USGS scientist John Fulton measures streamflow on Middle Fork Ranch Creek, Colorado using instream, conventional methods. USGS radar equipment is also shown recording non-contact river discharge.
Graham Sexstone
I am a Research Hydrologist in the USGS Colorado Water Science Center and Affiliate Faculty member of the Department of Geosciences at Colorado State University.
I investigate snow and hydrological processes in mountainous environments of the United States that are critically important for understanding water resources and availability for the nation. My current research uses a combination of field-based measurements, remote sensing observations, and physically based modeling over a range of spatial scales to better understand the spatial and temporal variability of snow water resources and how changes in snow processes are linked with changes to water availability, water budgets, and water quality. I received my PhD in Watershed Science from Colorado State University in 2016 and studied the importance of snow sublimation to seasonal snowpack variability. A list of my Science and Products are provided below and can also be viewed on my Google Scholar page.
Science and Products
Rocky Mountain Regional Snowpack Chemistry Monitoring Study
Estimating the Future Effects of Forest Disturbance on Snow Water Resources in a Changing Environment
Linking water, carbon, and nitrogen cycles in seasonally snow-covered catchments under changing land resource conditions
Snowpack Sublimation - Measurements and Modeling in the Colorado River Basin
Lidar Point Clouds (LPCs), Digital Elevation Models (DEMs), and Snow Depth Raster Maps Derived from Lidar Data Collected on Small, Uncrewed Aircraft Systems in the Upper Colorado River Basin, Colorado, 2020-22
High Resolution Canopy Structure and Density Metrics for Southwest Colorado Derived from 2019 Aerial Lidar
Snow Measurements in Specific Canopy Structure Regimes for the 2022-2023 Water Years, North of Coal Creek, San Juan Mountains, Colorado, USA
NGWOS Ground Based Discrete Snowpack Measurements
High Resolution Current and Future Climate SnowModel Simulations in the Upper Colorado River Basin
Basin Characteristics and Streamflow Statistics for Selected Gages, Alaska, USA (ver. 2.0, September, 2022)
Historical simulated snowpack for the Lake Sherburne, MT watershed and vicinity, water years 1980-2019
National Hydrologic Model Alaska Domain parameter database, version 1
SnowModel simulations and supporting observations for the Rio Grande Headwaters, southwestern Colorado, United States, 1984 - 2017
Climatological data for the Loch Vale watershed in Rocky Mountain National Park, Colorado, water years 1992-2019
Geospatial Fabric for the National Hydrologic Model Alaska Domain, version 1
Data release in support of Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model
USGS scientist John Fulton measures streamflow on Middle Fork Ranch Creek, Colorado using instream, conventional methods. USGS radar equipment is also shown recording non-contact river discharge.
Aquatic carbon export and dynamics in mountain headwater streams of the western U.S.
Snowpack relative permittivity and density derived from near-coincident lidar and ground-penetrating radar
Snow surface roughness across spatio-temporal scales
High resolution SnowModel simulations reveal future elevation-dependent snow loss and earlier, flashier surface water input for the Upper Colorado River Basin
Upper Rio Grande Basin water-resource status and trends: Focus area study review and synthesis
Evaluating hydrologic region assignment techniques for ungaged basins in Alaska, USA
Black carbon dominated dust in recent radiative forcing on Rocky Mountain snowpacks
Snow depth retrieval with an autonomous UAV-mounted software-defined radar
Spatial variability in seasonal snowpack trends across the Rio Grande headwaters (1984 - 2017)
Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters
Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model
Relating hydroclimatic change to streamflow, baseflow, and hydrologic partitioning in the Upper Rio Grande Basin, 1980 to 2015
Science and Products
- Science
Rocky Mountain Regional Snowpack Chemistry Monitoring Study
Snowpacks collect atmospheric deposition throughout the snowfall season and offer a unique opportunity to obtain a composite sample of the chemistry of most of the annual precipitation at high elevations [> 1,800 meters]. The purpose of the snowpack network is to determine annual concentrations and depositional amounts of selected nutrients and other constituents in snow resulting from atmospheric...Estimating the Future Effects of Forest Disturbance on Snow Water Resources in a Changing Environment
