Daily Crop Evapotranspiration Research Articles

Irrigation Water Treated with Oxygen Nanobubbles Decreases Irrigation Volume While Maintaining Turfgrass Quality in Central Chile

The efficient use of water resources is a growing priority in multiple sectors, including the turfgrass industry. Nanobubbles (NB) represent an innovative technology that, by enriching solutions with various gases, offers significant benefits in several industrial areas. In crop irrigation, they have been shown to increase dissolved oxygen in the root zone and thereby boost yields. The objective of this study was to evaluate the impact of the use of oxygen NB in irrigation water on turfgrass quality, considering different levels of water restriction (0%, 30%, and 50% of daily crop evapotranspiration), compared to conventional irrigation. During the summer of 2024, trials were conducted using turf quality indices based on multispectral reflectance and RGB digital image analysis. The results showed that the use of NB allowed for a reduction in irrigation by 50% without compromising turf quality, reaching values similar to treatments without water restriction. In contrast, treatment with the same restriction but without NB (WNB50%) showed a deterioration in quality. This study shows NB as an innovative tool to optimize water use, with great potential for applications in landscape green areas, promote water use efficiency, and reduce the costs associated with irrigation.

Water consumption of a Paulownia plantation in an arid climate in Kyrgyzstan, Central Asia

Recently, Paulownia spec. has been introduced to Central Asia in a number of small plantations. Paulownia yields timber of high quality for applications such as furniture, house construction, boat construction, and surf boards, or skis. Thus, Paulownia might offer a much-needed raw material for this region and beyond. However, Central Asia is largely occupied by drylands so that Paulownia needs irrigation. Against the background of frequent water stress across the region, this study aimed at assessing the water consumption and water productivity of that tree, using a 6-year-old plantation as study site. Trees were planted in May 2017 and cut back to their stumps in 2018. Daily crop evapotranspiration was calculated after the Penman-Monteith approach, whereby the crop coefficients were inherited from actual evapotranspiration values which stemmed from the remote sensing approach S-SEBI. Water consumption per tree was 1741 l, 4461 l, 4500 l, and 4407 l over the growing seasons 2020, 2021, 2022, and 2023, respectively. The water productivity for the stem wood over the whole time-span from planting in 2017 until 2023 was 1.59 g l-1 and 5.65 ml l-1. Given the high quality of its timber and its range of high-value applications, it can be concluded that the water consumed by Paulownia enables higher value timber and timber products than other trees that grow in comparable areas of Central Asia.

Daily crop evapotranspiration and diurnal dynamics of the surface energy balance of a drip-irrigated blueberry (Vaccinium corymbosum) orchard

Daily crop evapotranspiration and diurnal dynamics of the surface energy balance of a drip-irrigated blueberry (Vaccinium corymbosum) orchard

Innovative Solutions for Drought: Evaluating Hydrogel Application on Onion Cultivation (Allium cepa) in Morocco

Throughout the last decade, and particularly in 2022, water scarcity has become a critical concern in Morocco and other Mediterranean countries. The lack of rainfall during spring was worsened by a succession of heat waves during the summer. To address this drought, innovative solutions, including the use of new technologies such as hydrogels, will be essential to transform agriculture. This paper presents the findings of a study that evaluated the impact of hydrogel application on onion (Allium cepa) cultivation in Meknes, Morocco. The treatments investigated in this study comprised two different types of hydrogel-based soil additives (Arbovit® polyacrylate and Huminsorb® polyacrylate), applied at two rates (30 and 20 kg/ha), and irrigated at two levels of water supply (100% and 50% of daily crop evapotranspiration; ETc). Two control treatments were included, without hydrogel application and with both water amounts. The experiment was conducted in an open field using a completely randomized design. The results indicated a significant impact of both hydrogel-type dose and water dose on onion plant growth, as evidenced by various vegetation parameters. Among the hydrogels tested, Huminsorb® Polyacrylate produced the most favorable outcomes, with treatment T9 (100%, HP, 30 kg/ha) yielding 70.55 t/ha; this represented an increase of 11 t/ha as compared to the 100% ETc treatment without hydrogel application. Moreover, the combination of hydrogel application with 50% ETc water stress showed promising results, with treatment T4 (HP, 30 kg, 50%) producing almost the same yield as the 100% ETc treatment without hydrogel while saving 208 mm of water.

