Skip to main content
SpringerLink
Log in

Applicability evaluation and improvement of different snow evaporation calculation methods in the Great Xing’an mountains

  • Research Article
  • Published:
Earth Science Informatics Aims and scope Submit manuscript

Abstract

This study highlights the importance of environmental factors and resultant snow evaporation rate change in the hydrologic balance of the seasonal snow-cover forest, and suggests that modeling studies must account for seasonally dissimilar characters of the environmental factors in order to accurately predict snow evaporation. Meanwhile, the relationship between the snow evaporation rate and environmental factors in spring snowmelt was analysed from 2016 to 2018. Temperature, net radiation, vapour pressure and wind speed played important roles in snow evaporation during the snowmelt season. The Penman combination equation was improved by using multiple linear regression and variance function analysis. The Root mean square errors (RMSE) of the Improved Penman combination equation from 2016 to 2018 were 0.052, 0.057, and 0.059 mm/day, and the R2 values were 0.781, 0.749, and 0.751. The methods and data sets presented in this study can be used to develop and improve snow evaporation models to reflect the relationship between environmental factors and the snow evaporation rate, as well as the spatial and temporal variability of snow evaporation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Atlaskina K, Berninger F, de Leeuw G (2015) Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere. Cryosphere 9(5):1879–1893

    Article  Google Scholar 

  • Baldocchi DD, Meyers TP, Wilson KB (2000) Correction of eddy-covariance measurements incorporating both advective effects and density fluxes. Bound-Layer Meteorol 97(3):487–511

    Article  Google Scholar 

  • Baldocchi D, Falge E, Gu L, Olson R, Hollinger D, Running S, Anthoni P, Bernhofer C, Davis K, Evans R (2001) FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities. Bull Am Meteorol Soc 82(11):2415–2434

    Article  Google Scholar 

  • Barr A, Morgenstern K, Black T, McCaughey J, Nesic Z (2006) Surface energy balance closure by the eddy-covariance method above three boreal forest stands and implications for the measurement of the CO2 flux. Agric For Meteorol 140(1–4):322–337

    Article  Google Scholar 

  • Bartholdy J (2006) A simple model for estimating current velocity in tidal inlets: example from Grådyb in the Danish Wadden Sea. Geo-Mar Lett 26(3):133–140

    Article  Google Scholar 

  • Bernier PY, Swanson R (1993) The influence of opening size on snow evaporation in the forests of the Alberta Foothills. Can J For Res 23(2):239–244

    Article  Google Scholar 

  • Bewley D, Alila Y, Varhola A (2010) Variability of snow water equivalent and snow energetics across a large catchment subject to Mountain Pine Beetle infestation and rapid salvage logging. J Hydrol 388(3–4):464–479

    Article  Google Scholar 

  • Biederman J, Harpold A, Gochis D, Ewers B, Reed D, Papuga S, Brooks P (2014) Increased evaporation following widespread tree mortality limits streamflow response. Water Resour Res 50(7):5395–5409

    Article  Google Scholar 

  • Browne MW (2000) Cross-validation methods. J Math Psychol 44(1):108–132

    Article  Google Scholar 

  • Chen N, Guan D, Jin C, Wang A, Wu J, Yuan F (2011) Influences of snow event on energy balance over temperate meadow in dormant season based on eddy covariance measurements. J Hydrol 399(1–2):100–107

    Article  Google Scholar 

  • Cho K-R, Seok J-K (2008) Correction on current measurement errors for accurate flux estimation of AC drives at low stator frequency. IEEE Trans Ind Appl 44(2):594–603

    Article  Google Scholar 

  • Chong I-G, Jun C-H (2005) Performance of some variable selection methods when multicollinearity is present. Chemom Intell Lab Syst 78(1–2):103–112

    Article  Google Scholar 

  • Constantin J, Inclan M, Raschendorfer M (1998) The energy budget of a spruce forest: field measurements and comparison with the forest–land–atmosphere model (FLAME). J Hydrol 212:22–35

