Evaluating the role of remote sensing-based energy balance models in improving site-specific irrigation management for young walnut orchards

2021 ◽  
Vol 256 ◽  
pp. 107132
Author(s):  
Jingyuan Xue ◽  
Allan Fulton ◽  
Isaya Kisekka
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Irrigation Management ◽  
Site Specific ◽  
Energy Balance Models

scholarly journals Comparison of the Remote Sensing Based-Energy Balance Models for Estimating Evaporation from Salin Lakes

2019 ◽  
Vol 7 (2) ◽  
pp. 155-175
Author(s):  
Mostafa Khorsand Movaghar ◽  
Somayeh Sima ◽  
◽  
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Energy Balance Models

scholarly journals Evaluation of a Hybrid Reflectance-Based Crop Coefficient and Energy Balance Evapotranspiration Model for Irrigation Management

2018 ◽  
Vol 61 (2) ◽  
pp. 533-548 ◽  
Author(s):  
J. Burdette Barker ◽  
Christopher M. U. Neale ◽  
Derek M. Heeren ◽  
Andrew E. Suyker
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Water Balance ◽  
Real Time ◽  
Eddy Covariance ◽  
Irrigation Management ◽  
Crop Coefficient ◽  
Irrigation Scheduling ◽  
Balance Model ◽  
Crop Coefficients

Abstract. Accurate generation of spatial soil water maps is useful for many types of irrigation management. A hybrid remote sensing evapotranspiration (ET) model combining reflectance-based basal crop coefficients (Kcbrf) and a two-source energy balance (TSEB) model was modified and validated for use in real-time irrigation management. We modeled spatial ET for maize and soybean fields in eastern Nebraska for the 2011-2013 growing seasons. We used Landsat 5, 7, and 8 imagery as remote sensing inputs. In the TSEB, we used the Priestly-Taylor (PT) approximation for canopy latent heat flux, as in the original model formulations. We also used the Penman-Monteith (PM) approximation for comparison. We compared energy balance fluxes and computed ET with measurements from three eddy covariance systems within the study area. Net radiation was underestimated by the model when data from a local weather station were used as input, with mean bias error (MBE) of -33.8 to -40.9 W m-2. The measured incident solar radiation appeared to be biased low. The net radiation model performed more satisfactorily when data from the eddy covariance flux towers were input into the model, with MBE of 5.3 to 11.2 W m-2. We removed bias in the daily energy balance ET using a dimensionless multiplier that ranged from 0.89 to 0.99. The bias-corrected TSEB ET, using weather data from a local weather station and with local ground data in thermal infrared imagery corrections, had MBE = 0.09 mm d-1 (RMSE = 1.49 mm d-1) for PM and MBE = 0.04 mm d-1 (RMSE = 1.18 mm d-1) for PT. The hybrid model used statistical interpolation to combine the two ET estimates. We computed weighting factors for statistical interpolation to be 0.37 to 0.50 for the PM method and 0.56 to 0.64 for the PT method. Provisions were added to the model, including a real-time crop coefficient methodology, which allowed seasonal crop coefficients to be computed with relatively few remote sensing images. This methodology performed well when compared to basal crop coefficients computed using a full season of input imagery. Water balance ET compared favorably with the eddy covariance data after incorporating the TSEB ET. For a validation dataset, the magnitude of MBE decreased from -0.86 mm d-1 (RMSE = 1.37 mm d-1) for the Kcbrf alone to -0.45 mm d-1 (RMSE = 0.98 mm d-1) and -0.39 mm d-1 (RMSE = 0.95 mm d-1) with incorporation of the TSEB ET using the PM and PT methods, respectively. However, the magnitudes of MBE and RMSE were increased for a running average of daily computations in the full May-October periods. The hybrid model did not necessarily result in improved model performance. However, the water balance model is adaptable for real-time irrigation scheduling and may be combined with forecasted reference ET, although the low temporal frequency of satellite imagery is expected to be a challenge in real-time irrigation management. Keywords: Center-pivot irrigation, ET estimation methods, Evapotranspiration, Irrigation scheduling, Irrigation water balance, Model validation, Variable-rate irrigation.

Remote sensing of evapotranspiration over cotton using the TSEB and METRIC energy balance models

2015 ◽  
Vol 158 ◽  
pp. 281-294 ◽  
Author(s):  
Andrew N. French ◽  
Douglas J. Hunsaker ◽  
Kelly R. Thorp
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Energy Balance Models

scholarly journals Evapotranspiration and evaporation/transpiration partitioning with dual source energy balance models in agricultural lands

2018 ◽  
Vol 380 ◽  
pp. 17-22 ◽  
Author(s):  
Gilles Boulet ◽  
Emilie Delogu ◽  
Sameh Saadi ◽  
Wafa Chebbi ◽  
Albert Olioso ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Water Stress ◽  
Energy Balance ◽  
Surface Temperature ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Stress Levels ◽  
Dual Source ◽  
Energy Balance Models

