Help
RSS
API
Feed
Maltego
Contact
Domain > www.davidmoeser.com
×
More information on this domain is in
AlienVault OTX
Is this malicious?
Yes
No
DNS Resolutions
Date
IP Address
2020-12-02
160.153.44.193
(
ClassC
)
2026-02-27
107.180.115.161
(
ClassC
)
Port 80
HTTP/1.1 200 OKDate: Fri, 27 Feb 2026 11:50:11 GMTServer: ApacheUpgrade: h2,h2cConnection: UpgradeLast-Modified: Thu, 03 Oct 2024 19:43:04 GMTETag: 1a006f0-102e4-62397c35cb00aAccept-Ranges: bytesContent-Length: 66276Vary: Accept-EncodingContent-Type: text/html !DOCTYPE html> html classno-js langen> head> !--- Basic Page Needs --> meta charsetutf-8> title>C. David Moeser, PhD - Hydrologist/title> meta namepersonal website content> meta namemoeser content> !-- Mobile Specific Metas --> meta nameviewport contentwidthdevice-width, initial-scale1, maximum-scale1> !-- CSS --> link relstylesheet hrefcss/default.css> link relstylesheet hrefcss/layout.css> link relstylesheet hrefcss/media-queries.css> link relstylesheet hrefcss/magnific-popup.css> !-- Script --> script srcjs/modernizr.js>/script> !-- Favicons --> link relshortcut icon hreffavicon.png > /head> body> !-- Start of StatCounter Code for Dreamweaver --> script typetext/javascript> var sc_project7308544; var sc_invisible1; var sc_security410ad643; /script> script typetext/javascript srchttp://www.statcounter.com/counter/counter.js>/script> noscript>div classstatcounter>a titledrupal statistics module hrefhttp://statcounter.com/drupal/ target_blank>img classstatcounter srchttp://c.statcounter.com/7308544/0/410ad643/1/ altdrupal statistics module>/a>/div>/noscript> !-- End of StatCounter Code for Dreamweaver --> !-- Header --> header idhome> nav idnav-wrap> a classmobile-btn href#nav-wrap titleShow navigation> Show navigation/a> a classmobile-btn href# titleHide navigation>Hide navigation/a> ul idnav classnav> li classcurrent>a classsmoothscroll href#home>Home/ a>/li> li>a classsmoothscroll href#about>About/a>/li> li>a classsmoothscroll href#resume>Resume/a>/li> li>a classsmoothscroll href#portfolio>Works/a>/li> li>a classsmoothscroll href#testimonials>Water Facts/a >/li> li>a classsmoothscroll href#contact>Contact/a>/li> /ul> !-- end #nav --> /nav> !-- end #nav-wrap --> div classrow banner> div classbanner-text> h1 classresponsive-headline>C. David Moeser/h1> h3>span>Im a New Mexico based hydrologist, environmental scientist and data analyst, specializing in snow and watershed modeling. /span> hr /> ul classsocial> li>a hrefhttps://www.facebook.com/cdmoeser>i classfa fa-facebook>/i>/a>/li> li>a hrefhttps://www.linkedin.com/in/david-moeser-4a91246/>i classfa fa-linkedin>/i>/a>/li> li>a hrefskype:cdmoeser?userinfo>i classfa fa-skype>/i>/a>/li> /ul> /div> /div> p classscrolldown> a classsmoothscroll href#about>i classicon-down-circle>/i>/a> /p> /header> !-- Header End --> !-- About Section --> section idabout> div classrow> div classthree columns> img classprofile-pic srcimages/profilepic.jpg alt /> /div> div classnine columns main-col> h2>About Me/h2> p>I am a hydrologist for the USGS – New Mexico Water Science Center and in charge of all technical watershed-modeling activities. I have developed data processing and analysis techniques and serve as the centers technical authority on all waterhsed modeling and snow hydrology activities. I am currently developing and implementing novel characterizations of forest canopy as well as snow modeling tools in order to quantify the effects of canopy disturbance on snow water resources. /p> div classrow> div classcolumns contact-details> h2>Contact Details/h2> p classaddress> span>C. David Moeser/span>br> span>314 14th st NW/span>br> span>Albuquerque, NM 87104 USA/span>br> span>+1 (77five) 3five7- 66six8/span>br> span>cdmoeser(at)yahoo(dot)com/span>/p> /div> div classcolumns download> p> a href../cv/cv_moeser.pdf classbutton>i classfa fa-download>/i>Download Resume/a> /p> /div> /div> !-- end row --> /div> !-- end .main-col --> /div> /section> !-- About Section End--> !-- Resume Section --> section idresume> !-- Education ----------------------------------------------- --> div classrow education> div classthree columns header-col> h1>span>Education/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> h3>Swiss Federal Institute of Technology, Zürich a hrefhttps://en.wikipedia.org/wiki/ETH_Zurich> (ETH) /a>/h3> p classinfo>PhD span>•/span>em>December 2015/em>/p> p classinfo>em>Surface Water Hydrology/em>span>•/span>Department of span>Environmental Systems Science/span>/p> p> Dissertation: The Influence of Forest Canopy Structure on Snow Hydrology. Download a href../downloads/final_dissertation_moeser_2016.pdf> here /a> /p> Funding: Successful Swiss National Science Foundation Grant Proposal. Download a href../downloads/proposal_snsf.pdf> here /a> p> /p> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>University of Nevada, Reno/h3> p classinfo>M.S.span>•/span>em>December 2010/em>/p> p classinfo>em>Surface Water Hydrology/em>span>•/span>Department of span>Hydrologic Sciences/span>/p>p>Thesis: Development, Analysis and Use of a Distributed Wireless Sensor Network for Quantifying Spatial Trends of Snow Depth and Snow Water Equivalence. Download a href../downloads/thesis_final_moeser.pdf> here /a>/p> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>Fort Lewis College/h3> p classinfo>B.S.span>•/span>em>December 2004/em>/p> p classinfo>em>Environmental Geology / Chemistry minor/em>span>•/span>Department of span>Geosciences/span>/p>p>Thesis: Discriminating Pre- and Post- Mining Effects on The Middle Fork of Mineral Creek, Silverton, CO, Using Tree Core Analysis/p>p>Awarded outstanding senior in the earth sciences (Eugene M. Shoemaker Award)/p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Education --> !-- Work ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Work/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> h3>United States Geological Survey/h3> p classinfo>New Mexico Water Science Centerem classdate>/em>/p> p classinfo>Hydrologist span>•/span> em classdate>July 2016 - Present/em>/p> li>Serve as the centers technical authority on all surface water modeling and snow hydrology activities, both, in the office and the field. /li> li>Act as a regional technical advisor to external land managers with stakes in water resources and planning./li> li>Charged with all technical watershed-modeling activities. /li> li>Develop novel data processing and analysis techniques. /li> li>Currently developing and implementing novel characterizations of forests and modeling tools to quantify the effects of forest disturbance and changing climate on water resources. /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>WSL Institute for Snow and Avalanche Research SLF /h3> p classinfo>Davos, Switzerlandem classdate>/em>/p> p classinfo>Snow Hydrologist / PhD Candidate span>•/span> em classdate>February 2012 - February 2016/em>/p> li> Snow model and analysis tool development/li> li> Aerial and terrestrial LiDAR (light detection and ranging) data gathering, and manipulation /li> li> Snow survey campaign supervision (total: 12 employees)/li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>World Business Council For Sustainable Development/h3> p classinfo>Geneva, Switzerland em classdate>/em>/p> p classinfo>Contract Hydrologist span>•/span> em classdate>September 2011 - February 2012/em>/p> li> Water and energy use linkage analyses between food, feed, and fiber management scenarios/li> li> Knowledge exchange coordination between UN organizations, research institutes, and businesses for water related projects/li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>WSL Institute for Snow and Avalanche Research SLF /h3> p classinfo>Davos, Switzerlandem classdate>/em>/p> p classinfo>Snow Hydrology Internspan>•/span> em classdate>January 2011 - July 2011/em>/p> li> Snow survey campaign leader within a high alpine basin in avalanche terrain/li> li> Snow melt modeling implementation and analysis/li> li> Geographic data parsing and analysis /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>University of Nevada, Reno /h3> p classinfo>Research Assistantspan>•/span> em classdate>September 2008 - December 2010/em>/p> li> Wireless snow depth sensing equipment and affiliated meteorological station deployment, maintenance, and analysis/li>li> Statistical and geo-statistical modeling of snow /li> li> Stilling well and V-notch weir installation in an urban watershed/li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>Bureau of Land Management/ U.S. Forest Service /h3> p classinfo>Public Lands Center - em classdate>/em>Durango, Colorado/p> p classinfo>Hydrologic Technicianspan>•/span> em classdate>2005 - 2007/em>/p> li> Surface and groundwater water quantity and quality monitoring in springs and streams within Colorado, Utah, and New Mexico/li> li> Groundwater monitoring well and piezometer installation /li> li> Forest stream remediation and characterization /li> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Education --> !