Abstract
Heat flux is important for studying interactions between atmosphere and lake. The heat exchange between air-water interfaces is one of the important ways to govern the temperature of the water surface. Heat exchange between the air-water interfaces and the surrounding environment is completed by solar radiation, conduction, and evaporation, and all these processes mainly occur at the air-water interface. Hulun Lake was the biggest lake which is also an important link and an indispensable part of the water cycle in Northeast China. This study mapped surface energy budget to better understand spatial and temporal variations in Hulun Lake in China from 2001 to 2018. Descriptive statistics were computed to build a historical time series of mean monthly heat flux at daytime and nighttime from June to September during 2001–2018. Remote sensing estimation methods we used was suitable for Hulun Lake (R2 = 0.81). At month scale, shortwave radiation and latent heat flux were decrease from June to September. However, the maximum sensible heat flux appeared in September. Net longwave radiation was the largest in August. The effective heat budget showed that Hulun Lake gained heat in the frost-free season with highest value in June (686.31 W/m2), and then steadily decreased to September (439.76 W/m2). At annual scale, net longwave radiation, sensible heat flux and latent heat flux all show significant growth trend from 2001 to 2018 (P < 0.01). Wind speed had the well correlation on sensible heat flux and latent heat flux. Water surface temperature showed the highest coefficient in sensitivity analysis.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bogard M J, Finlay K, Waiser M J et al., 2017. Effects of experimental nitrogen fertilization on planktonic metabolism and CO2 flux in a hypereutrophic hardwater lake. PLoS One, 12(12): e0188652. doi: https://doi.org/10.1371/journal.pone.0188652
Bolsenga S J, 1975. Estimating energy budget components to determine Lake Huron evaporation. Water Resources Research, 11(5): 661–666. doi: https://doi.org/10.1029/WR011i005p00661
Bonan G B, 1995. Sensitivity of a GCM simulation to inclusion of inland water surfaces. Journal of Climate, 8(11): 2691–2704. doi: https://doi.org/10.1175/1520-0442(1995)008<2691:SOAGST>2.0.CO;2
Bonnet M P, Poulin M, Devaux J, 2000. Numerical modeling of thermal stratification in a lake reservoir: methodology and case study. Aquatic Sciences, 62(2): 105–124. doi: https://doi.org/10.1007/s000270050001
Chen J Q, Li N, Liu Z L et al., 2016. Area monitoring of Namco lake in summer by high-resolution TerraSAR-X spotlight mode. Proceedings of 2016 Progress in Electromagnetic Research Symposium. Shanghai, China: IEEE, 5140–5143. doi: https://doi.org/10.1109/PIERS.2016.7735858
Cho E, Arhonditsis G B, Khim J et al., 2016. Modeling metal-sediment interaction processes: parameter sensitivity assessment and uncertainty analysis. Environmental Modelling & Software, 80: 159–174. doi: https://doi.org/10.1016/j.envsoft.2016.02.026
Cole J J, Caraco N F, Kling G W et al., 1994. Carbon dioxide supersaturation in the surface waters of lakes. Science, 265(5178): 1568–1570. doi: https://doi.org/10.1126/science.265.5178.1568
de Alcântara E H, Stech J L, Lorenzzetti J A et al., 2011. Time series analysis of water surface temperature and heat flux components in the Itumbiara Reservoir (GO), Brazil. Acta Limnologica Brasiliensia, 23(3): 245–259. doi: https://doi.org/10.1590/S2179-975X2012005000002
