scholarly journals Development of Rainfall Intensity-Duration-Frequency (IDF) Curve for Abuja, Nigeria

2021 ◽  
Vol 40 (1) ◽  
pp. 154-160
Author(s):  
M.A. Ahmed ◽  
A.T. Olowosulu ◽  
B.K. Adeogun ◽  
A.A. Murana ◽  
H.A. Ahmed ◽  
...  

Urban flooding is a major social and economic problem of any nation. The social implication is attributed to loss of lives and property, unwanted displacement and emotional disturbance attached. While that of economic problem is the cost of mitigation of flood and the aftermath solution. Thus, storm water drainage is part of essential modern city infrastructure. The need for proper analysis and design of drainages and other road water facilities cannot be overemphasized. To achieve this, critical analysis of available rainfall data, which is a key input, is required. A 35 years daily rainfall data were obtained from NIMET, from which the analysis was carried out using frequency method. The output generated are presented in graphical forms and model. Ultimately, an IDF curve generated, depicts Abuja rainfall pattern from which a 3-parameter model equation, I = 37Tr0.2 (t + 0.1)−0.9 was formulated. This is site or location specific. The curve and/or the formulated model can be adopted to determine rainfall intensity of Abuja city if the rainfall duration and return period are predictable.

Author(s):  
Bappaditya Koley ◽  
Anindita Nath ◽  
Subhajit Saraswati ◽  
Kaushik Bandyopadhyay ◽  
Bidhan Chandra Ray

Land sliding is a perennial problem in the Eastern Himalayas. Out of 0.42 million km2 of Indian landmass prone to landslide, 42% fall in the North East Himalaya, specially Darjeeling and Sikkim Himalaya. Most of these landslides are triggered by excessive monsoon rainfall between June and October in almost every year. Various attempts in the global scenario have been made to establish rainfall thresholds in terms of intensity – duration of antecedent rainfall models on global, regional and local scale for triggering of the landslide. This paper describes local aspect of rainfall threshold for landslides based on daily rainfall data in and around north Sikkim road corridor region. Among 210 Landslides occurring from 2010 to 2016 were studied to analyze rainfall thresholds. Out of the 210 landslides, however, only 155 Landslides associated with rainfall data which were analyzed to yield a threshold relationship between rainfall intensity-duration and landslide initiation. The threshold relationship determined fits to lower boundary of the Landslide triggering rainfall events is I = 4.045 D - 0.25 (I=rainfall intensity (mm/h) and D=duration in (h)), revealed that for rainfall event of short time (24 h) duration with a rainfall intensity of 1.82 mm/h, the risk of landslides on this road corridor of the terrain is expected to be high. It is also observed that an intensity of 58 mm and 139 mm for 10-day and 20-day antecedent rainfall are required for the initiation of landslides in the study area. This threshold would help in improvement on traffic guidance and provide safety to the travelling tourists in this road corridor during the monsoon.


Author(s):  
J. O. Ehiorobo ◽  
O.C. Izinyon ◽  
R. I. Ilaboya

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.


Időjárás ◽  
2021 ◽  
Vol 125 (3) ◽  
pp. 513-519
Author(s):  
Tibor Rácz

Historical rainfall data registered by siphoned rainfall recorder (SRW) devices have been widely used for a long time in rainfall intensity investigations. A relatively known counting error of the SRW devices is the siphoning error, when the registration of rainfall is blocked temporarily, during the drainage of measure tank. This issue causes a systematic underestimation in the rainfall and rainfall intensity measurement results. To reduce its consequences, a data correction is crucial when SRW data are used, for example as a reference for climate comparison studies, or for proceeding of intensity-duration-frequency curves, etc. In this paper, a formula is presented to fix the siphonage error of SRW devices for historical rainfall data. The early measures were processed in a significant percentage of cases, and sometimes the original measurement results (registration ribbon) have been lost. An essential advantage of the presented formula is that it can be applied for these processed data, which show only the intensity of a known length time interval. For this correction, the average rainfall intensity and the length of the time window are needed, over the physical parameters of the SRW device. The data correction can provide a fixed value of the rainfall intensity, which is undoubtedly closer to the real average rainfall intensity. The importance of this formula is in the reprocessing and validation of the historical rainfall intensity data, measured by siphoned rainfall recorders.


Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1853
Author(s):  
Tang ◽  
Xu ◽  
Jia ◽  
Luo ◽  
Shao

Low impact development (LID) devices or green infrastructures have been advocated for urban stormwater management worldwide. Currently, the design and evaluation of LID devices adopt the Intensity-Duration-Frequency (IDF) method, which employs the average rainfall intensity. However, due to variations of rainfall intensity during a storm event, using average rainfall intensity may generate certain errors when designing a LID device. This paper presents an analytical study to calculate the magnitude of such errors with respect to LID device design and associated device performance evaluation. The normal distribution rainfall (NDR) with different standard deviations was employed to represent realistic rainfall processes. Compared with NDR method, the error in sizing the LID device was determined using the IDF method. Moreover, the overflow difference calculated using the IDF method was evaluated. We employed a programmed hydrological model to simulate different design scenarios. Using storm data from 31 regions with different climatic conditions in continental China, the results showed that different rainfall distributions (as represented by standard deviations (σ) of 5, 3, and 2) have little influence on the design depth of LID devices in most regions. The relative difference in design depth using IDF method was less than 1.00% in humid areas, −0.61% to 3.97% in semi-humid areas, and the significant error was 46.13% in arid areas. The maximum absolute difference in design depth resulting from the IDF method was 2.8 cm. For a LID device designed for storms with a 2-year recurrence interval, when meeting for the 5-year storm, the relative differences in calculated overflow volume using IDF method ranged from 19.8% to 95.3%, while those for the 20-year storm ranged from 7.4% to 40.5%. The average relative difference of the estimated overflow volume was 29.9% under a 5-year storm, and 12.0% under a 20-year storm. The relative difference in calculated overflow volumes using IDF method showed a decreasing tendency from northwest to southeast. Findings from this study suggest that the existing IDF method is adequate for use in sizing LID devices when the design storm is not usually very intense. However, accurate rainfall process data are required to estimate the overflow volume under large storms.


Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2337
Author(s):  
Sherien Fadhel ◽  
Mustafa Al Aukidy ◽  
May Samir Saleh

Most areas around the world lack fine rainfall records which are needed to derive Intensity-Duration-Frequency (IDF) curves, and those that are available are in the form of daily data. Thus, the disaggregation of rainfall data from coarse to fine temporal resolution may offer a solution to that problem. Most of the previous studies have adopted only historical rainfall data as the predictor to disaggregate daily rainfall data to hourly resolution, while only a few studies have adopted other historical climate variables besides rainfall for such a purpose. Therefore, this study adopts and assesses the performance of two methods of rainfall disaggregation one uses for historical temperature and rainfall variables while the other uses only historical rainfall data for disaggregation. The two methods are applied to disaggregate the current observed and projected modeled daily rainfall data to an hourly scale for a small urban area in the United Kingdom. Then, the IDF curves for the current and future climates are derived for each case of disaggregation and compared. After which, the uncertainties associated with the difference between the two cases are assessed. The constructed IDF curves (for the two cases of disaggregation) agree in the sense that they both show that there is a big difference between the current and future climates for all durations and frequencies. However, the uncertainty related to the difference between the results of the constructed IDF curves (for the two cases of disaggregation) for each climate is considerable, especially for short durations and long return periods. In addition, the projected and current rainfall values based on disaggregation case which adopts historical temperature and rainfall variables were higher than the corresponding projections and current values based on only rainfall data for the disaggregation.