Site‐specific estimation of spatiotemporal crop evapotranspiration through field‐level sensing data

AbstractThis study integrated field‐level sensor data into the FAO‐56 Penman–Monteith algorithm to provide a site‐specific estimate of crop evapotranspiration. This was carried out at two contrasting sites for pea and bean (Manawatū) and barley (Hawke's Bay) crops managed within two irrigation management zones, at each site, under variable‐rate irrigation systems in New Zealand. Daily crop evapotranspiration estimates were calculated using data from a weather station situated at the field site combined with in‐field crop sensing data (spectral reflectance, canopy temperature, and canopy height). In addition, calibrated soil moisture data were used with a soil water balance model to compare estimations of daily crop evapotranspiration with those estimated using the crop sensing method. The results indicated that variable crop responses to different irrigation strategies and soil types provided a good opportunity to quantify different levels of spectral reflectance, canopy temperature, and consequently the estimation of crop water use. The statistical comparisons revealed that the modified FAO‐56 Penman–Monteith using crop sensor data compared well with the more conventional soil water balance approach using soil moisture data (R2 = 0.70, 0.83, 0.91 for barley, pea, and bean, respectively). Overall, the results from this study indicated that crop sensing approaches combined with the FAO‐56 Penman–Monteith model have potential to provide a more easily determined site‐specific field estimation of crop evapotranspiration than other methods, and it can take into consideration the spatiotemporal variability of crop growth in a field.

Evapotranspiration Rates of Three Sweet Corn Cultivars under Different Irrigation Levels

Understanding plants’ response to different irrigation levels is essential for developing effective irrigation scheduling practices that conserve water without affecting plant growth and yield. The objective of this study was to evaluate the responses of three sweet corn (Zea mays var. saccharata) cultivars 1170, 8021, and Battalion under three irrigation levels (50%, 75%, and 100%). Irrigation treatments were based on soil moisture management allowable depletion. Replicated trials were conducted, in an open field using 1-gal containers, at the Tropical Research and Education Center, Homestead, FL. A drip system with microsprinklers was used for irrigation. Daily crop evapotranspiration (ETc) rates were measured using a digital scale based on differences in weights of soil containers and plants. Reference evapotranspiration (ETo) was calculated using the FAO-Penman-Monteith equation. Crop-coefficient (Kc) values for the three cultivars were calculated from measured ETc and calculated ETo. In addition, leaf area, stomatal conductance, and fresh biomass were measured. Total irrigation amounts corresponding to the 50%, 75%, and 100% treatments were 116, 162, and 216 mm, and total ETc values were 128, 157, and 170 mm, respectively. The two deficit irrigation treatments (50% and 75%) resulted in a reduction of ETc for the three cultivars compared with the 100% irrigation treatments. Results also showed that under 75% and 100% treatments, Kc values were usually greater than 1 for the three cultivars and reached as high as 1.5. Additionally, leaf area and fresh biomass weight in the 50% treatment were mostly lower than in the 75% or 100% treatments.

Hybrid deep learning techniques for estimation of daily crop evapotranspiration using limited climate data

Smart agriculture aims to improve the quality and quantity of crops by efficiently managing available resources. One of the main components of smart agriculture is precision irrigation which applies the required amount of water at the right time to crops. Crop evapotranspiration (ETc) prediction can contribute to managing the irrigation strategies effectively. Although several methods have been introduced for estimating ETc values, these methods are still associated with various challenges and limitations (high cost, time-consuming, and meteorological data unavailability). The current study is motivated by the desire to create deep learning (DL) based models capable of estimating ETc reliably to eliminate the above-mentioned limitations and forecast future ETc values for adaptation strategies. In this paper, two-hybrid DL models, i.e., Convolution Neural Network-eXtreme Gradient Boosting (CNN-XGB) and Convolution Neural Network-Support Vector Regression (CNN-SVR) are proposed to estimate daily ETc values of wheat and rice crops. Further, limited climate data (minimum temperature (Tmin), maximum temperature (Tmax), mean temperature (Tmean) and solar radiation (Rs)) is used for the prediction of ETc values to handle data-scarce situations. Also, the future climate data obtained using two emission scenarios: Representative Concentration Pathways (RCP) 4.5 and RCP 8.5 for the time period 2023–2033, are used to project changes in ETc. The results demonstrate that the proposed hybrid models provide satisfactory performance with the Nash–SutcliffeEfficiency (NSE) = 0.95 and 0.976 for rice and wheat ETc values, respectively. The simulation of future data reveals the increase in Tmin by 7.03%, 7.33%, and Tmax by 10.5%, 11.5% for RCP 4.5 and RCP 8.5 respectively. Also, an increase in ETc of rice crop has been reported by 20%–22% while increment of wheat ETc has been noticed by 3%–4%. Thus, the proposed approach efficiently estimates ETc of wheat and rice crops using limited climate data and could assist water resource managers in achieving agricultural water sustainability.