Abstract. EvapoTranspiration (ET) is an important component of the water cycle, especially in semi-arid lands. Its quantification is crucial for a sustainable management of scarce water resources. A way to quantify ET is to exploit the available surface temperature data from remote sensing as a signature of the surface energy balance, including the latent heat flux. Remotely sensed energy balance models enable to estimate stress levels and, in turn, the water status of most continental surfaces. The evaporation and transpiration components of ET are also just as important in agricultural water management and ecosystem health monitoring. Single temperatures can be used with dual source energy balance models but rely on specific assumptions on raw levels of plant water stress to get both components out of a single source of information. Additional information from remote sensing data are thus required, either something specifically related to evaporation (such as surface water content) or transpiration (such as PRI or fluorescence). This works evaluates the SPARSE dual source energy balance model ability to compute not only total ET, but also water stress and transpiration/evaporation components. First, the theoretical limits of the ET component retrieval are assessed through a simulation experiment using both retrieval and prescribed modes of SPARSE with the sole surface temperature. A similar work is performed with an additional constraint, the topsoil surface soil moisture level, showing the significant improvement on the retrieval. Then, a flux dataset acquired over rainfed wheat is used to check the robustness of both stress levels and ET retrievals. In particular, retrieval of the evaporation and transpiration components is assessed in both conditions (forcing by the sole temperature or the combination of temperature and soil moisture). In our example, there is no significant difference in the performance of the total ET retrieval, since the evaporation rate retrieved from the sole surface temperature is already fairly close to the one we can reconstruct from observed surface soil moisture time series, but current work is underway to test it over other plots.

scholarly journals Evapotranspiration of sorghum from the energy balance by METRIC and STSEB

2020 ◽  
Vol 24 (1) ◽  
pp. 24-30
Author(s):  
João G. A. Lima ◽  
Juan M. Sánchez ◽  
José G. Piqueras ◽  
José Espínola Sobrinho ◽  
Paula C. Viana ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Surface Energy Balance ◽  
Irrigation Management ◽  
The Other ◽  
Accurate Estimation ◽  
Actual Surface ◽  
Arid Conditions ◽  
Source Models ◽  
Semi Arid

ABSTRACT The estimate of the actual surface evapotranspiration (ET) contributes to quantifying the water needs of crops. An alternative to the use of lysimeter for an accurate estimation of water needs, which has proved to be of great value in recent years, is the use of remote sensing combined with models based on surface energy balance. There is wide variety of models that can be classified into two types: one-source models, such as the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) algorithm, or two-source models, such as the Simplified Two-Source Energy Balance (STSEB). The objective of this study was to analyze how METRIC and STSEB can be used to estimate ET, in comparison with the lysimeter data, for the different stages of development of the sorghum crop in Apodi, RN, Brazil. The accuracy of both models in the daily ET estimation for the semi-arid conditions of the experiment, with RMSE values of 0.8 and of 0.7 mm d-1 through METRIC and STSEB, respectively, is considered acceptable for irrigation management purposes. The errors obtained with METRIC at an instantaneous scale were 60, 50, 130 and 5 W m-2 for Rn, LE, H and G, respectively, on the other hand, using STSEB these errors were of 40, 70, 120 and 21 W m-2 for Rn, LE, H and G, respectively. The METRIC and STSEB models are very similar when it comes to providing information on water needs of the sorghum.

scholarly journals EVAPOTRANSPIRAÇÃO DE CULTURA: UMA ABORDAGEM DOS PRINCIPAIS MÉTODOS APLICADOS ÀS PESQUISAS CIENTÍFICAS E NA AGRICULTURA

Irriga ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 719-746
Author(s):  
Luan Peroni Venancio ◽  
Fernando França Da Cunha ◽  
Everardo Chartuni Mantovani ◽  
Cibele Hummel Do Amaral ◽  
Edvaldo Fialho Dos Reis
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Irrigation Management ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Crop Coefficient ◽  
Bowen Ratio ◽  
Climatic Conditions ◽  
Irrigated Agriculture ◽  
Crop Evapotranspiration

