Assessment Of Evapotranspiration Research Articles

Assessment of maize evapotranspiration, water requirements and productivity using weather data in Coimbatore’s semiarid climate

Accurately estimating crop water use is crucial for efficient water management in conservation agriculture, especially in Coimbatore's semiarid climate. This study assessed maize water use and productivity over three growing seasons (2023-2024) at AC&RI, Coimbatore. Irrigation applied each season varied between 500.8mm and 554.1 mm, averaging 535.8 mm, while total water supply ranged from 810.6 to 985.3 mm. Actual evapotranspiration (ETa) was estimated using locally developed crop coefficient curves (Lkc) and FAO crop coefficients. Water productivity for maize was calculated based on these estimates. Daily ETa for maize ranged from 0.9mm to 8.2 mm. Other than the different seasons, ETa varied from 342.6 to 372 mm, averaging 355.6 mm with the Lkc curve. By FAO Kc, ETa ranged from 400.8mm to 479.1 mm, with an average of 444.2 mm. The irrigation requirement ranged from 579.6mm to 672.7 mm, with an average of 629.5 mm using LKc. Using FAO Kc, the range was 637.8mm to 762.9 mm, with an average of 718 mm. Crop water use efficiency (CWUE) ranged from 0.8 and 0.9 kg/m³, with an average of 0.9 kg/m³. The evapotranspiration water use efficiency (ETWUE) ranged from 2.0 to 2.1 kg/m³, with an average of 2.1 kg/m³. The irrigation water use efficiency (IWUE) varied across seasons, averaging 1.4 kg/m³. Strong correlations were observed between CWUE, IWUE, and the amount of seasonal irrigation (R² = 0.98 and 0.99, respectively). CWUE and ETWUE strongly correlated with IWUE (R² = 0.98 and 0.75, respectively). These findings suggest that maize irrigation in Coimbatore's semiarid regions should be tailored to local conditions to enhance water productivity.

Assessment of reference evapotranspiration forecasting in the Mediterranean climate of Central Chile using the ASCE standardized Penman-Monteith equation, the Hargreaves-Samani equation, and weather predictions from the Global Forecast System model

Accurate estimation of crop evapotranspiration (ETc) is essential for effective agricultural water resource planning. To determine ETc it is common multiplying the reference evapotranspiration (ETref) by an appropriate crop coefficient (Kc). Forecasting ETref could be particularly beneficial for irrigation scheduling. In this work, daily and cumulative (7 days) ETref predictions were estimated with the Penman-Monteith (PM) and the Hargreaves-Samani (HS) models using environmental variables obtained from the Global Forecast System (GFS). Results were compared with ETref calculated with the ASCE (American Society of Civil Engineers) PM equation from measured daily values of solar radiation, air temperature, relative humidity and wind speed. Four weather stations located in Central Chile during 2020 to 2022 were used. The best results were obtained using the HS equation, for all weather stations, the statistical indicators for daily ETref predictions fall within the following ranges: Accuracy (defined as the percentage of daily ETref predictions with an absolute error within 1mmd−1) varies between 72.8% and 91.8%; the root mean square error (RMSE) ranges from 0.59mmd−1 to 0.98mmd−1; the normalized root mean square error (NRMSE) is between 16.1% and 24.1%; the mean bias error (MBE) is between 0.10mmd−1 and 0.36mmd−1; and the normalized mean bias error (NMBE) varies from 2.5% to 8.3%. On the other hand, the indicators for the 7-day cumulative ETref forecasts were: RMSE from 2.86mm to 5.08mm; NRMSE from 11.0% to 16.3%; MBE from 0.66mm to 2.57mm; and NMBE from 2.4% to 8.3%. These results suggest that HS ETref values predicted from GFS temperature forecasts could be effective for foreseeing near-future water demand and enhancing the accuracy of irrigation scheduling and management in Central Chile.

