Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data
Adequate estimation of the spatial distribution of snowfall is critical in hydrologic modelling. However, this is a well-known problem in estimating basin-scale snowfall, especially in mountainous basins with data scarcity. This study focuses on correction and estimation of this spatial distribution...
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doaj-d0ce056344574601b982630fce7b75562020-11-24T21:06:37ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382014-02-0118274776110.5194/hess-18-747-2014Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing dataM. Shrestha0L. Wang1T. Koike2H. Tsutsui3Y. Xue4Y. Hirabayashi5Department of Civil Engineering, The University of Tokyo, Tokyo, JapanKey Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, ChinaDepartment of Civil Engineering, The University of Tokyo, Tokyo, JapanDepartment of Civil Engineering, The University of Tokyo, Tokyo, JapanDepartment of Geography and Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, USAInstitute of Engineering Innovation, The University of Tokyo, Tokyo, JapanAdequate estimation of the spatial distribution of snowfall is critical in hydrologic modelling. However, this is a well-known problem in estimating basin-scale snowfall, especially in mountainous basins with data scarcity. This study focuses on correction and estimation of this spatial distribution, which considers topographic effects within the basin. A method is proposed that optimises an altitude-based snowfall correction factor (<i>C</i><sub>fsnow</sub>). This is done through multi-objective calibration of a spatially distributed, multilayer energy and water balance-based snowmelt model (WEB-DHM-S) with observed discharge and remotely sensed snow cover data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The Shuffled Complex Evolution–University of Arizona (SCE–UA) automatic search algorithm is used to obtain the optimal value of <i>C</i><sub>fsnow</sub> for minimum cumulative error in discharge and snow cover simulations. Discharge error is quantified by Nash–Sutcliffe efficiency and relative volume deviation, and snow cover error was estimated by pixel-by-pixel analysis. The study region is the heavily snow-fed Yagisawa Basin of the Upper Tone River in northeast Japan. First, the system was applied to one snow season (2002–2003), obtaining an optimised <i>C</i><sub>fsnow</sub> of 0.0007 m<sup>−1</sup>. For validation purposes, the optimised <i>C</i><sub>fsnow</sub> was implemented to correct snowfall in 2004, 2002 and 2001. Overall, the system was effective, implying improvements in correlation of simulated versus observed discharge and snow cover. The 4 yr mean of basin-average snowfall for the corrected spatial snowfall distribution was 1160 mm (780 mm before correction). Execution of sensitivity runs against other model input and parameters indicated that <i>C</i><sub>fsnow</sub> could be affected by uncertainty in shortwave radiation and setting of the threshold air temperature parameter. Our approach is suitable to correct snowfall and estimate its distribution in poorly gauged basins, where elevation dependence of snowfall amount is strong.http://www.hydrol-earth-syst-sci.net/18/747/2014/hess-18-747-2014.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
M. Shrestha L. Wang T. Koike H. Tsutsui Y. Xue Y. Hirabayashi |
spellingShingle |
M. Shrestha L. Wang T. Koike H. Tsutsui Y. Xue Y. Hirabayashi Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data Hydrology and Earth System Sciences |
author_facet |
M. Shrestha L. Wang T. Koike H. Tsutsui Y. Xue Y. Hirabayashi |
author_sort |
M. Shrestha |
title |
Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data |
title_short |
Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data |
title_full |
Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data |
title_fullStr |
Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data |
title_full_unstemmed |
Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data |
title_sort |
correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data |
publisher |
Copernicus Publications |
series |
Hydrology and Earth System Sciences |
issn |
1027-5606 1607-7938 |
publishDate |
2014-02-01 |
description |
Adequate estimation of the spatial distribution of snowfall is critical in
hydrologic modelling. However, this is a well-known problem in estimating
basin-scale snowfall, especially in mountainous basins with data scarcity.
This study focuses on correction and estimation of this spatial
distribution, which considers topographic effects within the basin. A method
is proposed that optimises an altitude-based snowfall correction factor
(<i>C</i><sub>fsnow</sub>). This is done through multi-objective calibration of a spatially
distributed, multilayer energy and water balance-based snowmelt model
(WEB-DHM-S) with observed discharge and remotely sensed snow cover data from
the Moderate Resolution Imaging Spectroradiometer (MODIS). The Shuffled
Complex Evolution–University of Arizona (SCE–UA) automatic search algorithm is
used to obtain the optimal value of <i>C</i><sub>fsnow</sub> for minimum cumulative error
in discharge and snow cover simulations. Discharge error is quantified by
Nash–Sutcliffe efficiency and relative volume deviation, and snow cover
error was estimated by pixel-by-pixel analysis. The study region is the
heavily snow-fed Yagisawa Basin of the Upper Tone River in northeast Japan.
First, the system was applied to one snow season (2002–2003), obtaining an
optimised <i>C</i><sub>fsnow</sub> of 0.0007 m<sup>−1</sup>. For validation purposes, the
optimised <i>C</i><sub>fsnow</sub> was implemented to correct snowfall in 2004,
2002 and 2001. Overall, the system was effective, implying improvements in
correlation of simulated versus observed discharge and snow cover. The
4 yr mean of basin-average snowfall for the corrected spatial snowfall
distribution was 1160 mm (780 mm before correction). Execution of
sensitivity runs against other model input and parameters indicated that
<i>C</i><sub>fsnow</sub> could be affected by uncertainty in shortwave radiation and
setting of the threshold air temperature parameter. Our approach is suitable
to correct snowfall and estimate its distribution in poorly gauged basins,
where elevation dependence of snowfall amount is strong. |
url |
http://www.hydrol-earth-syst-sci.net/18/747/2014/hess-18-747-2014.pdf |
work_keys_str_mv |
AT mshrestha correctingbasinscalesnowfallinamountainousbasinusingadistributedsnowmeltmodelandremotesensingdata AT lwang correctingbasinscalesnowfallinamountainousbasinusingadistributedsnowmeltmodelandremotesensingdata AT tkoike correctingbasinscalesnowfallinamountainousbasinusingadistributedsnowmeltmodelandremotesensingdata AT htsutsui correctingbasinscalesnowfallinamountainousbasinusingadistributedsnowmeltmodelandremotesensingdata AT yxue correctingbasinscalesnowfallinamountainousbasinusingadistributedsnowmeltmodelandremotesensingdata AT yhirabayashi correctingbasinscalesnowfallinamountainousbasinusingadistributedsnowmeltmodelandremotesensingdata |
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