Articles | Volume 18, issue 12
https://doi.org/10.5194/gmd-18-3799-2025
https://doi.org/10.5194/gmd-18-3799-2025
Development and technical paper
 | 
27 Jun 2025
Development and technical paper |  | 27 Jun 2025

Process-based modeling framework for sustainable irrigation management at the regional scale: integrating rice production, water use, and greenhouse gas emissions

Yan Bo, Hao Liang, Tao Li, and Feng Zhou

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Cited articles

Arenas-Calle, L., Sherpa, S., Rossiter, D., Nayak, H., Urfels, A., Kritee, K., Poonia, S., Singh, D. K., Choudhary, A., Dubey, R., Kumar, V., Nayak, A. K., and McDonald, A.: Hydrologic variability governs GHG emissions in rice-based cropping systems of Eastern India, Agr. Water Manage., 301, 108931, https://doi.org/10.1016/j.agwat.2024.108931, 2024. 
Balaine, N., Carrijo, D. R., Adviento-Borbe, M. A., and Linquist, B.: Greenhouse Gases from Irrigated Rice Systems under Varying Severity of Alternate-Wetting and Drying Irrigation, Soil Sci. Soc. Am. J., 83, 1533–1541, https://doi.org/10.2136/sssaj2019.04.0113, 2019. 
Bo, Y.: Codes for running WHCNS to simulate rice yield, irrigation water use, methane and nitrous oxide, figshare [code], https://figshare.com/s/139f3ad8a70faa99724d (last access: 25 January 2025), 2025. 
Bo, Y., Jägermeyr, J., Yin, Z., Jiang, Y., Xu, J., Liang, H., and Zhou, F.: Global benefits of non-continuous flooding to reduce greenhouse gases and irrigation water use without rice yield penalty, Glob. Change Biol., 28, 3636–3650, https://doi.org/10.1111/gcb.16132, 2022. 
Bouman, B. A. M., Kropff, M., Tuong, T. P., Wopereis, M. C. S., Berge, H. F. M. T., and Laar, H. H. V.: ORYZA2000: modeling lowland rice, International Rice Research Institute, https://doi.org/10.22004/ag.econ.281825, 2001. 
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Short summary
This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with vital physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for multi-objective optimization of rice irrigation schemes at a large scale.
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