Evaluation of Forecast Reference Evapotranspiration for Different Microclimate Regions in California to Enable Prospective Irrigation Scheduling

AbstractIn California, daily crop evapotranspiration (ETc) is commonly estimated using near-real-time, standardized reference evapotranspiration (ETo) calculated from ground-based meteorological da...

Effect of Performance of Water Stashes Irrigation Approaches on Selected Species of Plant’s Water Productivity in Urban Rooftop Agriculture with Respect to Climate Change

Urbanization and population growth have led to urban areas with a substantial concrete surface compared to adjacent rural areas, creating challenges regarding fresh food, water security, and the need for agricultural land. Climate change affects the rainfall pattern and ground water in urban areas, so the gradual growth of urban rooftop agriculture (URTA) is an increasing trend for the owners of residential buildings. URTA is increasing in the form of private initiatives, but without consideration of efficient water management techniques and application of other related inputs. URTA differs substantially from traditional agriculture in terms of sunshine, thermal regime, the moisture dynamics of a concrete roof top, etc. Considering these aspects of URTA, an effective, efficient, science-based and economically viable irrigation method is necessary to popularize this approach and consequently increase the productivity of crops. With this in mind, the drip irrigation method is considered for the cultivation and determination of water productivity for selected species of plants such as the Bottle Gourd, Tomato, Chili, and Brinjal in the URTA, which was also compared to the traditional irrigation approach. This is why groundwater and green (grey and rain) water were considered as the source of irrigation during the dry season, based on the daily crop evapotranspiration and moisture content of the plant growing medium. For this reason, ET0 of the selected crops was measured using the CROPWAT 8.0 model. The results of this study revealed that the optimum irrigation water requirement of any crop in URTA is around 54% access (ETc), and 46–64% of access irrigation water is used by the traditional method compared to the drip irrigation method. The study reported that with drip irrigation with potable water, the yield was increased by 21.43–22.40% and rain and grey-water also increased yield by 31.87–33.33% compared to container and traditional pipe irrigation. It was also found that the water qualities of mixed water (grey and rainwater) are in an acceptable range limit for irrigation. As a result, urban planners, city dwellers, and researchers can formulate appropriate plans to cultivate different species of plants through this water saving irrigation method using green water, and should explore the concept of water-smart URTA technologies as organic inventions embedded in these results.

Analysis of crop water requirements and irrigation demands for rice: Implications for increasing effective rainfall

Determining the irrigation demands of rice in a humid region is essential for water conservation through improving rainfall utilization in southern China. In this paper, six representative rice areas in southern China were selected, and the daily reference evapotranspiration (ETo) of the representative stations during 1953–2017 was calculated using the Penman-Monteith method. The daily crop evapotranspiration (ETc) was computed using the single crop coefficient method, and the irrigation scheduling under flood irrigation (FI) was obtained by establishing a field water balance model. The characteristics and trends of the irrigation demand of early, middle and late rice, as well as the irrigation changes under a “double-to-single” cropping pattern, were also analyzed with advanced statistical tests. The results indicated that most of the abundant rainfall was concentrated in the growth period of early rice in southern China. Early rice required less water (135.0 mm) and even no irrigation in some wet years, while middle and late rice required more irrigation water (288.1 mm and 265.2 mm, respectively). The key reasons for the differences in irrigation demand among the three rice types are the amount and distribution characteristics of rainfall during the rice growth period. In addition, the irrigation demands of rice showed a downward trend as a response to a decrease in ETc and the increase in rainfall in the past 60 years, where rainfall was the dominant factor. With this increasing trend of rainfall and its better and efficient utilization in the future, rice irrigation demands may be further reduced or completely stopped. Under the “double-to-single” cropping pattern, irrigation demand decreased by 16% on average, and the irrigation frequency, as well as the drainage volume burden, were simultaneously reduced.

