RainIDF: automated derivation of rainfall intensity–duration–frequency relationship from annual maxima and partial duration series

Chang, Kian Boon; Hin, Lai Sai; Faridah, Othman

doi:10.2166/hydro.2013.192

Cited by 15 publications

(5 citation statements)

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“…Limited information is available on how to bring climate change into the IDF calculations [20][21][22][23][24][25] and even less on how to implement updated IDF curves in practice [26]. Authors such as [27,28] have presented decision support systems to assist in the calculation of IDF curves, using GIS tools and Microsoft Excel, respectively.…”

Section: Introductionmentioning

confidence: 99%

Web-Based Tool for the Development of Intensity Duration Frequency Curves under Changing Climate at Gauged and Ungauged Locations

Schardong

Simonović́

Gaur

et al. 2020

Water

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Rainfall Intensity–Duration–Frequency (IDF) curves are among the most essential datasets used in water resources management across the globe. Traditionally, they are derived from observations of historical rainfall, under the assumption of stationarity. Change of climatic conditions makes use of historical data for development of IDFs for the future unreliable, and in some cases, may lead to underestimated infrastructure designs. The IDF_CC tool is designed to assist water professionals and engineers in producing IDF estimates under changing climatic conditions. The latest version of the tool (Version 4) provides updated IDF curve estimates for gauged locations (rainfall monitoring stations) and ungauged sites using a new gridded dataset of IDF curves for the land mass of Canada. The tool has been developed using web-based technologies and takes the form of a decision support system (DSS). The main modifications and improvements between version 1 and the latest version of the IDF_CC tool include: (i) introduction of the Generalized Extreme value (GEV) distribution; (ii) updated equidistant matching algorithm (QM); (iii) gridded IDF curves dataset for ungauged location and (iv) updated Climate Models.

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Section: Introductionmentioning

confidence: 99%

Web-Based Tool for the Development of Intensity Duration Frequency Curves under Changing Climate at Gauged and Ungauged Locations

Schardong

Simonović́

Gaur

et al. 2020

Water

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“…What is observed is the use of a particular probability extreme distribution, such as Gumbel, in a generalised way, which can compromise the accuracy of the IDF equations. Examples can be seen in the works of Chang et al (2013) and Schardong et al (2020).…”

Section: Introductionmentioning

confidence: 99%

IDFequations: an R-based tool to generate intensity-duration-frequency (IDF) equations

Costa,

Rufino,

de Aragão

et al. 2024

Preprint

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IDFequations is a tool for determining intensity-duration-frequency (IDF) equations. It was specially developed to facilitate the adjustment of different probabilistic models in the frequency analysis of historical precipitation series and the adjustment of the IDF curve model without the user requiring prior knowledge about the model parameters. The tool integrates the ten most used statistical distributions to estimate maximum 1-day precipitation values for different return periods (Tr). A fitting equation was used to estimate sub-daily rainfall. The empirical parameters (k, m, t0 and n) were defined using an algorithm developed in the R programming language. It is directly connected to two precipitation database servers. It also provides IDF equations from precipitation estimation remote-sensing and local data.

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“…The main difference between the two series is that the AMS takes only the highest rainfall values in each year while the PDS takes all the values within each year that exceed a predetermined threshold value. Comparisons between the two data series have been carried out for certain localities to determine the best analysis model for deriving IDF relationships [9]- [12].…”

Section: Introductionmentioning

confidence: 99%

Design Runoff Estimation Using an Efficient Rainfall Analysis Model for Low Data Available Catchment

Ngene

Nwafor

Bamigboye

2020

JERA

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The challenge of various methods of analysis of rainfall intensity for design runoff estimation is in the availability of data for the given area. This work aims to evaluate the use of the Intensity Duration and Frequency (IDF) method in design runoff estimation using a rainfall analysis model for low data catchment areas such as Nigeria. The source of the data for the study is the Nigerian Meteorological Agency, and it is for Lokoja, a city in the North Central Zone of the country. Analysis of the data compared to the annual and partial duration series for rainfall intensities at various return periods. Also analyzed was the daily rainfall data to determine the rainfall intensity for the different duration and return periods for the study area. From the analysis, partial duration series analysis offered better design estimates than the annual series. Also noted is the fact that the intensity of rainfall increases with a return period of a given duration. The work also indicates that frequency curves can be used to extrapolate rainfall intensity of a given duration for a longer period than years of record. The paper, therefore, presents a design intensity equation useful for the estimation runoff necessary for sustainable infrastructures such as in water utilization and controls.

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RainIDF: automated derivation of rainfall intensity–duration–frequency relationship from annual maxima and partial duration series

Cited by 15 publications

References 0 publications

Web-Based Tool for the Development of Intensity Duration Frequency Curves under Changing Climate at Gauged and Ungauged Locations

Web-Based Tool for the Development of Intensity Duration Frequency Curves under Changing Climate at Gauged and Ungauged Locations

IDFequations: an R-based tool to generate intensity-duration-frequency (IDF) equations

Design Runoff Estimation Using an Efficient Rainfall Analysis Model for Low Data Available Catchment

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