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Numerical assessment of effective evapotranspiration from maize plots to estimate groundwater recharge in lowlands

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  • Mastrocicco, M.
  • Colombani, N.
  • Salemi, E.
  • Castaldelli, G.

Abstract

To maximize the irrigation efficiency and to protect groundwater from agrochemical pollution, two variables must be known with good accuracy: effective evapotranspiration and infiltration, especially in lowland areas were the run-off is minimal. Three different experimental plots cultivated with maize were equipped with tensiometers and soil moisture probes to monitor every day the water movement in the unsaturated zone. Other relevant parameters of the various soil layers, as hydraulic conductivity and water retention curve, were obtained in laboratory experiments, while boundary conditions, as precipitations, temperature and root growth, were obtained on site. Inverse modeling was performed using HYDRUS-1D to assess the degree of uncertainty on model parameters. Results showed a good model fit of water content and head pressure at various depths, in each site, using Penman-Monteith formula for daily potential evapotranspiration calculation, but poor fit applying the Hargreves and Turk formulas. Best performance of model fit was observed for S-shaped equation employed to simulate the root water-uptake reduction with respect to Feddes equation. The soil parameters uncertainty was limited and remained within analytical errors, thus a robust estimation of cumulative infiltration and evapotranspiration has been derived. This study points out that evapotranspiration is the most important variable in defining groundwater recharge for maize crops in lowlands.

Suggested Citation

  • Mastrocicco, M. & Colombani, N. & Salemi, E. & Castaldelli, G., 2010. "Numerical assessment of effective evapotranspiration from maize plots to estimate groundwater recharge in lowlands," Agricultural Water Management, Elsevier, vol. 97(9), pages 1389-1398, September.
    • Handle: RePEc:eee:agiwat:v:97:y:2010:i:9:p:1389-1398
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    1. Liaqat, Umar Waqas & Awan, Usman Khalid & McCabe, Matthew Francis & Choi, Minha, 2016. "A geo-informatics approach for estimating water resources management components and their interrelationships," Agricultural Water Management, Elsevier, vol. 178(C), pages 89-105.
    2. Nicolò Colombani & Micòl Mastrocicco & Beatrice Giambastiani, 2015. "Predicting Salinization Trends in a Lowland Coastal Aquifer: Comacchio (Italy)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(2), pages 603-618, January.
    3. Li, Danfeng, 2020. "Quantifying water use and groundwater recharge under flood irrigation in an arid oasis of northwestern China," Agricultural Water Management, Elsevier, vol. 240(C).

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