Geology topics

Colin A. Penn

Publications and source records attributed to Colin A. Penn.

8 recordsLinked to original sources

USGS2020

Groundwater levels in the Denver Basin bedrock aquifers of Douglas County, Colorado, 2011–19

Municipal and domestic water users in Douglas County, Colorado, rely on groundwater from the bedrock aquifers in the Denver Basin aquifer system as part of their water supply. The four principal Denver Basin bedrock aquifers are, from shallowest to deepest, the Dawson aquifer (divided administratively into “upper” and “lower” Dawson aquifers in Douglas County), the Denver aquifer, the Arapahoe aquifer, and the Laramie-Fox Hills aquifer. Increased groundwater pumping in response to rapid population growth and development has led to declining groundwater levels in Douglas County, where groundwater is a primary water source for densely populated and rural communities. The U.S. Geological Survey, in cooperation with the Rural Water Authority of Douglas County, began a study in 2011 to assess the groundwater resources of the Denver Basin bedrock aquifers within the county. The primary purpose of this report is to present a summary of groundwater levels measured during the study period (2011–19) and present results from statistical analyses of changes in groundwater-level elevations, reported above the land-surface datum, North American Vertical Datum of 1988, through time. During the study period, January 2011 through June 2019, discrete groundwater levels were routinely measured at 36 wells producing from Denver Basin bedrock aquifers within Douglas County. Of the 36 wells, 15 are instrumented with pressure transducers that record groundwater-level measurements at hourly intervals, and these data were temporally aggregated into time-series records. During 2011, wells were added to the monitoring network in phases, so that the start dates of the well records are noncontemporaneous. To keep temporal analysis among wells consistent, the periods of record used in statistical analyses were from February 2012 through February 2019 for the discrete data and from January 2012 through June 2019 for the time-series data. The upper Dawson, lower Dawson, Denver, and Arapahoe aquifers had some wells with rises in calculated groundwater-level elevations, but most wells showed declines on the basis of statistically significant trends and the relative differences in static groundwater-level elevations between the February 2012 and February 2019 measurements. Neither of the two wells in the Laramie-Fox Hills aquifer showed significant trends in groundwater-level elevations, and these wells had few static discrete measurements, precluding a comparison between 2012 and 2019 static groundwater-level elevations. Of the 13 wells in the upper Dawson, lower Dawson, Denver, and Arapahoe aquifers with significant trends in discrete groundwater-level elevation measurements, the records of 12 wells demonstrated negative trends during the study period. The upper Dawson, lower Dawson, Denver, and Arapahoe aquifers had median significant trends of −0.23, −0.31, −0.92, and −2.26 feet per year, respectively. Although the Arapahoe aquifer had the greatest negative median trend, this median only represents one well with significant trends. Otherwise, the Denver aquifer had the next greatest negative trend, with a median trend of −0.92 foot per year. Significant trends in time-series groundwater-level elevations agreed with significant trends in discrete groundwater-level elevations; for all wells with statistically significant trends in discrete and in time-series groundwater-level elevation data, trend estimates from the two records were within 0.1 foot per year of each other. Potentiometric-surface maps of the upper Dawson, lower Dawson, and Denver aquifers, created using discrete static groundwater levels measured in February 2019, show that groundwater flow direction for the upper Dawson, lower Dawson, and Denver aquifers is generally from south to north. Results of this study could guide future groundwater monitoring in the county and aid in long-term planning of water resources.

Colorado↗

USGS2020

Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters

Seasonal streamflow forecast bias, changes in climate, snowpack, and land cover, and the effects of these changes on relations between basin‐wide snowpack, SNOw TELemetry (SNOTEL) station snowpack, and seasonal streamflow were evaluated in the headwaters of the Rio Grande, Colorado. Results indicate that shifts in the seasonality of precipitation and changing climatology are consistent with periods of overprediction and underprediction in streamflow forecasts. Multiple linear regression of SNOTEL data, postcedent precipitation, and land‐cover changes explained 2%–18% more variability in streamflow prediction than using SNOTEL station data alone. Simulated basin‐wide snowpack from a physically based model had significant negative trends in snow water equivalent (−4.33 mm/yr) and snow‐covered area (−0.05%/yr) during the melt period April–June. Simulated streamflow from a precipitation‐runoff model increased an average 5% when the effects of bark beetle‐induced tree mortality were compared to a baseline simulation with static vegetation. The effects of a 2013 wildfire increased simulated seasonal streamflow an average 35% for 1–4 years postfire. The combined effects of climate and land‐cover changes on snowpack‐streamflow relations highlight the difficulty in seasonal streamflow forecasting, which has important implications for water‐resource management.

