Asset Details
Do you wish to reserve the book?
Estimating Extreme Tidal Range by Frequency Analysis at Iraqi Coastal Water
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Estimating Extreme Tidal Range by Frequency Analysis at Iraqi Coastal Water
Do you wish to request the book?
Estimating Extreme Tidal Range by Frequency Analysis at Iraqi Coastal Water
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Estimating Extreme Tidal Range by Frequency Analysis at Iraqi Coastal Water
2025
Overview
Iraqi coast is one of the most vulnerable regions to the effects of flooding as a result of extreme sea level events, with a population of over one million people along it, and a level of less than one meter above sea level. When long data are accessible, Federal Emergency Management Agency of the United States (FEMA) recommends frequency analysis in analyzing extreme water levels. Therefore, 54 years of data from the Shatt Al-Arab Outer Bar Station, located near the Al-Faw peninsula in the Shatt Al-Arab River Estuary utilized in this study to estimate the 100-year Annual Maximum Tidal Range (AMTR). The efficacy of four popular frequency distribution models was assessed. Based on a high correlation coefficient of 0.997 and a low Chi-square value of 0.1903, the Gumbel model gives the most accurate estimate of a 55-year AMTR of 4.024 m, with a small error of about 0.024 m compared to the recorded value. The Weibull and Lognormal distribution models predict an underestimation of the 55-year AMTR by 0.095 m and 0.07 m, respectively, while the GEV distribution model predicts an overestimation of the 55-year AMTR by 0.084 m. Consequently, choosing a suitable distribution model can enhance the accuracy of your predictions.
Publisher
IOP Publishing
