scholarly journals Modeling of IDF curves for stormwater design in Makkah Al Mukarramah region, The Kingdom of Saudi Arabia

2018 ◽  
Vol 10 (1) ◽  
pp. 954-969 ◽  
Author(s):  
Hatem A. Ewea ◽  
Amro M. Elfeki ◽  
Jarbou A. Bahrawi ◽  
Nassir S. Al-Amri
Keyword(s):  
Saudi Arabia ◽  
Probability Distributions ◽  
Daily Rainfall ◽  
Type I ◽  
Kingdom Of Saudi Arabia ◽  
Hourly Data ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Negative Impacts

Abstract Reducing the negative impacts of flooding in Makkah AL Mukarramah region in the Kingdom of Saudi Arabia (KSA) is of utmost importance. In the last decade, there are huge mega infrastructure projects in KSA in general and in Makkah AL Mukarramah region in particular. These projects require adequate stormwater drainage systems. Since, the availability of rainfall and runoff data are scarce, engineers and hydrologists rely on models developed in temperature regions that are not hydrologically similar from temperate regions. This leads to inaccurate designs of stormwater facilities. Therefore, deveoping in situ Intensity-Duration-Frequency (IDF) curves is a must in this arid region. This paper aims at modeling IDF curves for Makkah Al-Mukarramah region. Maximum annual daily rainfall series of 80 storms (with sub-hourly and hourly data) from four stations are investigated through six different probability distributions. Consequently, rainfall depth-duration-frequency models and curves are derived. Results revealed that the Gumbel Type I is the optimal one. Thus, it is used to deduce the IDF curves and relations for each station and for the region as a whole. The R2 value for fitting power-lawfunction (i = a Db) to the data is very high for the IDF parameters. The R2 for the coefficient parameter, a, is between 0.9999 and 0.9988 while it ranges between 0.8754 and 0.8039 for exponent parameter, b. High correlation coefficient (more than 0.95) has been obtained. The resulting IDF models are strongly recommended for rigorous, effective and safe design of the stormwater systems in Makkah Al-Mukarramah region.

scholarly journals Deriving intensity–duration–frequency (IDF) curves using downscaled in situ rainfall assimilated with remote sensing data

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yabin Sun ◽  
Dadiyorto Wendi ◽  
Dong Eon Kim ◽  
Shie-Yui Liong
Keyword(s):  
Remote Sensing ◽  
Daily Rainfall ◽  
Remote Sensing Data ◽  
Rainfall Events ◽  
Hourly Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Improved Accuracy

AbstractThe rainfall intensity–duration–frequency (IDF) curves play an important role in water resources engineering and management. The applications of IDF curves range from assessing rainfall events, classifying climatic regimes, to deriving design storms and assisting in designing urban drainage systems, etc. The deriving procedure of IDF curves, however, requires long-term historical rainfall observations, whereas lack of fine-timescale rainfall records (e.g. sub-daily) often results in less reliable IDF curves. This paper presents the utilization of remote sensing sub-daily rainfall, i.e. Global Satellite Mapping of Precipitation (GSMaP), integrated with the Bartlett-Lewis rectangular pulses (BLRP) model, to disaggregate the daily in situ rainfall, which is then further used to derive more reliable IDF curves. Application of the proposed method in Singapore indicates that the disaggregated hourly rainfall, preserving both the hourly and daily statistic characteristics, produces IDF curves with significantly improved accuracy; on average over 70% of RMSE is reduced as compared to the IDF curves derived from daily rainfall observations.

scholarly journals Spatiotemporal Variability of Intensity–Duration–Frequency (IDF) Curves in Arid Areas: Wadi AL-Lith, Saudi Arabia as a Case Study

Hydrology ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 6
Author(s):  
Ibrahim H. Elsebaie ◽  
Mohamed El Alfy ◽  
Atef Qasem Kawara
Keyword(s):  
Saudi Arabia ◽  
Daily Rainfall ◽  
Spatiotemporal Variability ◽  
Mountainous Area ◽  
Arid Areas ◽  
Return Periods ◽  
Maximum Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency

