@book{
 title = {Copula Functions and Drought},
 type = {book},
 year = {2016},
 identifiers = {[object Object]},
 publisher = {Handbook of Drought and Water Scarcity, Vol. 1: Principles of Drought and Water Scarcity, CRC press, Taylor & Francis Group},
 chapter = {26},
 id = {667851ce-0897-352e-b2ed-4aeb5c199d8b},
 created = {2016-04-20T21:45:04.000Z},
 file_attached = {false},
 profile_id = {a803ed47-5875-3558-8068-231f4d481f8e},
 last_modified = {2016-05-09T20:39:07.000Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 abstract = {Copula functions are a group of multivariate distribution functions that join the marginal distribution of multiple variables. They have been used in different fields of science and engineering during the past decades. The main advantage of copulas over other multivariate distribution functions is their flexible structure in choosing marginal distributions. They are also strongly capable to characterize the joint behavior of dependent random variables. The focus of this chapter is on the application of copula functions in hydrology, specifically in predicting drought events. The first application explains how copulas can help to identify the multivariate return period (i.e. conditional and joint return periods) of drought events with particular duration, severity, and intensity under climate change impacts. The second application involves in drought forecasting at seasonal and multi-seasonal lead times. The copula-based drought forecasting model is a conditional model given the past observation of drought status. The forecast model can provide the decision makers with probability maps of drought events and useful information on drought recovery in forecast season. Copulas have demonstrated appealing performance in hydrological applications and it is expected to witness their more applications in the future.},
 bibtype = {book},
 author = {Madadgar, S and Moradkhani, H}
}

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