Multiple spectral and statistical analyses of a 700 yearlong temporal record of groundwater recharge from the dry lands, Badain Jaran Desert (Inner Mongolia) of Northwest China reveal a stationary harmonic cycle at 200 ± 20 year. Interestingly, the underlying periodicity in groundwater recharge fluctuations is similar to those of solar-induced climate cycle "Suess wiggles" and appears to be coherent with phases of the climate fluctuations and solar cycles. Matching periodicity of groundwater recharge rates and solar and climate cycles renders a strong impression that solar-induced climate signals may act as a critical amplifier for driving the underlying hydrographic cycle through the common coupling of long-term Sun-climate groundwater linkages.
IntroductionA spatiotemporal variation of groundwater recharge is emerging as one of the useful archives of past climate and hydrological changes [Edmunds et al., 2004]. Many geophysical parameters, such as climate changes deduced from various sources especially lake sediments [Gasse, 2000], speleotherm [Bar-Matthews et al., 1997], ice core, tree rings, and environmental changes (temperature, precipitation, and evapotranspiration), are intimately linked to the groundwater recharge. Evidence exist of dramatic climate changes affecting water availability [Lambert and Millard, 1969], and therefore, it is challenging for researchers to link geohydrological records to growing body of climate data and related exogenic and endogenic forcing parameters. Finding trend and cyclic pattern in groundwater fluctuations is, therefore, crucial for constraining the model of groundwater recharge cycles and issues related to the climate and environmental changes. Here we examine a long-term groundwater recharge record using the multiple spectral and statistical techniques to (i) identify long-term cyclic pattern and (ii) discuss its possible coupling with solar-induced climate cycle. Singular spectral analysis (SSA) is the most suitable time series analysis tool to identify the unknown or partially known dynamics of the underlying systems that generated the series [Vautard and Ghil, 1989;Ghil et al., 2002]. It is popular for trend extraction [Alexandrov, 2009], principal component analysis [Serita et al., 2005], and signal extraction from noise [Varadi et al., 1999] of different types of atmospheric and geophysical signals. SSA allows us to identify the principal processes and their contribution through the eigenvalue estimates, which, in turn, provide the order of major periodic component driving the groundwater recharge cycle.
Groundwater Recharge Rates RecordGroundwater recharge time series analysed adopted here is based on densely sampled data , which posses enough homogeneity and completeness. Accordingly, the 700 yearlong groundwater TIWARI AND RAJESH