Determination of snow water equivalent over the eastern part of Turkey using passive microwave data

Sorman A. U. , Beser O.

HYDROLOGICAL PROCESSES, vol.27, no.14, pp.1945-1958, 2013 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 27 Issue: 14
  • Publication Date: 2013
  • Doi Number: 10.1002/hyp.9267
  • Page Numbers: pp.1945-1958


Information on regional snow water equivalent (SWE) is required for the management of water generated from snowmelt. Modeling of SWE in the mountainous regions of eastern Turkey, one of the major headwaters of Euphrates-Tigris basin, has significant importance in forecasting snowmelt discharge, especially for optimum water usage. An assimilation process to produce daily SWE maps is developed based on Helsinki University of Technology (HUT) model and AMSR-E passive microwave data. The characteristics of the HUT emission model are analyzed in depth and discussed with respect to the extinction coefficient function. A new extinction coefficient function for the HUT model is proposed to suit models for snow over mountainous areas. Performance of the modified model is checked against the original, other modified cases and ground truth data covering the 2003-2007 winter periods. A new approach to calculate grain size and density is integrated inside the developed data assimilation process. An extensive validation was successfully performed by means of snow data measured at ground stations during the 2008-2010 winter periods. The root mean square error of the data set for snow depth and SWE between January and March of the 2008-2010 periods compared with the respective AMSR-E footprints indicated that errors for estimated snow depth and predicted SWE values were 16.92cm and 40.91mm, respectively, for the 3-year period. Validation results were less satisfactory for SWE less than 75.0mm and greater than 150.0mm. An underestimation for SWE greater than 150mm could not be resolved owing to the microwave signal saturation that is observed for dense snowpack. Copyright (c) 2012 John Wiley & Sons, Ltd.