Rainfall Intensity–Duration–Frequency (IDF) Curves: Effects of Uncertainty on Flood Protection and Runoff Quantification in Southwestern Saudi Arabia

Al-Areeq, Ahmed M.; Al-Zahrani, Muhammad A.; Chowdhury, Shakhawat

doi:10.1007/s13369-021-06142-0

Cited by 8 publications

(2 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The distribution of flash flood disasters in time and space is uneven [32], which is mainly manifested as different group occurrences of flash flood disasters and different combinations of flash flood disaster types in different regions, which shows the characteristics of regional differentiation; the uneven distribution of the flash flood disasters in time is mainly manifested as the sudden occurrence of disasters. In addition, as flash flood disasters have problems of fast occurrence [33], great difficulty in monitoring [34], and lack of data [35], it is very difficult to accurately identify the location and time of flash floods [36]. With the continuous development of monitoring sensors [37][38][39] and computer technology [40,41], various early identification technologies [42] are more and more widely applied to the research of flash flood disasters.…”

Section: Introductionmentioning

confidence: 99%

Meta-Analysis and Visualization of the Literature on Early Identification of Flash Floods

et al. 2022

View full text Add to dashboard Cite

Flash flood is one of the extremely destructive natural disasters in the world. In recent years, extreme rainfall events caused by global climate change have increased, and flash flood disasters are becoming the main types of natural disasters in the world. Due to the characteristics of strong suddenness, complex disaster-causing factors, great difficulty in prediction and forecast, and the lack of historical data, it is difficult to effectively prevent and control flash flood disaster. The early identification technology of flash floods is not only the basis of flash flood disaster prediction and early warning, but also an effective means of flash flood prevention and control. The paper makes a meta-analysis and visual analysis of 475 documents collected by the Web of Science Document Platform in the past 31 years by comprehensively using Citespace, Vosviewer, Origin, etc. We systematically summarize the research progress and development trend of early identification technology of flash flood disasters from five key research subfields: (1) precipitation, (2) sediment, (3) sensitivity analysis, (4) risk assessment, (5) uncertainty analysis. In addition, we analyze and discuss the main problems encountered in the current research of several subfields and put forward some suggestions to provide references for the prevention and control of flash flood disasters.

show abstract

Section: Introductionmentioning

confidence: 99%

Meta-Analysis and Visualization of the Literature on Early Identification of Flash Floods

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Abdeen et al [23] looked at the distribution of maximum daily rainfall in Saudi Arabia and found that the log-Pearson Type III (LPT III) distribution was the best model. Al-Areeq et al [24] used Gumbel and LPT III distribution to develop IDF curves for five areas (Abha, Al-Baha, Bisha, Gizan, and Khamis Mushait) in the southwestern region of Saudi Arabia. The authors of [25] developed IDF curves for Krishna District, India, using log-normal, normal, and Gumbel distributions.…”

Section: Introductionmentioning

confidence: 99%

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

2021

View full text Add to dashboard Cite

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.

show abstract

Development of intensity–duration–frequency curves for Herat, Afghanistan: enhancing flood risk management and implications for infrastructure and safety

Doost,

Chowdhury,

Al‑Areeq

et al. 2024

Nat Hazards

View full text Add to dashboard Cite

Rainfall Intensity–Duration–Frequency (IDF) Curves: Effects of Uncertainty on Flood Protection and Runoff Quantification in Southwestern Saudi Arabia

Cited by 8 publications

References 34 publications

Meta-Analysis and Visualization of the Literature on Early Identification of Flash Floods

Meta-Analysis and Visualization of the Literature on Early Identification of Flash Floods

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

Development of intensity–duration–frequency curves for Herat, Afghanistan: enhancing flood risk management and implications for infrastructure and safety

Contact Info

Product

Resources

About