4.7 Article

Factors Controlling a Synthetic Aperture Radar (SAR) Derived Root-Zone Soil Moisture Product over The Seward Peninsula of Alaska

Journal

REMOTE SENSING
Volume 14, Issue 19, Pages -

Publisher

MDPI
DOI: 10.3390/rs14194927

Keywords

soil moisture; permafrost root-zone; synthetic aperture radar; random forest; Arctic

Funding

  1. Department of Energy Office of Science, Office of Biological and Environmental Research through the Next Generation Ecosystem Experiment (NGEE) Arctic project
  2. U.S. Geological Survey's Alaska Climate Adaptation Science Center [G17AC00213]

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This study analyzed the factors controlling summer root-zone soil moisture in a 4500 km(2) area on the Seward Peninsula of Alaska, showing that vegetation primarily controls soil moisture in shallow soil layers, while topography and meteorological factors play a larger role in deeper layers. The random forest model developed accounted for 40% to 60% of the observed variation, indicating the importance of secondary factors in influencing root-zone soil moisture distribution.
Root-zone soil moisture exerts a fundamental control on vegetation, energy balance, and the carbon cycle in Arctic ecosystems, but it is still not well understood in vast, remote, and understudied regions of discontinuous permafrost. The root-zone soil moisture product (30 m resolution) used in this analysis was retrieved from a time-series P-Band (420-440 MHz) synthetic aperture radar (SAR) backscatter observations (August 2017 & October 2017). While similar approaches have been taken to retrieve surface (0 cm to 5 cm) soil moisture from L-Band (1.2 GHz) SAR backscatter, this is one of the first known attempts at reaching the root-zone in permafrost regions. Here, we analyze secondary factors (excluding primary factors, such as precipitation) controlling summer (August) soil moisture at depths of 6 cm, 12 cm, and 20 cm over a 4500 km(2) area on the Seward Peninsula of Alaska. Using a random forest model, we quantify the impact of topography, vegetation, and meteorological factors on soil moisture distributions. In developing the random forest model, we explore a variety of feature scales (30 m, 60 m, 90 m, 120 m, 180 m, and 240 m), tune hyperparameters (the structure of individual decision trees making up the ensemble including the number and depth of trees), and perform the final feature selection using cross-validated recursive feature elimination. Results suggest that root-zone soil moisture on the Seward Peninsula is primarily controlled by vegetation at 6 cm, but deeper in the soil column topography and meteorological factors, such as predominant winter wind direction and summer insolation, play a larger role. The random forest model accounts for 40% to 60% of the variation observed (R-2 = 0.44 at 6 cm, R-2 = 0.52 at 12 cm, R-2 = 0.58 at 20 cm). These results indicate that vegetation is the dominant control on soil moisture shallow in the soil column, but the impact of vegetation does not extend to deeper layers retrieved from P-Band SAR backscatter.

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