Comparison of Satellite Driven Surface Energy Balance Models in Estimating Crop Evapotranspiration in Semi-Arid to Arid Inter-Mountain Region

The regional-scale estimation of crop evapotranspiration (ETc) over a heterogeneous surface is an important tool for the decision-makers in managing and allocating water resources. This is especially critical in the arid to semi-arid regions that require supplemental water due to insufficient precipitation, soil moisture, or groundwater. Over the years, various remote sensing-based surface energy balance (SEB) models have been developed to accurately estimate ETc over a regional scale. However, it is important to carry out the SEB model assessment for a particular geographical setting to ensure the suitability of a model. Thus, in this study, four commonly used and contrasting remote sensing models viz. METRIC (mapping evapotranspiration at high resolution with internalized calibration), SEBAL (surface energy balance algorithm for land), S-SEBI (simplified surface energy balance index), and SEBS (surface energy balance system) were compared and used to quantify and map the spatio-temporal variation of ETc in the semi-arid to arid inter-mountain region of Big Horn Basin, Wyoming (Landsat Path/Row: 37/29). Model estimates from 19 cloud-free Landsat 7 and 8 images were compared with the Bowen ratio energy balance system (BREBS) flux stationed in a center pivot irrigated field during 2017 (sugar beet), 2018 (dry bean), and 2019 (barley) growing seasons. The results indicated that all SEB models are effective in capturing the variation of ETc with R2 ranging in between 0.06 to 0.95 and RMSD between 0.07 to 0.15 mm h−1. Pooled data over three vegetative surfaces for three years under irrigated conditions revealed that METRIC (NSE = 0.9) performed better across all land cover types, followed by SEBS (NSE = 0.76), S-SEBI (NSE = 0.73), and SEBAL (NSE = 0.65). In general, all SEB models substantially overestimated ETc and underestimated sensible heat (H) fluxes under dry conditions when only crop residue was available at the surface. A mid-season density plot and absolute difference maps at image scale between the models showed that models involving METRIC, SEBAL, and S-SEBI are close in their estimates of daily crop evapotranspiration (ET24) with pixel-wise RMSD ranged from 0.54 to 0.76 mm d−1 and an average absolute difference across the study area ranged from 0.47 to 0.56 mm d−1. Likewise, all the SEB models underestimated the seasonal ETc, except SEBS.

Mapping Very-High-Resolution Evapotranspiration from Unmanned Aerial Vehicle (UAV) Imagery

There is a growing concern about water scarcity and the associated decline in Australia’s agricultural production. Efficient water use as a natural resource requires more precise and adequate monitoring of crop water use and irrigation scheduling. Therefore, accurate estimations of evapotranspiration (ET) at proper spatial–temporal scales are critical to understand the crop water demand and uptake and to enable optimal irrigation scheduling. Remote sensing (RS)-based ET estimation has been adopted as a method for large-scale applications when the detailed spatial representation of ET is required. This research aimed to estimate instantaneous ET using very-high-resolution (VHR) multispectral and thermal imagery (GSD < 8 cm) collected using a single flight of a UAV over a high-density peach orchard with a discontinuous canopy. The energy balance component estimation was based on the high-resolution mapping of evapotranspiration (HRMET) model. A tree-by-tree ET map was produced using the canopy surface temperature and the leaf area index (LAI) resampled at the corresponding scale via a systematic feature segmentation method based on pure canopy extraction. Results showed a strong linear relationship between the estimated ET and the leaf transpiration (n = 42) measured using a gas exchange sensor, with a coefficient of determination (R2) of 0.89. Daily ET (5.5 mm d−1) derived from the instantaneous ET map was comparable with daily crop ET (6.4 mm d−1) determined by the meteorological approach over the study site. The proposed approach has important implications for mapping tree-by-tree ET over horticultural fields using VHR imagery.

