Spatiotemporal variability of runoff events in response to rainfall, snowmelt, and rain-on-snow in the Lake Erie Basin. Ali, G., Siebert, K., & Mizero, S. M. Journal of Hydrology: Regional Studies, 53:101774, June, 2024. ![Spatiotemporal variability of runoff events in response to rainfall, snowmelt, and rain-on-snow in the Lake Erie Basin [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Study Region The Lake Erie Basin spanning Canada and the United States. Study Focus Countless studies have performed event-based hyetograph-hydrograph analyses. However, most studies focused on experimental forested catchments and rainfall-runoff analyses, thereby neglecting larger, mid-latitude, heterogenous watersheds where snowmelt and rain-on-snow events can generate significant runoff. The goal of the present study was, therefore, to examine runoff generation in contrasted watersheds, by: (1) quantifying the spatiotemporal variability of event-specific runoff response across the Lake Erie Basin; 2) assessing the difference in runoff response characteristics based on precipitation type; and 3) identifying the influence of event precipitation and watershed characteristics on runoff response. Daily gridded climate and gauged streamflow data spanning 2000–2019 were used for 99 watersheds, resulting in the analysis of 28,123 rainfall, snowmelt, rain-on-snow and mixed events and their associated runoff responses. New Hydrological Insights for the Region Rainfall events were rarely identified as the triggers of the largest runoff responses. Conversely, snowmelt and rain-on-snow events led to high-magnitude and flashy runoff responses for 70 out of 99 watersheds. Watershed characteristics pertaining to topography, soil, and land use were good predictors of the temporal variability of runoff response metrics. Given the link between runoff-driven nutrient mobilization and recurrent algal blooms in Lake Erie, this study offers a comprehensive assessment of the variability of runoff responses and triggering precipitation events across the large transboundary basin.
@article{ali_spatiotemporal_2024,
title = {Spatiotemporal variability of runoff events in response to rainfall, snowmelt, and rain-on-snow in the {Lake} {Erie} {Basin}},
volume = {53},
issn = {2214-5818},
url = {https://www.sciencedirect.com/science/article/pii/S2214581824001228},
doi = {10.1016/j.ejrh.2024.101774},
abstract = {Study Region
The Lake Erie Basin spanning Canada and the United States.
Study Focus
Countless studies have performed event-based hyetograph-hydrograph analyses. However, most studies focused on experimental forested catchments and rainfall-runoff analyses, thereby neglecting larger, mid-latitude, heterogenous watersheds where snowmelt and rain-on-snow events can generate significant runoff. The goal of the present study was, therefore, to examine runoff generation in contrasted watersheds, by: (1) quantifying the spatiotemporal variability of event-specific runoff response across the Lake Erie Basin; 2) assessing the difference in runoff response characteristics based on precipitation type; and 3) identifying the influence of event precipitation and watershed characteristics on runoff response. Daily gridded climate and gauged streamflow data spanning 2000–2019 were used for 99 watersheds, resulting in the analysis of 28,123 rainfall, snowmelt, rain-on-snow and mixed events and their associated runoff responses.
New Hydrological Insights for the Region
Rainfall events were rarely identified as the triggers of the largest runoff responses. Conversely, snowmelt and rain-on-snow events led to high-magnitude and flashy runoff responses for 70 out of 99 watersheds. Watershed characteristics pertaining to topography, soil, and land use were good predictors of the temporal variability of runoff response metrics. Given the link between runoff-driven nutrient mobilization and recurrent algal blooms in Lake Erie, this study offers a comprehensive assessment of the variability of runoff responses and triggering precipitation events across the large transboundary basin.},
urldate = {2024-08-12},
journal = {Journal of Hydrology: Regional Studies},
author = {Ali, Geneviève and Siebert, Krystal and Mizero, Steven Mugisha},
month = jun,
year = {2024},
keywords = {NALCMS},
pages = {101774},
}
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The goal of the present study was, therefore, to examine runoff generation in contrasted watersheds, by: (1) quantifying the spatiotemporal variability of event-specific runoff response across the Lake Erie Basin; 2) assessing the difference in runoff response characteristics based on precipitation type; and 3) identifying the influence of event precipitation and watershed characteristics on runoff response. Daily gridded climate and gauged streamflow data spanning 2000–2019 were used for 99 watersheds, resulting in the analysis of 28,123 rainfall, snowmelt, rain-on-snow and mixed events and their associated runoff responses. New Hydrological Insights for the Region Rainfall events were rarely identified as the triggers of the largest runoff responses. Conversely, snowmelt and rain-on-snow events led to high-magnitude and flashy runoff responses for 70 out of 99 watersheds. 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However, most studies focused on experimental forested catchments and rainfall-runoff analyses, thereby neglecting larger, mid-latitude, heterogenous watersheds where snowmelt and rain-on-snow events can generate significant runoff. The goal of the present study was, therefore, to examine runoff generation in contrasted watersheds, by: (1) quantifying the spatiotemporal variability of event-specific runoff response across the Lake Erie Basin; 2) assessing the difference in runoff response characteristics based on precipitation type; and 3) identifying the influence of event precipitation and watershed characteristics on runoff response. Daily gridded climate and gauged streamflow data spanning 2000–2019 were used for 99 watersheds, resulting in the analysis of 28,123 rainfall, snowmelt, rain-on-snow and mixed events and their associated runoff responses.\nNew Hydrological Insights for the Region\nRainfall events were rarely identified as the triggers of the largest runoff responses. 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