Special Issue "Crop Evapotranspiration"

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Water Use and Irrigation".

Deadline for manuscript submissions: closed (31 December 2018).

Special Issue Editors

Dr. Andrew N. French
Website
Guest Editor
Arid-Land Agricultural Research Center, United States Department of Agriculture–Agricultural Research Service (USDA-ARS), Maricopa, AZ 85138, USA
Dr. Ray G. Anderson
Website
Guest Editor
US Salinity Laboratory, USDA-Agricultural Research Service, George E. Brown Jr. Salinity Laboratory, 450 W. Big Springs Rd., Riverside, CA, 92507-4617, USA

Special Issue Information

Dear Colleagues,

Knowledge of evapotranspiration (ET) over croplands is becoming increasingly important across multiple disciplines, spatial scales, and time. ET estimation is critical for addressing immediate needs at farm scales including improved crop water management and irrigation efficiencies, weather and crop-stress forecasting, and decision support tools. Additionally, large-scale ET model development and validation are critically needed at watershed to continental scales to help assess agronomic, hydrological, and economic impacts of drought and climate change.

In recent years significant advances in ET science have been made to address these issues. Field experiments assessing ET have considered multiple crop types, wide ranges in cultivars, differing management practices, and environmental settings. Biophysical models have improved their characterization of ET. Remote sensing sensors and platforms have become increasingly available for ET research, providing a greater ability to synthesize model estimates with diverse sensors. Noteworthy are the accessibility of Landsat, MODIS, Sentinel 2 data sets, along with soon-to-be-available data from the multispectral ECOSTRESS  and the high repeat period Venus missions.

This Special Issue will focus on Crop Evapotranspiration in both irrigated and non-irrigated environments. We welcome novel research, reviews and opinion pieces covering all ET-related topics. We are especially interested in recent integrated ET research using data fusion techniques, combining biophysical models with observations, evaluating the roles of simple vs. complex models, ET estimation at multiple spatial scales, and assessments of the impact of advances in remote sensing technology using satellites, aircraft, and drones.

Dr. Andrew N. French
Dr. Ray G. Anderson
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • evapotranspiration
  • crop water requirements
  • remote sensing
  • satellites
  • drones
  • multispectral
  • thermal infrared
  • irrigation
  • drought
  • biophysical modeling
  • watersheds
  • decision support tools
  • soil moisture

Published Papers (10 papers)

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Editorial

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Open AccessEditor’s ChoiceEditorial
Crop Evapotranspiration
Agronomy 2019, 9(10), 614; https://doi.org/10.3390/agronomy9100614 - 05 Oct 2019
Cited by 2
Abstract
Evapotranspiration (ET) is one of the largest components of the water cycle, and accurately measuring and modeling ET is critical for improving and optimizing agricultural water management. However, parameterizing ET in croplands can be challenging due to the wide variety of irrigation strategies [...] Read more.
Evapotranspiration (ET) is one of the largest components of the water cycle, and accurately measuring and modeling ET is critical for improving and optimizing agricultural water management. However, parameterizing ET in croplands can be challenging due to the wide variety of irrigation strategies and techniques, crop varieties, and management approaches that employ traditional tabular ET and make crop coefficient approaches obsolete. This special issue of Agronomy highlights nine approaches to improve the measurement and modeling of ET across a range of spatial and temporal resolutions and differing environments that address some of the challenges encountered. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)

