Energy-Based Approaches in Estimating Actual Evapotranspiration Focusing on Land Surface Temperature: A Review of Methods, Concepts, and Challenges

Taheri, Mercedeh; Mohammadian, Abdolmajid; Ganji, Fatemeh; Bigdeli, Mostafa; Nasseri, Mohsen

doi:10.3390/en15041264

Cited by 23 publications

(8 citation statements)

References 294 publications

(390 reference statements)

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“…variability in stress levels and disease management across the field, aligning with prior studies by Benedetti and Rossini, (1993) and Thapa et al, (2019). Furthermore, the significance of NDVI in the pySEBAL model, particularly in delineating cold and hot pixels, has been highlighted by (Taheri et al 2022). This study underscores the utility of high resolution NDVI-based spatial analysis in elucidating temporal patterns of crop health and facilitating targeted interventions and management strategies for optimizing processing tomato production and precision water management.…”

Section: Normalized Difference Vegetation Index Spatial Variabilitysupporting

confidence: 70%

Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes

Peddinti,

Nicolas,

Raij-Hoffman

et al. 2024

Preprint

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The utilization of high-resolution aerial imagery for assessing actual crop evapotranspiration (ETa) holds the potential to optimize the use of limited water resources in agriculture. Despite this potential, there is a shortage of information regarding the effectiveness of energy balance algorithms, initially designed for satellite remote sensing, in estimating ETa using aerial imagery. This study addresses this gap by employing the remote sensing model pySEBAL (Surface Energy Balance Algorithm for Land) in conjunction with high-resolution aerial imagery to estimate ETa for processing tomatoes. Throughout the 2021 growing season, an aircraft captured multispectral and thermal imagery over a processing tomato field near Esparto, California. Simultaneously, an eddy covariance flux tower within the field measured high-frequency turbulent fluxes and low-frequency biometeorology variables essential for evaluating the energy balance. The comprehensive assessment of energy balance components, including ETa, yielded compelling evidence that pySEBAL accurately estimated ETa at high spatial resolution. The root mean square error (RMSE) for various energy balance components were as follows: 33 Wm− 2 for latent heat flux, 29 Wm− 2 for sensible heat flux, 24 Wm− 2 for net radiation, and 10 Wm− 2 for soil heat flux. Additionally, ETa exhibited an RMSE of 0.26 mmd− 1. Notably, all components demonstrated an R2 exceeding 0.92. Moreover, the spatial mapping of ETa across the processing tomato field visually depicted the spatial variability associated with irrigation scheduling, crop development, areas affected by disease, and soil heterogeneity. This research underscores the value of high resolution spatial aerial imagery and pySEBAL algorithm for estimating ETa variability in the field, a crucial aspect for guiding precision irrigation management and ensuring the optimal use of limited water resources in agriculture.

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Section: Normalized Difference Vegetation Index Spatial Variabilitysupporting

confidence: 70%

Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes

Peddinti,

Nicolas,

Raij-Hoffman

et al. 2024

Preprint

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“…This finding was in line with previous studies that have indicated that ET was constrained by moisture in arid regions and that the surface energy fluxes were dominated by sensible heat fluxes. In contrast, in the humid subsurface, ET was mainly limited by energy supply, with smaller sensible heat fluxes, and the surface energy fluxes were dominated by latent heat transfer (Taheri et al, 2022). The elevated CO 2 concentration (Liu et al, 2021a), land use/land cover change (LULCC) (Sterling et al, 2013;Li et al, 2017), and reservoir storage (Scanlon et al, 2018) may also have larger impacts on ET by changing the local water and energy balance.…”

Section: Discussionmentioning

confidence: 99%

Main influencing factors of terrestrial evapotranspiration for different land cover types over the Tibetan Plateau in 1982–2014

Li,

Pan,

Zhao

2024

Front. Environ. Sci.

