ET0 Values Research Articles

Quantitative Analysis of the Impact of Meteorological Factors on Reference Evapotranspiration Changes in Beijing, 1958–2017

The effects of meteorological factors on reference evapotranspiration (ET0) are variable on different time scales, although research tends to focus only on certain time scales. Therefore, using the meteorological data from 1958 to 2017 of Beijing, China, ET0 values over the last 60 years were calculated using Penman–Monteith method. The variation in ET0 values was thus analyzed against four meteorological factors over different time scales. The sensitivity of ET0 to these factors was assessed using a sensitivity coefficient, while the contribution of each factor to ET0 change was quantified by combining this sensitivity coefficient with the factor’s relative change rate over multiple time scales. The results showed that the sensitivity coefficient of relative humidity over different time scales were all negative, while the sensitivity coefficients of net radiation, temperature and wind speed were mostly positive. The main sensitivity factors of ET0 on different time scales varied. On annual time scales, the main factors were relative humidity and temperature. Over annual time scales, relative humidity and net radiation alternated as the main sensitivity factor; while over interannual time scales, the most sensitive factor was relative humidity during 1958–1979 and net radiation thereafter. The contribution of these four meteorological factors to ET0 also fluctuated greatly on intra-annual time scales. On daily time scales, the contributions of temperature and wind speed at the start and end of the year were large, while net radiation and relative humidity were dominant mid-year. On monthly to seasonal time scales, the contributions of these four meteorological factors to ET0 were notable. The contribution of relative humidity was largest in spring and autumn; net radiation was dominant in summer, while temperature and wind speed were dominant in winter. This research on the temporal variability of ET0 response factors is of great significance for understanding regional climate change.

Long-term effects of climatic and hydrological variation on natural vegetation production and characteristics in a semiarid watershed: The northern Negev, Israel

Climate models for semiarid and arid regions predict increasing average temperatures and reduced amounts of total annual rainfall. This warming and drying trend could have critical, adverse effects on natural vegetation activity and survival in arid and semiarid zones. We investigated the long-term effects of climate change and surface-runoff variations on the production of natural vegetation in a dry, undisturbed, first-order watershed in the northern Negev, Israel. Vegetation dynamics were estimated by normalized difference vegetation index. Yearly annual vegetation cover varied greatly during the monitoring period (2000−2013), but a significant positive regression was found with annual rainfall and runoff amounts, suggesting a strong relationship between annual vegetation dynamics and rainfall amount in a given year. A significant positive linear regression was found between annual ET0 values and year of measurement (1994–2013), with no corresponding decrease in vegetation condition. Surface runoff in the watershed affected the vegetation's water source. Large variation in annual runoff amounts was observed for 1994–2011, averaging 22.3 and 9 mm for the first (2000–2006) and second (2007–2013) vegetation-monitoring subperiods, respectively. Perennial vegetation was less sensitive to drought years than annual vegetation, likely due to differences in water-source availability. Perennials also benefited from the arrival of nutrients, organic matter, and fertile soil flowing with the surface runoff and eroded soil into their growing area.

Effect of meteorological data quality control and data adjustment on the reference evapotranspiration: a case study in Jafariye, Iran

Irrigation water management as an essential strategy to prevent water stress in the arid and semiarid regions of the world strongly relies on the appropriate estimation of reference evapotranspiration (ET0). Validated and high-quality meteorological data are required to estimate ET0 appropriately. In this study, to improve ET0 estimations, the data quality control approach was applied to weather parameters obtained from Jafariye agricultural automatic weather station (AWS), Qom, Iran. All parameters were measured from 16 July 2011 to 8 June 2018. After removing outlier data, the integrity of weather data was investigated using the range, step, internal consistency, and persistence tests. Inlier errors that pass all of the quality control procedures were detected. Modifications and adjustment methods were applied to correct weather data, and ET0 calculated with original, modified, and adjusted datasets. Range test flagged 0.85% and 0.6% of solar radiation and wind speed values, respectively. The most suspected data were indicated by the internal consistency test which was 35.6% of wind speed data. Persistence test flagged 2.2% of wind speed values as well. Quality control and adjustment methods increased ET0 values by 21% and 27% on average throughout the entire period, respectively, while the maximum variation due to the application of adjustment methods was 9% that occurred in 2013. Results showed that the proposed quality control procedures could improve the reliability of weather data of automatic weather stations.

