Scales of snow depth variability in high elevation rangeland sagebrush

Molly E. TEDESCHE, Steven R. FASSNACHT, Paul J. MEIMAN

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Front. Earth Sci. ›› 2017, Vol. 11 ›› Issue (3) : 469-481. DOI: 10.1007/s11707-017-0662-z
RESEARCH ARTICLE
RESEARCH ARTICLE

Scales of snow depth variability in high elevation rangeland sagebrush

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Abstract

In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush (Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran’s I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

Keywords

snow hydrology / high elevation rangelands / spatial statistics / variograms / snow pack spatial variability / snow drifts

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Molly E. TEDESCHE, Steven R. FASSNACHT, Paul J. MEIMAN. Scales of snow depth variability in high elevation rangeland sagebrush. Front. Earth Sci., 2017, 11(3): 469‒481 https://doi.org/10.1007/s11707-017-0662-z
<strong>AUTHOR BIOGRAPHIES</strong

Molly E. Tedesche has a BS in civil engineering technology from Rochester Institute of Technology (RIT) in Rochester, NY, USA, and an MS in watershed science from Colorado State University (CSU) in Fort Collins, CO, USA.

She is has worked as an Engineer, Snow Hydrologist, and in Forestry; as well as an Environmental Scientist and Science Educator. She is currently pursuing a PhD in hydrology from the University of Alaska Fairbanks (UAF). Her research interests include snow hydrology, arctic hydrology, remote sensing, climate science, and impacts of these on people in remote and rural communities.

Ms. Tedesche is an active member of the American Water Resources Association (AWRA), the American Geophysical Union (AGU), the American Association of University Women (AAUW), and the Arctic Institute of North America (AINA). She has won graduate student fellowships from NASA, NSF, AWRA, AINA, National Park Service, and was a US Fulbright scholar.

E-mail: metedesche@alaska.edu

Steven R. Fassnacht has a BASc, MASc, and PhD in civil engineering from the University of Waterloo in Ontario, Canada; where he focused on water resources, sediment transport, hydraulics, and hydrology.

He has worked as a Snow Hydrologist and Researcher, as well as an Assistant, Associate, and Full Professor. He is currently a Professor of Snow Hydrology at Colorado State University in Fort Collins, CO and a Visiting Professor at the Geographisches Institut of Georg-August-Universität in Göttingen, Germany. His research interests include improving our understanding of snow and cold land hydrological processes, especially considering different complexities of models.

Dr. Fassnacht has served as a scholarship committee chair at CSU, as an associate editor of Water Resources Research, on the advisory board of Cuadernos de Investigación Geográfica, and as the President of the Eastern Snow Conference. He is currently advising eight graduate students, including five PhD students and three MS students.

E-mail: steven.fassnacht@colostate.edu

Paul J. Meiman has a BS in range management and an MS in rangeland ecology and watershed management from the University of Wyoming (UW) in Laramie, WY, USA. He also has a PhD in rangeland ecosystem science from Colorado State University (CSU) in Fort Collins, CO, USA.

He has worked as a Researcher in Rangeland Management and is currently an Associate Professor of Rangeland Ecosystem Science in the Department of Forest and Rangeland Stewardship at CSU. His research interests include the ecology and management of rangelands; including invasive plants, riparian areas, and livestock grazing.

Dr. Meiman has been an advisor for many students at CSU over the years, has served as faculty advisor for the CSU Rangeland Ecology Club, won the Early Career Teaching Award from the Range Science Education Council and was recognized by the Society for Range Management as an Outstanding Young Range Professional.

