New cognition on the response of reference evapotranspiration to climate change in China using an independent climatic driver system

2022 ◽  
Vol 262 ◽  
pp. 107445
Juying Sun ◽  
Genxu Wang ◽  
Xiangyang Sun ◽  
Zhaoyong Hu ◽  
Shan Lin ◽  
Agronomy ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 416
Barbara Jagosz ◽  
Stanisław Rolbiecki ◽  
Roman Rolbiecki ◽  
Ariel Łangowski ◽  
Hicran A. Sadan ◽  

Climate warming increases the water needs of plants. The aim of this study was to estimate the water needs of grapevines in central Poland. Water needs were calculated using the crop coefficients method. Reference evapotranspiration was assessed by the Blaney–Criddle’s equation, modified for climate conditions in Poland. Crop coefficients were assumed according to the Doorenbos and Pruitt method. Water needs were calculated using the data from four meteorological stations. Rainfall deficit with the probability occurrence of normal years, medium dry years, and very dry years was determined by the Ostromęcki’s method. Water needs of grapevines during the average growing season were estimated at 438 mm. Upward time trend in the water needs both in the period of May–October and June–August was estimated. Temporal variability in the water needs was significant for all of the provinces. These changes were mainly impacted by a significant increasing tendency in mean air temperature and less by precipitation totals that did not show a clear changing tendency. Due to climate change, vineyards will require irrigation in the near future. The use of resource-efficient irrigation requires a precise estimate of the grapevines’ water needs. The study identified the water requirements for grapevines in central Poland.

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 666 ◽  
Maryam Bayatvarkeshi ◽  
Binqiao Zhang ◽  
Rojin Fasihi ◽  
Rana Muhammad Adnan ◽  
Ozgur Kisi ◽  

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.

2016 ◽  
Vol 48 (5) ◽  
pp. 1391-1401 ◽  
Parisa Hosseinzadehtalaei ◽  
Hossein Tabari ◽  
Patrick Willems

Projections of evapotranspiration form the basis of future runoff and water availability assessment in a climate change context. The scarcity of data or insufficiency of time/funds compels the application of simple reference evapotranspiration (ETo) methods requiring less meteorological inputs for ETo projections which adds uncertainty to the projected changes. This study investigates the bias in ETo climate change signals derived from seven simple temperature- and radiation-based methods (Blaney–Criddle, Hargreaves–Samani, Schendel, Makkink, Turc, Jensen–Haise, Tabari) compared with that from the standard Penman–Monteith FAO 56 method on the basis of 12 general circulation model (GCM) outputs from the Coupled Model Intercomparison Project Phase 5 for central Belgium for four future greenhouse gas scenarios (RCP2.6, RCP4.5, RCP6.0, RCP8.5). The results show the lack of conformity on the amount of ETo changes between the simple and standard methods, with biases of over 100% for some simple methods. The uncertainty affiliated with ETo methods for monthly ETo changes is smaller but of comparable magnitude to GCM uncertainty, which is usually the major source of uncertainty, and larger for daily extreme ETo changes. This emphasizes the imperative of addressing the uncertainty associated with ETo methods for quantifying the hydrological response to climate change.

2017 ◽  
Mengsheng Qin ◽  
Lu Hao ◽  
Lei Sun ◽  
Yongqiang Liu ◽  
Ge Sun

Abstract. Reference evapotranspiration (ETo) is an important hydrometeorological term widely used in water resource management, hydrological modeling, and understanding and projecting the hydrological effects of future climate change and land use change. Identifying the individual climatic controls on ETo helps better understand the processes of global climatic change impacts on local water resources and also simplify modeling efforts to predict actual evapotranspiration. We conducted a case study on the Qinhuai River Basin (QRB), a watershed dominated by a humid subtropical climate and mixed land uses in southern China. Long term (1961–2012) daily meteorological data at six weather stations across the watershed were used to estimate ETo by the FAO-56 Penman−Monteith model. The seasonal and annual trends of ETo were examined using the Mann−Kendall nonparametric test. The individual contributions from each meteorological variable were quantified by a detrending method. The results showed that basin-wide annual ETo had a decreasing trend during 1961–1987 due to decreased wind speed (WS), solar radiation (Rs), vapor pressure deficit (VPD), and increased relative humidity (RH). These variables had different magnitudes of contribution to the ETo trend in different seasons examined during 1961−1987. However, during 1988–2012, both seasonal and annual ETo showed an increasing trend, mainly due to increased VPD and decreased RH and, to lesser extent, to decreased absolute humidity (AH) and a rising air temperature. We show that the key climatic controls on ETo have dramatically shifted as a result of global climate change during the past five decades. Now the atmospheric demand, instead of air temperature alone, is a major control on ETo. Thus, we conclude that accurately predicting current and future ETo and hydrological change under a changing climate must consider changes in VPD (i.e., air humidity and temperature) in the study region. Water resource management in the study basin must consider the increasing trend of ETo to meet the associated increasing water demand for irrigation agriculture and domestic water uses.

2021 ◽  
Junaid Maqsood ◽  
Aitazaz A. Farooque ◽  
Farhat Abbas ◽  
Travis Esau ◽  
Xander Wang ◽  

Abstract Evapotranspiration, one of the major elements of the water cycle, is sensitive to climate change. The main objective of this study was to examine the response of reference evapotranspiration (ET0) under various climate change scenarios using artificial neural networks and a general circulation model (GCM) - the Canadian Earth System Model Second Generation (CanESM2). The Hargreaves method was used to calculate ET0 for western, central, and eastern parts of Prince Edward Island. The two input parameters of the Hargreaves method; daily maximum temperature (Tmax), and daily minimum temperature (Tmin) were projected using CanESM2. The Tmax and Tmin were downscaled with the help of statistical downscaling and simulation model (SDSM) for three future periods 2020s (2011–2040), 2050s (2041–2070), and 2080s (2071–2100) under three representative concentration pathways (RCP’s) including RCP 2.6, RCP P4.5, and RCP 8.5, and the. Temporally, there were major changes in Tmax, Tmin, and ET0 for the 2080s under RCP8.5. The temporal variations in ET0 for all RCPs matched the reports in the literature for other similar locations and for RCP8.5 it ranged from 1.63 (2020s) to 2.29 mm/day (2080s). As a next step, a one-dimensional convolutional neural network (1D-CNN), long-short term memory (LSTM), and multilayer perceptron (MLP) were used for estimating ET0 due to the non-linear behavior of ET0 and the limited meteorological input data. High coefficient of correlation (r > 0.95) values for both calibration and validation periods showed the potential of the artificial neural networks in ET0 estimation. The results of this study will help decision makers and water resource managers to quantify the availability of water in future for the island and to optimize the use of island water resources on a sustainable basis.

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