United States Geological Survey

New Mexico Water Science Center

Hydrologist • July 2016 - Present

Serve as the center's technical authority on all surface water modeling and snow hydrology activities, both, in the office and the field.

Act as a regional technical advisor to external land managers with stakes in water resources and planning.

Charged with all technical watershed-modeling activities.

Develop novel data processing and analysis techniques.

Currently developing and implementing novel characterizations of forests and modeling tools to quantify the effects of forest disturbance and changing climate on water resources.

WSL Institute for Snow and Avalanche Research SLF

Davos, Switzerland

Snow Hydrologist / PhD Candidate • February 2012 - February 2016

Snow model and analysis tool development

Aerial and terrestrial LiDAR (light detection and ranging) data gathering, and manipulation

Snow survey campaign supervision (total: 12 employees)

World Business Council For Sustainable Development

Geneva, Switzerland

Contract Hydrologist • September 2011 - February 2012

Water and energy use linkage analyses between food, feed, and fiber management scenarios

Knowledge exchange coordination between UN organizations, research institutes, and businesses for water related projects

WSL Institute for Snow and Avalanche Research SLF

Davos, Switzerland

Snow Hydrology Intern• January 2011 - July 2011

Snow survey campaign leader within a high alpine basin in avalanche terrain

Snow melt modeling implementation and analysis

Geographic data parsing and analysis

University of Nevada, Reno

Research Assistant• September 2008 - December 2010

Wireless snow depth sensing equipment and affiliated meteorological station deployment, maintenance, and analysis

Statistical and geo-statistical modeling of snow

Stilling well and V-notch weir installation in an urban watershed

Bureau of Land Management/ U.S. Forest Service

Public Lands Center - Durango, Colorado

Hydrologic Technician• 2005 - 2007

Surface and groundwater water quantity and quality monitoring in springs and streams within Colorado, Utah, and New Mexico

Groundwater monitoring well and piezometer installation

Forest stream remediation and characterization

University of New Mexico

(2025 -2026) Department of Earth and Planetary Sciences

'Physical Hydrology' (476)

Guest Instructure and course development for Snow Hydrology Module

Fort Lewis College

(2023 -2026) Department of Environmental Science

'Collaborative Environmental Research' (400)

'Snow Hydrology' (470)

Guest Instructor and course module development for field measurement techniques for snow and forests

Swiss Federal Institute of Technology (ETH)

Zürich, Switzerland

(2013 - 2014) Department of Environment Systems Science

'Environmental Measurement Laboratory' (701)

Course and laboratory structure development for a 6-hour lecture module designed to integrate matlab programing with remotely sensed data

University of Nevada, Reno

(2008 - 2010) Department of Natural Resources and Environmental Science

'Principles of Ecohydrology' (295)

'Ecohydrology Field Camp (400)

New course material and method development

Field and laboratory lecturing and supervision 

University of Nevada, Reno Cooperative Extension

(2009 - 2010) 'Discover your Future'

Basic hydrologic field methods and applications: activity leader and guest lecturer for high school students

• Linhof, B., Moeser, D., Nichols, J., Kurzweil, J., 2026, Beavers as nature-based solutions to snowpack loss in Northern New Mexico, U.S. Geological Survey Fact Sheet, IN REVIEW.

• Norman, L., Cassassuce, F., Mack, T., Petrakis, R., Morales, A., Sorrenson, J., Evans, D., Garcia, D., Dominquez, A., strong>Moeser, D.,  Galanter, A., Lim, C., McDowell, J., White, E., Gomis, F., Villareal, M., Patron, G., Von Nonn, J., Smith, B., Wurl, J., Troyo-Diequez, E., Campos, A., Lane, J., 2026, Capturing Cyclonic Rainfall for Groundwater Recharge in Arid Regions: The Role of NIDS in Terrestrial Water Storage. Water Resources Research, In Review.

