Net ecosystem CO2 exchange from jute crop (Corchorus olitorius L.) and its environmental drivers in tropical Indo-Gangetic plain using open-path eddy covariance technique.

Present study is a maiden attempt to assess net ecosystem exchange (NEE) of carbon dioxide (CO2) flux from jute crop (Corchorus olitorius L.) in the Indo-Gangetic plain by using open-path eddy covariance (EC) technique. Diurnal variations of NEE were strongly influenced by growth stages of jute crop. Daytime peak NEE varied from - 5 µmol m-2 s-1 (in germination stage) to - 23 µmol m-2 s-1 (in fibre development stage). The ecosystem was net CO2 source during nighttime with an average NEE value of 5-8 µmol m-2 s-1. Combining both daytime and nighttime CO2 fluxes, jute ecosystem was found to be a net CO2 sink on a daily basis except the initial 9 days from date of sowing. Seasonal and growth stage-wise NEEs were computed, and the seasonal total NEE over the jute season was found to be - 268.5 gC m-2 (i.e. 10.3 t CO2 ha-1). In different jute growth stages, diurnal variations of NEE were strongly correlated (R2 > 0.9) with photosynthetic photon flux density (PPFD). Ecosystem level photosynthetic efficiency parameters were estimated at each growth stage of jute crop using the Michaelis-Menten equation. The maximum values of photosynthetic capacity (Pmax, 63.3 ± 1.15 µmol CO2 m-2 s-1) and apparent quantum yield (α, 0.072 ± 0.0045 µmol CO2 µmol photon-1) were observed during the active vegetative stage, and the fibre development stage, respectively. Results of the present study would significantly contribute to understanding of the carbon flux from the Indian agro-ecosystems, which otherwise are very sparse.

Seasonal and annual variations of CO2 and CH4 at Shadnagar, a semi-urban site.

Carbon dioxide (CO2) and methane (CH4) are the most important greenhouse gases (GHGs) due to their significant role in anthropogenic global climate change. The spatio-temporal variations of their concentration are characterized by the terrestrial biosphere, seasonal weather patterns and anthropogenic emissions. Hence, to understand the variability in regional surface GHG fluxes, high precision GHGs measurements were initiated by the National Remote Sensing Center (NRSC) of India. We report continuous CO2 and CH4measurements during 2014 to 2017 for the first time from Shadnagar, a suburban site in India. Annual mean CO2 and CH4 concentrations are 399.56 ± 5.46 ppm and 1.929 ± 0.09 ppm, respectively, for 2017. After the strong El Niño of 2015-2016, an abnormal rise in CO2 growth rate of 5.5 ppm year-1 was observed in 2017 at the study site, compared to 3.03 ppm year-1 at Mauna Loa. Thus, the repercussion of the El Niño effect diminishes the net uptake by the terrestrial biosphere accompanied by increased soil respiration. Seasonal tracer to tracer correlation between CO2 and CH4 was also analyzed to characterize the possible source-sink relationship between the species. We compared CO2 and CH4 concentrations to simulations from an atmospheric chemistry transport model (ACTM). The seasonal phases of CH4 were well captured by the ACTM, whereas the seasonal cycle amplitude of CO2 was underestimated by about 30%.

Assessing lodging damage of jute crop due to super cyclone Amphan using multi-temporal Sentinel-1 and Sentinel-2 data over parts of West Bengal, India.

The present study is a maiden attempt to assess jute crop lodging due to super cyclone Amphan (20 May 2020) by synergistic use of Sentinel-2 (optical) and Sentinel-1 (SAR) data over part of West Bengal, India. Pre-event Sentinel-2 data (9 April, 14 May) along with the ground information were used to map the jute crop of the affected districts with accuracy of 85%. The cross-polarized backscatter (σ0VH) of Sentinel-1 was found to be sensitive to the sudden change in the canopy structure due to lodging and partial flooding. [Formula: see text](σ0VH_22 May - σ0VH_16 May) indicating post-event damage was > 2.5 dB over the affected jute crop and [Formula: see text] (σ0VH_22 May - σ0VH_28 May) representing post-event recovery showed > 1.5 dB for recovered crop, depending on the crop vigor/height. Decision matrix was prepared combining [Formula: see text] and [Formula: see text] for NDVI-based crop vigor strata (low, medium, and high) to classify the area into affected, marginally affected and normal. Overall accuracy of the classified map was found to be 84.12% with kappa coefficient of 0.74. Nearly, 12.5% of the jute area, i.e., 38,119 ha was found to be either affected or marginally affected due to Amphan and distributed in the southern part of Murshidabad, north-eastern Nadia, northern 24 Paraganas (N), and middle region of Hooghli district. Geospatial map of block-wise affected jute area was prepared to facilitate informed decision making. The study demonstrated an operational methodology for assessing crop lodging due to natural calamities to support relief management and crop insurance.

Identification and characterization of spatio-temporal hotspots of forest fires in South Asia.

Forest fire is considered as one of the major threats to global biodiversity and a significant source of greenhouse gas emissions. Rising temperatures, weather conditions, and topography promote the incidences of fire due to human ignition in South Asia. Because of its synoptic, multi-spectral, and multi-temporal nature, remote sensing data can be a state of art technology for forest fire management. This study focuses on the spatio-temporal patterns of forest fires and identifying hotspots using the novel geospatial technique "emerging hotspot analysis tool" in South Asia. Daily MODIS active fire locations data of 15 years (2003-2017) has been aggregated in order to characterize fire frequency, fire density, and hotspots. A total of 522,348 active fire points have been used to analyze risk of fires across the forest types. Maximum number of forest fires in South Asia was occurring during the January to May. Spatial analysis identified areas of frequent burning and high fire density in South Asian countries. In South Asia, 51% of forest grid cells were affected by fires in 15 years. Highest number of fire incidences was recorded in tropical moist deciduous forest and tropical dry deciduous forest. The emerging hotspots analysis indicates prevalence of sporadic hotspots, followed by historical hotspots, consecutive hotspots, and persistent hotspots in South Asia. Of the seven South Asian countries, Bangladesh has highest emerging hotspot area (34.2%) in forests, followed by 32.2% in India and 29.5% in Nepal. Study results offer critical insights in delineation of fire vulnerable forest landscapes which will stand as a valuable input for strengthening management of fires in South Asia.