The National Map - Elevation

Gesch, Dean B.; Evans, Gayla A.; Mauck, James; Hutchinson, John M.; Carswell, William J.

doi:10.3133/fs20093053

Cited by 83 publications

(37 citation statements)

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“…Elevation bands used to distribute precipitation on the subgrid scale are generated using the National Elevation Dataset (NED) digital elevation model (Gesch et al, ). For the seven grid cells, we simulate only evergreen forest cover classifications (set to 100%) in order to limit the complexity of the sensitivity analysis.…”

Section: Methodsmentioning

confidence: 99%

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

Bennett

Blanco

Jonko

et al. 2018

Water Resources Research

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The Colorado River Basin is a fundamentally important river for society, ecology, and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent, and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space‐filling Latin Hypercube Sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance‐based approach. We find that snow‐dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

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Section: Methodsmentioning

confidence: 99%

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

Bennett

Blanco

Jonko

et al. 2018

Water Resources Research

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“…The elevation (m) and daily solar radiation values (watt hours per square meter; Wh/m 2 ) of camera stations were extracted from a 10‐m digital elevation model (DEM) from the National Elevation Dataset (Gesch et al. ). We used a global calculation, which incorporates direct and diffuse solar radiation and uses slope and aspect from the DEM to derive radiation values (Fu and Rich ).…”

Section: Methodsmentioning

confidence: 99%

Looking beyond wildlife: using remote cameras to evaluate accuracy of gridded snow data

Sirén

Somos‐Valenzuela

Callahan

et al. 2018

Remote Sens Ecol Conserv

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The use of remote cameras is widespread in wildlife ecology, yet few examples exist of their utility for collecting environmental data. We used a novel camera trap method to evaluate the accuracy of gridded snow data in a mountainous region of the northeastern US. We were specifically interested in assessing (1) how snow depth observations from remote cameras compare with gridded climate data, (2) the sources of error associated with the gridded data and (3) the influence of spatial sampling on bias. We compared daily observations recorded by remote cameras with Snow Data Assimilation System (SNODAS) gridded predictions using data from three winters (2014)(2015)(2016). Snow depth observations were correlated with SNODAS predictions for sites (R 2 = 0.20) and regions (R 2 = 0.16), yet we detected factors associated with SNODAS bias at both scales. Specifically, SNODAS underpredicted depths at high elevations, at sites with higher solar radiation, and within conifer-dominated forest. Depths were most underpredicted at highest elevations, up to 44 and 26 cm on average at the site and region scales, respectively. Bias was greatest when predictions were lowest, occasionally predicting snow absence when depths were >100 cm at camera sites. We also detected breakdowns in accuracy when certain environmental conditions varied within the 1 km 2 SNODAS grid cells. For example, underprediction was greatest when the solar radiation values of camera stations increased relative to the mean of the SNODAS grid cells. This relationship was most prominent in mountainous regions, suggesting that factors which influence solar radiation (e.g. topographic complexity) contribute to SNODAS inaccuracy. We caution using gridded snow data for ecological studies when bias is unknown. We suggest increased sampling to adjust for errors associated with gridded data products that arise from factors, such as forest cover and topographic variability. Increasing resolution and accuracy of climate data will improve predictions of species' responses to climate change.

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“…Predictor variables were extracted from a digital‐elevation model (DEM) and 2009 National Aerial Imagery Project (NAIP) imagery. Slope angle was computed from USGS 10‐m resolution DEM data, obtained from http://ned.usgs.gov [accessed 1 June 2010; verified 14 July 2011) (Gesch et al, 2009). Tree location and vegetation density were approximated with the Normalized Difference Vegetation Index (NDVI), calculated from four‐band NAIP imagery (red, green, blue, near infrared), and the first two principal components of the same NAIP image.…”

Section: Methodsmentioning

confidence: 99%

Soil Moisture Response to Snowmelt and Rainfall in a Sierra Nevada Mixed‐Conifer Forest

Bales

Hopmans

O’Geen

et al. 2011

Vadose Zone Journal

218

256

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Using data from a water‐balance instrument cluster with spatially distributed sensors we determined the magnitude and within‐catchment variability of components of the catchment‐scale water balance, focusing on the relationship of seasonal evapotranspiration to changes in snowpack and soil moisture storage. Co‐located, continuous snow depth and soil moisture measurements were deployed in a rain–snow transition catchment in the mixed‐conifer forest in the Southern Sierra Nevada. At each elevation sensors were placed in the open, under the canopy, and at the drip edge on both north‐ and south‐facing slopes. Snow sensors were placed at 27 locations, with soil moisture and temperature sensors placed at depths of 10, 30, 60, and 90 cm beneath the snow sensor. Soils are weakly developed (Inceptisols and Entisols) and formed from decomposed granite with properties that change with elevation. The soil–bedrock interface is hard in upper reaches of the basin (>2000 m) where glaciers have scoured the parent material approximately 18,000 yr ago. Below an elevation of 2000 m soils have a paralithic contact (weathered saprolite) that can extend beyond a depth of 1.5 m, facilitating pathways for deep percolation. Soils are wet and not frozen in winter, and dry out in the weeks following spring snowmelt and rain. Based on data from two snowmelt seasons, it was found that soils dry out following snowmelt at relatively uniform rates; however, the timing of drying at a given site may be offset by up to 4 wk because of heterogeneity in snowmelt at different elevations and aspects. Spring and summer rainfall mainly affected sites in the open, with drying after a rain event being faster than following snowmelt. Water loss rates from soil of 0.5 to 1.0 cm d−1 during the winter and snowmelt season reflect a combination of evapotranspiration and deep drainage, as stream baseflow remains relatively low. About one‐third of annual evapotranspiration comes from water storage below the 1‐m depth, that is, below mapped soil. We speculate that much of the deep drainage is stored locally in the deeper regolith during periods of high precipitation, being available for tree transpiration during summer and fall months when shallow soil water storage is limiting. Total annual evapotranspiration for water year 2009 was estimated to be approximately 76 cm.

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The National Map - Elevation

Abstract: A shaded-relief representation of the National Elevation Dataset (NED) covering the United States. Elevation is portrayed as a range of colors, from dark green for low elevations to white for high elevations.

Cited by 83 publications

References 0 publications

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

Looking beyond wildlife: using remote cameras to evaluate accuracy of gridded snow data

Soil Moisture Response to Snowmelt and Rainfall in a Sierra Nevada Mixed‐Conifer Forest

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