Water Resources Research Act Program

Details for Project ID MN_2024_Zhang

Urban Flood Prediction from Limited Data: A Data-Model Integrated Approach

Institute: Minnesota
Year Established: 2024 Start Date: 2024-09-01 End Date: 2025-08-31
Total Federal Funds: $9,263 Total Non-Federal Funds: $5,095

Principal Investigators: Kun Zhang

Project Summary: Urban flooding is becoming a major natural hazard of climate change and development. Prediction of urban flooding is challenging because model simulations are time-consuming and monitoring is costly and challenging. Therefore, questions to be answered include: Can we predict urban floods with limited measurements? What times and locations are measurements most informative of urban flood occurrence? And how can we strategically deploy measurements to maximize the effectiveness of flood prediction models? Our proposed study will utilize new computational algorithms to mine existing datasets to identify the optimal locations for flood monitoring and test the efficiency of these new computational algorithms in predicting flood occurrence and depths using limited measurements.