Evaluation of the Surface Renewal Method for Estimating Cotton Evapotranspiration in South Carolina

HighlightsThe Surface Renewal (SR), Eddy Covariance (EC), and FAO56 methods were used to estimate crop evapotranspiration.An independently calibrated SR approach was used with a low-cost cup anemometer and assumed energy balance closure.All three approaches (SR, EC, and FAO56) resulted in similar crop ET values during later stages of growth (R2 = 0.87).SR has the potential to lower field-scale ET measurement costs and equipment requirements.Abstract. Evapotranspiration (ET) is important for many agricultural and hydrological applications, but its measurement normally requires expensive instrumentation. The Surface Renewal method (SR) has been proposed as a relatively low-cost alternative to measure ET, but the need for local calibration has been cited as a shortcoming. Castellví (2004)(2004) proposed a similarity-based SR approach to address this shortcoming, but field comparisons evaluating the accuracy of the approach using low-cost anemometry are currently lacking. The objective of this study was to evaluate the reliability of the similarity-based SR approach using low-cost anemometry (cup anemometer) for estimating cotton ET in comparison to the Eddy Covariance (EC) and FAO56 methods (Allen et al., 1998). Concurrent estimates of cotton ET were taken in 2019 at two adjacent cotton fields in South Carolina using the SR, EC, and FAO56 methods. SR and EC measurements of sensible heat flux were replicated using two in-field tower locations in the north field and ET was derived using the energy balance closure approach. An analysis was made to ensure =90% of the EC and SR seasonal data came from the field area (Kljun et al., 2015), with additional filtering to ensure that the higher-mounted EC had >90% footprint from the field area for each half-hour of analysis. In general, the results showed very good agreement between the daily crop ET values measured by SR and EC (R2north = 0.93, R2south = 0.97) for all of the season, and good agreement between SR and FAO56 measurements when crop height was more developed (R2north = 0.92, R2south = 0.87), near or above a canopy height of 0.75 m. There was disagreement between the non-continuous north tower SR measurements and FAO56 measurements in earlier stages of growth (June and July R2 = 0.09), which may have been due to uncertainty with the FAO56 local single crop coefficients or with a lack of energy balance closure. The results suggest that the use of low-cost anemometry with the independently calibrated SR approach is a useful alternative to measure crop ET under the conditions of this study, but further research may be necessary to evaluate the use of low-cost anemometry for direct SR ET measurements. Keywords: Cotton irrigation, Crop coefficients, Eddy covariance, Evapotranspiration, ET, Surface renewal.

Evapotranspiration and crop coefficients from lysimeter measurements for sprinkler-irrigated canola

Canola is a water-stress tolerant crop, which could be an alternative in areas with limited water resources. However, in arid and semi-arid environments where rainfall events are scarce and increasingly erratic, the use of irrigation is necessary for canola production to reach its maximum yield. The goal of this study was to determine the crop evapotranspiration (ETc) and crop coefficients of sprinkler irrigated canola (Brassica napus L.) under non-limiting soil water content conditions. A 2-year field experiment was conducted in the lysimeter facility located in Albacete (SE Spain). A large weighing lysimeter (2.7 × 2.3 × 1.7 m), with an accuracy of 0.04 mm equivalent water depth, was used to measure the daily crop evapotranspiration (ETc) rate throughout two growing seasons. ETc values were determined using daily mass change in the lysimeter. Cumulative ETc was replaced in the lysimeter through sprinkler irrigation applications, thus crop water stress was avoided. Seasonal lysimeter based (measured) canola ETc was 472 and 602 mm in 2008 and 2012, respectively. The 28 % higher ETc value in 2012 was mainly due to a much higher evaporative demand during the crop growth mid-season period of 2012. The Kc values were determined using grass reference evapotranspiration (ETo) calculated with the FAO56 Penman-Monteith equation and the ETc calculations from the lysimeter data. The dual crop coefficient approach was used to separate crop transpiration (Kcb) from soil evaporation (Ke). For the two canola seasons, mid-season Kc and Kcb values, after FAO56 climate adjustment, were Kc mid (std) = 1.15 and Kcb mid (std) = 1.11. Those values were reached coinciding with maximum fraction of ground cover (fc) values of up 0.95 and 0.97 for 2008 and 2012, respectively. The seasonal evaporation component for sprinkler-irrigated canola was estimated to be about 24 % and 19 % of ETc in 2008 and 2012, respectively. The good linear relationship found between canola Kcb values and fc and the excellent agreement found between remotely sensed vegetation indices (VIs) and different biophysical parameters, such as Kcb and fc, will allow monitoring and estimating the spatially distributed water requirements of canola at field and regional scales using multispectral satellite imagery.

