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Remote Sensing of Evapotranspiration (ET) II

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Biogeosciences Remote Sensing".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 51027

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Special Issue Editors

Dr. Nishan Bhattarai

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Guest Editor

School for Environment and Sustainability (SEAS), The University of Michigan, Ann Arbor, MI, USA
Interests: remote sensing of evapotranspiration; surface energy balance; agricultural water management; groundwater irrigation; deforestation; climate change; agricultural sustainability; land cover and land use changes; environmental remote sensing; big data; thermal remote sensing; food–energy–water nexus

Dr. Pradeep Wagle

E-Mail Website
Guest Editor

USDA-ARS, Oklahoma and Central Plains Agricultural Research Center, El Reno, OK 73036, USA
Interests: land surface–atmosphere interactions with a focus on ecosystem carbon and water cycle dynamics using eddy covariance systems; integrating multi-source and multi-scale data from a variety of sources (ground-based measurements and remote sensing observations); modeling approaches; flux partitioning
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Special Issue Information

Dear Colleagues,

Evapotranspiration (ET) is a key component of the Earth’s surface and water balances. Remote sensing has played a significant role in understanding the process of ET over the last three decades. However, significant uncertainties exist in the current state-of-the-art remote sensing-based ET models, as no single model has been found to work best under all conditions. The main goal of this Special Issue is to report on recent advancements in the development and applications of remote sensing-based ET models at multiple scales and efforts to reduce existing uncertainties in current remote sensing-based ET models. Model evaluation and application studies that combine remote sensing, ground-based ET methods (Lysimeter, neutron probes, Eddy covariance, Bowen ratio, scintillometer, ET gauges, etc.), climate data, and socioeconomic outcomes are also welcome. Contributions to this Special Issue may include (but not be limited to): (1) evaluation of existing/new instruments for their ability to measure ET/surface energy fluxes accurately in different agrometeorological conditions, limitation, and challenges of current and new methods; (2) recent advancements in remote sensing-based ET models; (3) application of remote sensing-based ET models in water rights, interstate compacts, invasive species, agricultural and urban allocations, endangered species protection, drought and food insecurity, large-scale land-surface and climate models, water conservation projects, irrigation performance, environmental impact assessment due to groundwater extractions, dryland water management, hydrological modeling, crop modeling, assessing crop water productivity, and irrigation scheduling, to name a few; (4) understanding the drivers of ET in a given ecosystem with respect to environmental change; and (5) linking ET with field and social data to understand ET/crop water use responses to changes in socioeconomic conditions. Papers on coupling of CO₂ fluxes and ET and water use efficiency will also be considered.

Dr. Nishan Bhattarai
Dr. Pradeep Wagle
Guest Editors

Manuscript Submission Information

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Keywords

Evapotranspiration
Surface energy balance
Food–energy–water nexus
Water rights
Water security
Water use efficiency
Drought management
Irrigation management
Crop water requirement

Published Papers (14 papers)

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Editorial

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5 pages, 208 KiB

Open AccessEditorial

Recent Advances in Remote Sensing of Evapotranspiration

by Nishan Bhattarai and Pradeep Wagle

Remote Sens. 2021, 13(21), 4260; https://doi.org/10.3390/rs13214260 - 23 Oct 2021

Cited by 15 | Viewed by 3897

Abstract

Evapotranspiration (ET) plays an important role in coupling the global energy, water, and biogeochemical cycles and explains ecosystem responses to global environmental change. However, quantifying and mapping the spatiotemporal distribution of ET across a large area is still a challenge, which limits our understanding of how a given ecosystem functions under a changing climate. This also poses a challenge to water managers, farmers, and ranchers who often rely on accurate estimates of ET to make important irrigation and management decisions. Over the last three decades, remote sensing-based ET modeling tools have played a significant role in managing water resources and understanding land-atmosphere interactions. However, several challenges, including limited applicability under all conditions, scarcity of calibration and validation datasets, and spectral and spatiotemporal constraints of available satellite sensors, exist in the current state-of-the-art remote sensing-based ET models and products. The special issue on “Remote Sensing of Evapotranspiration II” was launched to attract studies focusing on recent advances in remote sensing-based ET models to help address some of these challenges and find novel ways of applying and/or integrating remotely sensed ET products with other datasets to answer key questions related to water and environmental sustainability. The 13 articles published in this special issue cover a wide range of topics ranging from field- to global-scale analysis, individual model to multi-model evaluation, single sensor to multi-sensor fusion, and highlight recent advances and applications of remote sensing-based ET modeling tools and products. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

