iSeeFlood is a research outcome of iSPUW, or integrative Sensing and Prediction of Urban Water for sustainable cities, a joint project among the University of Texas at Arlington, University of Michigan and University of Massachusetts Amherst. iSPUW is funded by the National Science Foundation's CyberSEES (Cyber Innovation for Sustainability Science and Engineering) program. iSeeFlood was developed by Dr. Michael Zink and his student, Lohith Lakshman, at UMass Amherst.Monitoring and prediction of urban flooding is very difficult because many urban catchments are very flashy due to impervious cover and have very complex physiography due to many man-made structures and changes. As such, hydrologic and hydraulic modeling alone is not enough to produce accurate flood predictions, particularly at high resolutions where the processes can vary greatly in space and change very quickly in time. The purpose of iSeeFlood is to gather a large number of flooding observations from the willing citizens to aid emergency management in times of flooding and to assimilate them into hydrologic and hydraulic models to keep the model states in line with what is actually happening in reality, and hence to improve the accuracy in model predictions of flooding.
iSeeFlood
