Modeling salinity effects on soil reflectance under various moisture conditions and its inverse application: A laboratory experiment

Abstract

Soil salinization is an important desertification process that threatens the stability of ecosystems, especially in arid lands. Quantifying and mapping soil salinity to monitor soil salinization is difficult because of its large spatial and temporal variability. There has been a growing interest in the use of hyperspectral reflectance as a rapid and inexpensive tool for soil salinity characterization in the recent past. However, as soil moisture often jointly affects soil reflectance, a moisture-insensitive reflectance model is needed to provide the base for soil salinity monitoring from soil reflectance. In this paper, we developed an exponent reflectance model to estimate soil salt contents inversely under various soil moisture conditions, based on a control laboratory experiment on the two factors (soil salinity and soil moisture) to soil reflectance. Main soil salt types (Na2SO4, NaCl, Na2CO3) with wide soil salinity (0% to 20%) and soil moisture (1.75% to 20%) levels (in weight base) from Western China were examined for their effects on soil reflectance through a model based approach. Moisture resistant but salt sensitive bands of reflected spectra have been identified for the model before being applied to inversely estimate soil salt content. Sensitive bands for Na2SO4 type of salt affected soils were identified as from 1920 to 2230nm, and 1970 to 2450nm for NaCl, 350 to 400nm for Na2CO3 type of salt affected soils, respectively. The sensitive bands focused on ranged from 1950 to 2450nm when all data were considered when ignoring salt types. The model was then applied to inversely estimate soil salt contents. High R2 of 0.87, 0.79, and 0.66, and low mean relative error (MRE) of 16.42%, 21.17%, and 27.16%; have been obtained for NaCl, Na2SO4 and Na2CO3, respectively. Performance of the inverse model dropped but remained significant when ignoring salt types with an R2 of 0.56 and a MRE of 33.25%. The approach proposed in this study should thus provide a new direction for estimating salinity from reflectance under various soil moisture conditions and should have wide applications in future monitoring of soil salinization.