Comparing and Modifying Eight Empirical Models of Snowmelt Using Data from Harp Experimental Station in Central Ontario

Abstract

Aims: To modify two empirical models of snowpack and snowmelt, and compare eight such models. Study Design: Test and modify the models by using five years of snow measurements from Harp Lake. Place and Duration of Study: Dorset Environmental Science Centre, Ontario Ministry of Environment, and Department of Geography, Nipissing University, between January 2009 and August 2012. Methodology: The old daily-run WINTER model was the first model. It was modified to create a second model. The enhanced-temperature-index (ETI) model was slightly modified to be the third model. Modified WINTER and ETI were combined into the fourth model. Hydrology model BROOK90 and SWAT were used as the fifth and sixth model, also daily-run. Operating the WINTER and ETI in hourly steps created the seventh and eighth model. The calculated snow water equivalent (SWE) by each model was evaluated against the observed data to give a coefficient of efficiency (CE). Accuracy and performance of the models were compared based on CE values. Results: Modified WINTER model improved original WINTER by 20.7% (CE increased 20.7%). The performance of ETI model was 27.6% higher than the original WINTER. The new combination model produced additional improvement by 40.7 % over the original WINTER, or by 16.5% over the modified WINTER or 10.3% over the ETI. Running the model with hourly time steps rather than daily steps increased model’s accuracy: hourly WINTER raised CE by 15.4% and hourly ETI raised CE by 7.9%. Two watershed hydrology models BROOK90 and SWAT performed even better than the above six simpler snow models. Conclusion: It is suggested that the daily combination model be considered if only daily data is available, or hourly WINTER and ETI models be used if hourly runs are desired while new calibration are required when applying them to any new locations. If data requirements by BROOK90 or SWAT are met, these hydrology models would be tried.