Developing model for forecasting rainfall intensity-duration-frequency curves using artificial neural network in Al-Najaf Region, Iraq
by Ayad K. Hussein; Hayder H. Kareem; Hussein A. Almadani
International Journal of Hydrology Science and Technology (IJHST), Vol. 12, No. 4, 2021

Abstract: The surface and subterranean water sources are greatly affected by the precipitation's intensity (I), sustainability (duration-D) as well as its return period (frequency-F). Therefore, attention is directed to identify the relationship between these elements, especially in present time which suffers from recession of rain. The research focuses on establishing the relationship (IDF) in Al-Najaf Governorate, Iraq. Using the artificial neural network (ANN) and MATLAB, a new and rapid method is developed to link these parts. The model is calibrated using multiple methods and the results matched the collected data. In addition, the accuracy of the results obtained from the developed program/model is compared to programs of other researchers and its accuracy is greater and striking. The ruling curve IDF of Al-Najaf Governorate is derived which will help in extracting these components easily. The developed program/model can be interesting for various locations with only changing its inputs.

Online publication date: Wed, 20-Oct-2021

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