**Acknowledgements**

*Drought - Detection and Solutions*

except over the NA river basins.

**5. Conclusions**

related variables.

behavior for both time scales.

events.

correlations also show that the SPEI-03 correlates well in general with the SFCEVP, showing significant correlations at the 95% confidence level for all river basins,

This chapter is devoted to analyzing spatiotemporal patterns of droughts over the IP, a region particularly vulnerable to this extreme event [7] for the period 1980–2014. To do this, a regional climate simulation using the WRF model was completed, obtaining thus high spatiotemporal resolution climate data.

Temperature and precipitation data from WRF were used to compute the SPEI at 3 and 12-month time scales with the purpose of analyzing different drought applications (e.g., agricultural and hydrological). This index has proved to be adequate to

Firstly, the regional performance of the SPEI was assessed. The most general evolution in droughts is consistent with other studies that allocated the main drought episodes occurred over the IP (e.g., [27]). The results evidenced that WRF appears as a promising tool for analyzing droughts since they provide a great number of climate variables at adequate spatial and temporal resolutions, which are unusually obtained from observations. In fact, climate data from regional simulations may be useful to determine where and when drought is occurring, providing valuable information to compute different drought indices using different drought-

These results also show that the SPEI-03 represents more frequent and shorter

On the other hand, the SPEI-12 presented longer drought episodes, showing, in general, more spread in its duration distributions, with the median values ranging from 5 to 17 months. However, in regard to the intensity, droughts presented similar

Concerning the existence of the trends in droughts along the analyzed period, the results indicate that, in general, an increase in at least one of the drought properties occurred over the period 2000–2014 with respect to the period 1980–1999 in

In the comparison between the SM and the SPEI-03, the results show that this variable presents a good agreement with the SPEI, which is an index based on a balance between water supply and potential demand at 3 months, which suggests

episodes, with the median duration and intensity of about 3–4 months and 1, respectively. In this regard, the largest events occurred over the southern IP, which is especially vulnerable due to its aridity conditions. In fact, this region is arid and then major damages may be produced under the occurrence of severe drought

analyze droughts in the context of global warming.

most of the river basins, more evident for the SPEI-03.

The hydrological droughts are represented in **Figure 7**. Here, the temporal evolution of the runoff, which was obtained by aggregated standardized anomalies at 12 months, was displayed, as well as the SPEI-12. As for the previous analysis, different periods with positive and negative anomalies were recorded in all river basins, reproducing wet and dry periods similar to the SPEI-12. In fact, the SPEI-12 reflects long-term precipitation patterns, being thus useful to determine streamflow and reservoir levels. For instance, a marked wet period clearly appeared during 2001 over the NA, the MS, the DU, the PB, and the TJ river basins in both the runoff and the SPEI-12 temporal series. In the same way, certain river basins presented marked negative standardized anomalies of runoff during 2005, which also showed important negative values of SPEI-12. As expected, r between the SPEI-12 and the runoff was really high showing values around 0.85, with the highest ones over the NA and the MS river basins (r values of 0.91).

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This study has been financed by the Spanish Ministry of Economy and Competitiveness, with additional support from the European Community fund (FEDER), project CGL2013-48539-R and CGL2017-89836-R. The WRF simulation was run in the ALHAMBRA supercomputer infrastructure (https://alhambra.ugr. es). The ERA-Interim data were obtained from ECMWF portal and the WRF model from NCAR.