Field scale partitioning of Landsat land surface temperature into soil and canopy components for evapotranspiration assessment using a two-source energy balance model

Field scale partitioning of Landsat land surface temperature into soil and canopy components for evapotranspiration assessment using a two-source energy balance model

Phenotyping of almond rootstocks for the assessment of evapotranspiration using remote sensing energy balance models

Phenotyping of almond rootstocks for the assessment of evapotranspiration using remote sensing energy balance models

A first assessment of airborne HyTES-based land surface temperature and evapotranspiration

The Hyperspectral Thermal Emission Spectrometer (HyTES) offers high spatial and spectral resolution thermal infrared (TIR) airborne measurements, which are crucial for deriving land surface temperature and emissivity (LST&E). These measurements have wide-ranging applications, particularly in understanding water stress and plant water use. One critical application of TIR satellite-sensor systems is the estimation of evapotranspiration (ET), which can be derived from LST. ET is essential for modeling water fluxes from the land surface, and various algorithms leverage LST as a key boundary condition for this purpose. In this study, we apply an ET algorithm to HyTES LST data for the first time, using an analytical surface energy balance model, the Surface Temperature Initiated Closure (STIC) version 1.3. We provide an overview of the STIC model, detailing its application to HyTES data, including the integration of ancillary datasets. We demonstrate the practicality of this approach by presenting ET and LST calculations for HyTES flightlines from three field campaigns conducted in 2019, 2021, and 2023. To validate our results, we compare the derived ET and LST against available in situ measurements, including eddy covariance-derived latent heat flux and radiometer-derived LST. While this study focuses on HyTES data, the same methodology is applicable to any instantaneous LST dataset. Advancing TIR mapping of ET is crucial for applications in agriculture, water management and for understanding the evolving water cycle.

Quantifying energy fluxes in Tarai region of India during post-monsoon season: Insights from METRIC model, ET station and remote sensing

Accurate evapotranspiration (ET) assessment is crucial for agricultural water management, encompassing crop water requirements, irrigation scheduling, water budgeting and drought monitoring. This study integrates remote sensing-based surface energy balance model with in-situ ET measurements to evaluate surface energy fluxes and ET in Pantnagar, Tarai region. The Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model, using high-resolution remote sensing data, was validated against observations from an ET station equipped with large aperture scintillometer and micrometeorological tower, situated in sugarcane farm at Govind Ballabh Pant University of Agriculture & Technology (GBPUA&T), Pantnagar. On November 13, 2021, METRIC and Landsat-9 satellite data estimated an instantaneous ET of 7.39 mm day-1, closely aligned with the observed value of 6.72 mm day-1 recorded by the ET station. The findings confirm the METRIC model's high accuracy for spatial ET estimation and its associated micrometeorological variables. This study underscores the utility of the METRIC model, ET station and remote sensing in determining ET and energy flux which may be further utilised in the estimation of crop water requirement, energy fluxes and irrigation water management for sugarcane cultivation in the Tarai region.

Evaluation of different methods for reference evapotranspiration assessment: A case study for Ukraine

The paper presents the results of the study devoted to the examination of the accuracy and reliability of the temperature-based approach of the ‘Evapotranspiration Calculator (Ukraine)’ application for the reference evapotranspiration assessment in Ukraine. The objective of the study was to determine the level of reliability and accuracy of modern alternative temperature-based algorithms for the reference evapotranspiration assessment in Ukraine compared to internationally recognized methods. The study was carried out for the territories of Ukraine, based on the meteorological data for the period 2021–2023. The basic methodology was compared to the standard Penman-Monteith method and the method of Hargreaves. The comparison was performed using the values of MAPE, RMSE, and correlation coefficient. Statistical analysis testified that there is a strong correlation and subtle difference between the Hargreaves method and the ‘Evapotranspiration Calculator (Ukraine)’ application, with an average MAPE of 30.3%, the correlation coefficient of 0.92, and RMSE of 1.46 mm. The difference between the Penman-Monteith method and the studied methodology was greater, as the MAPE averaged 41.0%, the correlation coefficient was 0.87, and the RMSE value was 2.05 mm. However, the high variation of the results by the regions of the country and the years of the study did not allow us to draw solid conclusions on whether the methodology embedded in the ‘Evapotranspiration Calculator (Ukraine)’ application is inferior to the method of Penman-Monteith. Further studies are required to clarify this issue through the improvement in the dataset, involvement of in-field reference evapotranspiration measurements, and application of adjustment guidelines for the ‘Evapotranspiration Calculator (Ukraine)’ application.