-- Teaching ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Teaching/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> h3>Swiss Federal Institute of Technology (ETH)/h3> p classinfo>Zürich, Switzerlandem classdate>/em>/p> p classinfo>(2013 - 2014) Department of Environment Systems Scienceem classdate>/em>/p> p classinfo>Environmental Measurement Laboratory (701) /p> li> Course and laboratory structure development for a 6-hour lecture module designed to integrate matlab programing with remotely sensed data /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>University of Nevada, Reno /h3> p classinfo>(2008 - 2010) Department of Natural Resources and Environmental Scienceem classdate>/em>/p> p classinfo>Principles of Ecohydrology (295) /p> p classinfo>Ecohydrology Field Camp (400)/p> li> New course material and method development /li> li> Field and laboratory lecturing and supervision /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>University of Nevada, Reno Cooperative Extension /h3> p classinfo>(2009 - 2010) Discover your Future/p> li> Basic hydrologic field methods and applications: activity leader and guest lecturer for high school students /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>Fort Lewis College /h3> p classinfo>(2023) Collaborative Environmental Research/p> li> Field measurement techniques for snow /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Work --> !-- Published Work ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Published Papers/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span> strong>Moeser, D, /strong>Sexstone, G., Kurzweil, J., 2024, Modeling Forest Snow Using Relative Canopy Structure Metrics, Water, 16, 1398, https://doi.org/10.3390/w16101398/p> p>span classinfo>span>•/span>/span> Mankin, K., Rumsey, C.,... strong>Moeser, D/strong>.,...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/p> p>span classinfo>span>•/span>/span> Broxton, P., strong>Moeser, D/strong>.,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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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: a hrefhttps://webapps.usgs.gov/urgb-prms/>https://webapps.usgs.gov/urgb-prms//a>/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>, 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>, 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 /p> p>span classinfo>span>•/span>/span>Helbig, N., strong>Moeser, D./strong>, 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 /p> p>span classinfo>span>•/span>/span>Sexstone, G.A., Penn, C.A., Liston, G.E., Gleason, K.E., strong> Moeser, D.,/strong> 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./p> p>span classinfo>span>•/span>/span>Mazzotti, G., Essery, R., strong>Moeser, D./strong>, 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 /p> p>span classinfo>span>•/span>/span>Chavarria, S.B., strong>Moeser, D./strong>., 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/p> p>span classinfo>span>•/span>/span>Douglas-Mankin, K. and strong>Moeser, D./strong>, 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 a hrefhttps://pubs.er.usgs.gov/publication/sir20195022> (link) /a> /p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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 a href../downloads/moeser2016wrr.pdf> (link) /a>/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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 a href../downloads/moeser2015wrr.pdf> (link) /a>/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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.2015.04.013a href../downloads/moeser_2015a_afm.pdf> (link) /a>/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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 a href../downloads/moeser_2014a_afm.pdf> (link) /a>/p> h3>Data and Code Releases/h3> p>span classinfo>span>•/span>/span> strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span> Sexstone, G., strong>Moeser, D.,/strong> 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/P13OM8Y3p> p>span classinfo>span>•/span>/span> strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span> strong>Moeser, D./strong>, 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/p> p>span classinfo>span>•/span>/span>Chavarria, S.B., strong>Moeser, D.,/strong> 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 /p> p>span classinfo>span>•/span>/span>Chavarria, S.B., strong>Moeser, D./strong> 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 /p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 2020, Lidar2CanopyMetrics package of scripts to calculated canopy structure and density from aerial lidar data, https://doi.org/10.5281/zenodo.4088667 /p> p>span classinfo>span>•/span>/span> strong>Moeser, D./strong>, 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./p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>, 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 /p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Published Work --> !-- external reports and grants ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Significant and Successful Competetive Grant Proposals /span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span>South Central Climate Adaptation Science Center – Estimating The Future Effects of Forest Disturbance on Snow Water Resources in a Changing Environment Part Two (2024)/p> p>•South Central Climate Adaptation Science Center – Estimating The Future Effects of Forest Disturbance on Snow Water Resources in a Changing Environment Part One (2021)/p> p>•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)/p> p>South Central Climate Adaptation Science Center – The Effects of Wildfire on Snow Water Resources Under Multiple Climate Conditions (2017)/p> p>span classinfo>span>•/span>/span>Swiss National Science Foundation – ‘Snow Distribution Dynamics under Forest Canopy’ (2012) a href../downloads/proposal_snsf.pdf> (link) /a> /p> p>span classinfo>span>•/span>/span>Agriculture Research Service – ‘Recommended Procedure for Assessing Soil Disturbances in Vegetation Management Projects within Sensitive Areas of the Lake Tahoe Basin’ (2008)/p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End xternal reports and grants --> !-- Conference Papers and Presentations ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1> /h1> h1>span>Conference Papers and Presentations/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span>Roussel, S., Galanter, A., strong>Moeser, D.,/strong> Mack, T., ‘Groundwater Response to Natural Infrastructure in Dryland Streams, National Conference on Ecosystem Restoration, Albuquerque, NM, April 2024/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>, 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/p> p>span classinfo>span>•/span>/span>Sexstone, G., Penn, C., Liston, G., Gleason, K., strong>Moeser, D./strong>, Clow, D.; ‘Fine-Scale Spatial Variability in Seasonal Snowpack Trends,’ American Geophysical Union meeting, San Francisco, California, December 2019/p> p>span classinfo>span>•/span>/span> strong>Moeser, D. /strong>, 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/p> p>span classinfo>span>•/span>/span>Helbig, N., strong>D. Moeser/strong>, M. Teich; ‘Spatially-Averaged Sky View Factors for Snow Interception over Forest Canopy,’ European Geophysical Union, Vienna, Austria, April 2018/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> p>span classinfo>span>•/span>/span>Sexstone, G., C. Penn, D. Clow,strong>D. Moeser/strong>, G. Liston; ‘Changes in the Relation Between Snow Station Observations and Basin Scale Snow Water Equivalence,’ American Geophysical Union, New Orleans, Louisiana, December 2017/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., M. Stähli; ‘Forest Canopy Controls on Snow Hydrology,’ Western Snow Conference, Boise, Idaho, March 2017/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>.; ‘Forest snow hydrology,’ Department colloquium series, Department of Earth and Environmental Science, New Mexico Tech, Socorro, New Mexico, January 2017/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>.; ‘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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., M. Stähli; ‘The influence of canopy structure on snow,’ poster presentation, American Geophysical Union meeting, San Francisco, California, December 2016/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., M. Stähli, T. Jonas; ‘Snow interception modeling,’ oral presentation, The International Union of Geodesy and Geophysics, Prague, Czech Republic, June 2015/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., F. Morsdorf, T. Jonas; ‘Improving snow interception modeling using LiDAR data,’ poster presentation, American Geophysical Union meeting, San Francisco, CA, December 2014/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., J. Roubinek, F. Morsdorf, T. Jonas; ‘Snow distribution dynamics under forest canopy,’ poster presentation, American Geophysical Union meeting, San Francisco, CA, December 2013/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> p>span classinfo>span>•/span>/span>Jonas, T., strong>D. Moeser/strong>, 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/p> p>span classinfo>span>•/span>/span>Jonas, T., strong>D. Moeser/strong>, 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Conference Papers and Presentations --> !