Kyle R. Mankin, Debora A. Edmunds, Gregory S. McMaster, Fred Fox, Larry E. Wagner, Timothy R. Green
{"title":"冬小麦作物模型通过纳入水分亏缺胁迫的物候响应来改善生长模拟","authors":"Kyle R. Mankin, Debora A. Edmunds, Gregory S. McMaster, Fred Fox, Larry E. Wagner, Timothy R. Green","doi":"10.1007/s10666-023-09939-5","DOIUrl":null,"url":null,"abstract":"Abstract Crop models can provide insights into the impacts of climate and management on crop growth and yield, but most currently are limited by overly simplistic assumptions about phenological development and response to water stress. We assessed winter wheat growth and yield performance of three crop models with lineage to the EPIC crop submodel. SWAT adopted the EPIC approach with few modifications, WEPS added new biomass accumulation, partitioning, and canopy approaches linked to key phenological development stages, and UPGM added to WEPS a detailed phenology component simulating responses to water-deficit stress. The models were evaluated with default parameters and compared to experimental data for winter wheat ( Triticum aestivum L.) from two sites and a range of water-stress conditions for yield, aboveground biomass, biomass partitioning, canopy height, harvest index, and leaf area index. All models simulated yield very well (index of agreement [d] ≥ 0.93), but differences in model performance were increasingly evident for biomass (d = 0.91 [WEPS] to 0.86 [SWAT]), final canopy height (d = 0.68 [UPGM] to 0.44 [SWAT]), and harvest index (d = 0.61 [WEPS] to 0.43 [SWAT]). Errors in biomass simulation were most evident in the grain-filling period late in the growing season. Both WEPS and UPGM exhibited improved simulation of biomass and other response variables by including more explicit simulation of phenological response to water stress. The consistent improvement in winter wheat growth and yield simulation achieved with detailed phenology simulation provides an incentive to develop and test detailed phenology simulation components for other crops: currently 11 crops are simulated in UPGM, although the phenological parameters are uncalibrated. Better modeling linkages of water-stressed phenological development with other physiological processes will be critical to inform crop production where water stress and irrigation limitation are concerns.","PeriodicalId":50515,"journal":{"name":"Environmental Modeling & Assessment","volume":"124 46","pages":"0"},"PeriodicalIF":2.7000,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Winter Wheat Crop Models Improve Growth Simulation by Including Phenological Response to Water-Deficit Stress\",\"authors\":\"Kyle R. Mankin, Debora A. Edmunds, Gregory S. McMaster, Fred Fox, Larry E. Wagner, Timothy R. Green\",\"doi\":\"10.1007/s10666-023-09939-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Crop models can provide insights into the impacts of climate and management on crop growth and yield, but most currently are limited by overly simplistic assumptions about phenological development and response to water stress. We assessed winter wheat growth and yield performance of three crop models with lineage to the EPIC crop submodel. SWAT adopted the EPIC approach with few modifications, WEPS added new biomass accumulation, partitioning, and canopy approaches linked to key phenological development stages, and UPGM added to WEPS a detailed phenology component simulating responses to water-deficit stress. The models were evaluated with default parameters and compared to experimental data for winter wheat ( Triticum aestivum L.) from two sites and a range of water-stress conditions for yield, aboveground biomass, biomass partitioning, canopy height, harvest index, and leaf area index. All models simulated yield very well (index of agreement [d] ≥ 0.93), but differences in model performance were increasingly evident for biomass (d = 0.91 [WEPS] to 0.86 [SWAT]), final canopy height (d = 0.68 [UPGM] to 0.44 [SWAT]), and harvest index (d = 0.61 [WEPS] to 0.43 [SWAT]). Errors in biomass simulation were most evident in the grain-filling period late in the growing season. Both WEPS and UPGM exhibited improved simulation of biomass and other response variables by including more explicit simulation of phenological response to water stress. The consistent improvement in winter wheat growth and yield simulation achieved with detailed phenology simulation provides an incentive to develop and test detailed phenology simulation components for other crops: currently 11 crops are simulated in UPGM, although the phenological parameters are uncalibrated. Better modeling linkages of water-stressed phenological development with other physiological processes will be critical to inform crop production where water stress and irrigation limitation are concerns.\",\"PeriodicalId\":50515,\"journal\":{\"name\":\"Environmental Modeling & Assessment\",\"volume\":\"124 46\",\"pages\":\"0\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2023-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Modeling & Assessment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s10666-023-09939-5\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Modeling & Assessment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10666-023-09939-5","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Winter Wheat Crop Models Improve Growth Simulation by Including Phenological Response to Water-Deficit Stress
Abstract Crop models can provide insights into the impacts of climate and management on crop growth and yield, but most currently are limited by overly simplistic assumptions about phenological development and response to water stress. We assessed winter wheat growth and yield performance of three crop models with lineage to the EPIC crop submodel. SWAT adopted the EPIC approach with few modifications, WEPS added new biomass accumulation, partitioning, and canopy approaches linked to key phenological development stages, and UPGM added to WEPS a detailed phenology component simulating responses to water-deficit stress. The models were evaluated with default parameters and compared to experimental data for winter wheat ( Triticum aestivum L.) from two sites and a range of water-stress conditions for yield, aboveground biomass, biomass partitioning, canopy height, harvest index, and leaf area index. All models simulated yield very well (index of agreement [d] ≥ 0.93), but differences in model performance were increasingly evident for biomass (d = 0.91 [WEPS] to 0.86 [SWAT]), final canopy height (d = 0.68 [UPGM] to 0.44 [SWAT]), and harvest index (d = 0.61 [WEPS] to 0.43 [SWAT]). Errors in biomass simulation were most evident in the grain-filling period late in the growing season. Both WEPS and UPGM exhibited improved simulation of biomass and other response variables by including more explicit simulation of phenological response to water stress. The consistent improvement in winter wheat growth and yield simulation achieved with detailed phenology simulation provides an incentive to develop and test detailed phenology simulation components for other crops: currently 11 crops are simulated in UPGM, although the phenological parameters are uncalibrated. Better modeling linkages of water-stressed phenological development with other physiological processes will be critical to inform crop production where water stress and irrigation limitation are concerns.
期刊介绍:
Environmental Modeling & Assessment strives to achieve this by publishing high quality, peer-reviewed papers that may be regarded as either instances of best practice, or as studies that advance the evolution and applicability of the theories and techniques of modeling and assessment. Consequently, Environmental Modeling & Assessment will publish high quality papers on all aspects of environmental problems that contain a significant quantitative modeling or analytic component, interpreted broadly. In particular, we are interested both in detailed scientific models of specific environmental problems and in large scale models of the global environment.
We invite models of environmental problems and phenomena that utilise, in an original way, the techniques of ordinary and partial differential equations, simulation, statistics and applied probability, control theory, operations research, mathematical economics, and game theory.
Emphasis will be placed on the novelty of the model, the environmental relevance of the problem, and the generic applicability of the techniques used. Generally, papers should be written in a manner that is accessible to a wide interdisciplinary audience.