Investigation into the Effects of Climate Change on Reference Evapotranspiration Using the HadCM3 and LARS-WG

This study evaluates the effect of climate change on reference evapotranspiration (ET0), which is one of the most important variables in water resources management and irrigation scheduling. For this purpose, daily weather data of 30 Iranian weather stations from 1981 and 2010 were used. The HadCM3 statistical model was applied to report the output subscale of LARS-WG and to predict the weather information by A1B, A2, and B1 scenarios in three periods: 2011–2045, 2046–2079, and 2080–2113. The ET0 values were estimated by the Ref-ET software. The results indicated that the ET0 will rise from 2011 to 2113 approximately in all stations under three scenarios. The ET0 changes percentages in the A1B scenario during three periods from 2011 to 2113 were found to be 0.98%, 5.18%, and 12.17% compared to base period, respectively, while for the B1 scenario, they were calculated as 0.67%, 4.07%, and 6.61% and for the A2 scenario, they were observed as 0.59%, 5.35%, and 9.38%, respectively. Thus, the highest increase of the ET0 will happen from 2080 to 2113 under the A1B scenario; however, the lowest will occur between 2046 and 2079 under the B1 scenario. Furthermore, the assessment of uncertainty in the ET0 calculated by the different scenarios showed that the ET0 predicted under the A2 scenario was more reliable than the others. The spatial distribution of the ET0 showed that the highest ET0 amount in all scenarios belonged to the southeast and the west of the studied area. The most noticeable point of the results was that the ET0 differs from one scenario to another and from a period to another.

Computation of daily Penman–Monteith reference evapotranspiration in the Carpathian Region and comparison with Thornthwaite estimates

Abstract. The Pannonian Basin Experiment (PannEx) is a Regional Hydroclimate Project (RHP) of the World Climate Research Programme (WCRP) Global Energy and Water Exchanges (GEWEX) Project. A gridded meteorological dataset is available for the PannEx region as part of the CarpatClim database, which consists of homogenized and harmonized daily meteorological observations for several climate parameters with 0.1∘ spatial resolution in the period of 1961–2010. The estimation of the Penman–Monteith reference evapotranspiration (ET0) on the daily scale was performed for the CarpatClim grid as one of the first results in the PannEx initiative. This study compares the already accessible Thornthwaite estimates of potential evapotranspiration (PET_Th) on the monthly scale to the newly derived Penman–Monteith estimates. The comparison is made on an annual and seasonal basis for the 50-year period. The distribution of both estimates is influenced by geographical location and orographic features. The annual time series are similar but the regional-average annual values of ET0 are ∼80 mm greater than the Thornthwaite estimate in the whole CarpatClim region. The relative bias and root mean square error was computed as well. The classical Thornthwaite method underestimates the ET0 by more than 20 % over extensive regions for selected grid points at elevations lower than 200 m in the Pannonian Basin. The slope of the fitted linear trend indicate increasing reference evapotranspiration in the Pannonian/Carpathian Basin due to climate change.

