An optimal model was developed for accounting forest carbon stock from synergistic use of optical data from Landsat TM and synthetic aperture radar (SAR) data from COSMO-Skymed (X-band), Radarsat-2 (C-band) and ALOS PALSAR (L-band) sensors over a tropical deciduous heterogeneous forest of India. The best-fit integrated multiple linear regression model had a model accuracy of 83%, r2 = 0.96, root mean square error = 10.02 Mg/ha and Willmott’s index of agreement of 0.98. The model further validated using chi-squared and t-test. Results of models for calculating the aboveground biomass (AGB) were converted to C and CO2 using conversion factors. Average AGB, C and CO2 were 70.5, 35.26 and 130.89 Mg/ha, respectively. The synergistic use of optical and multi-frequency SAR data enhanced the AGB saturation threshold to about 150 Mg/ha for tropical deciduous mixed forests. Hence, the synergistic use of this data is suggested for large-scale AGB and C estimations for tropical forests. Optical remote sensing sensors are extensively used due to greater data availability despite their poor sensitivity toward forest parameters. In contrast, SAR signals are highly sensitive toward forest biophysical and structural parameters, providing a better alternative. This unique integrated approach provides valuable information regarding the spatial distribution and quantification of forest biomass and carbon.
The objective of this study is to measure the balance of water demand versus water resource availability in an interfluve of West Bengal, India to support water resource planning, particularly of inter-basin transfers. Surface water availability was modelled using the US Soil Conservation Service curve number (SCS-CN) approach, whilst groundwater availability was modelled based on water-level fluctuations and the rainfall infiltration method. Water use was modelled separately for the agricultural, industrial, and domestic sectors using a predominantly normative approach and water use to availability ratios calculated for different administrative areas within the interfluve. Overall, the approach suggested that the interfluve receives 327 × 106 m3 year-1 of excess water after satisfying these sectoral demands, but that the eastern part of the study area is in deficit. However, a sensitivity analysis carried on the approach to several assumptions in the model suggested changed circumstances would produce surplus/deficit ranging from −215 × 106 to 435 × 106 m3 year-1 . The approach could have potential for localised water balance modelling in other Indian catchments.
16 November 2020 in Arabian Journal of Geosciences