Kirkuk Journal of Engineering Science

Seepage Analysis Through Earthen Dam by Artificial- Neural- Networks (ANNs): Duhok Dam as a Case Study

Document Type : Original Article

Authors

Derin Rauf Saber
Chelang A. Arslan

Department of Civil Engineering, University of Kirkuk, Kirkuk, Iraq

Abstract
An earthen dam is a structure made of soil particles that are bonded together and compacted in layers using mechanical methods. depend on their weight to combat forces such as sliding & overturning. Seepage passage during earth dam is the principal cause of collapse owing to erosion, scouring, and piping. The passage of water during soil can result in the displacement of the particles. Ongoing motion induces erosion. This study depends on Artificial Neural Networks (ANN) for estimation seepage in Duhok dam, utilizing measured upstream water level and flow rate, as well as piezometric head measurements from four distinct parts of the dam structure. The findings indicated excellent model efficacy. Artificial Neural Network models necessitate less field data, rendering them advantageous for dam safety evaluations, providing insights into their relative efficacy in forecasting seepage in earthen dams under diverse scenarios. The results were derived from established statistical metrics R², MAE, MAPE and E-NASH. This research concluded that many ANNs has excellent forecasting capabilities.

Keywords

Earth dam
Multiple ANN
Seepage
Duhok dam
Subjects
Kirkuk Journal of Engineering Science
Volume 1, Issue 1
Summer 2025
Pages 1-11

Home

Guide for Authors

Submit Manuscript

Reviewers

Contact Us