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Land use change in all river basins leads to changes in hydrologic response, soil erosion, and sediment dynamics characteristics. Those changes are often viewed as the main cause of accelerated erosion rates. We studied the impact of land use changes on soil erosion processes in one of the watersheds in Montenegro: the Miocki Potok, using this watershed as a pilot river basin for this area. We simulated responses of soil erosion processes by using a process-oriented soil erosion Intensity of Erosion and Outflow (IntErO) model, with different settings of land use for the years 1970, 1980, 1990, 2000, 2010, and 2020. The model provides fast, effective, and affordable insight into the effects of land use change on soil erosion processes. Testing of the applied procedures was important for the further establishment of watershed management methodologies at the national level, for the other 300 river basins of Montenegro. For the current state of land use, calculated peak discharge for the Miocki Potok was 364 m3 s−1 (2020)–372 m3 s−1 (1970) for the incidence of 100 years, and there is a possibility for large flood waves to appear in the studied basin. Real soil losses, Gyear, were calculated at 13680 m3 year−1 (2020) and specific 333 m3 km−2 year−1 (2020). A Z coefficient value of 0.439 (2020) indicated that the river basin belongs to destruction category III. The strength of the erosion process was medium, and according to the erosion type, it was mixed erosion. According to our analysis, the land use changes in the last 50 years influenced a decrease in the soil erosion intensity for 14% in the Miocki Potok River Basin. Further studies should be focused on the detailed analysis of the land use changes trends with the other river basins at the national level, closely following responses of soil erosion to the changed land use structure, and effects of plant-and-soil interaction on soil erosion and sediment dynamics.

This paper proposes a procedure for decision-making regarding the extent to which a certain geographical region is affected by drought. Professional circles generally recognize the Standardized Precipitation Index (SPI) as a good indicator of a drought event. However, as a result of varying precipitation levels due to various local geographical, climatic, vegetational and other factors, this indicator is determined based on precipitation measurements and different meteorological centres within the same administrative region often generate different SPI values, even when the geographical distance between them is small. During a dry period, various local authorities, ministries of agriculture or governments have to make important decisions about, for example, declaring disasters, subsidizing farmers for certain crops, or providing financial aid to agricultural producers, based on voluminous and diverse data about local precipitation, the yield of various crops, or the condition of the soil. This paper proposes an automated methodology for such decision-making, which can be used as a support tool by decision-makers. The methodology is based on the SPI and statistical pattern recognition methods (dimension reduction and classifier design based on the desired output). The entire procedure is illustrated using Vojvodina, a region in Serbia in the southern portion of the Pannonian Plain, as a case study. The proposed algorithm is not subject to any constraints with regard to geographical locations of regions, their surface areas, or inter-relationships.

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