Assessment and Monitoring of Droughts in Southeastern Europe: A Review - page 03

The evaluation of drought characteristics is further performed using a constant threshold (shown in Figure 5). It should be noted that, depending on the hydrologic series as well as the needed analyses, it is possible to apply a more complex threshold as a deterministic, stochastic or combined function (Radić and Mihajlović, 2008).

The basic characteristics of hydrologic time series for drought assessment (Figure 5) are then formed at a yearly level (Figure 6a). The following analyses are then performed on these series: probabilistic analysis, analysis of periodicity and trend analysis (Figure 6b).

 

Fig06
Figure 6: Time series (a) and methods for drought assessment (b).

 

The probabilistic analysis of drought uses time series of minimum discharge of different duration, as well as time series of duration and volume of deficit during the year. The first step is to define the empirical probability of said events, then evaluate the parameters of theoretical distribution functions. Lastly, the theoretical distribution function is selected to best fit the sample using goodness-of-fit tests (e.g. the Kolmogorov-Smirnov test). One theoretical distribution function often used to analyze low flows is the Weibull distribution (Koutsoyiannis, 2008).

The analysis of periodicity evaluates the mathematical model used to define long-term cyclical elements of drought. Time series of characteristic indicators of drought can be analysed using a discrete spectrum to identify the amplitudes of trigonometric waves in the low frequency domain (Stojković, 2015). It is also possible to use a continuous spectrum to define periodicity over all frequencies (Yevjevich, 1972), but without the possibility of modelling the evaluated periodicity.

Hydrologic processes are often exposed to both natural and anthropogenic nature, which can be manifested either gradually over time or abruptly. That is why when analyzing hydrological series, deterministic transitional components of series are often registered in one of two ways: either linear or nonlinear trend and "jumps". For trend analysis for time series of drought characteristics, such as duration and deficit volume, parametric and nonparametric tests can be applied (Helsel i Hirsch, 2002). Various trend analyses are based on the well-known Mann-Kendall trend test (Douglas et al, 2000), which is a nonparametric test based on sorting elements within a time series. This test can also be applied to a multi-temporal trend analysis (Stojković et al, 2014), which is an altrenative approach to trend analysis of subseries.

Conclusions

Droughts are a very complex natural hazard and can be characterized by multiple climatological and meteorological characteristics, therefore an interdisplinary approach is necessary to further the understanding of the relationships between these characteristics. Although many studies have already been done to assess droughts in Southeastern Europe, mostly on a country-to-country basis, there is still a need for understanding the relationship between climate indices and drought indices at a local scale. In order to reduce the impact of droughts, a risk management approach should be used to assess vulnerabilities and increase preparedness.

Remote sensing and GIS technologies can significantly contribute to different phases of drought management namely the preparedness phase where prediction and risk assessment are performed long before the event occurs, and Prevention phase where activities such as early warning, forecasting, monitoring can increase preparedness before and during an event.

Drought is a regional, transboundary phenomenon, and should therefore be treated from a regional perspective. Regional integration of drought monitoring and early warning should be improved, including development of national and regional frameworks, cooperation and application of legal and institutional instruments at a regional level.