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Introduction: Terrestrial evapotranspiration (ET) over the Tibetan Plateau (TP) has important implications for the global water cycle, climate change, and ecosystem, and its changes and driving factors have drawn increasing attention. Previous research studies have minimally quantified the effects and identified the pathways of the influencing factors on ET over different land surface types.Methods: In this study, we analyze the spatiotemporal distribution and variation of ET over the TP in 1982–2014 based on multiple datasets. Furthermore, the effects of each influencing factor on ET are quantified over different land surface types, and the major influencing factors and their affecting pathways are identified using structure equation modeling (SEM), which is a statistical method used to analyze relationships among multiple variables.Results: The results show that the climatology of ET decreases gradually from southeastern to northwestern TP, with the maximum spatial averaged value of 379.979 ± 0.417 mm a−1 for the fifth generation of European Reanalysis (ERA5) and the minimum of 249.899 ± 0.469 mm a−1 for the Global Land Data Assimilation System (GLDAS). The most significant differences among the ET datasets mainly occur in the summer. The annual ET averaged over the TP presents an increased trend from 1982 to 2014, as shown by all of the ET datasets. However, there are larger discrepancies in the spatial distribution of the increased trend for these datasets. The assessment result shows that the 0.05° land evapotranspiration dataset for the Qinghai–Tibet Plateau (LEDQTP) has the highest temporal correlation coefficient (0.80) and the smallest root-mean-square error (23.50 mm) compared to the observations. Based on LEDQTP, we find that precipitation is the main influencing factor of ET, which primarily affects ET through direct pathways in bare soil and grassland regions, with standardized estimates of 0.521 and 0.606, respectively. However, in meadow and shrub and forest regions, the primary factor influencing ET is air temperature, which is primarily affected by an indirect pathway through a vapor pressure deficit. Air temperature is also the controlling factor in sparse vegetation regions, but it affects ET through a direct pathway.Discussion: This study may provide some new useful information on the effects of climate change on ET in different land cover types over the TP.

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“…METRIC is similar to SEBAL but provides the possibility to consider surface slope and aspect, as outlined by [16]. SSEBop, a straightforward, cost-effective, and operational model, requires minimal computational resources and automatically selects reference pixels [121].…”

Section: Type Models Advantages Disadvantagesmentioning

confidence: 99%

Advancements in Remote Sensing for Evapotranspiration Estimation: A Comprehensive Review of Temperature-Based Models

Derardja,

Khadra,

Abdelmoneim

et al. 2024

Remote Sensing

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Quantifying evapotranspiration (ET) is crucial for a valid understanding of the global water cycle and for the precise management of the resource. However, accurately estimating ET, especially at large scales, has always been a challenge. Over the past five decades, remote sensing has emerged as a cost-effective solution for estimating ET at regional and global scales. Numerous models have been developed, offering valuable insights into ET dynamics, allowing for large-scale, accurate, and continuous monitoring while presenting varying degrees of complexity. They mainly belong to two categories despite the variability of their empirical or physical components: temperature and conductance-based models. This comprehensive review synthesizes the fundamental theories and development history of the most used temperature-based models. It focuses on this specific category to maintain conciseness and prevent extended work. It describes the approaches used and presents the chronology of the modifications made and suggested by researchers. Moreover, it highlights the validation studies and the models’ advantages and drawbacks. The review addresses the long-standing challenge of accurately quantifying evapotranspiration at different scales, offers a retrospective comparative analysis spanning a 15-year period, and supports practitioners in selecting the most appropriate model for a specific set of conditions. Moreover, it discusses advancements in satellite missions, such as the Copernicus Space Component and Landsat Next, and their impact on enhancing ET estimation models.

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Energy-Based Approaches in Estimating Actual Evapotranspiration Focusing on Land Surface Temperature: A Review of Methods, Concepts, and Challenges

Cited by 23 publications

References 294 publications

Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes

Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes

Main influencing factors of terrestrial evapotranspiration for different land cover types over the Tibetan Plateau in 1982–2014

Advancements in Remote Sensing for Evapotranspiration Estimation: A Comprehensive Review of Temperature-Based Models

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