The Yamuna's stretch within Delhi is considered as the dirtiest river reach in India and despite numerous restoration plans, pollution levels have risen unabated. However, the enforcement of a nationwide lockdown due to the ongoing COVID-19 pandemic can possibly provide a ray of hope. We analyze the lockdown's impact on the water quality status of this stretch using a combination of measured parameters and satellite image derived indices. Class C Water Quality Index estimates of nine stations indicate an improvement of 37% during the lockdown period. The Biological Oxygen Demand and Chemical Oxygen Demand values reduced by 42.83% and 39.25%, respectively, compared to the pre-lockdown phase, while Faecal Coliform declined by over 40%. Similar analysis of 20 major drains that meet the Yamuna revealed declining effluent loads and discernable improvements in drain contaminant status were ascertained via a hierarchical cluster analysis. Reach-wise suspended particulate matter content, turbidity and algal signatures were derived from multi-temporal Landsat-8 images of prior and ongoing lockdown periods for 117 channel segment zones. These parameters also declined notably within most stretches, although their extents were spatially varied. While the partial/non-operational status of most industries during the lockdown enabled significant reduction in effluent loads and a consequent betterment in the river water quality, its spatial variations and even deterioration in some locations resulted from the largely undiminished inflow of domestic sewage through multiple drains. This study provides an estimate of possible river recovery extents and degree of improvement if deleterious polluting activities and contaminants are regulated properly.

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Background With myriad geospatial datasets now available for terrain information extraction and particularly streamline demarcation, there arises questions regarding the scale, accuracy and sensitivity of the initial dataset from which these aspects are derived, as they influence all other parameters computed subsequently. In this study, digital elevation models (DEM) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER V2), Shuttle Radar Topography Mission (SRTM V4, C-Band, 3 arc-second), Cartosat -1 (CartoDEM 1.0) and topographical maps (R.F. 1:250,000 and 1:50,000), have been used to individually extract and analyze the relief, surface, size, shape and texture properties of a mountainous drainage basin.ResultsNestled inside a mountainous setting, the basin is a semi-elongated one with high relief ratio (>90), steep slopes (25°–30°) and high drainage density (>3.5 km/sq km), as computed from the different DEMs. The basin terrain and stream network is extracted from each DEM, whose morphometric attributes are compared with the surveyed stream networks present in the topographical maps, with resampling of finer DEM datasets to coarser resolutions, to reduce scale-implications during the delineation process. Ground truth verifications for altitudinal accuracy have also been done by a GPS survey.ConclusionsDEMs derived from the 1:50,000 topographical map and ASTER GDEM V2 data are found to be more accurate and consistent in terms of absolute accuracy, than the other generated or available DEM data products, on basis of the morphometric parameters extracted from each. They also exhibit a certain degree of proximity to the surveyed topographical map.