Dee D P, Uppala S M, Simmons A J et al., 2011. The ERA—Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656): 553–597. doi: https://doi.org/10.1002/qj.828
Edinger J E, Duttweiler D W, Geyer J C, 1968. The response of water temperatures to meteorological conditions. Water Resources Research, 4(5): 1137–1143. doi: https://doi.org/10.1029/WR004i005p01137
Goswami B N, 2004. Interdecadal change in potential predictability of the Indian summer monsoon. Geophysical Research Letters, 31(16): L16208. doi: https://doi.org/10.1029/2004GL020337
Hébert I, Dunlop E S, 2020. Temperature response in the physiology and growth of lake trout strains stocked in the Laurentian Great Lakes. Journal of Great Lakes Research, 46(2): 366–375. doi: https://doi.org/10.1016/j.jglr.2020.01.012
Henderson-Sellers B, 1986. Calculating the surface energy balance for lake and reservoir modeling: a review. Reviews of Geophysics, 24(3): 625–649. doi: https://doi.org/10.1029/RG024i003p00625
Hodges J L, Saylor J R, Kaye N B, 2016. A functional form for the diurnal variation of lake surface temperature on lake Hartwell, northwestern south Carolina. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(8): 3564–3577. doi: https://doi.org/10.1109/JSTARS.2016.2555798
Hu Z Z, 1997. Interdecadal variability of summer climate over East Asia and its association with 500 hPa height and global sea surface temperature. Journal of Geophysical Research, 102(D16): 19403–19412. doi: https://doi.org/10.1029/97JD01052
Huttunen J T, Alm J, Liikanen A et al., 2003. Fluxes of methane, carbon dioxide and nitrous oxide in boreal lakes and potential anthropogenic effects on the aquatic greenhouse gas emissions. Chemosphere, 52(3): 609–621. doi: https://doi.org/10.1016/S0045-6535(03)00243-1
Kalnay E, Kanamitsu M, Kistler R et al., 1996. The NCEP/NCAR 40-year reanalysis project. Bulletin of the American meteorological Society, 77(3): 437–472. doi: https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2
Large W G, Danabasoglu G, Doney S C et al., 1997. Sensitivity to surface forcing and boundary layer mixing in a global ocean model: annual-mean climatology. Journal of Physical Oceanography, 27(11): 2418–2447. doi: https://doi.org/10.1175/1520-0485(1997)027<2418:STSFAB>2.0.CO;2
Lerman A, Imboden D M, Gat J R, 1995. Physics and Chemistry of Lakes. 2nd ed. Berlin, Germany: Springer. doi: https://doi.org/10.1007/978-3-642-85132-2
Li Chong, Ma Wei, Ye Baisheng et al., 2006. Estimation of water evaporation and water balance in Ungauged Hulun Lake. Journal of China Hydrology, 26(5): 41–44. (in Chinese)
Liu H P, Zhang Y, Liu S H et al., 2009. Eddy covariance measurements of surface energy budget and evaporation in a cool season over southern open water in Mississippi. Journal of Geophysical Research, 114(D4): D04110. doi: https://doi.org/10.1029/2008JD010891
Liu W T, Katsaros K B, Businger J A, 1979. Bulk parameterization of air-sea exchanges of heat and water vapor including the molecular constraints at the interface. Journal of the Atmospheric Sciences, 36(9): 1722–1735. doi: https://doi.org/10.1175/1520-0469(1979)036<1722:BPOASE>2.0.CO;2
Lofgren B M, Zhu Y C, 2000. Surface energy fluxes on the Great Lakes based on satellite-observed surface temperatures 1992 to 1995. Journal of Great Lakes Research, 26(2): 305–314. doi: https://doi.org/10.1016/S0380-1330(00)70694-0
Lowe P R, 1977. An approximating polynomial for the computation of saturation vapor pressure. Journal of Applied Meteorology, 16(1): 100–103. doi: https://doi.org/10.1175/1520-0450(1977)016<0100:AAPFTC>2.0.CO;2