-- Stakeholder Presentations and Colloquiums ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Stakeholder Presentations and Colloquiums/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span>Galanter, A., Ritchie, A.,strong>Moeser, D.,/strong>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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> Chavarria, S., Streamflow Response to Potential Changes in the Upper Rio Grande Basin, Middle Rio Grande Endangered Species Collaborative Program, December 2022/p> p>span classinfo>span>•/span>/span>strong> Moeser, D.,/strong> Chavarria, S., Snow and Watershed Modeling in Forested Environments, United States Forest Severe Forest Science Laboratory Collaborative, November 2022/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> Chavarria, S., Sexstone, G., Wootten, A., Broxton, P., Harpold, A., strike>Can’t/strike> See the Forest strike>For/strike> and The Trees: High Resolution and Large-scale Canopy Characterization from Aerial Lidar, USGS Geospatial Group webinar, September 2022/p> p>span classinfo>span>•/span>/span>Sexstone, G., Fulton, J., McDermott, W.,…..strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> Chavarria, S., Recently Completed Snow and Watershed Modeling Projects, Oregon Water Science Center Seminar Series, February 2022/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> The Effects of Canopy Structure Changes on Snow Water Resources, USGS Fire Water Working Group, June 2021 /p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> The Effects of Canopy Structure Changes on Snow Water Resources Bureau of Reclamation Colloquium series, May 2021/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> The Effects of Wildfire on Snow Water Under Multiple Canopy Structure and Meteorological Conditions, New Mexico Forest and Watershed Health Coordinating Group, January 2021/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> Canopy disturbance and Snow Water Resources in the Upper Rio Grande Basin, 2-3-2 Collaborative, October 2020/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> The Effects of Canopy Structure Changes on Snow Water Resources, Rocky Mountain Region Science Exchange Conference, September 2020/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>; ‘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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>; ‘Forest snow hydrology,’ Department colloquium series, Department of Earth and Environmental Science, New Mexico Tech, Socorro, New Mexico, January 2017/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong>‘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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong>M. Stähli; ‘The influence of canopy structure on snow,’ poster presentation, American Geophysical Union meeting, San Francisco, California, December 2016/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>; ‘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/p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- Stakeholder Presentations and Colloquiums--> !-- Websites, Videos, and Press ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Websites, Videos, and Press/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span>USGS Upper Rio Grande Basin Climate Projections and dynamic hydrographsa hrefhttps://webapps.usgs.gov/urgb-prms/> (link) /a> /p> p>span classinfo>span>•/span>/span>Long Format Interview: Climate and Snowpack, New Mexico Water Data Stories (2021)a hrefhttps://www.youtube.com/watch?vnFRsca4mFm8> (link) /a>/p> p>span classinfo>span>•/span>/span>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 Grandea hrefhttps://www.usnews.com/news/best-states/new-mexico/articles/2022-02-20/experts-drastic-changes-forecast-for-rio-grande> (link) /a> /p> p>span classinfo>span>•/span>/span>Source New Mexico interview for report found a variety of online platforms: Watching the Oxbow Dry a hrefhttps://sourcenm.com/2023/02/10/watching-the-oxbow-dry/> (link) /a> /p> p>span classinfo>span>•/span>/span>Source New Mexico interview for report found a variety of online platforms: A River Wounded: Crisis on the Rio Grande a hrefhttps://sourcenm.com/2023/01/30/a-river-wounded-crisis-on-the-rio-grande/> (link) /a> /p> p>span classinfo>span>•/span>/span>South Central Climate Adaptation Science Center Webinar: A changing Rio Grande Watershed: Two modeling perspectivesa hrefhttps://www.youtube.com/watch?vLsJ8N4TRimY> (link) /a> /p> p>span classinfo>span>•/span>/span>U.S. geological Survey geopsatial group webinar: webinar strike>Can’t/strike> See the Forest strike>For/strike> and The Trees: High Resolution and Large-scale Canopy Characterization from Aerial Lidar, a href../downloads/moeser_lidar.mp4> (link) /a> /p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End ebsites, Videos, and Press --> !-- Languages ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Languages/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> li>English – native/li> li>German – CEFR level B2 | Chur, Switzerland (2012-2014) | Davos, Switzerland (2014-2016)/li>li>Spanish – CEFR level B2 | Xela, Guatemala (2005) | Bogota, Colombia (2006) | La Paz, Bolivia (2007) /li> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End languages --> !-- Hobbies ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Hobbies/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> li>Rock Climbing and Mountaineering/li> li>Travel/li>li>Language /li>li>Carpentry and Woodworking /li> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End languages --> !-- Skills ----------------------------------------------- --> div classrow skill> div classthree columns header-col> h1>span>Skills/span>/h1> /div> div classnine columns main-col> p>span classinfo>span>•/span>/span>Scripting / Coding is and has been an integral part of my work flow for over ten years. After I open my email each morning, I typically then open the command line window and start a blank matlab script. My scripting activities range from daily data analysis to dyanamically programmed interfaces and stand alone programs to process and analyze environmental data. I have several packages for novel LiDAR data manipulation, analysis and visualization available upon request. I coinisder myself an expert in Matlab, highly proficient in R, and have a base foundation in Python and Fortran as well as HTML and CSS./p>p>span classinfo>span>•/span>/span> Deployment and Development of Meteorological Equipment/p> /div> !-- End skills --> /section> !-- Resume Section End--> !-- Portfolio Section --> section idportfolio> div classrow> div classtwelve columns collapsed> h1>my current work quantifies the effects of landscape changes on hydrology. Click Below/h1> !-- portfolio-wrapper --> div idportfolio-wrapper classbgrid-quarters s-bgrid-thirds cf> div classcolumns portfolio-item> div classitem-wrap> a href#modal-01 title> img alt srcimages/post_fire_watershed.jpg> div classoverlay> div classportfolio-item-meta> h5>Post- fire Watershed Response and Recovery/h5> p>iphoto: USGS/p> /div> /div> div classlink-icon>i classicon-plus>/i>/div> /a> /div> /div> !-- item end --> div classcolumns portfolio-item> div classitem-wrap> a href#modal-02 titleWatershed Modeling> img alt srcimages/water_cycle.jpg> div classoverlay> div classportfolio-item-meta> h5>Watershed Modeling/h5> p>Precipitation Runoff Modeling System/p> /div> /div> div classlink-icon>i classicon-plus>/i>/div> /a> /div> /div> !-- item end --> div classcolumns portfolio-item> div classitem-wrap> a href#modal-03 title> img alt srcimages/interception.jpg> div classoverlay> div classportfolio-item-meta> h5>Forest Snow Hydrology/h5> p>modeling canopy processes/p> /div> /div> div classlink-icon>i classicon-plus>/i>/div> /a> /div> /div> !-- item end --> /div> !-- portfolio-wrapper end --> /div> !-- twelve columns end --> !-- Modal Popup --------------------------------------------------------------- --> div idmodal-01 classpopup-modal mfp-hide> img classscale-with-grid srcimages/post_fire_watershed.jpg alt /> div classdescription-box> h4>Post-Fire Watershed Recovery/h4> p>The recovery timing of burned watersheds, or the time the watershed takes to return to pre-fire peak flow state, is a function of many processes and can range from just a few years to decades. The watershed recovery continuum (the initialization, duration, rate and plenum) is based upon many interrelated aspects such as the portion of the watershed initially affected by fire, fire severity, storm duration, storm timing and storm intensity. However, recovery can be indirectly quantified by runoff efficiency, which is defined as the percent of precipitation that collects and creates runoff in a stream channel. Runoff efficiency is related to runoff travel time, and in general runoff travel time decreases as post-fire runoff efficiency increases following a wildfire compared to pre-fire values. img srcimages/recovery_response.jpg altIdealized watershed recovery and response width332 height156> /p> p> Stay tuned for an upcoming ISI joiurnal article which analyzes watershed response and recovery in a small SW US watershed./p> span classcategories>i classfa fa-tag>/i>Wildifire, Watershed, Modeling, Recovery/span> /div> div classlink-box> a hrefhttp://www.davidmoeser.com target_blank>Details/a> a classpopup-modal-dismiss>Close/a> /div> /div>!