Numerical assessment of effective evapotranspiration from maize plots to estimate groundwater recharge in lowlands
Introduction
Aquifer recharge assessment is essential to quantify water resources and to estimate contaminants flux towards aquifers (Scanlon et al., 2002). Presently, the most effective tool to quantify recharge flux is to model the unsaturated soil water dynamics; although this process faces many challenges in field conditions (Youngs, 1995). The most important are the soil heterogeneity, the development of aggregations/cracks and pore discontinuity, which causes deviations from Darcy's Law. Despite of these limitations, numerical models are more and more frequently employed to quantify soil water dynamics, often applying several simplifying assumptions to cope with these limitations. Deterministic numerical models require hydraulic conductivity and characteristic curve functions for each soil layer (Jarvis, 1994, Jacques et al., 2002, Suleiman and Ritchie, 2003, Šimunek et al., 2008): in field studies, these parameters are routinely calculated from soil physical properties, because their quantification is often difficult, time consuming and expensive (Suleiman and Ritchie, 2001). Nevertheless, a multiplicity of direct measurement methods have been developed to estimate hydraulic input parameters (Šimunek et al., 1998a, Dane and Topp, 2002, Peters and Durner, 2008). In this study an evaporative method was used to assess hydraulic parameters. Once these parameters have been characterized, other variables had to be addressed such as evapotranspiration, root growth and stress functions.
Several techniques have been developed to measure evapotranspiration: by weighting lysimeters (Gavilan et al., 2007), by field water balance equation (Lenka et al., 2009) or micrometeorological methods (Drexler et al., 2005), but these techniques are threatened to be time consuming and expensive. Evapotranspiration can also be estimated from climatic data, linking evapotranspiration with one or more climatic variables (Sharma, 1985). The performance of various equations has been assessed under a variety of climates (Allen et al., 1998, Berengena and Gavilàn, 2005). The Penman–Monteith equation is now considered the best approximation to estimate evapotranspiration over most of climates (Jensen et al., 1990). This equation is now become the United Nations Food and Agriculture Organization (FAO) standard equation to estimate evapotranspiration (Allen et al., 1998). In addition to evapotranspiration, studies on water stress on plants and roots have been performed at various scales, from microscopic to field sites and ecosystems (Passioura, 2002, Duchemin et al., 2006). These studies reveal that maize exerts a very high water demand mainly in the upper soil horizons (Lenka et al., 2009, Doorenbos and Pruitt, 1977) and that an important variable is the plants stress function due to water deficit and salinity stress (Maas, 1986, Katerji et al., 2000). There is a close connection between groundwater depth and crop evapotranspiration, in fact plants can use shallow groundwater, if present during the growing season, which can improve or threaten crop performance as recently demonstrated (Nosetto et al., 2009).
To simulate the abovementioned processes, numerical models have often been implemented and employed in the recent past (Azzaroli Bleken et al., 2009, Lopez-Cedron et al., 2005). Overall, the model accuracy depends on the accuracy of the input data and on the assumptions made to simplify the complex modeled environment (Panigrahi and Panda, 2003). Here residuals, i.e. differences between simulated and measured values, were used to evaluate the accuracy of each model run. The most common statistical tools, used to compute model accuracy are the average mean residual error and the root-mean square residual error (Whitmore, 1991). These statistics were used in this work to assess the effect of different potential evapotranspiration (PET) formulas and root water-uptake reduction functions on actual groundwater recharge in the Ferrara province, an area located in the Po Plain lowlands, characterized by a flat topography and by a temperate humid climate. The main goal of this study were to assess whether simple approaches to calculate the PET, like Hargreves and Turk ones, can substitute complex ones like Penman–Monteith and to assess the variability of the groundwater recharge estimated with different PET formulas. The same assessment was performed for root water-uptake reduction functions. In addition, simulations were run with minimum and maximum observed saturated hydraulic conductivities, to quantify its influence on groundwater recharge flux. To achieve these aims, three field sites consisting of different soils representative of the Po Plain lowlands were monitored for 400 days and modeled with HYDRUS-1D.
Section snippets
Field sites characterization and setup
Po Plain lowlands are intensively farmed due to the flat topography and to the abundance of surface water for irrigation; the primary land use is maize cropping. In the study area, located in Ferrara province (Italy) at an altitude ranging from 5 to −3 m above sea level, three sites (named SAP, CCR and MEZ) were selected to monitor and model the water movement in the unsaturated zone. For the research it was chosen a medium maturing maize hybrid (Zea mays L., FAO 500, 125 days), commonly
Water retention curves
The retention curves for the upper and lower soil horizons in each site were satisfactorily modeled, in fact the calculated soil water content and its corresponding pressure head mimicked the measured ones (Fig. 4).
Since water content was measured in triplicates soil cores a quite large variance was observed for some samples, as can be seen from the vertical error bars in Fig. 4. In both the upper and lower layers of SAP a similar retention curve can be observed even if the lower layer shows
Conclusions
Numerical models of unsaturated flow in cultivated maize field with different soils were successfully calibrated using laboratory derived parameters, PET calculated with Penman–Monteith formula and the S-shaped stress reduction formula. A comparative analysis leaded to exclude simple approaches to calculate PET such as Hargreaves or Turk ones, due to the worsening of model fit for every field site investigated.
In addition it was confirmed that water stress reduction was important in all field
Acknowledgements
Dr. Fabio Vincenzi Dr. Umberto Tessari and Dr. Corinne Corbau are acknowledged for their technical and scientific support. The Emilia–Romagna ARPA SIMC is acknowledge for the meteorological data and the Servizio Geologico Sismico e dei Suoli of Emilia-Romagna region is acknowledge for the pedological classification. The work presented in this paper was made possible and financially supported by AGRI-UNIFE and ENVIREN laboratory, respectively under Contratto di Programma (Delib. CIPEn̊ 202) and
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