Masters candidate Nathan Lentsch successfully defended his masters in Earth Sciences on August 16th, 2017. He is advised by Professor Chris Paola of the St. Anthony Falls Laboratory and the Department of Earth Sciences. Congratulations!
TIDE-INFLUENCED DELTAS: THE EBB AND FLOW OF A SYSTEM AT WORK
Nathan Lentsch, Masters Candidate in Earth Sciences
Advisor: Dr. Chris Paola, Department of Earth Sciences and St. Anthony Falls Laboratory, University of Minnesota
Tide-influenced deltas are among the largest depositional features on Earth and are ecologically and economically important. However, the continued rise in relative sea level threatens the sustainability of these landscapes and calls for new insights on their morphological response. While field studies of ancient deposits allow for insight into delta evolution during times of eustatic adjustment, tidal deltas are notoriously hard to identify in the rock record. Here we present a suite of physical experiments aimed at reproducing tide-influenced deltas subjected to relative sea-level rise (RSL). Using new techniques and methods, we investigate the evolution of such deltas in terms of shoreline migration and net deposition across the delta topset. By varying the ratio of fluvial to tidal energy, we show that tide-influenced deltas are subjected to shoreline transgression as compared to identical, yet purely fluvial, deltas that exhibit static or even regressive shorelines. Different magnitudes of net deposition among our experiments clearly reveal how tides effectively remove sediment, which would otherwise be deposited by fluvial processes, from the delta topset. Furthermore, strong tidal forcing can reduce the mobility of distributary channels and create composite deltas were different processes dominate varying areas of the delta plain leading to distinct morphologies. This reduction in channel mobility also leads to an increase in channel body connectivity and stacking density which we show using a new approach for creating synthetic stratigraphy wherein digital elevation model data is coupled with time-lapse photography.