Research

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31 pages, 6232 KiB

Open AccessArticle

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

by Bibek Acharya and Vivek Sharma

Remote Sens. 2021, 13(9), 1822; https://doi.org/10.3390/rs13091822 - 07 May 2021

Cited by 16 | Viewed by 3258

Abstract

The regional-scale estimation of crop evapotranspiration (ET_c) 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 ET_c 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 ET_c 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 ET_c 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 ET_c 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 ET_c, except SEBS. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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48 pages, 68484 KiB

Open AccessFeature PaperArticle

Riparian Area Changes in Greenness and Water Use on the Lower Colorado River in the USA from 2000 to 2020

by Pamela L. Nagler, Armando Barreto-Muñoz, Sattar Chavoshi Borujeni, Hamideh Nouri, Christopher J. Jarchow and Kamel Didan

Remote Sens. 2021, 13(7), 1332; https://doi.org/10.3390/rs13071332 - 31 Mar 2021

Cited by 17 | Viewed by 3049

Abstract

Declines in riparian ecosystem greenness and water use have been observed in the delta of the Lower Colorado River (LCR) since 2000. The purpose of our case study was to measure these metrics on the U.S. side of the border between Hoover and Morelos Dams to see if declining greenness was unique to the portion of the river in Mexico. In this case study, five riparian reaches of the LCR from Hoover to Morelos Dam since 2000 were studied to evaluate trends in riparian ecosystem health. We measure these riparian woodlands using remotely sensed measurements of the two-band Enhanced Vegetation Index (EVI2; a proxy for greenness); daily evapotranspiration (ET; mmd⁻¹) using EVI2 (ET(EVI2)); and an annualized ET based on EVI2, the Phenology Assessment Metric (PAM ET), an annualized ET using Landsat time-series. A key finding is that riparian health and its water use has been in decline since 2000 on the U.S. portion of the LCR, depicting a loss of green vegetation over the last two decades. EVI2 results show a decline of −13.83%, while average daily ET(EVI2) between the first and last decade had a decrease of over 1 mmd⁻¹ (−27.30%) and the respective average PAM ET losses were 170.91 mmyr⁻¹ (−17.95%). The difference between the first and last five-year periods, 2000–2005 and 2016–2020, showed the largest decrease in daily ET(EVI) of 1.24 mmd⁻¹ (−32.61%). These declines come from a loss in healthy, green, riparian plant-cover, not a change in plant water use efficiency nor efficient use of managed water resources. Our results suggest further deterioration of biodiversity, wildlife habitat and other key ecosystem services on the U.S. portion of the LCR. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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25 pages, 5459 KiB

Open AccessArticle

Evaluation of Penman-Monteith Model Based on Sentinel-2 Data for the Estimation of Actual Evapotranspiration in Vineyards

by Víctor García-Gutiérrez, Claudio Stöckle, Pilar Macarena Gil and Francisco Javier Meza

Remote Sens. 2021, 13(3), 478; https://doi.org/10.3390/rs13030478 - 29 Jan 2021

Cited by 12 | Viewed by 4268

Abstract

Water scarcity is one of the most important problems of agroecosystems in Mediterranean and semiarid areas, especially for species such as vineyards that largely depend on irrigation. Actual evapotranspiration (ET) is a variable that represents water consumption of a crop, integrating climate and biophysical variables. Actual evapotranspiration models based on remote sensing data from visible bands of Sentinel-2, including Penman-Monteith–Stewart (RS-PMS) and Penman-Monteith–Leuning (RS-PML), were evaluated at different temporal scales in a Cabernet Sauvignon vineyard (Vitis vinifera L.) located in central Chile, and their performance compared with independent ET measurements from an eddy covariance system (EC) and outputs from models based on thermal infrared data from Landsat 7 and Landsat 8, such as Mapping EvapoTranspiration with high Resolution and Internalized Calibration (METRIC) and Priestley–Taylor Two-Source Model (TSEB-PT). The RS-PMS model showed the best goodness of fit for all temporal scales evaluated, especially at instantaneous and daily ET, with root mean squared error (RMSE) of 28.9 Wm⁻² and 0.52 mm day⁻¹, respectively, and Willmott agreement index (d₁) values of 0.77 at instantaneous scale and 0.7 at daily scale. Additionally, both approaches of RS-PM model were evaluated incorporating a soil evaporation estimation method, one considering the soil water content (f_SWC) and the other hand, using the ratio of accumulated precipitation and equivalent evaporation (f_Zhang), achieving the best fit at instantaneous scale for RS-PMS f_SWC method with relative root mean squared error (%RMSE) of 15.2% in comparison to 58.8% of f_Zhang. Finally, the relevance of the RS-PMS model was highlighted in the assessment and monitoring of vineyard drip irrigation in terms of crop coefficient (Kc) estimation, which is one of the methods commonly used in irrigation planning, yielding a comparable Kc to the one obtained by the EC tower with a bias around 9%. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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16 pages, 3219 KiB

