About this Research Topic
In recent decades, the remote sensing community has strived to develop new theories, methods, algorithms, equipment, data, products, and applications in hydrology. For example, remote sensing has become an irreplaceable approach for global precipitation monitoring, remote sensing-based snow cover products have been key evidence for global climate change studies, and multi/hyperspectral and microwave remote sensing are playing critical roles for soil moisture and evapotranspiration estimation. Meanwhile, the integration of satellite remote sensing, UAV, and hydrological sensor web has provided a huge amount of data. This data treasure has been deepening our understanding of hydrological states and extreme events.
As the rapid development of remote sensing has shown great potential in the hydrology domain, it is critical to review and inspect the latest achievements in hydrology. How does remote sensing play a role in advancing the scientific understanding of hydrological states, phenomena, and processes? How can we synergize data sets from different sources (e.g., water sensor networks and remote sensing)? New theories, methods, and applications in hydrology are still needed to deal with these data challenges. For example, it is still difficult to leverage the diverse capabilities of remote sensing sensors to accurately measure hydrological states. Further, the fusion of remote sensing big data with hydrological/physical models is still unknown. Meanwhile, the devastative droughts and floods at a global scale pose great risks and concerns that can be evaluated by remote sensing techniques.
In this Research Topic, we anticipate unique studies on hydrology and extremes, including new methods for retrieving hydrological variables through remote sensing platforms and sensors, the spatiotemporal process of Extreme Hydrological Events (EHEs) revealed by remote sensing data, multi-sensor data fusion models for generating high-quality hydrological data (i.e., High resolution, High spatiotemporal continuity, and High accuracy), as well as scientific findings/software/services driven by various multi-/hyper-spectral remote sensing data and information. Manuscripts on reviews, theoretical research, case study, and policy relevant to this topic are all welcome.
1) Remote Sensing in Hydrological Variables
• precipitation;
• surface water hydrology:
• soil moisture:
• snow;
• groundwater hydrology;
• water quality;
• evapotranspiration;
• irrigation.
2) Remote Sensing in Hydrological Extremes
• drought;
• flood.
3) Data-model fusions
• The fusion and integration of remote sensing with hydrological models for process-based understanding;
• Hydrology-informed artificial intelligence driven by remote sensing big data, water sensor networks, etc.
4) Emerging applications
• Applications of small satellites or CubeSats in hydrology;
• New platforms, data, and algorithms in water resources;
• Large-scale mapping of water extent over land surfaces.
Keywords: Soil Moisture, Drought, Flood, Water, Fusion, Runoff, Glacier, evapotranspiration, Snow, Sensor Web
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.