Investigations on adsorptive removal of PVC microplastics from aqueous solutions using Pinus roxburghii-derived biochar.

This study investigates the adsorption mechanisms of pine bark biochar (BC) and modified pine bark biochar (MBC) in the removal of polyvinyl chloride (PVC) microplastics from aqueous solutions, with a significant focus on resource recovery from pine residues which is one of the key Himalayan Forest byproducts. The research findings highlighted the optimal adsorption capacity of biochar at 131.5 mg/g achieved after 6 h of contact time, with a pH of 10 and a PVC microplastic concentration of 200 mg/L.

Impacts of hydrometeorological factors on discharge simulation in the North West Himalayas: a SUFI-2 algorithm-driven investigation using the SWAT model.

The Soil and Water Assessment Tool (SWAT) is a computational hydrological model extensively utilised for developing sustainable strategies and viable approaches for prudent management of water resources. The central emphasis of this study is on the utilisation of SWAT model along with SWAT-CUP (SWAT calibration toolbox) to simulate streamflow in the upper Jhelum basin, the North West Himalayas, for a period of 20 years from 2000 to 2019. The global sensitivity analysis algorithm, Sequential Uncertainty Fitting 2 (SUFI-2) of SWAT-CUP, is used for sensitivity and uncertainty analysis.

Employing sensitivity analysis to catchments having scanty data.

Sensitivity analysis (SA) is generally desirable for parameter optimization, mapping, and calibration in hydrological models, yet the implementation of SA in data-sparse regions is usually avoided due to a lack of continuous data. The present study proposes the novel concept of "minimum continuous data period" to overcome this constraint. It analyses the sensitivity profile of two data-suffice sub-catchments of a data-sparse watershed using data at various timescales to determine the minimum data period required for the SA.

Investigating the potential of Morris algorithm for improving the computational constraints of global sensitivity analysis.

Sensitivity analysis (SA) is widely acknowledged as advantageous and worthwhile in recognizing parameters for model calibration and optimization, especially in complex hydrological models. Although Sobol global SA is an efficient way to evaluate the sensitivity indices, the computational cost is a constraint. This study analyzes the potential of Morris global SA to achieve results tantamount to Sobol SA, at a much cheaper computational expense, using a new approach of increasing the number of replications for the Morris algorithm.