E-mail: paul.meiman@colostate.edu

References

[1]
Bales R C, Molotch N P, Painter T H, Dettinger M D, Rice R, Dozier J (2006). Mountain hydrology of the western United States. Water Resour Res, 42(8): W08432
CrossRef Google scholar
[2]
Benson C S (1982). Reassessment of winter precipitation on Alaska’s Arctic slope and measurements on the flux of wind-blown snow. Geophysical Institute Report UAG R-288, University of Alaska, Fairbanks, 1–26
[3]
Blöschl G (1999). Scaling issues in snow hydrology. Hydrol Processes, 13(14–15): 2149–2175
CrossRef Google scholar
[4]
Bowling L C, Pomeroy J W, Lettenmaier D P (2004). Parameterization of blowing snow sublimation in a macroscale hydrology model. J Hydrometeorol, 5(5): 745–762
CrossRef Google scholar
[5]
Caldwell M M, Dawson T E, Richards J H (1998). Hydraulic lift: consequences of water efflux from the roots of plants. Oecologia, 113(2): 151–161
CrossRef Google scholar
[6]
Cline D W, Armstrong R, Davis R, Elder K J, Liston G E (2002). CLPX-Ground; ISASnow Depth Transects and Related Measurements. In situ data edited by M. Parsons and M.J. Brodzik. Boulder, CO: National Snow and Ice Data Center. Digital media
[7]
Cline D W, Elder K J, Bales R (1998). Scale effects in a distributed snow water equivalence and snowmelt model for mountain basins. Hydrol Processes, 12(10–11): 1527–1536
CrossRef Google scholar
[8]
Deems J S, Fassnacht S R, Elder K J (2006). Fractal distribution of snow depth from Lidar data. J Hydrometeorol, 7(2): 285–297
CrossRef Google scholar
[9]
Deems J S, Fassnacht S R, Elder K J (2008). Interannual consistency in fractal snow depth patterns at two Colorado mountain sites. J Hydrometeorol, 9(5): 977–988
CrossRef Google scholar
[10]
Deems J S, Painter T H, Finnegan D C (2013). Lidar measurement of snow depth: a review. J Glaciol, 59(215): 467–479
CrossRef Google scholar
[11]
Dickinson W T, Whiteley H R (1972). A sampling scheme for shallow snowpacks. Hydrol Sci Bull, 17(3): 247–258
CrossRef Google scholar
[12]
Doesken N J, Judson A (1996). The Snow Booklet: A Guide to the Science, Climatology, and Measurement of Snow in the United States (2nd ed.). Colorado Climate Center, Department of Atmospheric Science, Colorado State University Publications & Printing, Fort Collins, CO, 1–84
[13]
Ehleringer J R, Dawson T E (1992). Water uptake by plants: perspectives from stable isotope composition. Plant Cell Environ, 15(9): 1073–1082
CrossRef Google scholar
[14]
Elder K J, Goodbody A, Cline D W,Houser P, Liston G E, Mahrt L, Rutter N (2009a). NASA Cold Land Processes Experiment (CLPX 2002–2003): ground-based and near-surface meteorological observations. J Hydrometeorol, 10(1): 330–337
CrossRef Google scholar
[15]
Elder K J, Cline D W, Liston G E, Armstrong R (2009b). NASA Cold Land Processes Experiment (CLPX 2002–2003): field measurements of snowpack properties and soil moisture. J Hydrometeorol, 10(1): 320–329
CrossRef Google scholar
[16]
Erxleben J, Elder K J, Davis R (2002). Comparison of spatial interpolation methods for estimating snow distribution in the Colorado Rocky Mountains. Hydrol Processes, 16(18): 3627–3649
CrossRef Google scholar
[17]
Essery R L H, Pomeroy J W (2004). Vegetation and topographic control of wind-blown snow distributions in distributed and aggregated simulations for an arctic tundra basin. J Hydrometeorol, 5(5): 735–744
CrossRef Google scholar
[18]
Fassnacht S R, Deems J S (2006). Measurement sampling and scaling for deep montane snow depth data. Hydrol Processes, 20(4): 829–838
CrossRef Google scholar
[19]
Fassnacht S R, Williams M W, Corrao M V (2009). Changes in the surface roughness of snow from millimetre to metre scales. Ecol Complex, 6(3): 221–229
CrossRef Google scholar
[20]
Gilbert R O (1987). Statistical methods for environmental pollution monitoring.New York: Van Nostrand Reinhold Company, 1–336
[21]
Granger R J, Male D H (1978). Melting of a prairie snowpack. J Appl Meteorol, 17(12): 1833–1842
CrossRef Google scholar
[22]
Greene E M, Liston G E, Pielke R A Sr (1999). Simulation of above treeline snowdrift formation using a numerical snow-transport model. Cold Reg Sci Technol, 30(1): 135–144
CrossRef Google scholar
[23]
