Location: Northwest Watershed Research Center
Title: Effects of spatial and temporal variability in surface water inputs on streamflow generation and cessation in the rain–snow transition zoneAuthor
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KIEWIET, LEONIE - Colorado State University |
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TRUJILLO, ERNESTO - Boise State University |
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Hedrick, Andrew |
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Havens, Scott |
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HALE, KATE - University Of Colorado |
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Seyfried, Mark |
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KAMPF, STEPHANIE - Colorado State University |
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GODSEY, SARAH - Idaho State University |
Submitted to: Hydrology and Earth System Sciences
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 3/24/2022 Publication Date: 6/1/2022 Citation: Kiewiet, L., Trujillo, E., Hedrick, A., Havens, S.C., Hale, K., Seyfried, M.S., Kampf, S., Godsey, S. 2022. Effects of spatial and temporal variability in surface water inputs on streamflow generation and cessation in the rain–snow transition zone. Hydrology and Earth System Sciences. 26(10):2779-2796. https://doi.org/10.5194/hess-26-2779-2022. DOI: https://doi.org/10.5194/hess-26-2779-2022 Interpretive Summary: Mountainous regions are receiving more rain and less snow in response to climate change. This is concerning because snowmelt is an important source of water for downstream users and changes in snowfall could affect when and how much water is available. One emerging question is how snowfall decreases affect stream discharge in areas that already receive a mix of rain and snow in winter. We addressed this question by simulating rainfall and snowfall for years that were particularly snowy, rainy, wet and dry. We then compared when and where snowmelt or rainfall reached the ground surface with how much water flowed in the stream and when the stream dried up. We found that a large portion of the incoming water reaches the ground surface beneath snow drifts, especially in the snowy year. Stream discharge was not lower in years that received a smaller portion of precipitation as snow, and the stream also did not dry earlier in these years. Instead, we found that the day at which the stream dried was related to the day at which all snow in the area had melted. These findings indicate that stream discharge tends to depend more on when water reaches the ground surface rather than whether it does so as rain or snowmelt. Technical Abstract: Climate warming affects snowfall fractions and snowpack storage, displaces the rain-snow transition zone towards higher elevations, and impacts discharge timing and magnitude as well as low-flow patterns. However, it remains unknown how variations in the spatial and temporal distribution of precipitation at the rain-snow transition zone affect discharge. To investigate this, we used observations from eleven weather stations and snow depths measured in one lidar survey to force a spatially distributed snowpack model (iSnobal/Automated Water Supply Model) in a semi-arid, 1.8 km2 headwater catchment at the rain-snow transition zone. We focused on surface water inputs (SWI; the summation of rainfall and snowmelt) for four years with contrasting climatological conditions (wet, dry, rainy and snowy) and compared simulated SWI to measured discharge. We obtained a strong spatial agreement between snow depth from the lidar survey and model (r2: 0.88), and a median Nash-Sutcliffe Efficiency (NSE) of 0.65 for simulated and measured snow depths for all modelled years (0.75 for normalized snow depths). The spatial pattern of SWI was consistent between the four years, with north-facing slopes producing 1.09 to 1.25 times more SWI than south-facing slopes, and snow drifts producing up to six times more SWI than the catchment average. We found that discharge in a snowy year was almost twice as high as in a rainy year, despite similar SWI. However, years with a lower snowfall fraction did not always have lower annual discharge nor earlier stream drying. Instead, we found that the dry-out date at the catchment outlet was positively correlated to the snowpack melt-out date. These results highlight the heterogeneity of SWI at the rain-snow transition zone, and emphasize the need for spatially distributed modelling or monitoring of both the snowpack and rainfall. |