Modelagem da precipitação pluvial diária intra-anual da Bacia Hidrográfica Paraná III associada aos eventos ENOS

Baú, Antonio L.; Azevedo, Carlos Alberto Vieira de; Bresolin, Adriano de Andrade

doi:10.1590/s1415-43662013000800013

Cited by 7 publications

(8 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In selecting the periods of the historical rainfall series, the admissible fault limit of up to 1.8% in each data series was applied as a criterion. This limit of failures was adopted based on the study by Baú et al (2013), where the stochastic model chosen (Markov Chains) admitted, with good reasonableness, its application, but does not rule out the possibility of negative, albeit small, interference in the accuracy of the results. Figure 1 shows the site of the study area and the distribution of rainfall gauge stations.…”

Section: Study Area and Datamentioning

confidence: 99%

See 1 more Smart Citation

Distribution of rainfall probability in the Tapajos River Basin, Amazonia, Brazil

Santos¹,

Blanco²,

Júnior³

2019

Rev. ambiente água

View full text Add to dashboard Cite

Studies on the probability of rainfall and its spatiotemporal variations are important for the planning of water resources and optimization of the calendar of agricultural activities. This study identifies the occurrence of rain by first-order Markov Chain (MC) and by two states in the Tapajos River Basin (TRB), Amazon, Brazil. Cluster analysis (CA), based on the Ward method, was used to classify homogeneous regions and select samples for checking the probability of rainfall occurrence by season. The historical series of daily rainfall data of 80 stations were used for the period 1990-2014. The CA technique identified 8 homogeneous regions and their probability of occurrence of rainfall, helping to determine which regions and periods have greater need of irrigation. Results of the probability of occurrence of dry and rainy periods in the TRB were used to define the dry (May thru September) and rainy seasons (October thru April). Elements of the matrix transition probabilities showed variability in relation to time and, in addition, the influence of geographical position of seasonal rainfall in determining dry and rainy periods at specific sites in the TRB.

show abstract

Section: Study Area and Datamentioning

confidence: 99%

“…Table 1 provides information on the same. Szyniszewska and Waylen, 2012;Baú et al, 2013). The condition of rainy or dry state is associated with a probability of occurrence.…”

Section: Study Area and Datamentioning

confidence: 99%

Distribution of rainfall probability in the Tapajos River Basin, Amazonia, Brazil

Santos¹,

Blanco²,

Júnior³

2019

Rev. ambiente água

View full text Add to dashboard Cite

show abstract

“…In addition, for the model, monthly seasonality with steady behavior was adopted. This choice was based on the works of Baú, Azevedo, and Bresolin (2013), Detzel and Mine (2011b), and Kist and Virgens Filho (2015).…”

Section: Methodsmentioning

confidence: 99%

Cumulative distribution function of daily rainfall in the Tocantins–Araguaia hydrographic region, Amazon, Brazil

Progênio

Blanco

2020

Natural Resource Modeling

View full text Add to dashboard Cite

Knowing the temporal and spatial variability of the probability of rainfall occurrence is indispensable for the planning and management of agricultural and agroindustrial activities. This study aims to evaluate the applicability of four cumulative distribution functions (CDFs; exponential, two-parameter exponential, mixed exponential, and gamma) to estimate the probability of daily rainfall in the Tocantins-Araguaia hydrographic region (TAHR). The CDFs were applied to 196 rainfall gauge stations distributed in three homogeneous regions (HRs) of rainfall in the TAHR. In relation to the CDFs, the Kolmogorov-Smirnov test and the probability-probability plot showed that the mixed exponential best adhered to the observed data for most of the months of the year in the three HRs that were analyzed. In the few months that this function did not have a good statistical performance, the gamma function was the one with the best fit quality. This study can be used as a guide for studies in other river basins in Brazil and around the world to estimate CDFs of daily rainfall. Recommendations for Resource Managers• Stochastic models using cumulative distribution functions (CDFs) allow the simulation of rainfall data by means of their frequency of occurrence. Some CDFs have been used to verify the behavior and variability of precipitation over the years. For example, the mixed exponential, the Weibull with two parameters, the generalized Pareto, the lognormal, and the gamma with two parameters.• Daily rainfall modeling is important to recognize the occurrence patterns for the prediction of the climatic behavior of a region. Sectors such as agriculture, flood control, and human supply projects need knowledge of precipitation for planning, management, and operation.• The knowledge of the rainfall behavior is very important in Tocantins-Araguaia hydrographic region because it is located in the arc of deforestation in the Amazon. In this case, the dry season and temperatures have been increasing due to global climate change and deforestation itself. K E Y W O R D S adherence test, agroindustrial activities, ecotone, homogeneous regions, water resources

show abstract

“…Transition probabilities between dry and rainy conditions, i.e. P(0,0), P(0,1), P(1,0) and P(1,1) (BAÚ et al, 2013), were determined for an annual series, without considering monthly stationarity, since this study aimed to fulfill daily gaps and subsequently set an annual maximum daily rainfall series. After estimating transition probabilities, 100 sequences of dry/rainy days were generated for the entire period where gaps occurred.…”

