We invite submissions on topics related to machine learning and statistical methods applied to hydrologic problems, with a focus on real-world forecasting applications. We are also interested in submissions relating to the overall theme of Science in Service to Society as it applies to computational methods, hydrology, or hydrometeorology. Papers relating to the use of machine learning methods in creating hydrometeorological products and services, drought prediction, regional climate modeling, flood prediction and decision support tools are welcomed. The biennial AMS AI contest will also be held at the 2016 Annual AMS meeting as part of this joint session. The focus will be on estimating the probability of specific rainfall amounts given polarimetric radar observations. For more detail on the contest, see http://www.kaggle.com/c/how-much-did-it-rain. For additional information, please contact the program organizers, Valliappa Lakshmanan (firstname.lastname@example.org) or John McHenry (email@example.com).