author = "Rocha J{\'u}nior, Rodrigo Lins da and Silva, Fabr{\'{\i}}cio 
                         Daniel dos Santos and Costa, Rafaela Lisboa and Gomes, 
                         Heliof{\'a}bio Barros and Pinto, David Duarte Cavalcante and 
                         Herdies, Dirceu Lu{\'{\i}}s",
          affiliation = "{Universidade Federal de Alagoas (UFAL)} and {Universidade Federal 
                         de Alagoas (UFAL)} and {Universidade Federal de Alagoas (UFAL)} 
                         and {Universidade Federal de Alagoas (UFAL)} and {Universidade 
                         Federal de Alagoas (UFAL)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Bivariate assessment of drought return periods and frequency in 
                         brazilian northeast using joint distribution by copula method",
              journal = "Geosciences (Switzerland)",
                 year = "2020",
               volume = "10",
               number = "4",
                pages = "e135",
                month = "apr.",
             keywords = "meteorological drought analysis, Standardized Precipitation Index 
                         (SPI), archimedean copulas, probability distributions.",
             abstract = "The Northeast region of Brazil (NRB) is the most populous semiarid 
                         area in the world and is extremely susceptible to droughts. The 
                         severity and duration of these droughts depend on several factors, 
                         and they do not necessarily follow the same behavior. The aim of 
                         this work is to evaluate the frequency of droughts in the NRB and 
                         calculate the return period of each drought event using the copula 
                         technique, which integrates the duration and severity of the 
                         drought in the NRB in a joint bivariate distribution. Monthly 
                         precipitation data from 96 meteorological stations spatially 
                         distributed in the NRB, ranging from 1961 to 2017, are used. The 
                         copula technique is applied to the Standardized Precipitation 
                         Index (SPI) on the three-month time scale, testing three families 
                         of Archimedean copula functions (Gumbel-Hougaard, Clayton and 
                         Frank) to reveal which model is best suited for the data. 
                         Averagely, the most frequent droughts observed in the NRB are 
                         concentrated in the northern sector of the region, with an 
                         observed duration varying from three and a half to five and a half 
                         months. However, the eastern NRB experiences the most severe 
                         droughts, lasting for 14 to 24 months. The probability 
                         distributions that perform better in modeling the series of 
                         severity and duration of droughts are exponential, normal and 
                         lognormal. The observed severity and duration values show that, 
                         for average values, the return period across the region is 
                         approximately 24 months. Still in this regard, the southernmost 
                         tip of the NRB stands out for having a return period of over 35 
                         months. Regarding maximum observed values of severity and 
                         duration, the NRB eastern strip has the longest return period (>60 
                         months), mainly in the southeastern portion where a return period 
                         above 90 months was observed. The northern NRB shows the shortest 
                         return period (~45 months), indicating that it is the NRB sector 
                         with the highest frequency of intense droughts. These results 
                         provide useful information for drought risk management in the 
                  doi = "10.3390/geosciences10040135",
                  url = "http://dx.doi.org/10.3390/geosciences10040135",
                 issn = "2076-3263",
             language = "en",
           targetfile = "geosciences-10-00135.pdf",
        urlaccessdate = "13 abr. 2021"