-- modal-01 End --> div idmodal-02 classpopup-modal mfp-hide> img classscale-with-grid srcimages/water_cycle.jpg alt /> div classdescription-box> h4>Watershed Modeling/h4> p>I was responsible for the development of a Precipitation Runoff Modeling System (PRMS) created for a small southwestern US watershed to determine post-fire wildfire effects of the hydrologic system. I created and calibrated two models: one model for pre-fire conditions and one model for post-fire conditions. The post-fire model was able to accurately model post-fire watershed response primarily from the manipulation of 5 manually calibrated parameters (PRMS has over 130 tunable parameters), which includes 2 canopy density parameters, shortwave radiation transmission through the canopy, soil recharge capacity and soil-water storage capacity. img srcimages/runoff_post_pre_fire.jpg altcomparison of pre- and post- fire overland flow for varius precipitation regimes width780 height439>/p> p> There are dramatic diferences in pre- and post- wildfire watershed response. The above graph compares overland flow between the pre- and post- fire models at diferent precipiation events. Interestingly, the larget diference between the two models were at median soil moisture capacities. Stay tuned for an upcoming USGS Scientific Investigations Report and an ISI Journal article. /p> span classcategories>i classfa fa-tag>/i>PRMS modeling, post-fire watershed response/span> /div> div classlink-box> a hrefhttp://www.davidmoeser.com target_blank>Details/a> a classpopup-modal-dismiss>Close/a> /div> /div>!-- modal-02 End --> div idmodal-03 classpopup-modal mfp-hide> img classscale-with-grid srcimages/interception.jpg alt /> div classdescription-box> h4>Forest Snow Processes/h4> p>I was recently awarded a competetvie grant from the South Central Climate Science Center to qauntify the effects of forest canopy disturbance on the underlying snow water resources. /p> p> Snow accounts for approximately 70% of total streamflow from the South Western US region’s primary water arteries, the Colorado River and Rio Grande. Forests within these watersheds are affected by climate change, modifications in land management, and a variety of natural disturbances such as wildfire and bark beetle attacks, all of which create uncertainty regarding the fate of this major water source. No studies have characterized or quantified the effects of forest fire on snow-water resources under a range of meteorological conditions that represent potential future climate scenarios. Until recently, forest snow models have been ill equipped to accurately quantify under-canopy snow accumulation and melt processes as theyrelate to the overlying forest canopy structure. Without tools to simulate and analyze potential impacts of wildfire on snow-water resources, effective water-resource planning, watershed protection, post-wildfire risk assessments, and future forest gap and growth analyses will have limited scientific basis or applicability in regions with wildfire potential. In order to better constrain forest-snow processes, a new snow-melt model has been developed that directly integrates LiDAR data for a high resolution representation of the modeling domain. A new process-based snow-interception model has also been developed that integrates LiDAR data to characterize the forest canopy./p> span classcategories>i classfa fa-tag>/i>High Resolution Snow Modeling, Forest Canopy Disturbace, Aerial LiDAR/span> /div> div classlink-box> a hrefhttp://www.davidmoeser.com target_blank>Details/a> a classpopup-modal-dismiss>Close/a> /div> /div>!-- modal-03 End --> div idmodal-04 classpopup-modal mfp-hide> img classscale-with-grid srcimages/travel_photography.jpg alt /> /div> !-- row End --> /section> !-- Portfolio Section End--> section idcall-to-action> div classrow> div classtwo columns header-col> h1>span>Global Water is local water!/span>/h1> /div> div classtwelve columns> p>The Water Cycle is affected by our changing world and climate; as such, we need more accurate measures to quantify the distribution of this critical resource over the landscape/span>. /p> h2>span classlead>. David Moeser/span>/h2> p>span classlead>Please do not hesitate to contact me via email of phone with any questions, comments or ideas. Collaboration keeps it fun!/span>/p> /div> /section> !-- Call-To-Action Section End--> !-- Water Facts Section --> section idtestimonials> div classtext-container> div classrow> div classtwo columns header-col> h1>span>Water use Facts/span>/h1> /div> div classten columns flex-container> div classflexslider> ul classslides> li> blockquote> p>Just 0.3% of total freshwater ( less than 0.007% of total water) is seen on the surface as rivers and lakes. /p> cite>The United Nations World Water Assesment Programme/cite> /blockquote> /li> !-- slide ends --> li> blockquote> p> Water scarcity affects > 40 percent of the global population, over 1.7 billion people are living in river basins where water use exceeds recharge. /p> cite>The United Nations World Water Assesment Programme/cite> /blockquote> /li> !-- slide ends --> li> blockquote> p>On average the water footprint of a U.S. citizen is 32,911 glasses of water a day. CHECK YOUR PERSONAL WATER FOOTPRINT a hrefhttp://waterfootprint.org/en/resources/interactive-tools/personal-water-footprint-calculator/> HERE. /a>/p> cite>The Water Footprint Network/cite> /blockquote> /li> !-- slide ends --> /ul> /div> !-- div.flexslider ends --> /div> !-- div.flex-container ends --> /div> !-- row ends --> /div> !-- text-container ends --> /section> !-- Water Use Section End--> !-- Contact Section --> section idcontact> div classrow section-head> div classtwo columns header-col> h1>span>Get In Touch./span>/h1> /div> div classten columns> p classlead>Look forward to hearing from you! /p> /div> /div> div classrow> div classeight columns> !-- form --> form action methodpost idcontactForm namecontactForm> fieldset> div> label forcontactName>Name span classrequired>*/span>/label> input typetext value size35 idcontactName namecontactName> /div> div> label forcontactEmail>Email span classrequired>*/span>/label> input typetext value size35 idcontactEmail namecontactEmail> /div> div> label forcontactSubject>Subject/label> input typetext value size35 idcontactSubject namecontactSubject> /div> div> label forcontactMessage>Message span classrequired>*/span>/label> textarea cols50 rows15 idcontactMessage namecontactMessage>/textarea> /div> div> button classsubmit>Submit/button> span idimage-loader> img alt srcimages/loader.gif> /span> /div> /fieldset> /form> !-- Form End --> !-- contact-warning --> div idmessage-warning> Error boy/div> !-- contact-success --> div idmessage-success> i classfa fa-check>/i> MESSAGE NOT SENT- PLEASE USE MY EMAIL ADDRESS: cdmoeser@yahoo(dot)com. Thanks! br> /div> /div> aside classfour columns footer-widgets> div classwidget widget_contact> h4>Address and Phone/h4> p classaddress> C. David Moeserbr> 314 14th st. NW br> Albuquerque, NM 87104 USbr> cdmoeser(at)yahoo(dot)combr> span> +1 (77five) 3five7- 66six8/span> /p> /div> /div> /aside> /div> /section> !-- Contact Section End--> !-- footer --> footer> div classrow> div classtwelve columns> ul classsocial-links> li>a hrefhttps://www.facebook.com/cdmoeser>i classfa fa-facebook>/i>/a>/li> li>a hrefhttps://www.linkedin.com/in/david-moeser-4a91246/>i classfa fa-linkedin>/i>/a>/li> li>a hrefskype:cdmoeser?userinfo>i classfa fa-skype>/i>/a>/li> /ul> ul classcopyright> li>© Copyright 2017 C. David Moeser/li> li>Design by a hrefhttp://www.davidmoeser.com titleDavid Moeser target_blank>David Moeser/a>/li> /ul> /div> div idgo-top>a classsmoothscroll titleBack to Top href#home>i classicon-up-open>/i>/a>/div> /div> /footer> !-- Footer End--> !-- Java Script --> script srchttp://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js>/script> script>window.jQuery || document.write(script srcjs/jquery-1.10.2.min.js>\/script>)/script> script typetext/javascript srcjs/jquery-migrate-1.2.1.min.js>/script> script srcjs/jquery.flexslider.js>/script> script srcjs/waypoints.js>/script> script srcjs/jquery.fittext.js>/script> script srcjs/magnific-popup.js>/script> script srcjs/init.js>/script> /body> /html>
Port 443
