Analysis of Changes in Reference Evapotranspiration, Pan Evaporation, and Actual Evapotranspiration and Their Influencing Factors in the North China Plain During 1998–2005

Liu, Yujie; Chen, J.; Pan, Tao

doi:10.1029/2019ea000626

Cited by 31 publications

(20 citation statements)

References 52 publications

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“…The NCP is a major wheat‐producing region of China. The region has a temperate semihumid monsoon climate (Liu, Chen, & Pan, 2019). During the past 31 years (1985–2016), the mean annual temperature was about 13.1°C, and the mean annual precipitation was 561 mm, with about 70% of precipitation from June to September.…”

Section: Methodsmentioning

confidence: 99%

Wheat morpho‐physiological traits and radiation use efficiency under interactive effects of warming and tillage management

Hou

Tao

2020

Plant Cell & Environment

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Understanding the interactive effects of different warming levels and tillage managements on crop morphological and physiological traits and radiation use efficiency (RUE) is essential for breeding climate‐resilient cultivars. Here, we conducted temperature free‐air controlled enhancement (T‐FACE) experiments on winter wheat during two growth seasons in the North China Plain. The experiments consisted of three warming treatments and two tillage treatments (CT: conventional tillage and NT: no‐tillage). In the normal season, warming had significant positive effects on major morphological and physiological traits and increased significantly RUE of yield (RUEY) and biomass (RUEDM) by 13.3 and 11.3%, 19.3 and 12.4%, 42.3 and 43.7%, respectively, under the treatments of CTT1, CTT2 and NTT1 relative to the control (CTN, NTN). By contrast, in the warmer season, warming had negative effects on leaf width, light extinction coefficient, light‐saturated net photosynthetic rate, aboveground, stems and spike biomass and RUE from anthesis to maturity, and consequently grain yield under conventional tillage, but positive effects under no‐tillage. Our findings bring new insights into the mechanisms on the interactive effects of warming and tillage treatments on wheat growth and productivity; provide valuable information on crop ideotypic traits for breeding climate‐resilient crop cultivars.

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Section: Methodsmentioning

confidence: 99%

Wheat morpho‐physiological traits and radiation use efficiency under interactive effects of warming and tillage management

Hou

Tao

2020

Plant Cell & Environment

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“…As a variable measuring the evaporative demand of the atmosphere, reference crop evapotranspiration (ETo) has been widely used to estimate potential water loss from the land surface to the atmosphere (Hopson and Webster, 2009;Liu et al, 2019;Renard et al, 2010). Quantification of ETo has been increasingly performed to support efficient water use and water management (Mushtaq et al, 2019;Perera et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Bias-correcting input variables enhances forecasting of reference crop evapotranspiration

Yang

Wang

Hakala

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. Reference crop evapotranspiration (ETo) is calculated using a standard formula with temperature, vapor pressure, solar radiation, and wind speed as input variables. ETo forecasts can be produced when forecasts of these input variables from numerical weather prediction (NWP) models are available. As raw ETo forecasts are often subject to systematic errors, statistical calibration is needed for improving forecast quality. The most straightforward and widely used approach is to directly calibrate raw ETo forecasts constructed with the raw forecasts of input variables. However, the predictable signal in ETo forecasts may not be fully implemented by this approach, which does not deal with error propagation from input variables to ETo forecasts. We hypothesize that correcting errors in input variables as a precursor to forecast calibration will lead to more skillful ETo forecasts. To test this hypothesis, we evaluate two calibration strategies that construct raw ETo forecasts with the raw (strategy i) or bias-corrected (strategy ii) input variables in ETo forecast calibration across Australia. Calibrated ETo forecasts based on bias-corrected input variables (strategy ii) demonstrate lower biases, higher correlation coefficients, and higher skills than forecasts produced by the calibration using raw input variables (strategy i). This investigation indicates that improving raw forecasts of input variables could effectively reduce error propagation and enhance ETo forecast calibration. We anticipate that future NWP-based ETo forecasting will benefit from adopting the calibration strategy developed in this study to produce more skillful ETo forecasts.

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Section: Introductionmentioning

confidence: 99%

Comment on hess-2021-69

2021

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Reference crop evapotranspiration (ETo) is calculated using a standard formula with temperature, vapor pressure, solar radiation, and wind speed as input variables. ETo forecasts can be produced when forecasts of these input variables from numerical weather prediction (NWP) models are available. As raw ETo forecasts are often subjective to systematic errors, calibration is necessary for improving forecast quality. The most straightforward and widely used approach is to directly calibrate raw ETo forecasts constructed with the raw forecasts of input variables. However, the potential predictability of ETo may not be fully explored by this approach, which ignores the non-linear interactions of input variables in constructing ETo forecasts. We hypothesize that reducing errors in individual inputs as a precursor to ETo forecast calibration will lead to more skillful ETo forecasts. To test this hypothesis, we evaluate two calibration strategies, including i) calibration directly applied to raw ETo forecasts constructed with raw forecasts of input variables, and ii) bias-correcting input variables first, and then calibrating the ETo forecasts constructed with bias-corrected input variables. We calibrate ETo forecasts based on weather forecasts of the Australian Community Climate and Earth System Simulator G2 version (ACCESS-G2). Calibrated ETo forecasts with bias-corrected input variables (strategy ii) demonstrate lower bias, higher correlation coefficient, and higher skills than the calibration based on raw input variables (strategy i). This investigation indicates that improving raw forecasts of input variables could enhance ETo forecast calibration and produce more skillful ETo forecasts. This calibration strategy is expected to enhance future NWP-based ETo forecasting. IntroductionAs a variable measuring the evaporative demand of the atmosphere, reference crop evapotranspiration (ETo) has been widely used to estimate potential water loss from the land surface to the atmosphere (Hopson and Webster, 2009;Liu et al., 2019;Renard et al., 2010). Quantification of ETo has been increasingly performed to support efficient water use and water management (Mushtaq et al., 2019;Perera et al., 2016). Forecasts of short-term ETo (days to weeks) are highly valuable for real-time decision-making on farming activities and water allocation to competing users (Djaman et al., 2018;Kumar et al., 2012).A plethora of methods with divergent statistical assumptions, dependence on observations, and requirements of weather forecasts have been developed to predict future ETo (

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Analysis of Changes in Reference Evapotranspiration, Pan Evaporation, and Actual Evapotranspiration and Their Influencing Factors in the North China Plain During 1998–2005

Cited by 31 publications

References 52 publications

Wheat morpho‐physiological traits and radiation use efficiency under interactive effects of warming and tillage management

Wheat morpho‐physiological traits and radiation use efficiency under interactive effects of warming and tillage management

Bias-correcting input variables enhances forecasting of reference crop evapotranspiration

Comment on hess-2021-69

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