期刊
EXPERIMENTAL AGRICULTURE
卷 48, 期 2, 页码 252-271出版社
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0014479711001190
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- Vlaamse Interuniversitaire Raad (VLIR)
- Mekelle University
AquaCrop, the FAO water productivity model, is used as a tool to predict crop production under water limiting conditions. In the first step AquaCrop was calibrated and validated for barley (Hordeum vulgare L.). Data sets of field experiments at seven different locations in four countries (Ethiopia, Italy, Syria and Montana, USA) with different climates in different years and with five different cultivars were used for model calibration and validation. The goodness-of-fit between observed and simulated soil water content, green canopy cover, biomass and grain yield was assessed by means of the coefficient of determination (R-2), the Nash-Sutcliff efficiency (E), the index of agreement (d) and the root mean square error (RMSE). The statistical parameters indicated an adequate accuracy of simulations (validation regression of yield: R-2 = 0.95, E= 0.94, d= 0.99, RMSE= 0.34). Subsequently, sowing strategies in the semi-arid environment of northern Ethiopia were evaluated with the validated model. Dry sowing had a probability of 47% germination failure attributable to false start of the rainy season. On the other hand, delay sowing at the start of the rainy season to eliminate germinating weeds should be kept as short as possible because grain yields strongly reduce in the season due to water stress when sowing is delayed on shallow soils. This research demonstrates the ability of AquaCrop to predict accurately crop performance with only a limited set of input variables, and the robustness of the model under various environmental and climatic conditions.
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