HTTP/1.1 200 OKDate: Fri, 27 Feb 2026 11:50:11 GMTServer: ApacheUpgrade: h2,h2cConnection: UpgradeLast-Modified: Thu, 03 Oct 2024 19:43:04 GMTETag: 1a006f0-102e4-62397c35cb00aAccept-Ranges: bytesContent-Length: 66276Vary: Accept-EncodingContent-Type: text/html !DOCTYPE html> html classno-js langen> head> !--- Basic Page Needs --> meta charsetutf-8> title>C. David Moeser, PhD - Hydrologist/title> meta namepersonal website content> meta namemoeser content> !-- Mobile Specific Metas --> meta nameviewport contentwidthdevice-width, initial-scale1, maximum-scale1> !-- CSS --> link relstylesheet hrefcss/default.css> link relstylesheet hrefcss/layout.css> link relstylesheet hrefcss/media-queries.css> link relstylesheet hrefcss/magnific-popup.css> !-- Script --> script srcjs/modernizr.js>/script> !-- Favicons --> link relshortcut icon hreffavicon.png > /head> body> !-- Start of StatCounter Code for Dreamweaver --> script typetext/javascript> var sc_project7308544; var sc_invisible1; var sc_security410ad643; /script> script typetext/javascript srchttp://www.statcounter.com/counter/counter.js>/script> noscript>div classstatcounter>a titledrupal statistics module hrefhttp://statcounter.com/drupal/ target_blank>img classstatcounter srchttp://c.statcounter.com/7308544/0/410ad643/1/ altdrupal statistics module>/a>/div>/noscript> !-- End of StatCounter Code for Dreamweaver --> !-- Header --> header idhome> nav idnav-wrap> a classmobile-btn href#nav-wrap titleShow navigation> Show navigation/a> a classmobile-btn href# titleHide navigation>Hide navigation/a> ul idnav classnav> li classcurrent>a classsmoothscroll href#home>Home/ a>/li> li>a classsmoothscroll href#about>About/a>/li> li>a classsmoothscroll href#resume>Resume/a>/li> li>a classsmoothscroll href#portfolio>Works/a>/li> li>a classsmoothscroll href#testimonials>Water Facts/a >/li> li>a classsmoothscroll href#contact>Contact/a>/li> /ul> !-- end #nav --> /nav> !-- end #nav-wrap --> div classrow banner> div classbanner-text> h1 classresponsive-headline>C. David Moeser/h1> h3>span>Im a New Mexico based hydrologist, environmental scientist and data analyst, specializing in snow and watershed modeling. /span> hr /> ul classsocial> li>a hrefhttps://www.facebook.com/cdmoeser>i classfa fa-facebook>/i>/a>/li> li>a hrefhttps://www.linkedin.com/in/david-moeser-4a91246/>i classfa fa-linkedin>/i>/a>/li> li>a hrefskype:cdmoeser?userinfo>i classfa fa-skype>/i>/a>/li> /ul> /div> /div> p classscrolldown> a classsmoothscroll href#about>i classicon-down-circle>/i>/a> /p> /header> !-- Header End --> !-- About Section --> section idabout> div classrow> div classthree columns> img classprofile-pic srcimages/profilepic.jpg alt /> /div> div classnine columns main-col> h2>About Me/h2> p>I am a hydrologist for the USGS – New Mexico Water Science Center and in charge of all technical watershed-modeling activities. I have developed data processing and analysis techniques and serve as the centers technical authority on all waterhsed modeling and snow hydrology activities. I am currently developing and implementing novel characterizations of forest canopy as well as snow modeling tools in order to quantify the effects of canopy disturbance on snow water resources. /p> div classrow> div classcolumns contact-details> h2>Contact Details/h2> p classaddress> span>C. David Moeser/span>br> span>314 14th st NW/span>br> span>Albuquerque, NM 87104 USA/span>br> span>+1 (77five) 3five7- 66six8/span>br> span>cdmoeser(at)yahoo(dot)com/span>/p> /div> div classcolumns download> p> a href../cv/cv_moeser.pdf classbutton>i classfa fa-download>/i>Download Resume/a> /p> /div> /div> !-- end row --> /div> !-- end .main-col --> /div> /section> !-- About Section End--> !-- Resume Section --> section idresume> !-- Education ----------------------------------------------- --> div classrow education> div classthree columns header-col> h1>span>Education/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> h3>Swiss Federal Institute of Technology, Zürich a hrefhttps://en.wikipedia.org/wiki/ETH_Zurich> (ETH) /a>/h3> p classinfo>PhD span>•/span>em>December 2015/em>/p> p classinfo>em>Surface Water Hydrology/em>span>•/span>Department of span>Environmental Systems Science/span>/p> p> Dissertation: The Influence of Forest Canopy Structure on Snow Hydrology. Download a href../downloads/final_dissertation_moeser_2016.pdf> here /a> /p> Funding: Successful Swiss National Science Foundation Grant Proposal. Download a href../downloads/proposal_snsf.pdf> here /a> p> /p> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>University of Nevada, Reno/h3> p classinfo>M.S.span>•/span>em>December 2010/em>/p> p classinfo>em>Surface Water Hydrology/em>span>•/span>Department of span>Hydrologic Sciences/span>/p>p>Thesis: Development, Analysis and Use of a Distributed Wireless Sensor Network for Quantifying Spatial Trends of Snow Depth and Snow Water Equivalence. Download a href../downloads/thesis_final_moeser.pdf> here /a>/p> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>Fort Lewis College/h3> p classinfo>B.S.span>•/span>em>December 2004/em>/p> p classinfo>em>Environmental Geology / Chemistry minor/em>span>•/span>Department of span>Geosciences/span>/p>p>Thesis: Discriminating Pre- and Post- Mining Effects on The Middle Fork of Mineral Creek, Silverton, CO, Using Tree Core Analysis/p>p>Awarded outstanding senior in the earth sciences (Eugene M. Shoemaker Award)/p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Education --> !-- Work ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Work/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> h3>United States Geological Survey/h3> p classinfo>New Mexico Water Science Centerem classdate>/em>/p> p classinfo>Hydrologist span>•/span> em classdate>July 2016 - Present/em>/p> li>Serve as the centers technical authority on all surface water modeling and snow hydrology activities, both, in the office and the field. /li> li>Act as a regional technical advisor to external land managers with stakes in water resources and planning./li> li>Charged with all technical watershed-modeling activities. /li> li>Develop novel data processing and analysis techniques. /li> li>Currently developing and implementing novel characterizations of forests and modeling tools to quantify the effects of forest disturbance and changing climate on water resources. /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>WSL Institute for Snow and Avalanche Research SLF /h3> p classinfo>Davos, Switzerlandem classdate>/em>/p> p classinfo>Snow Hydrologist / PhD Candidate span>•/span> em classdate>February 2012 - February 2016/em>/p> li> Snow model and analysis tool development/li> li> Aerial and terrestrial LiDAR (light detection and ranging) data gathering, and manipulation /li> li> Snow survey campaign supervision (total: 12 employees)/li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>World Business Council For Sustainable Development/h3> p classinfo>Geneva, Switzerland em classdate>/em>/p> p classinfo>Contract Hydrologist span>•/span> em classdate>September 2011 - February 2012/em>/p> li> Water and energy use linkage analyses between food, feed, and fiber management scenarios/li> li> Knowledge exchange coordination between UN organizations, research institutes, and businesses for water related projects/li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>WSL Institute for Snow and Avalanche Research SLF /h3> p classinfo>Davos, Switzerlandem classdate>/em>/p> p classinfo>Snow Hydrology Internspan>•/span> em classdate>January 2011 - July 2011/em>/p> li> Snow survey campaign leader within a high alpine basin in avalanche terrain/li> li> Snow melt modeling implementation and analysis/li> li> Geographic data parsing and analysis /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>University of Nevada, Reno /h3> p classinfo>Research Assistantspan>•/span> em classdate>September 2008 - December 2010/em>/p> li> Wireless snow depth sensing equipment and affiliated meteorological station deployment, maintenance, and analysis/li>li> Statistical and geo-statistical modeling of snow /li> li> Stilling well and V-notch weir installation in an urban watershed/li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>Bureau of Land Management/ U.S. Forest Service /h3> p classinfo>Public Lands Center - em classdate>/em>Durango, Colorado/p> p classinfo>Hydrologic Technicianspan>•/span> em classdate>2005 - 2007/em>/p> li> Surface and groundwater water quantity and quality monitoring in springs and streams within Colorado, Utah, and New Mexico/li> li> Groundwater monitoring well and piezometer installation /li> li> Forest stream remediation and characterization /li> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Education --> !