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Activity Number: 11 - Spatio-Temporal Statistical Applications
Type: Invited
Date/Time: Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
Sponsor: Council of Chapters
Abstract #316802
Title: Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France
Author(s): Matthew Heiner* and Matthew J Heaton and Philip White and Benjamin Abbott and Camille Minaudo and Rémi Dupas
Companies: Brigham Young University and Brigham Young University and Brigham Young University and Brigham Young University and Physics of Aquatic Systems Laboratory, Ecole Polytechnique Fédérale de Lausanne and INRAe
Keywords: Harmonic regression; Mixture modeling; Hierarchical models; Hydrology; Directional data
Abstract:

Elevated nitrate from human activity causes ecosystem and economic harm globally. The factors that control the spatiotemporal dynamics of riverine nitrate concentration are not well understood. We analyzed nitrate concentration from 4,450 sites throughout France to group sites that exhibit similar trend and seasonal behaviors and relate these dynamics to catchment characteristics. We employed a latent-variable, Bayesian mixture of harmonic regressions model to infer site groupings based on multi-year trend, and annual cycle amplitude and phase. Cluster membership probabilities were governed by continuous, latent variates that we regressed on seven classes encompassing geology, hydrology, and land use.


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