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a CIHEAM—Mediterranean Agronomic Institute of Bari, Via Ceglie 9, 70010, Valenzano (BA), Italy
b Istituto per i Sistemi Agricoli e Forestali del Mediterraneo, CNR-ISAFoM, Via Patacca 85, 80056, Ercolano (NA), Italy
c Dipartimento di Scienze delle Produzioni Vegetali, Univ. degli Studi di Bari, Via Amendola 165/A, Bari, Italy
d Washington State Univ., Pullman, WA 99164-6120, USA
e FAO, AGLW, Viale delle Terme di Caracalla, 00153, Rome, Italy
* Corresponding Author (rossella.albrizio{at}cnr.it).
This work compares the performance of AquaCrop, a crop simulation model developed by FAO, with that of two well established models, CropSyst and WOFOST, in simulating sunflower (Helianthus annuus L.) growth under different water regimes in a Mediterranean environment. The models differ in the level of complexity describing crop development, in the main growth modules driving the simulation of biomass growth, and in the number of input parameters. AquaCrop is exclusively based on the water-driven growth module, in that transpiration is converted into biomass through a water productivity (WP) parameter; Cropsyst is based on both water and radiation driven modules, while WOFOST simulates crop growth using a carbon driven approach and fraction of intercepted radiation. The data used in the analysis were obtained in field experiments with hybrid Sanbro_MR, performed in a typical Mediterranean area of Southern Italy in 2005 and 2007. The models were calibrated on data from a full irrigation treatment in 2007, and were validated on a full irrigation treatment in 2005 and several deficit irrigation (DI) treatments, including regulated deficit irrigation (RDI) and rain-fed (RF) conditions. Although AquaCrop required less input information than CropSyst and WOFOST, it performed similarly to them in simulating both biomass and yield at harvesting. The use of different numbers of parameters and crop growth modules by the tested models did not influence substantially the simulation results. Therefore, for management purposes and in conditions of limited input information, the use of simpler models should be encouraged.
Abbreviations: DI, deficit irrigation ETo, reference evapotranspiration FI, full irrigation HI, harvest index LAI, leaf area index RDI, regulated deficit irrigation RF, rain fed RUE, radiation use efficiency VPD, vapor pressure deficit WP, water productivity
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Received for publication May 15, 2008.
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