Evapotranspiration estimation based on MODIS products and surface energy balance algorithms for land (SEBAL) model in Sanjiang Plain, Northeast China

2013 ◽  
Vol 23 (1) ◽  
pp. 73-91 ◽  
Author(s):  
Jia Du ◽  
Kaishan Song ◽  
Zongming Wang ◽  
Bai Zhang ◽  
Dianwei Liu
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Northeast China ◽  
Surface Energy Balance ◽  
Sanjiang Plain ◽  
Sebal Model ◽  
Evapotranspiration Estimation

scholarly journals EVAPOTRANSPIRAÇÃO E COEFICIENTE DE CULTURA DO CAFEEIRO IRRIGADO A PARTIR DE IMAGENS DE SENSORES ORBITAIS

Irriga ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 31-37
Author(s):  
THALLES LOIOLA DIAS ◽  
Alex PORTO RODRIGUES ◽  
MILLER RAIK ARCANJO BATISTA ◽  
Marcelo Rossi Vicente ◽  
RONALDO MEDEIROS DOS SANTOS
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Irrigation Management ◽  
Crop Coefficient ◽  
Minas Gerais ◽  
Crop Evapotranspiration ◽  
Landsat 7 ◽  
Sebal Model ◽  
E Mail

EVAPOTRANSPIRAÇÃO E COEFICIENTE DE CULTURA DO CAFEEIRO IRRIGADO A PARTIR DE IMAGENS DE SENSORES ORBITAIS     THALLES LOIOLA DIAS1; ALEX PORTO RODRIGUES2; MILLER RAIK ARCANJO BATISTA3; Marcelo Rossi Vicente4 e Ronaldo Medeiros dos Santos5   1 Instituto Federal do Norte de Minas Gerais, Campus Salinas, Fazenda Varginha Km 02 Rod. Salinas/Taiobeiras - Salinas/MG -CEP:39560-000, Salinas, MG, Brasil. E-mail: [email protected]. 2 Instituto Federal do Norte de Minas Gerais, Campus Salinas, Fazenda Varginha Km 02 Rod. Salinas/Taiobeiras - Salinas/MG -CEP:39560-000, Salinas, MG, Brasil. E-mail: [email protected]. 3 Instituto Federal do Norte de Minas Gerais, Campus Salinas, Fazenda Varginha Km 02 Rod. Salinas/Taiobeiras - Salinas/MG -CEP:39560-000, Salinas, MG, Brasil. E-mail: [email protected]. 4 Instituto Federal do Norte de Minas Gerais, Campus Salinas, Fazenda Varginha Km 02 Rod. Salinas/Taiobeiras - Salinas/MG -CEP:39560-000, Salinas, MG, Brasil. E-mail: [email protected]. 5 Instituto Federal do Norte de Minas Gerais, Campus Salinas, Fazenda Varginha Km 02 Rod. Salinas/Taiobeiras - Salinas/MG - CEP:39560-000, Salinas, MG, Brasil. E-mail:[email protected].     1 RESUMO   O uso de sensoriamento remoto na agricultura é uma realidade. Dentre os diversos usos, destaca-se a determinação da evapotranspiração dos cultivos para o auxílio do processo de gerenciamento da irrigação. O presente trabalho objetivou determinar a evapotranspiração e o coeficiente da cultura do cafeeiro através do algoritmo SEBAL (Surface Energy Balance Algorithm for Land) na região Oeste da Bahia. Para a realização do estudo foram utilizadas imagens do satélite LANDSAT 7. A evapotranspiração de referência foi estimada pelo método Penman-Monteith FAO e, posteriormente, calculou-se o coeficiente da cultura (Kc) com base na evapotranspiração obtida via SEBAL. Os índices estatísticos para avaliar a eficácia do modelo SEBAL foram: o desvio da raiz quadrada média (RMSE); o erro médio absoluto (MAE); o coeficiente de determinação (R2); e o erro relativo (RE). O modelo SEBAL mostrou-se eficiente na determinação da evapotranspiração da cultura do cafeeiro e no coeficiente de cultura.   Palavras-chave: índice de vegetação; sebal; manejo de irrigação.     DIAS, T.L.; RODRIGUES, A.P.; BATISTA, M.R.A.; VICENTE, M.R.; SANTOS, R. M. EVAPOTRANSPIRATION AND CROP COEFFICIENT OF COFFEE PLANTS FROM ORBITAL SENSORS IMAGES     2 ABSTRACT   The use of remote sensing in agriculture is a reality. Among the various uses, the determination of crop evapotranspiration to aid the irrigation management process is detached. The present work aimed to determine the evapotranspiration and the crop coefficient of coffee through the Surface Energy Balance Algorithm for Land (SEBAL) in western Bahia. LANDSAT 7 satellite images were used to perform the study. The reference evapotranspiration was estimated by the FAO Penman-Monteith method and subsequently the crop coefficient (Kc) was calculated based on the evapotranspiration obtained by SEBAL. The statistical indexes for evaluating the effectiveness of the SEBAL model were the root mean square error (RMSE), the mean absolute error (MAE), the coefficient of determination (R²) and the relative error (RE). The SEBAL model proved to be efficient in determining coffee crop evapotranspiration and crop coefficient.   Keywords: vegetation index; sebal; water management.