-- Teaching ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Teaching/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> h3>Swiss Federal Institute of Technology (ETH)/h3> p classinfo>Zürich, Switzerlandem classdate>/em>/p> p classinfo>(2013 - 2014) Department of Environment Systems Scienceem classdate>/em>/p> p classinfo>Environmental Measurement Laboratory (701) /p> li> Course and laboratory structure development for a 6-hour lecture module designed to integrate matlab programing with remotely sensed data /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>University of Nevada, Reno /h3> p classinfo>(2008 - 2010) Department of Natural Resources and Environmental Scienceem classdate>/em>/p> p classinfo>Principles of Ecohydrology (295) /p> p classinfo>Ecohydrology Field Camp (400)/p> li> New course material and method development /li> li> Field and laboratory lecturing and supervision /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>University of Nevada, Reno Cooperative Extension /h3> p classinfo>(2009 - 2010) Discover your Future/p> li> Basic hydrologic field methods and applications: activity leader and guest lecturer for high school students /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> h3>Fort Lewis College /h3> p classinfo>(2023) Collaborative Environmental Research/p> li> Field measurement techniques for snow /li> /div> /div> !-- item end --> div classrow item> div classtwelve columns> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Work --> !-- Published Work ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Published Papers/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span> strong>Moeser, D, /strong>Sexstone, G., Kurzweil, J., 2024, Modeling Forest Snow Using Relative Canopy Structure Metrics, Water, 16, 1398, https://doi.org/10.3390/w16101398/p> p>span classinfo>span>•/span>/span> Mankin, K., Rumsey, C.,... strong>Moeser, D/strong>.,...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/p> p>span classinfo>span>•/span>/span> Broxton, P., strong>Moeser, D/strong>.,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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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: a hrefhttps://webapps.usgs.gov/urgb-prms/>https://webapps.usgs.gov/urgb-prms//a>/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>, 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>, 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 /p> p>span classinfo>span>•/span>/span>Helbig, N., strong>Moeser, D./strong>, 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 /p> p>span classinfo>span>•/span>/span>Sexstone, G.A., Penn, C.A., Liston, G.E., Gleason, K.E., strong> Moeser, D.,/strong> 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./p> p>span classinfo>span>•/span>/span>Mazzotti, G., Essery, R., strong>Moeser, D./strong>, 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 /p> p>span classinfo>span>•/span>/span>Chavarria, S.B., strong>Moeser, D./strong>., 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/p> p>span classinfo>span>•/span>/span>Douglas-Mankin, K. and strong>Moeser, D./strong>, 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 a hrefhttps://pubs.er.usgs.gov/publication/sir20195022> (link) /a> /p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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 a href../downloads/moeser2016wrr.pdf> (link) /a>/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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 a href../downloads/moeser2015wrr.pdf> (link) /a>/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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.2015.04.013a href../downloads/moeser_2015a_afm.pdf> (link) /a>/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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 a href../downloads/moeser_2014a_afm.pdf> (link) /a>/p> h3>Data and Code Releases/h3> p>span classinfo>span>•/span>/span> strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span> Sexstone, G., strong>Moeser, D.,/strong> 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/P13OM8Y3p> p>span classinfo>span>•/span>/span> strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span> strong>Moeser, D./strong>, 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/p> p>span classinfo>span>•/span>/span>Chavarria, S.B., strong>Moeser, D.,/strong> 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 /p> p>span classinfo>span>•/span>/span>Chavarria, S.B., strong>Moeser, D./strong> 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 /p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 2020, Lidar2CanopyMetrics package of scripts to calculated canopy structure and density from aerial lidar data, https://doi.org/10.5281/zenodo.4088667 /p> p>span classinfo>span>•/span>/span> strong>Moeser, D./strong>, 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./p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>, 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 /p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Published Work --> !-- external reports and grants ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Significant and Successful Competetive Grant Proposals /span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span>South Central Climate Adaptation Science Center – Estimating The Future Effects of Forest Disturbance on Snow Water Resources in a Changing Environment Part Two (2024)/p> p>•South Central Climate Adaptation Science Center – Estimating The Future Effects of Forest Disturbance on Snow Water Resources in a Changing Environment Part One (2021)/p> p>•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)/p> p>South Central Climate Adaptation Science Center – The Effects of Wildfire on Snow Water Resources Under Multiple Climate Conditions (2017)/p> p>span classinfo>span>•/span>/span>Swiss National Science Foundation – ‘Snow Distribution Dynamics under Forest Canopy’ (2012) a href../downloads/proposal_snsf.pdf> (link) /a> /p> p>span classinfo>span>•/span>/span>Agriculture Research Service – ‘Recommended Procedure for Assessing Soil Disturbances in Vegetation Management Projects within Sensitive Areas of the Lake Tahoe Basin’ (2008)/p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End xternal reports and grants --> !-- Conference Papers and Presentations ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1> /h1> h1>span>Conference Papers and Presentations/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span>Roussel, S., Galanter, A., strong>Moeser, D.,/strong> Mack, T., ‘Groundwater Response to Natural Infrastructure in Dryland Streams, National Conference on Ecosystem Restoration, Albuquerque, NM, April 2024/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>, 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/p> p>span classinfo>span>•/span>/span>Sexstone, G., Penn, C., Liston, G., Gleason, K., strong>Moeser, D./strong>, Clow, D.; ‘Fine-Scale Spatial Variability in Seasonal Snowpack Trends,’ American Geophysical Union meeting, San Francisco, California, December 2019/p> p>span classinfo>span>•/span>/span> strong>Moeser, D. /strong>, 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/p> p>span classinfo>span>•/span>/span>Helbig, N., strong>D. Moeser/strong>, M. Teich; ‘Spatially-Averaged Sky View Factors for Snow Interception over Forest Canopy,’ European Geophysical Union, Vienna, Austria, April 2018/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> p>span classinfo>span>•/span>/span>Sexstone, G., C. Penn, D. Clow,strong>D. Moeser/strong>, G. Liston; ‘Changes in the Relation Between Snow Station Observations and Basin Scale Snow Water Equivalence,’ American Geophysical Union, New Orleans, Louisiana, December 2017/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., M. Stähli; ‘Forest Canopy Controls on Snow Hydrology,’ Western Snow Conference, Boise, Idaho, March 2017/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>.; ‘Forest snow hydrology,’ Department colloquium series, Department of Earth and Environmental Science, New Mexico Tech, Socorro, New Mexico, January 2017/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>.; ‘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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., M. Stähli; ‘The influence of canopy structure on snow,’ poster presentation, American Geophysical Union meeting, San Francisco, California, December 2016/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., M. Stähli, T. Jonas; ‘Snow interception modeling,’ oral presentation, The International Union of Geodesy and Geophysics, Prague, Czech Republic, June 2015/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., F. Morsdorf, T. Jonas; ‘Improving snow interception modeling using LiDAR data,’ poster presentation, American Geophysical Union meeting, San Francisco, CA, December 2014/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., J. Roubinek, F. Morsdorf, T. Jonas; ‘Snow distribution dynamics under forest canopy,’ poster presentation, American Geophysical Union meeting, San Francisco, CA, December 2013/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> p>span classinfo>span>•/span>/span>Jonas, T., strong>D. Moeser/strong>, 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/p> p>span classinfo>span>•/span>/span>Jonas, T., strong>D. Moeser/strong>, 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D/strong>., 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/p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End Conference Papers and Presentations --> !