 This paper examines the triple collocation error estimation technique for assessing the relative quality of multiple soil moisture data sets. The technique uses three sets of data with independent error structures, allowing for the estimation of the root mean square error while simultaneously solving for systematic differences between the data sets. The authors found that the triple collocation method provides accurate error estimates when the necessary conditions are met, such as having a sufficient number of common observations and the errors being uncorrelated. This allows for the development of strategies for combining multiple data sets, which could be useful for improving flood forecasting or generating superior multi-mission long-term soil moisture data sets. This article was authored by W. A. Derigo, K. Saipal, R. M. Paranusa, and others.