Inferences of Groundwater Response to Projected Hydroclimatic Changes in North Florida

Abstract

Discerning anthropogenic stressors on groundwater is critical for climate change adaptation to reduce risks and increase resiliency. Long-term groundwater level trends are forecasted and examined at three sites in North Florida using a large ensemble of Global Climate Model (GCM) projections under low and medium emission scenarios. The forecasts indicate groundwater levels are likely to decline from 2020 to 2099. However, the declines are expected to accelerate after 2040s, reaching critical levels by the end of this century. Pumping impact constitutes 10% to 45% of future declines but is amplified by enhanced drought. Examination of distinct influence of rainfall, evapotranspiration (ET), and groundwater pumping on future trends shows highly divergent groundwater response to projected hydroclimatic changes. The future long-term rainfall trend may lead to rising groundwater levels, which may be overshadowed by heightened ET loss driven by climate change and increased groundwater pumping, causing steep declines. This study also reveals poor performance of predictions driven by GCM projections in replicating the timing of high and low levels at the sites influenced by Florida’s peninsular climate due to the limitation of downscaling and bias-correction to capture oscillations in climate cycles driving hydrologic memory. However, groundwater levels are predicted well by a few GCMs at one site influenced primarily by continental climate. Additionally, a multidecadal harmonic analysis exposes presence of centennial periodicity in groundwater levels, which opens a new perspective in the understanding of climate change impacts on groundwater resources. Further investigation is needed to better understand the effect of centennial cycles on future groundwater levels and how these cycles can be incorporated into the downscaling methods. Hence, GCM-based forecasts are recommended to be cautiously utilized for groundwater resource planning when they significantly depart from historical long-term cyclic patterns.