Abstract
Predicting yield response to water is important in rainfed agriculture. The objective of this study was to calibrate and test AquaCrop for simulating yield of 3 sorghum genotypes (PAN8816, a hybrid; Macia, an open-pollinated variety; and Ujiba, a landrace) grown during the 2013/14 and 2014/15 planting seasons (early, optimal and late planting dates). Variables considered during model evaluation included canopy cover (CC), biomass (B) and yield (Y). The model was able to simulate CC ( R 2 ≥ 0.710; root mean square error (RMSE) ≤ 22.73%; Willmott’s d-index ( d ) ≥ 0.998), biomass accumulation ( R 2 ≥ 0.900; RMSE ≤ 10.45%; d ≥ 0.850), harvest index ( R 2 ≥ 0.902; RMSE ≤ 7.17%; d ≥ 0.987) and yield ( R 2 ≥ 0.945; RMSE ≤ 3.53%; d ≥ 0.783) well for all genotypes and planting dates after calibration. AquaCrop over-estimated biomass and crop yield. The relatively good simulations produced by the minimum data input calibration confirm AquaCrop’s simplicity and suitability for use in places where extensive datasets may be unavailable. Biomass and yield overestimation resulting from the use of the minimum data input calibration suggests that other parameters (water productivity, canopy sensitivity to water stress and water stress coefficient) are required to improve canopy and yield predictions for sorghum genotypes. Keywords: modelling, parameterization, minimum data input calibration, sorghum, water availability
Highlights
High seasonal rainfall variability, delays in onset and irregular distribution of rainfall, and occasional dry spells within seasons negatively impact cereal yields and household livelihoods in sub-Saharan Africa (SSA) (Fjelde and Von Uexkull, 2012)
Since AquaCrop simulates crop growth and yield response to water availability, it is important to establish a good goodness of fit between model simulated and field observed soil water content
AquaCrop simulated soil water content (R2 ≥ 0.901; root mean square error (RMSE) ≤ 13.32%; d ≥ 1.000) very well (Fig. 1), which gave confidence that other water-based crop processes were simulated based on good water availability prediction
Summary
Delays in onset and irregular distribution of rainfall, and occasional dry spells within seasons negatively impact cereal yields and household livelihoods in sub-Saharan Africa (SSA) (Fjelde and Von Uexkull, 2012). Cereal crops are a major contributor to food security and economy in arid and semi–arid regions. In SSA, a region where 95% of agriculture is rainfed (Singh et al, 2011), and arid and semi-arid areas account for 43% of total area (FAO, 2008), rainfall is a major limitation to cereal yields. Sorghum is predominantly grown in semi-arid and arid agro-ecologies of SSA, under rainfed conditions. This makes sorghum production highly susceptible to rainfall amount and distribution
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