Early Warning Indicators of Groundwater Drought in Mountainous Regions

• Published in: Water resources research Vol. 59; no. 8
• Main Authors: Gullacher, A., Allen, D. M., Goetz, J. D.
• Format: Journal Article
• Language: English
• Published: 01.08.2023
• Subjects: drought; generalized additive models; groundwater; indicators; mountain regions; prediction
• ISSN: 0043-1397; 1944-7973
• DOI: 10.1029/2022WR033399

Aquifers in mountainous regions are susceptible to drought. However, the diverse hydroclimatology, the small and responsive aquifers, and the varied nature of interactions between groundwater and surface water lead to complex groundwater level responses that are challenging to interpret for understanding groundwater drought. In this study, generalized additive models (GAMs) are used to explore the sensitivity of summer groundwater levels to various climate and hydrological predictor variables (indicators) in each of a snowmelt‐ and rainfall‐dominated hydroclimatic regime in British Columbia, Canada. A sensitivity analysis explores individual seasonal predictor variables, station versus gridded climate data, teleconnection indices, and time series length. GAMs are then generated for different combinations of predictor variables to identify the best combination for each region. In the snowmelt‐dominated regime, maximum spring temperature, maximum snow water equivalent, and the winter Nino 3.4 index is the best combination of variables for predicting summer groundwater levels. In the rainfall‐dominated regime, maximum spring temperature, winter precipitation, and spring streamflow is the best combination. The unique combinations of predictor variables for each region can be used as early warning indicators for groundwater drought preparedness by water managers prior to the beginning of the summer. The Standardized Groundwater Level Index (SGI) is also effective at indicating which wells had pronounced responses to periods of drought in each region. However, the SGI differed among aquifers of similar type, suggesting other factors such as aquifer response mechanism and groundwater pumping may have an important influence on the SGI. Key Points Generalized additive models are used to identify predictor variables associated with summer groundwater levels Summer groundwater levels are influenced uniquely by region‐specific seasonal climate and hydrological variables Combinations of predictor variables can be used as early warning indicators of groundwater drought