• Moeser, D, Sexstone, G., Kurzweil, J., 2024, Modeling Forest Snow Using Relative Canopy Structure Metrics, Water, 16, 1398, https://doi.org/10.3390/w16101398

• Thompson, L. C., Moeser, D,  2024, The Effects of Wildfire on Snow Water Resources Under Multiple Climate Conditions. CART. Retrieved from https://www.fws.gov/project/effects-wildfire-snow-water-resources-under-multiple-climate-conditions

• Mankin, K., Rumsey, C.,... Moeser, D.,...Lamber, P., 2022, Upper Rio Grande Basin Water-Resource Status and Trends: Focus Area Study Review and Synthesis., Transcations of the ASABE, https://doi.org/10.13031/ja.14964

• Broxton, P., Moeser, D.,Harpold, A., 2021, Accounting for Fine-Scale Forest Structure is Necessary to Model Snowpack Mass and Energy Budgets in Montane Forests., Water Resources Research, https://doi.org/10.1029/2021WR029716

•Moeser, D., Chavarria, S., Wootten, A., 2021, Streamflow Response to a Changing Climate in the Upper Rio Grande Basin; United States Geological Survey Scientific Investigations Report 2021–5138, 41 p., https://doi.org/10.3133/sir20215138 / interactive website: https://webapps.usgs.gov/urgb-prms/

•Moeser, D., Broxton, P., Harpold, A., 2020; Estimating the effects of forest structure changes from wildfire on snow water resources under varying meteorological conditions., Water Resources Research, https://doi.org/10.1029/2020WR027071

•Moeser, D., Douglas-Mankin, K., 2020; Simulating Hydrologic Effects of Wildfire on a Small Sub-alpine Soutwestern U.S. Watershed., Transcations of the ASABE, 64(1): 130-150, https://doi.org/10.13031/trans.13938

•Helbig, N., Moeser, D., Teich, M., Vincent, L, Lejeune, Y., Sicart, J.E., Monnet, J.M., 2020; Snow Processes in Mountain Forests: Interception Modeling for Coarse-scale applications, Hydrology and Earth Systems Science,https://doi.org/10.5194/hess-2019-348

•Sexstone, G.A., Penn, C.A., Liston, G.E., Gleason, K.E., Moeser, D., and Clow, D.W., 2020, Spatial variability in seasonal snowpack trends across the Rio Grande headwaters (1984-2017), Journal of Hydrometeorology, p. 1-56, https://doi.org/10.1175/JHM-D-20-0077.1.

•Mazzotti, G., Essery, R., Moeser, D., Jonas, T., 2020; Resolving small-scale forest snow patterns with an energy balance snow model and a 1-layer canopy; Water Resources Research, doi: https://doi.org/10.1029/2019WR026129

•Chavarria, S.B., Moeser, D.., and Douglas-Mankin, K.R., 2020; Application of the Precipitation-Runoff Modeling System (PRMS) to Simulate Near-Native Streamflow in the Upper Rio Grande Basin: U.S. Geological Survey Scientific Investigations Report 2020–5026, 348 p. https://doi.org/10.3133/sir20205026

•Douglas-Mankin, K. and Moeser, D., Calibration of PRMS to Simulate Pre- and Post-Fire Hydrologic Response in the Upper Rio Hondo Basin, New Mexico, 2019; United States Geological Survey Scientific Investigations Report, doi: https://doi.org/10.3133/sir20195022 (link)

•Moeser, D., G. Mazzotti, N. Helbig, T. Jonas; Representing spatial variability of forest snow: Implementation of a new interception model, 2016; Water Resources Research, doi: 10.1002/2015WR017961 (link)

•Moeser, D., M. Stähli, T. Jonas; Improved snow interception modeling using novel canopy parameters from airborne LID AR data, 2015; Water Resources Research, doi: 10.1002/2014WR016724 (link)

•Moeser, D., F. Morsdorf, T. Jonas; Novel forest structure metrics from airborne LiDAR data for improved snow interception estimation, 2015; Agriculture and Forest Meteorology, doi: 10.1016/j.agrformet.2015.04.013 (link)

•Moeser, D., J. Roubinek, P. Schleppi, F. Morsdorf, T. Jonas; Canopy closure, LAI and radiation transfer from airborne LiDAR synthetic images; 2014; Agricultural and Forest Meteorology, doi: 10.1016/j.agrformet.2014.06.008 (link)

Data and Code Releases

• Moeser, D., Sexstone, G., 2026, Model and Lidar derived Snow and Canopy information at the HUC-12 scale for SouthWestern Colorado, USA: U.S. Geological Survey data release, https://doi.org/10.5066/P18XAJPR. In Review.