Hardy J, Davis R, Koh Y, Cline D W, Elder K J, Armstrong R, Marshall H, Painter T, Saint-Martin G C, DeRoo R, Sarabandi K, Graf T, Koike T, McDonald K (2008). NASA Cold Land Processes Experiment (CLPX 2002–2003): local scale observation site. J Hydrometeorol, 9(6): 1434–1442
CrossRef Google scholar
[24]
Hiemstra C A, Liston G E, Reiners W A (2002). Snow redistribution by wind and interactions with vegetation at upper treeline in the Medicine Bow Mountains, Wyoming, USA. Arct Antarct Alp Res, 34(3): 262–273
CrossRef Google scholar
[25]
Hiemstra C A, Liston G E, Reiners W A (2006). Observing, modelling, and validating snow redistribution by wind in a Wyoming upper treeline landscape. Ecol Modell, 197(1–2): 35–51
CrossRef Google scholar
[26]
Hutchinson B A (1965). Snow accumulation and disappearance influenced by big sagebrush. United States Department of Agriculture Forest Service Research Note RM-46, Rocky Mountain Forest and Range Experiment Station
[27]
Hyder D N, Sneva F A (1956). Herbage response to sagebrush spraying. J Range Manage, 9(1): 34–38
CrossRef Google scholar
[28]
Isaaks E H, Srivastava R M (1989). An Introduction to Applied Geostatistics.New York: Oxford Univ. Press, 1–561
[29]
Kane D L, Gieck R E, Hinzman L D (1997). Snowmelt modeling at small Alaskan Arctic watershed. J Hydrol Eng, 2(4): 204–210
CrossRef Google scholar
[30]
Kelejian H H, Prucha I R (2001). On the asymptotic distribution of the Moran I test statistic with applications. J Econom, 104: 219–257
CrossRef Google scholar
[31]
Kelly R E J, Chang A T C (2003). Development of a passive microwave global snow depth retrieval algorithm for Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) data. Radio Sci, 38(4): 8076
CrossRef Google scholar
[32]
Liston G E, Birkenheuer D L, Hiemstra C A, Cline D W, Elder K J (2008a). NASA Cold Land Processes Experiment (CLPX 2002–2003): atmospheric analyses datasets. J Hydrometeorol, 9(5): 952–956
CrossRef Google scholar
[33]
Liston G E, Hiemstra C A (2008). A simple data assimilation system for complex snow distributions (SnowAssim). J Hydrometeorol, 9(5): 989–1004
CrossRef Google scholar
[34]
Liston G E, Hiemstra C A (2011). Representing grass-and shrub-snow-atmosphere interactions in climate system models. J Clim, 24(8): 2061–2079
CrossRef Google scholar
[35]
Liston G E, Hiemstra C A, Elder K J, Cline D W (2008b). Meso-cell study area (MSA) snow distributions for the Cold Land Processes Experiment (CLPX). J Hydrometeorol, 9(5): 957–976
CrossRef Google scholar
[36]
Liston G E, Sturm M (2002). Winter precipitation patterns in arctic Alaska determined from a blowing-snow model and snow-depth observations. J Hydrometeorol, 3(6): 646–659
CrossRef Google scholar
[37]
López-Moreno J I, Fassnacht S R, Heath J T, Musselman K N, Revuelto J, Latron J, Morán-Tejeda E, Jonas T (2013). Small scale spatial variability of snow density and depth over complex alpine terrain: Implications for estimating snow water equivalent. Adv Water Resour, 55: 40–52
CrossRef Google scholar
[38]
McFadden J P, Liston G E, Sturm M, Pielke R A Sr, Chapin F S III (2001). Interactions of shrubs and snow in arctic tundra: measurements and models. In: Soil-vegetation-atmosphere Transfer Schemes and Large-scale Hydrological Models. Proceedings of an International Symposium held during the Sixth Scientific Assembly of the International Association of Hydrological Sciences (IAHS) at Maastricht, The Netherlands, 18 to 27 July 2001. IAHS, 270: 317–326
[39]
McKay G A (1968). Problems of measuring and evaluating snowcover. Proceedings of the Snow Hydrology Workshop Seminar, Fredericton, New Brunswick, Canada
[40]
Moran P A P (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1–2): 17–23
CrossRef Google scholar
[41]
Neumann R B, Cardon Z G (2012). The magnitude of hydraulic redistribution by plant roots: a review and synthesis of empirical and modeling studies. New Phytol, 194(2): 337–352
CrossRef Google scholar
[42]
Nolan M, Larsen C, Sturm M (2015). Mapping snow depth from manned aircraft on landscape scales at centimeter resolution using structure-from-motion photogrammetry. Cryosphere, 9(4): 1445–1463
CrossRef Google scholar
[43]
Ott L R, Longnecker M (2001). An Introduction to Statistical Methods and Data Analysis (5th ed.). Duxbury, Thompson Learning, Inc., 1–1152
[44]
