2022 CSDMS meeting-037

Edit registration

Pay registration

(if you haven't already)

Log in (or create account for non-CSDMS members)
Forgot username? Search or email:CSDMSweb@colorado.edu

"2) Image Segmentation using Deep Learning and Human-In-the-Loop Machine Learning - Part I" is not in the list (1) Modeling Water Movement and Reservoir Operations with mosartwmpy, 3) Introduction to Landlab, 4) Xarray for Scalable Scientific Data Analysis, 5) Will not attend a clinic) of allowed values for the "CSDMS meeting select clinics2 2022" property. "3) Image Segmentation using Deep Learning and Human-In-the-Loop Machine Learning - Part II" is not in the list (1) Component Creation with Landlab, 2) Rapid hypothesis testing and analysis with the open-source delta model pyDeltaRCM, 4) Publishing Reproducible Computational Research with the Whole Tale, 5) Will not attend a clinic) of allowed values for the "CSDMS meeting select clinics3 2022" property.

Browse  abstracts

<<

>>

Back to meeting

Event Severity vs Frequency for a Patch of Seabed using Extreme Value Analysis (EVA)

Chris Jenkins, University of Colorado Boulder boulder Colorado, United States. jenkinsc0@gmail.com

This paper examines the behavior of an area of seabed in terms of temporal Extreme Value Analysis distributions for erosional/depositional events at the seabed. EVA provides an empirical quantitative basis for predicting the statistics of extreme events in areas. The study is thought to be the first to comprehensively derive EVA coefficients for an area of seabed.

Using a large multidecadal (31 year) data-cube of hydrographic standard bathymetric soundings for the inner shelf of the German Bight, statistics of annual seabed elevation change were compiled. Time-domain exceedance analysis on the elevation changes showed that return times on >1m of change range from 1 to 20 years depending systematically on location in relation to tidal channels, ebb deltas and sand ridges.

Of particular interest is that Weibull and Rayleigh distributions from EVA exhibited a close statistical fit to the change-frequency data – for the whole area and also sub-areas. Those distributions offer a new pathway for statistically modeling seabed deposition/erosion - especially for practical purposes in relation to human objects such as UXO, and in relation to episodic burial of epibenthic communities.