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.

Extreme low‐flow effects on riverine fauna: A perspective on methodological assessments

“…Hydrological characterisation of present and future ELF events: Flow regimes can vary significantly in chalk headwater environments where a gradient of flow permanence from temporary systems dry for >9 months of the year to perennial environments can occur within small spatial scales (e.g., <7 km - White et al, 2018). Recurring monitoring (White et al, 2018;Sarremejane et al, 2021b) and modelling (Eastman et al, 2021) of flow conditions or states can provide spatially continuous hydrological data over longer time-periods, which could be more widely used to better characterise ELF thresholds within chalk river networks. Such information could be more routinely combined with information including groundwater models, human population growth estimates and hydroclimatic change projections (e.g.…”

“…<7 km; White et al, 2018). Recurring monitoring (Sarremejane, Stubbington, et al, 2021; White et al, 2018) and modelling (Eastman et al, 2021) of flow conditions or states can provide spatially continuous hydrological data over longer time periods, which could be more widely used to better characterise ELF thresholds within chalk river networks. Such information could be more routinely combined with information including groundwater models, human population growth estimates and water demands, and hydroclimatic change projections (e.g.…”

“…<7 km; White et al, 2018). Recurring monitoring (Sarremejane, Stubbington, et al, 2021;White et al, 2018) and modelling (Eastman et al, 2021)…”

Drought in intermittent river and ephemeral stream networks

“…electrical resistance sensors; Jaeger & Olden, 2012), field observations by the general public and scientists (Allen et al, 2019; Gallart et al, 2017; Sefton et al, 2019; van Meerveld et al, 2019) or remote sensing (for larger streams and watercourses with limited riparian vegetation, e.g. Bishop‐Taylor et al, 2018), all of which can be complemented by spatio‐temporal infilling procedures (Eastman et al, 2021).…”

Assessment of the spatiotemporal dynamics of the hydrological state of non-perennial river systems and identification of flow-contributing areas

“…They are also of ecological importance as they provide refuge and spawning zones for aquatic life (Makwinja et al, 2014). Although generally perceived to be less important when compared to the flowing state (Rodríguez-Lozano et al, 2020;Leigh et al, 2019), some studies suggest that this is the most important state of NPRs as it caters for both aquatic and terrestrial life (Eastman et al, 2021). Dry riverbeds are perceived to be the least valuable of all three hydrological states and are often overlooked.…”