Abstract
Convective rainfall can cause dangerous flash floods within less than six hours. Thus, simple approaches are required for issuing quick warnings. The flash flood guidance (FFG) approach pre-calculates rainfall levels (thresholds) potentially causing critical water levels for a specific catchment. Afterwards, only rainfall and soil moisture information are required to issue warnings. This study applied the principle of FFG to the Wernersbach Catchment (Germany) with excellent data coverage using the BROOK90 water budget model. The rainfall thresholds were determined for durations of 1 to 24 h, by running BROOK90 in “inverse” mode, identifying rainfall values for each duration that led to exceedance of critical discharge (fixed value). After calibrating the model based on its runoff, we ran it in hourly mode with four precipitation types and various levels of initial soil moisture for the period 1996–2010. The rainfall threshold curves showed a very high probability of detection (POD) of 91% for the 40 extracted flash flood events in the study period, however, the false alarm rate (FAR) of 56% and the critical success index (CSI) of 42% should be improved in further studies. The proposed adjusted FFG approach has the potential to provide reliable support in flash flood forecasting.
Highlights
This case study has tested the definition of a rainfall threshold methodology
The thresholds were estimated by running a physically based model with synthetic rainfall under various pre-event moisture conditions of the catchment. It resulted in a whole range of rainfall threshold curves categorized according to the hyetotype of rain input and antecedent soil moisture
Critical discharge is caused by higher rainfall than under wet soil conditions
Summary
The term “flash” reflects the rapid reaction of a drainage network with water levels reaching a critical stage within only minutes to a few (usually less than six) hours after the onset of a heavy rainfall event [1,2,3]. This leaves an extremely short flood warning time which can cause tremendous socioeconomic damage [4,5]. These events are likely to increase in frequency and intensity with the impact of climate change [8]
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