Modeling quinoa growth under saline and water-limiting conditions using SWAP-WOFOST

Abstract

Soil salinization in arid and coastal areas poses a significant threat to crop production, which is further aggravated by climate change and the over-exploitation of aquifers. Cultivation of salt and drought-tolerant crops such as quinoa represents a promising adaptation pathway for agriculture in saline soils. Quinoa (Chenopodium quinoa Willd.) is a “salt-loving” plant, known for its tolerance to drought and salinity using complex stress responses. However, available models of quinoa growth are limited, particularly under salinity stress. The objective of this study was to calibrate the crop growth, and salinity and drought stress parameters of the SWAP – WOFOST model and evaluate whether this model can represent quinoa’s stress tolerance mechanisms. Field experimental data were used from two quinoa varieties: ICBA-Q5 grown under saline conditions in Laayoune, Morocco, in 2021, and Bastille grown under rainfed, non-saline conditions in Merelbeke, Belgium, from 2018 to 2023. Calibration and parameter uncertainty was performed using the DiffeRential Evolution Adaptive Metropolis (DREAMzs) algorithm on key parameters identified via sensitivity analysis using the Morris method. The resulting crop parameters provide insights into the stress tolerance mechanisms of quinoa, including reduction of transpiration and uptake of solutes. The salinity stress function of SWAP effectively represents these tolerance mechanisms and accurately predicts the impact on yield, under arid conditions. Under Northwestern European climate, the model replicates the impact of drought stress on yield. The calibrated model offers perspectives for evaluating practices to reduce soil salinization in arid conditions and for modeling crop performance under water-limited conditions or future salinization in temperate regions.