River Flow Estimation under Future Climate Conditions: The Case Study of the Nith River Basin Using SWAT Modeling Tools
Received: 22 May 2025 | Revised: 6 September 2025 and 28 September 2025 | Accepted: 5 October 2025 | Online: 15 December 2025
Corresponding author: Rana Md. Sohel
Abstract
The impact of climate change may pose a threat to the magnitude and occurrence of river flow. Efficient watershed management requires a rational approach to predicting future climate change impacts. The Nith River in Ontario, Canada has experienced frequent flooding as a result of extreme storm events every year or sometimes multiple times per year. The purpose of this study is to provide guidance on building watershed resiliency through flooding condition assessments and the use of climate scenarios for the watershed. Three future climate scenarios are assessed, to identify the most suitable one. The North American Regional Climate Change Assessment Program (NARCCAP) provided a scenario using Canadian Regional Climate Model and Canadian Global Climate Model version 3 (CRCM-CGCM3); another scenario involved Regional Climate Model version 3 and CGCM3 (RCM3-CGCM3), while the Ministry of Natural Resources (MNR) provided an additional scenario. This statistical analysis represents the best match between the observed and projected data of MNR. According to future climatic data, precipitation-runoff was calculated by a hydrological model which is known as the Soil and Water Assessment Tool (SWAT). Calibration and validation were performed to optimize the model's results. Bias factors were calculated from the observed period data and used to adjust future runoff estimates. This research showed significant changes in storm magnitude and frequency due to climate change, providing insights for watershed management and development. However, the results may vary, if different climate scenarios and precipitation-runoff models are used.
Keywords:
climate change, Nith River, watershed resiliency, SWAT model, precipitation-runoff modelDownloads
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Copyright (c) 2025 Rahman Mohammad Hafizur, Seidou Ousmanne, Rana Md. Sohel
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