{"id":{"repo_id":"brazil-uerj","oai_identifier":"oai:pantheon.ufrj.br:11422/3937"},"canonical_url":"https://search.dev.ndltd.org/etd/brazil-uerj/oai:pantheon.ufrj.br:11422/3937","repository":{"repo_id":"brazil-uerj","name":"Brazil UERJ","base_url":"https://pantheon.ufrj.br/oai/request"},"display":{"title":"Modelagem estocástica para a precipitação diária","abstract":"The stochastic daily precipitation modeling is the main objective of this dissertation. The occurrence of the process was modeled by a two-state (dry or rainy day) Markov chain and by the “wet-dry spell” approach. This second approach was considered appropriate, while the Markov chains could not describe the long droughts or the long wet spells. ln the rainy days, two assumptions were made: 1) the rainfall amounts are independents and 2) the rainfall amounts, in consecutive rainy days, are dependents and were generated by a first-order autoregressive model AR(1). The analysis of the generated and the historical data, indicated that only under the assumption of dependence, the annual series of maximum of daily precipitations, for specified durations in days, had the same probabilities distributions. This fact shows the importance of analizing extreme events and the need for some reflection on the serial correlation of the precipitation data.","abstract_html":"The stochastic daily precipitation modeling is the main objective of this dissertation. The occurrence of the process was modeled by a two-state (dry or rainy day) Markov chain and by the “wet-dry spell” approach. This second approach was considered appropriate, while the Markov chains could not describe the long droughts or the long wet spells. ln the rainy days, two assumptions were made: 1) the rainfall amounts are independents and 2) the rainfall amounts, in consecutive rainy days, are dependents and were generated by a first-order autoregressive model AR(1). The analysis of the generated and the historical data, indicated that only under the assumption of dependence, the annual series of maximum of daily precipitations, for specified durations in days, had the same probabilities distributions. This fact shows the importance of analizing extreme events and the need for some reflection on the serial correlation of the precipitation data.","abstract_has_math":false,"creators":["Nascimento, Carlos Eduardo de Siqueira"],"institution":"Universidade Federal do Rio de Janeiro","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Kelman, Jerson"],"committee_chairs":[],"committee_members":[],"year":1990,"date_issued":"1990-09","date_published":"1990-09","updated_at":"2026-07-24T01:16:10Z","subjects":["Engenharia Civil"],"languages":["por"],"rights":["Acesso Aberto"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11422/3937","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Kelman, Jerson"]},{"key":"dc:creator","label":"Author","values":["Nascimento, Carlos Eduardo de Siqueira"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-05-09T17:06:39Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-05-16T03:04:17Z"]},{"key":"dc:date.issued","label":"Date","values":["1990-09"]},{"key":"dc:publisher","label":"Institution","values":["Universidade Federal do Rio de Janeiro"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia"]},{"key":"dc:type","label":"Dc Type","values":["Dissertação"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engenharia Civil"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["por"]},{"key":"dc:rights","label":"Dc Rights","values":["Acesso Aberto"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11422/3937"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The stochastic daily precipitation modeling is the main objective of this dissertation. The occurrence of the process was modeled by a two-state (dry or rainy day) Markov chain and by the “wet-dry spell” approach. This second approach was considered appropriate, while the Markov chains could not describe the long droughts or the long wet spells. ln the rainy days, two assumptions were made: 1) the rainfall amounts are independents and 2) the rainfall amounts, in consecutive rainy days, are dependents and were generated by a first-order autoregressive model AR(1). The analysis of the generated and the historical data, indicated that only under the assumption of dependence, the annual series of maximum of daily precipitations, for specified durations in days, had the same probabilities distributions. This fact shows the importance of analizing extreme events and the need for some reflection on the serial correlation of the precipitation data."]},{"key":"dc:title","label":"Title","values":["Modelagem estocástica para a precipitação diária"]}]}],"canonical_facts":{"dc:contributor.advisor":["Kelman, Jerson"],"dc:creator":["Nascimento, Carlos Eduardo de Siqueira"],"dc:date.accessioned":["2018-05-09T17:06:39Z"],"dc:date.available":["2026-05-16T03:04:17Z"],"dc:date.issued":["1990-09"],"dc:description.abstract":["The stochastic daily precipitation modeling is the main objective of this dissertation. The occurrence of the process was modeled by a two-state (dry or rainy day) Markov chain and by the “wet-dry spell” approach. This second approach was considered appropriate, while the Markov chains could not describe the long droughts or the long wet spells. ln the rainy days, two assumptions were made: 1) the rainfall amounts are independents and 2) the rainfall amounts, in consecutive rainy days, are dependents and were generated by a first-order autoregressive model AR(1). The analysis of the generated and the historical data, indicated that only under the assumption of dependence, the annual series of maximum of daily precipitations, for specified durations in days, had the same probabilities distributions. This fact shows the importance of analizing extreme events and the need for some reflection on the serial correlation of the precipitation data."],"dc:identifier.uri":["http://hdl.handle.net/11422/3937"],"dc:language":["por"],"dc:publisher":["Universidade Federal do Rio de Janeiro"],"dc:publisher.department":["Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia"],"dc:rights":["Acesso Aberto"],"dc:subject":["Engenharia Civil"],"dc:title":["Modelagem estocástica para a precipitação diária"],"dc:type":["Dissertação"]},"updated_at":"2026-07-24T01:16:10Z"}