Open AccessArticle

Comparing Evapotranspiration Products of Different Temporal and Spatial Scales in Native and Managed Prairie Pastures

by Rajen Bajgain, Xiangming Xiao, Pradeep Wagle, John S. Kimball, Colin Brust, Jeffrey B. Basara, Prasanna Gowda, Patrick J. Starks and James P. S. Neel

Remote Sens. 2021, 13(1), 82; https://doi.org/10.3390/rs13010082 - 29 Dec 2020

Cited by 3 | Viewed by 2963

Abstract

Grasslands in the Southern Great Plains of the United States have major ecological and economic importance, with strong climate and water cycle connections. The historic native prairie grassland has been managed differently for enhancing productivity, while consequently altering water vapor fluxes. However, little is known about the impacts of different management activities on evapotranspiration (ET) at different spatio-temporal scales. In this study, we quantified and compared ET between co-located introduced managed pasture (MP) and native prairie (NP) pasture. Additionally, we compared the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived ET at four different spatial scales: 30 m (ET_MOD30), 200 m (ET_MOD200), 500 m (ET_MOD500), and 1000 m (ET_MOD1000) with eddy covariance-measured ET (ET_EC). Large differences in ET_EC were observed between two pastures from half-hourly to seasonal scales, with variations mainly controlled by the amount of rainfall and management activities. The results demonstrated differential responses of MP and NP in a pluvial year. The ET_MOD30 showed a better agreement with ET_EC than did the ET_MOD200, ET_MOD500, and ET_MOD1000. The ET_MOD200, ET_MOD500, and ET_MOD1000 largely underestimated ET_EC, most likely due to their inability to capture the spatial heterogeneity of vegetation growth impacted by various management activities. Our results facilitate understanding of the difference in ET of MP and NP due to differences in vegetation resulting from different management activities and their differential responses to precipitation. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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16 pages, 5089 KiB

Open AccessEditor’s ChoiceArticle

A First Assessment of the 2018 European Drought Impact on Ecosystem Evapotranspiration

by Kazi Rifat Ahmed, Eugénie Paul-Limoges, Uwe Rascher and Alexander Damm

Remote Sens. 2021, 13(1), 16; https://doi.org/10.3390/rs13010016 - 22 Dec 2020

Cited by 13 | Viewed by 3499

Abstract

The combined heatwave and drought in 2018 notably affected the state and functioning of European ecosystems. The severity and distribution of this extreme event across ecosystem types and its possible implication on ecosystem water fluxes are still poorly understood. This study estimates spatio-temporal changes in evapotranspiration (ET) during the 2018 drought and heatwave and assesses how these changes are distributed in European ecosystems along climatic gradients. We used the ET eight-day composite product from the MODerate Resolution Imaging Spectroradiometer (MODIS) together with meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF ERA5). Our results indicate that ecosystem ET was strongly reduced (up to −50% compared to a 10-year reference period) in areas with extreme anomalies in surface air temperature (T_sa) and precipitation (P) in central, northern, eastern, and western Europe. Northern and Eastern Europe had prolonged anomalies of up to seven months with extreme intensities (relative and absolute) of T_sa, P, and ET. Particularly, agricultural areas, mixed natural vegetation, and non-irrigated agricultural areas were the most affected by the increased temperatures in northern Europe. Our results show contrasting drought impacts on ecosystem ET between the North and South of Europe as well as on ecosystem types. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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29 pages, 10668 KiB