Effect of different irrigation and fertigation levels on yield and nutrient use efficiency in sweet orange (Citrus sinensis L. Osbeck) cv. Phule Mosambi

Water and nutrient use efficiency are primary requirements for optimum and sustained citrus productivity. The interactive effect of irrigation and fertigation levels on growth and yield of 10-year-old sweet orange (Citrus sinensis L. Osbeck) cv. Phule Mosambi was studied through a field experiment during 2017 and 2018 at Research Farm of AICRP on Fruits, Department of Horticulture, MPKV Rahuri. The experiment was laid out in factorial randomized block design with nine treatment combinations, comprising three irrigation levels (100%, 80% and 60% of daily crop evapo-transpiration), three fertigation levels (100%, 80% and 60% RDF based NPK doses through water soluble fertilizers) and control with surface irrigation and band placement of conventional fertilizers (SI+BPF) replicated thrice. The yield parameters such as no. of fruits tree-1, yield in kg tree-1 and partial factor productivity of nutrients were observed to be significantly highest in the treatment T1-I1F1 having irrigation at 100% ETc and fertigation at 100% RD through WSF than rest of the treatments however they were statistically at par with the treatment T5- I2F2 comprising irrigation at 80% of ETc and fertigation with 80% of RD with WSF during 2017, 2018 and in pooled results. The nutrient use efficiency parameters like nitrogen use efficiency, phosphorus use efficiency and potassium use efficiency were observed to be significantly higher in the treatment T3-I1F3 having irrigation at 100% ETc and fertigation at 60% RD through WSF which was statistically at par with the treatment T5- I2F2 comprising irrigation at 80% of ETc and fertigation with 80% of RD with WSF during 2018 and in pooled results. The sustained productivity of sweet orange with highest nutrient use efficiency can be achieved with irrigation scheduled at 80% ETc along with fertigation technology at 80% RDF especially under scarcity conditions of Western Maharashtra.

Using a lysimetric station to determine the irrigation water requirements for chufa crop (Cyperus esculentus var. sativus)

Chufa, also known as tigernut, is a typical irrigated crop in Valencia, Spain, where it is traditionally cultivated for its tubers. Its cultivation uses large amounts of water, in the order of 10,000 m3 ha(‑1) year‑1. During the last years, the research team in which this study has been developed, has carried out several studies leading to improve the irrigation water use efficiency in chufa. Although these improvements are considerable, they are not definitive, as the water requirements of the crop are still unknown. To know these needs, it would be recommended to determine the crop evapotranspiration (ETc). The experiment was carried out on an experimental plot of the Universitat Politecnica de Valencia, included in the traditional cultivation area. This plot includes a lysimetric station (Smart Field Lysimeter) which allows determining the daily ETc. In addition, the plot is equipped with a meteorological station, which provides the necessary parameters for the determination of the daily reference crop evapotranspiration (ETo) through the FAO-56 Penman-Monteith method. Relating the values of ETc and ETo, the crop coefficient (Kc) values corresponding to the different growth stages, has been estimated from the data obtained during the crop cycle. Considering the crop development, the length of the four growth stages were considered as 21, 76, 43 and 29 days for initial, development, mid-season and late season stages, respectively. The single Kc values for the initial, mean and end of the late season stages were established as 0.25, 1.43 and 0.75, respectively. The use of these Kc values will allow adjusting irrigation water doses to water requirements, thus reducing the volume of water applied and improving the irrigation application efficiencies in chufa crop.

IRRIGAMETER USE FOR ESTIMATING CROP EVAPOTRANSPIRATION IN PROTECTED ENVIRONMENT

ABSTRACT In the face of climatic adversities associated with water lacking for irrigation, crop cultivation in greenhouses in Brazil has increased significantly, thereby demanding research that makes it possible to estimate crop water demand when grown in these environments. Therefore, the objective of this study was to evaluate the performance of Irrigameters to estimate the evapotranspiration of cowpea grown in protected environment. The experiment was conducted in the experimental area of the State University of Southwest of Bahia (UESB) under protected environment and the cowpea variety used was BRS Guariba. For this study, two Irrigameters were installed for the direct estimation of the daily crop evapotranspiration. Likewise, with the use of an automatic weather, the meteorological data were collected and the crop evapotranspiration (ETc) was estimated using the Kc values recommended for different phases of the crop. The data collected by the Irrigameter were compared with the data estimated by the Penman-Monteith method, as well as with Radiation and Blaney Criddle methods at one-, two- and three-day intervals. The results show that all the methods were efficient and accurate at estimating ETc at all studied intervals.

