Rainfall and streamflow response to El Niño Southern Oscillation: a case study in a semiarid catchment, Australia

Abstract

This paper aims to compare the shift in frequency distribution and skill of seasonal climate forecasting of both streamflow and rainfall in eastern Australia based on the Southern Oscillation Index (SOI) Phase system. Recent advances in seasonal forecasting of climate variables have highlighted opportunities for improving decision making in natural resources management. Forecasting of rainfall probabilities for different regions in Australia is available, but the use of similar forecasts for water resource supply has not been developed. The use of streamflow forecasts may provide better information for decision-making in irrigation supply and flow management for improved ecological outcomes. To examine the relative efficacy of seasonal forecasting of streamflow and rainfall, the shift in probability distributions and the forecast skill were evaluated using the Wilcoxon rank-sum test and the linear error in probability space (LEPS) skill score, respectively, at three river gauging stations in the Border Rivers Catchment of the Murray-Darling Basin in eastern Australia. A comparison of rainfall and streamflow distributions confirms higher statistical significance in the shift of streamflow distribution than that in rainfall distribution. Moreover, streamflow distribution showed greater skill of forecasting with 0-3 month lead time, compared to rainfall distribution.

Long-range forecasting of intermittent streamflow

“…One of the key climatological parameters driving streamflow throughout Australia is the El Niño Southern Oscillation (ENSO) which describes variations in sea surface temperatures (SST) in the Pacific Ocean (Chiew et al, , 2003Dettinger and Diaz, 2000;Dutta et al, 2006;Piechota et al, 1998). More recently, effects of the Indian Ocean SST on South Eastern Australian rainfall have been suggested (Cai et al, 2009;Ummenhofer et al, 2009;Verdon and Franks, 2005a,b), and recent research suggests that the Indian Ocean is an important driver of streamflow in Victoria, Published by Copernicus Publications on behalf of the European Geosciences Union.…”

Climate science in support of sustainable agriculture and food security

“…Bates et al (2008) proposed incorporation of information about current climate variability into water management as a first step to assist in managing water resources effectively. The use of climate data and information for water resource management (Dutta et al 2006), water demand and irrigation optimisation under drought conditions (Meza et al 2008), and crop area decision strategies conditioned on climate information ) for better water resource management have demonstrated the role of climate science in water management and enhancing water productivity. Several of these pilot studies focussed on improving the reliability of seasonal-scale predictions and farm-level applicability.…”

Assessment of climate change impacts on rainfall using large scale climate variables and downscaling models – A case study

“…There have been advances in rainfall prediction by implementing linear methods such as, simple/multiple linear regression (Hanssen-Bauer et al 2003;Johansson and Chen 2003;Dutta et al 2006), canonical correlation analysis (CCA) Xoplaky et al 2004) or singular value decomposition (Conway et al 1996;Widmann and Bretherton 2003). When the predictand variable is precipitation, linear regression relationship may not work very well because the predictorpredictand relationships are often very complex.…”