Caloiero T., Coscarelli R., Ferrari E., Sirangelo B., 2018, Seasonal and annual trend analysis of SPI in Calabria, XXXVI Convegno di Idraulica e Costruzioni Idrauliche, Ancona, 12-14/09/2018,
URL: http://www.cnr.it/prodotto/i/391729

Among the more adversely impacting climate events, drought phenomena play a significant role in socio-economic and health terms, even though their impact on populations depends on the vulnerable elements (Wilhite et al., 2000). The impacts can be particularly significant for areas already under stress and suffering from a water shortage due to a dry climate and a growing water demand, as in the case of the Mediterranean area (De Luis et al., 2000). Understanding of drought phenomena is paramount for an appropriate planning and management of water resources. Usually, drought severity is evaluated by means of drought indices since they facilitate communication of climate anomalies to diverse user audiences; they also allow scientists to assess quantitatively climate anomalies in terms of their intensity, duration, frequency, recurrence probability and spatial extent (Wilhite et al., 2000, Tsakiris et al., 2007). One of the most diffused indexes for analysing meteorological droughts at different time-scales is the Standardized Precipitation Index (SPI), which allows the investigation of different drought categories (McKee et al., 1993). Also due to its intrinsic probabilistic nature, the SPI can be reliably assumed for carrying out drought risk analysis (Guttmann, 1999; Cancelliere et al., 2007). Several authors focused on SPI trend (Bordi et al., 2009; Golian et al., 2015; Buttafuoco et al., 2015), mainly adopting non-parametric tests, which are better suited to deal with non-normally distributed hydrometeorology data than the parametric ones. Recently, ?en (2012) proposed the Innovative Trend Analysis (ITA) technique that allows a graphical trend evaluation of the low, medium, and high values in the data. This technique has been largely applied to the trend detection of several hydrological variables, among which temperature data (?en, 2014; Ay & Kisi, 2015), annual maximum rainfall series (Haktanir & Citakoglu, 2014), water quality parameters (Kisi & Ay, 2014), heat waves (Martínez-Austria et al., 2015), monthly pan evaporations (Kisi, 2015) and streamflow data (Tabari & Willems, 2015). In the present work, the trend behaviour of the seasonal droughts of Calabria (southern Italy) has been analysed by applying the SPI on 3- and 12-month time scale on a homogeneous database of 24 monthly rainfall series observed in the period 1951-2016.

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