Research

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Open AccessArticle
Using Hyperspectral and Multispectral Indices to Detect Water Stress for an Urban Turfgrass System
Agronomy 2019, 9(8), 439; https://doi.org/10.3390/agronomy9080439 - 08 Aug 2019
Cited by 1
Abstract
Spectral reflectance measurements collected from hyperspectral and multispectral radiometers have the potential to be a management tool for detecting water and nutrient stress in turfgrass. Hyperspectral radiometers collect hundreds of narrowband reflectance data compared to multispectral radiometers that collect three to ten broadband [...] Read more.
Spectral reflectance measurements collected from hyperspectral and multispectral radiometers have the potential to be a management tool for detecting water and nutrient stress in turfgrass. Hyperspectral radiometers collect hundreds of narrowband reflectance data compared to multispectral radiometers that collect three to ten broadband reflectance data for a cheaper cost. Spectral reflectance data have been used to create vegetation indices such as the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (RVI) to assess crop growth, density, and fertility. Other indices such as the water band index (WBI) (narrowband index) and green-to-red ratio index (GRI) (both broadband and narrowband index) have been proposed to predict soil moisture status in turfgrass systems. The objective of this study was to compare the value of multispectral and hyperspectral radiometers to assess soil volumetric water content (VWC) and tall fescue (Festuca arundinacea Schreb.) responses. The multispectral radiometer VI had the strongest relationships to turfgrass quality, biomass, and tissue N accumulation during the trial period (April 2017–August 2018). Soil VWC had the strongest relationship to WBI (r = 0.60), followed by GRI and NDVI (both r = 0.54) for the 0% evapotranspiration (ET). Nonlinear regression showed strong relationships at high water stress periods in each year for WBI (r = 0.69–0.79), GRI (r = 0.64–0.75), and NDVI (r = 0.58–0.79). Broadband index data collected using a mobile multispectral sensor is a cheaper alternative to hyperspectral radiometry and can provide better spatial coverage. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Open AccessArticle
Grape Rootstock Response to Salinity, Water and Combined Salinity and Water Stresses
Agronomy 2019, 9(6), 321; https://doi.org/10.3390/agronomy9060321 - 18 Jun 2019
Cited by 2
Abstract
Diminishing availability of non-saline water in arid and semiarid regions is of concern to all irrigated agricultural producers, including wine and grape producers. Grapes are not a salt tolerant crop and producers often face the choice of either limiting fresh water application, using [...] Read more.
Diminishing availability of non-saline water in arid and semiarid regions is of concern to all irrigated agricultural producers, including wine and grape producers. Grapes are not a salt tolerant crop and producers often face the choice of either limiting fresh water application, using alternative saline waters or a combination of both. We examined the salt tolerance and effect of restricted water application on three purported salt tolerant rootstocks grafted to Cabernet Sauvignon scion in a 4-year replicated field experiment. ANOVA indicated significant effects of salinity water stress and rootstock on fruit yields. The 140 Ruggeri scion was the top producer across all treatments including control, followed by Salt Creek, with St. George significantly less productive than 140 Ruggeri across all treatments. In terms of salt tolerance, Salt Creek and 140 Ruggeri were not statistically different but St. George was significantly less tolerant than Salt Creek. In terms of drought tolerance (relative yield), there were no statistical differences among rootstocks. Soil salinity profiles and soil moisture sensors indicated reduced water consumption under high salinity, thus no matric stress under 60% of optimal water application when high salt stress was present. The multiplicative stress model where salt and water stress are individually evaluated did not satisfactorily predict yield under combined salinity and reduced water application, likely due to decreased water consumption under saline conditions. Short term (one year) experiments underestimate salt damage to grape vines as salt tolerance decreased over the 4-year experiment. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Open AccessArticle
Radiometric Method for Determining Canopy Stomatal Conductance in Controlled Environments
Agronomy 2019, 9(3), 114; https://doi.org/10.3390/agronomy9030114 - 27 Feb 2019
Cited by 2
Abstract
Canopy stomatal conductance is a key physiological factor controlling transpiration from plant canopies, but it is extremely difficult to determine in field environments. The objective of this study was to develop a radiometric method for calculating canopy stomatal conductance for two plant species—wheat [...] Read more.
Canopy stomatal conductance is a key physiological factor controlling transpiration from plant canopies, but it is extremely difficult to determine in field environments. The objective of this study was to develop a radiometric method for calculating canopy stomatal conductance for two plant species—wheat and soybean from direct measurements of bulk surface conductance to water vapor and the canopy aerodynamic conductance in controlled-environment chambers. The chamber provides constant net radiation, temperature, humidity, and ventilation rate to the plant canopy. In this method, stepwise changes in chamber CO2 alter canopy temperature, latent heat, and sensible heat fluxes simultaneously. Sensible heat and the radiometric canopy-to-air temperature difference are computed from direct measurements of net radiation, canopy transpiration, photosynthesis, radiometric temperature, and air temperature. The canopy aerodynamic conductance to the transfer of water vapor is then determined from a plot of sensible heat versus radiometric canopy-to-air temperature difference. Finally, canopy stomatal conductance is calculated from canopy surface and aerodynamic conductances. The canopy aerodynamic conductance was 5.5 mol m−2 s−1 in wheat and 2.5 mol m−2 s−1 in soybean canopies. At 400 umol mol−1 of CO2 and 86 kPa atmospheric pressure, canopy stomatal conductances were 2.1 mol m−2 s−1 for wheat and 1.1 mol m−2 s−1 for soybean, comparable to canopy stomatal conductances reported in field studies. This method measures canopy aerodynamic conductance in controlled-environment chambers where the log-wind profile approximation does not apply and provides an improved technique for measuring canopy-level responses of canopy stomatal conductance and the decoupling coefficient. The method was used to determine the response of canopy stomatal conductance to increased CO2 concentration and to determine the sensitivity of canopy transpiration to changes in canopy stomatal conductance. These responses are useful for improving the prediction of ecosystem-level water fluxes in response to climatic variables. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Open AccessArticle
Using Neural Networks to Estimate Site-Specific Crop Evapotranspiration with Low-Cost Sensors
Agronomy 2019, 9(2), 108; https://doi.org/10.3390/agronomy9020108 - 23 Feb 2019
Cited by 3
Abstract
Irrigation efficiency is facilitated by matching irrigation rates to crop water demand based on estimates of actual evapotranspiration (ET). In production settings, monitoring of water demand is typically accomplished by measuring reference ET rather than actual ET, which is then adjusted approximately using [...] Read more.
