Extreme weather events viz. cloud bursting, temperature inversion, landslides etc. along with the other global warming effects acts as the catalyst to snow melt and increase the size of existing glacial lakes in the mountainous regions like Himalayas of Himachal Pradesh. The extra load of water in these glacial lakes as a result of snow melt and extreme events causes ‘Glacial lakes Outburst Flood’ (GLOF) those are very remote phenomena and hard to map and monitored physically. Simultaneously, these events of GLOFs are hazardous for the region and habitants of the hills. Therefore, it is vital to map and monitor such type of glacial lakes with remote sensing and GIS techniques. The present research has been carried out for the spatio-temporal mapping of glacial lakes in the Himachal Pradesh state using Landsat satellite time series data during 1980 to 2017. The year of 1980, 1990, 2000, 2010, and 2017 were selected for the mapping using well known Normalized Difference Water Index (NDWI > 0.25). Results showed a continuous increase in the number and coverage of the glacial lakes during the study period. There were 102 glacial lakes covering an area of 222.8 ha during 1980. The number and area under these lakes increases afterward and reached up to 783 having 955.6 ha area in 2017. There were 253 glacial lakes with total area of 414 ha during 1990, 370 with total area of 654.4 ha for 2000, 588 with total area of 717.6 ha for 2010. It was observed that some of the lakes were appeared and some disappeared during the study period however, appearance was prominent in higher elevation ranges (4000–5500 m) making it potentially vulnerable altitude zone for GLOFs. The study provided base for further monitoring of the lake dynamics and recognize possible GLOF prone areas which is valuable information for the policy makers involved in the social engineering of hill habitants and researchers across the globe.

Greater NOIDA evolved from 1991 with 101 villages to 2020 with 293 villages. This is an ideal case of rural to urban transformation in the immediate past. This transformation led to a decrease in recharging natural surfaces and an increase in impermeable surfaces. Along with the reduction in recharge areas, an increase in population has necessitated more and more extraction of groundwater resulting in an imbalance of water extraction and recharge. The result is depletion of groundwater levels in this area. The area is part of the wide Indo-Gangetic alluvium with sand, silt and clay layers resting on quartzite’s of Delhi Super Group. Geomorphological map prepared using digital elevation models of the area shows older and younger alluvial plains and active flood plains of the river Hindan. Time series analysis of key land use land cover classes shows that recharge areas were reduced from 77 % to 30 % from 2005 to 2019 and impervious surfaces have increased from 19 % to 65 % for the same period. Aquifers of the area are both phreatic and semi-confined. The aquifer parameters estimated through step drawdown test and long duration aquifer performance test indicates that the average coefficient of transmissivity of the area is 1752 m2/day and the average coefficient of storage is 4.84 x 10-4. Discharge of the wells shows a yield of 8 to 16 lps for a drawdown of 3 to 6 m. An attempt has been made to know the behaviour of groundwater levels during the same period as that of land use land cover. The results indicate a 74 % depletion in groundwater levels with an average annual depletion of 21 %. An interrelationship between urban growth and groundwater levels has been established in this study. This analysis indicates that as agriculture declined water levels also depleted and have a positive correlation of 0.852. On the contrary, as the built-up increased water level has depleted hence have a negative relationship with a correlation coefficient of -0.851. To make it a sustainable resource, these overexploited aquifers need careful participatory management by communities, Scientists, and policymakers.

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