-- Stakeholder Presentations and Colloquiums ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Stakeholder Presentations and Colloquiums/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span>Galanter, A., Ritchie, A.,strong>Moeser, D.,/strong>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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> Chavarria, S., Streamflow Response to Potential Changes in the Upper Rio Grande Basin, Middle Rio Grande Endangered Species Collaborative Program, December 2022/p> p>span classinfo>span>•/span>/span>strong> Moeser, D.,/strong> Chavarria, S., Snow and Watershed Modeling in Forested Environments, United States Forest Severe Forest Science Laboratory Collaborative, November 2022/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> Chavarria, S., Sexstone, G., Wootten, A., Broxton, P., Harpold, A., strike>Can’t/strike> See the Forest strike>For/strike> and The Trees: High Resolution and Large-scale Canopy Characterization from Aerial Lidar, USGS Geospatial Group webinar, September 2022/p> p>span classinfo>span>•/span>/span>Sexstone, G., Fulton, J., McDermott, W.,…..strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> Chavarria, S., Recently Completed Snow and Watershed Modeling Projects, Oregon Water Science Center Seminar Series, February 2022/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> The Effects of Canopy Structure Changes on Snow Water Resources, USGS Fire Water Working Group, June 2021 /p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> The Effects of Canopy Structure Changes on Snow Water Resources Bureau of Reclamation Colloquium series, May 2021/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> The Effects of Wildfire on Snow Water Under Multiple Canopy Structure and Meteorological Conditions, New Mexico Forest and Watershed Health Coordinating Group, January 2021/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> Canopy disturbance and Snow Water Resources in the Upper Rio Grande Basin, 2-3-2 Collaborative, October 2020/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> The Effects of Canopy Structure Changes on Snow Water Resources, Rocky Mountain Region Science Exchange Conference, September 2020/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong> 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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>; ‘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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>; ‘Forest snow hydrology,’ Department colloquium series, Department of Earth and Environmental Science, New Mexico Tech, Socorro, New Mexico, January 2017/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong>‘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/p> p>span classinfo>span>•/span>/span>strong>Moeser, D.,/strong>M. Stähli; ‘The influence of canopy structure on snow,’ poster presentation, American Geophysical Union meeting, San Francisco, California, December 2016/p> p>span classinfo>span>•/span>/span>strong>Moeser, D./strong>; ‘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/p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- Stakeholder Presentations and Colloquiums--> !-- Websites, Videos, and Press ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Websites, Videos, and Press/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> p>span classinfo>span>•/span>/span>USGS Upper Rio Grande Basin Climate Projections and dynamic hydrographsa hrefhttps://webapps.usgs.gov/urgb-prms/> (link) /a> /p> p>span classinfo>span>•/span>/span>Long Format Interview: Climate and Snowpack, New Mexico Water Data Stories (2021)a hrefhttps://www.youtube.com/watch?vnFRsca4mFm8> (link) /a>/p> p>span classinfo>span>•/span>/span>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 Grandea hrefhttps://www.usnews.com/news/best-states/new-mexico/articles/2022-02-20/experts-drastic-changes-forecast-for-rio-grande> (link) /a> /p> p>span classinfo>span>•/span>/span>Source New Mexico interview for report found a variety of online platforms: Watching the Oxbow Dry a hrefhttps://sourcenm.com/2023/02/10/watching-the-oxbow-dry/> (link) /a> /p> p>span classinfo>span>•/span>/span>Source New Mexico interview for report found a variety of online platforms: A River Wounded: Crisis on the Rio Grande a hrefhttps://sourcenm.com/2023/01/30/a-river-wounded-crisis-on-the-rio-grande/> (link) /a> /p> p>span classinfo>span>•/span>/span>South Central Climate Adaptation Science Center Webinar: A changing Rio Grande Watershed: Two modeling perspectivesa hrefhttps://www.youtube.com/watch?vLsJ8N4TRimY> (link) /a> /p> p>span classinfo>span>•/span>/span>U.S. geological Survey geopsatial group webinar: webinar strike>Can’t/strike> See the Forest strike>For/strike> and The Trees: High Resolution and Large-scale Canopy Characterization from Aerial Lidar, a href../downloads/moeser_lidar.mp4> (link) /a> /p> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End ebsites, Videos, and Press --> !-- Languages ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Languages/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> li>English – native/li> li>German – CEFR level B2 | Chur, Switzerland (2012-2014) | Davos, Switzerland (2014-2016)/li>li>Spanish – CEFR level B2 | Xela, Guatemala (2005) | Bogota, Colombia (2006) | La Paz, Bolivia (2007) /li> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End languages --> !-- Hobbies ----------------------------------------------- --> div classrow work> div classthree columns header-col> h1>span>Hobbies/span>/h1> /div> div classnine columns main-col> div classrow item> div classtwelve columns> li>Rock Climbing and Mountaineering/li> li>Travel/li>li>Language /li>li>Carpentry and Woodworking /li> /div> /div> !-- item end --> /div> !-- main-col end --> /div> !-- End languages --> !-- Skills ----------------------------------------------- --> div classrow skill> div classthree columns header-col> h1>span>Skills/span>/h1> /div> div classnine columns main-col> p>span classinfo>span>•/span>/span>Scripting / Coding is and has been an integral part of my work flow for over ten years. After I open my email each morning, I typically then open the command line window and start a blank matlab script. My scripting activities range from daily data analysis to dyanamically programmed interfaces and stand alone programs to process and analyze environmental data. I have several packages for novel LiDAR data manipulation, analysis and visualization available upon request. I coinisder myself an expert in Matlab, highly proficient in R, and have a base foundation in Python and Fortran as well as HTML and CSS./p>p>span classinfo>span>•/span>/span> Deployment and Development of Meteorological Equipment/p> /div> !-- End skills --> /section> !-- Resume Section End--> !-- Portfolio Section --> section idportfolio> div classrow> div classtwelve columns collapsed> h1>my current work quantifies the effects of landscape changes on hydrology. Click Below/h1> !-- portfolio-wrapper --> div idportfolio-wrapper classbgrid-quarters s-bgrid-thirds cf> div classcolumns portfolio-item> div classitem-wrap> a href#modal-01 title> img alt srcimages/post_fire_watershed.jpg> div classoverlay> div classportfolio-item-meta> h5>Post- fire Watershed Response and Recovery/h5> p>iphoto: USGS/p> /div> /div> div classlink-icon>i classicon-plus>/i>/div> /a> /div> /div> !-- item end --> div classcolumns portfolio-item> div classitem-wrap> a href#modal-02 titleWatershed Modeling> img alt srcimages/water_cycle.jpg> div classoverlay> div classportfolio-item-meta> h5>Watershed Modeling/h5> p>Precipitation Runoff Modeling System/p> /div> /div> div classlink-icon>i classicon-plus>/i>/div> /a> /div> /div> !-- item end --> div classcolumns portfolio-item> div classitem-wrap> a href#modal-03 title> img alt srcimages/interception.jpg> div classoverlay> div classportfolio-item-meta> h5>Forest Snow Hydrology/h5> p>modeling canopy processes/p> /div> /div> div classlink-icon>i classicon-plus>/i>/div> /a> /div> /div> !-- item end --> /div> !-- portfolio-wrapper end --> /div> !-- twelve columns end --> !-- Modal Popup --------------------------------------------------------------- --> div idmodal-01 classpopup-modal mfp-hide> img classscale-with-grid srcimages/post_fire_watershed.jpg alt /> div classdescription-box> h4>Post-Fire Watershed Recovery/h4> p>The recovery timing of burned watersheds, or the time the watershed takes to return to pre-fire peak flow state, is a function of many processes and can range from just a few years to decades. The watershed recovery continuum (the initialization, duration, rate and plenum) is based upon many interrelated aspects such as the portion of the watershed initially affected by fire, fire severity, storm duration, storm timing and storm intensity. However, recovery can be indirectly quantified by runoff efficiency, which is defined as the percent of precipitation that collects and creates runoff in a stream channel. Runoff efficiency is related to runoff travel time, and in general runoff travel time decreases as post-fire runoff efficiency increases following a wildfire compared to pre-fire values. img srcimages/recovery_response.jpg altIdealized watershed recovery and response width332 height156> /p> p> Stay tuned for an upcoming ISI joiurnal article which analyzes watershed response and recovery in a small SW US watershed./p> span classcategories>i classfa fa-tag>/i>Wildifire, Watershed, Modeling, Recovery/span> /div> div classlink-box> a hrefhttp://www.davidmoeser.com target_blank>Details/a> a classpopup-modal-dismiss>Close/a> /div> /div>!