Integration of ENSO Signal Power Through Hydrological Processes in the Little River Watershed

The relationship of the El-Nino/Southern Oscillation (ENSO) to hydrology is typically discussed in terms of the ability to separate significantly different hydrologic variable responses versus the anomaly that has taken place. Most of the work relating ENSO trends to proxy variables had been done on precipitation records until the mid 1990s, at which point increasing numbers of studies started to focus on ENSO relationships with streamflow as well as other environmental variables. The signals in streamflow are typically complex, representing the integration of both climatic, landscape, and anthropological responses that are able to strengthen the inherent ENSO signal in chaotic regional precipitation data. There is a need to identify climate non-stationarities related to ENSO and their links to watershed-scale outcomes. For risk-management in particular, inter-annual modes of climate variability and their seasonal expression are of interest. In this study, we analyze 36 years of historical monthly streamflow data from the Little River Watershed (LWR), a coastal plain ecosystem in Georgia, in conjunction with wavelet spectral analysis and modeling via the Soil & Water Assessment Tool (SWAT). Using both spectral and physical models allows us to identify the mechanism by which the ENSO signal power in surface and simulated groundwater flow is strengthened as compared to precipitation. The clear increase in the power of the inter-annual climate signal is demonstrated by shared patterns in water budget and exceedance curves, as well as in high ENSO related energy in the 95% significant wavelet spectra for each variable and the NINO 3.4 index. In the LRW, the power of the ENSO teleconnection is increased in both the observed and simulated stream flow through the mechanisms of groundwater flow and interflow, through confinement by a geological layer, the Hawthorn Formation. This non-intuitive relationship between ENSO signal strength and streamflow could prove to be helpful for making seasonal climate predictions in a geographic area with a weaker than desirable ENSO signal, as a predictive relationship could be found between streamflow or other proxy hydro-climatic variables.