Stillwater, Oklahoma

metadata

Station Name: okl2

Location: Oklahoma, USA

Archive: UNAVCO

Ellipsoidal Coordinates:

  • Latitude: 36.063492 degrees

  • Longitude: -97.216964 degrees

  • Height: 328 meters

This use case demonstrates the advanced vegetation model (model 2) for soil moisture estimation at a well-studied site in Oklahoma with significant vegetation effects.

Background

Station okl2 was analyzed as part of the original PBO H2O network and has been used extensively for validating GNSS-IR soil moisture algorithms. The site experiences significant seasonal vegetation that requires correction to obtain accurate soil moisture estimates.

Step 1: GNSS-IR

Begin by generating the SNR files using the special archive for L2C data:

rinex2snr okl2 2012 1 -doy_end 366 -rate high -dec 15 -par 10

We must use -rate high to locate the correct file, and I optionally add -dec 15 for smaller file sizes and -par 10 for parallel downloads.

Now set up the analysis strategy:

gnssir_input okl2 -fr 20

Run gnssir to estimate reflector heights:

gnssir okl2 2012 1 -doy_end 366 -par 10

Step 2: Soil Moisture with Simple Model (Model 1)

First, let’s run the standard simple vegetation model for comparison.

Pick the satellite tracks:

vwc_input okl2 2012

Estimate phase for each satellite track:

phase okl2 2012 1 -doy_end 366 -par 10

Convert phase to volumetric water content using the simple model (default):

vwc okl2 2012

This produces the standard VWC output using model 1 (simple vegetation correction). Copy the file so it is not overwritten by the next step: $REFL_CODE/Files/okl2/okl2_vwc_L2_24hr+0.txt

Step 3: Soil Moisture with Advanced Model (Model 2)

Now run the advanced vegetation model:

vwc okl2 2012 -vegetation_model 2

The advanced model applies Clara Chew’s track-level KNN correction algorithm as described in DOI 10.1007/s10291-015-0462-4.

We can plot the results of each method to compare them:

../_images/okl2_model_comparison.png

Key Ideas

Model 1 (Simple):

  • First aggregate measurements into daily (or subdaily) bins

  • Then take the average phase of every measurement in the bin

  • Finally, convert that averaged phase value to VWC by a fixed scalar (1.48)

Model 2 (Advanced):

  • This model determines track-by-track corrections at the phase level, prior to VWC conversion.

  • The phase -> VWC conversion scaler is also variable (this is the “slope correction”)

  • Both the phase and slope corrections are found from a lookup table (created by Clara Chew)

  • The corrections are determined based on a smoothed value of (1) amplitude of interference pattern, (2) amplitude of LSP peaks, and (3) effective RH.

    • Each of these inputs will change throughout the year as vegetation structure and density changes

Saving Individual Track Data

To save detailed track-level data for further analysis:

vwc okl2 2012 -vegetation_model 2 -save_tracks T

Individual track files are saved to:

$REFL_CODE/Files/okl2/individual_tracks/