Mao J H, 2017. Study on the temporal and spatial pattern of achnatherum splendens community in Hulun Lake area. Proceedings of 2017 International Conference on Society Science. Atlantis Press. doi: https://doi.org/10.2991/icoss-17.2017.13
McFeeters S K, 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7): 1425–1432. doi: https://doi.org/10.1080/01431169608948714
Nordbo A, Launiainen S, Mammarella I et al., 2011. LongA, Launnergy flux measurements and energy balance over a small boreal lake using eddy covariance technique. Journal of Geophysical Research, 116(D2): D02119. doi: https://doi.org/10.1029/2010JD014542
Oesch D C, Jaquet J M, Hauser A et al., 2005. Lake surface water temperature retrieval using advanced very high resolution radiometer and Moderate Resolution Imaging Spectroradiometer data: validation and feasibility study. Journal of Geophysical Research, 110(C12): C12014. doi: https://doi.org/10.1029/2004JC002857
Oswald C J, Rouse W R, 2004. Thermal characteristics and energy balance of various-size Canadian Shield lakes in the Mackenzie River Basin. Journal of Hydrometeorology, 5(1): 129–144. doi: https://doi.org/10.1175/1525-7541(2004)005<0129:TCAEBO>2.0.CO;2
Pour H K, Choulga M, Eerola K et al., 2017. Towards improved objective analysis of lake surface water temperature in a NWP model: preliminary assessment of statistical properties. Tellus A: Dynamic Meteorology and Oceanography, 69(1): 1313025. doi: https://doi.org/10.1080/16000870.2017.1313025
Qiao B J, Zhu L P, Wang J B et al., 2019. Estimation of lake water storage and changes based on bathymetric data and altimetry data and the association with climate change in the central Tibetan Plateau. Journal of Hydrology, 578: 124052. doi: https://doi.org/10.1016/j.jhydrol.2019.124052
Reed R K, 1977. On estimating insolation over the ocean. Journal of Physical Oceanography, 7(3): 482–485. doi: https://doi.org/10.1175/1520-0485(1977)007<0482:OEIOTO>2.0.CO;2
Saltelli A, Annoni P, 2010. How to avoid a perfunctory sensitivity analysis. Environmental Modelling & Software, 25(12): 1508–1517. doi: https://doi.org/10.1016/j.envsoft.2010.04.012
Schladow S G, Pálmarsson S Ó, Steissberg T E et al., 2004. An extraordinary upwelling event in a deep thermally stratified lake. Geophysical Research Letters, 31(15): L15504. doi: https://doi.org/10.1029/2004GL020392
Sentlinger G I, Hook S J, Laval B, 2008. Sub-pixel water temperature estimation from thermal-infrared imagery using vectorized lake features. Remote Sensing of Environment, 112(4): 1678–1688. doi: https://doi.org/10.1016/j.rse.2007.08.019
Sharaf N, Fadel A, Bresciani M et al., 2019. Lake surface temperature retrieval from Landsat-8 and retrospective analysis in Karaoun Reservoir, Lebanon. Journal of Applied Remote Sensing, 13(4): 044505. doi: https://doi.org/10.1117/1.JRS.13.044505
Sturrock A M, Winter T C, Rosenberry D O, 1992. Energy budget evaporation from Williams Lake: a closed lake in north central Minnesota. Water Resources Research, 28(6): 1605–1617. doi: https://doi.org/10.1029/92WR00553
Steissberg T E, Hook S J, Schladow S G et al., 2005. Characterizing partial upwellings and surface circulation at Lake Tahoe, California-Nevada, USA with thermal infrared images. Remote sensing of environment, 99(1–2): 2–15. doi: https://doi.org/10.1029/2005GL022912
Sun X Y, Newham L T H, Croke B F W et al., 2012. Three complementary methods for sensitivity analysis of a water quality model. Environmental Modelling & Software, 37: 19–29. doi: https://doi.org/10.1016/j.envsoft.2012.04.010