•Barnhart, T.B., Drukker, O.A., Putman, A.L., Heldmyer, A.J., Hammond, J.C., Moeser, D., Rey, D.M., and Sexstone, G.A., 2025, Simulated Snowpack and Meteorological Variables for the Upper Colorado River Basin and Vicinity Using CONUS404 Historical and Future Mid-Century Meteorology: U.S. Geological Survey data release, https://doi.org/10.5066/P148RWR7

• Moeser, D., Kurzweil, J., and Sexstone, G., Burke, K., Roussel, S., 2025, Snow Measurements in Specific Canopy Structure and Aspect Regimes for the 2025 Water Year, North of Coal Creek, San Juan Mountains, Colorado, USA: U.S. Geological Survey data release, https://doi.org/10.5066/P18XAJPR

• Moeser, D., Galanter, A., Lim, C., Mack, T., 2025, Groundwater-level data in a subwatershed of the Los Planes Watershed, Baja California Sur, Mexico, May 2022 – May 2024: U.S. Geological Survey data release, https://doi.org/10.5281/zenodo.13891150

• Moeser, D., Kurzweil, J., McDermott, W., Lampard, T., 2024, Snow Measurements in Specific Canopy Structure Regimes for the April 9, 2024, North of Coal Creek, San Juan Mountains, Colorado, USA: U.S. Geological Survey data release, https://doi.org/10.5066/P1EAGT6Yœ

• Sexstone, G., Moeser, D., 2024, SnowModel Simulations for the 2022-2023 Water Years, near Coal Creek, San Juan Mountains, Colorado, USA: U.S. Geological Survey data release, https://doi.org/10.5066/P13OM8Y3

• Moeser, D., Kurzweil, J., and Sexstone, G.A., 2023, Snow Measurements in Specific Canopy Structure Regimes for the 2022-2023 Water Years, North of Coal Creek, San Juan Mountains, Colorado, USA: U.S. Geological Survey data release, https://doi.org/10.5066/P9E943GE

• Moeser, D., and Sexstone, G.A., 2023, High Resolution Canopy Structure and Density Metrics for Southwest Colorado Derived from 2019 Aerial Lidar: U.S. Geological Survey data release, https://doi.org/10.5066/P9ESQIAV

•Chavarria, S.B., Moeser, D., Ball, G.P., and Shephard, Z.M., 2020, Hydrologic simulations using projected climate data as input to the Precipitation-Runoff Modeling System (PRMS) in the Upper Rio Grande Basin (ver. 2.0, September 2021): U.S. Geological Survey, https://doi.org/10.5066/P9ML93QB

•Chavarria, S.B., Moeser, D. and Shephard, Z.M., 2020, Input and Output Data for the Application of the Precipitation-Runoff Modeling System (PRMS) to Simulate Near-Native Streamflow in the Upper Rio Grande Basin: U.S. Geological Survey data release, https://doi.org/10.5066/P9YOPYW7

•Moeser, D., 2020, Lidar2CanopyMetrics [package of scripts to calculated canopy structure and density from aerial lidar data], https://doi.org/10.5281/zenodo.4088667

• Moeser, D., Shephard, Z., 2019, Data Release: The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions: U.S. Geological Survey, https://doi.org/10.5066/P9BBCSVN.

•Moeser, D., Douglas-Mankin, K., Mitchell, A.C., Chavarria, S.B., 2018; PRMS simulations for the Rio Hondo Basin, New Mexico; United States Geological Survey data release, doi: https://doi.org/10.5066/F7KD1X7Q

•U.S. Army Corps of Engineers – Forest Snow Web Interface (2025)

•South Central Climate Adaptation Science Center – 'Estimating The Future Effects of Forest Disturbance on Snow Water Resources in a Changing Environment' Part Two (2024)

•South Central Climate Adaptation Science Center – 'Estimating The Future Effects of Forest Disturbance on Snow Water Resources in a Changing Environment' Part One (2021)

•South Central Climate Adaptation Science Center – 'Developing and Analyzing Response of Landscape-level Hydrology and Streamflow to Climate Projections in the Upper Rio Grande Basin (2019)

South Central Climate Adaptation Science Center – 'The Effects of Wildfire on Snow Water Resources Under Multiple Climate Conditions' (2017)

