Earth Observation satellites combined with in situ data for modelling the environmental and anthropogenic water stressors in Chennai, India

Water security is a growing global concern. Depending on the geographical location, a complex set of stressors pose an imbalance in the water utilization and distribution mechanisms. Studies suggest that the global water crisis is driven not only by climate change, but also by population, economic growth, and poor water management. Surface and ground water models using space-based or ground-based data continue to emerge. Also, traditional strategies with manual-based approaches based on field surveying with limited measuring equipment have been adopted to assess water body surface area and depth, hence volume. However, these methods are labour intensive and costly, and as currently delinked, do not provide synoptic views of the overall condition. Here, we show that the earth observation satellite data, in combination with in situ observatories, can offer vital spatiotemporal information about the environmental and anthropogenic water stressors in the metropolitan city of Chennai, India. Using the Normalized Difference Water Index (NDWI) derived from Sentinel-2A/B satellites from historical datasets since 2015 at a spatial resolution of 10 m, combined with in situ data from Chennai Metropolitan Water Supply and Sewerage Board (CMWSSB), revealing the spatiotemporal surface water reservoirs and their heterogeneous distribution. Simultaneously, environmental contributions were modelled with spatiotemporal rainfall data derived from Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) satellites respectively, in combination with Indian Meteorological Department (IMD) and CMWSSB data, and soil moisture and evapotranspiration data from the India Water Resources Information System (WRIS). Finally, anthropogenic factors were also considered in terms of population growth due to rapid urbanisation with the Census and water consumption from CMWSSB data. This work gives the first evidence of utilising both space-based data and ground-based data to create a hybrid hydrologic model. The results present the near-real time water capacity of Chennai to meet its ever-increasing needs. Therefore, the synoptic observations demonstrated by this unified approach outweighs the lack of critical considerations in individual fragmented models and allow the environmental and water boards to evaluate changes in the water stress conditions in near real-time and facilitate plausible strategies to address them on time. This approach may help getting closer to ensuring availability and sustainable management of water as per the United Nations' Sustainable Development Goal (SDG) 6.