Open AccessArticle

Quantification and Mapping of Satellite Driven Surface Energy Balance Fluxes in Semi-Arid to Arid Inter-Mountain Region

by Bibek Acharya, Vivek Sharma, James Heitholt, Daniel Tekiela and Fabian Nippgen

Remote Sens. 2020, 12(24), 4019; https://doi.org/10.3390/rs12244019 - 08 Dec 2020

Cited by 3 | Viewed by 3065

Abstract

Crop evapotranspiration (ET_c) estimates, on a regional scale, hold enormous potential in managing surface and groundwater resources. This is particularly important for the headwater state of Wyoming, which provides water to found major river basins of the US. In this study, METRIC (Mapping evapotranspiration at high resolution with internalized calibration), a satellite-based image processing model, was used to map and quantify daily, monthly, and seasonal ET_c and other energy balance fluxes, i.e., net radiation (R_n), sensible heat (H), and soil heat flux (G) dynamics for different land-use classes. Monthly and seasonal ETc estimated were further used to approximate regional water consumption patterns for different land-use types for nine irrigation districts in semi-arid to arid intermountain region of Big Horn Basin (BHB), Wyoming. The validation of METRIC retrievals against Bowen ratio energy balance system (BREBS) fluxes measured over three vegetative surfaces, viz. sugar beet in 2017, dry bean in 2018, and barley in 2019, indicated high accuracy. The pooled correlation observed between estimated (pooled) and measured instantaneous fluxes had R² values of 0.91 (RMSE = 0.08 mm h⁻¹, NSE = 0.91), 0.81 (RMSE = 49.6 Wm⁻², NSE = 0.67), 0.53 (RMSE = 27.1 Wm⁻², NSE = 0.53), and 0.86 (RMSE = 59.2 Wm⁻², NSE = 0.84) for ET_c, R_n, G, and H, respectively. The biggest discrepancy between measured and estimated monthly ETc values was observed during times when BREBS flux tower footprint was devoid of any crops or the crops at footprint were not actively transpiring. Validation results improved when comparisons were made on monthly scales with METRIC underestimating growing season ET_c in the range between 3.2% to 6.0%. Seasonal ETc by land-use type showed significant variation over the study area where crop ETc was 52% higher than natural vegetation ETc. Furthermore, it was found that, in the arid to semi-arid intermountain region of Wyoming, the contribution of irrigation to total seasonal ETc varied in the range of 73–81% in nine irrigation districts that fall within the study area. The high relative contribution of irrigation highlights the importance of identifying and quantifying ETc for improved management in irrigation system design and water allocation. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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25 pages, 19568 KiB

Open AccessArticle

Evapotranspiration Partitioning at Field Scales Using TSEB and Multi-Satellite Data Fusion in The Middle Reaches of Heihe River Basin, Northwest China

by Yan Li, Chunlin Huang, William P. Kustas, Hector Nieto, Liang Sun and Jinliang Hou

Remote Sens. 2020, 12(19), 3223; https://doi.org/10.3390/rs12193223 - 03 Oct 2020

Cited by 8 | Viewed by 2536

Abstract

Daily evapotranspiration (ET) and its components of evaporation (E) and transpiration (T) at field scale are often required for improving agricultural water management and maintaining ecosystem health, especially in semiarid and arid regions. In this study, multi-year daily ET, E, and T at a spatial resolution of 100 m in the middle reaches of Heihe River Basin were computed based on an ET partitioning method developed by combing remote sensing-based ET model and multi-satellite data fusion methodology. Evaluations using flux tower measurements over irrigated cropland and natural desert sites indicate that this method can provide reliable estimates of surface flux partitioning and daily ET. Modeled daily ET yielded root mean square error (RMSE) values of 0.85 mm for cropland site and 0.84 mm for desert site, respectively. The E and T partitioning capabilities of this proposed method was further assessed by using ratios E/ET and T/ET derived from isotopic technology at the irrigated cropland site. Results show that apart from early in the growing season when the actual E was reduced by plastic film mulching, the modeled E/ET and T/ET agree well with observations in terms of both magnitude and temporal dynamics. The multi-year seasonal patterns of modeled ET, E, and T at field scale from this ET partitioning method shows reasonable seasonal variation and spatial variability, which can be used for monitoring plant water consumption in both agricultural and natural ecosystems. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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20 pages, 8426 KiB