-- modal-01 End --> div idmodal-02 classpopup-modal mfp-hide> img classscale-with-grid srcimages/water_cycle.jpg alt /> div classdescription-box> h4>Watershed Modeling/h4> p>I was responsible for the development of a Precipitation Runoff Modeling System (PRMS) created for a small southwestern US watershed to determine post-fire wildfire effects of the hydrologic system. I created and calibrated two models: one model for pre-fire conditions and one model for post-fire conditions. The post-fire model was able to accurately model post-fire watershed response primarily from the manipulation of 5 manually calibrated parameters (PRMS has over 130 tunable parameters), which includes 2 canopy density parameters, shortwave radiation transmission through the canopy, soil recharge capacity and soil-water storage capacity. img srcimages/runoff_post_pre_fire.jpg altcomparison of pre- and post- fire overland flow for varius precipitation regimes width780 height439>/p> p> There are dramatic diferences in pre- and post- wildfire watershed response. The above graph compares overland flow between the pre- and post- fire models at diferent precipiation events. Interestingly, the larget diference between the two models were at median soil moisture capacities. Stay tuned for an upcoming USGS Scientific Investigations Report and an ISI Journal article. /p> span classcategories>i classfa fa-tag>/i>PRMS modeling, post-fire watershed response/span> /div> div classlink-box> a hrefhttp://www.davidmoeser.com target_blank>Details/a> a classpopup-modal-dismiss>Close/a> /div> /div>!-- modal-02 End --> div idmodal-03 classpopup-modal mfp-hide> img classscale-with-grid srcimages/interception.jpg alt /> div classdescription-box> h4>Forest Snow Processes/h4> p>I was recently awarded a competetvie grant from the South Central Climate Science Center to qauntify the effects of forest canopy disturbance on the underlying snow water resources. /p> p> Snow accounts for approximately 70% of total streamflow from the South Western US region’s primary water arteries, the Colorado River and Rio Grande. Forests within these watersheds are affected by climate change, modifications in land management, and a variety of natural disturbances such as wildfire and bark beetle attacks, all of which create uncertainty regarding the fate of this major water source. No studies have characterized or quantified the effects of forest fire on snow-water resources under a range of meteorological conditions that represent potential future climate scenarios. Until recently, forest snow models have been ill equipped to accurately quantify under-canopy snow accumulation and melt processes as theyrelate to the overlying forest canopy structure. Without tools to simulate and analyze potential impacts of wildfire on snow-water resources, effective water-resource planning, watershed protection, post-wildfire risk assessments, and future forest gap and growth analyses will have limited scientific basis or applicability in regions with wildfire potential. In order to better constrain forest-snow processes, a new snow-melt model has been developed that directly integrates LiDAR data for a high resolution representation of the modeling domain. A new process-based snow-interception model has also been developed that integrates LiDAR data to characterize the forest canopy./p> span classcategories>i classfa fa-tag>/i>High Resolution Snow Modeling, Forest Canopy Disturbace, Aerial LiDAR/span> /div> div classlink-box> a hrefhttp://www.davidmoeser.com target_blank>Details/a> a classpopup-modal-dismiss>Close/a> /div> /div>!-- modal-03 End --> div idmodal-04 classpopup-modal mfp-hide> img classscale-with-grid srcimages/travel_photography.jpg alt /> /div> !-- row End --> /section> !-- Portfolio Section End--> section idcall-to-action> div classrow> div classtwo columns header-col> h1>span>Global Water is local water!/span>/h1> /div> div classtwelve columns> p>The Water Cycle is affected by our changing world and climate; as such, we need more accurate measures to quantify the distribution of this critical resource over the landscape/span>. /p> h2>span classlead>. David Moeser/span>/h2> p>span classlead>Please do not hesitate to contact me via email of phone with any questions, comments or ideas. Collaboration keeps it fun!/span>/p> /div> /section> !-- Call-To-Action Section End--> !-- Water Facts Section --> section idtestimonials> div classtext-container> div classrow> div classtwo columns header-col> h1>span>Water use Facts/span>/h1> /div> div classten columns flex-container> div classflexslider> ul classslides> li> blockquote> p>Just 0.3% of total freshwater ( less than 0.007% of total water) is seen on the surface as rivers and lakes. /p> cite>The United Nations World Water Assesment Programme/cite> /blockquote> /li> !-- slide ends --> li> blockquote> p> Water scarcity affects > 40 percent of the global population, over 1.7 billion people are living in river basins where water use exceeds recharge. /p> cite>The United Nations World Water Assesment Programme/cite> /blockquote> /li> !-- slide ends --> li> blockquote> p>On average the water footprint of a U.S. citizen is 32,911 glasses of water a day. CHECK YOUR PERSONAL WATER FOOTPRINT a hrefhttp://waterfootprint.org/en/resources/interactive-tools/personal-water-footprint-calculator/> HERE. /a>/p> cite>The Water Footprint Network/cite> /blockquote> /li> !-- slide ends --> /ul> /div> !-- div.flexslider ends --> /div> !-- div.flex-container ends --> /div> !-- row ends --> /div> !-- text-container ends --> /section> !-- Water Use Section End--> !-- Contact Section --> section idcontact> div classrow section-head> div classtwo columns header-col> h1>span>Get In Touch./span>/h1> /div> div classten columns> p classlead>Look forward to hearing from you! /p> /div> /div> div classrow> div classeight columns> !-- form --> form action methodpost idcontactForm namecontactForm> fieldset> div> label forcontactName>Name span classrequired>*/span>/label> input typetext value size35 idcontactName namecontactName> /div> div> label forcontactEmail>Email span classrequired>*/span>/label> input typetext value size35 idcontactEmail namecontactEmail> /div> div> label forcontactSubject>Subject/label> input typetext value size35 idcontactSubject namecontactSubject> /div> div> label forcontactMessage>Message span classrequired>*/span>/label> textarea cols50 rows15 idcontactMessage namecontactMessage>/textarea> /div> div> button classsubmit>Submit/button> span idimage-loader> img alt srcimages/loader.gif> /span> /div> /fieldset> /form> !-- Form End --> !-- contact-warning --> div idmessage-warning> Error boy/div> !-- contact-success --> div idmessage-success> i classfa fa-check>/i> MESSAGE NOT SENT- PLEASE USE MY EMAIL ADDRESS: cdmoeser@yahoo(dot)com. Thanks! br> /div> /div> aside classfour columns footer-widgets> div classwidget widget_contact> h4>Address and Phone/h4> p classaddress> C. David Moeserbr> 314 14th st. NW br> Albuquerque, NM 87104 USbr> cdmoeser(at)yahoo(dot)combr> span> +1 (77five) 3five7- 66six8/span> /p> /div> /div> /aside> /div> /section> !-- Contact Section End--> !-- footer --> footer> div classrow> div classtwelve columns> ul classsocial-links> li>a hrefhttps://www.facebook.com/cdmoeser>i classfa fa-facebook>/i>/a>/li> li>a hrefhttps://www.linkedin.com/in/david-moeser-4a91246/>i classfa fa-linkedin>/i>/a>/li> li>a hrefskype:cdmoeser?userinfo>i classfa fa-skype>/i>/a>/li> /ul> ul classcopyright> li>© Copyright 2017 C. David Moeser/li> li>Design by a hrefhttp://www.davidmoeser.com titleDavid Moeser target_blank>David Moeser/a>/li> /ul> /div> div idgo-top>a classsmoothscroll titleBack to Top href#home>i classicon-up-open>/i>/a>/div> /div> /footer> !-- Footer End--> !-- Java Script --> script srchttp://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js>/script> script>window.jQuery || document.write(script srcjs/jquery-1.10.2.min.js>\/script>)/script> script typetext/javascript srcjs/jquery-migrate-1.2.1.min.js>/script> script srcjs/jquery.flexslider.js>/script> script srcjs/waypoints.js>/script> script srcjs/jquery.fittext.js>/script> script srcjs/magnific-popup.js>/script> script srcjs/init.js>/script> /body> /html>
View on OTX
|
View on ThreatMiner
Please enable JavaScript to view the
comments powered by Disqus.
Data with thanks to
AlienVault OTX
,
VirusTotal
,
Malwr
and
others
. [
Sitemap
]