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Sap flow was measured, with Granier-type sensors, in a crop of field-grown water-stressed cassava (Manihot esculenta Crantz) in Ghana, West Africa. The main objective of this study was to examine the environmental control of canopy conductance (g c ) with a view to modelling the stomatal control of water transport under water-stressed condition. Weather variables measured concurrently with sap flow were: air temperature (T a ), relative humidity (RH ), wind speed (u) and solar radiation (R s ). Relationship between canopy conductance (g c ) and vapour pressure deficit (D ε ) was curvilinear while no specific pattern was observed with R s . Average diurnal g c decreased from 3.0 ± 0.6 to 0.7 ± 0.4 mm s −1 between 0730 and 2000 h local time (= GMT) each day. A Jarvis-type model, based on a set of environmental control functions, was parameterized for the cassava crop in this study. Model results demonstrated that g c was estimated with a high degree of accuracy based on R s , T a , and D ε (r 2 = 0.92; F = 809.2; P < 0.0001). D ε explained about 90% (F = 2129.7; P < 0.0001) of the variations observed in g c , whereas both R s and T a contributed about 2% of the explained variance in g c . The aerodynamic conductance (g a ) was very high compared to g c , leading to a daily average ratio g a /g c > 100 and a decoupling factor< 0.1. Cross-validation analysis revealed a consistent good performance (r 2 > 0.85) of the g c model with D ε as the only independent environmental variable.

Biochar amendment has been widely investigated, in both laboratory and field experiments and reported to improve some soil quality parameters, with consequent net positive effect on crop growth and yield. However, the use of modelling techniques to predict maize growth and yields in soils individually or co-applied with biochar and inorganic fertiliser is scanty. In this study, we used field obtained data for two growing seasons, to calibrate and validate AquaCrop model for the prediction of canopy cover (CC), grain yield and total biomass yield of maize grown in biochar amended soil and the unamended control. Treatments consist of biochar application at two rates, 0 and 20 Mg ha −1 , in combination with inorganic fertiliser at two rates, 0 and 300 kg ha −1 , under different irrigation water managements. The simulation results replicated with good accuracy the field-measured soil water, CC, grain yield and total biomass yield, increasing in this order: F 0 B 0 (Control) < F 0 B 20 (Biochar alone) < F 300 B 0 (Fertiliser alone) < F 300 B 20 (Fertiliser + Biochar). In all treatments, the coefficient of determination (R 2), modelling efficiency (EF), and the normalised root mean square error (NRMSE) for CC ranged between 0.93-0.99, 0.71-0.92, and 0.12-0.20, respectively, in both growing seasons. The NRMSE and R 2 were < 10% and > 0.88 in all treatments for grain yield and total biomass yields, indicating a good predictive ability. Therefore, modelling approach with the use of AquaCrop predicted the suppressed negative impact of drought on crop productivity in soil treated with biochar and inorganic fertiliser.