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==Data and tools==
==Data and tools==
''Note:'' [https://wwa.colorado.edu/sites/default/files/2021-10/Snowpack_Monitoring_in_the_Rocky_Mountain_West_A_User_Guide.pdf Snowpack Monitoring in the Rocky Mountain West: A User Guide] provides more detailed descriptions of the datasets and tools listed below, and guidance on using them.
Key hydrologic models used for research and/or operational applications in the Colorado River Basin:
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===SNOTEL and other in-situ snow data===
===Sacramento Soil Moisture Accounting Model===
====[https://www.nrcs.usda.gov/wps/portal/wcc/home/quicklinks/imap NRCS Interactive Map]====
====[https://www.weather.gov/media/owp/oh/hrl/docs/23sacsma.pdf Sac-SMA; NOAA]====
This very versatile tool provides a clear spatial overview of snowpack (SNOTEL) and other hydroclimate conditions across the western U.S., while allowing users to easily drill down into site-level data. Displays
Sac-SMA is the primary model used for operational streamflow forecasting by the NOAA Colorado Basin River Forecast Center (CBRFC) and the other NOAA RFCs. Sac-SMA represents soil moisture and storage characteristics to effectively simulate streamflow. The Sac-SMA model is available in a number of coding languages, including [https://github.com/NOAA-OWP/sac-sma Fortran], [https://github.com/sungwookwi/SAC-SMA MATLAB], and [https://github.com/tanerumit/sacsmaR R]. Sac-SMA is used in [https://www.cbrfc.noaa.gov/wsup/sac_sm/cbrfc_sacsma_101_20140731.pdf NOAA CBRFC forecasts].  
both near-real-time data (previous day) and historical data.  


====NRCS State Snow Survey Snow Products====
[https://www.weather.gov/media/owp/oh/hrl/docs/22snow17.pdf SNOW-17]. A conceptual model simulating snowpack accumulation and ablation that is most often run as a module paired with Sac-SMA, to add snowpack processes to Sac-SMA, such as for NOAA CBRFC’s forecasts. The input parameters include precipitation and temperature; precipitation is characterized as rain or snow depending on the temperature. NOAA as current [https://github.com/NOAA-OWP/snow17 Snow-17 Fortran code]; the R code for Sac-SMA linked above includes SNOW-17 as a module.  
*[https://www.nrcs.usda.gov/wps/portal/wcc/home/quicklinks/states/colorado Colorado]
*[https://www.nrcs.usda.gov/wps/portal/wcc/home/quicklinks/states/utah Utah]
*[https://www.nrcs.usda.gov/wps/portal/wcc/home/quicklinks/states/wyoming Wyoming]
*[https://www.nrcs.usda.gov/wps/portal/wcc/home/quicklinks/states/arizona Arizona]
*[https://www.nrcs.usda.gov/wps/portal/wcc/home/quicklinks/states/ New Mexico]
The NRCS state snow survey sites provide many additional options--varying by state-- for viewing current and historical SNOTEL and snow course data, including monthly summary reports (Basin Outlook Reports).


====[https://www.cbrfc.noaa.gov/station/sweplot/sweplot2.cgi???open CBRFC Snow Groups]====
===Variable Infiltration Capacity (VIC) model (University of Washington)===
Provides current year's time-series plots of SNOTEL SWE averaged across multiple SNOTEL sites (“snow groups”) selected to represent a particular catchment or area; ~300 options for catchments within the Colorado River Basin and eastern Great Basin.
====[https://vic.readthedocs.io/en/master/ VIC, University of Washington]====
VIC is a grid-based land-surface model (LSM) that solves the energy balance and water balance at the surface and subsurface using physical equations. VIC is open-source and is currently on its fifth major version; development and maintenance of the ‘official’ version of VIC is led by the Computational Hydrology Group in Civil and Environmental Engineering at the University of Washington. The main page linked above provides access to code and documentation for running VIC on multiple platforms.


