Development of satellite-based surface methane flux model for major agro-ecosystems using energy balance diagnostics
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Development of satellite‑based surface methane flux model for major agro‑ecosystems using energy balance diagnostics Sneha Thakur1,2 · Bimal K. Bhattacharya1 · Hitesh A. Solanki2 Received: 9 June 2019 / Revised: 28 April 2020 / Accepted: 5 May 2020 © The International Society of Paddy and Water Environment Engineering 2020
Abstract Present study was carried out to develop multiple linear regression (MLR) model of surface C H4 flux emission from monthly atmospheric clearness index (8 km), day-night land surface temperature (LST) at 1 km and surface soil moisture (25 km) from Kalpana-1, MODIS TERRA and GCOM-W1 satellites, respectively. All these products were aggregated to GOSAT level-4A product resolution. 2° × 2° grids representing homogeneous agro-ecosystems were used to draw data samples. Initial results showed that methane flux (from GOSAT) produced significant coefficient of determination (R2 = 0.84) with tri-variate (LST, surface soil moisture and atmospheric transmissivity) as compared to bi-variate (LST-soil moisture, LST-atmospheric transmissivity, soil moisture-atmospheric transmissivity) MLR models. These have been utilised for predicting surface methane flux for monthly scale. Validation of predicted methane flux with actual GOSAT methane flux was carried out and RMSE of 4.2–15.9% was obtained using variance-based bias correction. All these scaling models may be utilised to predict C H4 flux at regional level using high-resolution LST from thermal remote sensing and soil moisture from Synthetic Aperture Radar. Keywords Green house gases · Methane · Global warming potential · GOSAT · LST · Soil moisture · Clearness index
Introduction Excessive green-house effect is one of the main causes for climate change. Green house gases (GHG) in the earth’s atmosphere are transparent to sun’s shortwave radiation flux and prevent longwave radiation flux to escape, thus maintains earth’s temperature favourable for living beings. Both natural and anthropogenic forcings lead to gradual built-up of GHG. The Global Warming Potential (GWP) of CO2 and CH4 are 1 and 28, respectively, for 100 years, and 1 and 56, respectively, for 20 years (Houghton et al. 1996). The lifetime of methane is 12 ± 3 years, thus considering its global warming potential for 20 years is more suitable than for 100 years. In total, methane emissions are observed from biomass burning, water treatment plants, energy, landfills, ruminants of bovine animals and rice fields. Water treatment * Sneha Thakur [email protected] 1
Agriculture and Land Eco‑System Division, Space Applications Centre, Jodhpur Tekra, ISRO, Ahmedabad, Gujarat 380015, India
Department of Environmental Sciences, School of Science, Gujarat University, Ahmedabad, Gujarat, India
2
plants are point source and methane emissions are restricted to only anaerobic digestion so its contribution is usually low (7%) as compared to other sources. The ruminants of livestock (30%) and energy sector (30%) contribute highest to methane emissions, while biomass burni
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