Comparison of Actual Evapotranspiration assessment by satellite-based model SEBS and hydrological model BBH in northern Tunisia

Comparison of Actual Evapotranspiration assessment by satellite-based model SEBS and hydrological model BBH in northern Tunisia

Assessment of satellite-based water requirements for a drip-irrigated apple orchard in Mediterranean agroclimatic conditions

Accurate assessment of evapotranspiration (ETa) and crop coefficient (Kc) is crucial for optimizing irrigation practices in water-scarce regions. While satellite-based surface energy balance models offer a promising solution, their application to sparse canopies like apple orchards requires specific validation. This study investigated the spatial and temporal dynamics of ETa and Kc in a drip-irrigated ‘Pink Lady’ apple orchard under Mediterranean conditions over three growing seasons (2012/13, 2013/14, 2014/15). The METRIC model, incorporating calibrated sub-models for leaf area index (LAI), surface roughness (Zom), and soil heat flux (G), was employed to estimate ETa and Kc. These estimates were validated against field-scale Eddy Covariance data. Results indicated that METRIC overpredicted Kc and ETa with errors less than 10 %. These findings highlight the potential of the calibrated METRIC model as a valuable decision-making tool for irrigation management in apple orchards.

Recurrent neural networks and sensitivity analysis for accurate monthly evapotranspiration estimation in the region of Fez, Morocco

AbstractGood water management is essential, including addressing water scarcity, which is exacerbated by climate change and increasing food demand due to population growth. In modern era of high technology, artificial intelligence and the Internet of Things have an important role to play in decision‐making approaches. According to hydro‐agrological studies, an accurate assessment of evapotranspiration is necessary for irrigation control, and to have an in‐depth understanding of the environmental factor interactions, a sensitivity analysis should be carried out. One of the tools, alongside empirical equations, is artificial intelligence for time‐series prediction. Thus, we compared several models for Penman–Monteith ET0 estimation to see which one performs better in the arid area of Morocco using meteorological data from the region of Fes. They were evaluated according to the MSE, RMSE, MAE, MAPE, and R2 and the variance of error distribution to show the performances of linear regression, K‐Nearest Neighbor, decision tree, random forest, support vector regression, long short‐term memory, and artificial neural network. According to the findings, LSTM outperformed the models with satisfactory results and an accuracy rate of 99.82%. An underlying mechanism of sensitivity analysis was also introduced to find the contribution of each element and estimate the target with a limited dataset. The findings show satisfactory results of R2 = 98.97%. The distribution and reliability of the prediction were proven using the Taylor diagram and Kruskal–Wallis test for the effectiveness of the study. This research demonstrates the potential of employing data‐driven techniques for evapotranspiration estimation to improve the efficacy of water management strategies. This will help to address present issues and establish sustainable water practices in the face of changing environmental conditions.

Evapotranspiration Assessment by Remote Sensing in Brazil with Focus on Amazon Biome: Scientometric Analysis and Perspectives for Applications in Agro-Environmental Studies

