Rainfall Threshold for Flash Flood Warning Based on Model Output of Soil Moisture: Case Study Wernersbach, Germany

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.

Assessing Flood Early Warning Systems for Flash Floods

“…The locations of the case studies are shown in Figure 3. The majority of studies which were reviewed, were carried out in high-income regions within Europe (Montesarchio et al, 2015;Papagiannaki et al, 2015;Candela and Aronica, 2016;Forestieri et al, 2016;Santos and Fragoso, 2016;Bouwens et al, 2018;Hofmann and Schüttrumpf, 2020;Luong et al, 2021) and Asia (Jang, 2015;Wu et al, 2015;Miao et al, 2016;Liu et al, 2018;Zhai et al, 2018;Li et al, 2019). Few studies using RT for flash floods EWS were reported in America (Ávila et al, 2015;UNAL, 2018;Guerrero Hoyos and Aristizábal Giraldo, 2019;Castillo et al, 2020), and low-income countries in Africa (Young et al, 2021).…”

“…The hydrological methods are based on the concepts of the FFG approach, which was created by focusing on mountainous regions, uniform rainfall depth/duration over space and time and catchment sizes up to 1,000 km 2 (Mogil et al, 1978). The FFG has been modified to include gridded data (Schmidt et al, 2007;Gourley et al, 2012), synthetic hyetographs (Jang, 2015;Montesarchio et al, 2015;Wu et al, 2015;Candela and Aronica, 2016), distributed hydrological model (Jang, 2015;Miao et al, 2016;Zhai et al, 2018), and the dynamic condition of antecedent soil moisture (AMC) (Montesarchio et al, 2015;Luong et al, 2021). Gridded FFG have proposed to derive RT based on rainfall raster data, in order to capture spatial variability (Bae et al, 2018).…”

“…Recent developments identified in the case studies reviewed are a hybrid of the deterministic-stochastic approach for multiple RT estimation, new methodologies for ungauged mountainous catchments integrating flooding thresholds and RT (using a simple binary classification of maximum cumulative rainfall, degree of soil saturation, and a flooding threshold), online/offline models which have been developed and combine two warning levels (RT and flow thresholds), the use of an additional water budget model to identify the daily moisture conditions and finally, the inclusion of rainfall forecast into hydrological warning systems. Reviewed case studies of hydrological model-based RT in this study are located in Taiwan (Jang, 2015;Wu et al, 2015), Italy (Montesarchio et al, 2015;Candela and Aronica, 2016;Forestieri et al, 2016), China (Miao et al, 2016;Zhai et al, 2018), Germany (Hofmann and Schüttrumpf, 2020;Luong et al, 2021) and two case studies are located in the Manizales (Andean region in Colombia) (UNAL, 2018;Castillo et al, 2020).…”

School Location Analysis by Integrating the Accessibility, Natural and Biological Hazards to Support Equal Access to Education

“…The sloping contours tended to hold water longer, thus increasing the likelihood of flooding, whereas steeper contours tended to displace water in lower elevation areas, thus flooding probability was low. The primary determining factor of flooding was the intensity of rainfall [51]. Furthermore, low river densities can also cause flooding.…”

“…Moreover, the quantile method also aims to standardize parameter values with different units and measurement methods, ranging from 1-5 in the present analysis. The simple additive weighting (SAW) method, often used to complete multi-attribute decision-making [51], was employed here to combine each parameter and was calculated according to Equation (2):…”