Sensitivity analysis of a Penman–Monteith type equation to estimate reference evapotranspiration in southern Spain

Estévez, Javier; Jiménez-Gavilán, Pablo; Berengena, J.

doi:10.1002/hyp.7439

Cited by 95 publications

(63 citation statements)

References 27 publications

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“…In general, Ep was more sensitive to net radiation, followed by air temperature, relative humidity, and wind speed (Figure 8). The results for Ep are not directly comparable to those of previous works, due to the differences of the equations being utilized, of the study media, of the varied approaches to conducting the sensitivity analyses, and of the derived and defined sensitivity coefficients (Estévez et al, 2009). Some other studies (McCuen, 1974;Saxton, 1975;Coleman and DeCoursey, 1976;Beven, 1979) showed that potential evaporation (or evapotranspiration) was much more sensitive to radiation, humidity, and temperature.…”

Section: Discussioncontrasting

confidence: 64%

Sensitivity of soil evaporation and reference evapotranspirationto climatic variables in South Korea

Aydin¹,

Jung²,

Yang³

et al. 2015

Turk J Agric For

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The quantification of evapotranspiration and soil evaporation is crucial for agricultural water management. The FAO-56 Penman-Monteith and E-DiGOR models were used to compute reference evapotranspiration (Eto) and bare soil evaporation, respectively, at 17 meteorological stations of South Korea, from 1980 to 2009. The same soil parameters were assumed for all stations in order to compare actual soil evaporation (Ea) rates jointly dominated by atmospheric evaporative demand and soil water availability, as well as the size of rainfall events. The sensitivity of Penman-Monteith type equations to the major climatic variables was determined based on 1-year dataset. The long-term mean annual precipitation and Eto calculated at selected stations over the country were 1339.7 mm and 1087.1 mm, respectively. Precipitation showed noticeable interyear fluctuations, and the annual Eto increased gradually during the study period. A strong correlation between pan evaporation (Epan) and Eto was observed (R = 0.808, P < 0.001), based on daily data of 30 years. Similarly, a significant correlation between Epan and potential soil evaporation (Ep) was existent (R = 0.622, P < 0.01). The Ep rates were lower than the Eto rates (Ep = 0.8 × Eto). The magnitude of Ea, as calculated with the model, reached a level of 63% of Ep. On the other hand, Ea accounted for 29.4% to 50.3% of the total precipitation over South Korea. Potential soil evaporation was more sensitive to net radiation, while reference evapotranspiration was mostly affected by the relative humidity. Wind speed was the less effective variable. The contribution of soil heat flux was negligible. The sensitivity of both Ep and Eto to the same climatic variables showed significant differences among seasons and locations. The aridity index ranged from 0.85 to 2.13, and all the study sites could be classified as humid areas. An aridity index of less than 1 appeared about once every 6 to 7 years, based on the station averages.

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Section: Discussioncontrasting

confidence: 64%

Sensitivity of soil evaporation and reference evapotranspirationto climatic variables in South Korea

Aydin¹,

Jung²,

Yang³

et al. 2015

Turk J Agric For

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“…The optimal parameters for the best model performance could then be determined with the highest value of NSeff. The model sensitivity to systematic and random errors in a and b was evaluated according to [40,41]. Briefly speaking, the i-th perturbed data value (X ip ) is the sum of the i-th original value (X io ), a constant systematic bias (E s ), and a random error with zero-mean and normally distribution (E r ):…”

Section: Sensitivity Testmentioning

confidence: 99%

Parameterization of Evapotranspiration Estimation for Two Typical East Asian Crops

