With our new series of articles we intend to build up a collection of useful resources on snow and ice hydrology. Primarily aimed at people who only occasionally deal with this field of research, the articles will outline basic concepts, provide insights on current methods, point at interesting open-source tools, and host opinion papers.
The first article deals with a very basic problem in snow hydrology: how to estimate the snow water equivalent if only snow depth data is available. Be it historic snow depth records, or a graduated rod that’s read out by a webcam. There are many situations in which an informed estimate of the snow density might come in handy. See also the supplement material (MS xlsx).
The second article focuses on two fundamental approaches to seasonal snow and glacier
surface melt modeling, specifically the differences between empirical (or temperature index) and physically-based (or mass- and energy-balance) snow and ice melt models.
The third article by Richard Essery (School of GeoSciences, University of Edinburgh, Edinburgh, UK) is a primer on the principles and use of physically based snowmelt models. It is based on the Factorial Snow Model (FSM, Essery 2015). The Fortran code for FSM, a quickstart guide, and a range of input data are freely available from links at the end of the article, allowing the user to repeat the examples and attempt their own experiments.
The fourth article by S. McKenzie Skiles is a starting guide to mapping snow depth from drones using structure from motion. I encompasses all the preliminary steps for snow SfM measurements, the required equipment, software and provides step-by-step guidance for snow depth mapping using UAVs, as well as links to further reading.
The fifth article by James McPhee addresses how to estimate the role of glaciers in the hydrological cycle at the watershed scale with a handful of data.
Feel free to suggest an update or a new topic for our series of articles. Or get involved and become an associate ICSIH member. Contact us at [email protected].