scholarly journals Modelling of Intensity-Duration Frequency curves for Upper Cauvery Karnataka through Normal Distribution

2019 ◽  
Vol 9 (1) ◽  
pp. 4480-4502
Keyword(s):  
Normal Distribution ◽  
Short Duration ◽  
Urban Areas ◽  
Extreme Rainfall ◽  
Climate Impacts ◽  
Distribution Method ◽  
Study Region ◽  
Maximum Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency

The IDF Curves accessible are for the most part done by fitting arrangement of yearly greatest precipitation force to parametric dispersions. Intensity-duration-frequency (IDF) curves represent the relationship between storm intensity, storm duration and return period. Environmental change is relied upon to intensify the boundaries in the atmosphere factors. Being prone to harsh climate impacts, it is very crucial to study extreme rainfall-induced flooding for short durations over regions that are rapidly growing. One way to approach the extremes is by the application of the Intensity-Duration-Frequency (IDF) curves. The annual maximum rainfall intensity (AMRI) characteristics are often used to construct these IDF curves that are being used in several infrastructure designs for urban areas. Thus, there is a necessity to obtain high temporal and spatial resolution rainfall information. Many urban areas of developing countries lack long records of short-duration rainfall. The shortest duration obtained is normally at a daily scale/24 h. Thus, it is very crucial to find a methodology to construct IDF curves for short-duration rainfall (sub-daily) for these urban areas. The fast extension of urban area that does not have adequate preparedness to cope with climate change is certainly a big risk to life and economy. The study region lies in Karnataka India. The sub-daily IDF curves for current and future climate for the region were constructed from 1 to 24 h based on the Normal Distribution approach. Rainfall data of 23 (Twenty three) hydrological years of all stations were used. Maximum rainfall frequency analysis was made by Normal Distribution method. Finally Equations were developed for different return periods

scholarly journals Disaggregation of future GCMs to generate IDF curves for the assessment of urban floods

2021 ◽  
Author(s):  
H. Tayşi ◽  
M. Özger
Keyword(s):  
Climate Change ◽  
Short Duration ◽  
Urban Areas ◽  
Climate Models ◽  
Global Climate ◽  
Drainage System ◽  
Global Climate Models ◽  
Urban Floods ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract Urbanization and industrialization cause an increase in greenhouse gas emissions, which in turn causes changes in the atmosphere. Climate change is causing extreme rainfalls and these rainfalls are getting stronger day after day. Floods are threatening urban areas, and short-duration rainfall and outdated drainages are responsible for urban floods. Intensity–Duration–Frequency (IDF) curves are crucial for both drainage system design and assessment of flood risk. Once IDF curves are determined from historical data, they are assumed to be stationary. However, IDF curves must be non-stationary and time varying based on preparation for extreme events. This study generates future IDF curves with short-duration rainfalls under climate change. To represent future rainfall, an ensemble of four Global Climate Models generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 were used in this study. A new approach to the HYETOS disaggregation model was applied to disaggregate daily future rainfall into sub-hourly using disaggregation parameters of hourly measured rainfalls. Hence, sub-hourly future rainfalls will be obtained capturing historical rainfall patterns instead of random rainfall characteristics. Finally, historical and future IDF curves were compared. The study concludes that increases in short-duration rainfalls will be highly intensified in both the near and distant futures with a high probability.

scholarly journals Spatial Heterogeneity Analysis of Short-Duration Extreme Rainfall Events in Megacities in China

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3364 ◽  
Author(s):  
Qi Zhuang ◽  
Shuguang Liu ◽  
Zhengzheng Zhou
Keyword(s):  
Spatial Heterogeneity ◽  
Short Duration ◽  
Urban Areas ◽  
Spatial Association ◽  
Extreme Rainfall ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Design Storm

Given the fact that researchers require more specific spatial rainfall information for storm flood calculation, hydrological risk assessment, and water budget estimates, there is a growing need to analyze the spatial heterogeneity of rainfall accurately. This paper provides insight into rainfall spatial heterogeneity in urban areas based on statistical analysis methods. An ensemble of short-duration (3-h) extreme rainfall events for four megacities in China are extracted from a high-resolution gridded rainfall dataset (resolution of 30 min in time, 0.1° × 0.1° in space). Under the heterogeneity framework using Moran’s I, LISA (Local Indicators of Spatial Association), and semi-variance, the multi-scale spatial variability of extreme rainfall is identified and assessed in Shanghai (SH), Beijing (BJ), Guangzhou (GZ), and Shenzhen (SZ). The results show that there is a pronounced spatial heterogeneity of short-duration extreme rainfall in the four cities. Heterogeneous characteristics of rainfall within location, range, and directions are closely linked to the different urban growth in four cities. The results also suggest that the spatial distribution of rainfall cannot be neglected in the design storm in urban areas. This paper constitutes a useful contribution to quantifying the degree of spatial heterogeneity and supports an improved understanding of rainfall/flood frequency analysis in megacities.

