title: Assessment of the accuracy of snow water equivalent calculation with the use of global numerical weather prediction models and SnoWE snowpack model (by the example of the Kama River basin)
metadata.name: dc.contributor.author
metadata.value: Shikhov, Andrey N.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Churiulin, Evgenii V.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Abdullin, Rinat K.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2021-06-01T16:34:25Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2021-06-01T16:34:25Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2021-03
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Shikhov, A. N., Churiulin, E. V., Abdullin, R. K. (2021). Assessment of the accuracy of snow water equivalent calculation with the use of global numerical weather prediction models and SnoWE snowpack model (by the example of the Kama River basin). Vestnik of Saint Petersburg University. Earth Sciences, 66 (1), 167–188.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/spbu07.2021.110
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/29090
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: The paper discusses the results of snow cover formation and snowmelt modeling in the Kama
  River basin (S = 507 km2) using two approaches previously developed by the authors. The
  first one is the SnoWE snowpack model developed at the Hydrometeorological Center of the
  Russian Federation and used in quasi-operational mode since 2015, and the second is a GISbased
  empirical technique which was previously implemented for the Kama River basin. Both
  methods are based on a combination of numerical weather prediction (NWP) models’ data
  with operational synoptic observations at the weather stations. The study was performed for
  the winter seasons 2018/2019 and 2019/2020. To assess the reliability of simulated snow water
  equivalent (SWE), we obtained in-situ data from 68 locations (snow survey routes) distributed
  over the entire area of the river basin. As a result of the study, the main advantages and
  limitations of the two methods for SWE calculation were identified. As for the maximum
  values of SWE, the root mean square error (RMSE) of simulated SWE ranges from 14 to 28 %
  of the average observed SWE according to in-situ data. It was found that the SnoWE model
  more reliably reproduces SWE in the lowland part of the river basin. Simultaneously, SWE
  was substantially underestimated according to the SnoWE model in the northern and mountainous
  parts of the basin. The second method provides a more realistic estimate of the spatial
  distribution of SWE over the area, as well as a higher accuracy of calculation for the northern
  part of the river basin. The main drawback of the method is the substantial overestimation of
  the intensity of snowmelt and snow sublimation. Consequently, the accuracy of SWE calculations
  sharply decreases in the spring season. SWE calculation accuracy in the winter season
  2019/2020 was substantially lower than in 2018/2019 due to frequent thaws.
metadata.lang: en_GB
metadata.name: dc.description.sponsorship
metadata.value: The study was funded by the RF President Grant Number MK-313.2020.5 and RFBR grant
  17-05-01001-а.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Earth Sciences;Volume 66; Issue 1
metadata.lang: -
metadata.name: dc.subject
metadata.value: snow cover
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: snow water equivalent
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: numerical weather prediction models
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: SnoWE snowpack cover model
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: GIS technologies
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: Kama river basin
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Assessment of the accuracy of snow water equivalent calculation with the use of global numerical weather prediction models and SnoWE snowpack model (by the example of the Kama River basin)
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 167-188.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/29090/1/167-188.pdf
resources.format: Adobe PDF
resources.size: 13 MB