The Hydrologic Modeling System (HEC-HMS), designed to accurately simulate precipitation-runoff processes in various watershed types, was employed in our study to establish a model for a particular watershed. Consequently, we planned to create a rainfall-runoff model to investigate the specific characteristics of floods, assess some pre-diction models, and issue assumptions about their viability, which could be beneficial in establishing flood warning systems. The model was developed using daily precipitation data collected from different rain gauge stations in the Gilort watershed, located in southern Romania. The study employed the HEC-GeoHMS terrain processing tool, utilizing a digital elevation design to build a hydrological model. The statistical indicators used to evaluate the runoff mechanisms, specifically regression, coefficient of determination, correlation coefficient, index of agreement (Willmott index), and the root mean squared error (RMSE), showed a strong relationship between the simulated and recorded flow of the watershed. The leaking model was assessed using other statistical parameters, including the deviation of runoff volumes (Dv = 6.40%), Nash−Sutcliffe efficiency (NSE = 0.908), and Kling-Gupta efficiency (KGE = 0.901). These parameters confirmed that the simulated data closely matched the observed data, indicating an effective association, and were considered reliable indicators of the model’s goodness of fit, ensuring its reliability and efficacy.

This study presents an integrated surveying methodology for efficient and accurate cadastral documentation, combining UAV photogrammetry, SLAM-based terrestrial and aerial scanning, and conventional geodetic measurements. Designed to be scalable across various cadastral and planning contexts, the workflow was tested in Charlottenburg, Romania’s only circular heritage village. The approach addresses challenges in built environments where traditional total station or GNSS techniques face limitations due to obstructed visibility and complex architectural geometries. The SLAM system was initially deployed in mobile scanning mode using a backpack configuration for ground-level data acquisition, and was later mounted on a UAV to capture building sides and areas inaccessible from the main road. The results demonstrate that the integration of aerial and terrestrial data acquisition enables precise building footprint extraction, with a reported RMSE of 0.109 m between the extracted contours and ground-truth total station measurements. The final cadastral outputs are fully compatible with GIS and CAD systems, supporting efficient land registration, urban planning, and historical site documentation. The findings highlight the method’s applicability for modernizing cadastral workflows, particularly in dense or irregularly structured areas, offering a practical, accurate, and time-saving solution adaptable to both national and international land administration needs. Beyond the combination of known technologies, the innovation lies in the practical integration of terrestrial and aerial SLAM (dual SLAM) with RTK UAV workflows under real-world constraints, offering a field-validated solution for complex cadastral scenarios where traditional methods are limited.

Juglans regia L. is an edible fruit tree cultivated worldwide for its fruits and wood and as an urban tree. Globally, there is growing concern for preserving the genetic diversity of trees with high economic and ecological value. This study investigates the genetic diversity of J. regia in urban landscapes and assesses the quality of its walnut kernels as a local food product. An inventory of 150 trees from five populations in public green spaces in Lugoj, Caransebeș and Jupa, as well as two semi-natural hilly ecosystems in the Banat Region, was conducted. Molecular analyses showed that Directed Amplification of Minisatellite-region DNA (DAMD) markers were more effective than Start Codon Targeted (SCoT) markers, with a higher average polymorphism of 56.26%, compared to 49.44%. DAMD07 achieved 100% polymorphism and DAMD05 showed a strong balance between P.I.C. (0.35) and polymorphism (54.54%). Chemical analysis revealed the following contents in walnut kernels: protein (12.81% to 16.80%), lipids (60.39% to 69.08%), total polyphenols (5484.66 to 10,788.4 mg GAE/kg), copper (3.655 to 8.532 mg/kg), manganese (14.408 to 28.618 mg/kg), zinc (19.813 to 46.583 mg/kg), lead (1.204 to 2.27 mg/kg) and cadmium (0.03451 to 0.08065 mg/kg). These findings are critical for conservation efforts, urban forestry management and ensuring the quality and safety of walnut products derived from J. regia.

