Global sensitivity and uncertainty analysis of the AquaCrop model for maize under different irrigation and fertilizer management conditions. Issue 8 (2nd July 2020)

• Record Type: Journal Article
• Authors: Guo, Daxin; Zhao, Rongheng; Xing, Xuguang; Ma, Xiaoyi
• Is Part Of: Archives of agronomy and soil science. Volume 66:Issue 8(2020)
• Page Start: 1115
• Page End: 1133
• Publication Date: 2020-07-02
• Subjects: Crop model -- sensitive parameter -- time response outputs -- water and fertility stresses -- canopy cover -- biomass; Horticulture -- Periodicals; Soils -- Periodicals; 630.5
• DOI: 10.1080/03650340.2019.1657845
• Languages: English
• ISSNs: 0365-0340

Abstract

ABSTRACT: Crop model parameters usually vary with diverse field management and environment conditions, which hinder the model calibration. Sensitivity analysis (SA) and uncertainty analysis (UA) for model parameters and outputs are helpful for calibrating crop model under diverse conditions. A global SA and UA were used to determine the maize parameters sensitivity and outputs uncertainty of the AquaCrop model under different irrigation and fertilizer management conditions, i.e. none, slight, and moderate stress pertaining to water and fertility. The results indicated that the sensitive parameters to maximum above ground biomass (AGB) and yield differed from those to canopy cover development and AGB production (time-response outputs of the AquaCrop). The sensitive parameters should be preferentially calibrated given their strong effects on all type of model outputs, besides, the sensitive parameters to the model time-response outputs were somewhat different from those to the model non-time-response outputs. The interaction effects among parameters on the model outputs should receive more attention in the model calibration. The SA and UA results between diverse management were clearly different, and these differences between different fertility stress levels were larger. Fertility stress is a more influential factor on parameters sensitivity and outputs uncertainty than water stress in the AquaCrop model.