Articles | Volume 19, issue 12
https://doi.org/10.5194/nhess-19-2727-2019
https://doi.org/10.5194/nhess-19-2727-2019
Research article
 | 
04 Dec 2019
Research article |  | 04 Dec 2019

Crops' exposure, sensitivity and adaptive capacity to drought occurrence

Catarina Alonso, Celia M. Gouveia, Ana Russo, and Patrícia Páscoa

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Abson, D. J., Dougill, A. J., and Stringer, L. C.: Using Principal Component Analysis for information-rich socio-ecological vulnerability mapping in Southern Africa, Appl. Geogr., 35, 515–524, https://doi.org/10.1016/j.apgeog.2012.08.004, 2012. 
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Andrade, C. and Belo-Pereira, M.: Assessment of droughts in the Iberian Peninsula using the WASP-Index, Atmos. Sci. Lett., 16, 208–218, https://doi.org/10.1002/asl2.542, 2015. 
Anselin, L. and Getis, A.: Spatial statistical analysis and geographic information systems, in Geographic Information Systems, Spatial Modelling and Policy Evaluation, Springer Berlin Heidelberg, Berlin, Heidelberg, Germany, 35–49, 1993. 
Beguería, S, Vicente-Serrano, S. M., Reig, F., and Latorre, B.: Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring, Int. J. Climatol., 34, 3001–3023, https://doi.org/10.1002/joc.3887, 2014. 
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A vulnerability assessment method is proposed to identify the most vulnerable regions over Portugal. Two methods were compared, namely a subjective categorical method and an automatic method, based on drought indicators, vegetation indices and soil variables. Both methods present similar results, and both identify Minho (Alentejo) as having low (extreme) vulnerability. The automatic method has advantages, as it is fully statistical and presents results without prior knowledge of the region.
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