In the Western U.S., approximately 65% of the water supply comes from forested regions with most of the water that feeds local rivers coming from snowmelt that originates in mountain forests. The Rio Grande headwaters (I.e. the primary water generating region of the Rio Grande river) is experiencing large changes to the landscape primarily from forest fires and bark beetle infestations. Already, 8Linking water, carbon, and nitrogen cycles in seasonally snow-covered catchments under changing land resource conditions
Changes in snowpack accumulation, distribution, and melt in high-elevation catchments are likely to have important impacts on water, carbon, and nitrogen cycles, which are tightly coupled through exchanges of energy and biogeochemical compounds between atmospheric, terrestrial, and aquatic environments. Our research helps to better understand how changes in climate will affect water availability...Snowpack Sublimation - Measurements and Modeling in the Colorado River Basin
Snow is an essential resource in the western United States (U.S.), providing water for drinking, irrigation, industry, energy production, and ecosystems across much of the region. In the mountains of the western U.S., most precipitation falls as snow, which accumulates in seasonal snowpacks that serve as a large natural reservoir. Snowpack sublimation, which is analogous to evaporation from land... - Data
Filter Total Items: 13
Lidar Point Clouds (LPCs), Digital Elevation Models (DEMs), and Snow Depth Raster Maps Derived from Lidar Data Collected on Small, Uncrewed Aircraft Systems in the Upper Colorado River Basin, Colorado, 2020-22
This data release consists of three child items distinguishing the following types of data: light detection and ranging (lidar) point clouds (LPCs), digital elevation models (DEMs), and snow depth raster maps. These three data types are all derived from lidar data collected on small, uncrewed aircraft systems (sUAS) at study areas in the Upper Colorado River Basin, Colorado, from 2020 to 2022. TheHigh Resolution Canopy Structure and Density Metrics for Southwest Colorado Derived from 2019 Aerial Lidar
Canopy density and canopy structure metrics were derived for the San Juan Mountains of southwest Colorado from aerial point cloud data at a 1-meter (m) resolution. The aerial lidar data originated from the ‘CO_Southwest_NRCS_2018’ project prepared by Quantum Spatial for the U.S. Geological Survey (USGS) from a series of flyovers between 2018 and 2019 and were made available in 2021. Canopy densitySnow Measurements in Specific Canopy Structure Regimes for the 2022-2023 Water Years, North of Coal Creek, San Juan Mountains, Colorado, USA
These data include snow depth and snow water equivalence (SWE) for the 2022 and 2023 water years during 16 separate field campaigns. The field area is comprised of 311 surveyed points in, on the perimeter of, and surrounding six forest openings next to Coal Creek off Coal Bank Pass in the San Juan Mountains in Southwest Colorado, USA. These measurements were taken to look at the relationship betweNGWOS Ground Based Discrete Snowpack Measurements
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 containHigh Resolution Current and Future Climate SnowModel Simulations in the Upper Colorado River Basin
This data release contains SnowModel snow evolution simulation output on a 100-meter (m) geospatial grid for a 311 kilometer (km) × 300 km model domain in Colorado, United States, encompassing the Colorado and Gunnison River Basin headwaters in the Upper Colorado River Basin. Weather Research and Forecasting (WRF) Model convection-permitting and orography-resolving (4-km grid spacing) regional cliBasin Characteristics and Streamflow Statistics for Selected Gages, Alaska, USA (ver. 2.0, September, 2022)
This data release documents the data used for the associated publication "Evaluating hydrologic region assignment techniques for ungaged watersheds in Alaska, USA" (Barnhart and others, 2022) The data sets within this release are stored in 14 files: (1) Streamflow observations and sites used. (2) Statistically estimated streamflow values computed for each site. (3) Streamflow statistics computed fHistorical simulated snowpack for the Lake Sherburne, MT watershed and vicinity, water years 1980-2019
Abstract This data release contains historical SnowModel (Liston and Elder, 2006) output for the Lake Sherburne, MT watershed and surrounding area. The two quantities simulated for this release were snow water equivalent depth (swed), the liquid water equivalent depth stored as snow in the simulation domain, and runoff (roff), which includes snowmelt at the snow-soil interface and rainfall on pixeNational Hydrologic Model Alaska Domain parameter database, version 1