scholarly journals Modelling and assessment of urban flood hazards based on rainfall intensity-duration-frequency curves reformation

2016 ◽  
Author(s):  
Reza Ghazavi ◽  
Ali Moafi Rabori ◽  
Mohsen Ahadnejad Reveshty
Keyword(s):  
Return Period ◽  
Urban Areas ◽  
Rainfall Intensity ◽  
Flood Hazards ◽  
Return Periods ◽  
Urban Flood ◽  
Design Storm ◽  
Hourly Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract. Estimate design storm based on rainfall intensity–duration–frequency (IDF) curves is an important parameter for hydrologic planning of urban areas. The main aim of this study was to estimate rainfall intensities of Zanjan city watershed based on overall relationship of rainfall IDF curves and appropriate model of hourly rainfall estimation (Sherman method, Ghahreman and Abkhezr method). Hydrologic and hydraulic impacts of rainfall IDF curves change in flood properties was evaluated via Stormwater Management Model (SWMM). The accuracy of model simulations was confirmed based on the results of calibration. Design hyetographs in different return periods show that estimated rainfall depth via Sherman method are greater than other method except for 2-year return period. According to Ghahreman and Abkhezr method, decrease of runoff peak was 30, 39, 41 and 42 percent for 5-10-20 and 50-year return periods respectively, while runoff peak for 2-year return period was increased by 20 percent.

scholarly journals Rainfall Intensity Analysis for Synoptic Stations in Northern Nigeria

2020 ◽  
Vol 17 (3) ◽  
pp. 223-228
Author(s):  
S.O. Oyegoke ◽  
A.S. Adebanjo ◽  
H.J. Ododo
Keyword(s):  
Rainfall Intensity ◽  
Linear Regression Analysis ◽  
Extreme Rainfall ◽  
Data Series ◽  
Northern Nigeria ◽  
Return Periods ◽  
Accurate Forecast ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Frequency Relationship

With the large inter-annual variability of rainfall in Northern Nigeria, a zone subject to frequent dry spells which often result in severe and widespread droughts, the need for intense study of rainfall and accurate forecast of rainfall intensity duration frequency (IDF) curves cannot be over emphasized. The Intensity Duration Frequency relationship is a mathematical relationship between the rainfall intensity and rainfall duration for given return periods. Using a subset of the network of fifteen continuous auto recording rain gauges available in Northern Nigeria, a total of seven different time durations ranging from 12 minutes to 24 hours were developed for return periods of 2, 5, 10, 25, 50 and 100 years. The maximum data series so obtained was fitted to Gumbel’s Extreme Value Type 1 distribution. Linear Regression Analysis was then used to obtain the intensity-duration relationships for the various locations from which Intensity-Duration Frequency (IDF) curves were generated using Microsoft Excel for various return periods. Keywords:  Extreme rainfall, intensity, duration, frequency, Northern Nigeria

scholarly journals Potential of plotting positions for intensity-duration-frequency curves with short rainfall records

2017 ◽  
Vol 13 (4-1) ◽  
pp. 394-399
Author(s):  
Noratiqah Mohd Ariff ◽  
Abdul Aziz Jemain ◽  
Mohd Aftar Abu Bakar
Keyword(s):  
Probability Distribution ◽  
Empirical Distribution ◽  
Annual Rainfall ◽  
Annual Maximum ◽  
Distribution Fitting ◽  
Maximum Rainfall ◽  
Gev Distribution ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Annual Maximum Rainfall

Intensity-duration-frequency (IDF) curves represent the relationship between storm intensity, storm duration and return period. The IDF curves available are mostly done by fitting series of annual maximum rainfall intensity to parametric distributions. However, the length of annual rainfall records, especially for small scaled data, are not always enough. Rainfall records of less than 50 years are usually deemed insufficient to unequivocally identify the probability distribution of the annual rainfall. Thus, this study introduces an alternative approach that replaces the need for parametric fitting by using empirical distribution based on plotting positions to represent annual maximum rainfall series. Subsequently, these plotting positions are used to build IDF curves. The IDF curves found are then compared to the IDF curves yielded from the parametric GEV distribution which is a common basis for IDF curves. This study indicates that IDF curves obtained using plotting positions are similar to IDF curves found using GEV distribution for storm events. Hence, researchers could model and subsequently build IDF curves for annual rainfall records of less than 50 years by using plotting positions and avoid any probability distribution fitting of insufficient data.

scholarly journals Development of Intensity Duration Frequency (IDF) Curves for Rainfall Prediction within the Middle Niger River Basin

