SMEX02: Field scale variability, time stability and similarity of soil moisture

Jennifer M. Jacobs, Binayak P. Mohanty, En Ching Hsu, Douglas Miller

Research output: Contribution to journalArticle

256 Scopus citations

Abstract

Evaluation of air- or space-borne remote sensors measuring soil moisture requires strategic ground-based sampling. As part of the Soil Moisture Experiment 2002 (SMEX02), daily surface soil moisture sampling at 90-140 locations were conducted in four fields in Walnut Creek watershed, Iowa. Various combinations of soils, vegetation, and topography characterize the fields. Depending on the field's characteristics and soil moisture content, 3-32 independent measurements were necessary to capture the field mean volumetric soil moisture with a ±2% bias and 95% confidence interval. Validation of the retrieved soil moisture products from the aircraft microwave instruments using the average of 14 samples per field is more appropriate for dry (<10% volumetric soil moisture) or wet (>25% volumetric soil moisture) range than for intermediate soil moisture range. Time stability analysis showed that an appropriately selected single sampling point could provide similar accuracy across a range of soil moisture conditions. Analyses based on landscape position (depression, hilltop, steep slope, and mild slope) showed that locations with mild slopes consistently exhibit time stable features. Hilltop and steep slope locations consistently underestimated mean field soil moisture. Soils parameters could not be used to identify time stable features as sampling locations with relatively high sand content consistently underestimated the field mean while those locations with relatively high clay content consistently overestimated the field mean. However, the slope position characterization of time stable features was enhanced using soils properties. The mild slope locations having the best time-stable features are those with moderate to moderately high clay content as compare to the field average (28-30% clay).

Original languageEnglish (US)
Pages (from-to)436-446
Number of pages11
JournalRemote Sensing of Environment
Volume92
Issue number4
DOIs
StatePublished - Sep 30 2004

All Science Journal Classification (ASJC) codes

  • Soil Science
  • Geology
  • Computers in Earth Sciences

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