Spatial assessment of flash‐flood vulnerability in the Moldova river catchment (N Romania) using theFFPI

Abstract

The identification of the areas vulnerable to flash floods is one of the greatest challenges in flood risk management for both the scientific world and decisionmakers. Its importance is underlined by the European Directive 2007/60/EC, which sets out the general framework of public policies to reduce the impacts of floods on the development of local communities. This research was conducted in the Moldova river catchment, located in the northern part of Romania, in the Carpathian Mountains, where half of the administrative-territorial units record floods annually. The methodology used the Flash Flood Potential Index (FFPI) which has been computed based on the correlation of various factors which have a direct impact on the surface runoff. Each geographical factor has been represented on a 30 m grid and the data aggregation has provided the spatial hazard model for floods. In addition, the impact of deforestation on flood events was also analysed. The result of the FFPI was compared with the official flood records of the local authorities from our study area. The results constitute a methodological instrument, complementary to the classical ones, for the elaboration of the flood hazard maps, with a special importance given to the modelling of this type of hazard in the area with no structural defence measures.

Flash Flood Assessment Using GIS and the Frequency Ratio Bivariate Statistical Model – Case Study, Codlea, Romania

“…In the present study, with the help of the FFPI method, we provided a way to determine floods in hydrologically unmonitored areas, thus covering a dysfunction mentioned in numerous studies that aimed to model the risk of flooding (Costache 2019b;Costache et al 2020;Minea 2013;Popa et al 2020;Zeng et al 2016).…”

Evaluating flash flood vulnerability using combined deterministic and parametric model: A case in the upper Ciliwung watershed, Indonesia

“…Its objective is to appraise the probability of flooding within a hydrological basin, grounded on the physicalgeographic attributes of the sub-basins where inundation could occur. Since then, several studies have utilized the FFPI method to assess the potential for flash flooding in watersheds [7,[14][15][16]. The methodology entails generating raster data sets that depict the physical-geographic characteristics that impact runoff and the probability of flash flooding [15].…”

“…Since then, several studies have utilized the FFPI method to assess the potential for flash flooding in watersheds [7,[14][15][16]. The methodology entails generating raster data sets that depict the physical-geographic characteristics that impact runoff and the probability of flash flooding [15]. The FFPI integrates four variables: slope, land use/land coverage, soil type/texture, and vegetation coverage/density -in GIS raster surfaces.…”

“…The database was integrated using a weighted average equation, resulting in five vulnerability categories from very low to very high. In northern Romania, the study utilized annual flood occurrences in 50% of administrative-territorial units [15]. The FFPI methodology was employed, correlating factors impacting surface runoff represented on a 30 m grid.…”

Computational advances and innovations in flood risk mapping

“…Three papers of this special issue are focused on this topic. Two of them discuss the need of identifying vulnerable areas (Popa et al, 2020) for assessing their susceptibility to flash floods (Iosub, Minea, Chelariu, & Ursu, 2020), with the final aim of evaluating population exposure to water-related risks. The combined use of innovative modelling techniques and remotely sensed data can reduce the time and effort needed for reaching the goal, allowing for more accurate risk maps and more timely responses to flash floods.…”