Evapotranspiration Of Winter Wheat Research Articles

The impacts of irrigation methods and regimes on the water and nitrogen utilization efficiency in subsoiling wheat fields

Long-term rotary tillage limit water infiltration and crop productivity in North China Plain (NCP). The practice of subsoiling to fracture plow pans has made beneficial impacts on soil surface structure and water infiltration. Further, appropriate irrigation method coupled with irrigation regime can improve crop productivity in subsoiling condition. A three-year field trial (2020–2023) was carried out to assess the effects of the irrigation regime and the method on winter wheat evapotranspiration (ET), grain yield (GY), water productivity (WP), partial factor productivity from applied nitrogen (PPFN), and economic analysis. The three irrigation regimes were irrigated when soil moisture levels decreased to 70%, 60% and 50% of the field capacity (referred as H, M and L) and two irrigation methods were the surface drip irrigation (SDI) and the micro-sprinkler irrigation (MSI). The traditional flood irrigation with 70% of the field capacity in subsoiling filed was CK. The results showed optimizing irrigation method and irrigation regime significantly influenced ET, GY, WP, PPFN, and net incomes. As the irrigation amount increased, the ET first increased while GY, WP, PPFN, and net incomes increased and then slightly decreased. Based on the three-year average, the maximum GY of 9454 kg ha−1 and the net income of 11089 yuan ha−1 was achieved in SDI-M, which had WP of 2.3 kg m−3 and PPFN of 39.4 kg kg−1. At the same time, SDI-M did not result in much increase of ET (average of 405.1 mm in three seasons). Considering comprehensively ET, GY, WP, PPFN, and net incomes, to irrigate when soil moisture decreases to 60% of the field capacity by surface drip irrigation was the optimal strategy in all aspects. These results will provide a scientific reference for irrigation management in subsoiling wheat field in NCP, as well as in similar production areas worldwide.

Surface temperature adjustment in METRIC model for monitoring crop water consumption in North China Plain

Evapotranspiration is the real water consumption element in agricultural water management. In order to improve the efficiency of agricultural water use and maintain the sustainable development of agriculture, more and more attention has been paid to the improvement of monitoring and management of farmland evapotranspiration. In this study, MODIS data and the Temperature Vegetation Dryness Index (TVDI) were used in the METRIC model to estimate evapotranspiration for winter wheat and summer corn in the North China Plain. In order to decrease the error caused by the spatial heterogeneity of air temperature in the estimation of evapotranspiration, based on the characteristics of cold pixels with surface temperatures close to their air temperature, the TVDI was used to assist the selection of cold pixels and obtain the spatial variation trend of air temperature with latitude from all cold pixels in the study area. The influence of the spatial heterogeneity of air temperature on the surface temperature at the time of the satellite overpass was corrected accordingly, thereby the estimation accuracy of evapotranspiration was improved. A METRIC-TVDI model was established and the evapotranspiration of winter wheat and summer corn in Hebei Plain was estimated from 2017 to 2019. The average evapotranspiration of the winter wheat over these three years were 361 mm, 327 mm and 354 mm respectively, and that of summer corn were 394 mm, 388 mm and 405 mm respectively. Based on the farmland water balance, the irrigation water consumption (evapotranspiration minus precipitation) of winter wheat and summer corn rotation were 324 mm, 134 mm and 360 mm respectively. This kind of crop rotation pattern consumed more groundwater for irrigation, especially the winter wheat. In order to realize the balance of groundwater between exploitation and replenishment in Hebei Plain, more water-saving irrigation technologies should be adopted to reduce the evapotranspiration and improving water use efficiency.

Estimation of Evapotranspiration from the People’s Victory Irrigation District Based on the Data Mining Sharpener Model