Colorado↗

USGS2020

Spatial variability in seasonal snowpack trends across the Rio Grande headwaters (1984 - 2017)

This study evaluated the spatial variability of trends in simulated snowpack properties across the Rio Grande headwaters of Colorado using the SnowModel snow evolution modeling system. SnowModel simulations were performed using a grid resolution of 100 m and 3-hourly time step over a 34-yr period (1984–2017). Atmospheric forcing was provided by phase 2 of the North American Land Data Assimilation System, and the simulations accounted for temporal changes in forest canopy from bark beetle and wildfire disturbances. Annual summary values of simulated snowpack properties [snow metrics; e.g., peak snow water equivalent (SWE), snowmelt rate and timing, and snow sublimation] were used to compute trends across the domain. Trends in simulated snow metrics varied depending on elevation, aspect, and land cover. Statistically significant trends did not occur evenly within the basin, and some areas were more sensitive than others. In addition, there were distinct trend differences between the different snow metrics. Upward trends in mean winter air temperature were 0.3°C decade −1 , and downward trends in winter precipitation were −52 mm decade −1 . Middle elevation zones, coincident with the greatest volumetric snow water storage, exhibited the greatest sensitivity to changes in peak SWE and snowmelt rate. Across the Rio Grande headwaters, snowmelt rates decreased by 20% decade −1 , peak SWE decreased by 14% decade −1 , and total snowmelt quantity decreased by 13% decade −1 . These snow trends are in general agreement with widespread snow declines that have been reported for this region. This study further quantifies these snow declines and provides trend information for additional snow variables across a greater spatial coverage at finer spatial resolution.

Colorado↗

USGS2019

Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models

Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribution of base flow inputs and the utility of this method to build a hydrologic model calibration dataset. OHS models with acceptable goodness-of-fit criteria were insensitive to drainage area, stream density, watershed slope, elevation, agricultural or perennial snow/ice land cover, average annual precipitation, runoff, or evapotranspiration, implying that OHS results are a viable calibration dataset applicable in diverse watersheds. OHS-estimated base flow contribution was compared to base flow-like model components from the USGS National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS). The NHM-PRMS variable gwres_flow is most conceptually like a base flow component of streamflow but the gwres_flow contribution to total streamflow is generally smaller than the OHS-estimated base flow contribution. The NHM-PRMS variable slow_flow , added to gwres_flow , produced similar or greater estimates of base flow contributions to total streamflow than the OHS-estimated base flow contribution but was dependent on the total flow magnitude.

conterminous United States↗

USGS2019

Groundwater-Level Elevations in the Denver Basin Bedrock Aquifers of Elbert County, Colorado, 2015–18

Public and domestic water supplies in Elbert County, Colorado, rely on groundwater withdrawals from five bedrock aquifers in the Denver Basin aquifer system (lower Dawson, upper Dawson, Denver, Arapahoe, and Laramie-Fox Hills) to meet water demands. Increased pumping in response to regional population growth and development has led to declining groundwater levels in neighboring Douglas County. The U.S. Geological Survey, in cooperation with the Elbert County Board of County Commissioners, began a study in 2015 to monitor groundwater levels within Elbert County. The purpose of this study is to report on groundwater levels measured between April 2015 and June 2018, and analyze trends and changes in groundwater-level elevations throughout the county. Discrete groundwater levels were measured at 42 wells within Elbert County. Six of those wells contained equipment to make and record continuous groundwater-level measurements at hourly intervals. All five aquifers had wells with a rise in groundwater-level elevation and wells with a decline in groundwater-level elevation, based on a relative change in groundwater-level elevation between the April 2015 and April 2018 measurements. All aquifers except the upper Dawson had more wells with significant negative trends in discrete groundwater-level elevations than significant positive trends; however, at least one well within the upper Dawson, lower Dawson, Arapahoe, and Laramie-Fox Hills aquifers had a significant positive trend. Wells screened in the lower Dawson aquifer consistently had the most significant negative trends, with an average trend of −1.96 feet per year (ft/year). The upper Dawson, Denver, Arapahoe, and Laramie-Fox Hills aquifers had average trends of 0.03 ft/year, −1.04 ft/year, −0.46 ft/year, and −0.65 ft/year, respectively. Trends in continuous groundwater-level elevations were in agreement with significant trends in discrete groundwater-level elevations. Potentiometric-surface maps of the upper and lower Dawson aquifers for April 2015 and April 2018 show that differences in hydraulic head from the two measurement periods were greatest along the western part of Elbert County. Results of this study could guide future groundwater monitoring in the county and aid in long-term planning of water resources.

