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Abstract: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.

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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.

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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.