Probability of Streamflow Permanence Model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest

Jaeger, Kristin L.; Sando, Roy; McShane, Ryan R.; Dunham, Jason B.; Hockman-Wert, David; Kaiser, Kendra E.; Hafen, Konrad; Risley, John C.; Blasch, Kyle W.

doi:10.1016/j.hydroa.2018.100005

Cited by 74 publications

(114 citation statements)

References 55 publications

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“…The challenges associated with measuring spatial and spatio‐temporal aspects of intermittence are large. Although it is relatively easy to calculate the distribution of perennial and intermittent streams in a network from NHD+, the accuracy of this dataset with respect to flow permanence is poor (Fritz et al, ), though progress is being made in this area (Jaeger et al, ). Even at smaller scales, leading models of stream drying are unable to reproduce the spatial patterns of drying (Ward, Schmadel, & Wondzell, ).…”

Section: Introductionmentioning

confidence: 99%

“…One potential, but unassessed, source of variation in DOC across headwaters is variation in streamflow intermittence. Although streamflow intermittence can occur throughout stream networks (González-Ferreras & Barquín, 2017), headwater streams are more likely to experience periodic drying (Fritz et al, 2013;González-Ferreras & Barquín, 2017;Jaeger et al, 2019). Streamflow intermittence varies across headwaters (e.g., Godsey & Kirchner, 2014;Jensen, McGuire, & Prince, 2017) and reach-scale patterns of stream drying have been linked to variation in carbon cycling and transport (e.g., Acuña, Giorgi, Muñoz, Sabater, & Sabater, 2007;Shumilova et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Dynamic stream network intermittence explains emergent dissolved organic carbon chemostasis in headwaters

Hale

Godsey

2019

Hydrological Processes

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Dissolved organic carbon (DOC) concentrations vary among headwaters, with variation typically decreasing with watershed area. We hypothesized that streamflow intermittence could be an important source of variation in DOC concentrations across a small watershed, through (a) temporal legacies of drying on organic matter accumulation and biotic communities and (b) spatial patterns of connectivity with DOC sources. To test these hypotheses, we conducted three synoptic water chemistry sampling campaigns across a 25.5‐km2 watershed in south‐eastern Idaho during early spring, late summer, and late fall. Using changepoint analysis, we found that DOC variability collapsed at a consistent location (watershed areas ~1.3 to ~1.8 km2) across seasons, which coincided with the watershed area where variability in streamflow intermittence collapsed (~1.5 km2). To test hypothesized mechanisms through which intermittence may affect DOC, we developed temporal, spatial, and spatio‐temporal metrics of streamflow intermittence and related these to DOC concentrations. Streamflow intermittence was a strong predictor of DOC across seasons, but different metrics predicted DOC depending on season. Seasonal changes in the effects of intermittence on DOC reflected seasonal changes from instream to flowpath controls. A metric that captured spatial connectivity to sources significantly predicted DOC during high flows, when DOC is typically controlled by transport. In contrast, a reach‐scale temporal metric of intermittence predicted DOC during the late growing season, when DOC is typically controlled by instream processes and when legacy effects of drying (e.g., diminished biological communities) would likely affect DOC. The effects of intermittence on DOC extend beyond temporal legacies at a point. Our results suggest that legacy effects of intermittence do not propagate downstream in this system. Instead, snapshots of spatial patterns of intermittence upstream of a reach are critical for understanding spatial patterns of DOC through connectivity to DOC sources, and these processes drive patterns of DOC even in perennial reaches.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic stream network intermittence explains emergent dissolved organic carbon chemostasis in headwaters

Hale

Godsey

2019

Hydrological Processes

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“…The scarcity of information on the spatial and temporal extent of flow intermittency has been identified as a major barrier for ecologists and managers to understand and protect intermittent stream ecosystems (Acuña et al, 2017). This barrier has been partly overcome in previous studies by using statistical models relating flow intermittency to surrounding environmental variables (Snelder et al, 2013;Jaeger et al, 2019;González-Ferreras and Barquín, 2017;Bond and Kennard, 2017), but most of these studies focused on only the spatial variations in flow intermittency, except for Jaeger et al 2019, overlooking its temporal aspects. This issue becomes particularly urgent in the time when flow regimes of streams are changing worldwide, mainly in response to climate change and water extraction for human uses (Jaeger et al, 2014;Chiu et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Improved understanding of temporal and spatial patterns in flow intermittency is fundamentally important for effective river management. Flow intermittency exerts primary control on the transfer of energy, materials and organisms by surface water through river networks (Jaeger et al, 2019) and is a key driver of riverine ecosystems (Stanley et al, 1997;Datry et al, 2017;Poff et al, 1997).…”

