The present study assessed the overall state of the soil based on the most sensitive soil attributes under different land uses—i.e., rainfed agriculture, mixed forest, afforestation and non-arable lands—in the lower Shivaliks of Indian Punjab. The soil parameters—i.e., erosion ratio, bulk density and water retention characteristics—and fertility parameters were integrated under different land uses to identify potential soil quality indicators.The overall state of the soil, based on a weighted average of primary soil functions under different land uses through fuzzy modeling, was deemed best for agricultural land use (0.515), followed by forests (0.465) and non-arable lands (0.456), and deemed worst under afforestation (0.428). Among the different land use systems, principal component analysis (PCA) clearly separated the agriculture and forest samples from afforestation and non-arable lands samples. The contribution of potential indicators such as erosion ratio (ER), phosphorus (P) and potassium (K) toward the soil quality index (SQI) was substantial. The order of contribution of the selected indicators to the SQI was 53.5%, 34.3% and 19.9% for ER, P and K, respectively. These indicators are most influential for studying real time soil health and ecological processes in the future, under various land use systems in degraded agroecosystems like the Shivaliks.

The novel coronavirus disease (COVID-19) halted almost all the industrial scale anthropogenic activities across the globe, resulting in improvements in water and air quality of megacities. Here, using Sentinel-2A data, we quantified impact of COVID-19 lockdown on the water quality parameters in one of the largest perennial creeks i.e., the Buddha Nala located in District Ludhiana in India. This creek has long been considered as a dumping ground for industrial wastes and has resulted in surface and ground water pollution in the entire lower Indus Basin. Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Chlorophyll Index (NDCI), Nitrogen Content Index (NI), Normalized Difference Turbidity Index (NDTI), and Total Suspended Matter (TSM) were compared prior (2019) and during (2020) lockdown in the creek. There was a significant enhancement in NDVI, NDWI, NDCI, and NI values, and reduction in NDTI and TSM values during the lockdown period. When compared with prior year (2019), the values of indices suggested an improvement in water quality and an indicative change in aquatic ecology in the creek. The impact of the COVID-19 lockdown on the improvement in water quality of Buddha Nala was more evident in the upstream and downstream sections than the middle section. This is intriguing since the middle section of the creek was continually impacted by domestic household effluents. The earth observation inspired methodology employed and findings are testament to the discriminatory power to employ remote sensing data and to develop protocols to monitor water quality in regions where routine surveillance of water remains cost prohibitive.