Reconstructing spatiotemporal dynamics in hydrological state along intermittent rivers

Abstract

Despite the impact of flow cessation on aquatic ecology, the hydrology of intermittent rivers has been largely overlooked. This has resulted in a lack of monitoring projects, and consequently, datasets spanning a period of sufficient duration to characterise both hydrological extremes. This report documents an investigation into the potential for statistical modelling to simulate the spatiotemporal dynamics of flowing, ponded and dry hydrological states in an internationally rare hydrological state dataset. The models presented predict unrecorded hydrological state data with performance metrics exceeding 95%, providing insights into the relationship between ponding prevalence and the performance of statistical simulation of this ecologically important intermediate state between drying and flowing conditions. This work demonstrates the potential for hydrological intermittence to be simulated in areas where hydrological state data are often sparse, providing opportunities for quality control and data infilling. This further understanding of the processes driving intermittence will inform future water resource assessments and the influence of climate change on hydrological intermittence.