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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2016, Vol. 13, No. 4, pp. 29-41

Modeling the spatial distribution of snow cover on a large catchment area using satellite data

S.V. Pyankov 1 , A.N. Shikhov 1 
1 Perm State National Research University, Perm, Russia
Accepted: 24.08.2016
DOI: 10.21046/2070-7401-2016-13-6-29-41
The article describes the method of snow water equivalent estimation, on the basis of combining ground-based and satellite observations data, and short-term precipitation forecasts of mesoscale atmospheric WRF model. The method was tested on the three winter seasons of 2012−2015. We used satellite data of the underlying surface (the actual vegetation types map and leaf area index) to calculate the snowmelt intensity and snow evaporation on the catchment area. This allowed us to take into account the influence of landscape conditions on snow accumulation and snowmelt processes. The GIS-based modeling provided reliable and highly detailed maps of the snow cover distribution with high spatial resolution.
Validation of simulation results was performed by comparing the actual and estimated snow water equivalents and snow covered area. Snow covered area was estimated using MODIS satellite data. The algorithm for determining snow covered area by MODIS data (ATBD-MOD 10) was adapted to the conditions of the studied catchment. As a result, we eliminated errors occurring at creating the snow cover mask on forested areas.
In general, the proposed method provides satisfactory calculation results of maximum snow water equivalent. The calculation accuracy is somewhat reduced during the spring snowmelt. Snow covered area is simulated with a higher reliability than the snow water equivalent. The differences in the simulated and actual snow water equivalents are caused by overestimation of precipitation amount by the WRF model and unrepresentative snow survey data.
Keywords: snow cover, snow accumulation, snowmelt, snow water equivalent, the WRF model, MODIS data
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References:

