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The paper explores the occurrence of minimal precipitation extremes at specific meteorological stations in the southeastern region of Serbia. With climate change leading to increased instances of droughts, these natural phenomena have garnered heightened interest due to their negative impacts on society, environment, and the economy. Employing the SPI-12 index in the southeastern part of Serbia from 1946 to 2021, the study sheds light on the vulnerability of this natural phenomenon in the observed stations. Understanding historical manifestation of these events helps water resource managers, farmers and policymakers manage these risks in the southeastern region of Serbia. [ABSTRACT FROM AUTHOR]

In February 1963, a huge landslide (ca. 1,950,000 m3) blocked the Visočica River and, thus, formed Zavoj Lake. The primary objective of this research was to investigate the importance of snowmelt in relation to landslide occurrence and to define the critical climatic conditions that may trigger massive winter landslides. We used monthly precipitation and average monthly maximum temperature data from meteorological and precipitation stations in the Visočica River basin (Dojkinci) and in the immediate proximity of Lake Zavoj (Pirot, Dimitrovgrad and Topli Do) as data inputs to the Snow-Melt Landslide (SML) index. It considers the summed monthly precipitation for previous months that continuously have an average maximum temperature below 0 °C. According to this method, the event at Zavoj Lake stands out among all other precipitation and snowmelt values for the past 72 years. After applying the SML index, all stations showed values of >300 mm for February 1963, which we consider as the threshold value for potential landslides appearance. In addition to meteorological data, we applied the SML index to data from the Coordinated Regional Downscaling Experiment (CORDEX) regional climate model outputs for the region from 2022 to 2100. As expected, climate change will have influenced the temperature values, especially during the winter. Conversely, the study area is experiencing drastic changes in land use caused by depopulation, leading to a reduced risk of winter landslides in the Visočica basin. We suggest that future climatic conditions in the area will make it more likely to experience extreme summer precipitation events, which might trigger large landslides. The SML method can be implemented for all landscapes that experience snowy winters, providing information in a timely manner so that local residents can react properly when the probability of landslide occurrence rises. The SML index, grounded in essential meteorological principles, provides a tailor-made, data-driven methodology applicable across varied geographical settings. Its utility extends to mitigating hydro-meteorological hazards on scales ranging from local to national scales, offering diverse and effective early warning solutions. [ABSTRACT FROM AUTHOR]

Considering recent weather events in Serbia (especially the floods in 2014), a need has arisen for research that would help in identifying extreme weather phenomena. Therefore, the aim of this paper is to determine the thresholds above which intense precipitation can be considered as extreme precipitation events in Serbia. In this study, we determined the frequency of precipitation occurring at an intensity above the threshold of an extreme phenomenon (1961–2015), as well as the frequency of precipitation occurring at or above the absolute daily maximum in the reference period (1961–1990). The study sample included daily rainfall observations from 28 stations from the national meteorological network in Serbia. Applying a decile method, all the stations recording precipitation above the threshold of dangerous phenomena on the same day are classified into the corresponding decile. The threshold value was determined as the average value of the extreme annual precipitation in the analyzed period. The cases that are due to the high prevalence listed in the last decile are considered extreme. The results showed that the critical number of observation points above which an event is considered extreme precipitation event is 6.21, and a warning of the danger could be ensured only in the case of neighboring stations in the network. The threshold of extreme precipitation events for the individual stations ranges up to 130 mm. The obtained results might be used to mitigate the effects of extreme precipitation events in Serbia in the future. [ABSTRACT FROM AUTHOR]