Reproducing an extreme flood with uncertain post-event information

Hydology and Earth System Sciences | Fuentes-Andino et al. [2016]


Prevention and mitigation of floods require information on discharge and extent of inundation, commonly unavailable or uncertain, especially during extreme events. This study was initiated by the devastating flood in Tegucigalpa when Hurricane Mitch struck the city. In this study we hypothesised that it is possible to estimate, in a trustworthy way despite large data uncertainties, this extreme 1998 flood discharge and the extent of the inundations that followed, from a combination of models and post–event measured data. Post–event data collected in 2000 and 2001 were used to estimate discharge peaks, times of peaks and high water marks. These data were used in combination with rain data from two gauges to drive and constrain a combination of well–known models: TOPMODEL, Muskingum–Cunge–Todini routing, and the LISFLOOD–FP hydraulic model. Simulations were performed within the GLUE uncertainty–analysis framework. The model combination predicted peak discharge, times of peaks and more than 90 % of the observed high–water marks within the uncertainty bounds of the evaluation data. This allowed an inundation likelihood map to be produced. Observed high–water marks could not be reproduced at a few locations on the floodplain. These locations are useful to improve model set–up, model structure or post–event data–estimation methods. Rainfall data were of central importance in simulating the times of peak and results would be improved by a better spatial assessment of rainfall, e.g. from satellite data or a denser rain–gauge network. Our study demonstrated that it was possible, considering the uncertainty in the post–event data, to reasonable reproduce the extreme Mitch flood in Tegucigalpa in spite of no hydrometric gauging during the event.

Full text can be found here.


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