Spatiotemporal variation in reference evapotranspiration and its contributing climatic factors in China under future scenarios

AbstractGlobal climate change is likely to affect reference evapotranspiration (ET0), which is important for agricultural water resources and food security. Analysis of ET0 changes is also important for understanding climate change and its impacts on hydrology. In this study, ET0 was calculated from 2020 to 2099 in nine agricultural regions and the entire country of China utilizing the Penman–Monteith method based on bias‐corrected climate data from the global climate models MIROC‐ESM‐CHEM, NorES1‐M, IPSL‐CM5A‐LR, GFDL‐ESM 2M and HadGEM2‐ES under future climate change scenarios. The spatiotemporal characteristics of seasonal and annual ET0 and climatic variables were analysed based on the Mann–Kendall test with trend‐free prewhitening (TFPW‐MK) and Sen's slope estimator. Sensitivity coefficient and multivariate regression were used to identify factors controlling the change in ET0. The results showed that seasonal and annual air temperature and precipitation both increased under all climate scenarios, and the majority of relative humidity and wind speed values showed downward trends during 2020–2099. The lowest annual ET0 values were found in the NECR and QTR, and the SCR had the maximum ET0. Both the TFPW‐MK and slope statistics showed an upward trend of seasonal ET0 during 2020–2059 under all scenarios. During 2060–2099, seasonal ET0 values showed a slight and nonsignificant downward trend under RCP 2.6, while upward trends were produced in other scenarios. Areas with high ET0 values were located in the SCR, GXR and HHHR, while low ET0 values mainly occurred in the NECR and QTR. The ET0 for the four seasons in the SCR was higher than that in the other regions, and the summer ET0 was the highest compared with that in the other seasons overall. For the attribution assessment, Tavg is the main controlling variables to ET0 trends under the interaction of multiple climatic factors though RH is the most sensitive.

Spatial and Temporal Variations of Potential Evapotranspiration in the Loess Plateau of China During 1960–2017

Potential evapotranspiration (ET0) is an integral component of the hydrological cycle and the global energy balance, and its long-term variation is of much concern in climate change studies. The Loess Plateau is an important area of agricultural civilization and water resources research. This study analyzed the spatial and temporal evolution processes and influential parameters of ET0 at 70 stations in different topographical areas of the Chinese Loess Plateau (CLP). Using the Mann–Kendall trend, Cross wavelet transform, and the ArcGIS platform, the ET0 of each station was quantified using the Penman–Monteith equation, and the effects of climatic factors on ET0 were assessed by analyzing the correlation coefficients and contribution rates of the climatic factors. The results showed that: (1) the overall trend of the ET0 in different terrains of the Loess Plateau is consistent, however, the ET0 values differ; the hill region (HR) has the highest ET0, followed by the valley region (VR), and the mountain region (MR) has the lowest, and ET0 changes differ between seasons. (2) Spatial distribution characteristics of multiyear mean ET0 in the study are as follows: the ET0 values in mountain and hilly areas are decreasing from west to east, and the higher mean annual ET0 value in the VR is mainly concentrated in the eastern CLP. (3) In the past 58 years, the annual mean and the seasonal ET0 of the region showed increasing trends, however, differences in different terrains were obvious. (4) ET0 has significant correlations with El Niño–Southern Oscillation (ENSO), Pacific–North American teleconnection (PNA), and Atlantic Multidecadal Oscillation (AMO). The resonance period of ET0 and ENSO was 3–6 a, mainly in 1976–1985. The mean coherence phase angle was close to 360°, indicating that ET0 lags behind PNA by approximately 2–6 a; ET0 has a very strong positive correlation with AMO. (5) Relative humidity (RH) is the main influencing factor of ET0 change in the Loess Plateau. Temperature (T) variation has the highest contribution rate (42%) to the regional ET0 variation in the entire CLP. We should pay more attention to the variation of evaporation under future climate change, especially temperature change.

Estimation of Daily Actual Evapotranspiration Using Vegetation Coefficient Method for Clear and Cloudy Sky Conditions

