A Comparative Study of Potential Evapotranspiration Estimation by Eight Methods with FAO Penman–Monteith Method in Southwestern China

Lang, Dengxiao; Zheng, Jiangkun; Shi, Jiaqi; Feng, Li; Ma, Xieyao; Wang, Wenwu; Chen, Xuli; Zhang, Mingfang

doi:10.3390/w9100734

Cited by 129 publications

(102 citation statements)

References 43 publications

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“…We think that the following two ways could be considered: To estimate the ET 0 using a variety of methods. Since the PM‐FAO method may cause obvious energy imbalance due to the difference of regional characteristics, such as climatic condition and land cover, we recommend to combine the PM method and a variety of radiation‐based and temperature‐based methods (Lang et al, ). The most suitable method for local use should be determined through comparative analyses and data validation based on the Bowen‐ratio, flux tower data, or lysimeter data. The fully parameterized PM method should be a good choice in sparsely vegetated regions.…”

Section: Discussionmentioning

confidence: 99%

The Uncertainty of Penman‐Monteith Method and the Energy Balance Closure Problem

Hao

Zhang

et al. 2018

JGR Atmospheres

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The Penman‐Monteith (PM) method is considered the most accurate method for estimating reference crop evapotranspiration (ET0). However, the method has obvious flaws in energy balance closure. In this study, the changing trends between latent heat flux of ET0 (LEp) and surface net radiation (Rn) in China were analyzed based on observational data from 800 meteorological stations. The results showed that the multiyear average ratio of LEp/Rn was highest in the warm temperate zone and was lowest in the subfrigid zone of the Tibetan Plateau. Correspondingly, the values of LEp/Rn in these areas were ranged from 1.138 to 0.647. At the site scale, there were 61, 178, and 170 meteorological stations with daily average LEp/Rn values >1 during three periods (from January to April, May to August, and September to December, respectively). The ratio of LEp/Rn showed an obvious surface energy imbalance, and it was extremely obvious in northern China. Meanwhile, it is found that there was also great uncertainty of the ET0, which estimated based on the calculated and measured net radiation. In general, the uncertainty of ET0 was ranged from −0.955 to 1.028 mm/day and the average value of uncertainty was 0.154 mm/day. The uncertainty also showed obviously temporal variation, which was lower during April to October, but was higher in other times. The main cause of the energy balance closure problem was the overestimation of the aerodynamic component of ET0. In view of such situation, this study suggested the two ways to estimate ET0 for different regions.

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Section: Discussionmentioning

confidence: 99%

The Uncertainty of Penman‐Monteith Method and the Energy Balance Closure Problem

Hao

Zhang

et al. 2018

JGR Atmospheres

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“…Seasonal variability of potential evapotranspiration plays a crucial role in influencing hydrological regime, thus impacting the vegetation dynamics including seasonal agricultural crops' water demand (Liu et al 2015). The evaluation significantly supports in various applications including irrigation plan and understanding climate change impacts (Lang et al 2017). The maps were produced for kharif, rabi and zaid seasons utilizing the long-term PET at the district level of India.…”

Section: Potential Evapotranspiration Pattern Analysismentioning

confidence: 81%

Analysis of Seasonal Precipitation, Potential Evapotranspiration, Aridity, Future Precipitation Anomaly and Major Crops at District Level of India

Goparaju¹,

Ahmad²

2019

KN J. Cartogr. Geogr. Inf.

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Climate-induced risks are very significant in these days and will impact the agriculture crop production because of the change in hydro-climatic condition. Remote sensing and GIS framework provide scientific understanding in practical application systems with the sustainable solution in new climate change reality and support significantly in resilience to mitigate the future risk. The paper deals with long-term (1970-2000) monthly thematic datasets and analyzed the seasonal (kharif, rabi and zaid) pattern of precipitation, potential evapotranspiration and aridity index to scale of district level of India. Additionally, we have used the predicted (2025) monthly precipitation anomalies data (climate change scenario) to examine the seasonal precipitation pattern at the district level of India. The major agriculture crops (rice, wheat, and maize) for the year 2005 were also evaluated during those seasons. Such analysis gives better understanding and knowledge of district-wise seasonal spatial pattern at country level (India) of climate stress, crop water demand and suitably applied to make strategies/ synergic approach toward agriculture resilience. The long-term seasonal aridity index pattern analysis varies significantly throughout India during kharif, rabi and zaid seasons which were manifested by cropping pattern adopted by farmers as per land potentiality. Several districts in some of the states of India receive adequate precipitation during kharif season and manifest low aridity index in rabi and zaid season which can be recommended for rainwater conservation at the watershed level to boost the agriculture crop production. Farmer's suicide hot spot districts in the arid and semiarid regions need policy intervention to develop a concrete plan including integrated watershed management strategies with traditional ecological knowledge for long-term sustainable management for climate resilience because these districts showed significantly low aridity index value in all seasons. The remote sensing and GIS-based evaluation/results of this study in conjugation with in situ ancillary datasets will support significantly to address the climate-induced risk of farmers to achieve sustainability in food security, enhancing the livelihood, eradication of poverty and magnifying the farm household resilience. AbstraktAufgrund von hydroklimatischen Änderungen im Rahmen des Klimawandels kommt es zu Risiken für die landwirtschaftliche Produktion von Nutzpflanzen. Fernerkundung und GIS können helfen nachhaltige Lösungen bzw. Anpassungsstrategien im Klimawandel für die Praxis bereitzustellen, um zukünftige Risiken zu mindern. Die Studie analysiert saisonale Muster (Kharif-, Rabi-und Zaidperiode) des Niederschlages, der Evapotranspiration und des Ariditätsindex auf Basis von monatlichen Datensätzen (1970-2000) auf der Ebene der Bundesstaaten in Indien. Zusätzlich wurden die aus Klimamodellen berechneten monatlichen Niederschlagsanomalien für 2025 in die Untersuchung einbezogen. Für 2005 wurden die Produktionsbedingungen für die wich...

