Constraining recharge and groundwater models with HydEOmex soil moisture observations

Jackson, Christopher; Bianchi, Marco. 2016 Constraining recharge and groundwater models with HydEOmex soil moisture observations. HydEOmex, 13pp. (UNSPECIFIED) (Unpublished)

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Estimation of groundwater recharge has underpinned a wide variety of groundwater resource and quality assessments within the UK at a range of scales. For example, there are many studies that have quantified time‑varying recharge rates in order to model the transport of diffuse and point-source pollutants from the land surface, through groundwater systems to receptors such as rivers and abstraction boreholes (e.g. Stuart et al., 2006; Wilby et al., 2006; Jackson et al., 2007; Cuthbert et al., 2013; Ascott et al., 2016; Wang et al., 2016). Groundwater recharge estimation is, of course, central to groundwater resource evaluation and catchment management (Environment Agency, 2011), including the estimation of sustainable groundwater abstraction licences (Environment Agency, 2013), predominantly undertaken by the UK’s environmental regulators. At the scale of a UK regional aquifer (approximately 100-2500km2) estimates of recharge have generally been evaluated by constructing catchment water balances, but also by assessing the performance of regional groundwater models driven with simulated recharge time-series (Quinn et al., 2012). Catchment boundaries used to construct water balances have not always coincided with those of groundwater systems, therefore the use of regional groundwater flow models to constrain estimates of groundwater recharge has become popular within the UK (Shepley et al., 2012). Because recharge can only be measured directly at the point scale, and even then with difficulty, regional groundwater flow models have often been used as the only means to evaluate recharge estimates. However, it is not uncommon for both the parameters of recharge and groundwater flow models to be adjusted at the same time during model calibration to obtain a good “fit” to the state variables that can be measured: principally groundwater levels and river flows. Recharge models typically simulate soil drainage, or potential recharge, by conceptualising the surface infiltration, evaporation, runoff, and drainage processes of the soil store. Many different types of recharge model, of varying degrees of complexity, have been applied (e.g. Finch, 1998; Heathcote et al., 2004; Sorensen et al., 2014), most of which include a variable that describes the saturation of the soil; often expressed as a soil moisture deficit (SMD) with respect to a field capacity (FC), or as a volumetric water content. Examples in which soil water contents simulated by recharge models used to drive regional groundwater models have been compared to observations of soil moisture are difficult to identify in the literature. Studies which consider aspects of this problem include Crow et al. (2005), Brunner et al. (2007), Montzka et al. (2012), and Albergel et al. (2012), but the specific task of assimilating soil moisture observations, whether derived from instruments installed in the soil (e.g. tensiometers or neutron probes) or remotely sensed, into distributed recharge and groundwater models does not appear to have been considered. Recently new spatial datasets have become available due to the development and application of remote sensing methods to monitor soil moisture. Many of these datasets are derived from satellite remote sensing (at a resolution of ~1km), but in-catchment instruments are now also generating time-series of soil moisture at the field-scale (approximately 100m). These new datasets provide the opportunity to evaluate recharge models used to drive regional groundwater flow models, and to constrain their parameter values and outputs. In this study we investigate the use of new remote-sensed soil moisture data products to do this, and consider their value to the groundwater modelling community. We do this using very simple recharge and groundwater models calibrated and evaluated against observed soil moisture content and groundwater level data.

Item Type: Publication - Report (UNSPECIFIED)
Funders/Sponsors: NERC
Additional Keywords: GroundwaterBGS, Groundwater, Groundwater modelling
Date made live: 14 Mar 2017 11:19 +0 (UTC)

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