Zhao

Lüers

2017

Atmosphere

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Estimation of evapotranspiration plays an important role in understanding the water cycle on the earth, especially the water budget in agricultural ecosystems. The parameterization approach of the Penman-Monteith-Katerji-Perrier (PM-KP) model, accounting for the influence of meteorological variables and aerodynamic resistance on surface resistance, was proposed in the literature, but it has not been applied to Asian croplands, and its error and sensitivity have not been reported yet. In this study, the estimation of evapotranspiration on half-hourly scale was carried out for two typical East Asian cropland research sites, and evaluated by using eddy-covariance measurements corrected with the energy-balance-closure concept. Sensitivity coefficients as well as systematic bias and random errors of the PM-KP approach were used to evaluate the model performance. Different distributions of the calibration coefficients between different crops were reported for the first time, indicating that the calibration of this model was more stable for the rice field than for the potato field. The commonly-used parameterization approach suggested by the Food and Agriculture Organization (FAO) was used as reference and was site-specifically optimized. The results suggest that the PM-KP approach would be a better alternative than the PM-FAO approach for estimating evapotranspiration for the flooded rice field, and an acceptable alternative for rain-fed croplands when the soil is well watered and the air is humid during the summer monsoon.

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“…With its simplicity and intuitionism, the method is popular and has been widely used (Ahn, 1996;Goyal, 2004;Xu et al, 2006a, b;Estévez et al, 2009 , 1997). In the study, a crop's GDD was calculated per year, following the most widely used "Method 1" (McMaster and Wilhelm, 1997), by summing the difference of the daily base temperature and the average air temperature over the reference crop-growing period in days (Table 1).…”

Section: Sensitivity Analysismentioning

confidence: 99%

Sensitivity and uncertainty in crop water footprint accounting: a case study for the Yellow River basin

Zhuo

Mekonnen²,

Hoekstra³

2014

Hydrol. Earth Syst. Sci.

139

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Abstract. Water Footprint Assessment is a fast-growing field of research, but as yet little attention has been paid to the uncertainties involved. This study investigates the sensitivity of and uncertainty in crop water footprint (in m 3 t −1 ) estimates related to uncertainties in important input variables. The study focuses on the green (from rainfall) and blue (from irrigation) water footprint of producing maize, soybean, rice, and wheat at the scale of the Yellow River basin in the period 1996-2005. A grid-based daily water balance model at a 5 by 5 arcmin resolution was applied to compute green and blue water footprints of the four crops in the Yellow River basin in the period considered. The one-at-a-time method was carried out to analyse the sensitivity of the crop water footprint to fractional changes of seven individual input variables and parameters: precipitation (PR), reference evapotranspiration (ET 0 ), crop coefficient (K c ), crop calendar (planting date with constant growing degree days), soil water content at field capacity (S max ), yield response factor (K y ) and maximum yield (Y m ). Uncertainties in crop water footprint estimates related to uncertainties in four key input variables: PR, ET 0 , K c , and crop calendar were quantified through Monte Carlo simulations.The results show that the sensitivities and uncertainties differ across crop types. In general, the water footprint of crops is most sensitive to ET 0 and K c , followed by the crop calendar. Blue water footprints were more sensitive to input variability than green water footprints. The smaller the annual blue water footprint is, the higher its sensitivity to changes in PR, ET 0 , and K c . The uncertainties in the total water footprint of a crop due to combined uncertainties in climatic inputs (PR and ET 0 ) were about ±20 % (at 95 % confidence interval). The effect of uncertainties in ET 0 was dominant compared to that of PR. The uncertainties in the total water footprint of a crop as a result of combined key input uncertainties were on average ±30 % (at 95 % confidence level).

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Sensitivity analysis of a Penman–Monteith type equation to estimate reference evapotranspiration in southern Spain

Cited by 95 publications

References 27 publications

Sensitivity of soil evaporation and reference evapotranspirationto climatic variables in South Korea

Sensitivity of soil evaporation and reference evapotranspirationto climatic variables in South Korea

Parameterization of Evapotranspiration Estimation for Two Typical East Asian Crops

Sensitivity and uncertainty in crop water footprint accounting: a case study for the Yellow River basin

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