Water sustainability is becoming a key concern worldwide due to hydrological uncertainty, climate change, landuse landcover changes, and growing water pollution. Degradation of water quality due to natural and anthropogenic activities poses significant threat to freshwater availability. Space-time modelling of water quality depends on the availability of long-term reliable datasets, which are often found to be incomplete, sparse, or unavailable. Water quality, though monitored frequently, limited knowledge is available about emerging contaminants. Subsurface environments, which are highly heterogeneous, influence flow and transport dynamics and surface-subsurface interaction mechanisms, making model calibration quite challenging. These drivers greatly influence catchment hydrology, hydrodynamics, biogeochemical processes and ecosystem. In dynamic environments, solute transport, sediment dynamics, and vegetation are also coupled through hydrodynamic and biogeochemical feedback for improved understanding of processes, nutrient cycling and ecosystem functioning.
These aspects draw paramount significance in catchments with large heterogeneity and spatial complexities such as mountainous and urban catchments, data scare regions, and low-income countries where investment in hydrological and water quality monitoring networks and installation of IoT sensors is very limited. It is therefore warranted to leverage geospatial, machine learning, decision science, statistical and modelling techniques to improve the understanding of catchment hydrology and consequences of climate change and anthropogenic drivers on surface and groundwater resources at various scales. The worldwide readily available satellite remote sensing data and global data products enable us to leverage these techniques in addressing water and environmental challenges.
We solicit novel contributions from researchers in catchment hydrology by utilizing Remote Sensing, GIS, Artificial Intelligence (AI), Machine Learning (ML), Decision Science, and advanced statistical techniques for addressing pressing challenges of water sustainability in mountainous and urban catchments and data scarce regions. The combined use of these technologies will revolutionize understanding of complicated hydrological, hydrodynamic and biogeochemical processes, and will be useful in evolving effective water resource management and ecosystem-based adaptation strategies to foster sustainable development.