Issue |
BIO Web Conf.
Volume 109, 2024
Conference on Water, Agriculture, Environment and Energy (WA2EN2023)
|
|
---|---|---|
Article Number | 01004 | |
Number of page(s) | 11 | |
DOI | https://doi.org/10.1051/bioconf/202410901004 | |
Published online | 20 May 2024 |
Prediction of Flood Events from the Nekor River Discharge Using the Flood Frequential Analysis Method
1 Laboratory of Engineering Sciences and Applications, National School of Applied Sciences of Al-Hoceima, Abdelmalek Essaâdi University, Ajdir 03, Morocco
2 Laboratory of Functional Ecology and Environment Engineering, Faculty of sciences and techniques, University of Sidi Mohammed Ben Abdellah, Fez 30500, Morocco
This work aims to analyze the yearly most extreme release of the Nekor River monitoring station Tamellaht between 1973 and 2011 and to predict possible future events using the Flood Frequency Analysis Method (FFA). We use the four most estimated distributions that are accessible for prediction of hydrological risk: the three Log Normal, LogPerson Type III, Weibull and GAMMA distributions, and conclude that the Weibull distribution is the suitable statistical model that describe well into our data series, even though the other distributions show data adjustment. Given the Weibull dispersion, the upsides of 580.3 m3/s, 1339 m3/s and 2146.7 m3/s are for the time of return of 10, 50 and 100 years, individually, still high relying upon the semi-dry environment that wins around this region. In fact, the period of extreme returns of the 10th period which can cause dangerous flooding especially considering the mountainous characteristics of the region. The magnitude of the floods is greater because the return period is greater, which explains the semi-arid climate of this region. In addition, a simple statistical description shows that the maximum flow trend has declined over the years, reflecting a possible impact of climate change phenomena.
Key words: Flood frequency analysis (FFA) / semi-arid climate / Nekour watershed / maximum annual discharge / return period
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.