The rehabilitation of mine waste dumps is a critical environmental challenge, particularly in areas like Uricani, Romania, where such sites are often characterized by hazardous conditions and poor ecological recovery. This study addresses the need for efficient, low-cost solutions for land reclamation by employing UAV photogrammetry and GIS spatial analysis to assess the potential for afforestation with Robinia pseudoacacia L., a species known for its soil stabilization and ecological benefits. Using UAV technology, high-resolution digital terrain models and orthophotos were generated, with an RMSE of 0.086 m, demonstrating the accuracy and efficiency of this method for large-scale landscape initiatives. GIS spatial analysis was performed to create six key terrain maps and four pedoclimatic factor maps, essential for evaluating the site’s suitability for ecological restoration. The pilot afforestation project, which involved planting R. pseudoacacia, achieved a 75% survival rate after four years, suggesting that the species can thrive under the site’s conditions. The landscape design proposal incorporates recreational spaces aimed at benefiting the local community and attracting tourism, thereby contributing to the area’s economic and cultural revitalization. The interdisciplinary integration of UAV surveying, GIS, and landscape design highlights the cost-effectiveness and interdisciplinary nature of this approach, offering a sustainable model for mine waste dump reclamation and future ecological restoration projects.

Coal mining leaves behind extensive tailing dumps that pose long-term ecological and soil degradation challenges. This study evaluates the restoration potential of vegetation on coal mine tailings in the Jiu Valley, Romania, focusing on soil nutrient dynamics and the heavy metal distribution. Field sampling was conducted across three vegetation types—unvegetated (UV), herbaceous (HV), and arboreal (AV, Robinia pseudoacacia)—at two intervals: three and six years post-plantation. Soil samples were analyzed for their pH, organic carbon, macronutrients, micronutrients, and heavy metals using standardized spectrometric and titrimetric methods. Between 2021 and 2024, AV plots showed a 9.5% increase in total nitrogen and a 5.2% rise in organic carbon, alongside a 6.9% reduction in soil pH. HV plots exhibited a 10.6% increase in magnesium availability and a 2.8% decrease in copper concentrations, indicating active nutrient cycling. In contrast, UV soils retained 68% higher total potassium and 24% more zinc than vegetated plots, likely due to limited biological uptake. Lead concentrations remained below the EU threshold of 60 mg kg⁻¹, while nickel levels exceeded recommended limits across all variants, peaking at 76.08 mg kg⁻¹. The vegetation type significantly influenced nutrient mobilization and metal stabilization, with arboreal cover demonstrating the most consistent ameliorative effects. These findings underscore the role of targeted revegetation—particularly with Robinia pseudoacacia—in improving soil quality and mitigating ecological risks in post-mining landscapes.

Peri-urban areas in Eastern Europe are undergoing rapid land transformation driven by suburban housing expansion and infrastructure development, yet the processes through which vegetation is progressively degraded and built-up areas intensify remain insufficiently documented. This study analyses vegetation loss and urban expansion in the peri-urban belt of Timișoara, Western Romania, between 2020 and 2025 using Sentinel-2 multispectral imagery, two key spectral indices (NDVI and NDBI), and a Random Forest (RF) classifier. The results reveal a gradual, multi-stage transformation trajectory, where dense vegetation transitions first into sparse vegetation and bare soil before consolidating into built-up surfaces, rather than being replaced abruptly. Substantial vegetation decline is accompanied by notable increases in built-up land, with strong spatial differences between communes depending on development pressure. The integration of RF classification with spectral index analysis allows these transitions to be validated and interpreted more reliably, helping distinguish structural suburbanisation from short-term spectral variability. Overall, the study demonstrates the value of combining NDVI, NDBI and AI-supported land-cover classification to capture nuanced peri-urban transformation dynamics and provides actionable insights for spatial planning and sustainable land management in rapidly growing metropolitan regions.