Observations of the presence or absence of surface water in streams are useful for characterizing streamflow permanence, which includes the frequency, duration, and spatial extent of surface flow in streams and rivers. Such data are particularly valuable for headwater streams, which comprise the vast majority of channel length in stream networks, are often non-perennial, and are frequently the most data deficient. Datasets of surface water presence exist across multiple data collection groups in the United States but are not well aligned for easy integration. Given the value of these data, a unified approach for organizing information on surface water presence and absence collected by diverse surveys would facilitate more effective and broad application of these data and address the gap in streamflow data in headwaters. In this paper, we highlight the numerous existing datasets on surface water presence in headwater streams, including recently developed crowdsourcing approaches. We identify the challenges of integrating multiple surface water presence/absence datasets that include differences in the definitions and categories of streamflow status, data collection method, spatial and temporal resolution, and accuracy of geographic location. Finally, we provide a list of critical and useful components that could be used to integrate different streamflow permanence datasets.

Numerical models that predict channel evolution are an essential tool for investigating processes that occur over timescales which render field observation intractable. The current generation of morphodynamic models, however, either oversimplify the relevant physical processes or, in the case of more physically complete codes based on computational fluid dynamics (CFD), have computational overheads that severely restrict the space–time scope of their application. Here we present a new, open-source, hybrid approach that seeks to reconcile these modelling philosophies. This framework combines steady-state, two-dimensional CFD hydraulics with a rule-based sediment transport algorithm to predict particle mobility and transport paths which are used to route sediment and evolve the bed topography. Data from two contrasting natural braided rivers (Rees, New Zealand, and Feshie, United Kingdom) were used for model verification, incorporating reach-scale quantitative morphological change budgets and volumetric assessment of different braiding mechanisms. The model was able to simulate 8 of the 10 empirically observed braiding mechanisms from the parameterized bed erosion, sediment transport, and deposition. Representation of bank erosion and bar edge trimming necessitated the inclusion of a lateral channel migration algorithm. Comparisons between simulations based on steady effective discharge versus event hydrographs discretized into a series of model runs were found to only marginally increase the predicted volumetric change, with greater deposition offsetting erosion. A decadal-scale simulation indicates that accurate prediction of event-scale scour depth and subsequent deposition present a methodological challenge because the predicted pattern of deposition may never “catch up” to erosion if a simple path-length distribution is employed, thus resulting in channel over-scouring. It may thus be necessary to augment path-length distributions to preferentially deposit material in certain geomorphic units. We anticipate that the model presented here will be used as a modular framework to explore the effect of different process representations, and as a learning tool designed to reveal the relative importance of geomorphic transport processes in rivers at multiple timescales.

Freshwater algal blooms are a global concern,^{1 – 4} and there is evidence that they are becoming more common in response to climate change.^{1,5 – 7} Because algal blooms can adversely affect public health, economies, and ecosystem services by degrading water quality,^8,9 early identification of algal blooms can improve public safety and mitigate economic concerns.

Stream permanence classifications (i.e., perennial, intermittent, ephemeral) are a primary consideration to determine stream regulatory status in the United States (U.S.) and are an important indicator of environmental conditions and biodiversity. However, at present, no models or products adequately describe surface water presence for regulatory determinations. We modified the Thornthwaite monthly water balance model (MWBM) with a flow threshold parameter to estimate flow permanence and evaluated the model’s accuracy and precision for more than 1.3 million headwater stream reaches in the U.S. Pacific Northwest (PNW). Stream reaches were assigned to one of eight calibration groups by unsupervised classification based on sensitivity to MWBM parameters. Suitable MWBM parameter sets were identified by comparing modeled stream permanence estimates to surface water presence observations (SWPO). Parameter sets with accuracies > 65% were considered suitable. The MWBM estimated stream permanence with high precision at 40% of reaches, with poor precision at 20% of reaches, and no suitable parameter sets were identified for 40% of reaches. Results highlight the need for increased SWPO collection to improve calibration and assessment of stream permanence models. Additionally, implementation of the MWBM to estimate surface water presence indicates potential for process-based models to predict stream permanence with future development.