Quantitative determination of moisture with nuclear magnetic resonance is usually a simple task, since the initial amplitude is proportional to the moisture content. However, situations can arise where the combination of short relaxation times, low signal-to-noise ratio and the ill-posed nature of the inverse Laplace transformation lead to a significant bias of the initial amplitude impeding it being an accurate proxy for the moisture content. This is often met when applying single-sided NMR to building materials with small pores, like concrete. We present a method to derive a generalised correlation function linking not only the initial amplitude, but relaxation attenuated signal amplitudes with moisture content. Therefore, the effect of de-saturation on the T2 distribution of the respective material near saturation, which is the input to the model, is simulated using a capillary bundle model. Predicted and measured moisture coincide, and the uncertainty is significantly smaller compared to the conventional approach.