EVAPOTRANSPIRAÇÃO DE CULTURA: UMA ABORDAGEM DOS PRINCIPAIS MÉTODOS APLICADOS ÀS PESQUISAS CIENTÍFICAS E NA AGRICULTURA     LUAN PERONI VENANCIO1; FERNANDO FRANÇA DA CUNHA1; EVERARDO CHARTUNI MANTOVANI1; CIBELE HUMMEL DO AMARAL2 E EDVALDO FIALHO DO REIS3     1Departamento de Engenharia Agrícola, Universidade Federal de Viçosa, Av. Peter Henry Rolfs, s/n, Campus Universitário, CEP: 36570-900, Viçosa, MG, Brasil, [email protected], [email protected], [email protected] 2Departamento de Engenharia Florestal, Universidade Federal de Viçosa, Av. Peter Henry Rolfs, s/n, CEP: 36570-900, Viçosa, MG, Brasil, [email protected] 3Departamento de Engenharia Rural, Universidade Federal do Espírito Santo, Alto Universitário, s/nº, Guararema, CEP: 29500-000, Alegre, ES, [email protected]     1 RESUMO   Existem muitas metodologias para medição ou estimativa da evapotranspiração de cultura (ETc). Essas metodologias apresentam grandes diferenças entre si, especialmente no que se refere à base de formulação (empíricos, físicos ou a combinação de ambos), ao nível tecnológico (equipamentos, sensores sofisticados, etc.), a necessidade de dados de entrada, a área de aplicação, custo e precisão. Esta diversidade está relacionada à complexidade envolvida na transferência de água do sistema solo-planta para a atmosfera, com as variadas condições climáticas ao redor do planeta e também com os diferentes tipos de vegetação estudados. Nesta revisão, os seguintes métodos foram descritos e revisados: lisimetria (LIS), balanço de água no solo (BAS), razão de Bowen - balanço de energia (RBBE), covariância de vórtices turbulentos (CVT), modelos de fluxo de seiva (MFS), sistema de câmaras (SC), e métodos baseados no coeficiente de cultura (MBKc). Por fim, os métodos baseados no balanço de energia das superfícies (SRBE) e em índices de vegetação (SRIV), calculados a partir de dados de sensoriamento remoto (SR). Esses métodos foram selecionados por serem considerados, dentro do seu tipo de abordagem (hidrológica, micrometeorológica, fisiológica, empírica e sensoriamento remoto), os mais difundidos entre a comunidade científica internacional, e na agricultura.   Palavras-chave: agricultura irrigada, consumo hídrico, manejo da irrigação, coeficiente de cultura, sensoriamento remoto.     VENANCIO, L. P.; CUNHA, F. F.; MANTOVANI, E. C.; AMARAL, C. H.; REIS, E. F. CROP EVAPOTRANSPIRATION: AN APPROACH TO MAIN METHODS APPLIED TO SCIENTIFIC RESEARCHES AND IN AGRICULTURE     2 ABSTRACT   There are many methodologies for measuring or estimating crop evapotranspiration (ETc). These methodologies differ greatly from each other depending on the approach (empirical, physical or a combination of both), technological level, input dataset, application area, cost and accuracy. This wide diversity is related to the complexity involved in water transference from the soil-plant system to the atmosphere, within various climatic conditions around the Earth and also to the different types of vegetation. In this review, the following methods were described and reviewed: lysimeter (LIS), soil water balance (BAS), Bowen ratio - energy balance (RBBE), eddy covariance (CVT), sap-flow models (MFS), chamber system (SC) and, crop coefficient-based methods (MBKc). Finally, the methods based on surface energy balance (SRBE) and vegetation indices (SRIV) were estimated through remote sensing data (SR).These methods were selected because they are considered, within their type of approach (hydrological, micrometeorological, physiological, empirical and remote sensing), the most widespread among the international scientific community and in agriculture.   Keywords: irrigated agriculture, water consumption, irrigation management, crop coefficient, remote sensing.

scholarly journals A Spatio-temporal disaggregation method to derive time series of Normalized Difference Vegetation Index and Land Surface Temperature at fine spatial resolution

2014 ◽  
Vol XL-8 ◽  
pp. 1397-1401
Author(s):  
V. M. Bindhu ◽  
B. Narasimhan
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Energy Balance ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Fine Spatial Resolution ◽  
Temporal Disaggregation ◽  
Energy Balance Models ◽  
Spatio Temporal ◽  
Fine Resolution

Estimation of evapotranspiration (ET) from remote sensing based energy balance models have evolved as a promising tool in the field of water resources management. Performance of energy balance models and reliability of ET estimates is decided by the availability of remote sensing data at high spatial and temporal resolutions. However huge tradeoff in the spatial and temporal resolution of satellite images act as major constraints in deriving ET at fine spatial and temporal resolution using remote sensing based energy balance models. Hence a need exists to derive finer resolution data from the available coarse resolution imagery, which could be applied to deliver ET estimates at scales to the range of individual fields. The current study employed a spatio-temporal disaggregation method to derive fine spatial resolution (60 m) images of NDVI by integrating the information in terms of crop phenology derived from time series of MODIS NDVI composites with fine resolution NDVI derived from a single AWiFS data acquired during the season. The disaggregated images of NDVI at fine resolution were used to disaggregate MODIS LST data at 960 m resolution to the scale of Landsat LST data at 60 m resolution. The robustness of the algorithm was verified by comparison of the disaggregated NDVI and LST with concurrent NDVI and LST images derived from Landsat ETM+. The results showed that disaggregated NDVI and LST images compared well with the concurrent NDVI and LST derived from ETM+ at fine resolution with a high Nash Sutcliffe Efficiency and low Root Mean Square Error. The proposed disaggregation method proves promising in generating time series of ET at fine resolution for effective water management.

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