In arid areas, flashflood water management is a major concern due to arid climate ambiguity. The examining and derivation of intensity–duration–frequency (IDF) curves in an urban arid area under a variety of terrain patterns and climatic changes is anticipated. Several flood events have been reported in the Al-Lith region of western Saudi Arabia that took away many lives and caused disruption in services and trade. To find and examine the extremities and IDF curves, daily rainfall data from 1966 to 2018 is used. The IDF curves are created for a variety of return periods and climate scenarios in three terrain variabilities. This research examines various distributions to estimate the maximum rainfall for several metrological stations with varying return periods and terrain conditions. Three main zones are identified based on ground elevation variability and IDF distributions from upstream in the eastern mountainous area to downstream in the western coastal area. These IDF curves can be used to identify vulnerable hotspot areas in arid areas such as the Wadi AL-Lith, and flood mitigation steps can be suggested to minimize flood risk.

scholarly journals Physical Parameterization of IDF Curves Based on Short-Duration Storms

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1813
Author(s):  
Gutierrez-Lopez ◽  
Jimenez Hernandez ◽  
Escalante Sandoval
Keyword(s):  
Numerical Procedure ◽  
Rainfall Duration ◽  
Storm Duration ◽  
C Value ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Parametric Adjustment ◽  
Physical Parameterization ◽  
Great Advance

Intensity–duration–frequency (IDF) curves are empirical mathematical formulations that have been used for years in engineering for planning, design, and operation of hydraulic projects. The expression proposed by Sherman (1931) has been validated and used largely by many researchers. In all cases, the four parameters of this formulation are obtained through a numerical procedure. Although these parameters are obtained from historical rainfall observations, the optimization of these parameters implies an infinite combination between them and all those solutions would be valid. Of the four parameters, only one of them (C) has units, and for this reason, a physical sense of parameter C is searched for. Having certainty that some of them can be measured in situ would represent a great advance for modern hydrology. With data from 523 storms monitored every minute, a parametric adjustment was made to the Sherman equation and the typical duration of storms at each site was also obtained. To demonstrate how rainfall intensities vary with the change in C value, rainfall intensities calculations for of 5, 10, 15, and 20 min rainfall duration are used to validate the proposed methodology. The results show that typical storm duration is correlated with the additive parameter of Sherman’s formula.

Estimating IDF-Relations consistently using a duration-dependent GEV with spatial covariates

2020 ◽  
Author(s):  
Jana Ulrich ◽  
Madlen Peter ◽  
Oscar E. Jurado ◽  
Henning W. Rust
Keyword(s):  
Extreme Precipitation ◽  
Probability Distributions ◽  
Skill Score ◽  
Exceedance Probability ◽  
Ungauged Sites ◽  
Extreme Precipitation Events ◽  
One Step ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
A Site

<p>Intensity-Duration-Frequency (IDF) Curves are a popular tool in Hydrology for estimating the properties of extreme precipitation events. They describe the relationship between rainfall intensity and duration for a given non-exceedance probability (or frequency). For a site where precipitation measurements are available, these curves can be estimated consistently over durations using a duration-dependent GEV (d-GEV, after Koutsoyiannis et al. 1998). In this approach, the probability distributions are modeled simultaneously for all durations.</p><p>Additionally, we integrate covariates to describe the spatial variability of the d-GEV parameters so that we can model the distribution of extreme precipitation for a range of durations and locations in one step. Thus IDF Curves can be estimated even at ungauged sites. Further advantages are parameter reduction and more efficient use of the available data. We use the Quantile Skill Score to investigate under which conditions this method leads to an improved estimate compared to the single-site approach and to evaluate the performance at ungauged sites.</p>

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 Anatomical Evaluation of Root and Root Canal Configuration of Permanent Maxillary Dentition in the Population of the Kingdom of Saudi Arabia

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Mohammed Mashyakhy ◽  
Mohammed Awawdeh ◽  
Abdulaziz Abu-Melha ◽  
Bushra Alotaibi ◽  
Nada AlTuwaijri ◽  
...  
Keyword(s):  
Systematic Review ◽  
Saudi Arabia ◽  
Sample Size ◽  
Root Canal ◽  
Case Series ◽  
Deciduous Teeth ◽  
Large Sample Size ◽  
International Studies ◽  
Type I ◽  
Kingdom Of Saudi Arabia