    Article  Google Scholar 

  • Davis R, Hardy J, Ni W, Woodcock C, McKenzie J, Jordan R, Li X (1997) Variation of snow cover ablation in the boreal forest: A sensitivity study on the effects of conifer canopy. J Geophys Res-Atmos 102(D24):29389–29395

    Article  Google Scholar 

  • Essery RRN, Pomeroy J et al (2009) SNOWMIP2: an evaluation of forest snow process simulations. Bull Am Meteorol Soc 90(8):1120–1135

    Article  Google Scholar 

  • Faria D, Pomeroy J, Essery R (2000) Effect of covariance between ablation and snow water equivalent on depletion of snow-covered area in a forest. Hydrol Process 14(15):2683–2695

    Article  Google Scholar 

  • Fayad A, Gascoin S, Faour G, López-Moreno JI, Drapeau L, Le Page M, Escadafal R (2017) Snow hydrology in Mediterranean mountain regions: A review. J Hydrol 551:374–396

    Article  Google Scholar 

  • Fisher JB, Baldocchi DD, Misson L, Dawson TE, Goldstein AH (2007) What the towers don’t see at night: nocturnal sap flow in trees and shrubs at two AmeriFlux sites in California. Tree Physiol 27(4):597–610

    Article  Google Scholar 

  • Fratini G, McDermitt D, Papale D (2014) Eddy-covariance flux errors due to biases in gas concentration measurements: origins, quantification and correction. Biogeosciences 11(4):1037–1051

    Article  Google Scholar 

  • Gelfan A, Pomeroy J, Kuchment L (2004) Modeling forest cover influences on snow accumulation, sublimation, and melt. J Hydrometeorol 5(5):785–803

    Article  Google Scholar 

  • Goulden ML, Munger JW, Fan SM, Daube BC, Wofsy SC (1996) Measurements of carbon sequestration by long-term eddy covariance: Methods and a critical evaluation of accuracy. Glob Change Biol 2(3):169–182

    Article  Google Scholar 

  • Hardy JP, Albert MR (1995) Snow-induced thermal variations around a single conifer tree. Hydrol Process 9(8):923–933

    Article  Google Scholar 

  • Hardy JP, Groffman PM, Fitzhugh RD, Henry KS, Welman AT, Demers JD, Fahey TJ, Driscoll CT, Tierney GL, Nolan S (2001) Snow depth manipulation and its influence on soil frost and water dynamics in a northern hardwood forest. Biogeochemistry 56(2):151–174

    Article  Google Scholar 

  • Herrero J, Polo MJ (2016) Evaposublimation from the snow in the Mediterranean mountains of Sierra Nevada (Spain). Cryosphere 10(6):2981–2998

  • Hiyama T, Strunin M, Tanaka H, Ohta T (2007) The development of local circulations around the Lena River and their effect on tower-observed energy imbalance. Hydrol Process 21(15):2038–2048

    Article  Google Scholar 

  • Högström U, Bergström H, Smedman A-S, Halldin S, Lindroth A (1989) Turbulent exchange above a pine forest, I: Fluxes and gradients. Bound-Layer Meteorol 49(1–2):197–217

    Article  Google Scholar 

  • Hood E, Williams M, Cline D (1999) Sublimation from a seasonal snowpack at a continental, mid-latitude alpine site. Hydrol Process 13(12‐13):1781–1797

    Article  Google Scholar 

  • Ireson A, Van Der Kamp G, Ferguson G, Nachshon U, Wheater H (2013) Hydrogeological processes in seasonally frozen northern latitudes: understanding, gaps and challenges. Hydrogeol J 21(1):53–66

    Article  Google Scholar 

  • Jackson SI, Prowse TD (2009) Spatial variation of snowmelt and sublimation in a high-elevation semi‐desert basin of western Canada. Hydrol Process 23(18):2611–2627

    Article  Google Scholar 

  • Kaser G (1982) Measurement of evaporation from snow. Arch Meteorol Geophys Bioclimatol Ser B 30(4):333–340

    Article  Google Scholar 

  • Kelliher F, Hollinger D, Schulze E-D, Vygodskaya N, Byers J, Hunt J, McSeveny T, Milukova I, Sogatchev A, Varlargin A (1997) Evaporation from an eastern Siberian larch forest. Agric For Meteorol 85(3–4):135–147