Modelling evapotranspiration of soilless cut roses 'Red Naomi' based on climatic and crop predictors

This study aimed to estimate the daily crop evapotranspiration (ETc) of soilless cut ‘Red Naomi’ roses, cultivated in a commercial glass greenhouse, using climatic and crop predictors. A multiple stepwise regression technique was applied for estimating ETc using the daily relative humidity, stem leaf area and number of leaves of the bended stems. The model explained 90% of the daily ETc variability (R2 = 0.90, n = 33, P < 0.0001) measured by weighing lysimeters. The mean relative difference between the observed and the estimated daily ETc was 9.1%. The methodology revealed a high accuracy and precision in the estimation of daily ETc.

Estimation of evapotranspiration using the crop canopy temperature at field to regional scales in large irrigation district

Evapotranspiration (ET) is a major component of the hydrologic cycle, and its accurate estimation is essential in water resource management. In this study, field experiments were performed from 2015 to 2016 in the Jiefangzha Irrigation Area, Inner Mongolia, in China. To estimate the daily crop ET (ETd) using the midday canopy and air temperature difference (Tc-Ta) and net radiation (Rnd), the S-I model (Seguin and Itier, 1983) was calibrated and validated based on observations from maize and sunflower fields. The canopy temperature and meteorological factors were monitored continuously and synchronously from June to August with a Canopy Temperature and Meteorology Monitoring System (CTMS). Parameters a and b in the S-I model were fitted at 10:00 to 16:00 by linear regression analysis between (ETd - Rnd) and (Tc - Ta), from June to August 2015. Based on the values of a and b, the daily ET can be estimated using the S-I model (named ETM) from 10:00 to 16:00 in 2016, which provided good results for all the statistical parameters. The S-I model has performed reasonably well in predicting the ETd during the maize and sunflower growth period at the field scale. The Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) was employed to produce and fuse daily Land Surface Temperature (LST) (30 m) data by integrating high-spatial Landsat data and high-temporal MODIS images during the primary growing period of maize and sunflowers from June to August in 2015 and 2016. The fused LSTs exhibited good performance compared with the canopy temperature observed using the CTMS system in situ. Afterwards, the daily scale-field ET (30 m) was estimated by using the validated S-I model during the primary growing periods for maize and sunflowers at 11:00 in 2015 and 2016. The results showed that the estimated values of ET from the S-I model were consistent with the results for the regional water balance, with average relative error (RE) values of 7.0%, 5.0%, 9.4% and 7.3% (absolute value) in two years, in the Huangji, Qinghui, Wula and Yangjiahe sections of the Jiefangzha Irrigation Area, respectively. This finding indicates that as a relatively simple and convenient method, the S-I model could be applied to estimate the ET at a regional scale.

A Bayesian modelling approach to forecasting short-term reference crop evapotranspiration from GCM outputs

Evapotranspiration is one of the most important climate variables for agricultural and environmental management. We investigate the characteristics of daily crop evapotranspiration (ETo) forecasts up to 16 days ahead derived from GCM outputs using the Penman-Monteith Equation. Furthermore, we propose a post-processing method to calibrate the raw ETo forecasts to observations and improve overall reliability and skill. The post-processing method comprises: (1) the Yeo-Johnson transformation to handle the non-normal distribution of daily ETo, (2) the bi-variate normal distribution to formulate the relationship between transformed raw forecasts and observations, and (3) the Schaake shuffle to establish realistic temporal behaviour in each ensemble member. For three distinct Australian case-study locations, ETo forecasts derived from raw ACCESS-S1 outputs are positively correlated with observations up to 16 days ahead. However, raw forecasts verify more poorly than naïve climatology forecasts because of significant bias and poor ensemble spreads. Post-processing the raw ACCESS-S1 ETo improves skill and reliability markedly. Skilful daily ETo forecasts are achieved in the first week, and the skill of cumulative ETo forecasts extends beyond two weeks into the future. The proposed ETo post-processing method could be applied to support operational, multi-week forecasting of short-term ETo in support of the day-to-day decisions of irrigators in Australia and elsewhere.