Comparison of methodologies for flood rainfall thresholds estimation

Abstract

A flood warning system based on rainfall thresholds makes it possible to issue alarms via an off-line approach. This technique is useful for mitigating the effects of flooding in small-to-medium-sized basins characterized by an extremely rapid response to rainfall. Rainfall threshold values specify the amount of precipitation that occurs over a given period of time and are dependent on both the amount of soil moisture and the spatiotemporal distribution of the rainfall. The precipitation generates a critical discharge in a particular river cross section. Exceeding these values can produce a critical situation in river sites that make them susceptible to flooding. In this work, we present a comparison of methodologies for estimating rainfall thresholds. Critical precipitation amounts are evaluated using empirical data, hydrological simulations and probabilistic methods. The study focuses on three small-to-medium-sized basins located in central Italy. For each catchment, historical data are first used to theoretically evaluate the empirical rainfall thresholds. Next, we calibrate a semi-distributed hydrological model that is validated using rain gauge and weather radar data. Critical rainfall depths over 30 min and 1, 3, 6, 12 and 24 h durations are then evaluated using the hydrological simulation. In the probabilistic approach, rainfall threshold values result from a minimization of two different functions, one following the Bayesian decision theory and the other following the informative entropy concept. In order to implement both functions, it is necessary to evaluate the joint probability function. The joint probability function is built up as a bivariate distribution of rainfall depth for a given duration with the corresponding flow peak value. Finally, in order to assess the performance of each methodology, we construct contingency tables to highlight the system performance. © 2014 Springer Science+Business Media Dordrecht

Evaluation of Rainfall Thresholds Through Entropy: Influence of Bivariate Distribution Selection

“…The consistency of this methodology is also shown in Montesarchio et al . (), where it is applied to three different basins, and the approach performs well for all three river case studies. It also shows that the approach is sensitive to the amount of available data, demonstrating that better performance is achieved when data are more accessible.…”

The Recent Floods in the Asso Torrent Basin (Apulia, Italy): An Investigation to Improve the Stormwater Management

“…It must be pointed out that the assessment of a rainfall threshold is generally an hard task. Several methods are used for exorheic basins, based on the comparison of the relative performance [40], or on the measurements of the soil moisture [41]. In karst endhoreic basins, such as the Asso Torrent basin, there is no outflow to external water bodies and the outlet of water course is strongly controlled by the discharge capacity of the swallow holes, therefore, if clogging processes take place, the assessment of a threshold is uncertain.…”

Umbrales de precipitación basados en intensidad para crecidas torrenciales en la quebrada Manizales, Colombia.

“…Los umbrales de alerta definen las condiciones hidrometeorológicas bajo las cuales se toma la decisión de emitir las alarmas por parte de los organismos de emergencia hacia las comunidades en riesgo (Sene, 2008). Inicialmente, el concepto de umbral de precipitación fue adoptado por Caine (1980) para determinar la lluvia que desencadena los movimientos en masa sobre las laderas (Montesarchio, et al, 2015). Posteriormente, este concepto se adaptó en los SAT por inundación, definiéndose como: la cantidad de lluvia acumulada para una duración dada, que genera un caudal crítico sobre una determinada sección transversal del río (Georgakakos, 1995).…”