•Swiss National Science Foundation – ‘Snow Distribution Dynamics under Forest Canopy’ (2012) (link)

•Agriculture Research Service – ‘Recommended Procedure for Assessing Soil Disturbances in Vegetation Management Projects within Sensitive Areas of the Lake Tahoe Basin’ (2008)

•Other substantial Funders: U.S. Army Corps of Engineers, Bureau of Land Management, Global Water Partnership, Interanl U.S. Geological Survey

•Norman, L., Cassassuce, F., Mack, T., Petrakis, R., Anides-Morales , A., Sorenson, J., Evans, D., Garcia, M., Dominguez, A., Moeser, D., Galanter, A., Lim, C., McDowell, J., White, E., Gomis, F., Capturing Cyclonic Rainfall to Enhance Basin Aquifer Storage: Natural Infrastructure in Dryland Streams of Baja California Sur, 122nd Annual Meeting of the GSA Cordilleran Section, Loreto, Baja California Sur, Mexico, April 2026.

•Moeser, D.,Moeser, D., Sexstone, G., Kurzweil, J., Development of a New Model Platform to Represent Forest Snow Interactions Using Relative Canopy Structure Metrics, International Union of Geodesy and Geophysics and International Association of Hydrological Sciences, Roorkee, India, October 2025. *Cancellation week prior due to government shutdown*.

•Roussel, S., Galanter, A., Moeser, D., Mack, T., ‘Groundwater Response to Natural Infrastructure in Dryland Streams, National Conference on Ecosystem Restoration, Albuquerque, NM, April 2024

•Moeser, D., Broxton, P., Harpold, A.; ‘The Effects of Wildfire on Snow Water Resources Under Multiple Canopy Structures and Meteorological Conditions,’ American Geophysical Union meeting, San Francisco, California, December 2019

•Sexstone, G., Penn, C., Liston, G., Gleason, K., Moeser, D., Clow, D.; ‘Fine-Scale Spatial Variability in Seasonal Snowpack Trends,’ American Geophysical Union meeting, San Francisco, California, December 2019

• Moeser, D. , Broxton, P., Harpold, A.; ‘The Effects of Wildfire on Snow Water Resources Under Multiple Canopy Structures and Meteorological Conditions,’ International Union of Geodesy and Geophysics, Montreal, Canada, July 2019

•Helbig, N., D. Moeser, M. Teich; ‘Spatially-Averaged Sky View Factors for Snow Interception over Forest Canopy,’ European Geophysical Union, Vienna, Austria, April 2018

•Moeser, D., K. Douglas - Mankin; ‘Hydrologic Impacts of Wildfire on a Small Sub-alpine Southwestern U.S. Watershed: A Simplified Modeling Approach,’ American Geophysical Union, New Orleans, Louisiana, December 2017

•Sexstone, G., C. Penn, D. Clow,D. Moeser, G. Liston; ‘Changes in the Relation Between Snow Station Observations and Basin Scale Snow Water Equivalence,’ American Geophysical Union, New Orleans, Louisiana, December 2017

•Moeser, D., M. Stähli; ‘Forest Canopy Controls on Snow Hydrology,’ Western Snow Conference, Boise, Idaho, March 2017

•Moeser, D.; ‘Forest snow hydrology,’ Department colloquium series, Department of Earth and Environmental Science, New Mexico Tech, Socorro, New Mexico, January 2017

•Moeser, D.; ‘The influence of forest canopy structure on snow hydrology: Novel modeling and visualization approaches,’ Department colloquium series, Department of Earth and Planetary Sciences, University of New Mexico, Albuquerque, New Mexico, December 2016

•Moeser, D., M. Stähli; ‘The influence of canopy structure on snow,’ poster presentation, American Geophysical Union meeting, San Francisco, California, December 2016

•Moeser, D., M. Stähli, T. Jonas; ‘Snow interception modeling,’ oral presentation, The International Union of Geodesy and Geophysics, Prague, Czech Republic, June 2015

•Moeser, D., F. Morsdorf, T. Jonas; ‘Improving snow interception modeling using LiDAR data,’ poster presentation, American Geophysical Union meeting, San Francisco, CA, December 2014

•Moeser, D., J. Roubinek, F. Morsdorf, T. Jonas; ‘Snow distribution dynamics under forest canopy,’ poster presentation, American Geophysical Union meeting, San Francisco, CA, December 2013

