Optimization of canopy resistance models for alpine meadow in the northeastern Tibetan Plateau
Optimization of canopy resistance models for alpine meadow in the northeastern Tibetan Plateau
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青藏高原东北部高寒草甸冠层抗性模型优化
DOI：
10.1016/j.jhydrol.2022.128007
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发表时间：
2022-06
影响因子：
6.4
通讯作者：
Shiqiang Zhang
中科院分区：
文献类型：
--
作者：
Yaping Chang;Yongjian Ding;Qiudong Zhao;Jia Qin;Shiqiang Zhang
比较了Jarvis模型的12种组合模型在高寒草甸冠层阻力估算中的应用。·使用六年的涡动协方差数据来评估模型的性能。·型号10(M10)在高山草甸上表现最好。·选择合适的应力函数是建立冠层阻力模型的关键。冠层阻力(Rc)是估算植被蒸腾作用的重要参数。利用有效叶面积指数(LAI)的倒置Penman-Monteith(PM)方程可以计算特定地点的rc，这需要气象和湍流通量数据。由于青藏高原恶劣的环境，rc的空间分布很难刻画。被描述为环境变量的乘法函数的Jarvis模型已被广泛使用。然而，高寒草甸不同类型Jarvis模型的差异和优化还没有得到充分的解决。因此，我们的总体目标是为高寒草甸生态系统确定合适的rc估计函数，并提高其精度。用12个不同应力函数组成的Jarvis模型对青藏高原东北部地区的Rc进行了检验，并与用PM方程计算的Rc进行了比较。结果表明，适当的气温函数和水汽压亏函数可以明显改善模型的性能。向下短波辐射的两种不同应力函数之间无明显差异。最优模型(M10)由下行短波辐射的渐近函数、气温的线性函数、水汽压亏差的指数函数和土壤水分的分段函数组成，其决定系数为0 93，均方根误差为60 2 S m−1，纳什-萨克利夫效率系数为0 92。选择合适的应力函数是RC建模的重要环节。在rc计算中考虑气温的模型比没有考虑温度的模型产生了更好的结果。Rc对环境变量的敏感性分析表明，rc对水汽压亏缺最敏感，其次是叶面积指数和向下短波辐射，而rc对土壤水分的敏感性较低。在所有优化参数中，rc对kT(温度的拟合参数)最敏感，其次是kD(蒸汽压亏缺的拟合参数)和rcmin(最佳生理条件下的最小rc)。本研究探讨了高寒草甸生态系统模拟中应力函数的选择问题，对其他生态系统也有一定的参考价值。
• Twelve combination models of the Jarvis-type model were compared for canopy resistance estimation of alpine meadows. • Six-year eddy covariance data were used to evaluate the model performance. • The model 10 (M10) performed best for the alpine meadow. • Selection of appropriate stress functions is essential for canopy resistance modeling. Canopy resistance ( r c ) is a critical parameter for estimating vegetation transpiration. The site-specific r c can be calculated using the inversed Penman-Monteith (PM) equation with the effective leaf area index (LAI), which requires meteorological and turbulent flux data. The spatial distribution of r c is difficult to characterize due to the harsh environment of the Tibetan Plateau. The Jarvis-type model for modeling r c , described as a multiplicative function of environmental variables, has been widely used. However, the differences and optimization of different Jarvis-type models for alpine meadows have not been fully addressed. Consequently, our overall objective was to determine the appropriate functions for r c estimation and improve its accuracy for the alpine meadow ecosystem. Twelve Jarvis-type models composed of different stress functions were examined and compared with the observed r c calculated using PM equation at the Arou site in the northeastern Tibetan Plateau. The results suggest that the proper air temperature function and vapor pressure deficit function could improve model performance obviously. There was no obvious difference between the two different stress functions of downward shortwave radiation. The best model (M10), which was composed of an asymptotical function of downward shortwave radiation, a linear function of air temperature, an exponential function of vapor pressure deficit and a piecewise function of soil water content, had best performance with coefficient of determination of 0.93, root mean square error of 60.2 s m −1 and Nash-Sutcliffe efficiency coefficient of 0.92. The selection of proper stress functions is important for r c modeling. Models that considered the air temperature for r c calculations produced better results than those without temperature. The sensitivity analysis of r c to environmental variables indicated that r c was most sensitive to vapor pressure deficit, followed by LAI and downward shortwave radiation, whereas r c was less sensitive to soil water content. For all optimized parameters, r c was the most sensitive to k T (a fitting parameter for temperature), followed by k D (a fitting parameter for vapor pressure deficit) and r cmin (minimum r c under the optimal physiological condition). This study addresses the selection of proper stress functions in modeling r c for the alpine meadow site, which can also provide a reference for other ecosystems.
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西北干旱内陆河流域梭梭灌丛冠层导度模拟
影响因子：
6.2
作者：
Xu Shiqin;Yu Zhongbo;Zhang Ke;Ji Xibin;Yang Chuanguo;Sudicky Edward A.
通讯作者：
Sudicky Edward A.
影响因子：
6.2
作者：
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通讯作者：
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DOI：
10.1175/1520-0450(2001)040
发表时间：
2001-08
期刊：
Journal of Applied Meteorology
影响因子：
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作者：
E. Valor;V. Meneu;V. Caselles
通讯作者：
E. Valor;V. Meneu;V. Caselles
影响因子：
3.2
作者：
T. Yabe;R. Tanaka;T. Nakamura;F. Xiao
通讯作者：
T. Yabe;R. Tanaka;T. Nakamura;F. Xiao
DOI：
10.1071/pp98023
发表时间：
1999
期刊：
Australian Journal of Plant Physiology
影响因子：
--
作者：
D. White;C. Beadle;P. Sands;D. Worledge;J. Honeysett
通讯作者：
D. White;C. Beadle;P. Sands;D. Worledge;J. Honeysett