Section: Introductionmentioning

confidence: 99%

Evaluating a landscape-scale daily water balance model to support spatially continuous representation of flow intermittency throughout stream networks

Yu¹,

Hong²,

Dijk³

et al. 2020

Preprint

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Abstract. There is a growing interest globally in the spatial distribution of intermittently flowing streams and rivers, and how their spatial extent varies in relation to climatic factors. However, deriving consistent information on the extent of flow intermittency within river networks is hampered by the fact that streamflow gauges are often sparsely distributed and more often located within the most perennial parts of the river network. Here, we developed an approach to quantify catchment-wide streamflow intermittency over long timeframes and in a spatially explicit manner, using readily accessible and spatially contiguous daily runoff data from a national-scale water balance model. We examined the ability of the water balance model to simulate streamflow in two hydro-climatically distinctive (subtropical and temperate) regions in Australia, with a particular focus on low flow simulations. We also evaluated the effect of model time step (daily vs. monthly) on flow intermittency estimation to inform future model selection. The water balance model showed better performance in the temperate region characterised by steady baseflow than in the subtropical region with flashy hydrographs and frequent cease-to-flow periods. The model tended to overestimate low flow magnitude due to both overestimation of gains (e.g. groundwater release to baseflow) and underestimation of losses (e.g. transmission losses) during low-flow periods. Modelled patterns of flow intermittency revealed highly dynamic behaviour in space and time, with intermittent flows affecting between 29 % and 80 % of the river network over the period of 1911–2016. The daily flow model did not perform better than the monthly flow model in quantifying flow intermittency, and model selection should depend on the intended application of the model outputs. Our general approach to quantifying spatio-temporal patterns of flow intermittency is transferable to other parts of the world, and can inform hydro-ecological understanding and management of intermittent streams where limited gauging data are available.

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“…However, these streamflow characteristics are binary indicators of surface water presence (flowing vs. non-flowing), and do not adequately characterize variation in surface water extent through space and time. Research quantifying the dynamics and environmental determinants of variation in surface water extent throughout river networks is scarce (but see Jaeger et al, 2019). In addition to surface flow, stream channel characteristics (e.g.…”

Section: Introductionmentioning

confidence: 99%

Development and Application of Predictive Models of Surface Water Extent to Identify Aquatic Refuges in Eastern Australian Temporary Stream Networks

Bond

Bunn

et al. 2019

Water Resources Research

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Many organisms living in temporary streams rely on remnant surface water to survive during extended dry periods and recolonize newly established habitats when flow resumes. However, research on the spatiotemporal variations in surface water extent for entire river networks is scarce. In this study, we first present a new field method for rapid surface water assessment. Next, we develop predictive models relating observed water extent to environmental attributes at a large number of surveyed stream segments (n = 241) in eastern Australian coastal catchments. We use the models to predict daily variations in surface water dynamics throughout entire river networks over the period of 1911–2017, based on available long‐term environmental attributes influencing hydrological processes. We find descriptors of surface water extent can be accurately predicted based on robust internal and external validations. Environmental predictor variables representing water gaining processes were more important in predicting surface water extent than variables representing water losses. Simulated long‐term variations in surface water extent were highly dynamic through space and time, particularly in inland streams, which were predicted to be the driest on average. Total stream length with surface water ranged from 8,974 to 13,742 km across the study period. Our study presents a novel and practical approach to quantifying and predicting variations in surface water extent, with potential applicability to other parts of the world. The simulated surface water extent through space and time can be used to identify and prioritize potential aquatic refuge areas that sustain aquatic biodiversity in river networks during extended dry periods.

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Probability of Streamflow Permanence Model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest

Cited by 74 publications

References 55 publications

Dynamic stream network intermittence explains emergent dissolved organic carbon chemostasis in headwaters

Dynamic stream network intermittence explains emergent dissolved organic carbon chemostasis in headwaters

Evaluating a landscape-scale daily water balance model to support spatially continuous representation of flow intermittency throughout stream networks

Development and Application of Predictive Models of Surface Water Extent to Identify Aquatic Refuges in Eastern Australian Temporary Stream Networks

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