Reasonable evaluation of evapotranspiration (ET) is crucial for optimizing agricultural water resource management. In the study, we utilized the Data Mining Sharpener (DMS) model; the Landsat thermal infrared images were sharpened from a spatial resolution of 100 m to 30 m. We then used the Surface Energy Balance System (SEBS) to estimate daily ET during the winter wheat growing season in the People’s Victory Irrigation District in Henan, China. It was concluded that the spatiotemporal patterns of land surface temperature and daily evapotranspiration remained consistent before and after sharpening. Results showed that the R2 value between the ET of 30 m spatial resolution and the value by eddy covariance method reached 0.814, with an RMSE of 0.516 mm and an MAE of 0.245 mm. All of these were higher than those of 100 m spatial resolution (R2 was 0.802, the RMSE was 0.534 mm, and the MAE was 0.253 mm). Furthermore, the daily ET image with a 30 m spatial resolution exhibited clear texture and distinct boundaries, without any noticeable mosaic effects. The changes in surface temperature and ET were more consistent in complex subsurface environments. The daily evapotranspiration of winter wheat was significantly higher in areas with intricate drainage systems compared to other regions. During the early growth stage, daily evapotranspiration decreased steadily until the overwintering stage. After the greening and jointing stages, it began to increase and peaked during the sizing period. The correlation between net solar radiation and temperature with ET was significant, while relative humidity and soil moisture were negatively correlated with ET. Throughout the growth period, net solar radiation had the greatest effect on ET.

Exploring interpretable and non-interpretable machine learning models for estimating winter wheat evapotranspiration using particle swarm optimization with limited climatic data

Accurate estimation of crop evapotranspiration (ETc) is crucial for improving the water use efficiency and designing and operating irrigation systems. To accurately calculate winter wheat ETc with limited meteorological data, the present study proposed two interpretable machine learning (ML) models (random forest (RF) and extreme gradient boosting (XGBoost)) as well as non-interpretable ML models (support vector machine (SVM) and deep neural network (DNN)) based on the particle swarm optimization (PSO) algorithm using observed winter wheat ETc data during the period from 2007 to 2013 at Luan Cheng Agro-ecosystem Experimental Station. Mean absolute error (MAE), root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), and global performance indicator (GPI) were used to assess the performance of models. This demonstrated that the ML models based on the crop coefficient (Kc) and solar radiation (Rn) were accurate and offered a workaround for calculating winter wheat ETc in the absence of meteorological data. In four ML models, the ninth input combination, consisting of Kc, Rn, daily air maximum temperature (Tmax), daily air minimum temperature (Tmin), sunshine hours (n), and wind speed with a height of 2 m (U2), produced the best estimate of ETc. Among them, the PSO-based SVM (PSO-SVM) model obtained the best results for estimating ETc with MAE, RMSE, NSE, R2, and GPI values of 0.389 mm·d−1, 0.562 mm·d−1 0.910, 0.911, and 0.975, respectively, showing the advantages of the non-interpretable ML model in ETc forecasting. Accurate descriptions of actual hydrological and climatic processes were given by local interpretable model-agnostic explanations (LIME). The inflection points of daily climatic parameters (Tmin, Tmax, Rn, n) related to ETc were determined to be 3.80 °C, 5.50 °C, 1.62 MJ·m−2·d−1, 1.37 h, respectively. This work has potential to overcome the difficulty of measuring winter wheat ETc properly due to the lack of meteorological data and accomplish appropriate water management to conserve water and increase water productivity.

Evapotranspiration of Winter Wheat in the Semi-Arid Southeastern Loess Plateau Based on Multi-Source Satellite Data

Continuous monitoring of evapotranspiration (ET) at high spatio-temporal resolutions is vital for managing agricultural water resources in arid and semi-arid regions. This study used the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) to calculate the ET of winter wheat between the green-up and milk stages in Linfen Basin, a typical, semi-arid area of the Loess Plateau, at temporal and spatial resolutions of 30 m and 8 d, respectively. We then analyzed the impact of meteorological factors on ET and its variation during the main growth period of winter wheat. The fused ET data displayed the spatial details of the OLI ET data better and could accurately reflect ET variation and local sudden variations during the main growth period of winter wheat. Moreover, winter wheat ET in rain-fed areas is more heavily influenced by meteorological factors, and the effect is more direct. Affected by the synergistic effect of wind velocity, precipitation, and temperature, the ET of winter wheat in rain-fed area was lower in the green-up stage. Then, ET gradually increased, reaching its maximum in the heading–grain filling stage. At the jointing stage, temperature had a significant effect on ET. A combination of precipitation and temperature had the greatest impact on the ET of winter wheat in the heading–filling stage. In the milk stage, meteorological factors had a minor impact on ET. This study serves as a reference for ET in winter wheat in semi-arid areas and its influencing meteorological factors, which can assist in drought mitigation and regional food security strategies.

