Title :
Using a modeling approach to predict soil hydraulic properties from passive microwave measurements
Author :
Burke, E.J. ; Gurney, R.J. ; Simmonds, L.P. ; Neill, P. E O
Author_Institution :
Environ. Syst. Sci. Centre, Reading Univ., UK
fDate :
3/1/1998 12:00:00 AM
Abstract :
A soil water and energy budget model coupled with a microwave emission model (MICRO-SWEAT) was used to predict the diurnal courses of soil surface water content and microwave brightness temperatures during a number of drying cycles on soils of contrasting texture that were either cropped or bare. The parameters describing the soil water retention and conductivity characteristics [saturated hydraulic conductivity, air entry potential, bulk density, and the exponent (b) describing the slope of the water release curve] had a strong influence on the modeled bare-soil microwave brightness temperatures. These parameters were varied until the error between the remotely sensed and modeled brightness temperatures was minimized, leading to their predicted values. These predictions agreed with the measured values to within the experimental error. The modeled brightness temperature for a soybean-covered soil was sensitive to some of the vegetation parameters (particularly to the optical depth), in addition to the soil hydraulic properties. Preliminary findings suggest that, given an independent estimate of the vegetation parameters, it may still be possible to estimate the soil hydraulic properties under a moderate vegetation canopy
Keywords :
hydrological techniques; moisture measurement; radiometry; remote sensing; soil; MICRO-SWEAT; diurnal variation; energy budget model; hydraulic conductivity; hydraulic properties; hydrology; land surface; measurement technique; microwave brightness temperature; microwave emission model; microwave radiometry; passive microwave measurements; remote sensing; soil moisture; terrain mapping; water content; water retention; Atmospheric modeling; Brightness temperature; Land surface; Microwave measurements; Microwave radiometry; Predictive models; Soil measurements; Soil moisture; Vegetation; Water;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on