UC Irvine

Global continental discharge is an important component of global water cycle, but it is difficult to measure by traditional methods alone. In this dissertation, we provide an overview of current methods of estimating global continental discharge, and provide mass-balance estimates of global discharge using remote sensing and reanalysis products. Evaluating against observation-based estimates, we find that discharge computed from land mass balance using reanalysis-based moisture convergences and GRACE can provide a viable alternative to declining in situ observations’ records for major river basins. Then we conduct a series of sensitivity experiments on an ocean-ice model forced with varying discharge to understand ocean’s response to changes and uncertainties in discharge. We find that sea surface salinity (SSS), mixed layer depth, potential temperature, net primary production, and stratification show notable changes in the coastal and river plume regions, and that for certain river plume regions, interannual variability accounts to up to half of the total variance. Lastly, we introduce another novel method of estimating discharge from space. We isolate discharge and transport signal in SSS after removing atmospheric freshwater flux signal from SSS using joint EOF analysis, and then use discharge-SSS correlation to infer discharge for the Orinoco-Amazon, and Congo-Niger river basins.