ESTIMATION OF SOIL MOISTURE WITH API ALGORITHMS AND MICROWAVE EMISSION¹

Abstract

Large area soil moisture estimations are required to describe input to cloud prediction models, rainfall distribution models, and global crop yield models. Satellite mounted microwave sensor systems that as yet can only detect moisture at the surface have been suggested as a means of acquiring large area estimates. Relations previously discovered between microwave emission at the 1.55 cm wavelength and surface moisture as represented by an antecedent precipitation index were used to provide a pseudo infiltration estimation. Infiltration estimates based on surface wetness on a daily basis were then used to calculate the soil moisture in the surface 0–23 cm of the soil by use of a modified antecedent precipitation index. Reasonably good results were obtained (R2= 0.7162) when predicted soil moisture for the surface 23 cm was compared to measured moisture. Where the technique was modified to use only an estimate of surface moisture each three days an R2 value of 0.7116 resulted for the same data set. Correlations between predicted and actual soil moisture fall off rapidly for repeat observations more than three days apart. The algorithms developed in this study may be used over relatively flat agricultural lands to provide improved estimates of soil moisture to a depth greater than the depth of penetration for the sensor.

Rainfall thresholds for flood triggering. The case of Marathonas in Greece

“…Subsequently, antecedent precipitation index (API), which has been used in the past as moisture content indicator (Blanchard et al 1981), was calculated at the beginning of every storm using Kohler and Linsley (1951) equation:…”

What made the June 2013 flood in Germany an exceptional event? A hydro-meteorological evaluation

“…We use the antecedent precipitation index (API) according to Köhler and Linsley (1951) as a proxy for the wetness conditions in a catchment in the period before the event precipitation. The relation between surface soil moisture content and different versions of the API was shown, for instance by Blanchard et al (1981) or Teng et al (1993). We quantify API over a 30-day period prior to the meteorological event start dates at each grid point for each event of the largescale flood set.…”

Passive Microwave Remote Sensing of Soil Moisture

“…There are some applications that can use this type of measurement directly, although most uses require an estimate to a depth of 1 or 2 m. Research by Blanchard et al (1981) using correlation methods and Jackson (1980) using theoretical models have shown that surface measurements can be extrapolated to estimate profile moisture. There are some applications that can use this type of measurement directly, although most uses require an estimate to a depth of 1 or 2 m. Research by Blanchard et al (1981) using correlation methods and Jackson (1980) using theoretical models have shown that surface measurements can be extrapolated to estimate profile moisture.…”

“…Other theories propose that scattering and absorption are also significant. Brunfeldt and Ulaby (1983) have developed a complete procedure for estimating both parameters, albedo and loss, by using a few mobile-tower measurements. Ulaby et al (1983), using an approach similar to that presented by Mo et al (1982), developed a model that utilizes two parameters, the single scattering albedo and a canopy loss factor.…”