This data release contains input data for hydrologic simulations of the Alaska Domain application of the U.S. Geological Survey (USGS) Precipitation Runoff Modelling System (PRMS) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan and others, 2018). The NHM Alaska Domain parameter database consists of 114 parameter files in ASCII format (CSV), two files needed to run the ASnowModel simulations and supporting observations for the Rio Grande Headwaters, southwestern Colorado, United States, 1984 - 2017
This data release supports the study by Sexstone and others (2020) and contains simulation output from SnowModel (Liston and Elder, 2006), a well-validated process-based snow modeling system. Simulations are for water years 1984 through 2017 (October 1, 1983 through September 30, 2017) across a 11,200 square kilometer model domain in the San Juan Mountains of southwestern Colorado, United States tClimatological data for the Loch Vale watershed in Rocky Mountain National Park, Colorado, water years 1992-2019
This data release contains hourly means of climatological data collected by the U.S. Geological Survey (USGS) from 10/1/1991 to 9/30/2019 at three weather stations in the Loch Vale watershed in Rocky Mountain National Park (RMNP), Colorado. In order of increasing elevation, the three weather stations are Loch Vale meteorological station at RMNP, Colo. (Main weather station, USGS station 4017191053Geospatial Fabric for the National Hydrologic Model Alaska Domain, version 1
This metadata record documents a geospatial dataset for the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS) used to drive the National Hydrologic Model (NHM). The Alaska Geospatial Fabric v1 is the spatial representation of the hydrologic response units (HRUs) used for the PRMS NHM Alaska domain. These HRUs were generated using the twelve-digit Hydrologic Unit Code (HUC12) waterData release in support of Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model
This data release includes simulation output from a modeling experiment conducted using the initial calibration of the conterminous United States (CONUS) application of the Precipitation-Runoff Modeling System (PRMS) (Hay, 2019) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan et al, 2018). The study associated with this data release (Sexstone et al., 2019) used the same - Multimedia
USGS scientist measures streamflow on Middle Fork Ranch Creek, COUSGS scientist measures streamflow on Middle Fork Ranch Creek, CO
USGS scientist John Fulton measures streamflow on Middle Fork Ranch Creek, Colorado using instream, conventional methods. USGS radar equipment is also shown recording non-contact river discharge.
USGS scientist John Fulton measures streamflow on Middle Fork Ranch Creek, Colorado using instream, conventional methods. USGS radar equipment is also shown recording non-contact river discharge.
- Publications
Filter Total Items: 21
Aquatic carbon export and dynamics in mountain headwater streams of the western U.S.
Mountain headwater streams actively cycle carbon, receiving it from terrestrial landscapes and exporting it through downstream transport and gas exchange with the atmosphere. Although their importance is now widely recognized, aquatic carbon fluxes in headwater streams remain poorly characterized. In this study, aquatic carbon fluxes were measured in 15 mountain headwater streams and were used inAuthorsDavid W. Clow, Garrett Alexander Akie, Robert G. Striegl, Colin Penn, Graham A. Sexstone, Gabrielle L. KeithSnowpack relative permittivity and density derived from near-coincident lidar and ground-penetrating radar
Depth-based and radar-based remote sensing methods (e.g., lidar, synthetic aperture radar) are promising approaches for remotely measuring snow water equivalent (SWE) at high spatial resolution. These approaches require snow density estimates, obtained from in-situ measurements or density models, to calculate SWE. However, in-situ measurements are operationally limited, and few density models haveAuthorsRandall Bonnell, Daniel McGrath, Andrew Hedrick, Ernesto Trujillo, Tate Meehan, Keith Williams, Hans-Peter Marshall, Graham A. Sexstone, John Fulton, Michael Ronayne, Steven R. Fassnacht, Ryan Webb, Katherine HaleSnow surface roughness across spatio-temporal scales
The snow surface is at the interface between the atmosphere and Earth. The surface of the snowpack changes due to its interaction with precipitation, wind, humidity, short- and long-wave radiation, underlying terrain characteristics, and land cover. These connections create a dynamic snow surface that impacts the energy and mass balance of the snowpack, blowing snow potential, and other snowpack pAuthorsSteven R. Fassnacht, Kazuyoshi Suzuki, Jessica E. Sanow, Graham A. Sexstone, Anna K.D. Pfohl, Molly E. Tedesche, Bradley M. Simms, Eric S. ThomasHigh resolution SnowModel simulations reveal future elevation-dependent snow loss and earlier, flashier surface water input for the Upper Colorado River Basin