Colorado↗

USGS2018

Snow sublimation in mountain environments and its sensitivity to forest disturbance and climate warming

Snow sublimation is an important component of the snow mass balance, but the spatial and temporal variability of this process is not well understood in mountain environments. This study combines a process‐based snow model (SnowModel) with eddy covariance (EC) measurements to investigate (1) the spatio‐temporal variability of simulated snow sublimation with respect to station observations, (2) the contribution of snow sublimation to the ablation of the snowpack, and (3) the sensitivity and response of snow sublimation to bark beetle‐induced forest mortality and climate warming across the north‐central Colorado Rocky Mountains. EC‐based observations of snow sublimation compared well with simulated snow sublimation at stations dominated by surface and canopy sublimation, but blowing snow sublimation in alpine areas was not well captured by the EC instrumentation. Water balance calculations provided an important validation of simulated sublimation at the watershed scale. Simulated snow sublimation across the study area was equivalent to 28% of winter precipitation on average, and the highest relative snow sublimation fluxes occurred during the lowest snow years. Snow sublimation from forested areas accounted for the majority of sublimation fluxes, highlighting the importance of canopy and sub‐canopy surface sublimation in this region. Simulations incorporating the effects of tree mortality due to bark‐beetle disturbance resulted in a 4% reduction in snow sublimation from forested areas. Snow sublimation rates corresponding to climate warming simulations remained unchanged or slightly increased, but total sublimation losses decreased by up to 6% because of a reduction in snow covered area and duration.

Water Resources Research↗

USGS2016

Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed

The effects of mountain pine beetle (MPB)-induced tree mortality on a headwater hydrologic system were investigated using an integrated physical modeling framework with a high-resolution computational grid. Simulations of MPB-affected and unaffected conditions, each with identical atmospheric forcing for a normal water year, were compared at multiple scales to evaluate the effects of scale on MPB-affected hydrologic systems. Individual locations within the larger model were shown to maintain hillslope-scale processes affecting snowpack dynamics, total evapotranspiration, and soil moisture that are comparable to several field-based studies and previous modeling work. Hillslope-scale analyses also highlight the influence of compensating changes in evapotranspiration and snow processes. Reduced transpiration in the Grey Phase of MPB-induced tree mortality was offset by increased late-summer evaporation, while overall snowpack dynamics were more dependent on elevation effects than MPB-induced tree mortality. At the watershed scale, unaffected areas obscured the magnitude of MPB effects. Annual water yield from the watershed increased during Grey Phase simulations by 11 percent; a difference that would be difficult to diagnose with long-term gage observations that are complicated by inter-annual climate variability. The effects on hydrology observed and simulated at the hillslope scale can be further damped at the watershed scale, which spans more life zones and a broader range of landscape properties. These scaling effects may change under extreme conditions, e.g., increased total MPB-affected area or a water year with above average snowpack.

Water Resources Research↗

USGS2015

Water-quality response to a high-elevation wildfire in the Colorado Front Range

Water quality of the Big Thompson River in the Front Range of Colorado was studied for 2 years following a high‐elevation wildfire that started in October 2012 and burned 15% of the watershed. A combination of fixed‐interval sampling and continuous water‐quality monitors was used to examine the timing and magnitude of water‐quality changes caused by the wildfire. Prefire water quality was well characterized because the site has been monitored at least monthly since the early 2000s. Major ions and nitrate showed the largest changes in concentrations; major ion increases were greatest in the first postfire snowmelt period, but nitrate increases were greatest in the second snowmelt period. The delay in nitrate release until the second snowmelt season likely reflected a combination of factors including fire timing, hydrologic regime, and rates of nitrogen transformations. Despite the small size of the fire, annual yields of dissolved constituents from the watershed increased 20–52% in the first 2 years following the fire. Turbidity data from the continuous sensor indicated high‐intensity summer rain storms had a much greater effect on sediment transport compared to snowmelt. High‐frequency sensor data also revealed that weekly sampling missed the concentration peak during snowmelt and short‐duration spikes during rain events, underscoring the challenge of characterizing postfire water‐quality response with fixed‐interval sampling.

Colorado↗