•Moeser, D., T. Jonas, F. Morsdorf; ‘Linking snow accumulation patterns in forests with LiDAR derived canopy structure data,’ oral presentation, Davos Atmosphere and Cryosphere Assembly – The International Union of Geodesy and Geophysics, Davos, Switzerland, July 2013

•Jonas, T., D. Moeser, F. Morsdorf; ‘Linking forest snow distribution measurements with canopy structure data,’ Presented by Dr. Tobias Jonas at the American Geophysical Union meeting, San Francisco, California, December 2012

•Jonas, T., D. Moeser, J. Magnusson, M. Bavay; ‘Validation of multiple approaches for modeling SWE Distribution and subsequent snowmelt in a small alpine watershed,’ Presented by Dr. Tobias Jonas at the International Union of Geodesy and Geophysics, Melbourne, Australia, July 2011

•Moeser, D., M. Walker, C. Skalka, J. Frolik; ‘A distributed wireless sensor network for quantifying spatial trends of snow depth and snow water equivalent,’ Presented by Dr. Mark Walker at the 79th Annual Western Snow Conference, Stateline, NV, April 2011

•Moeser, D., M. Walker, C. Skalka, J. Frolik; ‘Development, analysis & sse of a distributed wireless sensor network for quantifying spatial trends of snow,’ Presented by Dr. Mark Walker at the Nevada Water Resources Association, Annual conference Reno, NV, February 2011

•Moeser, D., Skalka, C., M. Walker, J. Frolik; ‘Snowcloud: development of a distributed in situ instrument for snowpack monitoring,’ Poster presentation, American Geophysical Union meeting, San Francisco, California, December 2009

•MMoeser, D., Forest-Snow Interaction Web-platform, Upper Rio Grande Water Operations Model Technical Team, April 2025.

•Sexstone, G., Hammond, J., Barnhart, T., Putman, A., Rey, D., Heldmyer, A., Moeser, D., Optimizing ground measurement site placement using airborne measurements, Bureau of Reclamation Snow Water Forecasting Forum, November 2024.

•Nichols, J., MMoeser, D., Linhof, B., Morrison, D., Improving Headwater Stream Resiliency to Climate Chagne in the Rio Grande Watershed, South Central Climate Adaptation Science Center , November 2024.

•Sexstone, G., Hammond, J., Barnhart, T., Putman, A., Rey, D., Heldmyer, A., Moeser, D., Snow Hydrology Research to Improve Water Budget Modeling Across Snow Dominated Regions, U.S. Geological Survey Modeling Community of Practice speaker series, November 2024.

•Matherne, A., Ritchie, A., Moeser, D., Galanter, A., Seelig, W., Teeple, A., Villa, J., Sanchez, R., Rodriguez, L., Data Scouring to Support the Transboundary Aquifer Assessment Program, U.S. Geological Survey, Water Mission Area, Earth System Processes Division, Project Lead Meeting, Remote, May 2023.

•Galanter, A., Ritchie, A.,Moeser, D.,Seelig, W., Teeple, A., Villa, J., Sanchez, R., Rodriguez, L., Data Scouring to Support The Transboundary Aquifer Assessment Program, Transboundary Aquifer Assessment Program Meeting, Tucson AZ, June, 2023

•Moeser, D., Upper Rio Grande Basin Response to Potential Changes in Climate to 2100, 2023 Annual Meeting of the Engineer Advisers to the Rio Grande Compact Commission, March 2023

•Moeser, D., Chavarria, S., Streamflow Response to Potential Changes in the Upper Rio Grande Basin, Middle Rio Grande Endangered Species Collaborative Program, December 2022

• Moeser, D., Chavarria, S., Snow and Watershed Modeling in Forested Environments, United States Forest Severe Forest Science Laboratory Collaborative, November 2022

•Moeser, D., Chavarria, S., Sexstone, G., Wootten, A., Broxton, P., Harpold, A., Can’t See the Forest For and The Trees: High Resolution and Large-scale Canopy Characterization from Aerial Lidar, USGS Geospatial Group webinar, September 2022

•Sexstone, G., Fulton, J., McDermott, W.,…..Moeser, D., From Stations to Satellites: Next Generation USGS Snow Hydrology Monitoring Activities to Improve Water Availability Assessments in the Upper Colorado River Basin, Rocky Mountain Region Science Exchange Workshop, April 2022

