Probabilistic forecasting of drought class transitions in Sicily (Italy) using Standardized Precipitation Index and North Atlantic Oscillation Index

Probabilistic forecasting of drought class transitions in Sicily (Italy) using Standardized... 1 Introduction</h5> It is largely recognized that an effective mitigation of the most adverse drought impacts is possible by capitalizing on the usually significant delay between drought inception (i.e. meteorological drought) and the moment when its consequences are perceived by the water supply systems and the end-users (i.e. socio-economic impacts of drought). To this end, a drought monitoring and forecasting system, able to promptly warn against an incipient phenomenon and to follow its evolution in space and time, represents the prerequisite for a successful mitigation strategy ( Rossi, 2003 ).</P>Many statistical and non statistical techniques have been proposed to forecast droughts ( Bonaccorso et al., 2012 and references therein). Regardless of the specific methodology, a distinction can be made with reference to the objective of the forecast. On the one hand, the interest may lie in forecasting future values of the hydrometeorological variable or drought index under investigation. On the other hand, the objective may lie in determining transition probabilities from a given current drought class (expressed in terms of a drought severity variable or index) to another one in the future.</P>Several forecasting techniques have been proposed to assess the probable evolution of drought related hydrometeorological variables or http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Hydrology Elsevier

Probabilistic forecasting of drought class transitions in Sicily (Italy) using Standardized Precipitation Index and North Atlantic Oscillation Index

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Publisher
Elsevier
Copyright
Copyright © 2015 Elsevier B.V.
ISSN
0022-1694
eISSN
1879-2707
D.O.I.
10.1016/j.jhydrol.2015.01.070
Publisher site
See Article on Publisher Site

Abstract

1 Introduction</h5> It is largely recognized that an effective mitigation of the most adverse drought impacts is possible by capitalizing on the usually significant delay between drought inception (i.e. meteorological drought) and the moment when its consequences are perceived by the water supply systems and the end-users (i.e. socio-economic impacts of drought). To this end, a drought monitoring and forecasting system, able to promptly warn against an incipient phenomenon and to follow its evolution in space and time, represents the prerequisite for a successful mitigation strategy ( Rossi, 2003 ).</P>Many statistical and non statistical techniques have been proposed to forecast droughts ( Bonaccorso et al., 2012 and references therein). Regardless of the specific methodology, a distinction can be made with reference to the objective of the forecast. On the one hand, the interest may lie in forecasting future values of the hydrometeorological variable or drought index under investigation. On the other hand, the objective may lie in determining transition probabilities from a given current drought class (expressed in terms of a drought severity variable or index) to another one in the future.</P>Several forecasting techniques have been proposed to assess the probable evolution of drought related hydrometeorological variables or

Journal

Journal of HydrologyElsevier

Published: Jul 1, 2015

References

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