Methodology for Analysis of Energy Balance using State Estimator and Real-Time Measurementas

Author(s):  
Angelica Felipe da Silva ◽  
Wagner Seizo Wokama ◽  
Daniel Pinheiro Bernardon ◽  
Daniel Sperb Porto ◽  
Alzenira da Rosa Abaide ◽  
...  
Author(s):  
Angelica Felipe da Silva ◽  
Daniel Pinheiro Bernardon ◽  
Alzenira da Rosa Abaide ◽  
Maicon Jaderson da Silveira Ramos ◽  
Daniel Sperb Porto

2018 ◽  
Vol 61 (2) ◽  
pp. 533-548 ◽  
Author(s):  
J. Burdette Barker ◽  
Christopher M. U. Neale ◽  
Derek M. Heeren ◽  
Andrew E. Suyker

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.


2020 ◽  
Vol 312 ◽  
pp. 127967 ◽  
Author(s):  
Jianguo Feng ◽  
Pavel Podesva ◽  
Hanliang Zhu ◽  
Jan Pekarek ◽  
Carmen. C. Mayorga-Martinez ◽  
...  
Keyword(s):  

Author(s):  
Ewout van der Laan ◽  
Frans Veldpaus ◽  
Cees van Schie ◽  
Maarten Steinbuch

1995 ◽  
Vol 3 (2) ◽  
pp. 275-280 ◽  
Author(s):  
M. Takahashi ◽  
M. Kitamura ◽  
H. Yoshikawa

2012 ◽  
Vol 13 (1) ◽  
pp. 59-70 ◽  
Author(s):  
Yufei Yuan ◽  
J. W. C. van Lint ◽  
R. Eddie Wilson ◽  
Femke van Wageningen-Kessels ◽  
Serge P. Hoogendoorn

2007 ◽  
Vol 292 (3) ◽  
pp. E820-E828 ◽  
Author(s):  
Patricia Silveyra ◽  
Paolo N. Catalano ◽  
Victoria Lux-Lantos ◽  
Carlos Libertun

Orexins and their receptors OX1 and OX2 regulate energy balance and the sleep-wake cycle. We studied the expression of prepro-orexin (PPO), OX1, and OX2 in brain and pituitary under the influence of the hormonal status in adult rats. Primarily, PPO, OX1, and OX2 expression was determined in Sprague-Dawley female cycling rats during proestrus and in males. Animals were killed at 2-h intervals. Anterior (AH) and mediobasal (MBH) hypothalamus, anterior pituitary (P), and frontoparietal cortex (CC) were homogenized in TRIzol, and mRNAs were obtained for screening of PPO, OX1, OX2 expression by semiquantitative RT-PCR. Main findings were confirmed and extended to all days of the cycle by quantitative real-time RT-PCR. Hormones and food consumption were determined. Finally, OX1, OX2, and PPO were measured by real-time RT-PCR in tissues collected at 1900 of proestrus after treatments at 1400 with ovulation-blocking agents Cetrorelix or pentobarbital. OX1 and OX2 expression increased at least threefold in AH, MBH, and P, but not in CC, between 1700 and 2300 of proestrus, without variations in estrus, diestrus, or in males. PPO in AH and MBH showed a fourfold or higher increase only during proestrus afternoon. Cetrorelix or pentobarbital prevented increases of OX1 and OX2 only in the pituitary and blunted gonadotropin surges, but left OX1, OX2, and PPO brain expression unchanged. Reproduction, energy balance, and sleep-wake cycle are integrated. Here, we demonstrate that, in the physiological neuroendocrine condition leading to ovulation, information to the orexinergic system acts in hypothalamus and pituitary by different mechanisms.


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