Special Issue "Crop Evapotranspiration: Accurate Ground and Remote Sensing Observations and Computational Tools"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 5300

Special Issue Editors

Prof. Dr. Luis Santos Pereira
grade E-Mail Website
Guest Editor
Research Center on Landscape, Environment, Agriculture and Food (LEAF), School of Agriculture (ISA), University of Lisbon, 1649-004 Lisbon, Portugal
Interests: reference and crop evapotranspiration; crop water and irrigation requirements; irrigation management; coping with water scarcity; drought characterization and management; performance of irrigation methods
Special Issues, Collections and Topics in MDPI journals
Dr. Paula Paredes
E-Mail Website
Guest Editor
LEAF-Linking Landscape, Environment, Agriculture and Food-Research Center, Associated Laboratory TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisbon, Portugal
Interests: crop and reference evapotranspiration; crop water requirements; irrigation management; modelling; water–yield relations; coping with water scarcity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Evapotranspiration (ET) plays a main role in the water balance at various scales, from the plant and the field to the watershed or the irrigation system. ET allows understanding the hydrological behavior of natural and cropped ecosystems and adopting improved water resource planning and management. With the increasing competition for water and decreasing water resource availability, the need to cope with water scarcity and climate change increases the importance of accurate knowledge and estimation of ET from annual and perennial crops and landscapes. Improved use of ET information allows enhancing water use in agriculture at various scales. Therefore, there is a great need for an accurate scrutiny of the ET measurements, of weather data, and of data processing procedures.

This Special Issue encourages the submission of review and application research articles which contribute to accurate measurement and estimation of crop evapotranspiration in a broad sense (plants, trees, natural, and human-made landscapes) aiming at improved crop and irrigation management. Potential topics include emerging fields such as the use of Internet of Things (IoT), big data, cloud computing, Artificial intelligence (AI), and advanced sensing technologies oriented to crop and irrigation management in agriculture.

Prof. Dr. Luis Santos Pereira
Dr. Paula Paredes
Guest Editors

Manuscript Submission Information

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Keywords

  • crop evapotranspiration (ETc)
  • accurate ET measuring and estimation
  • proximal and remote sensing
  • thermal sensing
  • plant and soil sensors
  • data processing, big data, cloud computing, artificial intelligence
  • IoT and multiuser application solutions
  • simulation models, irrigation requirements, and precise irrigation
  • assessing advection impacts
  • using saline and treated wastewater

Published Papers (5 papers)

