春玉米持续干旱过程中常用气孔导度模型的比较研究

Abstract

PDF HTML阅读 XML下载 导出引用 引用提醒 春玉米持续干旱过程中常用气孔导度模型的比较研究 DOI: 10.5846/stxb201711082000 作者: 作者单位: 中国气象科学研究院;南京信息工程大学应用气象学院,中国气象科学研究院;南京信息工程大学气象灾害预警协同创新中心 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金重点项目（41330531，31661143028）；公益性行业（气象）科研专项（重大专项）（GYHY201506001-3） Comparisons between common stomatal conductance models under progressive drought in spring maize Author: Affiliation: Chinese Academy of Meteorological Sciences;Nanjing University of Information Science & Technology,Chinese Academy of Meteorological Sciences Fund Project: National Natural Science Foundation of China (No. 31661143028, No. 41501047) and the China Special Fund for Meteorological Research in the Public Interest (No. GYHY201506001-3). 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:气候变化背景下，干旱频发导致的土壤水分变化将影响气孔导度模型的适用性，进而影响生态系统碳-氮-水循环模拟的准确性。基于春玉米持续干旱田间模拟试验资料，比较了常用气孔导度模型在干旱条件下的模拟效果，评价了土壤水分响应函数对气孔导度模型效果的影响，并探讨了气孔导度模型的适用土壤水分范围。结果表明，在持续干旱过程中，模型模拟效果表现为BBL模型最优，其次是USO模型和BWB模型，Jarvis模型最差；引入土壤水分响应函数，提高了BWB模型和USO模型的模拟效果，而降低了Jarvis模型和BBL模型模拟效果，模型模拟效果表现为USO修正模型最优，其次是BBL修正模型和BWB修正模型，Jarvis修正模型最差。在持续干旱过程中，Jarvis模型和BWB模型的剩余气孔导度较大，而BBL模型和USO模型的剩余气孔导度相对较小，表明BBL模型和USO模型在干旱条件下具有一定的稳定性。基于95%置信区间判断表明：Jarvis模型、BBL模型和USO模型在土壤相对湿度范围为33%-83%条件下适用，而BWB模型的适用土壤相对湿度范围为33%-76%，引入水分响应函数后可在试验条件下适用。研究结果可为干旱条件下选取合适的气孔导度模型以准确模拟陆地生态系统碳循环和水循环提供依据，并为改善农业水资源的有效使用和评估提供支撑。 Abstract:The accurate simulation of stomatal behavior in diverse soil moisture conditions is important for the characterization of the responses and the adaptive mechanisms of vegetation ecosystems to climate change and for the prediction of the carbon and water cycles between the plants and the atmosphere in the context of climate change. Based on the leaf gas exchange parameters data for spring maize from a field progressive drought manipulation experiment, the applicability of four common stomatal conductance models (Jarvis, BWB, BBL, and USO) in spring maize were studied under drought conditions, the effects of the soil water response function on the stomatal conductance models were evaluated, and a suitable soil moisture range for each stomatal conductance model was discussed. The results revealed that the simulation accuracy of the Jarvis, BWB, BBL, and USO models was affected by the soil relative water content (SRWC). In progressive drought conditions, the BBL model performed the best, followed by the USO model and the BWB model, and the Jarvis model performed the worst. After the introduction of the soil water response function, the modified USO model performed the best, followed by the modified BBL and BWB models, and the modified Jarvis model performed the worst. The simulation accuracy of the BWB and USO models was improved by the introduction of the soil water response function; the normalized root mean square error (NRMSE) value decreased by 1.99% and 1.02%, respectively, and the relative error (RE) value decreased by 3.20% and 0.63%, respectively. Although the performance of the Jarvis and BBL models decreased after the introduction of the soil water response function, the NRMSE value increased by 4.70% and 3.45%, respectively, and the RE value increased by 6.02% and 2.00%, respectively. The residual stomatal conductance of the BBL and USO models was relatively smaller than that of the Jarvis and BWB models, which indicated that the BBL and USO models displayed considerable stability under progressive drought conditions. According to the relationship between stomatal conductance and SRWC and in terms of the 95% confidence intervals, the Jarvis, BBL, and USO models were applicable when SRWC was between 33% and 83%, whereas the BWB model was applicable when SRWC was between 33% and 76%. After the introduction of the soil water response function, the modified BWB model could be applicable for the current experimental soil moisture range. The results might provide references for the selection of suitable stomatal conductance models to improve the efficient use and assessment of agricultural water resources. 参考文献 相似文献 引证文献