Sensitivity Analysis of Corn Crop Growth Parameters in AquaCrop Model under Interaction of Water Stress and Nitrogen Fertilizer

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Sensitivity analysis of crop models helps researchers to have the necessary information about the reaction of crop models to changes in input parameters before calibration and application. This makes it possible to introduce the input data to the model with more awareness and increase the accuracy of the model in the calibration stage. Due to using the AquaCrop model in recent years, in this study, the sensitivity of normalized water productivity (wp*), crop transpiration, initial canopy cover (CCo), canopy growth coefficient (CGC), canopy decline coefficient (CDC) and harvest index (HI) was analyzed using a new method. For this purpose, corn yield data collected from Research Institute of Seed and Plant Breeding during 2008-2010 were used. Data consisted of four irrigation levels (W1, W2, W3 and W4 indicate supply of 120, 100, 80 and 60% of water requirement, respectively) and four nitrogen fertilizer amount (N1, N2, N3 and N4 indicate supply of 100, 80, 60 and 0% of fertilizer requirements, respectively). The results showed that the AquaCrop was most sensitive to changes in harvest index (0.65≤Spi≤1.3) and normalized water productivity (0.55≤Spi≤1.2). The lowest sensitivity (0.02≤Spi≤0.07) was observed to changes in crop canopy decrease coefficient (CDC). Sensitivity coefficients were positive for all parameters except CDC. Therefore, by increasing the CDC value, the AquaCrop suffers from underestimated error. The sensitivity coefficients for treatments N1 to N4 were equal to 0.32, 0.41, 0.46 and 0.51, respectively. These results for irrigation treatments W1 to W4 were equal to 0.36, 0.39, 0.44 and 0.5, respectively. So, with increasing water stress and fertilizer, the sensitivity of the AquaCrop model to all parameters increased. The highest sensitivity was observed in W4N4 treatment.

Language:
Persian
Published:
Water Management in Agriculture, Volume:10 Issue: 1, 2023
Pages:
175 to 190
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