Date of Award
Doctor of Philosophy
Climate variability is important to understand as its effects on groundwater are complex than surface water. Climate association between Groundwater Storage (GWS) and sea level changes have been missing from the Intergovernmental Panel on Climate Change, demanding a requisite study of their linkage and responses. The current dissertation is primarily focused on the ongoing issues that have not been focused on the previous literatures. Firstly, the study evaluated the effects of short-term persistence and abrupt shifts in sea level records along the US coast by utilizing popular robust statistical techniques. Secondly, the study evaluated the variability in groundwater due to variability in hydroclimatic variables like sea surface temperature (SST), precipitation, sea level, and terrestrial water storage. Moreover, a lagged correlation was also analyzed to obtain their teleconnection patterns. Lastly, the relationship between the groundwater rise and one of the most common short-term climate variability, ENSO was obtained. To accomplish the research goals the current dissertation was subdivided into three research tasks.The first task attempted to answer a major question, Is sea level change affected by the presence of autocorrelation and abrupt shift? This question reflects the importance of trend and shift detection analysis in sea level. The primary factor driving the global sea level rise is often related to climate change. The current study investigates the changes in sea level along the US coast. The sea level records of 59 tide gauge data were used to evaluate the trend, shift, and persistence using non-parametric statistical tests. Mann-Kendall and Pettitt’s tests were utilized to estimate gradual trends and abrupt shifts, respectively. The study also assessed the presence of autocorrelation in sea level records and its effect on both trend and shift was examined along the US coast. The presence of short-term persistence was found in 57 stations and the trend significance of most stations was not changed at a 95% confidence level. Total of 25 stations showed increasing shift between 1990–2000 that was evaluated from annual sea level records. Results from the current study may contribute to understanding sea level variability across the contiguous US. The second task dealt with variability in the Hydrologic Unit Code—03 region. It is one of the major U.S. watersheds in the southeast in which most of the variability is caused by Sea Surface Temperature (SST) variability in the Pacific and Atlantic Ocean, was identified. Furthermore, the SST regions were identified to assess its relationship with GWS, sea level, precipitation, and terrestrial water storage. Temporal and spatial variability were obtained utilizing the singular value decomposition statistical method. A gridded GWS anomaly from the Gravity Recovery and Climate Experiment (GRACE) was used to understand the relationship with sea level and SST. The negative pockets of SST were negatively linked with GWS. The identification of teleconnections with groundwater may substantiate temporal patterns of groundwater variability. The results confirmed that the SST regions exhibited El Niño Southern Oscillation patterns, resulting in GWS changes. Moreover, a positive correlation between GWS and sea level was observed on the east coast in contrast to the southwestern United States. The findings highlight the importance of climate-driven changes in groundwater attributing changes in sea level. Therefore, SST could be a good predictor, possibly utilized for prior assessment of variabilities plus groundwater forecasting. The primary goal of the third task is to better understand the effects of ENSO climate patterns on GWS in the South Atlantic-Gulf region. Groundwater issues are complex and different studies focused on groundwater depletion while few emphasized, “groundwater rise”. The current research is designed to develop an outline for assessing how climate patterns can affect groundwater fluctuation, which might lead to groundwater rise. The study assessed the effect of ENSO phases on spatiotemporal variability of groundwater using Spearman Rank Correlation. A significant positive correlation between ENSO and GWS was observed. An increasing trend was detected in GWS where most grids were observed in Florida by utilizing the non-parametric Mann-Kendall. A positive magnitude of the trend was also detected by utilizing Theil-Sen’s Slope method with high magnitude in the mid-Florida region. The highest GWS anomalies were observed in the peak of El Niño events and the lowermost GWS was observed during La Niña events. Furthermore, most of the stations were above normal groundwater conditions. This study provides a better understanding of the research gap between groundwater rise and ENSO.
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