Comparison of different models for estimation of net primary productivity in India

Abstract

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.

Keywords

• Net primary productivity
• biomass potential
• moisture adequacy index (MAI)
• Chikugo model
• Precipitation