The Amazon biome plays a crucial role in the hydrological cycle, supplying water vapor for the atmosphere and contributing to evapotranspiration (ET) that influences regional humidity across Brazil and South America. Remote sensing (RS) has emerged as a valuable tool for measuring and estimating ET, particularly in the data-scarce Amazon region. A scientometric analysis was conducted to identify the most used RS-based ET product or model in Brazil and its potential application in the Amazon. Scientometrics allows for the quantitative analysis of scientific output; this study identified the most widely used RS product in the Amazon biome. Articles published in Web of Science, Scielo, and Scopus databases up to 2022 were searched using the keywords “Evapotranspiration”, “Remote Sensing”, and “Brazil”. After initial screening, 140 relevant articles were subjected to scientometric analysis using the Bibliometrix library in RStudio 2023.06.1+524. These articles, published between 2001 and 2022, reveal a collaborative research landscape involving 600 authors and co-authors from 245 institutions, with most studies originating from Brazil’s Southeast and North (Amazon) regions. Notably, within the 12 studies focusing on ET by RS in the Amazon biome, applications were diverse, encompassing river basins, climate change, El Niño, and deforestation, with the MOD16 product being the most frequently employed.

Novel Approaches for the Empirical Assessment of Evapotranspiration over the Mediterranean Region

The hydrological cycle should be scrutinized and investigated under recent climate change scenarios to ensure global water management and to increase its utilization. Although the FAO proposed the use of the Penman–Monteith (PM) equation worldwide to predict evapotranspiration (ET), which is one of the most crucial components of the hydrological cycle, its complexity and time-consuming nature, have led researchers to examine alternative methods. In this study, the performances of numerous temperature-driven ET methods were examined relative to the PM using daily climatic parameters from central stations in 11 districts of the Kahramanmaras province. Owing to its geographical location and other influencing factors, the city has a degraded Mediterranean climate with varying elevation gradients, while its meteorological patterns (i.e., temperature and precipitation) deviate from those of the main Mediterranean climate. A separate evaluation was performed via ten different statistical metrics, and spatiotemporal ET variability was reported for the districts. This study revealed that factors such as altitude, terrain features, slope, aspect geography, solar radiation, and climatic conditions significantly impact capturing reference values, in addition to temperature. Moreover, an assessment was conducted in the region to evaluate the effect of modified ET formulae on simulations. It can be drawn as a general conclusion that the Hargreaves–Samani and modified Blaney–Criddle techniques can be utilized as alternatives to PM in estimating ET, while the Schendel method exhibited the lowest performance throughout Kahramanmaras.

Simulation and Assessment of Daily Evapotranspiration in the Heihe River Basin over a Long Time Series Based on TSEB-SM

The high spatial and temporal resolution of recently developed evapotranspiration (ET) products facilitates agricultural water-savings in irrigated areas as well as improved estimates of crop yield, especially in arid and semi-arid regions. However, cloud cover interferes with ET estimates, in particular when using thermal-infrared-based models in temperate and tropical regions. Previous studies have shown that the two-source energy balance (TSEB) model coupled with soil moisture (TSEB-SM) has great potential for estimating surface ET by overcoming this issue. In this study, the TSEB-SM model was first used to generate a spatiotemporally continuous 1 km daily ET dataset across the Heihe River Basin in China from 2000 to 2020, which was then evaluated against four spatially distributed sites (Arou, Huazhaizi, Daman, and Sidaoqiao) and further compared with the two most widely used daily ET datasets (PML-V2 (Penman–Monteith–Leuning) and SEBAL (surface energy balance algorithm for land)). The results showed that the newly developed ET dataset agrees well with ground-based observations and outperforms the PML-V2 and SEBAL products in precisely characterizing the seasonal fluctuations and spatial distribution as well as the spatiotemporal trends of ET. In particular, ET in the Heihe River Basin exhibits clear regional differences. The upstream and midstream grassland and irrigated oasis areas provide much higher annual ET than the downstream desert areas, with a difference of up to 600 mm/year. A three-cornered hat (TCH)-based pixel-by-pixel analysis further demonstrated that the TSEB-SM and PML-V2 products have substantially smaller relative uncertainties as compared to SEBAL ET. In general, the proposed ET datasets are expected to be more beneficial for irrigation scheduling and to provide more efficient water management across the Heihe River Basin.