    Article  Google Scholar 

  • Knowles JF, Blanken PD, Williams MW, Chowanski KM (2012) Energy and surface moisture seasonally limit evaporation and sublimation from snow-free alpine tundra. Agric For Meteorol 157:106–115

    Article  Google Scholar 

  • Koivusalo H, Kokkonen T (2002) Snow processes in a forest clearing and in a coniferous forest. J Hydrol 262(1–4):145–164

    Article  Google Scholar 

  • Kokelj S, Palmer M, Lantz T, Burn CR (2017) Ground temperatures and permafrost warming from forest to tundra, Tuktoyaktuk Coastlands and Anderson Plain, NWT, Canada. Permafr Periglac Process 28(3):543–551

    Article  Google Scholar 

  • Leppänen L, Kontu A, Hannula H-R, Sjöblom H, Pulliainen J (2016) Sodankylä manual snow survey program. Geosci Inst Methods Data Syst 5(1):163–179

    Article  Google Scholar 

  • Lindroth A, Halldin S (1990) Gradient measurements with fixed and reversing temperature and humidity sensors above a thin forest. Agric For Meteorol 53(1–2):81–103

    Article  Google Scholar 

  • Ling F, Zhang T (2004) A numerical model for surface energy balance and thermal regime of the active layer and permafrost containing unfrozen water. Cold Reg Sci Technol 38(1):1–15

    Article  Google Scholar 

  • Link T, Marks D (1999) Distributed simulation of snowcover mass-and energy‐balance in the boreal forest. Hydrol Process 13(14‐15):2439–2452

    Article  Google Scholar 

  • Lundberg A, Halldin S (1994) Evaporation of intercepted snow: Analysis of governing factors. Water Resour Res 30(9):2587–2598

    Article  Google Scholar 

  • Lundberg A, Halldin S (2001) Snow measurement techniques for land-surface-atmosphere exchange studies in boreal landscapes. Theor Appl Climatol 70(1–4):215–230

    Article  Google Scholar 

  • Lundberg A, Koivusalo H (2003) Estimating winter evaporation in boreal forests with operational snow course data. Hydrol Process 17(8):1479–1493

    Article  Google Scholar 

  • MacDonald M, Pomeroy J, Pietroniro A (2010) On the importance of sublimation to an alpine snow mass balance in the Canadian Rocky Mountains. Hydrol Earth Syst Sci 14(7):1401–1415

    Article  Google Scholar 

  • MacDonald MK, Pomeroy JW, Essery RL (2018) Water and energy fluxes over northern prairies as affected by chinook winds and winter precipitation. Agric For Meteorol 248:372–385

    Article  Google Scholar 

  • Mahat V, Tarboton DG (2014) Representation of canopy snow interception, unloading and melt in a parsimonious snowmelt model. Hydrol Process 28(26):6320–6336

    Article  Google Scholar 

  • Male D, Granger R (1981) Snow surface energy exchange. Water Resour Res 17(3):609–627

    Article  Google Scholar 

  • Marks D, Winstral A, Flerchinger G, Reba M, Pomeroy J, Link T, Elder K (2008) Comparing simulated and measured sensible and latent heat fluxes over snow under a pine canopy to improve an energy balance snowmelt model. J Hydrometeorol 9(6):1506–1522

    Article  Google Scholar 

  • McCaughey J, Saxton W (1988) Energy balance storage terms in a mixed forest. Agric For Meteorol 44(1):1–18

    Article  Google Scholar 

  • Minderlein S, Menzel L (2015) Evapotranspiration and energy balance dynamics of a semi-arid mountainous steppe and shrubland site in Northern Mongolia. Environ Earth Sci 73(2):593–609

    Article  Google Scholar 

  • Mölder M, Grelle A, Lindroth A, Halldin S (1999) Flux-profile relationships over a boreal forest—roughness sublayer corrections. Agric For Meteorol 98:645–658

