Comparison of different models for estimation of net primary productivity in India
DOI:
https://doi.org/10.54386/jam.v14i2.1402Keywords:
Net primary productivity, biomass potential, moisture adequacy index (MAI), Chikugo model, PrecipitationAbstract
Net primary productivity (NPP) and biomass production potential were estimated for 167 stations of India by different models using weather parameters downloaded from CLIMWAT database of FAO. Moisture adequacy index (MAI) as suggested by Hargreaves was calculated. Chikugo model (NPPch), Miami models (NPPmp) and (NPPmt); Thornthwaite (NPPth) and Waginengen, (BIOwag) models were selected for estimating NPP. Correlation and best fit regression equations between MAI and NPP values showed positive relation with Chikugo (NPPch) and Miami based on precipitation (NPPmp) models but negative relation with others. Negative relations of MAI and NPP are not natural therefore the suitability of those models was rejected. The correlation coefficient with MAI to NPPch & NPPmp was 0.76 and 0.71 respectively. Chikugo model (NPPch) was found to be more sensible than Miami model because it estimated NPP in a broader range. The best fit equation developed using NPPch and MAI values showed a logarithmic relation (NPPcheq = 32.6 ln (MAI) + 33.13, R2 = 0.788) confirming that the net primary productivity by Chikugo model can also be estimated for the country using this as an alternative equation.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
This is a human-readable summary of (and not a substitute for) the license. Disclaimer.
You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.