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Simulated climate change effects on soybean production using two crop modules in RZWQM2
Author(s) -
Ma L.,
Fang Q. X.,
Sima M. W.,
Burkey K. O.,
Harmel R. D.
Publication year - 2021
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.1002/agj2.20548
Subject(s) - environmental science , irrigation , precipitation , sowing , agronomy , yield (engineering) , biomass (ecology) , climate change , crop , representative concentration pathways , crop yield , crop simulation model , baseline (sea) , climate model , biology , meteorology , ecology , materials science , metallurgy , physics , fishery
The ability to predict climate change effects on crop yield through field experiments and crop modeling is essential for developing mitigation strategies. The objective of this study was to compare two different crop modules (CROPGRO and HERMES) in the Root Zone Water Quality Model 2 (RZWQM2) for predicting climate change effects on soybean [ Glycine max (L.) Merr.] production. The modules were previously calibrated for measured temperature responses using data from a 4‐yr open‐top chamber experiment (2015–2018) in North Carolina. Both crop modules simulated similar climate change effects in terms of yield and biomass by the end of Year 2100 (2083–2099) using 40 general circulation model (GCM) projections and two Representative Concentration Pathways (RCP4.5 and RCP8.5), compared with the simulations using current baseline (2002–2018). For both modules, much greater reductions in biomass and seed yield were simulated under RCP8.5 than under RCP4.5 due to higher air temperature. In addition, both modules predicted lower variability of biomass and seed yield across these GCMs under irrigated than under rainfed conditions. CROPGRO predicted a greater positive climate change effect in response to the projected higher precipitation and increased atmospheric CO 2 (compared with baseline conditions) than HERMES. Soybean production will likely benefit more from the projected high precipitation and elevated CO 2 under rainfed conditions than under irrigated conditions. Due to much higher simulated yield under irrigation than under rainfed conditions, supplementary irrigation may be an effective mitigation strategy to maintain soybean yield; however, adjusting sowing dates appear to have little effect on soybean production.