The ability to extract flood hazard settings in highly vulnerable areas like populated floodplains by using new computer algorithms and hydraulic modeling software is an important aspect of any flood mitigation efforts. In this framework, the 1D/2D hydraulic models, which were generated based on a Light Detection and Ranging (LiDAR) derivate Digital Elevation Model (DEM) and processed within Geographical Information Systems (GIS), can improve large-scale flood hazard maps accuracy. In this study, we developed the first flood vulnerability assessment for 1% (100-year) and 0.1% (1000-year) recurrence intervals within the Jijia floodplain (north-eastern Romania), based on 1D HEC-RAS hydraulic modeling and LiDAR derivate DEM with 0.5 m spatial resolution. The results were compared with official flood hazards maps developed for the same recurrence intervals by the hydrologists of National Administration “Romanian Waters” (NARW) based on MIKE SHE modeling software and a DEM with 2 m spatial resolutions. It was revealed that the 1D HEC-RAS provides a more realistic perspective about the possible flood threats within Jijia floodplain and improves the accuracy of the official flood hazard maps obtained according to Flood Directive 2007/60/EC.

Using hydraulic modeling techniques (e.g., one-dimensional/two-dimensional (1D/2D) hydraulic modeling, dam break scenarios) for extracting the flood settings is an important aspect of any action plan for dam failure (APDF) and flood mitigation strategy. For example, the flood hydraulic models and dam break scenario generated based on light detection and ranging (LiDAR)-derived digital elevation models (DEMs) and processed in the dedicated geographic information systems (GIS) and hydraulic modeling software (e.g., HEC-RAS—Hydrologic Engineering Center River Analysis System, developed by USACE HEC, Davis, CA, USA) can improve the flood hazard maps in case of potentially embankment dam failure. In this study, we develop a small-scale conceptual approach using 2D HEC-RAS software according to the three embankment dam break scenarios, LiDAR data (0.5 m spatial resolution), and 2D hydraulic modeling for the Başeu multi-reservoir system which belongs to the Başeu River (NE Romania) including R1—Cal Alb reservoir, R2—Movileni reservoirs, R3—Tătărăşeni reservoirs, R4—Negreni reservoirs, and R5—Hăneşti reservoirs. In order to test the flood control capacity of the Bașeu multi-reservoir system, the Cal Alb (R1) dam break scenario (piping failure) was taken into account. Three 2D stream flow modeling configurations based on R1 inflow rate with a 1% (100 year), 0.5% (500 year), and 0.1% (1000 year) recurrence interval and the water volume which can be accumulated with that specific inflow rate (1% = 10.19 × 10⁶ m³; 0.5% = 12.39 × 10⁶ m³; 0.1% = 17.35 × 10⁶ m³) were computed. The potential flood wave impact was achieved on the basis of different flood severity maps (e.g., flood extent, flood depth, flood velocity, flood hazard) generated for each recurrence interval scenario and highlighted within the built-up area of 27 settlements (S1–S27) located downstream of R1. The results showed that the multi-reservoir system of Bașeu River has an important role in flood mitigation and contributes to the APDF in the context of climate change and the intensification of hydrological hazard manifestation in northeastern Romania.

The exposure of rural communities to illegal waste dumping practices associated with the lack of or poor waste collection schemes prior to the closure of rural dumpsites under EU regulations and the role of collection efficiency afterward in reducing this critical environmental threat constitutes a key issue in rural Romania. The present study reveals huge amounts of household uncollected waste released into the natural environment outside the official statistics of rural dumpsites. Despite the expansion of waste collection coverage towards rural areas since 2010, the problem of illegal dumping practice is difficult to solve. The improvement of collection efficiency, better law enforcement, and surveillance of environmental authorities coupled with educational and environmental awareness are necessary steps to combat this bad practice. A circular economy paradigm must be enacted in rural regions through separate collection schemes and to improve cost-efficient alternatives, such as home composting, and traditional and creative reuse practices, particularly in less developed regions.

When relating to hazards such as earthquakes, a primary task of a resilience approach is to evaluate vulnerability in an integrative manner by taking into account the most relevant indicators. Focused on Iasi, one of the major Romanian cities which are exposed to the earthquakes originating in Vrancea area, this study aims to assess seismic vulnerability using a multi-criteria analysis of buildings infrastructure and social vulnerability. Several indicators are taken into account, such as physical (related to the characteristics of buildings and terrain) and social indicators (related to population and economic income), as well as the accessibility from/to emergency services/hospitals. The indicators were processed by standardization (Z score), processed and correlated using the principal components analysis (PCA) and integrated within an Analytical Hierarchy Process (AHP). By summing the weighted values of the standardized indicators, a (integrated) seismic vulnerability index was obtained. It is a pre-assessment of the seismic vulnerability in Iasi City and also a prerequisite for the identification of the necessary prevention measures to be taken in compliance with the identified spatial patterns of vulnerability as a part of a resilient approach.

In landslide susceptibility assessment, an important issue is the correct identification of significant contributing factors, which leads to the improvement of predictions regarding this type of geomorphologic processes. In the scientific literature, different weightings are assigned to these factors, but contain large variations. This study aims to identify the spatial variability and range of variation for the coefficients of landslide predictors in different geographical conditions. Four sectors of 15 km × 15 km (225 km2) were selected for analysis from representative regions in Romania in terms of spatial extent of landslides, situated both on the hilly areas (the Transylvanian Plateau and Moldavian Plateau) and lower mountain region (Subcarpathians). The following factors were taken into consideration: elevation, slope angle, slope height, terrain curvature (mean, plan and profile), distance from drainage network, slope aspect, land use, and lithology. For each sector, landslide inventory, digital elevation model and thematic layers of the mentioned predictors were achieved and integrated in a georeferenced environment. The logistic regression was applied separately for the four study sectors as the statistical method for assessing terrain landsliding susceptibility. Maps of landslide susceptibility were produced, the values of which were classified by using the natural breaks method (Jenks). The accuracy of the logistic regression outcomes was evaluated using the ROC (receiver operating characteristic) curve and AUC (area under the curve) parameter, which show values between 0.852 and 0.922 for training samples, and between 0.851 and 0.940 for validation samples. The values of coefficients are generally confined within the limits specified by the scientific literature. In each sector, landslide susceptibility is essentially related to some specific predictors, such as the slope angle, land use, slope height, and lithology. The study points out that the coefficients assigned to the landslide predictors through logistic regression are capable to reveal some important characteristics in landslide manifestation. The study also shows that the logistic regression could be an alternative method to the current Romanian methodology for landslide susceptibility and hazard mapping.