Open AccessArticle

Estimation of Seasonal Evapotranspiration for Crops in Arid Regions Using Multisource Remote Sensing Images

by Mingxing Cha, Mengmeng Li and Xiaoqin Wang

Remote Sens. 2020, 12(15), 2398; https://doi.org/10.3390/rs12152398 - 26 Jul 2020

Cited by 5 | Viewed by 3125

Abstract

An accurate estimation of evapotranspiration (ET) from crops is crucial in irrigation management, crop yield assessment, and optimal allocation of water resources, particularly in arid regions. This study explores the estimation of seasonal evapotranspiration for crops using multisource remote sensing images. The proposed estimation framework starts with estimating daily evapotranspiration (ET_d) values, which are then used to calculate ET estimates during the crop growing season (ET_s). We incorporated Landsat images into the surface energy balance algorithm over land (SEBAL) model, and we used the trapezoidal and sinusoidal methods to estimate the seasonal ET. The trapezoidal method used multitemporal ET_d images, while the sinusoidal method employs time-series Moderate Resolution Imaging Spectroradiometer (MODIS) images and multitemporal ET_d images. Experiments were implemented in the agricultural lands of the Kai-Kong River Basin, Xinjiang, China. The experimental results show that the obtained ET_d estimates using the SEBAL model are comparable with those from the Penman–Monteith method. The ET_s obtained using the trapezoidal and sinusoidal methods both have a relatively high spatial resolution of 30 m. The sinusoidal method performs better than the trapezoidal method when using low temporal resolution Landsat images. We observed that the omission of Landsat images during the middle stage of crop growth has the greatest impact on the estimation results of ET_s using the sinusoidal method. Based on the results of the study, we conclude that the proposed sinusoidal method, with integrated multisource remote sensing images, offers a useful tool in estimating seasonal evapotranspiration for crops in arid regions. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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25 pages, 4945 KiB

Open AccessArticle

Estimating Near Real-Time Hourly Evapotranspiration Using Numerical Weather Prediction Model Output and GOES Remote Sensing Data in Iowa

by Wonsook S. Ha, George R. Diak and Witold F. Krajewski

Remote Sens. 2020, 12(14), 2337; https://doi.org/10.3390/rs12142337 - 21 Jul 2020

Cited by 6 | Viewed by 2970

Abstract

This study evaluates the applicability of numerical weather prediction output supplemented with remote sensing data for near real-time operational estimation of hourly evapotranspiration (ET). Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) systems were selected to provide forcing data for a Penman-Monteith model [...] Read more.

R_{n}

) estimates might potentially improve AET estimates, Geostationary Operational Environmental Satellite derived

R_{n}

(GOES-

R_{n}

) data were incorporated into each dataset for comparison with the RAP and HRRR

R_{n}

-based AET evaluations. The authors formulated a total of four AET models—RAP, HRRR, RAP-GOES, HRRR-GOES, and validated the respective ET estimates against two eddy covariance tower measurements from central Iowa. The implementation of HRRR-GOES for AET estimates showed the best results among the four models. The HRRR-GOES model improved statistical results, yielding a correlation coefficient of 0.8, a root mean square error (mm hr⁻¹) of 0.08, and a mean bias (mm hr⁻¹) of 0.02 while the HRRR only model results were 0.64, 0.09, and 0.04, respectively. Despite limited in situ observational data to fully test a proposed AET estimation, the HRRR-GOES model clearly showed potential utility as a tool to predict AET at a regional scale with high spatio-temporal resolution. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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25 pages, 5779 KiB

Open AccessArticle

Feasibility of Using the Two-Source Energy Balance Model (TSEB) with Sentinel-2 and Sentinel-3 Images to Analyze the Spatio-Temporal Variability of Vine Water Status in a Vineyard

by Joaquim Bellvert, Christian Jofre-Ĉekalović, Ana Pelechá, Mercè Mata and Hector Nieto

Remote Sens. 2020, 12(14), 2299; https://doi.org/10.3390/rs12142299 - 17 Jul 2020