  1. Burakov D.A., Gordeev I.N., Romas'ko V.Yu., Ispol'zovanie sputnikovoi informatsii dlya otsenki dinamiki snegovogo pokrytiya v gidrologo-matematicheskoi modeli stoka vesennego polovod'ya na primere basseina Sayano-Shushenskoi GES (Using satellite data to assessment of snow cover dynamics in the hydrological model of spring flood formation on example of the Sayano-Shushenskaya HPP catchment), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2010, Vol. 7, No. 2. pp. 113–121.
  2. “Vnedrit' avtomatizirovannye tekhnologii rascheta pritoka vody v vodokhranilishcha Sibirskikh GES na osnove nazemnoi i sputnikovoi informatsii srednego razresheniya. Razrabotat' metodiki prognoza maksimal'nykh urovnei vody na zatoroopasnykh uchastkakh rek Sibiri” ( “Implement automated technology for calculating the water inflow in the reservoir Siberian hydroelectric power station on the basis of terrestrial and satellite data of medium resolution. Develop the methods of forecast maximum water level in the places of ice jams occurrence on the Siberian rivers”), Roshydromet science project report, responsible executive D.A. Burakov, Krasnoyarsk, 2007, 138 p.
  3. Gordeev I.N., Raschet dinamiki al'bedo snezhnogo pokrova v period snegotayaniya v basseine reki Enisei (Simulation of the dynamics of snow albedo during the snowmelt in the basin of the Yenisey river), Kriosfera Zemli, 2013, Vol. 17, No. 1, pp. 47–50.
  4. Kalinin V.G., P'yankov S.V., Gidrologicheskaya geoinformatsionnaya sistema “Bassein Votkinskogo vodokhranilishcha” (Hydrological geoinformation system “Basin of Votkinsk reservoir”), Meteorologiya i gidrologiya, 2002, No. 5, pp. 95–100.
  5. Kalinin N.A., Shikhov A.N., Sviyazov E.M., Modelirovanie protsessov snegonakopleniya i snegotayaniya na vodosbore Votkinskogo vodokhranilishcha s ispol'zovaniem modeli WRF–ARW (Modeling of processes of snow accumulation and snowmelt on a Votkinsk reservoir catchment area using the WRF-ARW model), Meteorologiya i gidrologiya, 2015, No. 11, pp. 57–68.
  6. Karpechko Yu.V., Bondarik N.L., Gidrologicheskaya rol' lesokhozyaistvennykh i lesopromyshlennykh rabot v taezhnoi zone Evropeiskogo Severa Rossii (The hydrological role of agricultural and timber activities in the taiga zone of the European North of Russia), Petrozavodsk, Karel'skii nauchnyi tsentr RAN, 2010, 225 p.
  7. Kuz'min P.P. Protsess tayaniya snezhnogo pokrova (The process of snowmelt), Leningrad, Gidrometeoizdat, 1961, 346 p.
  8. Nosenko A.A., Dolgikh N.A., Nosenko G.A., Snezhnyi pokrov tsentra Evropeiskoi chasti Rossii po dannym AMSR-E i SSM/I (Snow cover of the center of the European part of Russia, according to the AMSR-E and SSM / I data), Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2006, Vol. 3, No. 1, pp. 296–301.
  9. P'yankov S.V., Shikhov A.N., Opasnye gidrometeorologicheskie yavleniya: rezhim, monitoring, prognoz (The hazardous hydrometeorological phenomena: regime, monitoring and forecasting), Perm. gos. nats. issl. un–t, Perm', Izd–vo OOO «Raritet–Perm'», 2014, 296 p.
  10. Shutov V.A., Metody analiza raznomasshtabnoi prostranstvennoi izmenchivosti snegozapasov (Methods of analysis of multiscale spatial variability of snow water equivalent), Izvestiya RAN, Seriya geogr, 1998, No. 1, pp. 122–132.
  11. Shutov V.A., Kalyuzhnyi I.L., Analiz prostranstvennogo raspredeleniya zimnikh osadkov i snegozapasov v basseine r. Beloi (Analysis of the spatial distribution of winter precipitation and snow water equivalent in the White river basin), Meteorologiya i gidrologiya, 1997, No. 1, pp. 105–114.
  12. Shikhov A.N., Sviyazov E.M., Otsenka summ osadkov za kholodnyi period na Zapadnom Urale s pomoshch'yu modeli WRF (Evaluation of precipitation during the cold period in the Western Urals using the WRF model), Geograficheskii vestnik, 2015, No. 3, pp. 67–74.
  13. Hall D.K., Riggs G.A., Salomonson V.V., Algorithm Theoretical Basis Document for the MODIS Snow and Sea Ice-Mapping Algorithms, 2001, 45 p.
  14. Kuchment L.S., Gelfan A.N., Demidov V.N., A distributed model of runoff generation in the permafrost regions, Journal of Hydrology, 2000, Vol. 240, No. 1–2, pp. 1–22.
  15. Kuchment L.S., Romanov P.Ju., Gelfan A.N., Demidov V.N., Use of satellite-derived data for characterization of snow cover and simulation of snowmelt runoff through a distributed physically based model of runoff generation, Hydrology and Earth system science, 2010, Vol. 14, No. 2, pp. 339–350.
  16. Melloh R.A., Hardy J.P., Bailey R.N, Hall T.J., An efficient snow albedo model for the open and sub-canopy, Hydrological Processes, 2002, Vol. 16, No. 18, pp. 3571–3584.
  17. Myneni R.B., Hoffman S., Knyazikhin Y., Privette J.L., Glassy J., Tian Y., Wang Y., Song X., Zhang Y., Smith G.R., Lotsch A., Friedl M., Morisette J.T., Votava P., Nemani R.R., Running S.W., Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data, Remote Sensing of Environment, 2002, Vol. 83, No. 1–2, pp. 214–231.
  18. Pomeroy J.W., Gray D.M., Shook K.R., Toth B., Essery R.L., Pietroniro A., Hedstrom N., An evaluation of snow accumulation and ablation processes for land surface modelling, Hydrological Processes, 1998, Vol. 12, No. 15, pp. 2339–2367.
  19. Tarboton D.G., Luce C.H., Utah energy balance snow accumulation and melt model (UEB): Computer model technical description and user’s guide, Utah Water Research Laboratory and USDA Forest Service Intermountain Research Station, Logan, Utah, 1996, 64 p.
  20. Verbunt M., Zappa M., Gurtz J., Kaufmann P., Verification of a coupled hydrometeorological modelling approach for alpine tributaries in the Rhine basin, Journal of Hydrology, 2006, Vol. 324, No. 1–4, pp. 224–238.
  21. Wilson, J.P., Gallant, J.C. (Eds.), Terrain analysis - principles and applications, New York, John Wiley & Sons, 2000, 520 pp.
  22. Zhao Q., Liu Z., Ye B., Qin Y., Wei Z., Fang S., A snowmelt runoff forecasting model coupling WRF and DHSVM, Hydrology and Earth Systems sciences, 2009, Vol. 13, No. 10, pp. 1897–1906.