伊拉克三大气候带40个参考蒸散估算模型的评价

Alaa Adel Jasim Al-Hasani, Shamsuddin Shahid
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The objectives of the present study were to assess the performance of 40 ETo empirical models (13 radiation-based, 13 mass-transfer-based, and 14 temperature-based) against the FAO-PM model and identify alternative models with the minimal available data in three major climatic zones of Iraq: the Mediterranean climate (MCZ), semiarid (SCZ), and arid desert (ACZ). The recent ERA5 data set was adopted. The results indicate that (1) the Rohwer mass-transfer method is the best for estimating ETo for two-thirds of Iraq with a mean correlation coefficient (R2) of 0.97, mean Kling-Gupta efficiency (KGE) of 0.84, mean percent bias (PBIAS) of −8.92%, mean Nash-Sutcliffe efficiency coefficient (NSE) of 0.92, and root mean square error (RMSE)-observations standard deviation ratio (RSR) of 0.27, followed by the Penman (R2=0.90, KGE=0.75, NSE=0.77, RSR=0.46, and PBIAS=6.36%) and Caprio (R2=0.90, KGE=0.66, NSE=0.54, RSR=0.58, and PBIAS=24.64%) models; (2) Caprio is the best radiation-based model for estimating ETo, mainly in the ACZ, whereas Kharrufa is the best temperature-based model for estimating ETo, primarily in the SCZ and ACZ. Overall, the mass-transfer-based models performed better than other-based models for ETo estimation. 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The study revealed that the choice of the ETo model varied depending on the climatic zone. The Caprio model performed best for radiation-based estimation in the arid desert, whereas the Kharrufa model was most effective for temperature-based estimation in the semiarid region and arid desert. 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引用次数: 0

摘要

准确的参考蒸散量估算对于灌溉管理和可持续农业规划至关重要。采用粮农组织推荐的Penman-Monteith方法(FAO-PM)进行可靠的ETo估计,很难获得若干数据要求,这导致了许多经验模型的发展。这对于位于西亚(29°15 ' 00″-38°15 ' 00″N;38°45 ' 00″-48°45 ' 00″E),那里的气象数据往往有限或缺失。本研究的目的是评估40个ETo经验模型(13个基于辐射、13个基于传质和14个基于温度)与FAO-PM模型的性能,并利用伊拉克三个主要气候带(地中海气候区(MCZ)、半干旱气候区(SCZ)和干旱沙漠气候区(ACZ)的最小可用数据确定替代模型。采用最新的ERA5数据集。结果表明,(1)Rohwer传质法最适用于伊拉克三分之二地区的ETo估算,平均相关系数(R2)为0.97,平均克林-古普塔效率(KGE)为0.84,平均百分比偏差(PBIAS)为- 8.92%,平均纳希-苏特克里夫效率系数(NSE)为0.92,均方根误差(RMSE)-观测标准差比(RSR)为0.27,其次是Penman法(R2=0.90, KGE=0.75, NSE=0.77, RSR=0.46, PBIAS=6.36%)和Caprio法(R2=0.90, PBIAS= 0.92)。KGE=0.66, NSE=0.54, RSR=0.58, PBIAS=24.64%)模型;(2) Caprio是估算ETo的最佳辐射模式,主要在ACZ, Kharrufa是估算ETo的最佳温度模式,主要在SCZ和ACZ。总体而言,基于传质的模型比基于其他模型的ETo估计效果更好。本研究结果为在有限数据集下利用经验模型准确估算ETo提供了科学参考,对伊拉克灌溉管理具有一定的参考价值。实际应用准确估算土壤水分流失对有效的灌溉管理和可持续农业规划至关重要。然而,推荐的估算经济贸易组织的方法,即粮农组织- pm方法,需要各种数据输入,这些数据可能并不总是随时可用,特别是在伊拉克等地区。因此,本研究在伊拉克三个主要气候带(地中海气候、半干旱区和干旱沙漠)与FAO-PM模型对比,评估了40个经验ETo模型(基于辐射、基于传质和基于温度)的性能。研究发现,Rohwer传质法在估计伊拉克三分之二地区的ETo方面表现最好。Penman和Caprio模型在估算特定领域的ETo方面也表现良好。研究表明,ETo模型的选择因气候带的不同而不同。Caprio模式对干旱荒漠地区基于辐射的估算效果最好,而Kharrufa模式对半干旱区和干旱荒漠地区基于温度的估算效果最好。总体而言,基于传质的模型在ETo估计方面优于其他类型的模型。
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Assessment of 40 Empirical Models for Estimating Reference Evapotranspiration under the Three Major Climate Zones of Iraq
Accurate reference evapotranspiration (ETo) estimation is crucial for water irrigation management and sustainable agriculture planning. The difficulty in obtaining several data requirements for employing the recommended Food and Agriculture Organization Penman-Monteith method (FAO-PM) for reliable estimation of ETo has led to the development of many empirical models. This is particularly crucial for Iraq, located in West Asia (29°15′00″–38°15′00″ N; 38°45′00″–48°45′00″ E), where meteorological data are often limited or missing. The objectives of the present study were to assess the performance of 40 ETo empirical models (13 radiation-based, 13 mass-transfer-based, and 14 temperature-based) against the FAO-PM model and identify alternative models with the minimal available data in three major climatic zones of Iraq: the Mediterranean climate (MCZ), semiarid (SCZ), and arid desert (ACZ). The recent ERA5 data set was adopted. The results indicate that (1) the Rohwer mass-transfer method is the best for estimating ETo for two-thirds of Iraq with a mean correlation coefficient (R2) of 0.97, mean Kling-Gupta efficiency (KGE) of 0.84, mean percent bias (PBIAS) of −8.92%, mean Nash-Sutcliffe efficiency coefficient (NSE) of 0.92, and root mean square error (RMSE)-observations standard deviation ratio (RSR) of 0.27, followed by the Penman (R2=0.90, KGE=0.75, NSE=0.77, RSR=0.46, and PBIAS=6.36%) and Caprio (R2=0.90, KGE=0.66, NSE=0.54, RSR=0.58, and PBIAS=24.64%) models; (2) Caprio is the best radiation-based model for estimating ETo, mainly in the ACZ, whereas Kharrufa is the best temperature-based model for estimating ETo, primarily in the SCZ and ACZ. Overall, the mass-transfer-based models performed better than other-based models for ETo estimation. The outcomes of this study provide a scientific reference for accurate ETo estimation using empirical models under limited data sets, which is valuable for irrigation management in Iraq.Practical ApplicationsAccurately estimating ETo is vital for effective water irrigation management and sustainable agriculture planning. However, the recommended method for estimating ETo, the FAO-PM method, requires various data inputs that may not always be readily available, especially in regions like Iraq. Therefore, this study assessed the performance of 40 empirical ETo models, categorized into radiation-based, mass-transfer-based, and temperature-based models, against the FAO-PM model in three major climatic zones of Iraq: the Mediterranean climate, the semiarid region, and the arid desert. The study found that the Rohwer mass-transfer method showed the best performance in estimating ETo for two-thirds of Iraq. The Penman and Caprio models also performed well in estimating ETo in specific areas. The study revealed that the choice of the ETo model varied depending on the climatic zone. The Caprio model performed best for radiation-based estimation in the arid desert, whereas the Kharrufa model was most effective for temperature-based estimation in the semiarid region and arid desert. Overall, the mass-transfer-based models outperformed other types of models in ETo estimation.
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