Geomorphology as a first order control on the connectivity of riparian ecohydrology

Cadol, Daniel; Wine, Michael L.

doi:10.1016/j.geomorph.2016.06.022

Cited by 18 publications

(14 citation statements)

References 69 publications

(27 reference statements)

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“…In the case of the Australian experience with wildfire-affected eucalypts, Nolan et al (2014) found that leaves resprouted along the trunk and branches, resulting in lower hydraulic resistance and hence higher transpiration per unit leaf area by nearly a factor of two. Therefore, despite the widespread practice of taking vegetation index as an index of transpiration (Nagler et al 2005, Wine and Hendrickx 2013, Cadol and Wine 2017, this approach is a simplification in areas in which the vegetation index-transpiration relationship changes following wildfire.…”

Section: Discussionmentioning

confidence: 99%

In ecoregions across western USA streamflow increases during post-wildfire recovery

Wine

Cadol

Makhnin

2018

Environ. Res. Lett.

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Continued growth of the human population on Earth will increase pressure on already stressed terrestrial water resources required for drinking water, agriculture, and industry. This stress demands improved understanding of critical controls on water resource availability, particularly in water-limited regions. Mechanistic predictions of future water resource availability are needed because non-stationary conditions exist in the form of changing climatic conditions, land management paradigms, and ecological disturbance regimes. While historically ecological disturbances have been small and could be neglected relative to climatic effects, evidence is accumulating that ecological disturbances, particularly wildfire, can increase regional water availability. However, wildfire hydrologic impacts are typically estimated locally and at small spatial scales, via disparate measurement methods and analysis techniques, and outside the context of climate change projections. Consequently, the relative importance of climate change driven versus wildfire driven impacts on streamflow remains unknown across the western USA. Here we show that considering wildfire in modeling streamflow significantly improves model predictions. Mixed effects modeling attributed 2%−14% of long-term annual streamflow to wildfire effects. The importance of this wildfire-linked streamflow relative to predicted climate change-induced streamflow reductions ranged from 20%−370% of the streamflow decrease predicted to occur by 2050. The rate of post-wildfire vegetation recovery and the proportion of watershed area burned controlled the wildfire effect. Our results demonstrate that in large areas of the western USA affected by wildfire, regional predictions of future water availability are subject to greater structural uncertainty than previously thought. These results suggest that future streamflows may be underestimated in areas affected by increased prevalence of hydrologically relevant ecological disturbances such as wildfire.

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Section: Discussionmentioning

confidence: 99%

In ecoregions across western USA streamflow increases during post-wildfire recovery

Wine

Cadol

Makhnin

2018

Environ. Res. Lett.

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“…), this practice could bias predictions toward wetlands that are more connected to surface hydrology (or simply the flow lines in the dataset being used). This may diminish the response of groundwater‐fed riparian areas (Cadol and Wine ) and isolated wetlands that would have otherwise been identified by the model. Therefore, we recommend developing initial models using only carefully selected spectral and terrain variables, assessing the results, and then adding ancillary variables as necessary.…”

Section: Discussionmentioning

confidence: 99%

An integrative modeling approach to mapping wetlands and riparian areas in a heterogeneous Rocky Mountain watershed

Chignell

Luizza

Young

et al. 2017

Remote Sens Ecol Conserv

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Accurate maps of wetlands and riparian areas are critical for targeting conservation and monitoring efforts. However, detailed inventories in mountain regions are largely non-existent, as conventional mapping approaches are hindered by high costs, remoteness, and landscape variability. Contemporary modeling techniques can circumvent many of these issues, but are often difficult to interpret and tend to rely on specialized datasets that prevent their wider application. In this study, we used machine learning, Landsat 8 imagery and geomorphometric indices to map the distribution of wetlands and riparian areas in the Cache la Poudre River watershed, Colorado, USA. We used a presence-background approach to develop and compare predictions from three popular algorithms: boosted regression trees, MaxEnt and random forests. In addition, we developed the models within three elevation-based life zones to account for altitudinal changes in ecohydrology and land use. Our results showed strong predictive performance, with top-performing models achieving area under the curve values as high as 0.98 and correctly classifying up to 95% of test data. Model performance varied by elevation zone, and no algorithm consistently outperformed the others. The boosted regression trees approach was uniquely able to differentiate wetlands from irrigated agriculture and residential areas in lower elevations. Multi-seasonal greenness and wetness indices were highly influential predictors in all models, underscoring the importance of capturing local phenological characteristics and hydrological regimes. Dissection and roughness terrain metrics were key predictors for identifying valley bottom meadows and emergent wetlands in high-elevation forests. We demonstrate how integrating ecological interpretation into the modeling workflow can inform conventional accuracy statistics and help bridge field-based and remote sensing perspectives. We also show how continuous model outputs can facilitate this process by depicting nuances of the wetland-upland continuum. Our approach requires only public data that are widely available, and can be easily adapted to other heterogeneous mountain settings.

