Impacts of tall shrub expansion on the hydrological dynamics of a low-arctic catchment
Section 1: Publication
Publication Type
Conference Poster
Authorship
Wallace Cory, Wilcox Evan, Chang Qianyu, Coles Anna, Sonnentag Oliver, Marsh Philip, Berg Aaron, Baltzer Jennifer
Title
Impacts of tall shrub expansion on the hydrological dynamics of a low-arctic catchment
Year
2022
Publication Outlet
AOSM2022
DOI
ISBN
ISSN
Citation
Cory Wallace, Evan Wilcox, Qianyu Chang, Anna Coles, Oliver Sonnentag, Philip Marsh, Aaron Berg, Jennifer Baltzer (2022). Impacts of tall shrub expansion on the hydrological dynamics of a low-arctic catchment. Proceedings of the GWF Annual Open Science Meeting, May 16-18, 2022.
Abstract
Shrub productivity and areal extent is increasing across much of the circumpolar arctic. Substantial focus has been placed on understanding the potential influence of this shrub expansion on global-scale surface energy balance feedbacks, including increased transport of water to the atmosphere, decreases in albedo, and changes to the carbon cycle. Much of our understanding of these processes has been informed by fine-scale studies, which document important impacts of shrub cover on hydrological conditions such as soil moisture, thaw depth, snow redistribution, and evapotranspiration. Despite this understanding, the cumulative effects of these local impacts have yet to be extended to hydrological responses at a regional or catchment scale.
Here we propose a conceptual model which considers the various hydrologically relevant ecosystem impacts of shrub expansion and generates specific hypotheses about how they may influence catchment-scale streamflow response to summer rainfall events. In particular, we expect increased shrub cover to increase evapotranspirative fluxes and interception, resulting in less total discharge and hydrographs with longer receding limbs. We test these hypotheses using time series of Normalized Difference Vegetation Index (NDVI), climatic variables, and streamflow responses collected from Trail Valley Creek, a watershed at the northern edge of the taiga-tundra ecotone of the Northwest Territories. As expected, maximum NDVI increased across much of the watershed, with 63% of pixels greening significantly from 2000 to 2019 and no pixels significantly browning. While both rainfall and discharge showed long term increases, the timing of these trends was inconsistent such that months showing increasing rainfall never displayed increasing streamflow. We propose that the lack of direct streamflow response to changing rainfall may be explained by shrub expansion across the basin. Our next steps are to test this by comparing individual storm responses in climatically similar years early and late in the time series to isolate the shrub response. Evidence of such a response would suggest shrub expansion may mediate future streamflow-climate relationships, complicating predictions of water resource availability in arctic systems.
Plain Language Summary
The partitioning of precipitation between rainfall and snowfall is a crucial component of the evolution of the snowpack in mountains. Most snowpack models use the air temperature and humidity near the surface to derive the precipitation phase. However, the phase at the surface is strongly influenced by processes such as melting and refreezing of falling hydrometeors that occur above the surface. Atmospheric models simulate these processes and the corresponding phase at the surface. However, snowpack models rarely use this information. In this study, we considered two estimates of precipitation phase from an atmospheric model and tested them with a physically-based snow model over the mountains of southwestern Canada and northwestern United States. The results were compared with traditional approaches using the air temperature and humidity near the surface to derive the precipitation phase. Our results showed that the precipitation phase associated with the snow level obtained from the atmospheric model improved snowfall estimate and snowpack prediction compared to the traditional approaches. In contrast, the cloud/precipitation scheme of the atmospheric model decreased performance in phase estimate and snow simulations due to missing physical processes. Our study highlights that snowpack predictions in the mountains can be improved if valuable information is obtained from atmospheric models.
Section 2: Additional Information
Program Affiliations
Project Affiliations
Submitters
Cory Wallace | Submitter/Presenter | wallac14@mcmaster.ca | McMaster University |
Publication Stage
N/A
Theme
Hydrology and Terrestrial Ecosystems
Presentation Format
poster presentation
Additional Information
AOSM2022 Northern Water Futures First Author: Cory Wallace, McMaster University Additional Authors: Evan Wilcox, Wilfrid Laurier University; Qianyu Chang, Guelph University; Anna Coles, Government of the Northwest Territories; Oliver Sonnentag, Université de Montréal; Philip Marsh, Wilfrid Laurier University; Aaron Berg, University of Guelph; Jennifer Baltzer, Wilfrid Laurier University