Gheorghe Șerban

The present study evaluates selected morphometric characteristics of 39 direct tributaries of the Buzău River (area of 4112 km²) to prioritize development actions in these sub-watersheds, which are distributed in three geographical regions within the full Buzău River watershed: the Carpathian, Subcarpathian, and plains regions. By combining a variable number of morphometric parameters, using various mathematical models, we can evaluate the state of balance or imbalance in a watershed and identify sub-watersheds vulnerable to natural processes. Prioritization was achieved using composite (Cp) values by comparing two scenarios. In the first scenario, 11 derived morphometric parameters were used, and in the second scenario, another 7 parameters were added. The obtained values were grouped into five classes (very high, high, medium, low, and very low). Due to the heterogeneity of relief units among geographical regions, there are classification differences for sub-watersheds among those regions. Watersheds classed as very high priority for intervention actions are located in the Carpathian (SW1, SW2, SW15, SW16) and Subcarpathian areas (SW24, SW30), which are characterized by high relief energy and pronounced slope instability, which leads to an increase in the risk of flooding and land degradation. For comparison, all sub-watersheds in the plains region, are classified as very low or low priority. Since the arithmetic mean is sensitive to extreme values, its use in the calculation of composite (Cp) values causes the values to be “eclipsed” and the sub-watersheds to be placed in different prioritization classes (SW18 and SW34), depending on the analyzed scenario, due to the large number of parameters and classified sub-watersheds.

The aim of this study is to model a rapid maximum runoff, response to a calculated rain with a probability of occurrence of 1% for several case studies within the Northwest Region of Romania, studied through NWPEAT project. The purpose of the study is focused also to identify the effect of raising ecological dams made of local materials in modifying the maximum torrential runoff at the outlet area from the peatlands sites. The methodology was applied to representative case studies, which revealed different/diversified conditions, both from the climatic, morphological, pedological, land cover or hydrological points of view. The first stage of the methodology focused on evaluating the inventory of the studied sites, the peatlands catchment features, their spatial analysis using morphological units and within the water balance, the analysis of runoff and aridity coefficients, etc. The modeling of the rain-runoff process was applied for two scenarios for each site, involving the presence or absence of the ecological dam. The results are quite dispersed from one case to another. Thus, we noticed a reduction in the maximum runoff of 70% in the case of the Mlaștina de la Iaz peatland, 40% in the case of the Lacul Manta peatland and only 8% in the case of the Ic Ponor peatland site. The difference between the three cases is made by the different patterns of some natural factors, among which are the peatland area, catchment area, shape of the basin and the slope, the degree of coverage with trees or less developed vegetation, the different layout of the sites compared to the flow directions of water vectors on the slope, etc.

The hydrophilic vegetation from reservoir deltas sustains rapid expansions in surface and important increases in vegetal mass against a background of a significant influx of alluvium and nutrients from watercourses. It contributes to reservoir water quality degradation and reservoir silting due to organic residues. In this paper, we propose an evaluation method of two-dimensional and three-dimensional parameters (surfaces and volumes of vegetation), using the combined photogrammetric techniques from the UAS category. Raster and vector data—high-resolution orthophotoplan (2D), point cloud (pseudo-LIDAR) (3D), points that defined the topographic surface (DTM—Digital Terrain Model (3D) and DSM—Digital Surface Model (3D))—were the basis for the realization of grid products (a DTM and DSM, respectively). After the successive completion of the operations within the adopted workflow (data acquisition, processing, post-processing, and their integration into GIS), after the grid analysis, the two proposed variables (topics) of this research, respectively, the surface of vegetation and its volume, resulted. The data acquisition area (deriving grids with a centimeter resolution) under the conditions of some areas being inaccessible using classical topometric or bathymetric means (low depth, the presence of organic mud and aquatic vegetation, etc.) has an important role in the reservoirs’ depth dynamics and reservoir usage. After performing the calculations in the abovementioned direction, we arrived at results of practical and scientific interest: Cut Volume = 196,000.3 m³, Cut 2D Surface Area = 63,549 m², Fill Volume = 16.59998 m³, Fill 2D Surface Area = 879.43 m², Total Volume Between Surfaces = 196,016.9 m³. We specify that this approach does not aim to study the vegetation’s diversity but to determine its dimensional components (surface and volume), whose organic residues participate in mitigating the reservoir functions (water supply, hydropower production, flash flood attenuation capacity, etc.).