Quantifying winter wheat evapotranspiration and crop coefficients under sprinkler irrigation using eddy covariance technology in the North China Plain

Sprinkler irrigation has been widely used for winter wheat crops in the North China Plain (NCP) to maintain high crop yield and enhance water use efficiency because water resources are scarce. Determining the accurate crop evapotranspiration (ETc) and crop coefficient (Kc) of winter wheat is critical for optimizing sprinkler irrigation management. In this study, an eddy covariance system was deployed in a sprinkler irrigation field to measure the energy balance components (net radiation Rn, soil heat flux G, sensible heat H, latent heat LE) and calculate ETc and Kc. The wheat growth parameters and yield were also investigated. The results showed that the energy balance closure rate, the rate of daily (LE + H) to (Rn - G), was 0.89, indicating a sufficient energy balance closure. Seasonal total LE flux accounted for 67% of the total available energy (Rn - G). The seasonal ETc values were 434 and 396 mm during the 2019–2020 and 2020–2021 growing seasons, respectively, which are comparable to those (400–470 mm) under surface irrigation. The mean daily ETc was 0.87, 0.46, 3.24, 4.81, and 3.94 mm day−1 in the early growth, overwintering, rapid growth, middle, and late growth stages, respectively. The corresponding Kc values were 0.77, 0.47, 1.09, 1.14 and 0.70. The Kc values were close to those reported in the FAO 56 paper. The Kc is positively related to the leaf area index (LAI), and their relationship was fitted as Kc=0.87+0.14lnLAI(R2=0.96) for an LAI range of 1–7, where ln is a natural logarithm function. The measured wheat grain yield was 9100 and 9857 kg ha−1, and the water productivity (WP) was 2.07 and 2.49 kg m−3 in the two seasons, respectively. Both factors are approximately 30% higher than those (7200 kg ha−1, 1.68 kg m−3) reported by other studies. Considering the high wheat yield and comparable crop ETc, sprinkler irrigation is recommended for application on the NCP. The seasonal ETc of 400–430 mm and the obtained Kc values in this study can be used to make sprinkler irrigation scheduling for winter wheat on the NCP.

Winter wheat evapotranspiration and irrigation requirements across tropical and sub-tropical producing regions in Brazil

Winter wheat evapotranspiration and irrigation requirements across tropical and sub-tropical producing regions in Brazil

Soil Management and Microclimate Effects on Ecosystem Evapotranspiration of Winter Wheat–Soybean Cropping in Northern Alabama

Nearly all the current winter wheat–soybean cropping systems occurring in the southeastern United States (SE) region are rainfed, as such, precipitation (P) underpins energy partitioning. We investigated, using the eddy covariance technique, the seasonal and interannual variability and rate and trend of energy partitioning, i.e., sensible and evapotranspiration (ET), for rainfed soybean and winter wheat cover cropping at Winfred Thomas Agricultural Research Station (WTARS) in Hazel Green, Alabama. Yearlong cumulative ET of 493, 743, and 746 mm during 2007, 2008, and 2009 relative to cumulative precipitation of 567, 1280, and 1356 mm y−1 resulted in a higher mean ET/P ratio of 0.87, in 2007, medium 0.58 in 2008, and lowest 0.55 in 2009. Mean daily ET for the cover crop and soybean ranged between 1.70 and 2.44 mm d−1 and 1.82 to 2.83 mm d−1, respectively. Overall, our findings suggest total and seasonal precipitation distribution were major controlling factors in the partitioning of the energy and water budgets. This study provides evidence that changes in rainfall frequency and intensity in the SE will likely alter the regional croplands hydrology with implications on water resource management decisions in rainfed agriculture.

Estimation of Landsat-like daily evapotranspiration for crop water consumption monitoring using TSEB model and data fusion.