Irrigation efficiency is facilitated by matching irrigation rates to crop water demand based on estimates of actual evapotranspiration (ET). In production settings, monitoring of water demand is typically accomplished by measuring reference ET rather than actual ET, which is then adjusted approximately using simplified crop coefficients based on calendars of crop maturation. Methods to determine actual ET are usually limited to use in research experiments for reasons of cost, labor and requisite user skill. To pair monitoring and research methods, we co-located eddy covariance sensors with on-farm weather stations over two different irrigated crops (vegetable beans and hazelnuts). Neural networks were used to train a neural network and utilize on-farm weather sensors to report actual ET as measured by the eddy covariance method. This approach was able to robustly estimate ET from as few as four sensor parameters (temperature, solar radiation, humidity and wind speed) with training time as brief as one week. An important limitation found with this machine learning method is that the trained network is only valid under environmental and crop conditions similar to the training period. The small number of required sensors and short training times demonstrate that this approach can estimate site-specific and crop specific ET. With additional field validation, this approach may offer a new method to monitor actual crop water demand for irrigation management. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Open AccessArticle
Evaluation of Evapotranspiration from Eddy Covariance Using Large Weighing Lysimeters
Agronomy 2019, 9(2), 99; https://doi.org/10.3390/agronomy9020099 - 20 Feb 2019
Cited by 3
Abstract
Evapotranspiration (ET) is an important component in the water budget and used extensively in water resources management such as water planning and irrigation scheduling. In semi-arid regions, irrigation is used to supplement limited and erratic growing season rainfall to meet crop water demand. [...] Read more.
Evapotranspiration (ET) is an important component in the water budget and used extensively in water resources management such as water planning and irrigation scheduling. In semi-arid regions, irrigation is used to supplement limited and erratic growing season rainfall to meet crop water demand. Although lysimetery is considered the most accurate method for crop water use measurements, high-precision weighing lysimeters are expensive to build and operate. Alternatively, other measurement systems such as eddy covariance (EC) are being used to estimate crop water use. However, due to numerous explicit and implicit assumptions in the EC method, an energy balance closure problem is widely acknowledged. In this study, three EC systems were installed in a field containing a large weighing lysimeter at heights of 2.5, 4.5, and 8.5 m. Sensible heat flux (H) and ET from each EC system were evaluated against the lysimeter. Energy balance closure ranged from 64% to 67% for the three sensor heights. Results showed that all three EC systems underestimated H and consequently overestimated ET; however, the underestimation of H was greater in magnitude than the overestimation of ET. Analysis showed accuracy of ET was greater than energy balance closure with error rates of 20%–30% for half-hourly values. Further analysis of error rates throughout the growing season showed that energy balance closure and ET accuracy were greatest early in the season and larger error was found after plants reached their maximum height. Therefore, large errors associated with increased biomass may indicate unaccounted-for energy stored in the plant canopy as one source of error. Summing the half-hourly data to a daily time-step drastically reduced error in ET to 10%–15%, indicating that EC has potential for use in agricultural water management. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Open AccessArticle
Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA
Agronomy 2018, 8(12), 278; https://doi.org/10.3390/agronomy8120278 - 26 Nov 2018
Cited by 5
Abstract
Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that [...] Read more.
Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6–8 mm/day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm/day, METRIC 6 mm/day, and VISW 8 mm/day. For alfalfa, the ET values from TSEB were 8.0 mm/day, METRIC 5 mm/day, and VISW 6 mm/day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from −10% to +18%, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators—potential ET (ET ), FAO-56 ET, and USDA-SW gravimetric-ET— showed still greater deviations, up to 35% of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Open AccessArticle
Effect of Irrigation and Nitrogen Fertilization Strategies on Silage Corn Grown in Semi-Arid Conditions
Agronomy 2018, 8(10), 208; https://doi.org/10.3390/agronomy8100208 - 28 Sep 2018
Cited by 6
Abstract
In water-scarce regions, high yield and improved water use efficiency (WUE) of crops can be obtained if water and nitrogen (N) are properly applied. While water and N have been the subject of research worldwide, studies are needed to advance our understanding on [...] Read more.
In water-scarce regions, high yield and improved water use efficiency (WUE) of crops can be obtained if water and nitrogen (N) are properly applied. While water and N have been the subject of research worldwide, studies are needed to advance our understanding on the complexity of their interaction. A field experiment was conducted at the University of Wyoming Powell Research and Extension Center in 2014 and 2015 growing seasons to determine the effect of irrigation water and N on growth, dry matter (DM) yield, and WUE of silage corn (Zea mays L.) grown under on-surface drip irrigation (ODI). The experiment was laid out as a randomized complete block design in split-plot arrangement with three replications. Irrigation was the main treatment and included 100ETc (100% crop evapotranspiration), 80ETc, and 60ETc. Nitrogen was the sub-treatment and included 0, 90, 180, 270, and 360 kg N ha−1 as urea-ammonium-nitrate solution Results showed that irrigation water, N, and application timing significantly affected growth and DM yield, especially at late vegetative and mid reproductive growth stages. At harvest (R4), no significant difference was observed between 180 kg N ha−1 and 270 kg N ha−1 on DM yield and WUE. However, significant differences of DM yield were observed between irrigation treatments, and 100ETc and 80ETc did not differ in WUE. Our findings suggest that 100ETc and 180 kg N ha−1 is the best combination for high yielding corn for silage grown in a semi-arid climate under ODI. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Open AccessArticle
Can Faba Bean Physiological Responses Stem from Contrasting Traffic Management Regimes?
Agronomy 2018, 8(10), 200; https://doi.org/10.3390/agronomy8100200 - 21 Sep 2018
Cited by 2
Abstract
Our study examined how faba beans (Vicia faba L.) grown in soil conditions that simulate common traffic management regimes and water availabilities displayed alterations to their physiological state. Physiological changes were tracked through plant and sensor-based measurements, such as evapotranspiration, water use [...] Read more.
Our study examined how faba beans (Vicia faba L.) grown in soil conditions that simulate common traffic management regimes and water availabilities displayed alterations to their physiological state. Physiological changes were tracked through plant and sensor-based measurements, such as evapotranspiration, water use efficiency, aboveground biomass, stomatal conductance, and normalized difference vegetation index. A greenhouse experiment comprised of faba beans were sown into pots of two different soil types that were separated by treatments of dry bulk density and volumetric water content. The compaction treatment with a bulk density of 1.2 g cm−3 coupled with a volumetric water content of 41% displayed more favorable changes to the physiological state of the faba beans than the contrasting treatment of 1.4 g cm−3 bulk density at 33% volumetric water content. Handheld sensor-based measurements, such as the normalized difference vegetation index, exhibited a strong correlation with faba bean biomass production. Furthermore, the stomatal conductance was able to reveal plant water stress and capture evapotranspiration responses. Conclusive observations showed that increasing soil compaction restricted plant productivity. However, the presence of high water content was shown to offset the negative effects of heavily applied compaction while relatively lower water contents exacerbated differences in plant responses across compaction treatments. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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Review

