Proceedings of the 2022 Mississippi Water Resources Conference

Year: 2022 Authors: Boyd D.R., Kurum M.

A longstanding research focus within hydrology is the remote sensing of soil moisture across the entire depth of the vadose zone at sufficient spatial and temporal resolutions to address human needs for crop growth, water management, drought prediction, and many other research areas. While many forms of remote sensing can provide insight into vegetation health and surface water availability, microwave remote sensing is perhaps the most mature method for detecting water content within Earth land structure's due to its penetrative capabilities. While active microwave remote sensing is capable of performing such remote sensing measurements at desirable resolutions, such systems cannot be easily proposed due to the cost of building such a network in addition to the competing frequency space between commercial and public ventures.

The signals of opportunity (SoOp) method is a form of radio spectrum recycling that allows for the reuse of active microwave signals from systems designed for navigation and communication to science application systems. The SoOp method allows for high spatiotemporal resolution microwave measurements while maintaining a low size, weight, power, and cost for individual receiver systems. Such systems have shown success in recent years for estimating surface soil moisture in recent years through machine learning, and future SoOp missions and experiments dedicated for surface and root-zone soil moisture are expected. The development of models which are capable of recreating these bistatic scenarios over land structures is an area of ongoing research within the remote sensing community.

This research showcases the development of a vadose-zone-capable model for estimating changes in soil moisture by means of a generalized, SoOp modeling suite developed at Mississippi State University. This model is an upgraded variant of the SoOp Coherent Bistatic scattering model (SCoBi) which allows for simulation of bistatic scattering within multilayered soil moisture profiles and vegetation structures across land surfaces. Added features to the model will enable the simulation of varying land structures across Earth structures with sensitivity to features such as topography, land cover classification, and surface roughness. This model is anticipated to help explore the sensitivity of multifrequency SoOp systems to variations in soil moisture profiles over multiple land surfaces. Sample simulations will be presented at the conference.