Evaluating MODIS snow products for modelling snowmelt runoff: Case study of the Rio Grande headwaters |
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| Institution: | 1. Department of Geography, University of Oviedo, Oviedo, Spain;2. Centre for Geographical Studies, Institute of Geography and Spatial Planning, Universidade de Lisboa, Lisbon, Portugal;3. Department of Geography, Masaryk University, Brno, Czech Republic;1. Finnish Environment Institute, Finland;2. Finnish Meteorological Institute, Finland;3. ENVEO IT GmbH, Austria;4. Environment Canada, Canada;1. Department of Forest Resources Management, University of British Columbia, 2424 Mail Mall, Vancouver, BC V6T 1Z4, Canada;2. fRI Research, Box 6330, Hinton, AB T7V 1X6, Canada;3. Department of Geography, University of British Columbia, 1984 West Mall, Vancouver, BC V6T 1Z2, Canada;1. Department of Geography, University of Zurich, 8057 Zurich, Switzerland;2. Institute of Geographical Information Systems (IGIS), National University of Sciences and Technology (NUST), Islamabad, Pakistan;3. Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan |
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| Abstract: | Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM) and in other models for simulating discharge from snowmelt. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM + ) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and may not always provide sufficient cloud-free dates. The coarser spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) offers better temporal resolution and in cloudy years, MODIS data offer the best alternative for mapping snow cover when finer spatial resolution data are unavailable. However, MODIS’ coarse spatial resolution (500 m) can obscure fine spatial patterning in snow cover and some MODIS products are not sensitive to end-of-season snow cover. In this study, we aimed to test MODIS snow products for use in simulating snowmelt runoff from smaller headwater basins by a) comparing maps of TM and MODIS-based SCA and b) determining how SRM streamflow simulations are changed by the different estimates of seasonal snow depletion. We compared gridded MODIS snow products (Collection 5 MOD10A1 fractional and binary SCA; SCA derived from Collection 6 MOD10A1 Normalised Difference Snow Index (NDSI) Snow Cover), and the MODIS Snow Covered-Area and Grain size retrieval (MODSCAG) canopy-corrected fractional SCA (SCAMG), with reference SCA maps (SCAREF) generated from binary classification of TM imagery. SCAMG showed strong agreement with SCAREF; excluding true negatives (where both methods agreed no snow was present) the median percent difference between SCAREF and SCAMG ranged between ?2.4% and 4.7%. We simulated runoff for each of the four study years using SRM populated with and calibrated for snow depletion curves derived from SCAREF. We then substituted in each of the MODIS-derived depletion curves. With efficiency coefficients ranging between 0.73 and 0.93, SRM simulation results from the SCAMG runs yielded the best results of all the MODIS products and only slightly underestimated discharge volume (between 7 and 11% of measured annual discharge). SRM simulations that used SCA derived from Collection 6 NDSI Snow Cover also yielded promising results, with efficiency coefficients ranging between 0.73 and 0.91.In conclusion, we recommend that when simulating snowmelt runoff from small basins (<4000 km2) with SRM, we recommend that users select either canopy-corrected MODSCAG or create their own site-specific products from the Collection 6 MOD10A1 NDSI. |
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| Keywords: | MODIS snow products MOD10A1 MODSCAG Snow covered area Snowmelt Runoff Model |
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