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ORIGINAL RESEARCH article

Front. Water

Sec. Water and Hydrocomplexity

Volume 7 - 2025 | doi: 10.3389/frwa.2025.1558218

Exploring Alternate Coupling Inputs of Data-Driven Model for Optimum Daily Streamflow Prediction in Calibrated SWAT-BiLSTM Rainfall-Runoff Modeling

Provisionally accepted
Khalil Ahmad Khalil Ahmad 1,2Mudassar Iqbal Mudassar Iqbal 1*Muhammad Atiq Ur Rehman Tariq Muhammad Atiq Ur Rehman Tariq 1,3Afed Ullah Khan Afed Ullah Khan 2Abdullah Nadeem Abdullah Nadeem 1Kseniia Usanova Kseniia Usanova 4,5Hamad Almujibah Hamad Almujibah 6Hashem Alyami Hashem Alyami 7Muhammad Abid Muhammad Abid 8
  • 1 Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore 54890, Pakistan, Lahore, Pakistan
  • 2 Department of Civil Engineering, University of Engineering and Technology Peshawar (Bannu Campus), 28100 Bannu, Pakistan, Peshawar, Khyber Pakhtunkhwa, Pakistan
  • 3 College of Engineering, IT and Environment, Charles Darwin University, Darwin, Northern Territory, Australia
  • 4 Scientific and Technological Complex for Digital Engineering in Construction, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia, Petersburg, Russia
  • 5 Academy of Engineering, RUDN University, 117198 Moscow, Russia, Moscow, Moscow Oblast, Russia
  • 6 Department of Civil Engineering, College of Engineering, Taif University, Taif, Saudi Arabia
  • 7 Department of Computer Science, College of Computers and Information Technology, Taif University, P.O.Box 11099, Taif 21944, Saudi Arabia, Taif, Saudi Arabia
  • 8 College of Aerospace and Civil Engineering, Harbin Engineering University, 150001, China, Harbin, Jilin Province, China

The final, formatted version of the article will be published soon.

    Accurate streamflow prediction in mountainous regions is vital for sustaining water resources in downstream areas, ensuring reliable availability for agriculture, energy, and consumption. However, physically based prediction models are prone to substantial uncertainties due to complex processes and the inherent variability in model parameters and parameterization. This study addresses these challenges by exploring alternative coupling inputs for data-driven (DD) models to optimize daily streamflow prediction in a calibrated SWAT-BiLSTM rainfall-runoff model within the Astore sub-basin of the Upper Indus Basin (UIB), Pakistan. The research explores two standalone models (SWAT and BiLSTM) and three alternative coupling inputs: conventional climatic variables (precipitation and temperature), cross-correlation based selected inputs, and exclusion of direct climatic inputs, in calibrated SWAT-BiLSTM model. The study spans calibration, validation, and prediction periods from 2007 to 2011, 2012 to 2015 and 2017 to 2019, respectively. Based on compromise programing (CP) ranking, SWAT-C-BiLSTM (QP) and SWAT-C-BiLSTM (T1 QP) showed competent performances followed by BiLSTM, SWAT-C-BiLSTM (PTQP), and SWAT. These findings highlight that excluding climatic parameters alternative SWAT-C-BiLSTM (QP) enhances the couple model’s accuracy sufficiently and underscores the potential for this approach to contribute to sustainable water resource management.

    Keywords: advancement in rainfall-runoff1, bilstm2, inputs selection3, Streamflow Pprediction4, SWAT-Bilstm modeling5, supervised machine learning6

    Received: 09 Jan 2025; Accepted: 12 Mar 2025.

    Copyright: © 2025 Ahmad, Iqbal, Tariq, Khan, Nadeem, Usanova, Almujibah, Alyami and Abid. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Mudassar Iqbal, Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore 54890, Pakistan, Lahore, Pakistan

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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