2020 ◽  
Vol 4 (2) ◽  
pp. 382-397
Author(s):  
J. O. Ehiorobo ◽  
O.C. Izinyon ◽  
R. I. Ilaboya
Keyword(s):  
River Basin ◽  
Rainfall Intensity ◽  
Rainfall Data ◽  
Annual Maximum ◽  
Return Periods ◽  
Maximum Rainfall ◽  
Niger River ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Best Fit

Rainfall Intensity-Duration-Frequency (IDF) relationship remains one of the mostly used tools in hydrology and water resources engineering, especially for planning, design and operations of water resource projects. IDF relationship can provide adequate information about the intensity of rainfall at different duration for various return periods. The focus of this research was to develop IDF curves for the prediction of rainfall intensity within the middle Niger River Basin (Lokoja and Ilorin) using annual maximum daily rainfall data. Forty (40) year’s annual maximum rainfall data ranging from 1974 to 2013 was employed for the study. To ascertain the data quality, selected preliminary analysis technique including; descriptive statistics, test of homogeneity and outlier detection test were employed. To compute the three hours rainfall intensity, the ratio of rainfall amount and duration was used while the popular Gumbel probability distribution model was employed to calculate the rainfall frequency factor. To assess the best fit model that can be employed to predict rainfall intensity for various return periods at ungauged locations, four empirical IDF equations, namely; Talbot, Bernard, Kimijima and Sherman equations were employed. The model with the least calculated sum of minimized root mean square error (RMSE) was adopted as the best fit empirical model. Results obtained revealed that the Talbot model was the best fit model for Ilorin and Lokoja with calculated sum of minimized error of 1.32170E-07 and 8.953636E-08. This model was thereafter employed to predict the rainfall intensity for different durations at 2, 5, 10, 25, 50 and 100yrs return periods respectively.

scholarly journals Extreme rainfall and IDF equations for Alagoas State, Brazil

2020 ◽  
Vol 15 (6) ◽  
pp. 1
Author(s):  
Álvaro José Back ◽  
Sabrina Baesso Cadorin ◽  
Sérgio Luciano Galatto
Keyword(s):  
Hydrological Modeling ◽  
Probability Distributions ◽  
Gumbel Distribution ◽  
Extreme Rainfall ◽  
Maximum Rainfall ◽  
Gev Distribution ◽  
Significance Level ◽  
Intensity Duration Frequency ◽  
Conservation Projects ◽  
Anderson Darling

Intensity-duration-frequency (IDF) equations have important applications in several engineering areas such as urban drainage designs, hydrological modeling, and soil conservation projects. This study analyzes the annual maximum series and fits IDF equations for 44 rainfall stations in Alagoas State, Brazil. We adjusted parameters of the Gumbel distribution (GD) and the Generalized Extreme Value (GEV) distribution. The fitting of the observed data to the probability distributions, as well as the selection of the best distribution, were based on the Kolmogorov-Smirnov and Anderson-Darling tests at a 5% significance level. The GEV distribution with parameters obtained by the L-moments method was considered the best in 73% of rainfall stations. The estimated IDF equations showed a good fit, with determination coefficients above 0.991. The maximum rainfall intensities have spatial variation following the climatic zones of the state. The fitted equations allow estimating rainfall intensities from 5 minutes to 24 hours with a return period of 2 to 100 years, and standard error of less than 6.83 mm h-1.

scholarly journals Disaggregation of Future Regional Climate Model Data to Generate Future Rainfall Intensity-Duration-Frequency Curves to Assess Climate Change Impacts

2021 ◽  
Author(s):  
Hüsamettin Tayşi ◽  
Mehmet Ozger
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Model ◽  
Regional Climate ◽  
Rainfall Data ◽  
Rainfall Events ◽  
Rainfall Characteristics ◽  
Hourly Data ◽  
Idf Curves ◽  
Intensity Duration Frequency

Heavy increase in urbanization, industrialization and population is causing an increase in emissions of greenhouse gases (GHG) and this causes variations in atmosphere. Climate change causes extreme rainfall events and these events are expected to be enhanced in the future. Since flooding is influencing urban areas, controlling and management of flooding is a major necessity. Intensity-Duration-Frequency (IDF) curves play a huge role in representing rainfall characteristics by linking intensity, duration, and frequency of rainfall. Analysing short-duration rainfall is crucial for urban areas due to fast responses of drainage systems against heavy rainfall events. IDF curves were generated via the Gumbel method for rainfalls from 5-min to 24-h in this study. However, providing short-duration rainfall data is challenging due to the low capacity, costs and geographic conditions. Therefore, the HYETOS disaggregation model was applied to obtain sub-hourly data. IDF curves are stationary since they only consider historical events. However, IDF curves must be non-stationary and time varying based on preparation for upcoming extreme events. This study aims to generate IDF curves under climate change scenarios. The Regional Climate Model (RCM) HadGEM2-ES generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios and was used in the study to represent future rainfalls. Future daily rainfalls were disaggregated into sub-hourly using disaggregation parameters of corresponding station’s historical rainfall data since it is impossible to estimate parameters when hourly data is not available. With this new approach, future daily rainfall data is disaggregated into 5-min data by complying with historical rainfall patterns rather than complying with randomly selected rainfall characteristics. The study concluded that future rainfall intensities increases compared to historical IDF curves. RCP8.5 scenarios have higher rainfall intensities for all return periods compared to RCP4.5 scenarios for all stations except a station. In addition, the accuracy of the selected disaggregation model was verified.

