Statistical analysis of monthly rainfall in Central West Brazil using probability distributions

Ozonur, Deniz; Pobocikova, Ivana; Souza, Amaury de

doi:10.1007/s40808-020-00954-z

Cited by 21 publications

(8 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Initially, eight hydrographs were computed in the hydrological modeling, referring to eight different return periods (3, 5, 10, 15, 25, 50, 100, and 500 years), needed for economic modeling in the HEC-FDA. It was decided to adopt the annual maximum 5-day rainfall, computed by the Gumbel model, considering that it is one of the most used probability distributions to estimate extreme rainfall (Ozonur et al, 2021). The HEC-HMS 4.…”

Section: Hydrological Modelingmentioning

confidence: 99%

Assessment of economic impacts in flood events in Lages/SC, Brazil

Primo,

Rafaeli

2023

Rev. Bras. Ciênc. Ambient.

View full text Add to dashboard Cite

Flood processes become increasingly harmful to communities due to factors such as climate change and land use. This study aims to evaluate the economic damages of flood events in an area of the urban basins of Lages/SC. Thus, four plans were considered for economic evaluation: one referring to conditions without protective measures and three with the application of elevation of structures at different heights, as well as two scenarios of the evolution of urban occupation. The rainfalls were obtained through the Gumbel probabilistic model to estimate the maximum accumulated precipitations over 5 days, with the hydrological modeling carried out at the HEC-HMS. The hydrodynamic modeling was performed in HEC-RAS through the simulation of a 1D model. The HEC-FDA model was used to perform the risk reduction analysis of damage caused by floods, where the expected annual damages (EAD) were calculated for the four proposed plans as well as for the urban growth scenarios. The results showed that the application of the mitigating measure of raising the structures reduced the EAD by up to 83.10%. As for the scenario of the evolution of urban growth, there was an increase in EAD of 62.09%, in the interval of 20 years. The HEC-FDA model has been demonstrated as good software for assessing the economic damage of floods in different scenarios, showing results that can help decision-makers in the development of public policies.

show abstract

Section: Hydrological Modelingmentioning

confidence: 99%

Assessment of economic impacts in flood events in Lages/SC, Brazil

Primo,

Rafaeli

2023

Rev. Bras. Ciênc. Ambient.

View full text Add to dashboard Cite

show abstract

“…Rainfall and other climatic factors such as temperature always have signi cant impacts on agricultural activities and the negative impacts of these factors are more aggravated by the global effects of climate change (Zakwan and Ara, 2019). Determination and analysis of available water resources especially for rain-fed agriculture are of utmost importance in water resources planning for agricultural purposes (Ozonur et al, 2020). Seasonal rainfall variation always has signi cant effects on food security and agricultural viability of many regions which depends on agriculture (Akhoury and Avishek, 2019).…”

Section: Introductionmentioning

confidence: 99%

Modelling rainfall in selected agricultural hubs in Nigeria: a comparative probability distributions study

Sasanya,

Awodutire,

Ufuoma

2024

Theor Appl Climatol

View full text Add to dashboard Cite

The most appropriate probability distribution for rainfall data varies from one region to the other. The need to research the best distribution for different locations is thus a continuous process. This research was designed to investigate rainfall variability and the best-t distribution model for monthly rainfall in Oke Ogun, the agricultural hub of Oyo state, Nigeria. Thirty-six years ' rainfall data (1982-2017) were statistically analysed and tted to ten different probability distributions for each calendar month. Parameters of each distribution were estimated from maximum likelihood estimates. Best t distribution models for each month were selected using Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and Corrected Akaike Information Criteria (CAIC) as model selection criteria. Gamma distribution had the best-t for six of the twelve-monthly rainfall data. Weibull distribution had best-t for three months, while Lognormal tted data for March and July best and Gumbel distribution had best-t for August. This study will enable adequate integrated water resources management as well as proper water resources evaluation and planning, for agricultural productivity in the Oke Ogun region of Oyo state. Nigeria.

show abstract

“…In another research, three different probability distributions were employed for modeling the peak discharge of the Jhelum River [27]. In a study to model the monthly rainfall data in Brazil [28], eight probability models and six goodness-of-fit tests included the Akaike information criterion. Additionally, they employed the maximum likelihood method to estimate the parameters of the distributions.…”

Section: Introductionmentioning

confidence: 99%

Tropically Adapted Passive Building: A Descriptive-Analytical Approach Using Multiple Linear Regression and Probability Models to Predict Indoor Temperature

Salleh,

Suleiman,

Daud

et al. 2023

Sustainability

View full text Add to dashboard Cite

The quest for energy efficiency in buildings has placed a demand for designing and modeling energy-efficient buildings. In this study, the thermal energy performance of a tropically adapted passive building was investigated in the warm tropical climate of Malaysia. Two mock-up buildings were built to represent a “green”, made of clay brick double-glazed passive building and a conventional, made of concrete “red” building. The mean indoor temperature of the passive building was found to be always lower than that of the red building throughout the experiment during different weather constellations. Our research builds upon existing work in the field by combining multiple linear regression models and distribution models to provide a comprehensive analysis of the factors affecting the indoor temperature of a building. The results from the fitted multiple linear regression models indicate that walls and windows are critical components that considerably influence the indoor temperature of both passive buildings and red buildings, with the exception of passive buildings during the hot season, where the roof has a greater influence than the window. Furthermore, the goodness-of-fit test results of the mean indoor temperature revealed that the Fréchet and Logistic probability models fitted the experimental data in both cold and hot seasons. It is intended that the findings of this study would help tropical countries to devise comfortable, cost-effective passive buildings that are green and energy efficient to mitigate global warming.

show abstract

Statistical analysis of monthly rainfall in Central West Brazil using probability distributions

Cited by 21 publications

References 37 publications

Assessment of economic impacts in flood events in Lages/SC, Brazil

Assessment of economic impacts in flood events in Lages/SC, Brazil

Modelling rainfall in selected agricultural hubs in Nigeria: a comparative probability distributions study

Tropically Adapted Passive Building: A Descriptive-Analytical Approach Using Multiple Linear Regression and Probability Models to Predict Indoor Temperature

Contact Info

Product

Resources

About