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.
This study explored the effect of soil water repellency (SWR) on soil hydrophysical properties with depth. Soils were sampled from two distinctly wettable and water repellent soil profiles at depth increments from 0–60 cm. The soils were selected because they appeared to either wet readily (wettable) or remain dry (water repellent) under field conditions. Basic soil properties (MWD, SOM, θ v) were compared to hydrophysical properties (Ks, Sw, Se, Sww, Swh, WDPT, RIc, RIm and WRCT) that characterise or are affected by water repellency. Our results showed both soil and depth affected basic and hydrophysical properties of the soils (p<0.001). Soil organic matter (SOM) was the major property responsible for water repellency at the selected depths (0–60). Water repellency changes affected moisture distribution and resulted in the upper layer (0–40 cm) of the repellent soil to be considerably drier compared to the wettable soil. The water repellent soil also had greater MWDdry and Ks over the entire 0–60 cm depth compared to the wettable soil. Various measures of sorptivity, Sw, Se, Sww, Swh, were greater through the wettable than water repellent soil profile, which was also reflected in field and dry WDPT measurements. However, the wettable soil had subcritical water repellency, so the range of data was used to compare indices of water repellency. WRCT and RIm had less variation compared to WDPT and RIc. Estimating water repellency using WRCT and RIm indicated that these indices can detect the degree of SWR and are able to better classify SWR degree of the subcritical-repellent soil from the wettable soil.