A new soil-temperature module for SWAT application in regions with seasonal snow cover

摘要

Accurate estimates of soil temperature are important for quantifying hydrological and biological processes in hydrological models. Soil temperature predictions in the widely used Soil and Water Assessment Tool (SWAT) have large prediction errors when applied to regions with significant snow cover during winter. In this study, a new physically-based soil-temperature module is developed as an alternative to the empirical soil-temperature module currently used in SWAT. The physically-based module simulates soil temperature in different soil layers as a result of energy transfer between the atmosphere and soil (or snow) interface. The modified version of SWAT with the new soil-temperature module in place, introduces only three new parameters over the original soil-temperature module. Both the original and new soil-temperature modules are tested against field data from the Black Brook Watershed, a small watershed in Atlantic Canada. The results indicate that both versions of soil temperature module are able to provide acceptable predictions of temperature in different layers of the soil during non-winter seasons. However, the original module severely underestimates soil temperatures in winter (within -10 to -20 degrees C), while the new module produces results that are more consistent with field measurements (within -2 to 2 degrees C). In addition, unlike its counterpart, the new module is able to simulate freeze thaw cycles in the soil profile. Ice-water content variations in winter are reasonably simulated by the new module for different snow cover scenarios. In general, modified-SWAT improves prediction accuracy on baseflow discharge compared with the original-SWAT, due to improved estimates of soil temperature during winter. The new physically-based soil-temperature module has greatly improved the ability of SWAT to predict soil temperatures under seasonal snow cover, which is essential to the application of the model in regions like Atlantic Canada. Crown Copyright (C) 2016 Published by Elsevier B.V. All rights reserved.