Snowbedo Data and Modeling Scripts
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|Created:||Sep 01, 2017 at 6:17 p.m.|
|Last updated:|| Sep 15, 2017 at 11:16 p.m.
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The .Rdata datasets were created to be used in the Snowbedo R Package, available on GitHub at : <a href="https://github.com/cahhansen/Snowbedo" rel="nofollow">https://github.com/cahhansen/Snowbedo</a>. The Snowbedo package and models were developed in part with support of the iUTAH project, under the Research Focus Area 3: Understanding the ties between human and environmental water systems.
The datasets contain a collection of time series of streamflow, meteorological, and land surface/atmospheric data which can be used to calibrate streamflow models. Each dataset corresponds to a different watershed/stream in the Wasatch Mountains.
Variables and their definitions are as follows:
Date - date, Year-Month-Day
Streamflow - streamflow rate in cms (from Salt Lake City Department of Public Utilities)
Tmax_C - maximum temperature, degrees Celsius from sub-daily measurements (SNOTEL)
Tmin_C - minimum temperature, degrees Celsius from sub-daily measurements (SNOTEL)
SWE_cm - snow water equivalent, centimeters (SNOTEL)
Albedo - average watershed albedo (derived from MOD01A1 product)
SolarRad_Whm2d - shortwave downwelling radiation, W-h/m2/day (from CERES SYN1deg product)
SnowCover - percentage of watershed covered by snow (derived from MOD01A1 product)
SnowDepth_cm - depth of snow, centimeters (SNOTEL)
Precip_cm - precipitation, centimeters/day (SNOTEL)
Additional parameters are also included for exploring the effects of the lagged parameters (lagged by one day) on streamflow.
Streams and the locations of the SLCDPU Gage Location and their corresponding SNOTEL sites are as follows:
City Creek - 40.7841, -111.883; SNOTEL Site: Louis Meadow (972)
Little Cottonwood - 40.579, -111.798; SNOTEL Site: Snowbird (766)
Lambs Creek -40.7548, -111.709; SNOTEL Site: Parley's Summit (684)
Dell Creek - 40.7809, -111.681; SNOTEL Site: Lookout Peak (596)
Big Cottonwood - 40.618, -111.780; SNOTEL Site: Mill-D (628)
The scripts are intended to be used with the Snowbedo R Package (github.com/cahhansen/Snowbedo. The scripts may be run using R Statistical Software and the dependent external packages (listed in the scripts). The Snowbedo package was developed in order to model streamflow as a result of changing snowpack dynamics (particularly albedo). The purpose of the NeuralNetwork script is to train and build a neural network model of streamflow based on climate and watershed characteristics.Results of the model are a daily time-series of streamflow covering the same time period as the input datasets. Different scenarios (with adjusted albedo) can be created with the ModelDifferencesInAlbedo.R script. The readme.txt file explains how the package can be used.
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Resource Level Coverage
# Snowbedo Package for modeling snowmelt and streamflow in semi-arid, snowpack-driven mountainous watersheds. This package utilizes streamflow, temperature data, precipitation, shortwave incoming (downwelling) radiation, and white-sky albedo to calibrate a streamflow model based on a simplified snowmelt-based process that is influenced by albedo. This calibrated model can then be used to explore various scenarios of albedo (which may be influenced by dust and black carbon deposition). ## Functions included in the Package ### Formatting data - limitperiod (limits data to specific time period) - dissipate (calculates daily precipitation from accumulative precipitation) ## Scripts for Using the Snowbedo Package - NeuralNetwork.R (reads in the formatted data for an individual watershed, subsets based on user-defined list of parameters, and trains a neural network model for streamflow. Produces a time series of modeled streamflow and saves a file of the neural network model) - ModelDifferencesInAlbedo.R (reads in a formatted dataset and neural network model (produced by NeuralNetwork.R) and creates different scenarios by adjusting the albedo. Produces time series of streamflow for each of the scenarios)
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|National Science Foundation||iUTAH-innovative Urban Transitions and Aridregion Hydro-sustainability||1208732|
|Steven Burian||University of Utah|
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