Estimating recharge from observation well hydrographs combined with meteorological data

Jean-Sébastien Gosselin, Christine Rivard, Richard Martel, Claudio Paniconi, René Lefebvre

In the proceedings of: GeoMontréal 2013: 66th Canadian Geotechnical Conference; 11th joint with IAH-CNC

Session: General Hydrogeology II

ABSTRACT: Groundwater recharge is commonly defined as the downward flow of water that reaches the water table and which is added to groundwater storage. It is one of the most important components of the water budget to be considered for sustainable groundwater management. Over the last decades, many methods have been developed and applied for groundwater recharge assessment in the fields of hydrology, agronomy, and hydrogeology, each with its strengths and weaknesses. Nonetheless, accurate quantification of natural groundwater recharge is still today a major challenge, especially in regional groundwater studies. The uncertainty associated with estimated total groundwater recharge and its spatial distribution over a study area is significant and difficult to characterize. This can in turn lead to improper policies or decisions by managers who may not be aware of these uncertainties. This issue highlights the need to improve current groundwater recharge assessment techniques in an effort to better characterize and ultimately reduce these uncertainties. The soil moisture balance (SMB) and the water-table fluctuation (WTF) methods are two recharge estimation techniques that have been extensively used due to their simplicity and to the ready availability of the data needed for their application. However, estimation of recharge fluxes with these two apparently simple methods is by no means an easy task in practice and their proper use requires a full understanding of the bases of the methods and of the study site conditions. The SMB method consists in estimating each component of the surface water budget in order to compute the resulting flow rate of water draining downward below the root zone (potential recharge). The mathematical description of the various land surface processes (ex.: evapotranspiration, runoff, snow accumulation and snow melt, rainfall interception) is usually performed using spatially averaged properties and empirical parameters whose values are often difficult to determine for a given study area. This in turn can lead to a high level of uncertainty of the computed recharge fluxes, which constitutes a major weakness of this method. The WTF method uses direct measurements of groundwater levels. It consists basically in the inverse resolution of an aquifer water budget, where recharge and water level are respectively the unknown and observed variables. This technique is sometimes difficult to apply because natural groundwater recharge is highly variable in time and because its impact on groundwater level is often blended with other processes such as root-water uptake and divergent or convergent groundwater flow. Consequently, low intensity recharge events are usually not accounted for in this method. Moreover, the method requires prior knowledge of the aquifer specific yield (Sy) local to the monitoring well. The Sy value is generally difficult to estimate and strongly controls the recharge value. This represents a major source of uncertainty, especially when the specific yield value is small, as is the case in fractured bedrock aquifers. The objective of this study is to test a technique that combines the SMB and the WTF methods to estimate recharge fluxes on a daily basis at the field scale. This approach bypasses many of the limitations of each method when used separately. The methodology consists in first computing the net infiltration flux with a daily soil moisture balance (DSMB) model at a site where an observation well is installed. This flux is subsequently substituted into a time-forward discretization of the aquifer water-budget equation in order to produce a synthetic well hydrograph. This synthetic hydrograph is then compared with the observed hydrograph and a best-fit solution is sought by adjusting the aquifer specific yield and the parameters of the DSMB model. In the final step, groundwater recharge is computed from the adjusted DSMB model. In this study, groundwater recharge was estimated with this hybrid method for a few wells in the Montérégie Est region in southern Quebec. Daily meteorological data available from 16 stations over the 2000-2012 period were used to compute the net infiltration flux for the DSMB model. Missing values in the dataset were estimated with a multiple regression analysis using data from neighbouring weather stations. Water level measurements in monitoring wells have been collected every 6 h since October 2010 with pressure transducers. For each well, a master regression curve (MRC) was established based on measured groundwater levels and was substituted into the aquifer water budget equation. Finally, the synthetic hydrograph and recharge estimates were computed in Matlab. A comparison with results obtained with the

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