A genetic programming model assimilates SAR images and geoenvironmental parameters to assess soil moisture at the watershed scale.

A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-apertureradar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a smallscale area, but it is impossible to acquire such information effectively in largescale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.