How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications

Abstract

Streamflow data are used for important environmental and economic decisions, such asspecifying and regulating minimum flows, managing water supplies, and planning for flood hazards.Despite significant uncertainty in most flow data, the flow series for these applications are oftencommunicated and used without uncertainty information. In this commentary, we argue that properanalysis of uncertainty in river flow data can reduce costs and promote robust conclusions in watermanagement applications. We substantiate our argument by providing case studies from Norway and NewZealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry,improved public acceptance of a controversial water management policy, and tested the accuracy of waterquality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flowseries realizations rather than simple error bounds. Although examples of such tools are in development,considerable barriers for uncertainty analysis and communication still exist for practitioners, and futureresearch must aim to provide easier access and usability of uncertainty estimates. We conclude that flowuncertainty analysis is critical for good water management decisions.