Effect of temporal averaging of meteorological data on predictions of groundwater recharge

Abstract

Accurate estimates of infiltration and groundwater recharge are critical for many hydrologic, agricultural and environmental applications. Anticipated climate change in many regions of the world, especially in tropical areas, is expected to increase the frequency of high-intensity, short-duration precipitation events, which in turn will affect the groundwater recharge rate. Estimates of recharge are often obtained using monthly or even annually averaged meteorological time series data. In this study we employed the HYDRUS-1D software package to assess the sensitivity of groundwater recharge calculations to using meteorological time series of different temporal resolutions (i.e., hourly, daily, weekly, monthly and yearly averaged precipitation and potential evaporation rates). Calculations were applied to three sites in Brazil having different climatological conditions: a tropical savanna (the Cerrado), a humid subtropical area (the temperate southern part of Brazil), and a very wet tropical area (Amazonia). To simplify our current analysis, we did not consider any land use effects by ignoring root water uptake. Temporal averaging of meteorological data was found to lead to significant bias in predictions of groundwater recharge, with much greater estimated recharge rates in case of very uneven temporal rainfall distributions during the year involving distinct wet and dry seasons. For example, at the Cerrado site, using daily averaged data produced recharge rates of up to 9 times greater than using yearly averaged data. In all cases, an increase in the time of averaging of meteorological data led to lower estimates of groundwater recharge, especially at sites having coarse-textured soils. Our results show that temporal averaging limits the ability of simulations to predict deep penetration of moisture in response to precipitation, so that water remains in the upper part of the vadose zone subject to upward flow and evaporation.

Simulations of freshwater lens recharge and salt/freshwater interfaces using the HYDRUS and SWI2 packages for MODFLOW

“…The episodic nature of recharge, reported in the literature (e.g., Hunt et al, 2008;Smerdon et al, 2008), is lost when precipitation values are averaged over longer time periods. Similar conclusions on the influence of time averaging of the weather data were also presented by Batalha et al (2018). These authors found that using long-term averages of precipitation and evapotranspiration will lead to severe underestimates of the recharge rates as compared to the use of daily data.…”

“…Foussereau et al, 2001;Persson and Saifadeen, 2016;Vero et al, 2014), with results showing that using longer averaging periods (e.g., daily vs. hourly) of weather data leads to less recharge and longer solute travel times. A systematic study by Batalha et al (2018) evaluated groundwater recharge in different climatic regions of Brazil. They found that recharge rates calculated using daily climatological data were up to 9 times larger than those obtained using yearly averages.…”

Estimation of Conservative Contaminant Travel Time through Vadose Zone Based on Transient and Steady Flow Approaches

“…In this way, one obtains estimations of both water and solute fluxes at the water table on condition that detailed weather, soil and vegetation data are available as the model input. This approach is gaining increasing popularity; however, the results were shown to depend on many factors, including the time resolution of the weather data [16][17][18]. Recently, Vero et al [19] presented a comprehensive framework for estimating travel time based on simulations with the HYDRUS-1D computer code [20].…”

A comparison of methods to estimate groundwater recharge from bare soil based on data observed by a large‐scale lysimeter

“…For instance, the groundwater level in Hebei plain of northern China has a declining rate of 1 to 2 m year −1 , with a total decline of 10 to 30 m over the past decades (Lu, Jin, van Genuchten, & Wang, 2011). Accordingly, there is a need to quantitatively assess the accuracy of the methods adopted to estimate groundwater recharge under intensive human activities and climate changes (Batalha, Barbosa, Faybishenko, & van Genuchten, 2018).…”