Consecutive Extreme Dry Days of the growing season in the Vojvodina region: Observations and Projections

Abstract

As a result of global climate change, the Vojvodina region in northern Serbia is witnessing more frequent extreme weather events. Furthermore, considering the existing trends and future climate change projections, a wide range of impacts are anticipated on the agricultural sector in Vojvodina. The Consecutive Dry Days (CDD) metric, commonly utilized in drought research, serves as an important indicator of drought severity by measuring the duration of dry spells. It is crucial to understand short-term droughts and their impact on agriculture and ecosystems. In this research, the occurrence and length of extreme CDDs during the growing season were studied for both historical (1950-2019) and future (2020-2100) periods in the Vojvodina region. Analyses of past and future occurrences of extreme CDD events were performed for 9 locations. This analysis utilized an ensemble of eight downscaled, bias-corrected regional climate models from the EURO-CORDEX project database, focusing on the RCP8.5 scenario to assess future CDD events. The analysis of CDD events was conducted using the Threshold Level Method on precipitation data, defining extreme CDDs as periods of at least 15 consecutive days without rain. The adapted threshold was chosen as it is more relevant for agriculture, considering that field crops may suffer from water stress after 15 days without rain or irrigation. The research examined various aspects of the stochastic process for CDDs, focusing on the distribution patterns of three key elements: distribution of the number of CDD events, distribution of the duration of CDDs, and distribution of the longest CDD events.To determine if extreme CDDs events act as independent and identically distributed random variables, run tests at a 5% significance level were conducted for all nine locations, utilizing both historical data and the chosen ensemble of eight regional climate models. These run tests confirmed the randomness hypothesis. Additionally, serial correlation coefficients for the series of extreme CDD events were computed, and a significance test at the 5% probability level indicated the independence of these CDDs, revealing no notable serial correlation within the data. The Poisson distribution was used to model the number of extreme CDD events, the exponential distribution function was used to model the distribution of the duration of CDDs, and the Gumbel distribution was selected to model the durations of the longest CDD events. The results indicate an increased likelihood of more frequent and severe droughts in the Vojvodina region in the future, compared to historical data. There is an expected rise in the probability of experiencing 3 to 6 dry periods in the growing season. Moreover, the lengths of the longest CDDs within a growing season are anticipated to extend, reaching up to 57 days for a 10-year return period and 83 days for a 100-year return period. This trend suggests a worsening in drought conditions, particularly in the eastern and northern areas of the Vojvodina region. These insights are valuable for predicting future agricultural drought scenarios, aiding decision-makers in adjusting agricultural practices to mitigate the adverse effects of climate change.