2017
DOI: 10.5194/hess-2017-292
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Depth scaling of soil moisture content from surface to profile: multistation testing of observation operators

Abstract: Abstract. The accurate assessment of profile soil moisture for spatial domains is usually difficult due to the associated costs, strong spatial-temporal variability, and nonlinear relationship between surface and profile moisture. Here we attempted to use observation operators built by Cumulative Distribution Frequency (CDF) matching method to directly predict profile soil moisture from surface measurements based on multi-station in situ observations from the Soil and Climate Analysis Network (SCAN). We first … Show more

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Cited by 5 publications
(6 citation statements)
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References 32 publications
(57 reference statements)
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“…Volumetric SWC was typically measured at several depths at each site-except at CH-AWS where measurements were available from one depth only. For the forest sites, we calculated the depth-weighted average SWC using data from each layer and depth of the layer, following the method of Gao et al [45]:…”
Section: (C) Atmospheric and Soil Drynessmentioning
confidence: 99%
“…Volumetric SWC was typically measured at several depths at each site-except at CH-AWS where measurements were available from one depth only. For the forest sites, we calculated the depth-weighted average SWC using data from each layer and depth of the layer, following the method of Gao et al [45]:…”
Section: (C) Atmospheric and Soil Drynessmentioning
confidence: 99%
“…Soil moisture is an important variable which affects infiltration, runoff, soil temperature and the amount of water available to plants. According to Gao et al (2017), these variables are affected by BT due to the increase of high-density woody plant roots. Since soil moisture has a strong spatial-temporal variability and is affected by the soil type, moisture readings commenced at the end of 2019 rainy season (Gao et al 2017).…”
Section: Soil Surveysmentioning
confidence: 99%
“…According to Gao et al (2017), these variables are affected by BT due to the increase of high-density woody plant roots. Since soil moisture has a strong spatial-temporal variability and is affected by the soil type, moisture readings commenced at the end of 2019 rainy season (Gao et al 2017). A neutron probe was used to measure soil water content at different depths at the three study sites (Manthe, Shongoane and D'Nyala NR) (Chanasyk & Naeth 1996;Reichardt 2007).…”
Section: Soil Surveysmentioning
confidence: 99%
“…The RZSM can be estimated from SSM by using filtering techniques [28] and analytical models [24,29]. Furthermore, Cumulative Distribution Function (CDF) matching could be used to derive RZSM with the depth scaling method [30].…”
Section: Introductionmentioning
confidence: 99%
“…The scaling parameters of the fifth-order polynomial fitting function were generated from the SSM and the differences between the corresponding values of ranked SSM and RZSM. Gao et al [30] identified the fifth-order polynomial as the optimal choice based on a pre-analysis to define the fitting function for depth scaling. The scaling parameters were used to estimate the predicted difference between SSM and RZSM over the Product Period; then, the predicted RZSM were generated while using blended SSM and the predicted differences.…”
mentioning
confidence: 99%