Changes in reference evapotranspiration over the non‐monsoon region of China during 1961–2017: Relationships with atmospheric circulation and attributions

Abstract

Reference evapotranspiration (ET 0) is an essential component of the hydrological cycle and is crucial to water resources management and assessment. Spatiotemporal variations in ET 0 and their attribution to five climatic variables (maximum and minimum air temperatures, solar radiation, vapour pressure, and wind speed) were estimated for the non-monsoon region of China from 1961-2017 meteorological data by using the Penman-Monteith equation and the partial-differential method. The association between ET 0 and atmospheric circulation patterns was explored by applying Pearson's correlation analysis. The annual ET 0 series had two earlier shift points, the first showing a significant increase from 1961 to 1973 (period I) and the second showing a significant decrease from 1974 to 1994 (period II). ET 0 has significantly increased again since 1994 (period III). Wind speed has been the dominant contributing factor to ET 0 followed by maximum air temperature during all three periods, but the contribution gap between minimum and maximum air temperatures is narrowing. ET 0 has been strongly correlated with eight selected teleconnection indices in some regions, but the locations and spatial extents have varied considerably for different indices. Eight relationships with ET 0 were divided into four groups: North Atlantic Oscillation and Arctic Oscillation (mainly the northwest non-monsoon region), Pacific North American Index and Pacific Decadal Oscillation (mainly the northern non-monsoon region), Antarctic Oscillation and Atlantic Multidecadal Oscillation (mainly the Hexi Corridor and the southern Xinjiang), and East Asian Summer Monsoon Index and South China Sea Summer Monsoon Index (mainly the southeast non-monsoon region). The Antarctic Oscillation, Atlantic Multidecadal Oscillation, and South China Sea Summer Monsoon Index indicated more potential for predicting ET 0. When we used Pearson's correlation analysis to analyse the relationship between atmospheric circulation and the dominant factors affecting ET 0 , we found that the circulation patterns are likely to affect the variation in ET 0 by influencing the dominant climatic variables.

Information Entropy-Based Hybrid Models Improve the Accuracy of Reference Evapotranspiration Forecast

“…Due to low requirement of data input and good capability of data ftting, those models have been widely adopted to ET 0 forecast [12]. With a limited amount of meteorological factors, linear regression models such as Bayesian linear regression and ridge regression have shown advantages in ET 0 forecast in China [13], Mediterranean zones [14], and US High Plains [15]. Besides, several neural network models were introduced to forecast ET 0 , including BP neural networks and support vector machine models [16].…”

Assessing and comparing crop evapotranspiration in different climatic regions of China using reanalysis products

“…Irrigation management in agricultural practices requires accurate estimation of crop water consumption, which in turn requires accurate estimation of crop evapotranspiration (ET c ), and its forecasting is signi cant for developing crop irrigation systems and real-time irrigation scheduling (Feng et al 2017; Dong et al 2020; Mao et al2020). A commonly used ETc estimation method at the eld scale consists of using the K c -ET 0 approach as proposed in FAO56 (Janssen and Heuberger 1995; Allen et al 1998).…”

Assessing and Comparing Reference Evapotranspiration across Different Climatic Regions of China Using Reanalysis Products

“…Irrigation management in agricultural practices requires the accurate estimation of crop water consumption, which in turn requires an accurate estimation of crop evapotranspiration (ET c ), and its forecasting is significant in developing crop irrigation systems and real-time irrigation scheduling [5,6]. A commonly used ET c estimation method at the field scale consists of using the Kc-ET 0 approach, as proposed in FAO56 [7], where a crop coefficient (K c ) for the considered vegetation is multiplied by the crop reference evapotranspiration (ET 0 ) to estimate the ET c , although the calculation of K c is based on experience, and applications worldwide are successful [8][9][10].…”