Cited by 37 | Viewed by 3885

Abstract

In viticulture, detailed spatial information about actual evapotranspiration (ET_a) and vine water status within a vineyard may be of particular utility when applying site-specific, precision irrigation management. Over recent decades, extensive research has been carried out in the use of remote sensing energy balance models to estimate and monitor ET_a at the field level. However, one of the major limitations remains the coarse spatial resolution in the thermal infrared (TIR) domain. In this context, the recent advent of the Sentinel missions of the European Space Agency (ESA) has greatly improved the possibility of monitoring crop parameters and estimating ET_a at higher temporal and spatial resolutions. In order to bridge the gap between the coarse-resolution Sentinel-3 thermal and the fine-resolution Sentinel-2 shortwave data, sharpening techniques have been used to downscale the Sentinel-3 land surface temperature (LST) from 1 km to 20 m. However, the accurate estimates of high-resolution LST through sharpening techniques are still unclear, particularly when intended to be used for detecting crop water stress. The goal of this study was to assess the feasibility of the two-source energy balance model (TSEB) using sharpened LST images from Sentinel-2 and Sentinel-3 (TSEB-PT_S2+3) to estimate the spatio-temporal variability of actual transpiration (T) and water stress in a vineyard. T and crop water stress index (CWSI) estimates were evaluated against a vine water consumption model and regressed with in situ stem water potential (Ψ_stem). Two different TSEB approaches, using very high-resolution airborne thermal imagery, were also included in the analysis as benchmarks for TSEB-PT_S2+3. One of them uses aggregated TIR data at the vine+inter-row level (TSEB-PT_airb), while the other is based on a contextual method that directly, although separately, retrieves soil and canopy temperatures (TSEB-2T). The results obtained demonstrated that when comparing airborne T_rad and sharpened S2+3 LST, the latter tend to be underestimated. This complicates the use of TSEB-PT_S2+3 to detect crop water stress. TSEB-2T appeared to outperform all the other methods. This was shown by a higher R² and slightly lower RMSD when compared with modelled T. In addition, regressions between T and CWSI-2T with Ψ_stem also produced the highest R². Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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19 pages, 3682 KiB

Open AccessArticle

The Reliability of Global Remote Sensing Evapotranspiration Products over Amazon

by Jie Wu, Venkataraman Lakshmi, Dashan Wang, Peirong Lin, Ming Pan, Xitian Cai, Eric F. Wood and Zhenzhong Zeng

Remote Sens. 2020, 12(14), 2211; https://doi.org/10.3390/rs12142211 - 10 Jul 2020

Cited by 25 | Viewed by 3521

Abstract

As a key component of terrestrial water cycle, evapotranspiration (ET), specifically over the Amazon River basin, is of high scientific significance. However, due to the sparse observation network and relatively short observational period of eddy covariance data, large uncertainties remain in the spatial-temporal characteristics of ET over the Amazon. Recently, a great number of long-term global remotely sensed ET products have been developed to fill the observation gap. However, the reliabilities of these global ET products over the Amazon are unknown. In this study, we assessed the consistency of the magnitude, trend and spatial pattern of Amazon ET among five global remotely sensed ET reconstructions. The magnitudes of these products are similar but the long-term trends from 1982 to 2011 are completely divergent. Validation from the eddy covariance data and water balance method proves a better performance of a product grounded on local measurements, highlighting the importance of local measurements in the ET reconstruction. We also examined four hypotheses dealing with the response of ET to brightening, warming, greening and deforestation, which shows that in general, these ET products respond better to warming and greening than to brightening and deforestation. This large uncertainty highlights the need for future studies focusing on ET issues over the Amazon. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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18 pages, 7629 KiB

Open AccessArticle

Global Trends in Evapotranspiration Dominated by Increases across Large Cropland Regions