Painter T H, Rittger K, McKenzie C, Slaughter P, Davis R E, Dozier J (2009). Retrieval of subpixel snow covered area, grain size, and albedo from MODIS. Remote Sens Environ, 113(4): 868–879
CrossRef Google scholar
[45]
Pomeroy J W, Bewley D S, Essery R L H, Hedstrom N R, Link T, Granger R J, Sicart J E, Ellis C R, Janowicz J R (2006). Shrub tundra snowmelt. Hydrol Processes, 20(4): 923–941
CrossRef Google scholar
[46]
Pomeroy J W, Gray D M (1995). Snowcover Accumulation, Relocation and Management. National Hydrology Research Institute Science Report 7, Environment Canada, Saskatoon, SK, Canada, 1–134
[47]
Pomeroy J W, Li L (2000). Prairie and Arctic areal snow cover mass balance using a blowing snow model. J Geophys Res, 105(D21): 26619–26634
CrossRef Google scholar
[48]
Ramage J M, Isacks B L (2002). Determination of melt-onset and refreeze timing on southeast Alaskan icefields using SSM/I diurnal amplitude variations. Ann Glaciol, 34(1): 391–398
CrossRef Google scholar
[49]
Schirmer M, Lehning M (2011). Persistence in intra-annual snow depth distribution: 2. Fractal analysis of snow depth development. Water Resour Res, 47: W09517
[50]
Shook K, Gray D M (1996). Small-scale spatial structure of shallow snowcovers. Hydrol Processes, 10(10): 1283–1292
CrossRef Google scholar
[51]
Sturges D L (1975). Hydrologic Relations on Undisturbed and Converted Big Sagebrush Lands: The Status of Our Knowledge. United States Department of Agriculture, Forest Service Research Paper RM-140, Rocky Mountain Forest and Range Experiment Station, 1–21
[52]
Sturges D L (1989). Response of mountain big sagebrush to induced snow accumulation. J Appl Ecol, 26(3): 1035–1041
CrossRef Google scholar
[53]
Sturm M, Holmgren J, McFadden J P, Liston G E, Chapin F S III, Racine C H (2001a). Snow-shrub interactions in Arctic tundra: a hypothesis with climatic implications. J Clim, 14(3): 336–344
CrossRef Google scholar
[54]
Sturm M, Racine C, Tape K (2001b). Increasing shrub abundance in the Arctic. Nature, 411(6837): 546–547
CrossRef Google scholar
[55]
Tape K, Sturm M, Racine C (2006). The evidence for shrub expansion in Northern Alaska and the pan-Arctic. Glob Change Biol, 12(4): 686–702
CrossRef Google scholar
[56]
Tedesco M, Kim E J, Gasiewski A, Klein M, Stankov B (2005). Analysis of multiscale radiometric data collected during the Cold Land Processes Experiment-1 (CLPX-1). Geophys Res Lett, 32(18): L18501
CrossRef Google scholar
[57]
Trujillo E, Ramirez J A, Elder K J (2007). Topographic, meteorologic, and canopy controls on the scaling characteristics of the spatial distribution of snow depth fields. Water Resour Res, 43(7): W07409
CrossRef Google scholar
[58]
Vermeire L T, Wester D B, Mitchell R B, Fuhlendorf S D (2005). Fire and grazing effects on wind erosion, soil water content, and soil temperature. J Environ Qual, 34(5): 1559–1565
CrossRef Google scholar
[59]
Von Thaden B C (2016). Spatial Accumulation Patterns of Snow Water Equivalent in the Southern Rocky Mountains. Dissertation for Master Degree. Watershed Science, Colorado State University, Fort Collins, Colorado, USA, 52pp+ 1 appendix (60 pages total)
[60]
Walker D A, Billings W D, de Molenaar J G (2001). Snow – vegetation interactions in tundra environments. In: Jones G, Bliss L, Hoham R, Pomeroy J, Stanton M, Lillie A, eds. Snow Ecology. Cambridge University Press, 1–398
[61]
Webster R, Oliver M (2001). Geostatistics for Environmental Scientists: Statistics in Practice. John Wiley and Sons, 1–217
[62]
Winkler R D, Spittlehouse D L, Golding D L (2005). Measured differences in snow accumulation and melt among clearcut, juvenile, and mature forests in southern British Columbia. Hydrol Processes, 19(1): 51–62
CrossRef Google scholar

Acknowledgements

The authors thank Dr. Christopher Hiemstra for providing the 2008 CIRA dataset, all the people who helped collect the CLPX data, and all the Colorado State University students who helped collect the WSD data. Thanks are also due to a Warner College of Natural Resources mini-grant in 2007 that provided the initial funding to start this research. Discussions and a field excursion with Dr. James R. Meiman were quite useful, and we thank him for his insight.

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