摘要

Passive microwave remote sensing has experienced significant success for soil moisture (SM) inversion. However, quantifying the uncertainties caused by soil parameter sensitivities has not attracted sufficient attention. Although local sensitivity analysis (SA) has been used to describe parameter sensitivity in the past, it fails to quantify parameter sensitivities, especially interactions, for nonlinear microwave emission models. This paper presents a comprehensive evaluation that combines physically based emission models and various global SA algorithms to evaluate parameter sensitivity. All the algorithms exhibit highly consistent sensitivity measures, which means a reliable SA result is obtained. The results indicate that the sums of the main sensitivity indices of SM and surface roughness parameters-root-mean-square height (RMSH) and correlation length-are greater than 0.92 and 0.95 for emissivity and brightness temperature (TB), respectively. Furthermore, we find that: 1) the parameter probability distributions have little effect on the sensitivity measures; 2) the SM sensitivity decreases and the RMSH sensitivity increases as the frequency increases and the incidence angle decreases; and 3) the SM is more sensitive on V-polarized than on H-polarized emissivity and TB, while the RMSH is much more sensitive on the polarization index. The presented global SA quantitatively explains the optimal frequency, incidence angle, and polarization for SM inversion and extends the parameter SA for microwave emission models to a more general framework, as well as provides an implication for bare soil emission modeling and SM inversion.