Evapotranspiration (ET) plays an essential role in agricultural water resource management. Understanding regional agricultural water consumption characteristics can be improved by predicting ET using remote sensing. However, due to the lack of high-resolution images on clear-sky days or the limitation of ET reconstruction on cloudy-sky days, it remains challenging to continuously derive ET at the field scale. In this study, the Landsat and MODIS data were initially fused to obtain the Landsat-like vegetation index and land surface temperature on clear-sky days. Then the two-source energy balance (TSEB) model was applied to calculate the daily ET during the clear-sky. A canopy resistance-based gap-filling method was involved in reconstructing regional ET on cloudy days while considering different environmental factors. The estimations were validated by automatic weather system data (AWS) and eddy covariance (EC) measurements in Guantao County. The results demonstrated that the proposed scheme performed well in estimating cropland ET, with an RMSE of 0.86 mm·d−1 and an R2 of 0.65, and the NSE and PBias were 0.61 and -0.29%, respectively. The crop water consumption analysis revealed that the daily ET of winter wheat peaked during the maturation stage. Nevertheless, summer maize water consumption peaked in the middle of the growing season in this area. The temperature during the early development stage and the soil moisture in the mid and late growth stages had the greatest impact on the ET of winter wheat. During the entire growing period, soil moisture had the largest effect on the ET of summer maize. The findings showed that the TSEB model can be effectively applied to field-scale water consumption monitoring in North China through MODIS and Landsat data fusion and ET temporal reconstruction considering environmental factors.

Partitioning evapotranspiration of winter wheat based on oxygen isotope approach under different irrigation regimes

AbstractEvapotranspiration (ET), which is an elusive component of the hydrological cycle, comprises transpiration from plants (T) and evaporation from soil surface (E). In this regard, it is essential to know how much water is lost by T and E during the irrigation period. The overall aim of this study is to separate the ET components by stable oxygen isotopes of winter wheat at the field scale under different irrigation regimes. For this purpose, the field experiment was conducted under rain‐fed, deficit and full irrigation conditions. Soil–water–plant samples were taken for isotopic (18O/16O) analyses. According to the research results, a significant positive relationship was found between applied irrigation water and the average T/ET ratio with a correlation coefficient of 0.81. The T/ET ratios were, on average, 70, 75 and 84% for rain‐fed, deficit and full irrigation treatments, respectively. During the growing season, 231 and 78 mm of irrigation water were applied for full and deficit irrigation, respectively. This showed that water savings of 66% were achieved, although there was a slight (12%) change in transpiration in deficit irrigation. Also, in the use of the oxygen isotope content results indicated that T was the dominant source of total evapotranspiration.

Evapotranspiration partitioning for winter wheat with shallow groundwater in the lower reach of the Yellow River Basin

Accurately partitioning evapotranspiration (ET) remains one of the key research gaps in agro-ecosystem water research. The interaction of shallow groundwater with winter wheat increased the complexity of ET partitioning. Here we proposed a cutting method to partition ET into soil evaporation (E) and transpiration (T). Field multiple lysimeter experiments under 4 different watertable conditions were conducted at the Yucheng Experimental Station to investigate the partitioning of ET for winter wheat under shallow groundwater. Results showed that the cutting method is applicable and could obtain reasonable ratio of T to ET for crop land of winter wheat. Moreover, the T/ET could be generalized into a curve for representing the ratio of T to ET (i.e. K=T/ET) at the mid- and late-season stages of winter wheat. The maximum value of generalized T/ET curve (Kmax) increased with the increase of groundwater table depth (DTW), and was 0.651, 0.768, 0.771 and 0.869 for the depth of 0.4 m, 0.7 m, 1.1 m and 1.5 m, respectively. The higher transpiration proportion corresponded to the higher yield of winter wheat, which indicated that increased groundwater depth was benefit to enhance the groundwater consumption by transpiration and hence yield when watertable depth was within 1.5 m. Moreover, the lower evaporation proportion might lower the soil salinization risk due to less soil evaporation. It is important for the understanding of the interaction between evapotranspiration components of crop with shallow groundwater and the sustainable management in the lower reach of the Yellow River Basin.

Characteristics of Winter Wheat Evapotranspiration in Eastern China and Comparative Evaluation of Applicability of Different Reference Evapotranspiration Models

Characteristics of Winter Wheat Evapotranspiration in Eastern China and Comparative Evaluation of Applicability of Different Reference Evapotranspiration Models

Use of Remote Sensing to Assess the Water-Saving Effect of Winter Wheat Fallow

Winter wheat fallow policy has a greater effect on water resource management, and the water-saving effect in the fallow process of winter wheat can provide data support for precise water resource utilization planning. In order to evaluate the water resource consumption of winter wheat and the related effect from winter wheat fallow, this study searched the changing trends of cultivated land evapotranspiration under five different scenarios through the object-oriented extraction method and a SEBS model based on multi-source data. The results indicated that the evapotranspiration during winter wheat growing period was higher than that of winter wheat fallow land, and there was no big difference in evapotranspiration between the fallow land during harvesting and the emergence of new crops. The evapotranspiration of winter wheat was higher than that of various fallow land, and the evapotranspiration of abandoned land was higher than other fallow land in the winter wheat growing season. From this point, this study concludes that the fallow land policy can effectively reduce evapotranspiration during the growing of winter wheat, which is conducive to the sustainable exploiting of water resources.

