of data, these models sometimes incorporate \u201coff-the- shelf\u201d damage calculations based on previous unrelated floods, which are often inaccurate.<\/p>\n

Gonzalo Pita<\/a>, an expert on natural disaster risk modeling, has developed a reliable and affordable way for governments to estimate expected damage from river floods. This new method provides users with step-by-step instructions and also measures and assigns numerical values to the level of uncertainty in individual flood damage forecasts, giving governments a clearer picture of how reliable their predictions are.<\/p>\n

\u201cAccurate predictions are crucial to the safety and well-being of people and property. If a government acts based on inaccurate information, its preparation can be off by orders of magnitude, with very serious results,\u201d says Pita, an associate research scientist in the Department of Civil and Systems Engineering and an instructor in the Johns Hopkins Engineering for Professionals\u2019 civil engineering program<\/a>.<\/p>\n

The study appears in The International Journal of Disaster Risk Reduction<\/i><\/a>. It builds upon work that previously appeared in The Journal of Hydrology<\/i><\/a>.<\/p>\n

In the new study, Pita first investigated the accuracy of using expert opinion alone to estimate and predict flood damage. He surveyed multiple authorities and simulated thousands of expert surveys in numerous combinations to analyze how the composition of the expert team influences prediction accuracy.<\/p>\n

Pita then tackled the issue of \u201cdamage functions,\u201d a fundamental component of natural disaster risk simulations. \u201cWith this method, these functions can be built inexpensively but with a useful level of accuracy that governments can use provisionally until they get better data that will enable them to generate more accurate functions,\u201d he says.<\/p>\n

The new approach works by helping quantify the uncertainty in experts\u2019 predictions by assigning weights to each expert, resulting in a more detailed analysis of the uncertainties involved. The result is a method that Pita expects to be \u201cvery useful\u201d for flood modelers and influencing preparedness policy, resulting in \u201cinsights that could inform policy directly and indirectly\u2014from enabling smarter zoning laws and budgeting for asset maintenance to designing disaster insurance programs.\u201d\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

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