181-15 Regional-Scale Soil Salinity Assessment Using Landsat ETM+.

See more from this Division: SSSA Division: Soil Physics and Hydrology
See more from this Session: Soil Physics and Hydrology: Honoring the Contributions of Bob Luxmoore, John Letey, and John Hanks: I

Tuesday, November 17, 2015: 11:45 AM
Minneapolis Convention Center, 101 DE

Elia Scudiero, Dennis L. Corwin and Todd H. Skaggs, USDA-ARS, Riverside, CA
Abstract:
Water for irrigation is a major limitation to agricultural production in arid zones of the world. Irrigating with low leaching fractions in arid zones leads to soil salinization, thereby causing reduction in crop yield. Throughout his career, John Letey made unprecedented strides towards efficient agricultural water use to manage soil salinity, culminating in his work on leaching requirement. To support policies on water allocation, reliable regional-scale inventories of soil salinity are needed. Despite decades of research in soil mapping, no reliable and up-to-date salinity maps are available for large geographical regions, especially for the salinity ranges that are relevant to agricultural productivity (i.e., salinities less than 20 dS m-1, when measured as the electrical conductivity of the soil saturation extract). This study presents a salinity assessment model for the western San Joaquin Valley, California, USA using multi-year Landsat 7 ETM+ canopy reflectance. Highly detailed salinity maps for 22 fields comprising 542 ha were used for ground-truthing. Re-gridded to 30×30 m, the ground-truth data totaled over 5000 pixels with salinity values in the range 0 to 35.2 dS m-1. Multi-year maximum values of vegetation indices were used to model soil salinity. Soil type, meteorological data, and crop type were evaluated as covariates. All considered models were evaluated for their fit to the whole data set as well as their performance in a leave-one-field-out spatial cross-validation. The best performing model was a function of canopy reflectance, crop type (i.e., cropped or fallow), rainfall, and average minimum temperature, with R2=0.728 when evaluated against all data and R2=0.611 for the cross-validation predictions. Overall, reasonably accurate and precise high resolution, regional-scale remote sensing of soil salinity is possible, even over the critical range of 0 to 20 dS m-1, where researchers and policy makers must focus to ameliorate loss of agricultural productivity and ecosystem health.

See more from this Division: SSSA Division: Soil Physics and Hydrology
See more from this Session: Soil Physics and Hydrology: Honoring the Contributions of Bob Luxmoore, John Letey, and John Hanks: I

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