Actual evapotranspiration (AET) can be studied and estimated using remote-sensing-based methods at multiple spatial and temporal scales. Reflectance and Land surface temperature are essential in these methods. However optical and thermal sensors fail to provide these data under overcast conditions and this creates gap in the AET product. Besides, there is a necessity of the AET method that requires less data and estimates AET with better accuracy. In this regard, AET was estimated for all-sky conditions using the vegetation coefficient (VI-Kv) method utilizing microwave, thermal, and optical data. Essential reference evapotranspiration (ET0) under cloudy conditions was estimated using LST-based Penman-Monteith temperature (PMT) and Hargreaves-Samani equations. Furthermore, LST predicted using the microwave polarization difference index (PLST) and LST of moderate resolution imaging spectroradiometer (MODIS) cloud product (MLST) were evaluated with in-situ air temperature (Ta) under cloudy sky conditions. Results revealed that the PLST correlated better with Ta than MLST with correlation coefficient (r) values of 0.71 and 0.81 for day and night times, respectively. Hence, PLST-based solar radiation (Rs) estimation yielded better accuracy with observed Rs with r and root mean square error values of 0.864 and 0.07 for Berambadi station under cloudy conditions, respectively. PMT-based ET0 values corresponded well with the observed ET0 under cloudy sky condition during this study. In addition, AET estimated using the VI-Kv method was compared with the simple two-source energy balance (TSEB) method under clear sky conditions. It was found that the improved VI-Kv method performed better than the TSEB method and could also fairly estimate AET even under cloudy sky conditions.

Characteristics and Drivers of Reference Evapotranspiration in Hilly Regions in Southern China

This paper has adopted related meteorological data collected by 69 meteorological stations between 1951 and 2013 to analyze changes and drivers of reference evapotranspiration (ET0) in the hilly regions located in southern China. Results show that: (1) ET0 in southern China’s hilly regions reaches its maximum in summer and its minimum in winter, and that the annual ET0 shows an increasing trend. ET0 happened abrupt change due to the impact of abrupt meteorological variables changes, and the significant year of mutation were 1953, 1964 and 2008. Most abrupt changes of ET0 in meteorological stations occurred in the 1950s and 1960s. (2) The low value of ET0 was mainly captured in high-altitude areas. Spatially, the ET0 in the east was higher than that in the west. With the exception of a handful of stations, the trend coefficients of ET0 were all positive, exhibiting a gradual rise. Changes in ET0 in the east were much more sensitive than that in the west. Since ET0 was affected by the cyclical changes in relative humidity, short-period oscillations were observed in all these changes. (3) In general, the ET0 was negatively correlated with relative humidity, and positively correlated with temperature and sunshine percentage. ET0 is most sensitive to changes in average temperature, with a sensitivity coefficient of 1.136. ET0 showed positive sensitivity to average temperature and sunshine hours, which were notable in the northeastern, and uniform in the spatial. ET0 showed negatively sensitivity to relative humidity, and the absolute value of sensitivity coefficient in the northwestern is smaller. The highest contribution to ET0 is the average temperature (6.873%), and the total contribution of the four meteorological variables to the change of ET0 is 7.842%. The contribution of average temperature, relative humidity, and sunshine hours to ET0 is higher in the northern and eastern, northern, northern and eastern areas, respectively. Climate indexes (Western Pacific Index (WP), Southern Oscillation Index (SOI), Tropical Northern Atlantic Index (TNA), and El Niño-Southern Oscillation (ENSO)) were correlated with the ET0. In addition, the ET0 and altitude, as well as the latitude and longitude were also correlated with each other.

Empirical and learning machine approaches to estimating reference evapotranspiration based on temperature data

