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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 1
Nat. Hazards Earth Syst. Sci., 9, 241–250, 2009
https://doi.org/10.5194/nhess-9-241-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Mediterranean Storms (Plinius 2007)

Nat. Hazards Earth Syst. Sci., 9, 241–250, 2009
https://doi.org/10.5194/nhess-9-241-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

  26 Feb 2009

26 Feb 2009

Indices of precipitation extremes in Southern Portugal – a geostatistical approach

R. Durão1, M. J. Pereira1, A. C. Costa2, J. M. Côrte-Real3, and A. Soares1 R. Durão et al.
  • 1CERENA, Instituto Superior Técnico, Lisboa, Portugal
  • 2ISEGI, Universidade Nova de Lisboa, Lisboa, Portugal
  • 3ICAM, Universidade de Évora, Évora, Portugal

Abstract. Most of the actual studies and previews of future rainfall patterns, based on past observed records for Mediterranean climate areas, focus on the decline of the rainfall amounts over the years, and also on the increase of the frequency of heavy/intense rainfall events particularly in the winter season. These changes in heavy rainfall events may have severe implications and impacts on soil erosion resulting in increased soil degradation risks.

The objective of the present work is to evaluate the spatial distribution of extreme precipitation events in Southern Portugal, using a geostatistical approach to assess the relationships between spatial and temporal extreme rainfall patterns. The used dataset comprises a set of 105 stations' records of daily precipitation within the period 1960–1999. Two indices of extreme precipitation were selected to be computed based on the daily precipitation observation series: one representing the frequency of extremely heavy precipitation events (R30) and another one characterizing flood events (R5D).

The space-time patterns of the precipitation indices were evaluated and simulated using a geostatistical approach. Despite no significant temporal trends were detected on the calculated indices series, the space-time decadal patterns are becoming more continuous in the last two decades than the previous ones.

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