scholarly journals CALIBRATION AND VALIDATION OF THERMAL-TIME BASED MODELS FOR FOREWARNING OF APHID PEST IN RAPESEED-MUSTARD CROP IN INDIA

MAUSAM ◽  
2021 ◽  
Vol 72 (2) ◽  
pp. 501-506
Author(s):  
MEHNAJ THARRANUM A. ◽  
K. K. SINGH ◽  
AVINASH C. PANDEY ◽  
Y. P. SINGH ◽  
BASANT K. KANDPAL
Keyword(s):  
Thermal Time ◽  
Calibration And Validation ◽  
Mustard Crop

Investigations of alternative kale management: Production, regrowth and quality from different sowing and defoliation dates

2007 ◽  
pp. 29-33 ◽  
Author(s):  
H.E. Brown ◽  
S. Maley ◽  
D.R. Wilson
Keyword(s):  
Sowing Date ◽  
Linear Increase ◽  
Thermal Time ◽  
Total Production

Gruner kale showed a linear increase (8.0 kg DM/ha per °Cd) in biomass with sowings on 1 October, 3 November and 1 December producing 23, 19 and 17 t DM/ha (respectively) by the 29 May. Regrowth following mid season defoliation was slow (5.3 kg DM/ha per °Cd) reducing total production (relative to undefoliated) by 7.5 and 5.5 t DM/ha for treatments defoliated on the 29 January and 14 March, respectively. Keyworks: defoliation, kale, quality, regrowth, sowing date, thermal time, yield

A thermal time model for optimising herbicide dose in maize

Weed Research ◽  
2021 ◽  
Author(s):  
Behnaz Pourmorad Kaleibar ◽  
Mostafa Oveisi ◽  
Hassan Alizadeh ◽  
Heinz Mueller Schaerer
Keyword(s):  
Thermal Time ◽  
Time Model ◽  
Thermal Time Model

scholarly journals Calibration and Validation of ArcGIS Solar Radiation Tool for Photovoltaic Potential Determination in the Netherlands

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1865
Author(s):  
Bala Bhavya Kausika ◽  
Wilfried G. J. H. M. van Sark
Keyword(s):  
Solar Radiation ◽  
The Netherlands ◽  
Urban Areas ◽  
Input Data ◽  
Solar Irradiation ◽  
Energy Yield ◽  
Atmospheric Parameters ◽  
Factors Affecting ◽  
Calibration And Validation ◽  
Solar Radiation Model

Geographic information system (GIS) based tools have become popular for solar photovoltaic (PV) potential estimations, especially in urban areas. There are readily available tools for the mapping and estimation of solar irradiation that give results with the click of a button. Although these tools capture the complexities of the urban environment, they often miss the more important atmospheric parameters that determine the irradiation and potential estimations. Therefore, validation of these models is necessary for accurate potential energy yield and capacity estimations. This paper demonstrates the calibration and validation of the solar radiation model developed by Fu and Rich, employed within ArcGIS, with a focus on the input atmospheric parameters, diffusivity and transmissivity for the Netherlands. In addition, factors affecting the model’s performance with respect to the resolution of the input data were studied. Data were calibrated using ground measurements from Royal Netherlands Meteorological Institute (KNMI) stations in the Netherlands and validated with the station data from Cabauw. The results show that the default model values of diffusivity and transmissivity lead to substantial underestimation or overestimation of solar insolation. In addition, this paper also shows that calibration can be performed at different time scales depending on the purpose and spatial resolution of the input data.

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