The precise estimation of reference evapotranspiration (ET0) is crucial for the planning and management of water resources and agricultural production. In this study, the applicability of the Hargreaves Samani (HS), artificial neural network (ANN), multiple linear regression (MLR) and extreme learning machine (ELM) models were evaluated to estimate ET0 based on temperature data from the Verde Grande River basin, southeastern Brazil. These models were evaluated in two scenarios: local and pooled. In the local scenario, training, calibration and validation of the models were performed separately at each station. In the pooled scenario, meteorological data from all stations were grouped for training and calibration and then separately tested at each station. The ET0 values estimated by the Penman-Monteith model (FAO-56 PM) were considered the target data. All the developed models were evaluated by cluster analysis and the following performance indices: relative root mean square error (RRMSE), Pearson correlation coefficient (r) and Nash-Sutcliffe coefficient (NS). In both scenarios evaluated, local and pooled, the results revealed the superiority of the artificial intelligence methods (ANN and ELM) and the MLR model compared to the original and adjusted HS models. In the local scenario, the ANN (with r of 0.751, NS of 0.687 and RRMSE of 0.112), ELM (with r of 0.747, NS of 0.672 and RRMSE of 0.116) and MLR (with r of 0.743, NS of 0.665 and RRMSE of 0.068) models presented the best performance, in addition to being grouped in the same cluster. Similar to the observations from the local scenario, the ANN (with r of 0.718, NS of 0.555 and RRMSE of 0.165), ELM (with r of 0.724, NS of 0.601 and RRMSE of 0.151) and MLR (with r of 0.731, NS of 0.550 and RRMSE of 0.091) models presented the best performance in the pooled scenario and were grouped in the same cluster. The locally trained models presented higher precision than the models generated with pooled data; however, the models generated in the pooled scenario could be used to estimate ET0 in cases of unavailability of local meteorological data. Although the MLR, ANN and ELM models, based on temperature data, are appropriate alternatives to accurately estimate ET0 in the Verde Grande River basin, southeastern Brazil, the MLR model presents the advantage of the use of explicit algebraic equations, facilitating its application.

Variations of the Reference Evapotranspiration and Aridity Index Over Northeast China: Changing Properties and Possible Causes

Temporal and spatial variations in reference evapotranspiration (ET0) and aridity index (AI) can be used as important indexes for understanding climate change and its effects on ecosystem stability. Thus, in this work, we comprehensively investigated 71 meteorological stations in Northeast China from 1965 to 2017 to analyze the spatial-temporal variation and trend of ET0 and AI using the nonparametric Mann–Kendall test, the linear regression, and the Morlet wavelet methods. The results elucidated that ET0 for Northeast China as a whole exhibited a decrease at a rate of −1.97 mm/yr, AI declined at a rate of −0.01/yr during 1965–2017, and approximately 94% stations showed a decrease trend. Spatially, the high values of AI and ET0 were primarily at the western part of the study area except for the Heilongjiang province, and the stations showing low values were mainly distributed in the central and eastern part. The decreasing trends for AI were more obvious in the eastern part compared with the western part over the study region. The abrupt changes in AI occurred in 2005 and 2007, whereas only one abrupt change for ET0 occurred in 1995. For annual ET0, there were periods of 3, 7, 11, and 15 yr, and there existed periods of 1, 7, 11, and 13 yr for annual AI. The correlation coefficients implied wind speed and precipitation were the dominant meteorological factors resulting in the ET0 and AI decrease, respectively. Additionally, the change of the Indian summer monsoon index (ISMI) may also contribute to the weakened AI in the study area. Nevertheless, further investigation is still required to clarify the mechanisms for AI and ET0 variations in the future.

Actual evapotranspiration of subalpine meadows in the Qilian Mountains, Northwest China

As a main component in water balance, evapotranspiration (ET) is of great importance for water saving, especially in arid and semi-arid areas. In this study, the FAO (Food and Agriculture Organization) Penman-Monteith model was used to estimate the magnitude and temporal dynamics of reference evapotranspiration (ET0) in 2014 in subalpine meadows of the Qilian Mountains, Northwest China. Meanwhile, actual ET (ETc) was also investigated by the eddy covariance (EC) system. Results indicated that ETc estimated by the EC System was 583 mm, lower than ET0 (923 mm) estimated by the FAO Penman-Monteith model in 2014. Moreover, ET0 began to increase in March and reached the peak value in August and then declined in September, however, ETc began to increase from April and reached the peak value in July, and then declined in August. Total ETc and ET0 values during the growing season (from May to September) were 441 and 666 mm, respectively, which accounted for 75.73% of annual cumulative ETc and 72.34% of annual cumulative ET0, respectively. A crop coefficient (kc) was also estimated for calculating the ETc, and average value of kc during the growing season was 0.81 (ranging from 0.45 to 1.16). Air temperature (Ta), wind speed (u), net radiation (Rn) and soil temperature (Ts) at the depth of 5 cm and aboveground biomass were critical factors for affecting kc, furthermore, a daily empirical kc equation including these main driving factors was developed. Our result demonstrated that the ETc value estimated by the data of kc and ET0 was validated and consistent with the growing season data in 2015 and 2016.