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“…Field-based methods Assessed changes in water and sediment connectivity within a watershed based on observed changes in channel geometry and bed grain size Vanacker et al, 2005 Assessed limits to sediment connectivity based on the presence of landforms or depositional features that indicate sediment storage or constraints on sediment removal Fryirs et al, 2007 Used electrical resistance sensors to quantify streamflow continuity through time and space Jaeger and Olden, 2012 Used hydrologic modeling and indirect flood stage indicators in the field to map the flood inundation width as a measure of channelfloodplain connectivity during an extreme flood Croke et al, 2013 Distribution of bedrock knickpoints (and associated channel and valley characteristics) as a feature that disconnects hillslopechannel processes May et al, 2017 Longitudinal changes in channel geometry, sediment storage, and grain size distribution as indicators of tributary-induced longitudinal sediment disconnectivity along river channels Rice, 2017 Remotely based methods Measured connectivity index defined in Table 2 using ArcGIS software with 2.5 m digital terrain model developed from lidar data Cavalli et al, 2013 Used graph theory to illustrate sediment connectivity; a graph is a data structure consisting of a set of nodes connected by edges; nodes can represent locations in space, groups of objects, or the properties of objects and edges can represent any causal, statistical, inferential, or spatial relationship or a process; edges can be undirected or directed Heckmann and Schwanghart, 2013;Heckmann et al, 2015 Used topographic and vegetation cover data to calculate a mean flow path length as a measure of hydrological connectivity on hillslopes Puttock et al, 2013 Assessed connectivity within a river network by conceptualizing a network as composed of links (river reaches) and nodes (confluences or dams) and measured the distance between nodes Grill et al, 2014 Using digital elevation models (DEMs) or digital terrain models (DTMs) with differencing in ArcGIS to calculate changes in elevation/topography/sediment volume through time e.g., Micheletti et al, 2015;Wester et al, 2014 Calculated sand transport using dendritic connectivity index and compared to channel migration rates as calculated from aerial photographs Czuba and Foufoula-Georgiou, 2015 Assessed spatial differences in vertical hydrologic connectivity based on multi-year correlations among precipitation, streamflow, and riparian vegetation Cadol and Wine, 2017 Numerical simulations of water and sediment routing through networks Coulthard and Van De Wiel, 2017; Gran and Czuba, 2017 to achieve (Blue and Brierley, 2016), how a particular area targeted...…”

Section: Methods Referencementioning

confidence: 99%

Connectivity in rivers

Wohl

2017

Progress in Physical Geography: Earth and Environment

181

112

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Connectivity describes the degree to which matter and organisms can move among spatially defined units in a natural system. River connectivity is typically described in longitudinal, lateral, and vertical dimensions within the river corridor and the watershed and can be conceptualized as a continuum from fully connected to disconnected over diverse temporal and spatial scales. Explicit characterization of connectivity helps understanding of disparities among short-term, local rates of flux and inferred fluxes over larger scales. Connectivity also strongly influences the response of rivers to natural and human disturbances. Investigations of connectivity facilitate the recognition of processes that cross traditional disciplinary boundaries, as well as understanding of nonlinear behavior and retention within rivers. Enhancing the ability to identify, quantify, and predict the processes that create and maintain connectivity is integral to the effective management of rivers.

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Geomorphology as a first order control on the connectivity of riparian ecohydrology

Cited by 18 publications

References 69 publications

In ecoregions across western USA streamflow increases during post-wildfire recovery

In ecoregions across western USA streamflow increases during post-wildfire recovery

An integrative modeling approach to mapping wetlands and riparian areas in a heterogeneous Rocky Mountain watershed

Connectivity in rivers

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