Advances in Hydrological Remote Sensing

With advances in remote sensing, the data available for hydrological simulation and monitoring has grown richer and more diverse, supporting hydrological studies at point, hillslope and watershed scales. Modern hydrology focuses on large-scale water cycles and couplings between the hydrosphere and other spheres. Multispectral and high-resolution remote sensing data combined with in situ monitoring data form hydrological big data, bringing new challenges to data processing and water cycle research, as well as new opportunities to develop hydrological theories and methods. This Reprint collects recent advances in hydrological process identification, hydrological big data analysis and hydrological simulation. Relevant contributions include, but are not limited to, remote sensing-based hydrological process identification, dynamic water resources monitoring, remote sensing-based water environment monitoring, hydrological big data analysis, and big-data-driven hydrological process simulation.