Aim. This study is aimed at combining the sample sizes of all studies on permanent maxillary teeth conducted in different regions of the Kingdom of Saudi Arabia (KSA) to obtain a large sample size that represents the population of the KSA. The outcome of these combined studies is compared with international studies in terms of the number of roots, number of canals, and canal configurations on the basis of Vertucci’s classification. Methodology. The studies were systematically reviewed using the Preferred Reporting Items for Systematic Review and Meta-analysis chart. Studies were included in the analysis if they were conducted in the KSA, involved permanent human maxillary teeth, and had a sample of more than 10 teeth (power). By contrast, studies were excluded if they involved deciduous teeth in the sample size, investigated nonhuman teeth, were not conducted in the KSA, and were case reports, case series, review studies, and anomalies. Relevant literature was searched from PubMed, Scopus, Web of Science, Embase, Cochrane, and Direct Science by two calibrated teams, starting in August 2020, without time limits or language restrictions. Results. The database searches and cross-referencing identified a total of 19 relevant studies. All maxillary canines ( N = 1,018 ) had one root, whereas 98.4% had one canal and 98.3% had Vertucci type I. Moreover, 63.2% of the maxillary first premolars had two roots, and 91.4% had two canals. The most common Vertucci root canal configuration was type IV (64.6%). The maxillary second premolars mostly had one root (84.4%) and one canal (50.4%). The most common canal configuration was Vertucci type I (47.1%). The majority of maxillary first molars had three roots (98.9%), 48.7% of which had three canals, and 46.4% had four canals. The most prevalent feature of the canal morphology of mesiobuccal roots was Vertucci type II (35.3%). The investigated maxillary second molars had three roots, 88.0% of which had three canals. Conclusion. This systematic review represents the Saudi population since samples were combined from different studies from different regions of the country. Variations in findings were observed in the same group of teeth from different regions and the same region, while the overall combined samples results fell within the range of other international studies.

scholarly journals ANALISIS CURAH HUJAN UNTUK MEMBUAT KURVA INTENSITY-DURATION-FREQUENCY (IDF) PADA SUB DAS METRO

2013 ◽  
Vol 11 (1) ◽  
Author(s):  
Ir. Ernawan S, MT ◽  
Yuda Al Qadr Latief
Keyword(s):  
Return Period ◽  
Statistical Parameter ◽  
Daily Rainfall ◽  
Rainfall Characteristics ◽  
Period 2 ◽  
Important Input ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Rain Events ◽  
Maximum Daily Rainfall

Ernawan S.1) , Yuda Al Qadr Latief2)1,2) Jurusan Teknik Sipil Universitas Muhammadiyah MalangAlamat korespondensi : Jl. Raya Tlogomas 246 Malang 65144AbstractHydrological conditions in Indonesia and elsewhere is typical, so not all the way and all the concepts can be used to solve the problem of hydrology in Indonesia, especially in the Upstream Brantas River precisely in Sub Watershed of Metro. Rain is an important input component in the hydrological processes. Rainfall characteristics of which are the intensity, duration, depth, and frequency. Intensity related to the duration and frequency can be expressed by curves Intensity-Duration-Frequency (IDF). IDF curves can be used to calculateflood plan to use a rational method.In this study, daily rainfall calculated by frequency analysis begins by determining the mean maximum daily rainfall, then calculate statistical parameter to choose the most suitable distribution. The time is long dominant rainfall event with the greatest frequency of rain events. The intensity is calculated by using the data of observation.Based on the analysis of the frequency of the rain turns to design return period 2, 5, 10, 20, 50 and 100 years in a row is 49; 70; 86; 111; 132 and 155 mm. The results showed that the amount of time the dominant rain events between 4-8 hours. IDF curves in sub watershed of Metro based on the data observations generally showed a pattern where the rainfall is always preceded by a high intensity then progressively decreases. Besides the greater the return period tend to have higher rainfall intensity. The results of this research could bedeveloped even if it may be modified in accordance with the specific conditions subwatershed of Metro.

scholarly journals Uncertainty of Intensity-Duration-Frequency Curves Due to Adoption or Otherwise of the Temperature Climate Variable in Rainfall Disaggregation

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2337
Author(s):  
Sherien Fadhel ◽  
Mustafa Al Aukidy ◽  
May Samir Saleh
Keyword(s):  
Daily Rainfall ◽  
Rainfall Data ◽  
The United Kingdom ◽  
Daily Rainfall Data ◽  
Daily Data ◽  
Idf Curves ◽  
The Difference ◽  
Intensity Duration Frequency ◽  
Historical Temperature ◽  
Temperature Climate

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.

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