Hydrologic modeling

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

Note: 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.

SNOTEL and other in-situ snow data

NRCS Interactive Map

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 both near-real-time data (previous day) and historical data.

NRCS State Snow Survey Snow Products

• Colorado
• Utah
• Wyoming
• Arizona
• 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).

CBRFC Snow Groups

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.

CoCoRaHS Interactive Map

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.

Gridded snow products based on in-situ data

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.

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.

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

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 Colorado Airborne Snowpack Monitoring Program (CASM) webpage

Other snowpack information

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.

Additional resources

State of the Science Report

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.

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.

Snowpack Monitoring in the Rocky Mountain West: A User Guide

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.