Extreme hydrological events often lead to catastrophes for humans and the environment. While identification, understanding, modeling, validation, and prediction of extreme hydrological events are crucial for preventing such catastrophes and eventually developing a system that is resilient to them, such tasks are challenging. In particular, it is difficult to obtain a comprehensive understanding of an extreme event and the corresponding damage that typically occurs over a spatial extent of several thousand kilometers within which spatio-temporal characteristics vary significantly.

Emerging techniques such as remote sensing and radar from multiple platforms have been actively applied to resolve these issues. Near-real-time precise and accurate observation of precipitation has become possible with the help of satisfactorily-confirmed radar, and information derived from satellites enables us to observe a variety of components of hydrological cycle at a global spatial scale.

In this special issue, we call for papers discussing how observations based on emerging techniques including remote sensing have broadened our understanding of hydrological disasters.

Potential topics include but are not limited to the following:

• Emerging techniques, methodologies, and developments to detect, forecast, or predict disasters related to extreme hydrological events such as floods and droughts
• Calibration, verification, and bias correction techniques for remotely sensed data, quantitative precipitation estimation/forecasting, and any types of weather or climate estimates dealing with extreme events
• Spatial and temporal downscaling of remotely sensed data, quantitative precipitation estimation/forecasting, and any types of weather or climate estimates in terms of extreme meteorological events
• Spatial and temporal compositions of remotely sensed and in-situ measurements in accounting for serial and spatial correlations at larger and longer spatiotemporal scales