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Abstract:Mean daily streamflow records from 44 river basins in Romania with an undisturbed runoff regime have been analyzed for trends with the nonparametric Mann-Kendall test for two periods of study : 1961-2009 (25 stations) and 1975-2009 (44 stations). The statistical significance of trends was tested for each station on an annual and seasonal basis, for different streamflow quantiles. In order to account for the presence of serial correlation that might lead to an erroneous rejection of the null hypothesis, a trend-free prewhitening was applied to the original data series. The regional field significance of trends is tested by a bootstrap procedure. Changes in the streamflow regime in Romania are demonstrated. The main identified trends are an increase in winter and autumn streamflow since 1961 and a decrease in summer flow since 1975. The streamflow trends are well explained by recent changes in temperature and precipitation that occurred in the last 50 years.

Given the significant worldwide human and economic losses caused due to floods annually, reducing the negative consequences of these hazards is a major concern in development strategies at different spatial scales. A basic step in flood risk management is identifying areas susceptible to flood occurrences. This paper proposes a methodology allowing the identification of areas with high potential of accelerated surface runoff and consequently, of flash-flood occurrences. The methodology involves assessment and mapping in GIS environment of flash flood potential index (FFPI), by integrating two statistical methods: frequency ratio and weights-of-evidence. The methodology was applied for Bâsca Chiojdului River catchment (340 km 2), located in the Carpathians Curvature region (Romania). Firstly, the areas with torrential phenomena were identified and the main factors controlling the surface runoff were selected (in this study nine geographical factors were considered). Based on the features of the considered factors, many classes were set for each of them. In the next step, the weights of each class/category of the considered factors were determined, by identifying their spatial relationships with the presence or absence of torrential phenomena. Finally, the weights for each class/category of geographical factors were summarized in GIS, resulting the FFPI values for each of the two statistical methods. These values were divided into five classes of intensity and were mapped. The final results were used to estimate the flash-flood potential and also to identify the most susceptible areas to this phenomenon. Thus, the high and very high values of FFPI characterize more than one-third of the study catchment. The result validation was performed by (i) quantifying the rate of the number of pixels corresponding to the torrential phenomena considered for the study (training area) and for the results' testing (validating area) and (ii) plotting the ROC (receiver operating characteristics) curve.

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).

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