Use of the FAO AquaCrop model in developing sowing guidelines for rainfed maize in Zimbabwe

Abstract

This paper presents a procedure in which the water-driven water productivity model AquaCrop was fine-tuned and validated for maize for the local conditions in Zimbabwe and then applied to develop sowing management options for decision support. Data from experiments of 2 seasons in Harare and from 5 other sites around Zimbabwe were used for the local calibration and validation of AquaCrop. Model parameters such as the reference harvest index (HI o ); the canopy growth coefficient (CGC); early canopy decline and normalised biomass water productivity (WP b * ) were adjusted during model calibration. Model performance was satisfactory after calibration with a Nash-Sutcliffe model efficiency parameter (EF = 0.81), RMSE = 15% and R 2 = 0.86 upon validation. To develop sowing guidelines, historical climate series from 13 meteorological stations around Zimbabwe were used to simulate maize yield for 6 consecutive sowing dates determined according to criteria applicable in Zimbabwe. Three varieties and typical shallow and deep soil types were considered in the simulation scenarios. The simulated yield was analysed by an optimisation procedure to select the optimum sowing time that maximised long-term mean yield. Results showed that highest yields depended on the climate of the site (rainfall availability), variety (length of growing cycle) and soil depth (soil water storage capacity). The late variety gave higher mean yields for all sowing dates in the maize belt. Staggered sowing is recommended as a way of combating the effects of rainfall variability and as an answer to labour constraints.

Modeling and Evaluation of AquaCrop for Maize (zea mays L.) under Full and Deficit Irrigation in Semi-Arid Tropics

“…The average grain yield of observed and simulated were 4.13 and 4.35 t ha -1 with RMSE and MAE of 0.24 and 0.35, respectively. The obtained results simulated by AquaCrop model are within acceptable range of under and over estimations and are in agreement with the results reported by Abdenipour et al, (2012), Mhizha et al (2014) and Ahmadi et al (2015) in wheat crop under similar agro-climatic conditions.…”

Global sensitivity analysis of the AquaCrop model for winter wheat under different water treatments based on the extended Fourier amplitude sensitivity test

“…The Food and Agriculture Organization (FAO) crop model to simulate yield response to water, also known as the AquaCrop model, is a crop model that is used by the FAO of the United Nations to simulate crop yield based on water input in areas susceptible to severe drought (Hsiao et al 2009;Raes et al 2009;Steduto et al 2009). The AquaCrop model has high precision in comparison with competing models; it has been used to accurately predict canopy cover (CC), biomass, yield, soil water content, water use efficiency (WUE), and water production (WP) for wheat (Shao et al 2009;Andarzian et al 2011;Mkhabela et al 2012;Iqbal et al 2014), maize (Hsiao et al 2009;Leekheng et al 2009;Stricevic et al 2011;Mhizha et al 2014), sugar beet (Stricevic et al 2011), sunflower (Stricevic et al 2011), potato (Casa et al 2013), cotton (Hussein et al 2011), rice (Maniruzzaman et al 2015), and sweet potato (Rankine et al 2014). SA must be applied to the parameters of the AquaCrop model to determine sensitive parameters because the model involves a relatively large number of parameters and is difficult to calibrate.…”

Water use of sorghum (<i>Sorghum bicolor</i> L. Moench) in response to varying planting dates evaluated under rainfed conditions

“…Early establishment and high seedling emergence for all genotypes for late planted sorghum were attributed to high cumulative rainfall 7 days after sowing and high initial soil water content at sowing. At least 25 mm of rainfall should fall within a 7-day period after sowing (Raes et al, 2004;Mhizha et al, 2014) for early and optimal emergence. Final emergence was significantly lower for Macia (57.6%), whilst other genotypes attained full establishment in response to early planting.…”