Estimating stomatal conductance and evapotranspiration of winter wheat using a soil-plant water relations-based stress index

Stomatal conductance, closely related to water flow in the soil-plant-atmosphere continuum, is an important parameter in the Penman-Monteith (P-M) model for estimating evapotranspiration (ET). In this study, a novel soil water stress index ω, considering intrinsic soil-plant water relations, was introduced into the Jarvis empirical estimation model of stomatal conductance to improve the representation of the effect of soil water stress on stomatal conductance. The index ω accounted not only for current water availability by combing the effects of relative distribution of soil water to roots and nonlinear stomatal response, but also for the hysteresis effect of water stress by means of the inclusion of a recovery coefficient. Combined plant and soil-based measurements from a greenhouse experiment provided the basis for investigating the relationship between leaf stomatal conductance gs and root zone soil water stress represented by ω. The response of gs to root-weighted soil matric potential was found to be nonlinear. The relationship between gs and the extent of previous water stress (i.e. the water stress recovery coefficient curve) was generalized by a power function and was verified and confirmed using results obtained from the literature. The reliability of ω was tested by coupling it into the Jarvis model to estimate leaf (gs) and canopy (gc) stomatal conductance, and thereupon into the P-M model to estimate cumulative ET (CET) in the greenhouse experiment and two field experiments. The estimated gs, gc and CET agreed well with the measurements, with root mean squared error not more than 0.0006 m s−1, 0.0020 m s−1 and 8.2 mm, respectively, and determination coefficient (Nash-Sutcliffe efficiency coefficient) consistently greater than 65% (0.14). Therefore, ω should be feasible and reliable to delineate the response of stomatal physiological reaction to water stress, and hence helpful for accurate estimation of ET using Jarvis-based P-M models.

Modeling Evapotranspiration of Winter Wheat Using Contextual and Pixel-Based Surface Energy Balance Models

HighlightsThree contextual-based (CB) and two pixel-based (PB) models were evaluated to estimate ET of rainfed winter wheat.Instantaneous available energy estimation and ET upscaling impacted model performance.The CB models performed better at instantaneous and daily scales compared to the PB models.ET estimation biases increased during low vegetation and drier conditions, especially for the PB models.Abstract. Surface energy balance (SEB) models based on thermal remote sensing data are widely used in research applications to map evapotranspiration (ET) across various landscapes. However, their ability to capture ET from winter wheat remains underexplored, especially in practical applications such as integrated resource management and drought preparedness. Investigating winter wheat ET dynamics is important in agricultural regions such as the Southern Great Plains of the U.S., where winter wheat is extensively cultivated. The goal of this study was to evaluate the performance of five fully automated SEB models, three contextual-based (CB) and two pixel-based (PB), in estimating instantaneous and daily ET of winter wheat by comparing the model results with flux tower observations. The CB models included Surface Energy Balance Algorithm for Land (SEBAL), Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC), and Triangular Vegetation Temperature (TVT). The PB models included Surface Energy Balance System (SEBS) and Two-Source Energy Balance (TSEB). Model evaluation during two winter wheat growing seasons (2016-2018) using 28 Landsat images showed that the instantaneous ET estimates from METRIC and TSEB had the smallest (RMSE = 0.14 mm h-1) and largest (RMSE = 0.27 mm h-1) errors, respectively. At the daily scale, SEBAL was the best performing model (RMSE = 1.0 mm d-1), followed by TVT (RMSE = 1.1 mm d-1), METRIC (RMSE = 1.2 mm d-1), SEBS (RMSE = 1.3 mm d-1), and TSEB (RMSE = 1.5 mm d-1). Overall, the CB models provided smaller errors than the PB models. Larger errors in daily ET estimation were observed during low vegetation and drier conditions, especially for the PB models. Keywords: Flux tower, Landsat, Southern Great Plains, Water use.

