Integration of soil moisture remote sensing and hydrologic modeling using data assimilation

TLDR

The study explores the feasibility of generating distributed soil‑moisture fields by applying four‑dimensional data assimilation within a hydrological model. The authors assimilated six 160‑km² PBMR images into the TOPLATS land‑atmosphere model, adapting conventional data‑assimilation techniques to high‑density microwave observations and incorporating surface‑subsurface moisture correlations. The PBMR images show horizontal correlations over tens of kilometers, and Newtonian nudging assimilation best preserves observed patterns while extrapolating plausible soil‑moisture fields into unmeasured regions and time.

Abstract

The feasibility of synthesizing distributed fields of soil moisture by the novel application of four‐dimensional data assimilation (4DDA) applied in a hydrological model is explored. Six 160‐km 2 push broom microwave radiometer (PBMR) images gathered over the Walnut Gulch experimental watershed in southeast Arizona were assimilated into the Topmodel‐based Land‐Atmosphere Transfer Scheme (TOPLATS) using several alternative assimilation procedures. Modification of traditional assimilation methods was required to use these high‐density PBMR observations. The images were found to contain horizontal correlations that imply length scales of several tens of kilometers, thus allowing information to be advected beyond the area of the image. Information on surface soil moisture also was assimilated into the subsurface using knowledge of the surface‐ subsurface correlation. Newtonian nudging assimilation procedures are preferable to other techniques because they nearly preserve the observed patterns within the sampled region but also yield plausible patterns in unmeasured regions and allow information to be advected in time.