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“…But in reality, all existing most temperature-based methods directly or indirectly incorporate radiation, at least in the form of sunshine hours [21]. Even these methods do not perform equally well [15] at all locations without calibrations [5,7,16]. For instance, Medeiros et al [18] propose the method of correction based on error autocorrelation and linear regression for local estimates improvement for temperature-based ET estimation methods.…”

Section: Plots Of the Three Methods Against Et-pm And Curve Fitting Wmentioning

confidence: 99%

Three methods of estimating the power of maximum temperature in TM–ET estimation equation

Mengistu

Amente

2019

SN Appl. Sci.

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The use of FAO56-PM is still the preferred method for the estimation of evapotranspiration (ET) regardless of locations. But in places where data that satisfy all the meteorological variables of PM equation are non-existent or missing, the use of either temperature or radiation-based methods is the alternative option, since both radiation and temperature are the main drivers of ET. From the latter two, temperature-based ET estimation methods are still the simplest ones to use. However, there are challenges since some of the parameters used in the temperature-based equations are location dependent. Such location dependence is due to variability in terms of latitude, altitude and other geo-location parameters. Therefore, local calibration of temperature-based methods is necessary to get better estimates of ET. In this study, one temperature-based ET estimation method known as Temesgen-Melesse's (TM) method was assessed in relation to the PM equation using data of ten Class I meteorological stations in Ethiopia. In the study, three different techniques were tested to find location-dependent maximum temperature power ('n') used in TM equation (i.e., to calibrate the method). The first two techniques involve calibration using PM data. In the first case, monthly averaged data that span from 1 to 5 years were used (as five data sets of 12, 24, 36, 48 and 60 months). In the second case, daily values that span from 10 to 30 days were used in three groups of 10-, 20-, and 30-day data sets. In the third technique, an attempt was made to estimate 'n' from the location latitude, altitude and average of the monthly averaged maximum temperature (T̄m x ). The results obtained from each technique are given as follows. Calibration from the monthly averaged data gave good 'n' values for all the stations with R 2 values ranging from 0.80 to 0.92. There were no differences in the number of data points (12,24, 36, 48 and 60 months) used, which means data points of 12 months are sufficient for the calibration. Calibration using the daily data gave satisfactory 'n' results for all the stations tested, though the statistical parameters and performance tests did not give results that are comparable to the monthly averaged values. The results were nearly the same for 10-, 20-, or 20-day data points, which means any one of them can be used for calibration purposes. Estimation of 'n' from latitude, altitude and T̄m x gave results that are comparable to the ones with 'n' calibrated. The percent differences between the 'n' calibrated using data of 131 months and the 'n' values obtained from monthly data and daily data calibrations are less than 0.16% and 0.5%, respectively. The calculated 'n' showed a percent difference of less than 1.1%. Using calculated 'n' is better than performing calibration using daily data. It can also be considered as option when at least 1-year PM data are not available for calibration.

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A Comparative Study of Potential Evapotranspiration Estimation by Eight Methods with FAO Penman–Monteith Method in Southwestern China

Cited by 129 publications

References 43 publications

The Uncertainty of Penman‐Monteith Method and the Energy Balance Closure Problem

The Uncertainty of Penman‐Monteith Method and the Energy Balance Closure Problem

Analysis of Seasonal Precipitation, Potential Evapotranspiration, Aridity, Future Precipitation Anomaly and Major Crops at District Level of India

Three methods of estimating the power of maximum temperature in TM–ET estimation equation

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