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ARS Home » Pacific West Area » Riverside, California » U.S. Salinity Laboratory » Water Reuse and Remediation Research » Research » Publications at this Location » Publication #307780

Research Project: Integrated Field Scale Management Systems for the Use of Degraded Waters

Location: Water Reuse and Remediation Research

Title: Regional scale soil salinity evaluation using Landsat 7, western San Joaquin Valley, California, USA

Author
item Scudiero, Elia - University Of California
item Skaggs, Todd
item Corwin, Dennis

Submitted to: Geoderma Regional
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/21/2014
Publication Date: 10/24/2014
Citation: Scudiero, E., Skaggs, T.H., Corwin, D.L. 2014. Regional scale soil salinity evaluation using Landsat 7, western San Joaquin Valley, California, USA. Geoderma Regional. 2:82-90. doi: 10.1016/j.geodrs.2014.10.004.

Interpretive Summary: Soil salinization diminishes the productivity of irrigated farmlands throughout the world. However, no reliable inventory of soil salinity exists at regional scale anywhere in the world due to the spatial complexity and temporally dynamic nature of salinity. Satellite imagery has the greatest potential for inventorying and monitoring salinity at large spatial extents. This work explores the potential of mapping soil salinity using canopy reflectance measured by the Landsat 7 satellite (spatial resolution 30 × 30 m). In particular canopy reflectance can be used to measure plant health. The rationale behind this study is that multi-year reflectance data would help highlight landscape features stable in time (i.e., 5-10 years) over those less stable in time (caused by pests, water stress occurring on single dry years, etc). Seven years (2007-2013) of Landsat 7 data were analyzed for the west side of California’s San Joaquin Valley (ca.1.5 × 10**6 ha). The use of multi-year canopy reflectance helped locate soil salinity. The strength of the salinity-crop reflectance relationships varied throughout the years due to changing meteorological conditions, and across the fields according to changing soil type. The results suggest that integrating L7 multi-year reflectance data with information on meteorological conditions, crop type, and soil texture could lead to a reliable salinity prediction model for the entire western San Joaquin Valley, and could be possibly used in other regions of the U.S.A. where salinity affects crop yield. Land resource managers, producers, agriculture consultants, extension specialists, and Natural Resource Conservation Service field staff are the beneficiaries of regional-scale maps of soil salinity.

Technical Abstract: Despite decades of research in soil mapping, characterizing the spatial variability of soil salinity across large regions remains a crucial challenge. This work explores the potential use of Landsat 7 (L7) satellite reflectance data to facilitate salinity mapping. Reflectance data spanning a seven-year period were obtained for western San Joaquin Valley, California (ca.1.5 × 10**6 ha). Data for the six spectral bands of the L7 sensor (30 × 30 m resolution), as well as several vegetation indices, were analyzed in relation to two soil salinity ground-truth datasets differing in spatial resolution. Multi-year averages of the L7 data and vegetation indices were generally better correlated with soil salinity (up to R**2=0.43) than were individual-year data and indices. The strength of the correlations between L7 data and soil salinity varied with changing meteorological conditions throughout the seven-year period, and also according to soil properties on a field-by-field basis. The results suggest that a fusion of the L7 multi-year reflectance data with information on meteorological conditions, crop type, and soil texture could lead to a reliable salinity prediction model for the entire western San Joaquin Valley. Land resource managers, producers, agriculture consultants, extension specialists, and Natural Resource Conservation Service field staff are the beneficiaries of regional-scale maps of soil salinity.