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Abstract:The purpose of this paper is to identify areas with high flash-flood potential based on an evaluation of physiographic factors controlling the formation of surface runoff. The research method relies on the use of the Flash Flood Potential Index (FFPI), which incorporates physiographic characteristics from the catchment (terrain slope, profile curvature, land use and soil texture). The spatial distribution of the physiographic factors (which contribute to the creation, control and concentration within the drainage network of the overland flow) and the classified zoning of areas according to their hydrological response were achieved with GIS techniques. The results obtained show that physiographic factors on 227 sq km (29%) favor surface runoff on slopes and its localization towards the drainage network. Notably, the highest values of FFPI belong to the lower part of the catchment, where high human population density can be found, reflecting an increased vulnerability to floods and inundations of this area.

Flood risk assessment is an important component of risk management. Given this context, this paper aims to identify and map areas with high potential for flash-floods and flooding occurrence, at different spatial scales (from catchment to local scale), in order to estimate the flood/flooding vulnerability. The paper is based on three main methods, which were applied in the Slȃnic River catchment (427 km 2), located in the external curvature region of the Romanian Carpathians: (i) statistical analyses; (ii) determination and mapping of some indices to assess the flash-flood and flooding potential (FFPI and respectively FPI) and (iii) hydraulic modelling. The data used mainly include hydrological statistics (maximum monthly and annual discharges, flood-related data) and spatial data on catchment geographical characteristics (hypsometry, geology, soils, land use) obtained or derived from various sources (maps, aerial images, digital databases, field measurements) which were integrated into the GIS environment. The aforementioned methods helped to (i) highlight specificities of floods in the Slȃnic catchment (magnitude, frequency, flood waves characteristics); (ii) identify areas with high potential for flash-floods and flooding at the catchment spatial scale; (iii) assess the structural vulnerability in the Cernȃteşti village, by simulating flood-prone areas for flood peaks with exceedance probability of 1%, 5% and 10%. The results could lead to a better knowledge and understanding of flood characteristics in the study area, in order to mitigate the flood risk through a more effective management, both at the catchment scale, as well as local scale (in the Cernȃteşti village).

The aim of the present study was to explore the correlation between the land-use/land cover change and the flash-flood potential changes in Zăbala catchment (Romania) between 1989 and 2019. In this regard, the efficiency of GIS, remote sensing and machine learning techniques in detecting spatial patterns of the relationship between the two variables was tested. The paper elaborated upon an answer to the increase in flash flooding frequency across the study area and across the earth due to the occurred land-use/land-cover changes, as well as due to the present climate change, which determined the multiplication of extreme meteorological phenomena. In order to reach the above-mentioned purpose, two land-uses/land-covers (for 1989 and 2019) were obtained using Landsat image processing and were included in a relative evolution indicator (total relative difference-synthetic dynamic land-use index), aggregated at a grid-cell level of 1 km2. The assessment of runoff potential was made with a multilayer perceptron (MLP) neural network, which was trained for 1989 and 2019 with the help of 10 flash-flood predictors, 127 flash-flood locations, and 127 non-flash-flood locations. For the year 1989, the high and very high surface runoff potential covered around 34% of the study area, while for 2019, the same values accounted for approximately 46%. The MLP models performed very well, the area under curve (AUC) values being higher than 0.837. Finally, the land-use/land-cover change indicator, as well as the relative evolution of the flash flood potential index, was included in a geographically weighted regression (GWR). The results of the GWR highlights that high values of the Pearson coefficient (r) occupied around 17.4% of the study area. Therefore, in these areas of the Zăbala river catchment, the land-use/land-cover changes were highly correlated with the changes that occurred in flash-flood potential.

River morphological quality assessment, derived from quantification of human pressures as well as river channel alteration, is a demand of the Water Framework Directive (WFD) in terms of integrating hydromorphological elements in defining ecological status. Our study's aim is to contribute to the hydromorphological evaluation by proposing indicators and separating classes, based on a revisited Morphological Quality Index (rMQI) protocol. The rMQI is based on 12 indicators of human pressures, 10 indicators of channel form adjustments, and 11 indicators of functionality. The rMQI scoring system allows for the quantification of changes when compared to reference conditions, be they undisturbed or nearly undisturbed by human interventions, with absent channel adjustments and a functioning natural river style. We used the lower, meandering sector of the Prahova River to demonstrate our assessment methodology. The Lower Prahova River suffers from a minor local intervention and a diminishing intensity of fluvial processes specific to a meandering style. Meanders geometry was affected by significant changes that included a decrease in the radius of curvature, width and width-to-mean-depth ratio. We concluded that the Lower Prahova River has a good morphological quality, which is rated as second class on a scale of five levels, from natural to severely modified. We recommend an improvement in the OPEN ACCESS Water 2015, 7 2972 hydromorphological evaluation protocol in Romania by additional indicators for morphological alterations specific to each channel pattern.