AquaCrop model-based sensitivity analysis of soil salinity dynamics and productivity under climate change in sandy-layered farmland

Abstract

To improve the simulation accuracy and efficiency of crop water models in semi-arid regions and considering climate change, we conducted a sensitivity analysis of the AquaCrop model crop parameters for maize (Zea mays) based on field monitoring data from 2020 to 2021 in the Hetao Irrigation District, China. We simulated soil water and salt dynamics, crop growth, water consumption, and final yield under climate change conditions. Non-conservative parameters, such as the crop growth coefficient (CGC) and maximum effective rooting depth (Zx), significantly influenced soil water content and salt profile sensitivity. Zx was highly sensitive to soil salt content. For maize biomass and yield, maximum canopy cover (CCx) and CGC consistently showed high sensitivity. The standard crop transpiration coefficient (KcTr,x) had a significant impact on yield. Water productivity (WPET) and harvest index (HI) were mainly sensitive to CCx, KcTr,x, normalized water productivity (WP*), and reference HI (HI0). The model simulations, calibrated with these sensitive parameters, indicated that under future climate change scenarios, maize yield is projected to increase by approximately 19 % by mid-21st century due to elevated CO2 concentrations and water productivity increasing by 22–27 %. Soil salinity is expected to rise by 0.2 t ha−1 under high-emission scenarios, indicating that the challenge of soil salinization will become more severe. This study provides scientific evidence for developing agricultural management strategies to adapt to climate change, with the aim of enhancing crop yield and water-use efficiency, thus promoting sustainable agricultural development.

Keywords

• salinization
• parameter sensitivity analysis
• sand layer soil
• climate change
• soil water-salt balance
• crop water productivity