Special Issue "Hydrological Remote Sensing"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (31 August 2013)
Prof. Dr. Okke Batelaan
School of the Environment, Flinders University, GPO Box 2100, Adelaide SA 5001, Australia
Website | E-Mail
Interests: shallow groundwater hydrology; groundwater recharge-discharge estimation; ecohydrology; GIS/RS based distributed rainfall-runoff modelling; groundwater-surface water interaction; hydrological remote sensing
This special issue on ‘Hydrological Remote Sensing’ aims to follow-up on the promise that remote sensing offers to the hydrological sciences. Previous reviews and special issues on hydrological remote sensing tried often to demonstrate the potential of remote sensing for improved hydrological characterization or modelling. In the last decade there has been a strong increase in the availability of both satellite and airborne sensors from low to high spatial-temporal-spectral resolutions, some of them designed specifically for hydrological purposes. Alongside the increased availability of sensors there are now many remote sensing derived data sets publicly available, ready for use in hydrology. Also the development of non-optical sensors like e.g. gravity, LiDAR and micro-wave allows unprecedented new opportunities. Did the hydrological community now embrace and use therefore remote sensing to its full potential?
In this special issue of Remote Sensing we aim to present the state-of-the-art in combining remote sensing and hydrological research. Reviews, recent advances, future trends and case studies of general interest in the use of remote sensing for precipitation estimation, surface water hydrology, soil moisture, snow monitoring, groundwater hydrology, water quality and evapotranspiration estimation are welcome. We are also interested in how remote sensing can improve spatial-temporal input data, calibration and validation of hydrological modelling. Possible questions of interest are: Does our hydrological prediction become better; does remote sensing reduce the uncertainty? Do we increase our process understanding due to integration of remote sensing data? Are our operational and management tools improved due to remote sensing?
Professor Dr. Okke Batelaan
• surface water hydrology
• soil moisture
• groundwater hydrology
• water quality
• integration in hydrological modelling