====[https://maps.cocorahs.org/ CoCoRaHS Interactive Map]====
===Structure for Unifying Multiple Modeling Alternatives (SUMMA) (NCAR)===
Provides daily new snow depth and SWE, and snow depth and SWE on the ground, from the hundreds of volunteer CoCoRaHS observers in the basin. Select ''Map Options > What'' to map these snow variables.
====[https://ral.ucar.edu/model/summa SUMMA (NCAR)====
 
SUMMA is a hydrologic modeling approach that is built on a common set of physical equations and a common numerical solver, which together constitute the structural core of the model. Different modeling options can then be implemented within the structural core. The main page linked above provides access to the Fortran code and documentation for running SUMMA.
===Gridded snow products based on in-situ data===
 
====[https://www.nohrsc.noaa.gov/interactive/html/map.html NOAA NOHRSC - SNODAS Interactive Map]====
Provides access to SNODAS daily gridded SWE and other snow variables; the SNODAS model builds and maintains a snowpack based on weather data and also assimilates SNOTEL data.
 
====[https://climate.arizona.edu/snowview/ SnowView – Snow-Water Artificial Neural Network modeling system (SWANN)]====
This tool, developed at the U. of Arizona, shows a daily gridded snow dataset (SWANN) that uses snow models, assimilated SNOTEL data, and machine-learning methods. Users can compare SWANN with SNODAS for a catchment of interest.
 
====[https://www.cbrfc.noaa.gov/lmap/lmap.php?interface=snow CBRFC Modeled Snowpack – Interactive Conditions Map]====
Interactive map that provides daily-updated modeled SWE for ~500 catchment-elevation zones in the Colorado River Basin and eastern Great Basin. These modeled SWE data are used as key inputs for CBRFC's seasonal streamflow forecasts.
 
===Gridded snow products based on remotely-sensed data===
 
====[https://data.airbornesnowobservatories.com/ ASO (Airborne Snow Observatories, Inc.) - Basin Map]====
ASO uses airborne lidar to measure snow depths across a basin on demand; these depth measurements are combined with snow-density modeling to estimate SWE with high accuracy at 50-m spatial resolution. Free registration required to view the data for all ASO-flown basins.
* For more information about ASO activities in Colorado, see the [https://coloradosnow.org/ Colorado Airborne Snowpack Monitoring Program (CASM) webpage]
 
===Other snowpack information===
 
====[http://www.codos.org/ Colorado Dust-on-Snow (CODOS) reports]====
The CODOS program at the Center for Snow and Avalanche Studies (CSAS) tracks the deposition and emergence of dust layers in the snowpack, and snowpack temperature and other metrics, at 11 mountain pass locations throughout Colorado.  
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==Additional resources==
==Additional resources==
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===State of the Science Report===
===State of the Science Report===


[https://wwa.colorado.edu/publications/reports/CRBreport/ColoRiver_StateOfScience_WWA_2020_Chapter_2.pdf Chapter 2] of the State of the Science report, Section 2.5, provides an overview of the basin's snowmelt-dominated hydrology and key snowpack processes and patterns.
[https://wwa.colorado.edu/sites/default/files/2021-06/ColoRiver_StateOfScience_WWA_2020_Chapter_6.pdf Chapter 6](Hydrologic Models) of the State of the Science report provides expanded descriptions of hydrologic hydrologic modeling relevant to the Basin, including key models, calibration techniques, and model applications.  
 
[https://wwa.colorado.edu/publications/reports/CRBreport/ColoRiver_StateOfScience_WWA_2020_Chapter_5.pdf Chapter 5] of the State of the Science report, Section 5.1, describes the different methods for snowpack monitoring in much greater detail, along with links to several snow-monitoring tools.


===[https://wwa.colorado.edu/sites/default/files/2021-10/Snowpack_Monitoring_in_the_Rocky_Mountain_West_A_User_Guide.pdf Snowpack Monitoring in the Rocky Mountain West: A User Guide]===
[https://wwa.colorado.edu/sites/default/files/2021-06/ColoRiver_StateOfScience_WWA_2020_Chapter_8.pdf Chapter 8](Streamflow Forecasting) and [https://wwa.colorado.edu/sites/default/files/2021-06/ColoRiver_StateOfScience_WWA_2020_Chapter_11.pdf Chapter 11] (Climate change-informed hydrology) describe how hydrologic models are used in those respective applications.


This user guide expands on Section 5.1 of the State of the Science report with guidance on selecting appropriate snow-monitoring data and tools, and guidance on accessing and using the different online tools.
[https://wwa.colorado.edu/sites/default/files/2021-06/ColoRiver_StateOfScience_WWA_2020_Chapter_4.pdf Chapter 4] (Observations - Weather and Climate) and [https://wwa.colorado.edu/sites/default/files/2021-06/ColoRiver_StateOfScience_WWA_2020_Chapter_5.pdf Chapter 5] (Observations - Hydrology) describe the key sources of data used as inputs for hydrologic models, and to calibrate and validate the models, in applications for the Basin.