Continued climate warming is reducing seasonal snowpacks in the western United States, where >50% of historical water supplies were snowmelt-derived. In the Upper Colorado River Basin, declining snow water equivalent (SWE) and altered surface water input (SWI, rainfall and snowmelt available to enter the soil) timing and magnitude affect streamflow generation and water availability. To adapt effecAuthorsJohn C. Hammond, Graham A. Sexstone, Annie L. Putman, Theodore B. Barnhart, David Rey, Jessica M. Driscoll, Glen Liston, Kristen L. Rasmussen, Daniel McGrath, Steven R. Fassnacht, Stephanie K. KampfUpper Rio Grande Basin water-resource status and trends: Focus area study review and synthesis
The Upper Rio Grande Basin (URGB) is a critical international water resource under pressure from a myriad of climatic, ecological, infrastructural, water-use, and legal constraints. The objective of this study is to provide a comprehensive assessment of the spatial distribution and temporal trends of selected water-budget components (snow processes, evapotranspiration (ET), streamflow processes, aAuthorsKyle R. Douglas-Mankin, Christine Rumsey, Graham A. Sexstone, Tamara I. Ivahnenko, Natalie Houston, Shaleene Chavarria, Gabriel B. Senay, Linzy K. Foster, Jonathan V. Thomas, Allison K. Flickinger, Amy E. Galanter, C. David Moeser, Toby L. Welborn, Diana E. Pedraza, Patrick M. Lambert, Michael Scott JohnsonEvaluating hydrologic region assignment techniques for ungaged basins in Alaska, USA
Building continental-scale hydrologic models in data-sparse regions requires an understanding of spatial variation in hydrologic processes. Extending these models to ungaged locations requires techniques to group ungaged locations with gaged ones to make process importance and model parameter transfer decisions to ungaged locations. This analysis (1) tested the utility of fundamental streamflow stAuthorsTheodore B. Barnhart, William H. Farmer, John C. Hammond, Graham A. Sexstone, Janet H. Curran, Joshua C. Koch, Jessica M. DriscollBlack carbon dominated dust in recent radiative forcing on Rocky Mountain snowpacks
The vast majority of surface water resources in the semi-arid western United States start as winter snowpack. Solar radiation is a primary driver of snowmelt, making snowpack water resources especially sensitive to even small increases in concentrations of light absorbing particles such as mineral dust and combustion-related black carbon (BC). Here we show, using fresh snow measurements and snowpaAuthorsKelly Gleason, Joseph R. McConnell, Monica Arienzo, Graham A. Sexstone, Stefan RahimiSnow depth retrieval with an autonomous UAV-mounted software-defined radar
We present results from a field campaign to measure seasonal snow depth at Cameron Pass, Colorado, using a synthetic ultrawideband software-defined radar (SDRadar) implemented in commercially available Universal Software Radio Peripheral (USRP) software-defined radio hardware and flown on a small hexacopter unmanned aerial vehicle (UAV). We coherently synthesize an ultrawideband signal from steppeAuthorsS. Prager, Graham A. Sexstone, Daniel J McGrath, John Fulton, Mahta MoghaddamSpatial 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 AssimilationAuthorsGraham A. Sexstone, Colin A. Penn, Glen Liston, Kelly Gleason, C. David Moeser, David W. ClowChanges 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 periodAuthorsColin A. Penn, David W. Clow, Graham A. Sexstone, Sheila F. MurphyRunoff sensitivity to snow depletion curve representation within a continental scale hydrologic model
The spatial variability of snow water equivalent (SWE) can exert a strong influence on the timing and magnitude of snowmelt delivery to a watershed. Therefore, the representation of subgrid or subwatershed snow variability in hydrologic models is important for accurately simulating snowmelt dynamics and runoff response. The U.S. Geological Survey National Hydrologic Model infrastructure with the PAuthorsGraham A. Sexstone, Jessica M. Driscoll, Lauren Hay, John C. Hammond, Theodore B. BarnhartRelating hydroclimatic change to streamflow, baseflow, and hydrologic partitioning in the Upper Rio Grande Basin, 1980 to 2015
Understanding how changing climatic conditions affect streamflow volume and timing is critical for effective water management. In the Rio Grande Basin of the southwest U.S., decreasing snowpack, increasing minimum temperatures, and decreasing streamflow have been observed in recent decades, but the effects of hydroclimatic changes on baseflow, or groundwater discharge to streams, have not been invAuthorsChristine Rumsey, Matthew P. Miller, Graham A. Sexstone