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首页> 外文期刊>Agricultural Water Management >Using Bayesian analysis to compare the performance of three evapotranspiration models for rainfed jujube (Ziziphus jujuba Mill.) plantations in the Loess Plateau
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Using Bayesian analysis to compare the performance of three evapotranspiration models for rainfed jujube (Ziziphus jujuba Mill.) plantations in the Loess Plateau

机译:利用贝叶斯分析比较黄土高原雨养枣(Ziziphus jujuba Mill。)人工林的三种蒸散模型的性能

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摘要

In order to select suitable evapotranspiration (ET) models for rainfed and sparsely cultivated jujube (Ziziphus jujuba Mill.) plantations in the Loess Plateau, this study used Bayesian analysis to compare the performances (accuracies and uncertainties) of the Shuttleworth-Wallace (SW) model, the Penman-Monteith (PM) model and the Penman-Monteith equation with a variable surface canopy resistance (PMv) model in terms of daily and hourly ET. To determine seasonal variations and soil water dependence, probabilistic analyses were independently used to calibrate the SW and PM model parameters at every growth stages and the PMv model parameters for different soil water conditions in the growth season of rainfed jujube plantations in 2013. Finally, data for the growth season in 2012 were used to validate the calibrated models. The results showed that the posterior distributions of the parameters of the three models narrowed down at both daily and hourly scales, suggesting decreasing uncertainties in the parameters. Some model parameters varied with season (increasing for the last two growth seasons) or soil water condition (decreasing with increasing soil moisture). The performances of the ET models also varied with time scale, generally less precise at hourly than at daily time scale. Irrespectively, the three ET models met the evaluation criteria (mean relative error (MAE) 20% and coefficient of determination (R-2) > 0.8 and Willmott index of agreement (D) > 0.8) with acceptable accuracy and uncertainty at the daily time scale in both calibration (with R-2, MAE and D values of 0.94, 6.78% and 0.94 for the SW model; 0.94, 7.52% and 0.94 for the PM model; and 0.89, 8.49% and 0.83 for the PMV model, respectively) and validation periods (with R-2, MAE and D values of 0.94, 5.77% and 0.92 for the SW model; 0.93, 5.15% and 0.91 for the PM model; and 0.89, 10.26% and 0.86 for the PMV model, respectively). Where only climate data were available, the PMV model was recommended for estimation of daily ET in the study area due to less complexity, low data requirements, and high accuracy. Where sufficient monitoring data were available, the PM model was preferred for estimation of the daily ET in the study area due to less complexity and small differences in performance with the SW model. All three models met the evaluation criteria for calibration period(with R-2, MAE and D values of 0.92, 16.04% and 0.92 for the SW model; 0.96,14.37% and 0.94 for the PM model; and 0.89, 18.56% and 0.91 for the PMV model, respectively) while only the SW model met the evaluation criteria for validation period (with R-2, MAE and D values of 0.87, 16.33% and 0.88 for the SW model; 0.85, 20.70% and 0.85 for the PM model; and 0.85, 23.95% and 0.83 for the PMV model, respectively) at the hourly time scale. Based on model accuracy and uncertainty at the hourly time scale, the SW model was recommended for use in estimating ET in jujube plantations in the Loess Plateau. (C) 2015 Elsevier B.V. All rights reserved.
机译:为了为黄土高原雨养和稀疏种植的枣(Ziziphus jujuba Mill。)种植园选择合适的蒸发蒸腾(ET)模型,本研究使用贝叶斯分析比较了Shuttleworth-Wallace(SW)的性能(准确性和不确定性)模型,Penman-Monteith(PM)模型和具有可变表面冠层阻力(PMv)模型的Penman-Monteith方程,按日和小时ET表示。为确定季节变化和土壤水分依赖性,分别使用概率分析来校准2013年雨养枣种植园每个生长阶段的SW和PM模型参数以及不同土壤水分条件下PMv模型参数。针对2012年的生长季节进行了验证。结果表明,三个模型的参数的后验分布在日标度和小时标度上均变小,表明参数的不确定性降低。一些模型参数随季节(最后两个生长季节增加)或土壤水分状况(随土壤湿度增加而变化)而变化。 ET模型的性能也随时间范围而变化,通常每小时的精度不如每天的时间精度高。三种ET模型分别满足评估标准(平均相对误差(MAE)<20%,测定系数(R-2)> 0.8和威尔莫特同意指数(D)> 0.8)),并且每天的准确性和不确定性都可接受两种校准的时间尺度(SW模型的R-2,MAE和D值分别为0.94、6.78%和0.94; PM模型的R-2,MAE和D值为0.94、7.52%和0.94; PMV模型的为0.89、8.49%和0.83,和验证期(SW模型的R-2,MAE和D值分别为0.94、5.77%和0.92; PM模型的R-2,MAE和D值分别为0.93、5.15%和0.91; PMV模型的R-2,MAE和D值为0.89、10.26%和0.86,分别)。如果只有气候数据可用,则建议使用PMV模型来估计研究区域的每日ET,因为它的复杂性较低,数据要求较低且准确性较高。如果有足够的监测数据,则首选PM模型来估计研究区域的每日ET,因为与SW模型相比,其复杂性较低且性能差异较小。这三个模型均满足校准期的评估标准(SW模型的R-2,MAE和D值分别为0.92、16.04%和0.92; PM模型的R-2,MAE和D值为0.96、14.37%和0.94; PM模型的为0.89、18.56%和0.91分别针对PMV模型)和仅SW模型满足验证期的评估标准(SW模型的R-2,MAE和D值分别为0.87、16.33%和0.88; PM为0.85、20.70%和0.85模型;在小时时间尺度上分别为0.85、23.95%和0.83)。基于模型的准确性和每小时时间尺度的不确定性,建议将SW模型用于估算黄土高原枣园中的ET。 (C)2015 Elsevier B.V.保留所有权利。

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