An assessment of the economic value of using seasonal climate forecasting in water resources management

An assessment of the economic value of using seasonal climate forecasting in water resources management

Australia’s water resource systems are suffering from excessive diversion of surface flows with adverse effects on the riverine environments now becoming clearly
evident. The capacity of water managers to achieve current reform aims whilst minimising impacts on rural communities will be improved with the aid of new technologies and decision-making processes. Seasonal climate forecasting (SCF) based on the relationship between the El Niño-Southern Oscillation phenomenon (ENSO) and streamflow is a technology that may play a part to improving the
management of river-flow regimes providing benefits to both extractive and nonextractive (environmental) users of water.

This research uses a case study to test the use of SCF information in managing access to one component of irrigation water supply in the Border Rivers catchment in the northern part of the Murray-Darling Basin in eastern Australia. The aims were twofold including developing an appropriate methodology and modelling framework that
is transferable across a range of locations and evaluating the efficacy of seasonal climate forecasting information. A modelling approach tested water access rules by
simulating both economic and environmental outcomes. These outcomes were analysed using a trade-off analysis based on the production possibility frontier (PPF) in conjunction with the Pareto principle whereby the SCF information would be considered efficacious if its use improved environmental outcomes without economic costs or visa versa.

Although seasonal climate forecasting has progressed significantly in recent years, there appears to be of little use of seasonal climate forecast information in catchment water management decision-making. Forecast accuracy, or the perceived lack of forecast accuracy, is cited as a key impediment to the uptake of forecast information in decision-making, despite the efforts of researchers to statistically validate forecast systems.

The research findings indicate that the use of SCF information was sufficiently accurate to improve economic outcomes without negatively impacting on environmental outcomes. In addition, an improvement in forecasting accuracy would further improve economic outcomes without major impacts on environmental outcomes. The increase in economic outcomes from using seasonal forecasting
information are small relative to the total regional gross margin produced by the case study area in the absence of the SCF based water access rules for irrigation. This
suggests that the study findings may not be of sufficient scale to convince decisionmakers to adopt the information to assist in managing water access.