An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration.

Reference evapotranspiration (ET0) plays a fundamental role in irrigated agriculture. The objective of this study is to simulate monthly ET0 at a meteorological station in India using a new method, an improved support vector machine (SVM) based on the cuckoo algorithm (CA), which is known as SVM-CA. Maximum temperature, minimum temperature, relative humidity, wind speed and sunshine hours were selected as inputs for the models used in the simulation. The results of the simulation using SVM-CA were compared with those from experimental models, genetic programming (GP), model tree (M5T) and the adaptive neuro-fuzzy inference system (ANFIS). The achieved results demonstrate that the proposed SVM-CA model is able to simulate ET0 more accurately than the GP, M5T and ANFIS models. Two major indicators, namely, root mean square error (RMSE) and mean absolute error (MAE), indicated that the SVM-CA outperformed the other methods with respective reductions of 5–15% and 5–17% compared with the GP model, 12–21% and 10–22% compared with the M5T model, and 7–15% and 5–18% compared with the ANFIS model, respectively. Therefore, the proposed SVM-CA model has high potential for accurate simulation of monthly ET0 values compared with the other models.

Calibration and Validation of the Hargreaves‐Samani Model for Reference Evapotranspiration Estimation in China

AbstractDaily meteorological data of 12 years from 838 stations over China were collected and applied to calibrate the HS model by comparison between the values of ET0 calculated from the original HS and those from the PM model. The calibrated HS model was evaluated by the distribution and values of statistical indices. After calibration, the mean values of the mean absolute error (MAE) and the root mean square error (RMSE) decreased by 24.6 and 23.9%, respectively. The correlation coefficients (R) for most areas were greater than 0.9, and the minimum R increased by 2% compared with the values of the original. The minimum and maximum slope of the zero‐intercept regression lines changed from 0.839 to 0.898 and from 1.46 to 1.04 during the validation period, respectively. The distribution of the statistical indices also showed better performance in most areas. The calibrated HS model produced the greatest ET0 estimation in the subtropical monsoon climate zone and the south‐western part of the temperate monsoon climate zone. Although the performance of the HS model improved after calibration in the plateau and mountain climate and temperate monsoon climate zones, the original HS model had high enough accuracy. However, for the tropical climate regions, the HS model failed to give reliable results even in calibrated form. Overall, the study illustrated that the calibrated HS model has higher accuracy for most climate zones. © 2019 John Wiley & Sons, Ltd.

Detecting linear trend of reference evapotranspiration in irrigated farming areas in Brazil’s semiarid region

Northeast Brazil’s semiarid region is characterized by water deficit. However, little is known about the trends in joint water loss by evaporation and transpiration (evapotranspiration) in the region. Thus, this study aimed to analyze indications on the linear trend of reference evapotranspiration (ET0) in the monthly, annual, and interdecadal scales in irrigated agricultural areas in the microregions of Juazeiro, Bahia State (9° 24’ S; 40° 26’ W and 375.5 m), and Petrolina, Pernambuco State (09° 09’ S, 40° 22’ W, and 376 m). For this purpose, we used a set of daily meteorological data, collected from January 1, 1976, to December 31, 2014. Daily ET0 values were estimated by the FAO’s Penman-Monteith equation (ET0PM). The main statistical tests used were the nonparametric Mann-Kendall test, the Sen test to detect the magnitude of the trend, and the Pettitt test to detect the start of the trend. For all tests, statistical significance was 5% and/or 1%. Analysis of variance (ANOVA) was also applied to identify significant differences between the mean interdecadal values for each season. The results showed a significant decreasing trend for ET0 in both Juazeiro (α = 5%) and Petrolina (α = 1%), with declines of 14.5 mm/year (Juazeiro) and 7.7 mm/year (Petrolina) and that this trend started in 1996. Probably, the ET0 decrease was associated with the increase in the irrigated agricultural areas, and the lake formed upstream from the areas by the construction of Sobradinho Dam.