Estimating ETO and scheduling crop irrigation using Blaney–Criddle equation when only air-temperature data are available and solving the issue of missing meteorological data in Egypt

Accurate assessment of evapotranspiration is essential for crop irrigation planning. In developing countries and given the cost of evaluating evapotranspiration based on the Penman-Monteith equation, this research is an attempt to provide a simple equation that depends only on temperature to estimate evapotranspiration and serve as an alternative method to FAO56-PM when only air temperature data are available and the problem of missing meteorological data is solved. Four reference methods for evapotranspiration (ET) were compared under the local climatic conditions of the El-Nobaria region in northern Egypt. The Blaney–Criddle method was found to have the highest correlation with the FAO56-PM method. Using the simple equations to calculate ETo for irrigation scheduling of peanuts had a positive effect on the yield and yield components of peanuts. The highest productivity value was obtained when the Blaney–Criddle equation was used to estimate peanut irrigation scheduling, while equation resulted in lower productivity. When the equation was used, the differences in productivity between the equations were highly significant. It is worth noting that when the Blaney–Criddle and Thorthwaite equations were used, followed by the FAO56-PM equation, the superiority of the water productivity value became evident, as the increase in nutrient concentration in the root zone led to increased nutrient uptake, resulting in an increase in the productivity of peanut yield, oil and protein.

Hydrological Balance in the Vistula Catchment under Future Climates

The hydrological assessment of the Vistula River basin in the near future will be a key element in the development of strategies to adapt agriculture to climate change. The Vistula River basin covers 61% of Poland’s area (190,062 km2) and is mainly used for agricultural production. The aim of this study is to assess the water balance of the Vistula River basin from the perspective of 2050 based on the analysis of two climate scenarios, RCP 4.5 and RCP 8.5, and the three climate models ICHEC-EC-EARTH_KNMI-RACMO22E (A), ICHEC-EC-EARTH_DMI-HIRHAM5 (B), and ICHEC-EC-EARTH_SMHI-RCA4 (C). This paper presents the steps in the development of the SWAT model and the results of the hydrological analysis of the Vistula catchment. Calibration and validation of the model were carried out using the SUFI-2 algorithm in the SWAT-CUP programme for 2013–2018. The data used to calibrate the SWAT model are monthly flow measurements [m3/s] from the measurement station in Tczew, located near the estuary of the Vistula basin to the Baltic Sea. The summary result of the work is the results of modelling the flow of the Vistula River catchment for different climate scenarios in the 2020–2050 perspective. The average annual precipitation for all projections in 2021–2030, 2031–2040, and 2041–2050 will be higher by up to 22% (763 mm) (RCP 8.5.C for 2041–2050) compared to the 2013–2018 simulation years (624 mm). The average annual temperature for most climate projections for 2021–2030 will fall to as low as 8.7 °C (RCP 4.5.B) compared to the 2013–2018 simulation period (9.2 °C). In contrast, for all projections in 2031–2040 and 2041–2050, the average annual temperature will increase to as much as 10.3 °C (RCP 8.5.C). The simulation results for the climate projections (2020–2050) indicate that there are no clear trends of change in the water management of the Vistula River basin for the coming decades. According to scenarios RCP 4.5.A, RCP 8.5.A, and RCP 8.5.B, the annual sums of potential evapotranspiration show a slight downward trend. On the other hand, for the RCP 8.5.C and RCP 4.5.C projections and the climate change scenario RCP 4.5.B, the results obtained show a slight upward trend in the annual sum of potential evapotranspiration. For the overall evapotranspiration and potential evapotranspiration assessment for all climate projections analysed, the annual evapotranspiration total shows a clear increase compared to the 2013–2018 baseline period. The average annual actual evapotranspiration for all projections in 2021–2030, 2031–2040, and 2041–2050 will increase up to 467 mm (RCP 4.5.A—2021–2030) compared to the 2013–2018 simulation period of 401 mm. The average annual potential evapotranspiration for all projections in 2021–2030, 2031–2040, and 2041–2050 will increase up to 755 mm (RCP 8.5.C—2031–2040) compared to the 2013–2018 simulation period—616 mm. The analysis of the total runoff in all climate models for the RCP 4.5 scenario shows that the annual average total runoff tends to decrease. The results of the simulations carried out for the RCP 8.5 scenario, which are generally characterised by an increase in total runoff in subsequent years, are different. When analysing annual total runoff on a regional basis, it appears that for most of the climate projections analysed (except for the RCP 8.5.A scenario), annual runoff will be lower, especially in the lowlands in the central part of the Vistula basin. In regions where the increase in precipitation is greatest in the north-western and southern basins, higher total runoff should be expected. The analysis of the total runoff in all climate models for the RCP 4.5 scenario shows that the annual average total runoff tends to decrease. The results of the simulations carried out for the RCP 8.5 scenario, which are generally characterised by an increase in total runoff in subsequent years, are different. When analysing annual total runoff on a regional basis, it appears that for most of the climate projections analysed (except for the RCP 8.5.A scenario), annual runoff will be lower, especially in the lowlands in the central part of the Vistula basin. In regions where the increase in precipitation is greatest in the north-western and southern basins, higher total runoff should be expected.

