Quantifying the Impacts of Climate Change on Streamflow Dynamics of Two Major Rivers of the Northern Lake Erie Basin in Canada

Binbin Zhang, Narayan Kumar Shrestha, Prasad Daggupati, Ramesh Rudra, Rituraj Shukla, Baljeet Kaur and Jun Hou
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Binbin Zhang: School of Engineering, University of Guelph, 50 Stone Rd E, Guelph, ON N1G 2W1, Canada
Narayan Kumar Shrestha: School of Engineering, University of Guelph, 50 Stone Rd E, Guelph, ON N1G 2W1, Canada
Prasad Daggupati: School of Engineering, University of Guelph, 50 Stone Rd E, Guelph, ON N1G 2W1, Canada
Ramesh Rudra: School of Engineering, University of Guelph, 50 Stone Rd E, Guelph, ON N1G 2W1, Canada
Rituraj Shukla: School of Engineering, University of Guelph, 50 Stone Rd E, Guelph, ON N1G 2W1, Canada
Baljeet Kaur: School of Engineering, University of Guelph, 50 Stone Rd E, Guelph, ON N1G 2W1, Canada
Jun Hou: School of Engineering, University of Guelph, 50 Stone Rd E, Guelph, ON N1G 2W1, Canada

Sustainability, 2018, vol. 10, issue 8, 1-23

Abstract: This paper focuses on understanding the effects of projected climate change on streamflow dynamics of the Grand and Thames rivers of the Northern Lake Erie (NLE) basin. A soil water assessment tool (SWAT) model is developed, calibrated, and validated in a base-period. The model is able to simulate the monthly streamflow dynamics with ‘Good’ to ‘Very Good’ accuracy. The calibrated and validated model is then subjected with daily bias-corrected future climatic data from the Canadian Regional Climate Model (CanRCM4). Five bias-correction methods and their 12 combinations were evaluated using the Climate Model data for hydrologic modeling (CMhyd). Distribution mapping (DM) performed the best and was used for further analysis. Two future time-periods and two IPCC AR5 representative concentration pathways (RCPs) are considered. Results showed marked temporal and spatial variability in precipitation (−37% to +63%) and temperature (−3 °C to +14 °C) changes, which are reflected in evapotranspiration (−52% to +412%) and soil water storage (−60% to +12%) changes, resulting in heterogeneity in streamflow (−77% to +170%) changes. On average, increases in winter (+11%), and decreases in spring (–33%), summer (−23%), and autumn (−15%) streamflow are expected in future. This is the first work of this kind in the NLE and such marked variability in water resources availability poses considerable challenges to water resources planners and managers.

Keywords: climate change; bias-correction; Northern Lake Erie basin; streamflow; SWAT (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:10:y:2018:i:8:p:2897-:d:163908

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