Long-Range River Discharge Forecasting Using the Gravity Recovery and Climate Experiment

Abstract

Diarrheal diseases, notably cholera, have been shown to be related to episodic seasonal variability in river discharge, predominantly low flows, in regions where water and sanitation infrastructure are inadequate. Forecasting river discharge in transboundary international basins a few months in advance remains elusive because the necessary geophysical data are unavailable or are not shared with stakeholders. We hypothesized that river discharge in large river basins is directly related to upstream water conditions that lead to generation of high and low flows. Using the Ganges-Brahmaputra-Meghna Rivers as an example and Bayesian regressive models, we showed that terrestrial water storage (TWS) anomalies from the Gravity Recovery and Climate Experiment (GRACE) can provide reliable estimates of flows, which are essential hydroclimatic variables for predicting endemic cholera, with an overall accuracy of 70% and up to 60 days in advance, without ancillary ground-based data.