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Potentials and limitations of modelling spatio‐temporal patterns of soil moisture in a high mountain catchment using WaSiM‐ETH
Author(s) -
Rößler Ole,
Löffler Jörg
Publication year - 2010
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.7663
Subject(s) - environmental science , water content , evapotranspiration , precipitation , land cover , spatial variability , hydrology (agriculture) , moisture , soil science , snow , vegetation (pathology) , atmospheric sciences , geology , land use , geography , meteorology , geomorphology , ecology , medicine , statistics , geotechnical engineering , mathematics , pathology , biology
Soil moisture is a highly dynamic ecological variable. This dynamic is especially distinct in high mountains areas, where topography, snow cover, micro‐climate, vegetation, soil properties and land cover vary across short distances. For such areas, soil moisture modelling on a fine scale is therefore particularly challenging. We evaluated the distributed, physically based model WaSiM‐ETH with regard to its ability to model soil moisture in high mountain catchments, including spatio‐temporal patterns. The study was performed in the alpine catchment area of the Lötschen valley (160 km 2 ) in Switzerland, an area ranging from 600 to 4000 m a.s.l. The model was run for the period of 2003–2007 with high temporal (hourly) and spatial (50 m) resolution. Extensive TDR‐ and FD‐measurements conducted in 2006 and 2007 enabled the validation of the simulated soil moisture. A local sensitivity analysis indicated a dependence of soil moisture on skeleton fraction and temperature. The validation results showed that WaSiM‐ETH is able to simulate absolute soil moisture variability across different altitudes and land cover types with only a moderate accuracy (R = 0·47), whereas the soil moisture dynamic is reproduced well (R = 0·69, IoA = 0·66). High spatial variability of skeleton fraction and coarse meteorological data are the main causes for the limitation in soil moisture modelling. Nevertheless, analysing the spatio‐temporal patterns of soil moisture revealed a clear seasonal pattern that is in line with literature. We found soil moisture to be determined by liquid precipitation, snow‐melt and evapotranspiration. Greatest efforts should be laid on the exact determination of fine‐scale meteorological data and spatial skeleton estimation to improve soil moisture modelling in high mountain areas in the future. Copyright © 2010 John Wiley & Sons, Ltd.