Annual and interannual variations in terrestrial water storage during and following a period of drought in South Carolina, USA

Summary The goal of this research is to quantify variations in both space and time of water stored in the terrestrial environment within South Carolina during and following a period of drought. We use a water balance approach that synthesizes observed and modeled hydrologic fluxes for sub-watersheds defined by the drainage area between streamflow gaging stations. We apply the approach for the period 1998–2007 to study the impact of a drought that occurred during the early part of this time period on terrestrial water storage within the state. Results from the analysis provide evidence of distinct annual and interannual variation in water storage for different regions of the state, with the fall season having a water surplus and spring season exhibiting a water deficit. The impact of the drought varied for different regions of the state depending in part on hydrogeological conditions including soil type and depth to the groundwater level. Comparing estimates of rate of change in terrestrial water storage with observed groundwater levels, as an independent validation of the terrestrial water storage estimations, shows that many of the sub-watersheds within the state exhibited similar patterns between variation of rate of change in terrestrial water storage estimates and observed groundwater levels during the period of analysis, as expected. However, some sub-watersheds did not follow general annual and interannual variations in groundwater level or in estimated rate of change in terrestrial water storage relative to neighboring sub-watersheds. We speculate that these abnormalities may be related to human influences that alter local water storage trends within specific sub-watersheds of the state, however future work is needed to further investigate this possible explanation. We conclude through this study that the water balance approach presented is a simple yet valuable means for estimating variations in water availability at a regional spatial scale by synthesizing existing observations and model output data within a geospatially-explicit context.

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