Use of Remote Sensing for Parameterisation of Hydrological Models

With the advancement of earth observing satellites, remote sensing has become an important tool in monitoring and managing natural resources. Substantial research has been carried out in the field of hydrology to obtain wide range of information from remote sensing data. In particular, use of remote sensing data in estimating evapotranspiration, snow cover mapping, and flood-plain mapping, monitoring of sediment and water pollution and estimating soil moisture have been topics of intense interest during the past three decades. In the present paper, various remote sensing approaches to extract information for hydrological modelling are examined. Discussions are focused on the remote sensing data, land use and land cover (LULC) classification techniques and retrieval of leaf area index and surface albedo. The literature review suggested that major approaches during the past decade include LULC classification using traditional pixel based approaches for hydrological modelling. In addition to this, there has been a lag between the development of techniques of land surface parameter determination from remote sensing and application of these techniques in hydrological modelling.