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Research

Article
CSM-CERES-Wheat Sensitivity to Evapotranspiration Modeling Frameworks under a Range of Wind Speeds
Water 2022, 14(19), 3023; https://doi.org/10.3390/w14193023 - 26 Sep 2022
Viewed by 513
Abstract
Crop modeling uncertainty is expected to be high under weather data limitations; thus, jeopardizing decision-making on food-water security. Missing near-surface wind speed (u2) data required to accurately estimate reference evapotranspiration (ETo) seemed to significantly affect both the potential evapotranspiration [...] Read more.
Crop modeling uncertainty is expected to be high under weather data limitations; thus, jeopardizing decision-making on food-water security. Missing near-surface wind speed (u2) data required to accurately estimate reference evapotranspiration (ETo) seemed to significantly affect both the potential evapotranspiration (ETP) and yield simulations for data-scarce windy regions. In this study, the uncertainty in crop modeling based on different ETP approaches was assessed. In this regard, wheat yield and evapotranspiration were simulated with the CSM-CERES-Wheat model using either the Priestley-Taylor/Ritchie (PT) or the Penman-Monteith DSSAT (PM) methods under “rain-fed, low-nitrogen stress”, “rain-fed, high nitrogen stress”, “full irrigation, low nitrogen stress”, and “full irrigation, high nitrogen stress” scenarios for a u2 range from 0.8 to 3.5 m s−1. The daily weather data required to run the model were retrieved from 18 semi-arid areas located in western Iran. The statistically significant differences in mean yield and cumulative distribution were determined by the non-parametric Wilcoxon signed-rank and the Kolmogorov-Smirnov tests, respectively. The deviation in evaporation and transpiration simulated by applying PT and PM was lower under rain-fed condition. Under “rain-fed, low-nitrogen stress”, the PT-simulated yield deviated significantly (p < 0.05) from PM-simulated yield by more than 26% for the sites with u2 above 3 m s−1. The deviation in ETP estimates did not, however, lead to statistically significant difference in yield distribution curves for almost all sites and scenarios. Nitrogen deficiency resulted in a smaller difference in yield for rain-fed condition. The yield results showed a deviation below 6% under full irrigation condition. Under windy rain-fed condition, high deviation in leaf area index (LAI) and ETP estimates caused a large difference in the actual transpiration to potential transpiration ratio (Ta/TP), and yield. However, the deviation between PT- and PM-simulated LAI and Ta/TP for the full irrigation scenarios was less than 6%. Overall, the results from this study indicate that when soil moisture is depleted, resembling rain-fed condition, simulation of yield appears to be highly sensitive to the estimation of ETP for windy areas. Full article
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Article
Assessing Spatio-Temporal Dynamics of Deep Percolation Using Crop Evapotranspiration Derived from Earth Observations through Google Earth Engine
Water 2022, 14(15), 2324; https://doi.org/10.3390/w14152324 - 27 Jul 2022
Cited by 1 | Viewed by 822
Abstract
Excess irrigation may result in deep percolation and nitrate transport to groundwater. Furthermore, under Mediterranean climate conditions, heavy winter rains often result in high deep percolation, requiring the separate identification of the two sources of deep percolated water. An integrated methodology was developed [...] Read more.
Excess irrigation may result in deep percolation and nitrate transport to groundwater. Furthermore, under Mediterranean climate conditions, heavy winter rains often result in high deep percolation, requiring the separate identification of the two sources of deep percolated water. An integrated methodology was developed to estimate the spatio-temporal dynamics of deep percolation, with the actual crop evapotranspiration (ETc act) being derived from satellite images data and processed on the Google Earth Engine (GEE) platform. GEE allowed to extract time series of vegetation indices derived from Sentinel-2 enabling to define the actual crop coefficient (Kc act) curves based on the observed lengths of crop growth stages. The crop growth stage lengths were then used to feed the soil water balance model ISAREG, and the standard Kc values were derived from the literature; thus, allowing the estimation of irrigation water requirements and deep drainage for independent Homogeneous Units of Analysis (HUA) at the Irrigation Scheme. The HUA are defined according to crop, soil type, and irrigation system. The ISAREG model was previously validated for diverse crops at plot level showing a good accuracy using soil water measurements and farmers’ irrigation calendars. Results show that during the crop season, irrigation caused 11 ± 3% of the total deep percolation. When the hotspots associated with the irrigation events corresponded to soils with low suitability for irrigation, the cultivated crop had no influence. However, maize and spring vegetables stood out when the hotspots corresponded to soils with high suitability for irrigation. On average, during the off-season period, deep percolation averaged 54 ± 6% of the annual precipitation. The spatial aggregation into the Irrigation Scheme scale provided a method for earth-observation-based accounting of the irrigation water requirements, with interest for the water user’s association manager, and at the same time for the detection of water losses by deep percolation and of hotspots within the irrigation scheme. Full article
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Article
Searching for Sustainable-Irrigation Issues of Clementine Orchards in the Syrian Akkar Plain: Effects of Irrigation Method and Canopy Size on Crop Coefficients, Transpiration, and Water Use with SIMDualKc Model
Water 2022, 14(13), 2052; https://doi.org/10.3390/w14132052 - 27 Jun 2022
Viewed by 821
Abstract
