A method to downscale soil moisture to fine resolutions using topographic, vegetation, and soil data

摘要

Soil moisture can be estimated over large regions with spatial resolutions greater than 500 m, but many applications require finer resolutions (10-100 m). Several methods use topographic data to downscale, but vegetation and soil patterns can also be important In this paper, a downscaling model that uses fine-resolution topographic, vegetation, and soil data is presented. The method is tested at the Cache la Poudre catchment where detailed vegetation and soil data were collected. Additional testing is performed at the Tarrawarra and Nerrigundah catchments where limited soil data are available. Downscaled soil moisture patterns at Cache la Poudre improve when vegetation and soil data are used, and model performance is similar to an EOF method. Using interpolated soil data at Tarrawarra and Nerrigundah decreases model performance and results in worse performance than an EOF method, suggesting that soil data needs greater spatial detail and accuracy to be useful for downscaling.