scholarly journals Intensity–duration–frequency (IDF) rainfall curves in Senegal

2018 ◽  
Vol 18 (7) ◽  
pp. 1849-1866 ◽  
Author(s):  
Youssouph Sane ◽  
Geremy Panthou ◽  
Ansoumana Bodian ◽  
Theo Vischel ◽  
Thierry Lebel ◽  
...  
Keyword(s):  
Spatial Vision ◽  
Extreme Rainfall ◽  
Sub Saharan Africa ◽  
Parameter Estimates ◽  
Infrastructure Development ◽  
Demographic Pressure ◽  
Tropical Regions ◽  
Scaling Parameter ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract. Urbanization resulting from sharply increasing demographic pressure and infrastructure development has made the populations of many tropical areas more vulnerable to extreme rainfall hazards. Characterizing extreme rainfall distribution in a coherent way in space and time is thus becoming an overarching need that requires using appropriate models of intensity–duration–frequency (IDF) curves. Using a 14 series of 5 min rainfall records collected in Senegal, a comparison of two generalized extreme value (GEV) and scaling models is carried out, resulting in the selection of the more parsimonious one (four parameters), as the recommended model for use. A bootstrap approach is proposed to compute the uncertainty associated with the estimation of these four parameters and of the related rainfall return levels for durations ranging from 1 to 24 h. This study confirms previous works showing that simple scaling holds for characterizing the temporal scaling of extreme rainfall in tropical regions such as sub-Saharan Africa. It further provides confidence intervals for the parameter estimates and shows that the uncertainty linked to the estimation of the GEV parameters is 3 to 4 times larger than the uncertainty linked to the inference of the scaling parameter. From this model, maps of IDF parameters over Senegal are produced, providing a spatial vision of their organization over the country, with a north to south gradient for the location and scale parameters of the GEV. An influence of the distance from the ocean was found for the scaling parameter. It is acknowledged in conclusion that climate change renders the inference of IDF curves sensitive to increasing non-stationarity effects, which requires warning end-users that such tools should be used with care and discernment.

scholarly journals Uncertainty in Rainfall Intensity Duration Frequency Curves of Peninsular Malaysia under Changing Climate Scenarios

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1750 ◽  
Author(s):  
Muhammad Noor ◽  
Tarmizi Ismail ◽  
Eun-Sung Chung ◽  
Shamsuddin Shahid ◽  
Jang Sung
Keyword(s):  
General Circulation ◽  
Rainfall Intensity ◽  
Daily Rainfall ◽  
General Circulation Models ◽  
Peninsular Malaysia ◽  
Climate Change Scenarios ◽  
Rcp Scenarios ◽  
Maximum Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency

This study developed a methodological framework to update the rainfall intensity-duration-frequency (IDF) curves under climate change scenarios. A model output statistics (MOS) method is used to downscale the daily rainfall of general circulation models (GCMs), and an artificial neural network (ANN) is employed for the disaggregation of projected daily rainfall to hourly maximum rainfall, which is then used for the development of IDF curves. Finally, the 1st quartiles, medians, and 3rd quartiles of projected rainfall intensities are estimated for developing IDF curves with uncertainty level. Eight GCM simulations under two radiative concentration pathways (RCP) scenarios, namely, RCP 4.5 and RCP 8.5, are used in the proposed framework for the projection of IDF curves with related uncertainties for peninsular Malaysia. The projection of rainfall revealed an increase in the annual average rainfall throughout the present century. The comparison of the projected IDF curves for the period 2006–2099 with that obtained using GCM hindcasts for the based period (1971–2005) revealed an increase in rainfall intensity for shorter durations and a decrease for longer durations. The uncertainty in rainfall intensity for different return periods for shorter duration is found to be 2 to 6 times more compared to longer duration rainfall, which indicates that a large increase in rainfall intensity for short durations projected by GCMs is highly uncertain for peninsular Malaysia. The IDF curves developed in this study can be used for the planning of climate resilient urban water storm water management infrastructure in Peninsular Malaysia.

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