Crop productivity estimation by integrating multisensor satellite, in situ, and eddy covariance data into efficiency-based model.

Accurate and quantitative regional estimates of the carbon budget require an integration of eddy covariance (EC) flux-tower observations and remote sensing in ecosystem models. In this study, a simple remote sensing driven light use efficiency (LUE) model was used to estimate the primary productivity for major cropping systems using multi-temporal satellite data over the Saharanpur district in India.The model is based on radiation absorption and its conversion into biomass. The LUE model was implemented for major crop rotations derived from the time-series of Sentinel-2 and Landsat 8 with monthly satellite-based spatially explicit fields of photosynthetically active radiation (PAR), fraction of absorbed PAR (fAPAR) and down-regulated light use efficiency. Incident PAR and fAPAR were estimated on monthly basis from the ground-calibrated empirical equation using INSAT-3D insolation product and remote sensing-based vegetation indices, respectively. Spatial LUE maps created by down-regulating maximum LUE (EC tower-based) with water and temperature stressors derived from land surface water index (LSWI) and EC-based cardinal temperature, respectively. LUE-based modeled GPP over the sugarcane-wheat system was found higher than the rice-wheat system in Saharanpur district. This is because C4 crop (sugarcane) has very high photosynthetic efficiency compared to C3 crops (rice and wheat). Modeled GPP over the sugarcane-wheat system was found in good agreement with observed EC tower-based GPP (Index of Agreement = 0.93). Further regionally calibrated remote sensing-based LUE model well captures gross photosynthesis rates (GPP) over cropland ecosystem compared to globally modeled MODIS GPP product.

Dynamics of CO2 fluxes and controlling environmental factors in sugarcane (C4)-wheat (C3) ecosystem of dry sub-humid region in India.

In this study, CO2 exchange over sugarcane and wheat growing season was quantified by continuous measurement of CO2 fluxes using eddy covariance (EC) system from January 2014 to June 2015. We also elaborated on the response of CO2 fluxes to environmental variables. The results show that the ecosystem has seasonal and diurnal dynamics of CO2 with a distinctive U-shaped curve in both growing seasons with maximal CO2 absorption reaching up to -8.94 g C m-2 day-1 and -6.08 g C m-2 day-1 over sugarcane and wheat crop, respectively. The ecosystem as a whole acted as a carbon sink during the active growing season while it exhibits a carbon source prior to sowing and post-harvesting of crops. The cumulative net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Reco) were -923.04, 3316.65, and 2433.18 g C m-2 over the sugarcane growing season while the values were -192.30, 621.47, and 488.34 g C m-2 over the wheat growing season. The sesbania (green manure) appeared to be a carbon source once it is incorporated into soil. The response of day-time NEE to photosynthetically active radiation (PAR) under two vapor pressure deficit (VPD) sections (0-20 h Pa and 20-40 h Pa) seems more effective over sugarcane (R2 = 0.41-0.61) as compared to the wheat crop (R2 = 0.25-0.40). A decrease in net CO2 uptake was observed under higher VPD conditions. Similarly, night-time NEE was exponentially related to temperature at different soil moisture conditions and showed higher response to optimum soil moisture conditions for sugarcane (R2 = 0.87, 0.33 ≤ SWC < 0.42 m3 m-3) and wheat (R2 = 0.75, 0.31 ≤ SWC < 0.37 m3 m-3) crop seasons. The response of daily averaged NEE to environmental variables through path analysis indicates that PAR was the dominant predictor with the direct path coefficient of -0.65 and -0.74 over sugarcane and wheat growing season, respectively. Satellite-based GPP products from Moderate Resolution Imaging Spectroradiometer (GPPMOD) and Vegetation Photosynthetic model (GPPVPM) were also compared with the GPP obtained from EC (GPPEC) technique. The seasonal dynamics of GPPEC and GPPVPM agreed well with each other. This study covers the broad aspects ranging from micro-meteorology to remote sensing over C4-C3 cropping system.