Virdis S G P, Soodcharoen N, Lugliè A et al., 2020. Estimation of satellite-derived lake water surface temperatures in the western Mediterranean: integrating multi-source, multi-resolution imagery and a long-term field dataset using a time series approach. Science of the Total Environment, 707: 135567. doi: https://doi.org/10.1016/j.scitotenv.2019.135567
Wan Z M, 2008. New refinements and validation of the MODIS land-surface temperature/emissivity products. Remote Sensing of Environment, 112(1): 59–74. doi: https://doi.org/10.1016/j.rse.2006.06.026
Wang Y L, Wang L, Cheng J L et al., 2019. Recognizing crucial aquatic factors influencing greenhouse gas emissions in the eutrophication zone of Taihu Lake, China. Sustainability, 11(19): 5160. doi: https://doi.org/10.3390/su11195160
Wang Yajuan, Mi Wenbao, Wang Li et al., 2010. Study on sustainable utilization of Ningxia Xinghai Lake wetland based on assessment of water environment pollution. Journal of Agricultural Sciences, 31(4): 46–49. (in Chinese)
Webb E K, Pearman G I, Leuning R, 1980. Correction of flux measurements for density effects due to heat and water vapour transfer. Quarterly Journal of the Royal Meteorological Society, 106(447): 85–100. doi: https://doi.org/10.1002/qj.49710644707
Winter T C, Buso D C, Rosenberry D O et al., 2003. Evaporation determined by the energy-budget method for Mirror Lake, New Hampshire. Limnology and Oceanography, 48(3): 995–1009. doi: https://doi.org/10.4319/lo.2003.48.3.0995
Woolway R I, Jones I D, Maberly S C et al., 2016. Diel surface temperature range scales with lake size. PLoS One, 11(3), e0152466. doi: https://doi.org/10.1371/journal.pone.0152466
Xu L Y, Zhang P A, Fang X J et al., 2009. Multi-range fusion technique using multi-channel monitoring SST. Proceedings of the 2009 5th International Conference on Semantics, Knowledge and Grid. Zhuhai, China: IEEE, 49–53. doi: https://doi.org/10.1109/SKG.2009.35
Yang Kun, He Jie, 2018. China meteorological forcing dataset (1979–2018). National Tibetan Plateau Data Center, doi: https://doi.org/10.11888/AtmosphericPhysics.tpe.249369.file
Yang K, Yu Z Y, Luo Y et al., 2019. Spatial K, Yu Z Y, Luo Y et al., 2019. Spogical forcing dataseand its driving factors in Yunnan-Guizhou Plateau. Water Resources Research, 55(6): 4688es Re. doi: https://doi.org/10.1029/2019WR025316
Zhang G Q, Xie H J, Gao Y, 2011. Seasonal snow cover variations in the Nam Co basin of Tibetan Plateau using MODIS data. In: Proceedings of the 2011 19th International Conference on Geoinformatics. Shanghai, China: IEEE, 1–4. doi: https://doi.org/10.1109/GeoInformatics.2011.5980902
Zhang Z B, 1998. Annals of the Lake (Sequel 1). Hohhot: Inner Mongolia Cultural Publishing House.
Acknowledgement
The authors thank National Aeronautics and Space Administration (NASA) for providing MODIS LST imagery data free of charge.
Author information
Authors and Affiliations
Corresponding author
Additional information
Foundation item
Under the auspices of National Key Research and Development Program of China (No. 2016YFA0602301, 2016YFB0501502), Strategic Planning Project of the Northeast Institute of Geography and Agroecology (IGA), Chinese Academy of Sciences (No. Y6H2091001), National Forestry Science and Technology Demonstration Promotion Project (No. JLT2018-03)
Rights and permissions
About this article
Cite this article
Zhao, B., Du, J., Song, K. et al. Spatio-temporal Variation of Water Heat Flux Using MODIS Land Surface Temperature Product over Hulun Lake, China During 2001–2018. Chin. Geogr. Sci. 30, 1065–1080 (2020). https://doi.org/10.1007/s11769-020-1166-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11769-020-1166-4