Establishing predevelopment benchmark groundwater conditions is challenging without long-term records to discern impacts of pumping and climate change on aquifer levels. Understanding periodic natural cycles and trends require 100 years or more data which rarely exist. Using limited records, we develop an approach to hindcast multidecadal levels and examine the temporal evolution of climatic and pumping impacts. The methodology includes a wavelet-aided statistical model, constrained by temporal scales of physical processes responsible for groundwater level variation, including rainfall, evapotranspiration and pumping stresses. The model and hindcasts are tested at three sites in Florida using traditional split calibration-verification methods for the period of record and with the documented historical drought and wet years for the period of no-record. The pumping impact is quantified over time and compared with regional groundwater models, revealing that withdrawals are responsible for 30 to 70% of the declines in levels since 1960s. Hindcasting yielding 110 years of monthly levels is used to assess the effect of climate change and pumping on the frequency of critical low levels. At all three sites, the frequencies of critical low levels increase significantly in the 1960 to 2015 period when compared to the 1904 to 1959 period. For example, at site 1, the return period of the critical low level is shortened by 3.9 years due to climate change and 2.2 years due to pumping.

A physically constrained wavelet-aided statistical model (PCWASM) is presented to analyse and predict monthly groundwater dynamics on multi-decadal or longer time scales. The approach retains the simplicity of regression modelling but is constrained by temporal scales of processes responsible for groundwater level variation, including aquifer recharge and pumping. The methodology integrates statistical correlations enhanced with wavelet analysis into established principles of groundwater hydraulics including convolution, superposition and the Cooper-Jacob solution. The systematic approach includes (1) identification of hydrologic trends and correlations using crosscorrelation and multi-time scale wavelet analyses; (2) integrating temperature-based evapotranspiration and groundwater pumping stresses and (3) assessing model prediction performances using fixed-block k-fold cross-validation and split calibrationvalidation methods. The approach is applied at three hydrogeologicaly distinct sites in North Florida in the United States using over 40 years of monthly groundwater levels. The systematic approach identifies two patterns of cross-correlations between groundwater levels and historical rainfall, indicating low-frequency variabilities are critical for long-term predictions. The models performed well for predicting monthly groundwater levels from 7 to 22 years with less than 2.1 ft (0.7 m) errors. Further evaluation by the moving-block bootstrap regression indicates the PCWASM can be a reliable tool for long-term groundwater level predictions. This study provides a parsimonious approach to predict multi-decadal groundwater dynamics with the ability to discern impacts of pumping and climate change on aquifer levels. The PCWASM is computationally efficient and can be implemented using publicly available datasets. Thus, it should provide a versatile tool for managers and researchers for predicting multi-decadal monthly groundwater levels under changing climatic and pumping impacts over a long time period.

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