4.2 Article

Hydrometeorological validation of a Canadian Regional Climate Model simulation within the Chaudiere and Chateauguay watersheds (Quebec, Canada)

Journal

CANADIAN JOURNAL OF CIVIL ENGINEERING
Volume 36, Issue 2, Pages 253-266

Publisher

CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/L08-125

Keywords

hydrometeorology; regional climate model; Canadian Regional Climate Model (CRCM); watershed; Chateauguay; Chaudiere

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This study involved regional validation of a recently developed Canadian Regional Climate Model (CRCM) simulation (version 4.1.1). Four hydrometeorological variables, minimum and maximum daily temperatures, total precipitation, and total runoff, were examined within the Chateauguay and Chaudiere watersheds, Quebec, Canada. These watersheds, located in southern Quebec, are smaller in area (2530 and 6682 km(2), respectively) than the size of watersheds usually used to validate this type of model (104-106 km(2)). The objective of the study was to evaluate if the model could reproduce data similar to field observations within these watersheds. A successful model could be used to produce reliable predictions regarding future climate change effects on watershed hydrology within any given watershed demonstrating similar climatological variables. Results show that even though the CRCM can produce reliable results, there remains a significant bias for each variable at least during one season. Analyses show that the bias for maximum temperature is not very strong (< 1 degrees C) within either of the studied watersheds. However, minimum temperature is clearly underestimated (approximate to 2 degrees C) in winter and in spring within both watersheds. Total precipitation is significantly overestimated in winter, spring and summer within the Chateauguay watershed (11%, 35%, and 30%, respectively), but for the Chaudiere watershed overestimation is less than 5%. Total runoff is strongly overestimated in both watersheds for most of the annual cycle (> 30%) and is highly variable in winter and spring. Ideally, the results of this study will be used to guide future studies on the causes of CRCM bias and ultimately lead to model improvement.

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