Estimating daily actual evapotranspiration of a rice–wheat rotation system in typical farmland in the Huai River Basin using a two-step model and two one-step models

The objective of this study is to evaluate the performance of three models for estimating daily evapotranspiration (ET) by employing flux observation data from three years (2007, 2008 and 2009) during the growing seasons of winter wheat and rice crops cultivated in a farmland ecosystem (Shouxian County) located in the Huai River Basin (HRB), China. The first model is a two-step model (PM–Kc); the other two are one-step models (e.g., Rana–Katerji (R–K) and advection-aridity (AA)). The results showed that the energy closure degrees of eddy covariance (EC) data during winter wheat and rice-growing seasons were reasonable in the HRB, with values ranging from 0.84 to 0.91 and R2 of approximately 0.80. Daily ET of winter wheat showed a slow decreasing trend followed by a rapid increase, while that of rice presented a decreasing trend after an increase. After calibrating the crop coefficient (Kc), the PM–Kc model performed better than the model using the Kc recommended by the Food and Agricultural Organization (FAO). The calibrated key parameters of the R–K model and AA model showed better universality. After calibration, the simulation performance of the PM–Kc model was satisfactory. Both the R–K model and AA model underestimated the daily ET of winter wheat and rice. Compared with that of the R–K model, the simulation result of the AA model was better, especially in the simulation of daily ET of rice. Overall, this research highlighted the consistency of the PM–Kc model to estimate the water demand for rice and wheat crops in the HRB and in similar climatic regions in the world.

Estimating Soil Water Content and Evapotranspiration of Winter Wheat under Deficit Irrigation Based on SWAP Model

Deficit irrigation strategy is essential for sustainable agricultural development in arid regions. A two−year deficit irrigation field experiment was conducted to study the water dynamics of winter wheat under deficit irrigation in Guanzhong Plain in Northwest China. Three irrigation levels were implemented during four growth stages of winter wheat: 100%, 80% and 60% of actual evapotranspiration (ET) measured by the lysimeter with sufficient irrigation treatment (CK). The agro−hydrological model soil−water−atmosphere−plant (SWAP) was used to simulate the components of the farmland water budget. Sensitivity analysis for parameters of SWAP indicated that the saturated water content and water content shape factor n were more sensitive than the other parameters. The verification results showed that the SWAP model accurately simulated soil water content (average relative error (MRE) < 21.66%, root mean square error (RMSE) < 0.07 cm3 cm−3) and ET (R2 = 0.975, p < 0.01). Irrigation had an important impact on actual plant transpiration, but the actual soil evaporation had little change among different treatments. The average deep percolation was 14.54 mm and positively correlated with the total irrigation amount. The model established using path analysis and regression methods for estimating ET performed well (R2 = 0.727, p < 0.01). This study provided effective guidance for SWAP model parameter calibration and a convenient way to accurately estimate ET with fewer variables.

Evaluation of seasonal evapotranspiration of winter wheat in humid region of East China using large-weighted lysimeter and three models

Water consumption demand of winter wheat remains uncertain in humid region of East China. A better prediction of water consumption can improve agricultural water management. Based on the evapotranspiration (ET) data determined by large-weighted lysimeter and the meteorological data during 2011–2018, the actual ET of winter wheat was compared with the ET simulated by Priestley-Taylor (PT), Penman-Monteith (PM) and FAO-56 single crop coefficient (Kc) models, and the relationships between ET of winter wheat and its driving environmental factors were assessed to localize the model’s parameters. The results showed that the seasonal variations of ET in winter wheat could be divided into three stages with the canopy development, i.e., Stage I: from sowing to wintering when hourly ET maintained a low level (0.03–0.35 mm/h); Stage II: from revival to dough when hourly ET increased rapidly to 0.60–1.50 mm/h during daytime; Stage III: the ripening stage with hourly ET decreasing to 0.01–1.00 mm/h. The ET of winter wheat was mainly determined by wind speed at Stage I and by net solar radiation (Rn) at Stage II and III by Besides primary determining factor net radiation at the whole season, vapor pressure deficit and air temperature was the second factor that dominated ET at Stages I-II and Stage III, respectively. The PM model performed excellently for hourly ET modelling at Stage II with R2 of 0.944 during 2017–2018. All models did not perform well at Stage I and III on hourly time scale. PM model was the best among the three models for calculating daily ET at Stage II, while both PM and PT models could be used to simulate daily ET at Stage III. After local parameterization, the calibrated PTx and Kcx models were validated with daily ET simulation with the coefficients of 1.52 and 1.25 at Stage I, 1.81 and 1.80 at Stage II, and 1.12 and 0.78 at Stage III, respectively. The PTx model was suitable to calculate daily ET at Stage I and III with R2 of 0.19 and 0.55, MAE of 0.39 and 0.88 mm/d, GPI of 0.59 and 2.93, respectively, while Kcx model was the best model at Stage II, with R2 of 0.86, MAE of 0.74 mm/d and GPI of 0.22. Moreover, the PTx at Stage I, Kcx at Stage II, and PTx at Stage III appeared to give reasonable results in evaluating seasonal ET of winter wheat, with values of 53.8, 375.8 and 21.0 mm at Stage I, II and III in 2017–2018, respectively. Total ET suggested that the main water management period should be Stage II. The results can improve the simulation of seasonal ET and may be used as a benchmark for water management of winter wheat in East China.

