Soil salinity mapping with remote sensing-based vegetation indices and crop water use estimates

In the Arkansas River basin, Colorado, USA, water up-flux from saline shallow groundwater tables leaves salts in the vadose zone. These salts accumulate over decades threatening agricultural sustainability. Remote sensing is an economical and practical tool that can be used to monitor soil salinity (EC, electrical conductivity) at large spatial scales. In this study, several EC algorithms were developed utilizing different combinations of explanatory variables, including a salinity index and actual crop evapotranspiration estimates for surface irrigated maize fields located within a (sub-surface) drainage district in the Arkansas River basin. Estimates of crop water use were performed using a surface energy balance approach and Landsat (satellite) multispectral imagery. Results indicate that the developed EC algorithms that included crop water use and a salinity index improved the accuracy of soil EC mapping over models that included a vegetation index alone.