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The Laurentian Great Lakes (hereafter the Great Lakes) comprise the world’s largest surface freshwater system. Over the past two decades, water levels in the Great Lakes have fluctuated drastically, reaching both record highs and lows. Accurate water level forecasting is critical due to the extensive ecosystem and millions of US and Canadian citizens that rely on this valuable resource. One of the most dominant variables for water supply in any freshwater system is surface runoff, which is directly impacted by precipitation amount, type, magnitude, and timing across the system’s land surfaces. Lake Superior, the most upstream of the Great Lakes, receives the greatest amount of seasonal snowfall annually out of all the great Lakes. This snowfall affects both the timing and quantity of runoff into the Great Lakes system and impacts the water supply of the Great Lakes. In this study, I analyzed the patterns of snow water equivalent and its effect on surface runoff in the Lake Superior basin. My results indicate important changes in snow water equivalent and runoff patterns over time. Specifically, I found that, as of 1971, maximum seasonal snow water equivalent is occurring on average 12 days earlier in the spring season. I also found that maximum seasonal runoff is occurring earlier; however, the change in the timing of peak runoff occurred in 1983 and is found to now be on average 11 days earlier than it was before 1983. By advancing an understanding of these relationships and ensuring they are reflected in state-of-the-art modeling systems, I provided critical information for improving the skill of water level forecasts and preparing water managers and communities for future hydrologic changes, including those associated with climate change.
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SnowWaterEquivalent_trainingdata
Snow Water Equivalent dataset contains information about snow water equivalent (SWE), temperature, precipitation, wind speed, relative humidity, and related climate variables across different locations and time periods. It includes daily observations and derived variables for hydrological and climate analysis. An additional column, source, specifies the origin of each data column.
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- Award ID(s):
- 2425687
- PAR ID:
- 10629254
- Publisher / Repository:
- Hugging Face
- Date Published:
- Format(s):
- Medium: X
- Location:
- https://huggingface.co/datasets/Geoweaver/SnowWaterEquivalent_trainingdata
- Institution:
- George Mason University
- Sponsoring Org:
- National Science Foundation
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