Intercomparisons between passive and active microwave remote sensing, and hydrological modeling for soil moisture

Abstract

Soil moisture estimates from a distributed hydrological model and two microwave remote sensors (Push Broom Microwave Radiometer and Synthetic Aperture Radar) were compared with the ground measurements collected during the MAC-HYDRO'90 experiment over a 7.4-km 2 watershed in central Pennsylvania. Various information, including rainfall, soil properties, land cover, topography and remote sensing imagery, were integrated and analyzed using an image integration technique. It is found that the hydrological model and both microwave sensors successfully pick up the temporal variation of soil moisture. Results also indicate the spatial soil moisture pattern can be remotely sensed within reasonable accuracy using existing algorithms. Watershed averaged soil moisture estimates from the hydrological model are wetter than remotely sensed data. It is difficult to conclude which instrument yield better performance for the studied case. The choice will be based on the intended applications and information that is available.

Non-parametric Methods for Soil Moisture Retrieval from Satellite Remote Sensing Data

“…Many researchers have used a linear regression model to simplify complex relationship between radar backscatter and soil moisture from a limited number of sample points [17,[19][20][21][22][23][24][25][26][27][28][29]. These studies have shown that surface backscatter cannot be considered as a only source to retrieve soil moisture for vegetated soil surface.…”

Effects of initialization on response of a fully-distributed hydrologic model

“…Similarly, Troch et al (1993) presented a physically meaningful technique to determine the effective depth to water table as a measure of the initial storage of a basin based on a simplified groundwater model and streamflow observations. In an interesting application of remote sensing, Famiglietti and Wood (1991), Wood et al (1993) and Famiglietti et al (1999) inferred the initial depth to water table prior to a storm event from surface soil moisture by assuming hydraulic equilibrium in the unsaturated zone. Salvucci (1993) and Salvucci and Entekhabi (1994) also obtained a relation between the depth to the water table and soil water content by assuming hydrostatic equilibrium for the vertical distribution of the pressure head, corresponding to zero initial flux in the unsaturated zone.…”

Utilizing calibrated GPS reflected signals to estimate soil reflectivity and dielectric constant: Results from SMEX02

“…The importance of an accurate widespread soil moisture measurement is well recognized within the scientific community [see for instance O'Neil et al, 1993;Wood et al, 1993;Jackson and Schmugge, 1992;Kostov et al, 1991;Jackson and O'Neil, 1988;Njoku and Kong, 1977]. However, the monitoring of large area surface water resources is generally impractical via in situ observations because of the large number of sites required and the high cost of monitoring equipment.…”