Improved river transmission loss modelling for environmental flow releases during droughts

Basin-scale water resources models lack key physical factors such as antecedent conditions, that strongly influence transmission losses under dry conditions. This study presents the development and evaluation of two river transmission loss models for integration into river systems models: dynamic maximum alluvium as river storage (DMAARS) and DMAARS coupled with river dead storage (DMAARSDS). The models were applied to environmental flow events during the 2018/2019 drought in the northern Murray-Darling Basin and compared with a benchmark piecewise linear loss model. They provided significantly improved performance in 8 out of 12 fit metrics and more realistic estimates of environmental flow metrics. Scenario testing revealed that model choice significantly influences predictions, especially of baseline conditions and ecological benefits, e.g., peak water height, flow extent. Analyses also showed strong potential for use in long-term water resource planning. To enable adoption, the new models have been integrated into eWater Source as a community plugin. • New river loss models that represent alluvium and pool storage were developed. • The new models provide variable losses that are dependent on antecedent conditions. • A conventional benchmark loss model was outperformed by the new models. • The new models produce more realistic predictions of environmental flows. • The developed algorithms suit integration into existing river management models.