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Statistical self‐similarity of spatial variations of snow cover: verification of the hypothesis and application in the snowmelt runoff generation models
Author(s) -
Kuchment L. S.,
Gelfan A. N.
Publication year - 2001
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.1032
Subject(s) - snowmelt , hydrograph , hydrometeorology , snow , hydrology (agriculture) , surface runoff , environmental science , drainage basin , structural basin , flood myth , runoff model , geology , meteorology , geography , precipitation , geomorphology , ecology , cartography , geotechnical engineering , archaeology , biology
An analysis of snow cover measurement data in a number of physiographic regions and landscapes has shown that fields of snow cover characteristics can be considered as random fields with homogeneous increments and that these fields exhibit statistical self‐similarity. A physically based distributed model of snowmelt runoff generation developed for the Upper Kolyma River basin (the catchment area is about 100 000 km 2 ) has been used to estimate the sensitivity of snowmelt dynamics over the basin and flood hydrographs to the parameterization of subgrid effects based on the hypothesis of statistical self‐similarity of the maximum snow water equivalent fields. Such parameterization of subgrid effects enables us to improve the description of snowmelt dynamics both within subgrid areas and over the entire river basin. The snowmelt flood hydrographs appear less sensitive to the self‐similarity of snow cover over subgrid areas than to the dynamics of snowmelt because of a too large catchment area of the basin under consideration. However, for certain hydrometeorological conditions and for small river basins this effect may lead to significant changes of the calculated hydrographs. Copyright © 2001 John Wiley & Sons, Ltd.