Hydrology and Earth System Sciences www.hydrol-earth-syst-sci.net 1027-5606 1607-7938 14 2 2010 10.5194/hess-14-339-2010 http://www.hydrol-earth-syst-sci.net/14/339/2010/ http://www.hydrol-earth-syst-sci.net/14/339/2010/hess-14-339-2010.html http://www.hydrol-earth-syst-sci.net/14/339/2010/hess-14-339-2010.pdf 339 350 2010-02-22 Use of satellite-derived data for characterization of snow cover and simulation of snowmelt runoff through a distributed physically based model of runoff generation L. S. Kuchment P. Romanov A. N. Gelfan V. N. Demidov Water Problem Institute of the Russian Academy of Sciences, Moscow, Russia University of Maryland, College Park, MD, USA A technique of using satellite-derived data for constructing continuous snow characteristics fields for distributed snowmelt runoff simulation is presented. The satellite-derived data and the available ground-based meteorological measurements are incorporated in a physically based snowpack model. The snowpack model describes temporal changes of the snow depth, density and water equivalent (SWE), accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The remote sensing data used in the model consist of products include the daily maps of snow covered area (SCA) and SWE derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites as well as available maps of land surface temperature, surface albedo, land cover classes and tree cover fraction. The model was first calibrated against available ground-based snow measurements and then applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The satellite-derived SWE data were used for assigning initial conditions and the SCA data were used for control of snow cover simulation. The simulated spatial distributions of snow characteristics were incorporated in a distributed physically based model of runoff generation to calculate snowmelt runoff hydrographs. The presented technique was applied to a study area of approximately 200 000 km² including the Vyatka River basin with catchment area of 124 000 km². The correspondence of simulated and observed hydrographs in the Vyatka River are considered as an indicator of the accuracy of constructed fields of snow characteristics and as a measure of effectiveness of utilizing satellite-derived SWE data for runoff simulation. Andreadis, K. M. and Lettenmaier, D. P.: Assimilating remotely sensed snow observations into a macroscale hydrology model, Adv. Water Resour., 6, 872–886, 2006. Carroll, T., Cline, D., Olheiser, C., Rost, A., Nilsson, A., Fall, G., Bovitz, C., and Li, L.: NOAA national snow analysis. Proceedings of the 74th Annual Western Snow Conference, National Operational Hydrologic Remote Sensing Center, National Weather Service, NOAA, Chanhassen, Minnesota, 2–14, 2006. Chang, A. T. C. and Rango, A.: Algorithm Theoretical Basis Document for the AMSR-E Snow Water Equivalent Algorithm, Version 3.1, Greenbelt, MD, USA, NASA Goddard Space Flight Center, 49~pp., 2000. Dong, J., Walker, J. P., and Houser, P. R.: Factors affecting remotely sensed snow water equivalent uncertainty, Remote Sens. Environ., 97, 68–82, 2005. Dressler, K. A., Leavesley, G. H., Bales, R. C., and Fassnacht, S. R.: Evaluation of gridded snow water equivalent and satellite snow products for mountain basins in a hydrologic model, Hydrol. Process., 20, 673–688. 2006. Engen, G., Guneriussen, T., Overrein, Ø.: Delta-K interferometric SAR technique for snow water equivalent (SWE) retrieval, IEEE Geosci. Remote S., 1(2), 57–61, 2004. Foster, J., Hall, D., Eylander, J., Kim, E., Riggs, G., Tedesco, M., Nghiem, S., Kelly, R., Choudhury, B., and Reichle, R.: Blended visible, passive microwave and scatterometer global snow products. Proc. 64th Eastern Snow Conf., St. Johns, Newfoundland, Canada 2007, 27–36, 2007. Gelfan, A. N., Pomeroy, J. W., and Kuchment, L. S.: Modelling Forest Cover Influences on Snow Accumulation, Sublimation, and Melt, J. Hydrometeorol., 5, 785–803, 2004. Gelfan, A. N.: Physically based model of heat and water transfer in frozen soil and its parametrization by basic soil data, in: Predictions in Ungauged Basins: Promises and Progress, edited by: Sivapalan, M., Wagener, T., Uhlenbrook, S., Zehe, E., Lakshmi, V., Liang, X., Tachikawa, Y., and Kumar, P., IAHS Publication, Foz do Iguazu, Brazil, 303, 293–304, 2006. Hall, D. K., Riggs, G., Salomonson, V., DiGirolamo, N. E., and Bayr, K. J.: MODIS snow cover products, Remote Sens. Environ., 83, 181–194, 2002. Hall, D. K. and Riggs, G.: Accuracy assessment of the MODIS snow products, Hydrol. Process., 21, 1534–1547, 2007 Hansen, M., DeFries, R., Townshend, J. R. G., and Sohlberg, R.: Global land cover classification at 1-km resolution using a decision tree classifier, Int. J. Remote Sens., 21, 1331–1365, 2000. Kolberg, S., Rue, H., and Gottschalk, L.: A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model, Hydrol. Earth Syst. Sci., 10, 369–381, 2006. König, M., Winther, J. G., and Isacsson, E.: Measuring snow and glacier ice properties from satellite, Rev. Geophys., 39, 1–27, 2001. Kuchment, L. S., Demidov, V. N., and Motovilov, Yu. G.: A physically based model of the formation of snowmelt and rainfall runoff, IAHS Publication, 155, 27–36, 1986. Kuchment, L. S. and Gelfan, A. N.: Physically based model of snow accumulation and melt in a forest, Meteorology and Hydrology, 5, 85–95, 2004 (in Russian). Kuchment, L. S., Gelfan, A. N., and Demidov, V. N.: Assessments of magnitude and risk of dangerous floods on the basis of physically based models of runoff generation. In: "Dangerous phenomena at the land surface: physical mechanisms and catastrophic consequences" Published in the Institute of Geography of RAS, Moscow, Russia, 124–147, 2008 (in Russian). Kuchment, L. S., Gelfan, A. N., and Demidov, V. N.: A distributed model of runoff generation in the permafrost regions, J. Hydrol., 240, 1–22, 2000. Nosenko, O. A., Dolgih, N. A., and Nosenko, G. A.: Snow cover in the Central European Russia under the data derived from AMSR-E and SSM/I, in: "Recent problems of the land surface remote sensing from the space: physical basis, technologies of monitoring of the environment and dangerous phenomena", "Azbuka-2000", Moscow, Russia, 296–301, 2006 (in Russian.) Rodell, M. and Houser, P. R.: Updating a land surface model with MODIS-derived snow cover, J. Hydrometeorol., 5, 1064–1075, 2004. Simic, A., Fernandes, R., Brown, R., Romanov, P., and Park, W.: Validation of VEGETATION, MODIS, and GOES + SSM/I snow-cover products over Canada based on surface snow depth observations, Hydrol. Process., 18, 1089–1104, 2004.