Estimation and Analysis of Regional Evapotranspiration in the eastern province of China with Remote Sensing data

2020 ◽  
Author(s):  
Wenyu Wu
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Surface Energy ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Meteorological Data ◽  
Computation Method ◽  
Model Parameters ◽  
Sebal Model ◽  
Regional Evapotranspiration

<p>Evapotranspiration(ET) is a critical component of the land surface energy balance system and hydrologic processes. Analysis of spatiotemporal variations and influencing factors of ET is of great importance to evaluate the growing environment for crops and to effectively use water resources, a critical base for production in research region. The traditional methods are based on point measurement, while the remote sensing provides extensive surface information. The development of remote sensing has promoted the study of regional ET.SEBAL model is based on Surface Energy Balance Algorithm for Land and its physical meaning is clear. This model was developed to show the spatial variability of surface evapotranspiration. SEBAL model was capable of being applied to large regional areas in conjunction with Moderate-resolution Imaging Spectroradiometer (MODIS) data products.According to the shortcomings of the traditional method of calculating ET, based on SEBAL model, the daily regional evapotranspiration of Anhui Province was estimated with 1km spatial resolution by using MODIS products and a few of meteorological data(temperature, wind speed) collected in meteorological stations distributed over the study area.Because of lacking observed data from the lysimeter, the results of P-M were compared with the estimation results based on SEBAL model in this research.The comparison of the evapotranspiration estimated with MODIS products and field observation showed that the former results were lower than the latter results on the whole, and demonstrated that there existed certain trend in correlation between the two results, the average relative error was different at different land surface.The ET computation method based on Remote Sensing proves that this model has strong practicality in Anhui, and it will show great potential in this field with more optimizing the model parameters.</p>

scholarly journals Comparing Remotely-Sensed Surface Energy Balance Evapotranspiration Estimates in Heterogeneous and Data-Limited Regions: A Case Study of Tanzania’s Kilombero Valley

2019 ◽  
Vol 11 (11) ◽  
pp. 1289 ◽  
Author(s):  
William Senkondo ◽  
Subira E. Munishi ◽  
Madaka Tumbo ◽  
Joel Nobert ◽  
Steve W. Lyon
Keyword(s):  
Energy Balance ◽  
Water Resources ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Rapid Development ◽  
Remotely Sensed ◽  
Eastern Africa ◽  
Irrigated Agriculture ◽  
Kilombero Valley ◽  
Sebal Model

Evapotranspiration (ET) plays a crucial role in integrated water resources planning, development and management, especially in tropical and arid regions. Determining ET is not straightforward due to the heterogeneity and complexity found in real-world hydrological basins. This situation is often compounded in regions with limited hydro-meteorological data that are facing rapid development of irrigated agriculture. Remote sensing (RS) techniques have proven useful in this regard. In this study, we compared the daily actual ET estimates derived from 3 remotely-sensed surface energy balance (SEB) models, namely, the Surface Energy Balance Algorithm for Land (SEBAL) model, the Operational Simplified Surface Energy Balance (SSEBop) model, and the Simplified Surface Balance Index (S-SEBI) model. These products were generated using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery for a total of 44 satellite overpasses in 2005, 2010, and 2015 in the heterogeneous, highly-utilized, rapidly-developing and data-limited Kilombero Valley (KV) river basin in Tanzania, eastern Africa. Our results revealed that the SEBAL model had a relatively high ET compared to other models and the SSEBop model had relatively low ET compared to the other models. In addition, we found that the S-SEBI model had a statistically similar ET as the ensemble mean of all models. Further comparison of SEB models’ ET estimates across different land cover classes and different spatial scales revealed that almost all models’ ET estimates were statistically comparable (based on the Wilcoxon’s test and the Levene’s test at a 95% confidence level), which implies fidelity between and reliability of the ET estimates. Moreover, all SEB models managed to capture the two spatially-distinct ET regimes in KV: the stable/permanent ET regime on the mountainous parts of the KV and the seasonally varied ET over the floodplain which contains a Ramsar site (Kilombero Valley Floodplain). Our results have the potential to be used in hydrological modelling to explore and develop integrated water resources management in the valley. We believe that our approach can be applied elsewhere in the world especially where observed meteorological variables are limited.

scholarly journals Using climate reanalysis data in conjunction with multi-temporal satellite thermal imagery to derive supraglacial debris thickness changes from energy-balance modelling

2021 ◽  
pp. 1-19
Author(s):  
Rebecca L. Stewart ◽  
Matthew Westoby ◽  
Francesca Pellicciotti ◽  
Ann Rowan ◽  
Darrel Swift ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Current Knowledge ◽  
Meteorological Data ◽  
Reanalysis Data ◽  
Balance Model ◽  
Thermal Imagery ◽  
Thickness Estimation ◽  
Miage Glacier

Abstract Surface energy-balance models are commonly used in conjunction with satellite thermal imagery to estimate supraglacial debris thickness. Removing the need for local meteorological data in the debris thickness estimation workflow could improve the versatility and spatiotemporal application of debris thickness estimation. We evaluate the use of regional reanalysis data to derive debris thickness for two mountain glaciers using a surface energy-balance model. Results forced using ERA-5 agree with AWS-derived estimates to within 0.01 ± 0.05 m for Miage Glacier, Italy, and 0.01 ± 0.02 m for Khumbu Glacier, Nepal. ERA-5 data were then used to estimate spatiotemporal changes in debris thickness over a ~20-year period for Miage Glacier, Khumbu Glacier and Haut Glacier d'Arolla, Switzerland. We observe significant increases in debris thickness at the terminus for Haut Glacier d'Arolla and at the margins of the expanding debris cover at all glaciers. While simulated debris thickness was underestimated compared to point measurements in areas of thick debris, our approach can reconstruct glacier-scale debris thickness distribution and its temporal evolution over multiple decades. We find significant changes in debris thickness over areas of thin debris, areas susceptible to high ablation rates, where current knowledge of debris evolution is limited.

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