Citrus is one of the most valuable crops in Syria, with the largest production areas in the Tartus and Latakia provinces. Water-saving policies have been adopted to modernize the irrigation systems and increase water productivity. Following dedicated research, this study aimed to evaluate [...] Read more.
Citrus is one of the most valuable crops in Syria, with the largest production areas in the Tartus and Latakia provinces. Water-saving policies have been adopted to modernize the irrigation systems and increase water productivity. Following dedicated research, this study aimed to evaluate the water balance in clementine trees irrigated with diverse methods and schedules using the SIMDualKc software model. Two experiments are reported: one with 10–14 years old trees irrigated with different methods (2007−2011) and the other with the same trees but now 18−20 years old, irrigated with different schedules (2015−2019). The SIMDualKc model successfully simulated the soil water contents measured in the various field plots, with root mean square error values lower than 0.004 m3 m−3 and modeling efficiencies up to 0.83. The model-calibrated standard basal crop coefficients (Kcb) were approximately constant throughout all growing stages, assuming values of 0.54−0.55 for the mature trees having smaller height (h) and fraction of ground cover (fc), and 0.64 for older trees with larger canopies, i.e., larger h and fc. With drip irrigation, single Kc had a higher value (1.14) at the end, non-growing, and initial stages, and a lower value (0.75–0.76) during mid-season (Kc mid), because precipitation was lesser then, contributing less to soil evaporation. On the other hand, Kc values were nearly constant with micro-sprinkler and surface irrigation techniques because the ground was fully wetted. The Kcb values derived from the fraction of ground cover and height (A&P approach) were similar to those obtained from the model, thus showing that the A&P approach represents a practical alternative to estimate Kcb in the practice of irrigation management. The soil water balance further revealed a large weight of the terms corresponding to the non-beneficial water consumption and non-consumptive water use when the fraction wetted was large and the application efficiencies were low. These terms were reduced, namely, evaporation losses when drip irrigation was used. This study, thus, provides a valuable tool for improving the irrigation management, water saving, and water productivity of Syrian citrus production systems. Full article
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Article
Evapotranspiration and Quantitative Partitioning of Spring Maize with Drip Irrigation under Mulch in an Arid Region of Northwestern China
Water 2021, 13(22), 3169; https://doi.org/10.3390/w13223169 - 10 Nov 2021
Cited by 3 | Viewed by 1137
Abstract
To examine evapotranspiration (ETc), soil evaporation (Es), and transpiration (Tr), and partitioning of ETc, a two-year field experiment was carried out in a maize field with drip irrigation under mulch in an arid region of [...] Read more.
To examine evapotranspiration (ETc), soil evaporation (Es), and transpiration (Tr), and partitioning of ETc, a two-year field experiment was carried out in a maize field with drip irrigation under mulch in an arid region of northwestern China in 2017 and 2018. In the experiment we designed two treatments with full irrigation (T1) and growth stage-based strategic regulated deficit irrigation (T2). The applied irrigation of T2 was 40% of the T1 during both late vegetative and reproductive growth stages. Based on the measurements of soil water content (SWC) and Tr, a dual crop coefficient model (SIMDualKc) was calibrated and validated, and daily ETc, Es, and Tr were estimated. The model can simulate well the dynamic variations of SWC and Tr. The calibrated basic crop coefficient at the initial, mid-season, and end growth stages was 0.2, 1.15, and 0.75, respectively. The ETc was 507.9 and 519.1 mm for the T1 treatment, and 428.9 and 430.9 mm for the T2 treatment. The ratios of Tr to ETc were higher for the two treatments, ~90%, for two years. Collectively, both drip irrigation under mulch and strategic deficit irrigation after canopy covering of the ground can significantly reduce the ineffective proportion of ETc and Es. Full article
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Article
Estimation of Evapotranspiration and Crop Coefficient of Chinese Cabbage Using Eddy Covariance in Northwest China
Water 2021, 13(19), 2781; https://doi.org/10.3390/w13192781 - 07 Oct 2021
Cited by 2 | Viewed by 1234
Abstract
Chinese cabbage is a key vegetable crop in northwest China. It is of great significance to study the evapotranspiration (ET) and crop coefficient (Kc) for agricultural water-saving management in this area. Eddy covariance (EC) was used to measure [...] Read more.
Chinese cabbage is a key vegetable crop in northwest China. It is of great significance to study the evapotranspiration (ET) and crop coefficient (Kc) for agricultural water-saving management in this area. Eddy covariance (EC) was used to measure the ET and Kc of Chinese cabbage in northwest China from 1 May to 16 October 2020, in order to analyze the characteristics of these variables under plastic mulch. The results showed that the average Kc of the first crop of cabbage was higher in the middle and late stages, with values of 1.08 and 1.09 during the heading and maturity stages, respectively. The average Kc of the second crop of cabbage was higher in the middle stage, with values of 1.10 and 1.13 during the rosette and heading stages, respectively. The average annual Kc of Chinese cabbage was 0.81. Although Kc was higher in the middle and late periods, the water use efficiency was still 28.96 kg·ha−1·mm−1. The annual ET of Chinese cabbage was 505.3 mm. The study revealed the variation pattern of ET and Kc of Chinese cabbage, which provides an important scientific basis for the irrigation management of Chinese cabbage and is of great significance to guide the practice of water-saving vegetable planting. Full article
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