The NRCS-CN (Natural Resources Conservation Service curve number) method, developed by the USDA (U.S. Department of Agriculture) is among the most widely used for the estimation of surface runoff from watersheds. Ever since its introduction in the 1950s, although it has been used to a great extent by engineers and hydrologists, the applicability of the original procedure used to determine its main parameter, the curve number (CN), to various regions with diverse environmental conditions, is still subject to many uncertainties and debates. This study presents a comparative analysis of different methods applied to determine curve numbers from local data in four watersheds located in the central part of Romania, within the mountain region surrounding the Brașov Depression. The CN values were not only computed using rainfall–runoff records from 1991 to 2020, but also determined from the standard NRCS tables documented in the National Engineering Handbook part 630 (NEH-630), for comparison purposes. Thus, a total of 187 rainfall–runoff data records from the study watersheds and five different methods were used to assess the accuracy of various procedures for determining the CN values, namely: tabulated CN (CN values selected from NRCS tables, TAB), asymptotic fitting (AF) of both natural and ordered data, median CN (MD), geometric mean CN (GM) and the arithmetic mean CN (AM) methods. The applicability of the aforementioned methods was investigated both for the original fixed initial abstraction ratio λ = 0.2 and its adjustment to λ = 0.05. Relatively similar results were found for the curve number-based runoff estimates related to the field data analysis methods, yet slightly better when the λ was reduced to 0.05. A high overall performance in estimating surface runoff was achieved by most CN-based methods, with the exception of the asymptotic fitting of natural data and the tabulated CN method, with the latter yielding the lowest results in the study area.

In recent years, the frequency of flooding has increased due to population growth and climate change worldwide

Groundwater, which is the main source of water for human consumption in many rural areas, has its quality determined by the complex interaction of environmental factors and anthropogenic activities. The present study evaluated the quality of shallow groundwater (1 to 25 m depth) in the rural area of the Târgovişte Plain, a densely populated area (200 inhabitants/km²) using 80 water samples collected from public wells. In order to explain the spatial distribution of the concentrations of the 19 physicochemical parameters considered (including heavy metals), the evaluation of groundwater quality for human consumption and potential impact on human health was conducted using the Water Quality Index (WQI), Integrated Weight Water Quality Index (IwWQI), Total Hazard Index (THI), and cumulative carcinogenic risk (CCR). For the WQI/IwWQI the comparative analysis of the two indices showed that for the WQI, it is important to select an optimal set of parameters, because use of a large number of physicochemical parameters can eclipse the values that exceed WHO guideline limits. In contrast, the use of entropy in the calculation of the IwWQI did not lead to eclipsing of exceedance, no matter the number of parameters used. Areas with poor and very poor groundwater quality according to the WQI/IwWQI overlapped, with a moderate risk to human health (THI > 1) for noncarcinogenic contaminants and also a risk of developing cancer according to the CCR average value (1.15 × 10⁻²). The health of 43% of the rural population in the Târgovişte Plain can be affected if they drink contaminated groundwater, and it is estimated that about 600 people can develop cancer during their lifetime. If the risk of developing cancer is reduced only in the rural population that does not have access to a water source from a centralized and verified network, the results suggest that 385 people (1.15%) can develop cancer as a result of consuming groundwater contaminated with heavy metals based on the average value of CCR. This value is lower than the general mortality rate in areas with high CCR and below the average number of cancer patients in Romania (2.65%). The quality of groundwater and the risk of developing diseases and cancer due to water consumption is directly proportional to the intensity of agricultural land use and inversely proportional to the depth of the groundwater layer, the distance from the main hydrographic network and the reservoirs, and the distance from the main city, Târgovişte. The complex and integrated analysis of groundwater quality using quality indices and indicators of health risk for the population, validated by hot-spot analysis and compared to the mortality rate, is an approach with practical applicability. This integrated approach allows public authorities, policymakers, and health services to implement an efficient monitoring program and optimize anthropogenic activities in order to prevent groundwater contamination and finally improve the quality of life for the residents in the area of this study.