Soil moisture data as a constraint for groundwater recharge estimation

Mathias, Simon A.; Sorensen, James P.R.; Butler, Adrian P.. 2017 Soil moisture data as a constraint for groundwater recharge estimation. Journal of Hydrology, 552. 258-266. https://doi.org/10.1016/j.jhydrol.2017.06.040

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Official URL: https://doi.org/10.1016/j.jhydrol.2017.06.040

Abstract/Summary

Estimating groundwater recharge rates is important for water resource management studies. Modeling approaches to forecast groundwater recharge typically require observed historic data to assist calibration. It is generally not possible to observe groundwater recharge rates directly. Therefore, in the past, much effort has been invested to record soil moisture content (SMC) data, which can be used in a water balance calculation to estimate groundwater recharge. In this context, SMC data is measured at different depths and then typically integrated with respect to depth to obtain a single set of aggregated SMC values, which are used as an estimate of the total water stored within a given soil profile. This article seeks to investigate the value of such aggregated SMC data for conditioning groundwater recharge models in this respect. A simple modeling approach is adopted, which utilizes an emulation of Richards’ equation in conjunction with a soil texture pedotransfer function. The only unknown parameters are soil texture. Monte Carlo simulation is performed for four different SMC monitoring sites. The model is used to estimate both aggregated SMC and groundwater recharge. The impact of conditioning the model to the aggregated SMC data is then explored in terms of its ability to reduce the uncertainty associated with recharge estimation. Whilst uncertainty in soil texture can lead to significant uncertainty in groundwater recharge estimation, it is found that aggregated SMC is virtually insensitive to soil texture.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.jhydrol.2017.06.040
ISSN:	0022-1694
Additional Keywords:	GroundwaterBGS, Groundwater, Groundwater resources, Groundwater modelling
Date made live:	02 Aug 2017 14:22 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/517455

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.jhydrol.2017.06.040

ISSN:

0022-1694

Additional Keywords:

GroundwaterBGS, Groundwater, Groundwater resources, Groundwater modelling

Date made live:

02 Aug 2017 14:22 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/517455