The risk associated with extreme hydrological processes (flash floods, floods) is more present than ever, taking into account the global climatic changes, the expansion of inhabited areas and the changes emerging as a result of inadequate land management. Of all the hydrological risks, slope flash floods represent the processes that have the highest impact because of the high speed of their development and their place of origin, which makes them difficult to predict. This study is performed in an area susceptible to the emergence of slope flash floods, the Valea Rea catchment area, spatially located in Northwest Romania, and exposed to western circulation, which favours the development of such processes. The entire research is based on a methodology involving the integration of spatial databases, which indicate the vulnerability of the territory in the form of a weighted average equation to highlight the major impact of the most relevant factor. A number of 15 factors have been used in raster spatial databases, obtained by conversion (land use, soil type, lithology, Hydrologic Soil Group, etc.), derived from the digital elevation model (slope, aspect, TWI, etc.) or by performing spatial analysis submodels (precipitation, slope length, etc). The integration of these databases by means of the spatial analysis equation based on the weighted average led to the vulnerability of the territory to FFPI, classified on five classes from very low to very high. The final result underlines the high and very high vulnerability (43%) of the analysed territory that may have a major impact on the human communities and the territorial infrastructure. The results obtained highlight the torrential nature of the analysed catchment area, identifying several hotspots of great risk, located mainly within the built-up areas of intensely inhabited regions; a fact which involves a major risk and significant potential material damage in the territory. The model was validated by directly comparing the results obtained with locations previously affected, where the flood effects have been identified, highlighting the fact that the model may be taken into account to be applied in practice, and also to be implemented in territories that share the same features.
There is an increasing need to assess and quantify the impact of land use/land cover changes, especially on surface runoff, due to rapid population growth. This study aims to investigate the land use/land cover (LULC) changes over time, for an intense rainfall event in Țibleș, Runc and Sălăuța watersheds, and their impacts on surface runoff for various antecedent moisture conditions (AMC). The GIS-based SCS-CN method and the CORINE land cover (CLC) databases for 2000, 2006 and 2012 laid the foundation for this research. Results indicated that even small land cover changes can significantly affect runoff on the short time scale, with quantitatively different effects regarding moisture conditions. The reduction in forest cover due to agricultural intensification and the conversion from pasture to cropland (especially between 2000 and 2006) resulted in higher surface runoff volumes. These changes mostly affected the middle and downstream catchments of the main rivers which means that over the years, the soil water retaining capacity has decreased.
Rain gauges provide accurate rainfall amount data; however, the interpolation of their data is difficult, especially because of the high spatial and temporal variability. On the other hand, a high-resolution type of information is highly required in hydrological modeling for discharge calculations in small catchments. This problem is partially solved by meteorological radars, which provide precipitation data with high spatial and temporal distributions over large areas. The purpose of this study is to validate a conditional merging technique (CMT) for 15 rainfall events that occurred on the southern slope of the Tibleș and Rodnei Mountains (Northern Romania). A Geographic Information System (GIS) methodology, based on three interpolation techniques—simple kriging, ordinary kriging, and cokriging—were utilized to derive continuous precipitation fields based on discrete rain gauge precipitation data and to derive interpolated radar data at rain gauge locations, and spatial analysis tools were developed to extract and analyze the optimal information content from both radar data and measurements. The dataset contains rainfall events that occurred in the period of 2015–2018, having 24 h temporal resolution. The model performance accuracy was carried out by using three validation metrics: mean bias error (MBE), mean absolute error (MAE), and root mean square error (RMSE). The validation stage showed that our model, based on conditional merging technique, performed very well in 11 out of 15 rainfall events (approximate 78%), with an MAE under 0.4 mm and RMSE under 0.7 mm.
On August 1, 2019, the atmospheric instability was very pronounced in the hydrographic basin related to the Călinești-Oaș Reservoir, the main phenomenon being the local rainstorms, of very high intensity. The successive radar images, observed in real time, predicted the outbreak of a hydrometeorological event with a strong impact in the catchment basin of the Huta Certeze hydrometric station, on Valea Rea river (the upper hydrographic basin of the Tur river, Oașului Mountains, Satu-Mare district). In a very short time of only 4 hours, a total of 132.5 mm precipitation was measured, which generated a flash flood with a single peak, exceeding the flooding stages, with a maximum discharge of 46.6 m 3 /s. Being an extreme hydrometeorological phenomenon, the question arises to verify whether it is possible to modeling a flash flood of an almost unprecedented magnitude. For modelling purpose MIKE HYDRO River -UHM (Unit Hydrograph) has been selected, being the most suitable for the unit hydrograph method, when the inputs are generated by a single storm event. A GIS based application; ArcMap was used to delimit the affected catchment area. The simulated discharge hydrographs were compared with the observed one at the Huta Certeze hydrometric station, which represent the closing point of the studied basin. The obtained results confirm the modeling's veracity. Therefor MIKE HYDRO River can be used for forecasting water flows to rivers or lakes, for estimating water resources, as well as for river basin management.
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