The research proposed within this document is to be a small part of a greater NSF funded coordinated research project involving controlled naturally seeded measured plots in a sagebrush ecosysterm typical of the Great Basin regional domain. The panoramic multi-year project incorporates studies of plant species diversity in an historic post wildfire community. Within this project - Harnessing the Data Revolution for Fire Science (https://hdrfs.epscorspo.nevada.edu/ ) was a designed set of controlled burns to collect pre-post burn data tested against analog non-burned segments. The HDRFS project consists of specific research components - Hydro, Eco, Fire Processes, Fire Emissions and Atmospheric Aging, and CyberInfrastructure Innovations. These research components stimulate cross-disciplinary groups all working on addressing scientific and technological problems related to Sagebrush ecosystem science. For further details and specifics the reader is encouraged to directly access the HDRFS site as linked above. A need for hydrological scientists to quantify detailed aspects of soil moisture variability is the focus of this proposal. The ground surface conditions are altered by the severity of the surface burn (and other states of the ground-air interface system), which in-turn alter the rate and depth of penetration of water from precipitation events. Run-off and surface infiltration have strong connections to post wildfire plant species growth and recovery, and surface geomorphologic responses such as landslide. UAS-borne L-Band radiometry can bridge the gap between point source in-ground volumetric soil moisture measurement values and those from satellite instruments with greater geospatial domain, but diminished temporal resolution. This sub-study is to make progress in technological, methodological, and scientific aspects of the need to accurately determine near surface soil moisture and the local scale geophysical variables which influence its variability. Comment: this sub-award document should be considered as peer-reviewed by a scientific community of experts who agreed to grant this sub-award on the basis of scientific merit. Project Summary: This project aims to establish new technological limits for real time measurement of spatio temporal spectral land surface characteristics such as surface soil moisture (SSM), surface reflectance, and surface emissivity. These are essential for such diverse applications as water resources management, assessing vegetation health as well as reducing wildfire and flood risks in semi-arid environments such as Nevada. We propose to implement innovative instrumentation and techniques to rapidly obtain near surface highly portable Unmanned Aerial System (UAS)-obtained measures near surface soil moisture (SSM). To achieve this, we propose three tasks related to upgrading functional electronic componentry of the microwave antenna owned by DRI’s Airborne Systems Testing and Environmental Research (ASTER) laboratory, fitting it specifically to a US-made, heavy lift Alta-X Unmanned Aircraft System (UAS), calibrating it over an open water body, preliminary testing over specific characteristic desert surface types, validating it's near surface soil moisture measurements in a semi-arid environment of known soil moisture content over diurnal and seasonal cycling, and correlating the validated SSM data with available ground and satellite data to create a downscaled data product. Initial tasks will be carried out at the ASTER lab by the PI, a DRI Reno Instrument Scientist, and a Ph.D. student. For field related tasks, the PI, Professor Berli and the Ph.D. student will work at an NSF-EPSCoR-sponsored experimental site near Reno, Nevada. Satellite correlation studies will be carried out by the PI, the student, and Professor Wilcox. This project provides a calibrated and validated tool (UAS-based PoLRa) to rapidly measure soil moisture remotely at a spatial resolution of about 1 m over an area of about 1km2. It will also provide part time support for a Ph.D. student with the potential for a chapter on L-band remote sensing for the student’s thesis. These tasks satisfy NSHE's 2020 Science and Technology Plan objectives for water resources -by creating repeatable measurement technologies using a rural sensor and data network to accurately quantify water inputs and their complex responses to variability in climate and extreme events such as fire.
Giordano et al. (Sat,) studied this question.