The El Nino-Southern Oscillation and long-range forecasting of flows in the Ganges

Several recent studies have shown that the El Nino-Southern Oscillation (EN SO) index has a significant influence on various climatic and hydrologic si gnals across the globe. This study attempts to identify the nature and stre ngth of possible teleconnections between the Ganges River flow and ENSO, an d to develop a model which can capture, at least in part, the natural varia bility of flow, and provide a large forecasting lead-time. The motivation c ame from the fact that, in the past, hydrologic forecasts of the basin thro ugh rainfall-runoff modelling could provide a lead-time on the order of the basin response time, which is several days or so. Such a short forecasting lead-time is not adequate to hedge against extreme events (flood or drough t) in large river basins. This is, perhaps, the first attempt to relate flo ws in the Ganges with ENSO. Our analysis suggests that a significant relationship exists between the na tural variability of the Ganges annual flow and ENSO index. Through further investigation, we show that the rate of change of ENSO index is also stati stically related to the Ganges flow. A statistical model that combines all these indicators to forecast annual flow in the Ganges is proposed. This mo del uses current flow data, predicted ENSO data and its gradient to forecas t flow in the Ganges with a forecasting lead-time of 1 year. The model also provides a quantitative measure of forecasting uncertainty. A key advantag e of this model is that it does not require rainfall and stream flow inform ation from upstream areas and countries. We have used 45 years of data for model development and calibration, and 15 years of data for validation. It is encouraging to note that all four of the validation forecasts during the El Nino and La Nina events are within the 95% confidence intervals. These results demonstrate the strength of the proposed approach and suggest furth er exploration of this long-range forecasting methodology for other major r ivers in the world. Copyright (C) 2001 Royal Meteorological Society.