2021 ◽  
Vol 16 (3) ◽  
pp. 898-907
Author(s):  
S. KOKILAVANI S. KOKILAVANI ◽  
SP. Ramanathan SP. Ramanathan ◽  
GA. Dheebakaran ◽  
N.K. Sathyamoorthy ◽  
B. Arthirani B. Arthirani ◽  
...  

Understanding the pattern of regional climatic extremes is essential for creating an important adaptation measure to safeguard farmers from monsoon tantrums. This paper focuses on the rainfall variability and intensity for spatially different locations of Tamil Nadu. The daily rainfall data over a period of 30 years (1990-2019) for the study locations were collected from the constituent research centres of TNAU. The results indicated that an increasing trend in SWM rainfall was observed in Coimbatore (209.3 to 300.6mm), Ooty (681.4 to 703.1mm), Aduthurai (227.8 to 320.6mm), Kovilpatti (132.8 to 141.3 mm) while the decreasing trend was observed in rest of the places. A decreasing trend was reported in general for all the places during NEM. The decreasing trend in the number of rainy days was registered in Kovilpatti, Virudhunagar and Killikulam that exhibits an alert in modifying the crop planning programme in those areas. The frequency of rainfall intensity revealed that except Ooty, the number of Heavy Rain (HR) to VHR(VHR) was found to be meagre to absent in most of the study locations.


2017 ◽  
Vol 75 (8) ◽  
pp. 1971-1981 ◽  
Author(s):  
H. Madsen ◽  
I. B. Gregersen ◽  
D. Rosbjerg ◽  
K. Arnbjerg-Nielsen

A regional partial duration series (PDS) model is applied for estimation of intensity duration frequency relationships of extreme rainfalls in Denmark. The model uses generalised least squares regression to relate the PDS parameters to gridded rainfall statistics from a dense network of rain gauges with daily measurements. The Poisson rate is positively correlated to the mean annual precipitation for all durations considered (1 min to 48 hours). The mean intensity can be assumed constant over Denmark for durations up to 1 hour. For durations larger than 1 hour, the mean intensity is significantly correlated to the mean extreme daily precipitation. A Generalised Pareto distribution with a regional constant shape parameter is adopted. Compared to previous regional studies in Denmark, a general increase in extreme rainfall intensity for durations up to 1 hour is found, whereas for larger durations both increases and decreases are seen. A subsample analysis is conducted to evaluate the impacts of non-stationarities in the rainfall data. The regional model includes the non-stationarities as an additional source of uncertainty, together with sampling uncertainty and uncertainty caused by spatial variability.


Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1750 ◽  
Author(s):  
Muhammad Noor ◽  
Tarmizi Ismail ◽  
Eun-Sung Chung ◽  
Shamsuddin Shahid ◽  
Jang Sung

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.


2017 ◽  
Vol 47 (1) ◽  
pp. 15-21
Author(s):  
Alcinei Ribeiro Campos ◽  
João Batista Lopes da Silva ◽  
Glenio Guimarães Santos ◽  
Rafael Felippe Ratke ◽  
Itauane Oliveira de Aquino

ABSTRACT Rainfall is the primary water source for hydrographic basins. Hence, the quantification and knowledge of its temporal and spatial distribution are indispensable in dimensioning hydraulic projects. This study aimed at assessing the fit of a series of rainfall data to different probability models, as well as estimating parameters of the intensity-duration-frequency (IDF) equation for rain stations of the Paraíba State, Brazil. The rainfall data of each station were obtained from the Brazilian Water Agency databanks. To estimate the maximum daily rainfall of each station and return period (5, 10, 15, 25, 50 and 100 years), the following probability distributions were used: Gumbel, Log-Normal II, Log-Normal III, Pearson III and Log-Pearson III. The estimation of rainfall in durations of 5-1,440 min was carried out by daily rainfall disaggregation. The adjustment of the IDF equation was performed via nonlinear multiple regression, using the nonlinear generalized reduced gradient interaction method. When compared to the data observed, the intense rainfall equations for most stations showed goodness of fit with coefficients of determination above 0.99, which supports the methodology applied in this study.


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