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Advances in regional-scale crop growth and associated process modeling.

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Title: Advances in regional-scale crop growth and associated process modeling.
Authors: Liu, Wenfeng1,2,3 (AUTHOR) wenfeng.liu@cau.edu.cn, Bai, Yawei1,2,3 (AUTHOR), Du, Taisheng1,2,3 (AUTHOR), Li, Mengxue1,2,3 (AUTHOR), Yang, Hong4 (AUTHOR), Chen, Shichao1,2,3 (AUTHOR), Liang, Chuanbin1,2,3 (AUTHOR), Kang, Shaozhong1,2,3 (AUTHOR)
Source: SCIENCE CHINA Earth Sciences. Mar2025, Vol. 68 Issue 3, p653-668. 16p.
Subjects: Sustainable agriculture, Greenhouse gases, Nonpoint source pollution, Crop physiology, Crop growth, Human activity recognition
Abstract: In the context of global change, ensuring national food security and achieving sustainable development of agricultural production systems have become major challenges worldwide. To address these issues, regional-scale crop growth and associated process (CROP-AP) models, with their robust simulation and predictive capabilities, have emerged as important tools for studying a wide range of issues relating to agricultural production at river basin, national, and even global scales. Here, we provide a systematic review of the advances of regional-scale CROP-AP models. First, regional-scale CROP-AP models are categorized based on model characteristics: statistical models, crop growth models, hydrology-crop coupling models, and ecosystem models. The origin, development, principle, structure, and application of each model type are introduced. Then, the main functions of regional-scale CROP-AP models are critically reviewed from five aspects: crop yield prediction, crop water consumption, agricultural non-point source pollution, greenhouse gas emissions, and climate change impact and responses. Finally, the future development trends and research priorities of regional-scale CROP-AP models are explored from six key perspectives: model validation and calibration, the ability to simulate the coupling of crop physiology and human activities, enhancing model scalability, multi-model ensembles, data and code sharing, and the integration of artificial intelligence. This review aims to provide comprehensive references and insights for the further development and application of large-scale, high-precision CROP-AP models. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:In the context of global change, ensuring national food security and achieving sustainable development of agricultural production systems have become major challenges worldwide. To address these issues, regional-scale crop growth and associated process (CROP-AP) models, with their robust simulation and predictive capabilities, have emerged as important tools for studying a wide range of issues relating to agricultural production at river basin, national, and even global scales. Here, we provide a systematic review of the advances of regional-scale CROP-AP models. First, regional-scale CROP-AP models are categorized based on model characteristics: statistical models, crop growth models, hydrology-crop coupling models, and ecosystem models. The origin, development, principle, structure, and application of each model type are introduced. Then, the main functions of regional-scale CROP-AP models are critically reviewed from five aspects: crop yield prediction, crop water consumption, agricultural non-point source pollution, greenhouse gas emissions, and climate change impact and responses. Finally, the future development trends and research priorities of regional-scale CROP-AP models are explored from six key perspectives: model validation and calibration, the ability to simulate the coupling of crop physiology and human activities, enhancing model scalability, multi-model ensembles, data and code sharing, and the integration of artificial intelligence. This review aims to provide comprehensive references and insights for the further development and application of large-scale, high-precision CROP-AP models. [ABSTRACT FROM AUTHOR]
ISSN:16747313
DOI:10.1007/s11430-024-1477-2