Developing a Regional Network for the Assessment of Evapotranspiration

Determining evapotranspiration (ET) is essential for water accounting and for the management of irrigated agriculture from farm to region. We describe here a collaborative initiative aimed at establishing a prototype ET network in six countries of North Africa and the Near East (NENA region). The network utilizes a low-cost and open-source system, termed the CORDOVA-ET, consisting of a base station and sensing nodes to collect the weather data needed to determine the reference and actual ET (ETo and ETa). Here, we describe the network-deployment processes, system architecture, data-collection methodology, quality-control procedures, and some of the ET results obtained so far during a four-year period, starting in 2018. The network has been developed as an iterative and collaborative process, where training and capacity building have been the main drivers. The feedback and experiences gathered from the users have helped improve the different versions of the prototypes and enhance their assembly, deployment, reliability, and ease of operation. At the same time, the involvement in the construction, maintenance, and data analysis has also provided valuable insight into calculating ET from energy-balance methods. The network operated during six cropping seasons and the results were mixed, while data integrity (hourly and daily) varied from 95 to 23% depending on the country and season. Validation of the ET estimates was performed using the ECMWF ERA5 dataset as an independent reference. The energy-balance algorithm implemented in the system to determine the ETa was validated using the OpenCropLib Python library. While the results of the data validation demonstrated the reliability and accuracy of the CORDOVA-ET system, network operations required significant support and special motivation on the part of the users. It is concluded that collaboration among users, together with the support services and participation of different stakeholders interested in agricultural water management, would be essential elements to ensure the sustainability of the ET network.

Assessment of Precipitation and Evapotranspiration in an Urban Area Using Remote Sensing Products (CHIRP, CMORPH, and SSEBop): The Case of the Metropolitan Region of Belem, Amazon

The aim of this study was to assess precipitation (P) and actual evapotranspiration (ET) by analyzing data from in situ stations compared with remote sensing products. Climate Hazards Center InfraRed Precipitation (CHIRP) and Climate Prediction Center morphing technique (CMORPH) were used for P and Operational Simplified Surface Energy Balance (SSEBop) was used for ET. The P in situ data for six stations were also compared to a reference station in the city. ET was analyzed for a single in situ station. The region chosen for this study was the Metropolitan Area of Belem (MAB), close to the estuary of the Amazon River and the mouth of the Tocantins River. Belem is the rainiest state capital in Brazil, which causes a myriad of challenges for the local population. The assessment was performed using the statistical metrics root-mean-square error (RMSE), normalized root-mean-square error (NRMSE), mean bias error (MBE), coefficient of determination (R2), regression slope, and Nash–Sutcliffe coefficient (NS). For the reference station, the automatic and conventional CHIRP and CMORPH results, in mm/month, were as follows: automatic CHIRP: RMSE = 93.3, NRMSE = 0.32, MBE = −33.54, R2 = 0.7048, Slope = 0.945, NS = 0.5668; CMORPH: RMSE = 195.93, NRMSE = 0.37, MBE = −52.86, R2 = 0.6731, Slope = 0.93, NS = 0.4344; conventional station CHIRP: RMSE = 94.87, NRMSE = 0.32, MBE = −33.54, R2 = 0.7048, Slope = 0.945, NS = 0.5668; CMORPH: RMSE = 105.58, NRMSE = 0.38, MBE = −59.46 R2 = 0.7728, Slope = 1.007, NS = 0.4308. In the MAB region, ET ranges on average between 83 mm/month in the Amazonian summer and 112 mm/month in the Amazonian winter. This work concludes that, although CMORPH has a coarser resolution than CHIRP for the MAB at a monthly resolution, both remote sensing products were reliable. SSEBop also showed acceptable performance. For analyses of the consistency of precipitation time series, these products could provide more accurate information. The present study validates P and ET from remote sensing products with station data in the rain-dominated urban MAB.

