Filters: partyWithName: Water Resources (X) > Types: Map Service (X) > partyWithName: Colin A Penn (X)
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Ground-based discrete snowpack measurements were collected during winter field campaigns starting in 2020. These data were collected as part of the U.S. Geological Survey (USGS) Next Generation Water Observing System (NGWOS) Upper Colorado River Basin project focusing on the relation between snow dynamics and water resources. This data release consists of three child items. Each child item contains snow depth, snow density, snow temperature, or snow water equivalent values measured discretely in the field. The data are provided in comma separated value (CSV) files.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Colorado,
Colorado River,
Hydrology,
Integrated Water Science,
Rocky Mountains,
This data release includes simulation output from SnowModel (Liston and Elder, 2006), a well-validated process-based snow modeling system, and supporting snow, meteorological, and streamflow observations from the water years 2011 through 2015 (October 1, 2010, through September 30, 2015) across a 3,600 square kilometer model domain in the north-central Colorado Rocky Mountains. For each water year, SnowModel simulations were completed for a (1) baseline simulation, (2) bark-beetle disturbance condition simulation, (3) 2016 - 2035 future climate condition simulation (S1), and (4) 2046 - 2065 future climate condition simulation (S2). Sexstone and others (2018) provide details and summarize findings from each of the...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Bark beetles,
Climate warming,
Climatology,
Colorado Rocky Mountains,
Eddy covariance,
The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) was used to assess the effects of changing climate and land disturbance on seasonal streamflow in the Rio Grande Headwaters (RGHW) region. Three applications of PRMS in the RGHW were used to simulate 1) baseline effects of climate, 2) effects of bark-beetle induced tree mortality, and 3) effects of wildfire, on components of the hydrologic cycle and subsequent seasonal streamflow runoff from April through September for water years 1980 through 2017. PRMS input files and select PRMS output variables for each simulation are contained in this data release to accompany the journal article.
Optimal hydrograph separation (OHS) is a two-component, hydrograph separation method that uses a two-parameter, recursive digital filter (RDF) constrained via chemical mass balance to estimate the base flow contribution to a stream or river (Rimmer and Hartman, 2014; Raffensperger et al., 2017). A recursive digital filter distinguishes between high-frequency and low-frequency discharge data within a hydrograph, where high-frequency data corresponds to quick flow or storms and low-frequency data corresponds to base flow. The two parameters within the RDF are alpha and beta, both are unitless. Alpha is defined as the recession constant and typically found through recession analysis. For the purposes of this data release...
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