Organic Carbon and Texture Control Moisture Dependence of Soil Shortwave Infrared Reflectance

Moisture content affects soil reflectance in the optical domain (400–2500 nm), acting as a confounding factor in soil property prediction models. Soil reflectance needs to be simulated efficiently for varying levels of soil moisture, in order to aid soil property prediction efforts and inform physical land surface models. Here, we built on previous work that investigated how soil reflectance decreases with increasing soil moisture. We explored how the relationship between the reflectance and soil moisture content changes as a function of wavelength and soil characteristics. For this purpose, we acquired the spectra of 28 soil samples from various locations across Europe in a laboratory setting, at different levels of soil moisture. The soil reflectance-moisture relationship was found to be wavelength-dependent and best represented by decreasing exponential functions. The rates of exponential decrease, however, varied across soil samples and were normalised to isolate effects of different soil characteristics. It was found that organic carbon (OC), clay and silt content displayed a statistically significant relationship with the normalisation factor, a proxy for how quickly soil ‘darkens’ with increasing soil moisture content. A multiple linear regression model was used to describe the normalisation factor based on OC content and soil textural information. The resulting model was able to explain 67% of the variance, with OC and clay content accounting for almost 70% of the relative feature importance. Our findings call for the inclusion of OC content and textural information, especially clay content, in physical models of soil moisture-reflectance, for more efficient simulations of soil reflectance at varying levels of soil moisture, to support climate models and soil property predictions efforts based on field and remotely sensed data.