by Mostafa Javadian, Ali Behrangi, William Kolby Smith and Joshua B. Fisher

Remote Sens. 2020, 12(7), 1221; https://doi.org/10.3390/rs12071221 - 10 Apr 2020

Cited by 28 | Viewed by 5613

Abstract

Irrigated croplands require large annual water inputs and are critical to global food production. Actual evapotranspiration (AET) is a main index of water use in croplands, and several remote-sensing products have been developed to quantify AET at the global scale. In this study, we estimate global trends in actual AET, potential ET (PET), and precipitation rate (PP) utilizing the MODIS Evapotranspiration product (2001–2018) within the Google Earth Engine cloud-computing environment. We then introduce a new index based on a combination of AET, PET, and PP estimates—the evapotranspiration warning index (ETWI)—which we use to evaluate the sustainability of observed AET trends. We show that while AET has not considerably changed across global natural lands, it has significantly increased across global croplands (+14% ± 5%). The average ETWI for global croplands is −0.40 ± 0.25, which is largely driven by an extreme trend in AET, exceeding both PET and PP trends. Furthermore, the trends in water and energy limited areas demonstrate, on a global scale, while AET and PET do not have significant trends in both water and energy limited areas, the increasing trend of PP in energy-limited areas is more than water-limited areas. Averaging cropland ETWI trends at the country level further revealed nonsustainable trends in cropland water consumptions in Thailand, Brazil, and China. These regions were also found to experiencing some of the largest increases in net primary production (NPP) and solar-induced fluorescence (SIF), suggesting that recent increases in food production may be dependent on unsustainable water inputs. Globally, irrigated maize was found to be associated with nonsustainable AET trends relative to other crop types. We present an online open access application designed to enable near real-time monitoring and improve the understanding of global water consumption and availability. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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34 pages, 10325 KiB

Open AccessArticle

Evapotranspiration Estimation in the Sahel Using a New Ensemble-Contextual Method

by Aubin Allies, Jérôme Demarty, Albert Olioso, Ibrahim Bouzou Moussa, Hassane Bil-Assanou Issoufou, Cécile Velluet, Malik Bahir, Ibrahim Maïnassara, Monique Oï, Jean-Philippe Chazarin and Bernard Cappelaere

Remote Sens. 2020, 12(3), 380; https://doi.org/10.3390/rs12030380 - 24 Jan 2020

Cited by 17 | Viewed by 3577

Abstract

In many tropical areas, evapotranspiration is the most important but least known component of the water cycle. An innovative method, named E3S (for EVASPA S-SEBI Sahel), was developed to provide spatially-distributed estimates of daily actual evapotranspiration (ET_d) from remote sensing data in the Sahel. This new method combines the strengths of a contextual approach that is used to estimate the evaporative fraction (EF) from surface temperature vs. albedo scatterograms and of an ensemble approach that derives ET_d estimates from a weighted average of evapotranspiration estimated from several EF methods. In this work, the two combined approaches were derived from the simplified surface energy balance index (S-SEBI) model and the EVapotranspiration Assessment from SPAce (EVASPA) tool. Main innovative aspects concern (i) ensemble predictions of ET_d through the implementation of a dynamic weighting scheme of several evapotranspiration estimations, (ii) epistemic uncertainty of the estimation of ET_d from the analysis of the variability of evapotranspiration estimates, and (iii) a new cloud filtering method that significantly improves the detection of cloud edges that negatively affect EF determination. E3S was applied to MODIS/TERRA and AQUA datasets acquired during the 2005–2008 period over the mesoscale AMMA-CATCH (Analyse Multidisciplinaire de la Mousson Africaine—Couplage de l’Atmosphère Tropicale et du Cycle Hydrologique) observatory in South-West Niger. E3S estimates of instantaneous and daily available energy, evaporative fraction, and evapotranspiration were evaluated at a local scale based on two field-monitored plots representing the two main ecosystem types in the area—a millet crop and a fallow savannah bush. In addition to these ground-based observations, the local scale evaluation was performed against continuous simulations by a locally-calibrated soil-vegetation-atmosphere transfer model for the two plots. The RMSE (root mean square error) from this comparison for E3S’s ET_d estimates from combined AQUA/TERRA sources was 0.5 mm·day⁻¹, and the determination coefficient was 0.90. E3S significantly improved representation of the evapotranspiration seasonality, compared with a classical implementation of S-SEBI or with the original EVASPA’s non-weighted ensemble scheme. At the mesoscale, ET_d estimates were obtained with an average epistemic uncertainty of 0.4 mm·day⁻¹. Comparisons with the reference 0.25°-resolution GLEAM (global land evaporation Amsterdam model) product showed good agreement. These results suggested that E3S could be used to produce reliable continuous regional estimations at a kilometric resolution, consistent with land and water management requirements in the Sahel. Moreover, all these innovations could be easily transposed to other contextual approaches. Full article

(This article belongs to the Special Issue Remote Sensing of Evapotranspiration (ET) II)

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