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Open AccessReview
Modelling Crop Transpiration in Greenhouses: Different Models for Different Applications
Agronomy 2019, 9(7), 392; https://doi.org/10.3390/agronomy9070392 - 17 Jul 2019
Cited by 7
Abstract
Models for the evapotranspiration of greenhouse crops are needed both for accurate irrigation and for the simulation or management of the greenhouse climate. For this purpose, several evapotranspiration models have been developed and presented, all based on the Penman–Monteith approach, the “big-leaf” model. [...] Read more.
Models for the evapotranspiration of greenhouse crops are needed both for accurate irrigation and for the simulation or management of the greenhouse climate. For this purpose, several evapotranspiration models have been developed and presented, all based on the Penman–Monteith approach, the “big-leaf” model. So, on the one hand, relatively simple models have been developed for irrigation scheduling purposes, and on the other, “knowledge–mechanistic” models have been developed for climate control purposes. These models differ in the amount of detail about variables, such as stomatal and aerodynamic conductance. The aim of this review paper is to present the variables and parameters affecting greenhouse crop transpiration, and to analyze and discuss the existing models for its simulation. The common sub-models used for the simulation of crop transpiration in greenhouses (aerodynamic and stomatal conductances, and intercepted radiation) are evaluated. The worth of the multilayer models for the simulation of the mass and energy exchanges between crops and air are also analyzed and discussed. Following the presentation of the different models and approaches, it is obvious that the different applications for which these models have been developed entail varying requirements to the models, so that they cannot always be compared. Models developed in different locations (high–low latitudes or for closed or highly ventilated greenhouses) are discussed, and their sensitivity to different parameters is presented. Full article
(This article belongs to the Special Issue Crop Evapotranspiration)
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