Artan Hysa

Urban watercourses are vital natural elements within cities that can provide multiple ecosystem services to society. However, rivers are under continuous urbanization pressures in developing urban areas like the post-socialist countries. We focus on the Western Balkans (WB) countries to assess the relationship between the urban rivers and the respective metropolitan capital areas. First, we analyze the land use and land cover (LULC) along the respective watercourse at five buffer distances. Our work relies on Urban Atlas data acquired from the European Environment Agency. According to our results the natural land surfaces share on the waterfronts range between 89% along Lana River (Tirana) and 22% along Miljacka River (Sarajevo). The green surfaces share along the Moraca River (Podgorica) and Vardar River (Skopje) are more constant along five buffer distances. We report the results of each case in detail and compare among the selected five developing European urban centers with respect to their unique socio-political background. Our findings highlight the importance of natural and semi-natural surfaces presence along the urban rivers in support of sustainable decision-making at multiple spatial and jurisdiction levels in the WB, which is a hotspot of political, economic, and urban transformation triggered by the EU membership aspirations.

In light of population growth and climate change, groundwater is one of the most important water resources globally. Groundwater is crucial for sustaining many vital sectors in Syria, including industrial and agricultural sectors. However, groundwater exploitation has significantly escalated to meet different water needs especially in the post-war period and the earthquake disaster. Therefore, the goal was this study delineation of the groundwater potential zones (GPZs) by integrating the analytic hierarchy process (AHP) method in a geographic information systems (GIS) within the AlAlqerdaha river basin in western Syria. In this study, ten criteria were used to map the spatial distribution of GPZs, including slope, geomorphology, drainage density, land use/land cover (LU/LC), lineament density, lithology, rainfall, soil, curvature and topographic wetness index (TWI). GPZs map was validated by using the location of 74 wells and the Receiver Operating Characteristic Curve (ROC). The findings suggest that the study area is divided into five GPZs: very low, 21.39 km² (10.87%); low, 52.45 km² (26.65%); moderate, 65.64 km² (33.35%); high, 40.45 km² (20.55%) and very high, 16.90 km² (8.58%). High and very high zones mainly corresponded to the western regions of the study area. The conducted spatial modeling indicated that the AHP-based GPZs map showed a remarkably acceptable correlation with wells locations (AUC = 87.7%, n = 74), demonstrating the precision of the AHP–GIS as a rating method. The results of this study provide objective and constructive outputs that can help decision-makers to optimally manage groundwater resources in the post-war phase in Syria.

Purpose: Particle size distribution (PSD) assessment, which affects all physical, chemical, biological, mineralogical, and geological properties of soil, is crucial for maintaining soil sustainability. It plays a vital role in ensuring appropriate land use, fertilizer management, crop selection, and conservation practices, especially in fragile soils such as those of the North-Western Himalayas. Materials and methods: In this study, the performance of eleven mathematical and three Machine Learning (ML) models used in the past was compared to investigate PSD modeling of different soils from the North-Western Himalayan region, considering that an appropriate model must fit all PSD data. Results and discussion: Our study focuses on the significance of evaluating the goodness of fit in particle size distribution modeling using the coefficient of determination (R²_adj = 0.79 to 0.45), the Akaike information criterion (AIC = 67 to 184), and the root mean square error (RMSE = 0.01 to 0.09). The Fredlund, Weibull, and Rosin Rammler models exhibited the best fit for all samples, while the performance of the Gompertz, S-Curve, and Van Genutchen models was poor. Of the three ML models tested, the Random Forest model performed the best (R² = 0.99), and the SVM model was the lowest (R² = 0.95). Thus, the PSD of the soil can be best predicted by ML approaches, especially by the Random Forest model. Conclusion: The Fredlund model exhibited the best fit among mathematical models while random forest performed best among the machine learning models. As the number of parameters in the model increased better was the accuracy.

Ecosystem services (ES) are essential to sustainable development at multiple spatial scales. Monitoring ES potential (ESP) at the metropolitan level is imperative to sustainable cities. We developed a procedure for long-term monitoring of metropolitan ESP dynamics, utilizing open-source land use land cover (LULC) data and the expert matrix method. We compared the ESP results of 38 European Capital Metropolitan Areas (ECMA) regarding biodiversity integrity, drinking water provision, flood protection, air quality, water purification, and recreation & tourism. Our results show significant declines in ESP across ECMA due to LULC alteration between 2006, 2012, and 2018. We found that ECMA in post-socialist European countries like Poland (Warszawa) have experienced high rates of land use transformation with a remarkable impact on ESP. Surprisingly, we found that Fennoscandinan ECMA, like Helsinki, Stockholm, and Oslo which lead the cumulative ESP ranking, faced the ESP reduction of the highest impact in recent years. The correlation analysis of ESP dynamics to urban expansion and population growth rates suggests that inattentive urbanization processes impact ESP more than population growth. We unveil the implications of our results to the EU and global level agendas like the European Nature Conservation Law and the Sustainable Development Goals.

The port of Tangier Med is essential due to its strategic location, as it is an important trading center linking Europe, North America, and Africa. However, the increased rates of downstream sediment transportation put pressure on the sustainable future of the port. Thus, assessing the existing erosion rates and future improvement scenarios is imperative for planning sustainable management at the catchment level. We utilize the Erosion Potential Model (EPM) combined with the Intensity of Erosion and Outflow (IntErO) algorithm to assess the erosion and outflow intensity and to distinguish the sediment-producing areas in the R’mel watershed. The port’s proximity at the bottom of the slope opposite the R’mel Dam is relevant in this context. Initial results show an average erosion rate of 13 t/ha/year. Quarry operations were identified as the primary sediment source, as indicated by the factors contributing to erosion. The qualitative PAP/RAC (Priority Actions Program/Regional Activity Center) model was used to assess the development trends in the watershed, confirming a clear tendency toward irreversible degradation in the quarry areas. Considering that the mined carbonate lithology represents 23.77% of the total area of the catchment, the situation in the region could deteriorate if quarry operations continue. The simulation of quarry rehabilitation scenarios through land use and land cover change (LULC) with IntErO shows that reforestation of quarries can significantly reduce erosion rates (4.78 t/ha/year) compared to their conversion to agricultural land. This study underlines the effectiveness of IntErO, based on the EPM model, in quickly and effectively mapping and quantifying water erosion.