Welcome to the supplemental website for Atmospheric vapor and precipitation are not in isotopic equilibrium in a continental mountain environment. Because there was so much going on in the paper (potentially too much), I thought I would include some extra information to help folks better understand or explore the data that was collected. My hope is that some of the additional context will prove useful in future endeavors hoping to use the data collected, invoke a similar analysis, etc.
This paper combined a number of novel elements (e.g., temporal scale and resolution, environment, Bayesian analysis) to analyze the validity of a common assumption made by practicing isotope hydrologists: That precipitation and vapor are in isotopic equilibrium. While it is not surprising or exceptional that we found this assumption to be inaccurate (the literature seems to go back and forth on the validity of the assumption, as highlighted in the introduction of the paper), this is the first study to quantify the uncertainties generated by such an assumption over a long period of time using a Bayesian framework. In aggregate, our findings suggest that the equilibrium assumption is likely reasonable over longer periods of time (in accordance with principles of mass balance). However, over shorter evaluation times and periods of large potential evapotranspiration (or possibly sublimation), we need to account for kinetic or nonequilibrium (e.g., source) effects. Not accounting for such effects leads to very large errors that make hydrological inference very difficult, if not impossible.
I am an open science advocate, which means trying to generate reproducible research and ensure the data and code I’ve used or made is open to others. So, in addition to the manuscript and this site, there is also a compendium that contains all raw and processed data, code, and writing materials used and generated for the paper. The hope of sharing the compendium is to further contextualize the data collected and the code used to generate the results and interpretations. The full compendium can be found here, but also checkout the data page. Please let me know if you’ve found any mistakes or have suggestions of how I could improve my analysis — I’m a big fan constructive criticism.
For those interested, this site was made using the rmarkdown
package in R. For more on using rmarkdown to make websites, check out this chapter in the R Markdown book. It was pretty fun to learn what I can do in terms of making static sites using a combination of R, html, css, javascript, etc.
If you’d like to see the underlying source code used to generate the site (i.e., the .Rmd files rendered to html), then click here (or click the GitLab icon in the upper right corner of the navbar — it looks like a fox) to go to the GitLab repo hosting the site (code for this site is located in the public/
folder). Additionally, the repo contains the functions and scripts used to analyze the data associated with the paper, if you want to check that out, too (though the compendium hosts both the code and data, for richer context).