Fluvial organic carbon cycling regulated by sediment transit time and mineral protection

Rivers transfer terrestrial organic carbon (OC) from mountains to ocean basins, playing a key role in the global carbon cycle. During fluvial transit, OC may be oxidized and emitted to the atmosphere as CO2 or preserved and transported to downstream depositional sinks. The balance between oxidation and preservation determines the amount of particulate OC (POC) that can be buried long term, but the factors regulating this balance are poorly constrained. Here, we quantify the effects of fluvial transit on POC fluxes along an ~1,300 km lowland channel with no tributaries. We show that sediment transit time and mineral protection regulate the magnitude and rate of POC oxidation, respectively. Using a simple turnover model, we estimate that annual POC oxidation is a small percentage of the POC delivered to the river. Modelling shows that lateral erosion into POC-rich floodplains can increase POC fluxes to downstream basins, thereby offsetting POC oxidation. Consequently, rivers with high channel mobility can enhance CO2 drawdown while management practices that stabilize river channels may reduce the potential for CO2 drawdown.

'Unified' unstructured ocean, land and river modelling in the coastal zone

<p>The representation of coupled physical processes in coastal models is often constrained and simplified by details of the underlying numerical approach. Ocean, land and river dynamics are generally represented using different computational grids and numerical methods, and are not typically resolved at the fine spatial and temporal scales needed to capture coupled dynamics. In this work, we describe a new 'unified' approach to coupled ocean, land and river modelling, in which all components are represented on a common, multi-scale unstructured mesh, and employ compatible numerical formulations and coupling strategies. In contrast to conventional approaches, this unified approach does not rely on a hierarchy of nested sub-models, but rather leverages the flexibility of unstructured grids to seamlessly embed high-resolution domains within global model configurations. This initiative is an extension of the US Department of Energy's E3SM framework, designed to enhance the representation of coastal dynamics in global-scale ESMs. Initial work on a 'unified' representation of coastal environments is reported, focusing on the development of an unstructured model for the US mid-Atlantic coastal zone as part of the Integrated Coastal Modelling (ICoM) effort.</p>

Corrigendum to: Trajectory river modelling – a decision-support tool to help manage multiple risks associated with planning around variable water resources

The application of river-system models to inform water-resource planning and management is a growing global phenomenon. This requires models to be applied so that they are useful to water decision makers charged with setting targets that provide adequate water flows to sustain landholders and communities. This article examines why and how the innovative application of river-system models can facilitate interactions between water science and water management in Australia's Murray–Darling Basin (the Basin). A trajectory river-modelling method was applied to run multiple short historical climate sequences through a river-system model to provide historical probabilities. These can allow better assessment of the risks and impacts associated with stream flow and water availability. This method allows known historical variability to be presented, and produces relevant results for a 10–15-year water-sharing plan lifetime. The benefits were demonstrated in the Basin's Lachlan Catchment where modelled river-flow results demonstrated the increased variability between shorter 15-year sequences than for a single 114-year run. This approach highlighted the benefits of expressing modelling results as historical probabilities to inform short-term and strategic water-planning efforts.

Uncertainty analysis of floodplain friction in hydrodynamic models

This study proposes a framework to estimate the uncertainty of hydrodynamic models on floodplains. The traditional floodplain resistance formula of Pasche (1984) (based on Lindner, 1982) used for river modelling as well as the approaches of Baptist et al. (2007), Järvelä (2004), and Battiato and Rubol (2014) have been considered for carrying out an uncertainty analysis (UA). The analysis was performed by means of three different methods: traditional Monte Carlo (MC), First-Order Second-Moment (FOSM) and Metamodelling. Using a two-dimensional hydrodynamic model, a 10 km reach of the River Rhine was simulated. The model was calibrated with water level measurements under steady flow conditions and then the analysis was carried out based on flow velocity results. The compared floodplain friction formulae produced qualitatively similar results, in which uncertainties in flow velocity were most significant on the floodplains. Among the tested resistance formulae the approach from Järvelä presented on average the smallest prediction intervals i.e. the most accurate results. It is important to keep in mind that UA results are not only dependent on the defined input parameters deviations, but also on the number of parameters considered in the analysis. In that sense, the approach from Battiato and Rubol is still attractive for it reduces the current analysis to a single parameter, the canopy permeability. The three UA methods compared gave similar results, which means that FOSM is the less expensive one. Nevertheless it should be used with caution as it is a first-order method (linear approximation). In studies involving dominant non-linear processes, one is advised to carry out further comparisons.

Non-stationarity of low flows and their relevance to river modelling during drought periods

Changes in groundwater storage lead to a reduction in groundwater contribution to river flow and present as non-stationarity, especially during low-flow conditions. Conventional river models typically ignore this non-stationarity, and, hence, their predictions of declines in low flows during drought periods are likely to be compromised. The present study assesses non-stationarity and highlights its implications for river modelling. A quantile regression analysis showed non-stationarity of low flows in the Namoi catchment (Australia), with statistically significant downward trends in the 10th percentile of log-transformed baseflow (10-LTB). This highlighted the usefulness of the 10-LTB metric to identify non-stationarity and, hence, alert modellers to the importance of adopting models that explicitly account for groundwater processes when modelling such river systems.