Publications

Raju, A; Sijikumar, S; Burman, PKD; Valsala, V; Tiwari, YK; Mukherjee, S; Lohani, P; Kumar, K (2023). Very high-resolution Net Ecosystem Exchange over India using Vegetation Photosynthesis and Respiration Model (VPRM) simulations. ECOLOGICAL MODELLING, 481, 110340.

Abstract
The terrestrial biosphere has a crucial role in controlling the rate of CO2 accumulation in the atmosphere. The quantification of Net Ecosystem Exchange (NEE) is critical to determine whether the regional terrestrial ecosystem is a net sink or source of CO2. This study uses a satellite-data derived light-use-efficiency model (the Vegetation Photosynthesis and Respiration Model, VPRM) to compute the biospheric CO2 fluxes over India from 2011-2020. A very high-resolution Land Use-Land Cover (LULC) data from the IRS-P6 satellite and MODIS derived surface reflectance are utilised to compute the NEE over distinct vegetation types at similar to 9 kmx 9 km. The VPRM model for the Indian region captures the spatial pattern and seasonal features of NEE over the country. The magnitude of annual mean NEE over India from the VPRM model is relatively high compared to that from Carbon Tracker, FLUXCOM, and Soil Moisture Active Passive Level-4 carbon data products. However, the VPRM model simulated NEE agrees with the NEE observations from the eddy covariance estimates, which are accepted as the ground truth. The fusion of high-resolution LULC and surface reflectance data in VPRM suggests that the average NEE over the Indian region during 2011-2020 is -0.16 +/- 0.02 PgC yr-1. Among this, the contribution from Gross Ecosystem Exchange is about -0.47 +/- 0.02 PgC yr-1, and Respiration is 0.31 +/- 0.01 PgC yr-1. The maximum biospheric CO2 absorption is during the post-monsoon season, and the minimum is during the pre-monsoon season. The very high spatial resolution and heterogeneity resolved in the NEE data derived in this work offer the first data product of this kind for a variety of NEE analyses over India.

DOI:
10.1016/j.ecolmodel.2023.110340

ISSN:
1872-7026