Modelling Impacts of Climate Change on Snow Drought, Groundwater Drought, and their Feedback Mechanism in a Snow Dominated Watershed in Western Canada

• Author / Creator

  Huang, Yinlong

• In snow-dominated regions, snow storage is a primary water resource contributing to surface water (SW) and groundwater (GW) supplies. Snow drought is defined as either lack of snow storage or high-temperature-induced early snowmelt, leading to a loss of snow water resources. GW drought refers to a period of decreased GW levels that results in insufficient water supply in GW-dependent regions. Due to snowmelt infiltration to the soil, an interaction mechanism between snow drought and GW drought is possible, requiring attention. Most of the recent studies focused on assessing the hydrological, meteorological, and agricultural droughts, and in some cases, the relationship between some of them was studied.
  Since snow is a primary driver of hydrologic processes in most cold watersheds of the mid-to-high latitude regions, the overarching goal of this study was to assess the relationship between snow drought and GW drought, which can inform water management and environmental protection in these regions. Two physical process-based SW and GW models were calibrated and coupled to simulate the interactions and feedback mechanism between snow and GW droughts for a historical period (i.e., 1980-2013) under different eco-hydro(geo)logical (EHG) settings, including Mountains, Foothills, and Plains. Using a set of downscaled climate data, projected from an ensemble of five Global Climate Models of the Coupled Model Intercomparison Project 6, the coupled SW-GW model was forced to simulate physical processes associated with snow and groundwater droughts for the 2040-2073 period under two Shared Socioeconomic Pathways (SSP126, and SSP585). With a drainage area of about 59,000 km2, comprising heterogeneous EHG conditions, the North Saskatchewan River Basin, Alberta, Canada was selected as the study area. The study results indicated that characteristics of snow and GW droughts were reversed across different EHG regions under future SSP scenarios compared to the historical period. Mountains experienced the worst historical snow drought compared to Foothills and Plains. The multi-model ensemble mean projections indicated more intensified and prolonged snow droughts with higher frequency in Mountains, leading to lower snow accumulation in Mountains. Among all regions, Plains experienced worst historical GW drought, and it was projected to experience lower intensity GW droughts in the future. On the other hand, mountains were projected to experience relatively less frequent and low intensity GW droughts compared to other regions. This implies a potential shift of snow drought events to GW droughts in Plains and the opposite processes in the Mountains in the future.
  The statistical analysis of the simulated snow water equivalent and GW heads for historical period indicated that the propagation time from snow to GW drought varies across regions, with 4 months in Mountains, 5 months in Foothills, and 6 months in Plains. Both future scenarios projected decreased propagation time for all regions, suggesting accelerated water cycle. The Least Absolute Shrinkage and Selection Operator analysis of the simulated results indicated that dominant physical process that control GW head and its connection to snow processes varies across EHG regions. All regions showed sensitive response to soil water content and percolation. Mountains and Foothills were more sensitive to curve number than Plains, whereas Foothills and Plains were more sensitive to total water yield, with Plains alone being extremely sensitive to evapotranspiration.
  This study provides a basis for further studies concerning the GW management strategies due to changes in snow processes that results from global warming effects in cold watersheds of the mid-to-high latitude regions. It also provides a unified approach for analyzing snow drought and GW drought relationship.

• Subjects / Keywords

  • Hydrology
  • snow drought
  • groundwater drought
  • modelling
  • LASSO
  • statistical analysis

• Graduation date

  Fall 2023

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-z9hk-4j46

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.