Using AI and big data to optimise land management decisions for reducing river flood risk
Abstract
Local authorities across Wales are increasingly seeking natural approaches to river flood management, especially the role of land management decisions in reducing peak flows. Physics-based hydrological models, which simulate river flood response to storm events, can provide multi-scenario assessment of land-use changes on floods. However, they require prior calibration of parameters using measured streamflow data, which is not available for many rivers. We investigate how AI and big data can be used to implement hydrological models in river basins with no streamflow data.
A. M. F. Rigby, P. W. S. Butcher, S. D. Patil, and P. D. Ritsos, “Using AI and big data to optimise land management decisions for reducing river flood risk,” in Data Transformation: Wales Data Nations Accelerator, Cardiff, UK, 2022.
Bibtex
@inproceedings{Rigby-et-al-Poster-WDNA-2022,
author = {Rigby, Alex M.F. and Butcher, Peter W.S. and Patil, Sopan D. and Ritsos, Panagiotis D.},
title = {{Using AI and big data to optimise land management decisions for reducing river flood risk}},
year = {2022},
month = may,
booktitle = {Data Transformation: Wales Data Nations Accelerator, Cardiff, UK}
}