比较美国各地的作物生长模式,重点关注干旱和温暖时期

IF 6.5 1区 农林科学 Q1 AGRONOMY
Sneha Chevuru , Gambhir Lamsal , L.P.H. (Rens) van Beek , Michelle T.H. van Vliet , Landon Marston , Marc F.P. Bierkens
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引用次数: 0

摘要

在全球人口不断增长和气候不断变化的背景下,高效用水和可持续作物生产对于确保粮食和水安全至关重要。由于气候变化导致的极端水文气候预计将增加,预计灌溉农业将增加,从而进一步将粮食和水安全相互联系起来。因此,对未来作物产量预测的需求变得更加迫切,包括关于作物产量和耗水量方面的作物生长模型准确性的知识。为此,本研究对aquacrop - os和PCR-GLOBWB 2-WOFOST两种作物生长模型进行了评价。应用耦合水文作物生长模型PCR-GLOBWB 2-WOFOST,同时使用其原始设置并与AquaCrop-OS输入进行协调,产生两个模型实验,将其与AquaCrop-OS结果进行比较,从而分析模型结构和参数化的差异。采用AquaCrop-OS和PCR-GLOBWB 2-WOFOST(原始输入和协调输入)模拟了2001 - 2019年美国(CONUS)各地灌溉玉米、大豆、冬小麦和春小麦的产量。在作物耗水量、生物量产量和作物产量方面比较了模型输出,并评估了模型在干燥和温暖条件下的敏感性。对于所有考虑的作物,PCR-GLOBWB 2-WOFOST(原始)模拟产量与平均报告产量非常接近,统一版本显示大豆和冬小麦的产量被低估了(约23% %)。AquaCrop-OS通常高估作物产量(高达34% %)。AquaCrop-OS和PCR-GLOBWB 2-WOFOST模型在作物耗水量、生物量和产量的空间格局上也存在显著差异。具体来说,AquaCrop-OS和PCR-GLOBWB 2-WOFOST(协调)模型之间的差异归因于每个模型中生物质转化为产量的方式不同。此外,与PCR-GLOBWB 2-WOFOST模型相比,AquaCrop-OS对较高空气温度的敏感性要低得多。最后,PCR-GLOBWB 2-WOFOST原始设置与其协调设置之间的差异强调了在作物生长建模中使用当地和最新作物特定参数化信息的重要性。这些发现强调了模型选择和参数化在准确模拟极端气候条件下作物产量和作物耗水量方面的重要性,这对于改善气候变化条件下的农业实践至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparing crop growth models across the contiguous USA with a focus on dry and warm spells
Efficient water use and sustainable crop production are vital for ensuring both food and water security amidst the growing global population and changing climate. With expected increases in hydroclimatic extremes under climate change, irrigated agriculture is projected to rise, further interlinking food and water security. Hence, the need for future crop yield projections has become more urgent, including knowledge about the accuracy of crop growth modeling in terms of crop yield and water consumption. To this end, our study evaluates two crop growth models—AquaCrop-OS and PCR-GLOBWB 2-WOFOST. The coupled hydrological-crop growth model PCR-GLOBWB 2-WOFOST was applied using both its original settings and harmonized with AquaCrop-OS input, resulting in two model experiments that were compared to the AquaCrop-OS results, allowing analyses of differences in both model structure and parametrizations. AquaCrop-OS and PCR-GLOBWB 2-WOFOST (with original and harmonized input) were used to simulate the yield of irrigated maize, soybean, winter wheat and spring wheat across the contiguous United States (CONUS) from 2001 to 2019. Model outputs were compared in terms of crop water consumption, biomass production, and crop yield and the model sensitivity under dry and warm conditions was evaluated.
For all considered crops, PCR-GLOBWB 2-WOFOST (original) simulated yields align closely with mean reported yields, with the harmonized version showing some underestimates for soybeans and winter wheat (∼23 %). AquaCrop-OS generally overestimates crop yields (up to ∼34 %). Our results also highlight significant differences in spatial patterns of crop water consumption, biomass, and crop yield between AquaCrop-OS and PCR-GLOBWB 2-WOFOST (original and harmonized) models. Specifically, differences between the AquaCrop-OS and PCR-GLOBWB 2-WOFOST (harmonized) models are attributed to variations in how biomass is converted to yield within each model. Also, AquaCrop-OS is found to be much less sensitive to higher air temperatures than the PCR-GLOBWB 2-WOFOST model. Finally, the differences between PCR-GLOBWB 2-WOFOST original and its harmonized settings emphasize the importance of using local- and up-to-date information on crop-specific parametrization in crop growth modeling. These findings underscore the importance of model selection and parameterization in accurately simulating crop yield and crop water consumption under climate extremes, which is essential for improving agricultural practices under climate change.
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来源期刊
Agricultural Water Management
Agricultural Water Management 农林科学-农艺学
CiteScore
12.10
自引率
14.90%
发文量
648
审稿时长
4.9 months
期刊介绍: Agricultural Water Management publishes papers of international significance relating to the science, economics, and policy of agricultural water management. In all cases, manuscripts must address implications and provide insight regarding agricultural water management.
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