    Article  Google Scholar 

  • Molotch NP, Blanken PD, Williams MW, Turnipseed AA, Monson RK, Margulis SA (2007) Estimating sublimation of intercepted and sub-canopy snow using eddy covariance systems. Hydrol Process 21(12):1567–1575

    Article  Google Scholar 

  • Musselman KN, Margulis SA, Molotch NP (2013) Estimation of solar direct beam transmittance of conifer canopies from airborne LiDAR. Remote Sens Environ 136:402–415

    Article  Google Scholar 

  • Nakai Y, Sakamoto T, Terajima T, Kitamura K, Shirai T (1999) The effect of canopy-snow on the energy balance above a coniferous forest. Hydrol Process 13(14‐15):2371–2382

    Article  Google Scholar 

  • Nichols WD (1992) Energy budgets and resistances to energy transport in sparsely vegetated rangeland. Agric For Meteorol 60(3–4):221–247

    Article  Google Scholar 

  • Nordlund A, Galsgaard K (2012) In EGU General Assembly Conference Abstracts, Abbasi A, Giesen N (rds) EGU General Assembly Conference Abstracts 14, 12646

  • Ohta T, Hiyama T, Tanaka H, Kuwada T, Maximov TC, Ohata T, Fukushima Y (2001) Seasonal variation in the energy and water exchanges above and below a larch forest in eastern Siberia. Hydrol Process 15(8):1459–1476

    Article  Google Scholar 

  • Oliphant A, Grimmond C, Zutter H, Schmid H, Su H-B, Scott S, Offerle B, Randolph J, Ehman J (2004) Heat storage and energy balance fluxes for a temperate deciduous forest. Agric For Meteorol 126(3–4):185–201

    Article  Google Scholar 

  • Onuchin A, Burenina T, Shvidenko A, Guggenberger G, Musokhranova A Hydrology of Taiga Forests in High Northern Latitudes (2016) In Forest Hydrology, Processes, Management and Assessment. Amatya DM, Williams TM, Bren L, de Jong C (eds). CAB International and USDA, Wallingford, pp 254–269

  • Rasmus S, Lundell R, Saarinen T (2011) Interactions between snow, canopy, and vegetation in a boreal coniferous forest. Plant Ecolog Divers 4(1):55–65

    Article  Google Scholar 

  • Roth TR, Nolin AW (2017) Forest impacts on snow accumulation and ablation across an elevation gradient in a temperate montane environment. Hydrol Earth Syst Sci 21(11):5427–5442

    Article  Google Scholar 

  • Rutter N, Essery R, Pomeroy J, Altimir N, Andreadis K, Baker I, Barr A, Bartlett P, Boone A, Deng H (2009) Evaluation of forest snow processes models (SnowMIP2). J Geophys Res Atmos 114:D6

    Article  Google Scholar 

  • Sevruk B, Ondrás M, Chvíla B (2009) The WMO precipitation measurement intercomparisons. Atmos Res 92(3):376–380

    Article  Google Scholar 

  • Sheng H, Cai T, Li Y, Liu Y (2014) Rainfall redistribution in Larix gmelinii forest on northern of Daxing’an Mountains, Northeast of China. J Soil Water Conserv 28:101–105, (In Chinese with English abstract)

    Google Scholar 

  • Smith SL, Riseborough DW, Bonnaventure PP (2015) Eighteen year record of forest fire effects on ground thermal regimes and permafrost in the Central Mackenzie Valley, NWT, Canada. Permafr Periglac Process 26(4):289–303

    Article  Google Scholar 

  • Spittlehouse DL, Winkler RD (1996) Forest canopy effects on sample size requirements in snow accumulation and melt comparisons. In: Proceedings of the 64th Western Snow Conference, Bend, OR, April 16–18, 1996, pp 39–46

  • Stähli M, Gustafsson D (2006) Long-term investigations of the snow cover in a subalpine semi‐forested catchment. Hydrol Process 20(2):411–428

    Article  Google Scholar 

  • Steffen WL, Denmead OT (eds) (1988) Flow and transport in the natural environment: advances and applications. Springer-Verlag, New York, pp 95–127

