Hydrological Estimation via Reflectometry from an Overflying Navigation-signal Receiver (HERON)

HERON Logo

Objective: The objective of this graduate project course is to use a UAV-based system to (1) collect both direct and reflected Global Navigation Satellite System (GNSS) signals over the surface of inland water bodies (IWB) such as rivers, lakes, and reservoirs, and (2) to develop algorithms to process the data to retrieve IWB dimensions and surface gradient for flood, drought, and vegetation monitoring.Ìý

Background: IWB provide important ecological, environmental, hydrological, and socioeconomic services to mankind.Ìý The distribution of water and its changes over time are central to many agricultural, environmental, and ecological systems.Ìý They are also fundamental to developing theories and understanding the impacts of human activities and climate change on water resources.Ìý Global observations of IWB provide the scientific under-pinning for our comprehension of land surface hydrological processes.Ìý Yet, knowledge of changes in the volume of water stored and flowing in the rivers, lakes, and wetlands is poor.Ìý Mapping the dynamic distribution of water is crucial for scientific research and sustainable ecosystem management.Ìý

Current global surface water products are based on in situ measurements, satellite images, and satellite-based altimetry missions and they have critical drawbacks.Ìý For example, in situ measurements are limited to focused local areas, while satellite images have low temporal resolution and lack coverage during night-time, in vegetated areas, and under cloudy or rainy conditions. ÌýRecent NASA satellite active-radar altimetry missions, such as NISAR and SWOT are well-suited for addressing annual andÌý Ìý

seasonal variations of the global water cycle, but are inadequate for observing local events at daily or sub-daily time scales.ÌýLow cost, passive GNSS-based missions such as CYGNSS and Spire Global’s CubeSats can provide shorter revisit time and the GNSS signals have good cloud and vegetation penetration ability.ÌýHowever, the measurement spatial resolution is on the order of ~1km which is not adequate for small IWBs and narrow rivers.Ìý Moreover, it is challenging to have ground tracks that follow a river as the satellite orbits cannot be easily manipulated on a regular basis.Ìý Figure 1 shows the maps of small water bodies in three distinctively different regions in North America permafrost zone using GNSS reflection signals collected by Spire Global CubeSats. Figure 2 shows the track of specular reflection location (red line) of a GPS satellite signal collected by a NASA CYGNSS satellite over Orinoco River in South American.Ìý This ground track crosses the river multiple times as highlighted by the green shaded column.Ìý The bottom plot shows the surface height retrieved from the measurements.Ìý

Project/Course Requirement:

A previous Graduate Project titledÌýSURGE – Surface-water Reflectometry GNSS Experiment designed and built a UAV payload that can (1) provide UAV position solution at 10 cm accuracy, (2) capture and record baseband reflected GPS signals from IWB surface, (3) capture images of IWB and surrounding environment, (4) communicate with a base station to relay the UAV location and operational status, and (5) collect and store UAV position, reflection baseband signal data, and images of IWB during flight. This payload and UAV are available to theÌýHERON project.

TheÌýHERON project will include the following tasks:

  1. UAV data collection:
    1. Update the SURGE UAV payload using the latest receiver and antenna technology to improve the data collection system.
    2. Select appropriate areas-of-interest for data collection experiment based on GNSS satellite orbit information and target IWB geographical information.Ìý
    3. Learn to work with GNC software that will fly the UAV according to the planned flight path and record UAV position solutions.
    4. Conduct flight experiments to collect data over a period when the surface water coverage and conditions experience sufficient variations.
  2. Algorithms Development.
    1. Develop algorithms to compute specular reflection locations for given GNSS satellite orbit, UAV position, and surface topography.Ìý
    2. Develop algorithms to read the data and extract GNSS signal amplitude, carrier phase, and pseudorange information.
    3. Develop algorithms to compute surface water content indicators from the GNSS signal parameters and to map the surface water boundaries.
    4. Develop algorithms to retrieve surface water height variations.
  3. Scientific Analysis and Validation
    1. Process the collected data.
    2. Quantify errors and bias in the measurement and processing results.
    3. Analyze the processing results to study patterns of the surface water content variations
    4. Perform cross validation of the retrieved results with measurements obtained from other sources.

Advisor: Jade Morton