•Moeser, D., Chavarria, S., Sexstone, G., Wootten, A., Broxton, P., Harpold, A., A changing Rio Grande Watershed: Two Modelling Perspectives, Southern Planes Climate Science Webinar, April 2022

•Moeser, D., Chavarria, S., Recently Completed Snow and Watershed Modeling Projects in the Upper Rio Grande Basin, 2022 Annual Meeting of the Engineer Advisers to the Rio Grande Compact Commission, March 2022

•Moeser, D., Chavarria, S., Recently Completed Snow and Watershed Modeling Projects, Oregon Water Science Center Seminar Series, February 2022

•Moeser, D., The Effects of Canopy Structure Changes on Snow Water Resources, USGS Fire Water Working Group, June 2021

•Moeser, D., The Effects of Canopy Structure Changes on Snow Water Resources Bureau of Reclamation Colloquium series, May 2021

•Moeser, D., The Effects of Wildfire on Snow Water Under Multiple Canopy Structure and Meteorological Conditions, New Mexico Forest and Watershed Health Coordinating Group, January 2021

•Moeser, D., Canopy disturbance and Snow Water Resources in the Upper Rio Grande Basin, 2-3-2 Collaborative, October 2020

•Moeser, D., The Effects of Canopy Structure Changes on Snow Water Resources, Rocky Mountain Region Science Exchange Conference, September 2020

•Moeser, D., Surface Water Modeling: The Effects of Landscape Changes in the Rio Grande Watershed, USGS Office of International Programs collaborative with the NM WSC, June 2018

•Moeser, D.; ‘Snow Hydrology Research in The New Mexico Water Science Center,’ New Mexico Bureau of Geology and Mineral Resources, New Mexico Tech, Socorro, New Mexico, June 2017

•Moeser, D.; ‘Forest snow hydrology,’ Department colloquium series, Department of Earth and Environmental Science, New Mexico Tech, Socorro, New Mexico, January 2017

•Moeser, D.,‘The influence of forest canopy structure on snow hydrology: Novel modeling and visualization approaches,’ Department colloquium series, Department of Earth and Planetary Sciences, University of New Mexico, Albuquerque, New Mexico, December 2016

•Moeser, D.,M. Stähli; ‘The influence of canopy structure on snow,’ poster presentation, American Geophysical Union meeting, San Francisco, California, December 2016

•Moeser, D.; ‘The influence of forest canopy structure on snow hydrology’ Department colloquium series, USGS New Mexico Water Science Center, Colloquium series, Albuquerque, New Mexico, October 2016

•Forest-Snow Web interface coming mid-year 2026.

Interactive platform where an end-user can look at the effects of existing forest canopy and scenarios of canopy changes on snow water resreouces for varying hydrologic and meteorologic conditions for ~ 170 HUC-12 sub-watersheds of the San Juan Mountains of Southwest Colorado.

•Watersheds of the Rio Grande Basin: Climate Based Streamflow Projections and Dynamic Hydrographs to 2100 (link)

•U.S. Fish and Wildlife Service Conservation and Adaption Resources Tool Box: Effects of Wildfire Snow on Water Resources Under Multiple Climate Conditions (link)

•U.S. Fish and Wildlife Service Conservation and Adaption Resources Tool Box: Effects of Wildfire on Snow Water Resources Handout (link)

•Long Format Interview: Climate and Snowpack, New Mexico Water Data Stories' (2021) (link)

•AP Report found in a variety of U.S. newspapers including the Albuquerque journal, US News, Durango Herald, Colorado Politic, San Francisco Chronicle among others: Drastic Changes forescast for Rio Grande (link)

•Source New Mexico interview for report found a variety of online platforms: Watching the Oxbow Dry (link)

•Source New Mexico interview for report found a variety of online platforms: A River Wounded: Crisis on the Rio Grande (link)

•South Central Climate Adaptation Science Center Webinar: A changing Rio Grande Watershed: Two modeling perspectives (link)

•U.S. Geological Survey geopsatial group webinar: webinar Can’t See the Forest For and The Trees: High Resolution and Large-scale Canopy Characterization from Aerial Lidar, (link)