Revision as of 13:29, 23 August 2023

Overview

Figure 1. Colorado River Basin modeled average April 1st snow-water equivalent (SWE; left) and modeled average annual runoff (right). Note that areas producing >1" of runoff closely coincide with those that have a consistent April 1st snowpack. Maps: Figure 2.3, State of the Science Report (Lukas and Payton 2020); data: Livneh et al. 2013

Hydrologic models are widely used in the Colorado River Basin to study various aspects of hydrological processes and response (e.g., how runoff responds to wildfire, or climate change); for operational streamflow forecasting; and, coupled with other models, to generate hydrologic scenarios for planning exercises.

Relevance

Hydrologic models are computer-based simulators used to characterize the likely behavior of real watersheds under user-specified conditions and inputs (e.g., current snowpack and soil moisture, future weather and climate, vegetation change). These models generally include meteorological inputs (e.g., precipitation and temperature), governing equations and physical laws, and model structure, such as the connectivity of watershed components such as tree canopy, snowpack, and subsurface water storage and flow. While all of these components are generally present in hydrologic models, there are large differences among models in how these components are represented, the ways in which runoff is calculated, and the spatial extent and resolution of the catchment areas in the model. There is no one approach or level of complexity that is optimal for all applications of hydrologic models.

Hydrologic models can be broadly categorized into conceptual models and physical (or dynamical) models, although in reality there is more like a continuum. Conceptual models tend to have simple representations of watershed attributes and processes. The linkages between components are typically controlled by adjustable parameters whose values may be derived from observations, or deduced through calibration of the model. Physical models tend to be more complex, and spatial and temporal variations in watershed characteristics are more robustly incorporated, leading to a model that more closely reflects the physical workings of the actual watershed. That said, a simpler model can be better suited for forecasting than a more complex model.

Data and tools

Key hydrologic models used for research and/or operational applications in the Colorado River Basin:

Sacramento Soil Moisture Accounting Model

Sac-SMA; NOAA

Sac-SMA is the primary model used for operational streamflow forecasting by the NOAA Colorado Basin River Forecast Center (CBRFC) and the other NOAA RFCs. Sac-SMA represents soil moisture and storage characteristics to effectively simulate streamflow. The Sac-SMA model is available in a number of coding languages, including Fortran, MATLAB, and R. Sac-SMA is used in NOAA CBRFC forecasts.

SNOW-17. A conceptual model simulating snowpack accumulation and ablation that is most often run as a module paired with Sac-SMA, to add snowpack processes to Sac-SMA, such as for NOAA CBRFC’s forecasts. The input parameters include precipitation and temperature; precipitation is characterized as rain or snow depending on the temperature. NOAA as current Snow-17 Fortran code; the R code for Sac-SMA linked above includes SNOW-17 as a module.

Variable Infiltration Capacity (VIC) model (University of Washington)

VIC, University of Washington

VIC is a grid-based land-surface model (LSM) that solves the energy balance and water balance at the surface and subsurface using physical equations. VIC is open-source and is currently on its fifth major version; development and maintenance of the ‘official’ version of VIC is led by the Computational Hydrology Group in Civil and Environmental Engineering at the University of Washington. The main page linked above provides access to code and documentation for running VIC on multiple platforms.

Structure for Unifying Multiple Modeling Alternatives (SUMMA) (NCAR)

[https://ral.ucar.edu/model/summa SUMMA (NCAR)

SUMMA is a hydrologic modeling approach that is built on a common set of physical equations and a common numerical solver, which together constitute the structural core of the model. Different modeling options can then be implemented within the structural core. The main page linked above provides access to the Fortran code and documentation for running SUMMA.

Additional resources

State of the Science Report

Chapter 6(Hydrologic Models) of the State of the Science report provides expanded descriptions of hydrologic hydrologic modeling relevant to the Basin, including key models, calibration techniques, and model applications.

Chapter 8(Streamflow Forecasting) and Chapter 11 (Climate change-informed hydrology) describe how hydrologic models are used in those respective applications.

Chapter 4 (Observations - Weather and Climate) and Chapter 5 (Observations - Hydrology) describe the key sources of data used as inputs for hydrologic models, and to calibrate and validate the models, in applications for the Basin.