Developing a regional network for the assessment of evapotranspiration.

Abstract Determining evapotranspiration (ET) is essential for water accounting and for the management of irrigated agriculture from farm to region. We describe here a collaborative initiative aimed at establishing a prototype ET network in six countries of North Africa and the Near East (NENA Region). The network utilizes a low-cost and open-source system, termed the CORDOVA-ET, consisting of a base station and sensing nodes to collect the weather data needed to determine reference and actual ET (ETo and ETa). Here, we describe the network deployment processes, system architecture, data collection methodology, quality control procedures, and some of the ET results obtained so far during a four-year period, starting in 2018. The network has been developed as an iterative and collaborative process, where training and capacity building have been the main drivers. The feedback and experiences gathered from the users have helped improve the different versions of the prototypes and enhance their assembly, deployment, reliability, and ease of operation. At the same time, the involvement in the construction, maintenance, and data analysis has also provided valuable insight into calculating ET from energy balance methods. The network operated during six cropping seasons and the results were mixed, data integrity (hourly and daily) varied from 95 to 23%, depending on the country and season. Validation of ET estimates was performed using the ECMWF ERA5 dataset as an independent reference. The energy balance algorithm implemented in the system to determine ETa was validated using the OpenCropLib Python library. While the results of data validation demonstrated the reliability and accuracy of the CORDOVA-ET system, network operations required significant support and special motivation on the part of the users. It is concluded that collaboration among users, together with support services and participation of different stakeholders interested in agricultural water management would be essential elements to ensure the sustainability of the ET network.

Simulation of irrigation in southern Ukraine incorporating soil moisture state in evapotranspiration assessments

The paper studies the accuracy of modeling moisture transport under the conditions of sprinkler irrigation using evapotranspiration assessment methods that take into account the soil moisture conditions. Appropriate modifications of the Penman-Monteith and the Priestley-Taylor models are considered. Moisture transport modeling is performed using the Richards equation in its integer- and fractional-order forms. Parameters identification is performed by the particle swarm optimization algorithm based on the readings of suction pressure sensors. Results for the two periods of 11 and 50 days demonstrate the possibility of up to ~20% increase in the simulation accuracy by using a modified Priestley-Taylor model when the maintained range of moisture content in the root layer is 70%-100% of field capacity. When irrigation maintained the range of 80%-100% of field capacity, moisture content consideration within evapotranspiration assessment models did not enhance simulation accuracy. This confirms the independence of evapotranspiration from soil moisture content at its levels above 80% of field capacity as in this case actual evapotranspiration reaches a level close to the potential one. Scenario modeling of the entire growing season with the subsequent estimation of crop (maize) yield showed that irrigation regimes generated using evapotranspiration models, which take into account soil moisture data, potentially provide higher yields at lower water supply.

Evaluation of irrigation scheduling to maximize tomato production using comparative assessment of soil moisture and evapotranspiration in restricted irrigated regions

Evaluation of irrigation scheduling to maximize tomato production using comparative assessment of soil moisture and evapotranspiration in restricted irrigated regions