Detecting Irrigation From Spectral Differences Between Satellite and Modelled Soil Moisture Across the Contiguous United States

This archive contains the analysis scripts, example notebook, and derived irrigation products associated with the article “Detecting Irrigation From Spectral Differences Between Satellite and Modelled Soil Moisture Across the Contiguous United States.” The archive includes code used to compute wavelet-derived soil-moisture metrics, train and apply a Random Forest classifier, and generate the SMOS-derived irrigation classification. It also includes a minimal example notebook illustrating the workflow and point-scale wavelet diagnostics, including global wavelet power, cross-wavelet power, wavelet coherence, the wavelet power bias metric (M_B), and the coherence reduction metric (M_C). The derived data products include the SMOS-derived binary irrigation classification, the LGRIP30 irrigated fraction regridded to the analysis grid, a cropland mask, and the SMOS-derived irrigated-fraction map obtained by scaling the binary SMOS classification with LGRIP30 irrigated fractions. Large external input datasets used in the study, including SMOS soil moisture, LGRIP30, meteorological forcing data, and benchmark irrigation water-use data, are not redistributed in this archive and should be obtained from their original data providers.