Remote Sensing and GIS for hydrological modeling
Usage of remote sensing and GIS for hydrological modeling is increasing. Remotely sensed data (aerial photography and satellite imagery) provide spatial information about the processes of the land phase of the hydrological cycle. The land cover maps derived by remote sensing are the basis of hydrologic response units for modeling units. For an understanding of the hydrology of areas with little available data, a better insight into the distribution of the physical characteristics of the catchments is provided by image processing techniques. Some of the new measurement methods (photographic systems, active radar systems etc.) could yield assessment of areal distribution or at least to some extent reliable areal totals or averages of hydrologic variable such as precipitation, evapotranspiration and soil moisture.
Original remote sensing imagery can be directly use to identify hydrologically important spatial phenomena and processed remote sensing data can be used as forcings of hydrological models. Further, using multispectral data, such as vegetation (land cover) types and density are most useful to quantify surface parameters. Direct calculation of evapotranspiration distribution in terms of spectral data of satellite remote sensing based on surface energy balance is a new invention in the modeling world. Some remote sensing derived fields, such as soil moisture, use to improve the model simulations through data assimilations. Remotely sensed data can, at least, improve model simulations by Providing more accurate spatially distributed model parameters such as vegetation information over a study region, land cover, LAI, NDVI, Albedo etc and also Helps to identify potential model structure weaknesses through validation, data assimilation, etc.
More to come
Usage of remote sensing and GIS for hydrological modeling is increasing. Remotely sensed data (aerial photography and satellite imagery) provide spatial information about the processes of the land phase of the hydrological cycle. The land cover maps derived by remote sensing are the basis of hydrologic response units for modeling units. For an understanding of the hydrology of areas with little available data, a better insight into the distribution of the physical characteristics of the catchments is provided by image processing techniques. Some of the new measurement methods (photographic systems, active radar systems etc.) could yield assessment of areal distribution or at least to some extent reliable areal totals or averages of hydrologic variable such as precipitation, evapotranspiration and soil moisture.
Original remote sensing imagery can be directly use to identify hydrologically important spatial phenomena and processed remote sensing data can be used as forcings of hydrological models. Further, using multispectral data, such as vegetation (land cover) types and density are most useful to quantify surface parameters. Direct calculation of evapotranspiration distribution in terms of spectral data of satellite remote sensing based on surface energy balance is a new invention in the modeling world. Some remote sensing derived fields, such as soil moisture, use to improve the model simulations through data assimilations. Remotely sensed data can, at least, improve model simulations by Providing more accurate spatially distributed model parameters such as vegetation information over a study region, land cover, LAI, NDVI, Albedo etc and also Helps to identify potential model structure weaknesses through validation, data assimilation, etc.
More to come
No comments:
Post a Comment