Improving the cotton simulation model, GOSSYM, for soil, photosynthesis, and transpiration processes

Authors

Sahila Beegum, University of Nebraska-Lincoln, USDA-ARSFollow
Dennis Timlin, USDA-ARS
Kambham Raja Reddy, Mississippi State University
Vangimalla Reddy, USDA-ARS
Wenguang Sun, University of Nebraska-Lincoln, USDA-ARS
Zhuangji Wang, USDA-ARS
David Fleisher, USDA-ARS, University of Maryland
Chittaranjan Ray, University of Nebraska - LincolnFollow

Date of this Version

5-5-2023

Citation

Scientific Reports | (2023) 13:7314 | https://doi.org/10.1038/s41598-023-34378-3

Comments

Open access.

Abstract

GOSSYM, a mechanistic, process-level cotton crop simulation model, has a two-dimensional (2D) gridded soil model called Rhizos that simulates the below-ground processes daily. Water movement is based on gradients of water content and not hydraulic heads. In GOSSYM, photosynthesis is calculated using a daily empirical light response function that requires calibration for response to elevated carbon dioxide ( CO₂). This report discusses improvements made to the GOSSYM model for soil, photosynthesis, and transpiration processes. GOSSYM’s predictions of below-ground processes using Rhizos are improved by replacing it with 2DSOIL, a mechanistic 2D finite element soil process model. The photosynthesis and transpiration model in GOSSYM is replaced with a Farquhar biochemical model and Ball-Berry leaf energy balance model. The newly developed model (modified GOSSYM) is evaluated using field-scale and experimental data from SPAR (soil–plant–atmosphereresearch) chambers. Modified GOSSYM better predicted net photosynthesis (root mean square error (RMSE) 25.5 versus 45.2 g CO2 m⁻² day⁻¹; index of agreement (IA) 0.89 versus 0.76) and transpiration (RMSE 3.3 versus 13.7 L m⁻² day⁻¹; IA 0.92 versus 0.14) and improved the yield prediction by 6.0%. Modified GOSSYM improved the simulation of soil, photosynthesis, and transpiration processes, thereby improving the predictive ability of cotton crop growth and development.