, 2007) predict a weak increase in SESA precipitation

over the 20th century as a consequence of anthropogenic climate forcing that could explain some of the observed wet trend in SESA. However, Vera et al. (2010) showed find more that evidence of observed decadal variability makes clear that the anthropogenic climate change signal at the regional level may be strongly modulated by natural climate variations. On the other hand, several studies have linked SESA precipitation in interannual time scales to the El Niño–Southern Oscillation (ENSO), with El Niño conditions showing increased precipitation (e.g., Paegle and Mo, 2002) and leading to increased streamflow in the rivers (e.g., Robertson and Mechoso, 1998). In this paper we consider an area in NEA characterized by homogeneity in relief, climate and natural resources, delimited by −26.25° < lat < −35.75°, −58.25° < lon < −64.75° (Fig. 1b). The study area is located within the Argentine Litoral and West and South borders of the LPB—according to the divisions

proposed by Caffera and Berbery (2006)—and covers a large selleck products portion of the Low Paraná sub-basin and important territories of the Salado River Basin (Fig. 1a and b). The water resources in these basins include a highly productive region where the main economic activities are cereal production and livestock. The Low Paraná River presents very low coasts and therefore, the very high discharges 6-phosphogluconolactonase cause severe floods (Coronel and Menéndez, 2006). The largest flood of the Paraná River in the 20th century occurred in 1983, when more than 100,000 people had to be evacuated and economic losses amounted to more than one billion dollars (Krepper and Zucarelli, 2010). Additionally, the Salado river—a tributary of the Paraná river—experienced the most catastrophic flood in April 2003, causing economic losses of approximately US$ 1000 million (ECLAC, 2003) and affecting nearly one-third of the population

of Santa Fe city (140,000 inhabitants). An analysis of precipitation characteristics is a critical component for the management of climate risk (Bordi et al., 2009). In the recent years, the SPI (McKee et al., 1993) has been widely used and highlighted for a number of advantages over other indices (Guttman, 1999 and Keyantash and Dracup, 2002). Thus, SPI has been accepted by the World Meteorological Organization (WMO) as the reference index for more effective drought monitoring and climate risk management (Hayes et al., 2011). Furthermore, SPI was designed to quantify the precipitation deficit/excess for multiple time scales, which reflect the impact of drought and wetness on the availability of different water resources. Shorter time scales (weeks to months) are used to characterize meteorological conditions, important to agricultural activities since soil moisture has a relative fast response to precipitation anomalies.