The territory of the Republic of Serbia is vulnerable to various natural disasters, among which forest fires stand out. In relation with climate changes, the number of forest fires in Serbia has been increasing from year to year. Protected natural areas are especially endangered by wildfires. For Nature Park Golija, as the second largest in Serbia, with an area of 75,183 ha, and with MaB Reserve Golija-Studenica on part of its territory (53,804 ha), more attention should be paid in terms of forest fire mitigation. GIS and multi-criteria decision analysis are indispensable when it comes to spatial analysis for the purpose of natural disaster risk management. Index-based and fuzzy AHP methods were used, together with TOPSIS method for forest fire susceptibility zonation. Very high and high forest fire susceptibility zone were recorded on 26.85% (Forest Fire Susceptibility Index) and 25.75% (fuzzy AHP). The additional support for forest fire prevention is realized through an additional Internet of Thing (IoT)-based sensor network that enables the continuous collection of local meteorological and environmental data, which enables low-cost and reliable real-time fire risk assessment and detection and the improved long-term and short-term forest fire susceptibility assessment. Obtained results can be applied for adequate forest fire risk management, improvement of the monitoring, and early warning systems in the Republic of Serbia, but are also important for relevant authorities at national, regional, and local level, which will be able to coordinate and intervene in a case of emergency events.

Snow avalanches are one of the most devastating natural hazards in the highlands that often cause human casualties and economic losses. The complex process of modeling terrain susceptibility requires the application of modern methods and software. The prediction of avalanches in this study is based on the use of geographic information systems (GIS), remote sensing, and multicriteria analysis—analytic hierarchy process (AHP) on the territory of the Šar Mountains (Serbia). Five indicators (lithological, geomorphological, hydrological, vegetation, and climatic) were processed, where 14 criteria were analyzed. The results showed that approximately 20% of the investigated area is highly susceptible to avalanches and that 24% of the area has a medium susceptibility. Based on the results, settlements where avalanche protection measures should be applied have been singled out. The obtained data can will help local self-governments, emergency management services, and mountaineering services to mitigate human and material losses from the snow avalanches. This is the first research in the Republic of Serbia that deals with GIS-AHP spatial modeling of snow avalanches, and methodology and criteria used in this study can be tested in other high mountainous regions.

The municipality of Štrpce (Southern Serbia) is an area located within Šar Mountain National Park, which is of great ecological importance. Due to the vicinity of settlements, it is necessary to analyze the terrain's susceptibility to natural hazards. The main goal of this research was to determine locations that are highly vulnerable at times of natural hazards (such as earthquakes, erosion, torrential flooding, snow avalanches, and forest fires). The first step in this research was to analyze seismic hazards for a 475 years return period (VII–VIII MCS for the observed area), which was possible by means of Geographic Information Systems. The second step was to determine the intensity of erosion and total sediment production using the Erosion Potential Model. The third step was related to the analysis of the potential of torrential floods using the Flash Flood Potential Index. The Avalanches Potential Index method was used as the fourth step. The fifth step included the analysis of a terrain susceptibility to the occurrence of forest fires. Following the five criteria analysis, weight coefficients were assigned to each of the analyzed parameters by using the Analytical Hierarchy Process (AHP), which provided results of the total susceptibility to natural hazards of the territory of Štrpce. Results indicated that over 45% of the municipality is highly or very highly susceptible to various natural hazards. This article represents a significant step toward a better understanding of natural hazards and it provides a unique knowledge basis for establishing the management and mitigation guidelines and measures, not only within the researched area but at regional and national levels as well.

The fluvial process is characterized by an intense meandering riverbed. The aim of this study was to perform a reconstruction of the lateral migration of a 15 km length of an active meandering river during the period 1930–2016. River morphological changes were analyzed and quantified from cadastral maps and aerial photographs as well as by geodetic survey and GIS. Hydrological characteristics and extreme hydrological events were evaluated in relation to bank erosion rate. The rate of bank erosion was markedly different from the long-term studied meanders, just like in the short-term period. During the 87 years of observation (from 1930 to 2016), the length of the Kolubara River was enlarged by 3.44 km. The average migration rate of the Kolubara River for monitored meanders in the period 1930–2010 was 1.9 m·year⁻¹, while in the period 2010–2016, the average migration rate was 3.3 m·year⁻¹. The rate of bank erosion was more intensive across the entire short-term period than during the longer period, and the maximum annual rate of bank erosion during the period 2010–2016 varied between 0.3 and 11.5 m. It is very likely that in the period from 2010, frequent discharge variations and rapid change of its extreme values caused more intensive bank erosion. These research results will be valuable for river channel management, engineering (soft and hard engineering), and planning purposes (predicting changes in river channel form) in the Kolubara River Basin.

One of the most vulnerable parts to natural hazards in Serbia is Kolubara river basin. In the past, during the period from 1929 to 2013, 121 torrential flood events in the Kolubara river basin were recorded which show that this territory is extremely vulnerable to the torrential floods. The extreme event which occurred in May 2014 causing the catastrophic material damages and casualties was the latest and historical flood. The analysis of natural conditions in the Kolubara basin uniformly showed that this area is predisposed to a greater number of torrential floods due to its geomorphological, hydrological and land use properties. Torrential floods are closely related to the intensity and spatial distribution of erosive processes in the upper part of the Kolubara basin. The estimation of soil erosion potential is generally achieved by Erosion Potential Model (EPM). For the purposes of determining the degree of torrential properties in various water streams in the Kolubara basin, the calculation of susceptibility to torrential floods was assessed by Flash Flood Potential Index (FFPI). More than half of the basin area (57.2%) is located within the category of very weak and weak erosion (Z_sr = 0.35), but the category of medium erosion is geospatially very common. Such a distribution of medium erosion category provides conditions for generating, i.e. production of sediment which would boost torrential properties of water streams. After the classification of the obtained FFPI values it was determined that 25% of the Kolubara basin is very susceptible to torrents and this data should be seriously taken into consideration. Based on the analyses, the best and most successful manner of defence is prevention which consists of the integrated river basin management system (integrated torrent control system) so that technical works in hydrographic networks of torrents and biological and biotechnical works on the slope of the basin would be the best solution. Permanent control of erosive and torrential processes in the river basin will be not only important for flood control but it can also protect the existing and future water reservoirs and retentions from siltation with erosion sediment which is of great significance to the water management, agriculture, energy sector, and the entire society.

The erosion potential model was applied to estimate the soil erosion status of rural settlements during the years 1971 and 2011. We used univariate and bivariate local Moran’s I indices to detect and visualize the spatial clustering of settlements with respect to changes in erosion intensity and agricultural land use, as well as their mutual spatial correlation. The study area was differentiated into four statistically significant clusters using the calculated bivariate local Moran’s I indices. The statistical analysis examined the two largest clusters, i.e., the high–high and low–low clusters, and the results of the research indicate that the first four principal components explained 70.50% and 73.47% of the total variance, respectively. In the high–high cluster, the low rates of erosion reduction (average Index Z = 98) in the most significant types of rural settlements were determined according to demographic indicators (i.e., the higher population vitality and population density, the smaller share of the old population and the lower average age of the population) and the large proportion of arable land and Neogene sediments. In the low–low cluster, high erosion reduction rates were detected (average index Z = 64). In this cluster, the more statistically significant influence of natural conditions in combination with demographic–agrarian processes (i.e., the larger share of the old population, the higher average age of the population, the lower vitality index and deagrarization) were decisive factors in changing erosion intensity.