Section: Methodsmentioning

confidence: 99%

Intensity-Duration-Frequency relationships: stochastic modeling and disaggregation of daily rainfall in the lagoa Mirim watershed, Rio Grande do Sul, Brazil

et al. 2016

View full text Add to dashboard Cite

This study aimed to investigate information gain by using rainfall intensity-durationfrequency (IDF) relationships, with data gathered within N+M years from seven rain gauge stations located in the Lagoa Mirim Watershed (South Atlantic basin). After N years of daily rainfall, the transition probabilities of a time homogeneous two-state Markov chain were defined to simulate rainfall occurrence, as well as gamma distribution to measure it; for that, daily rainfall series were composed of N+M years, with M being the generated series. The series were adjusted to Gumbel distribution, being used in annual maximum daily rainfall disaggregation for durations of 10, 20, 30, 40, 50, 60, 120, 360, 720 and 1440 min. Daily rainfall disaggregation was validated through IDF relationships taken from pluviograph records of N years and from N+M years, using the "t" test of relative mean squared error. We can infer that there was information gain using IDF relationships of rainfall occurrence when using N years of observed data and M years of generated data by stochastic modeling compared to those obtained from a composed series of N years.KEY WORDS: intense rainfall, hydrologic modeling, pluviographic records, hydrological series. RELAÇÕES INTENSIDADE-DURAÇÃO-FREQUÊNCIA: MODELAGEM ESTOCÁSTICAE DESAGREGAÇÃO DA CHUVA DIÁRIA NA BACIA HIDROGRÁFICA DA LAGOA MIRIM/RS/BRASIL RESUMO: Objetivou-se verificar se há ganho de informação em termos de relações IntensidadeDuração-Frequência (IDF) de ocorrência de chuva, obtidas a partir de N+M anos de dados para sete estações pluviométricas, pertencentes à bacia hidrográfica da lagoa Mirim (bacia do Atlântico Sul). A partir de N anos de chuva diária observada, foram ajustadas as probabilidades de transição da cadeia de Markov homogênea de dois estados, utilizada na simulação da ocorrência de dias secos e chuvosos, bem como a distribuição Gama, para quantificar a chuva, sendo a série de c huva diária composta por N+M anos, e M a série gerada. As séries compostas foram ajustadas à distribuição de Gumbel e utilizadas na desagregação da chuva máxima diária anual para as durações de 10, 20, 30, 40; 50; 60; 120; 360; 720 e 1440 min. Na validação da metodologia da desagregação da chuva diária, foram comparadas as relações IDFs, a partir de registros pluviográficos, com as obtidas a partir de N anos, bem como as obtidas a partir de N+M anos, utilizando o teste "t" do erro relativo médio quadrático. Concluiu-se que houve ganho de informação em termos de relações IDF de ocorrência de chuva, quando são utilizados N anos de dados observados e M anos de dados gerados, mediante a modelagem estocástica, comparativamente às obtidas a partir da série compost a de N anos.PALAVRAS-CHAVE: chuva intensa, modelagem hidrológica, registros pluviográficos, séries hidrológicas.Intensity-duration-frequency relationships: stochastic modeling and disaggregation of daily rainfall

show abstract

Modelagem da precipitação pluvial diária intra-anual da Bacia Hidrográfica Paraná III associada aos eventos ENOS

Cited by 7 publications

References 13 publications

Distribution of rainfall probability in the Tapajos River Basin, Amazonia, Brazil

Distribution of rainfall probability in the Tapajos River Basin, Amazonia, Brazil

Cumulative distribution function of daily rainfall in the Tocantins–Araguaia hydrographic region, Amazon, Brazil

Intensity-Duration-Frequency relationships: stochastic modeling and disaggregation of daily rainfall in the lagoa Mirim watershed, Rio Grande do Sul, Brazil

Contact Info

Product

Resources

About