Transient, spatially varied groundwater recharge modeling
Article first published online: 2 AUG 2013
©2013. American Geophysical Union. All Rights Reserved.
Water Resources Research
Volume 49, Issue 8, pages 4593–4606, August 2013
How to Cite
2013), Transient, spatially varied groundwater recharge modeling, Water Resour. Res., 49, 4593–4606, doi:10.1002/wrcr.20332., and (
- Issue published online: 23 SEP 2013
- Article first published online: 2 AUG 2013
- Accepted manuscript online: 3 JUN 2013 05:45AM EST
- Manuscript Accepted: 28 MAY 2013
- Manuscript Revised: 12 FEB 2013
- Manuscript Received: 13 JUL 2012
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Canadian Water Network (CWN)
 The objective of this work is to integrate field data and modeling tools in producing temporally and spatially varying groundwater recharge in a pilot watershed in North Okanagan, Canada. The recharge modeling is undertaken by using the Richards equation based finite element code (HYDRUS-1D), ArcGIS™, ROSETTA, in situ observations of soil temperature and soil moisture, and a long-term gridded climate data. The public version of HYDUS-1D and another version with detailed freezing and thawing module are first used to simulate soil temperature, snow pack, and soil moisture over a one year experimental period. Statistical analysis of the results show both versions of HYDRUS-1D reproduce observed variables to the same degree. After evaluating model performance using field data and ROSETTA derived soil hydraulic parameters, the HYDRUS-1D code is coupled with ArcGIS™ to produce spatially and temporally varying recharge maps throughout the Deep Creek watershed. Temporal and spatial analysis of 25 years daily recharge results at various representative points across the study watershed reveal significant temporal and spatial variations; average recharge estimated at 77.8 ± 50.8 mm/year. Previous studies in the Okanagan Basin used Hydrologic Evaluation of Landfill Performance without any attempt of model performance evaluation, notwithstanding its inherent limitations. Thus, climate change impact results from this previous study and similar others, such as Jyrkama and Sykes (2007), need to be interpreted with caution.