Variation of reference evapotranspiration and its teleconnection with multiple large‐scale climate oscillations in the Yangtze River Delta, China

Evapotranspiration is a key factor in regional hydrological processes and water resources management. Long‐term variation of evapotranspiration affects the regional climate wet/dry tendency and agricultural production profoundly. Thus, reference evapotranspiration (ET0) values for 46 meteorological stations in the Yangtze River Delta (YRD) were calculated for 1957–2014 using the FAO‐Penman–Monteith (FAO‐PM) method. The variation patterns of ET0 values were determined based on the principal component analysis (PCA) method. In addition, the methods of cross wavelet transform (CWT), Kendall tau‐b correlation coefficient determination and cross‐correlation method were applied in the assessment of the correlation between ET0 values and large‐scale climate oscillations, such as the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), the Oceanic Niño3.4 Sea Surface Temperature Index (NINO) and the Indian Ocean Dipole (IOD). Annual ET0 patterns for three dominant geographic subregions of the YRD (the southeastern, northwestern and mid‐eastern) were determined. There were only several discontinuous lower timescale bands between the three change patterns of annual ET0 and climate oscillations. In seasonal scale, the temporal patterns of ET0 changed simultaneously with the NAO, NINO and PDO in spring, the PDO in summer and the NAO in winter. The monthly ET0 was mostly influenced by the NAO and IOD in January, the IOD in February, the IOD and NINO in March, the NINO in June, the PDO in July to October, the NINO, IOD and NAO in October and the NINO in December. The lag times for the ET0 changes were about 0–5 months for the NAO and NINO, 1–2 months for the PDO and 4 months for the IOD.

Temporal Change of Climatological Precipitation Deficit Index in the Buyuk Menderes Basin, Turkey

Core Ideas Climatological precipitation deficit index is used to monitor agricultural drought by examining the difference between precipitation and evapotranspiration. The increasing trend determined in the precipitation deficit derived more from the increases determined in the ET0 values than from the decrease in precipitation. A suitable threshold value must be set when classifying precipitation deficit, which is in accordance with the conditions of the region in designating drought years. Climatological precipitation deficit index (PD) is one the indices used to monitor agricultural drought by examining the difference between precipitation and evapotranspiration. In this study, the meteorological stations located in the Buyuk Menderes Basin, which has an important agricultural potential for Turkey, are used to determine the PD and its temporal variation by Mann–Kendall trend analysis using the monthly climate data of the period 1975 to 2014. The long‐term average rainfall in the Buyuk Menderes Basin is 574 mm, the reference evapotranspiration is 1225 mm, and the average PD value is 651 mm. It was observed that the value of the precipitation deficit in the basin varies considerably in the long term. The trend analysis showed five of the six stations in the basin to have an increasing trend, which in three of these five stations was statistically significant. It was concluded that the increasing trend determined in the precipitation deficit derived more from the increases determined in the ET0 values than from the decrease in precipitation.

Estimation and comparison of reference evapotranspiration using different methods to determine olive trees irrigation schedule in different bioclimatic stages of Tunisia

