Crops' exposure, sensitivity and adaptive capacity to drought occurrence

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

doi:https://doi.org/10.5194/nhess-19-2727-2019

Articles | Volume 19, issue 12

https://doi.org/10.5194/nhess-19-2727-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Hydroclimatic extremes and impacts at catchment to regional...

https://doi.org/10.5194/nhess-19-2727-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 12

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

Data sets

Global Patterns of Groundwater Table Depth, Science (https://glowasis.deltares.nl/thredds/catalog/opendap/opendap/Equilibrium_Water_Table/catalog.html) Y. Fan, H. Li, and G. Miguez-Macho https://doi.org/10.1126/science.1229881

Updated high-resolution grids of monthly climatic observations - The CRU TS3.10 Dataset (https://crudata.uea.ac.uk/cru/data/hrg/) I. Harris, P. D. Jones, T. J. Osborn, and D. Lister https://doi.org/10.1002/joc.3711

Estatísticas agrícolas: 2015 INE (Instituto Nacional de Estatística) https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_indicadores&indOcorrCod=0000018&contexto=bd&selTab=tab2

Estatísticas agrícolas: 2015 INE (Instituto Nacional de Estatística) https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_indicadores&indOcorrCod=0003006&contexto=bd&selTab=tab2

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Vegetation Health and Drought Products (VHDP) from NDE (ftp://ftp.star.nesdis.noaa.gov/pub/corp/scsb/wguo/data/Blended_VH_4km/geo_TIFF/) F. Kogan, W. Guo, H. Ding, and NOAA JPSS Program Office https://doi.org/10.7289/V58W3BCR

Short summary

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.