Winter wheat growth and water use under different drip irrigation regimes in the North China PlainWinter wheat growth and water use under different drip irrigation regimes in the North China Plain

A 3-year field experiment was conducted to evaluate the applicability of drip irrigation, winter wheat growth and water use under different drip irrigation regimes in the North China Plain (NCP) during 2014–2017. Five irrigation regimes with the soil matric potential (SMP) thresholds at 20 cm depth immediately under the emitters were − 10, − 20, − 30, − 40 and − 50 kPa. The results showed that scheduling drip irrigation with SMP thresholds at 20 cm depth obviously affected the soil moisture status in the root zone, and the lower the SMP threshold was, the lower the average soil moisture content was. Soil moisture consumption of winter wheat occurred mainly in 0–60 cm soil layer in anthesis stage, and reached a depth of 80 cm in grain filling stage, and there was no deep percolation but groundwater recharge in 130 cm layer. SMP thresholds had significant effects on grain yield and water use efficiency (WUE), and there was a tendency for the two indicators to reach their highest values when the SMP threshold was around − 40 kPa in the normal years. Both yield and WUE decreased with the decrease of SMP in the dry year. Winter wheat evapotranspiration and irrigation amount decreased by 0.12% and 0.92%, respectively, and the irrigation water use efficiency increased by 1.22% with each unit of SMP decrease. Compared with the average grain yield, irrigation amount and WUE under local surface irrigation management, drip irrigation with the SMP threshold of − 40 kPa resulted in a yield increase of 4.3%, water savings of 46.6%, and WUE increase of 10.5%. The yield increase wasn’t significant to attract farmers to adopt drip irrigation technology, but the water saving was obvious. So, in the NCP, if the investment of drip irrigation system was likely to be government subsidized, it was recommended to drip irrigate winter wheat with the SMP threshold of − 40 kPa at 20 cm depth immediately under the emitters.

NDVI‐based estimates of evapotranspiration of winter wheat indicate positive effects of N fertilizer application on agronomic water‐use efficiency

AbstractYield increases by fertilizer application impose higher crop water use, as biomass production is positively correlated with transpiration. To quantify effects of N fertilizer supply on evapotranspiration (ET) of winter wheat, a field experiment with three nitrogen rates (N0, N120 and N230) under non‐water‐limited conditions was performed during 2014 and 2015. Normalized difference vegetation index (NDVI) was used to derive crop coefficients which were used to calculate N effects on bare soil evaporation (E), transpiration, evapotranspiration (ET), grain yield and harvest index (HI). E during the early post‐winter growth period was measured with micro‐lysimeters and compared with model estimates. N fertilizer supply resulted in lower cumulative E, and increases in grain yield were higher than increases in ET, resulting in a higher agronomic water‐use efficiency (WUEY). HI of treatment N120 was higher than that of treatment N230 indicating that HI was not the main reason of higher WUEY of treatment N230. It is concluded that estimates of ET under variable N supply require consideration of N‐induced effects on canopy development which could be successfully monitored by NDVI measurements. N supply increases ET and WUEY potentially imposing a trade‐off between water conservation and efficiency of water use for crop production.