The study of olive trees water requirements allows a better water management by using more accurate methods including maximum parameters of the continuum soil-plant- atmosphere. The Penman-Monteith equations is consideredas the most rational approach and the most reliable for calculating evapotranspiration. Only this approach necessarily requires an important number of climate parameters. The use of other equations, less complicated and using less climate parameters may be a reliable and efficient alternative. This experimental study was carried out on two cultivars cv. "Meski" and cv. "Chemlali" conducted in the intensive system in different bioclimatic stages (Subhumid, Semi-Arid and Arid) in Tunisia. This work aims to estimate olive trees water needs using evapotranspiration calculation in three different bioclimatic stages. For that, we compared the Penman-Monteith formula with Blaney-Criddel, Hargreaves-Temperature, Hargreaves- Radiation and Priestley-Taylor formulas to estimate reference evapotranspiration (ET0). Results show that ET0 values calculated by Priestley-Taylor and Blaney-Criddel formulas were more or less similar to Penman-Monteith. The ET0 values found by Hargreaves-Temperature and Hargreaves-Radiation were twice the values calculated by Penman-Monteith formula. We also found good correlations between the reference evapotranspiration calculated by the Penman-Monteith equation and that calculated by Priestley-Taylor and Blaney-Criddel equations in all bioclimatic stages (R2 more than 0.85, p < 1%). The ET0 sensitivity analysis has shown that solar radiation and air temperature (energetic climatic parameters) have the dominant effect on the ET0 at the level of the different climatic regions. Accordingly, in the case of lack of some climatic parameters and in sub-humid, semi-arid and arid conditions and for the different phenological stages of the olive tree, we can use Priestley-Taylor and/or Blaney-Criddle formulas to estimate water needs.

Performance of 12 reference evapotranspiration estimation methods compared with the Penman–Monteith method and the potential influences in northeast China

Reference evapotranspiration (ET0) is an important factor for agricultural activity and water management. Its estimation methods have significant regional differences. The Penman–Monteith (P‐M) method, which is recommended by the Food and Agriculture Organization (FAO), has been widely accepted, but it requires a large amount of data. This study analysed the performance of 12 ET0 estimation methods in different sub‐regions and periods by comparing them with the FAO P‐M method. Northeastern China was divided into eight sub‐regions according to their terrains and climates. Meteorological data obtained from 126 stations in these sub‐regions between the 1950s and 2014 were used to calculate the ET0 values. The performances were identified via four indices: root mean squared error, mean absolute error, average ratio and Spearman's correlation co‐efficient. The optimal method for agricultural areas was then modified by using linear regression analysis. The results are as follows: the Valiantzas2, Romanenko2 and H‐Makkink methods are recommended as alternative methods during the crop‐growing period, whereas the Turc and Hargreaves–Samani methods can generate significant biases. The Valiantzas2 and H‐Makkink methods are the optimal ones for estimating ET0 values in agricultural areas. Based on the outputs from the FAO P‐M method, ET0 values are most sensitive to temperature, accounting for 59.5%. Other methods that provide similar results can be considered as alternatives. Finally, the modified equation can provide the most accurate results, but drought events also affect the accuracy of the modified method.

A reference evapotranspiration map for Bosnia and Herzegovina

There are three major challenges for climatic data availability for Reference Evapotranspiration (ET0) calculations in Bosnia and Herzegovina: limited data availability, discontinuity of data records, and low station density. The main objective of this study was to apply reliable methods to calculate and spatially distribute ET0, while considering the impact of the elevation. A 20 m spatial resolution map was created for mean ET0 values at monthly, vegetation period (April–September) and annual temporal resolution at municipality (143 municipalities), regional (4 regions) and national spatial resolutions. 108 weather stations for the period 1961–2016 (56 years) were utilized for spatial interpolation of ET0 using kriging with external drift method. The required elevation for ET0 estimation at each grid node was extracted from the digital elevation model of Bosnia and Herzegovina. ET0 was calculated using FAO-56 Penman-Monteith, and in cases where only minimum and maximum temperature data were available the Hargreaves-Samani equation adjusted with locally appropriate empirical radiation coefficient was used. A gradual decrease of mean ET0 values from the southern to central and northern to central part of the country is notable. For the all seasons (monthly, vegetation and annually), the southern region has greater ET0 than the other three regions (north, west and central-east), which are similar. The long-term mean annual ET0 for Bosnia and Herzegovina is 716 mm, approximately 78% (559 mm) of which occurs during in the vegetation period.