  • Tanaka H, Hiyama T, Kobayashi N, Yabuki H, Ishii Y, Desyatkin RV, Maximov TC, Ohta T (2008) Energy balance and its closure over a young larch forest in eastern Siberia. Agric For Meteorol 148(12):1954–1967

    Article  Google Scholar 

  • Thom A, Stewart J, Oliver H, Gash J (1975) Comparison of aerodynamic and energy budget estimates of fluxes over a pine forest. Q J R Meteorol Soc 101(427):93–105

    Article  Google Scholar 

  • Valipour M (2013) Estimation of surface water supply index using snow water equivalent. Adv Agric Sci Eng Res 3(1):587–602. http://ejournal.sedinst.com/index.php/agser/article/view/244. Accessed 25 Jan 2013

  • Valipour M (2014) Application of new mass transfer formulae for computation of evapotranspiration. J Appl Water Eng Res 2(1):33–46

    Article  Google Scholar 

  • Valipour M (2015) Long-term runoff study using SARIMA and ARIMA models in the United States. Meteorol Appl 22(3):592–598

    Article  Google Scholar 

  • Van Wijk M, Bouten W (1999) Water and carbon fluxes above European coniferous forests modelled with artificial neural networks. Ecol Model 120(2–3):181–197

    Article  Google Scholar 

  • Varhola A, Coops NC, Weiler M, Moore RD (2010) Forest canopy effects on snow accumulation and ablation: An integrative review of empirical results. J Hydrol 392(3–4):219–233

    Article  Google Scholar 

  • Veatch W, Brooks P, Gustafson J, Molotch N (2009) Quantifying the effects of forest canopy cover on net snow accumulation at a continental, mid-latitude site. Ecohydrology 2(2):115–128

    Article  Google Scholar 

  • Webb RW, Fassnacht SR, Gooseff MN (2018) Hydrologic flow path development varies by aspect during spring snowmelt in complex subalpine terrain. Cryosphere 12(1):287–300

    Article  Google Scholar 

  • Wilson K, Goldstein A, Falge E, Aubinet M, Baldocchi D, Berbigier P, Bernhofer C, Ceulemans R, Dolman H, Field C (2002) Energy balance closure at FLUXNET sites. Agric For Meteorol 113(1–4):223–243

    Article  Google Scholar 

  • Winkler R, Spittlehouse D, Golding D (2005) Measured differences in snow accumulation and melt among clearcut, juvenile, and mature forests in southern British Columbia. Hydrol Process 19(1):51–62

    Article  Google Scholar 

  • Zhang Y, Ohata T, Ersi K, Tandong Y (2003) Observation and estimation of evaporation from the ground surface of the cryosphere in eastern Asia. Hydrol Process 17(6):1135–1147

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledged that Heilongjiang Mohe Forest Ecosystem Research Station provide the original data and help with fieldwork. This research was financially supported by the National Key R&D Program of China (2018YFC0507302), the National Science Foundation of China (Grant No.31971451 and 31370460) and the Doctoral Independent Innovation Fund Project (2572016AA33). The Heilongjiang Mohe Forest Ecosystem Research Station also supported this research.

Author information

Authors and Affiliations

  1. College of Forestry, Northeast Forestry University, Harbin, 150040, China

    Youwei Lin, Tijiu Cai & Cunyong Ju

  2. Academy of Forest Inventory and Planning, National Forestry and Grassland Administration, Beijing, 100714, China

    Xueqing Cui

Authors
  1. Youwei Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tijiu Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cunyong Ju
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xueqing Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

TJ.C. and YW.L. performed the experiments, analysed the data, and prepared the manuscript. CY.J. and YW.L. performed the kinetic studies, analysed the data, and prepared the figures and the manuscript.

Corresponding author

Correspondence to Tijiu Cai.

Ethics declarations

Conflict of interest

The authors declare no conflicts of interest.

Additional information

Communicated by: H. Babaie.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, Y., Cai, T., Ju, C. et al. Applicability evaluation and improvement of different snow evaporation calculation methods in the Great Xing’an mountains. Earth Sci Inform 14, 1809–1820 (2021). https://doi.org/10.1007/s12145-021-00597-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12145-021-00597-3

Keywords

Search

Navigation