Stochastic storm transposition (SST) relies on storm observations that come from high-resolution precipitation data with a typical spatial resolution of 1-4 km and temporal resolution of 1 hour. A long period of record (POR) is always helpful, but due to the space-for-time substitution principle, large samples of storm events can be generated even if the POR is much shorter for radar-based precipitation than gage observations. Since SST relies on real observations of rainfall distributions in space, the data must accurately represent the time-varying nature of storms in space. Using gage data that has solely been interpolated is not recommended. Radar-based data are the preferred data source. The NOAA Analysis of Record for Calibration (AORC) dataset is the recommended source for storm catalog development. The most recent version of the data has 1 km spatial resolution, 1 hour temporal resolution, and a period of record for CONUS of 1979-near present. The dataset is accessible here on AWS: NOAA AORC on AWS.

Before performing the SST workflow in HEC-HMS outlined later in this guide, three principal data components are required:

  • Transposition Domain
  • Randomly Generated Storm Centers
  • Storm Catalog

The following sections will outline developing each data component.

Select a Transposition Domain

Developing a transposition domain for a watershed is not a one-size-fits-all process. It requires engineering judgment and the analysis of meteorological datasets to develop an appropriate domain. Considerations for what makes up this region include (but are not limited to):

  • Normal annual total precipitation
  • Seasonal variability in precipitation
  • Dewpoint and temperature for convective meteorology
  • Frequency of tropical storm occurrence and proximity to a coastline
  • Elevation, orographically-enhanced rainfall, and blocking

The area should be large enough that a good sample of significant events can be collected, but the larger a domain is, the more likely you are stretching the homogeneity assumption of the domain which asserts that any storm in the domain is equally likely to occur at any other point within the domain. The map below shows the transposition domain that was developed for the Duwamish (Green) River project in Washington State. The watershed polygon is shown below in red. PRISM normal annual total precipitation is shown as the base layer and gives a sense of the complexity of rainfall in this region - it is highly influenced by orographic effects. The watershed's headwaters are at the ridge of the Cascade Range and the river flows down to Elliott Bay in Puget Sound.

This transposition domain had to carefully consider the role of atmospheric rivers and their interactions with the mountains in the region. One challenge in identifying a homogeneous region is that the target watershed may be large enough to contain several different precipitation mechanisms, and and the domain must encompass all these processes in equal measure. The Duwamish watershed is at lower elevation than neighboring drainages and receives less rainfall at its headwaters. It descends into a valley in the Seattle/Tacoma area that experiences rain shadow effects from the Olympic Mountains to the west. The resulting domain was drawn to exclude storms that occurred in the Coast Range or the OIympic Mountains to the west, and anything on the leeward side of the Cascades. It avoids the regions further south in Oregon where the normal rainfall in the Cascades drops off due to the Klamath Mountains robbing the moisture before it can make it too far inland. The northern boundary passes through the Vancouver, BC metro area and stops just before the rise of the North Shore Mountains. It also reflects the northernmost boundary of the precipitation dataset. Work is underway by the Hydroclimate Extremes Research Group at University of Wisconsin to develop a repeatable, rapid data-driven statistical approach to defining the transposition domain.

Generate Storm Centers

Develop a restricted domain, which is a polygon defining the area inside the transposition domain that, when transposed to the target basin, do not result in any areas outside the domain inside the watershed. Randomly select an (x, y) coordinate pair from inside the restricted transposition domain with equal probability. The current recommended practice is to generate a large sample of points within the transposition domain using an external tool such as a GIS. See Generating Coordinates using QGIS for a brief guide.

Develop a Storm Catalog

Storm Identification 

A "storm event" is identified as a significant accumulation of rainfall over an area the size and shape of the target watershed.  To encompass typical meteorological scales, a 72 hour duration is used to capture both mesoscale and synoptic-scale events.  Sub-daily precipitation data is necessary for adequately capturing fluvial and pluvial flood response, but storms are identified by their 72-hour total rainfall totals.  The hourly precipitation must be aggregated on a rolling basis to make the storm identification.  Then for each 72-hour window, the target watershed polygon is transposed across the 72-hour precipitation total field to the point where it maximizes the watershed-averaged 72-hour precipitation. Storm potential precipitation is computed using an optimization routine that performs geographic operations on a polygon and transposes the watershed polygon over the storm's accumulated precipitation field and computes the average of that field over the polygon at every step. It is searching for the global maximum of the average precipitation over the polygon. The global maximum is the storm's potential precipitation for the watershed and is used to determine if it will be included in the catalog. Events are included in the catalog if their maximized watershed-averaged 72-hour precipitation exceeds a selected threshold.  The threshold is selected such that the average rate of events is 10 per year.  For the current AORC period-of-record, which is 1979-2025, this is 47 years of record.  The threshold is adjusted until there are 470 events (47 * 10) above the threshold.  The actual number of events per year in the catalog is allowed to vary just as the number of events per year in the SST simulations will vary. This procedure is completed within StormCloud and uses underlying processes from the StormHub software created by Dewberry. A step-by-step guide for creating a storm catalog can be found here: StormCloud User Guide.  A snapshot of this optimization process is shown below for one storm event transposed within the Duwamish River Watershed Domain.

Computing Storm Potential Precipitation Example

  • Background raster is the 72-hour accumulation for an event beginning on 2015-12-07.
  • Precipitation data are clipped to the extent of the transposition domain.
  • Light grey polygon is the real location of the Duwamish watershed.
  • Black polygon is the position of the watershed polygon when maximized for area-averaged precipitation.
    • The polygon was moved around the transposition domain by a numerical optimization routine.
    • The polygon is not allowed to "leave" the transposition domain.
  • Resulting potential precipitation is 15.39 inches.

Storm Catalog Data Format

The output of the storm catalog will be a series of HEC-DSS files, one for each identified and selected storm event and a .grid file containing data for all storm events, which will be placed in the HMS project directory so that upon opening the HMS project each event is loaded.  Tools such as the hec-dss-python project can be used for manipulating HEC-DSS files. Each storm should be in its own DSS file with a logical and consistent name. A recommended convention is: $data-source $event-date $rank , e.g. AORC 2015-12-07 T001 . Other metadata may be added to the filename, such as the type of storm (see Storm Typed Stochastic Storm Transposition in a Quasi-Continuous Framework).

The image below shows one storm event in HEC-DSSVue. Each entry in the catalog shown below is an hourly grid.

  • The A part indicates that the resolution and projection of these grids are 4 km using the SHG grid, purely informational.
  • The B part is used to identify which project, watershed, or catalog the storm belongs to.
  • The C part should always be PRECIPITATION
  • The D part is the start of the precipitation recording period
  • The E part is the end of the precipitation recording period
  • The F part can be free-form but is typically used to indicate the source of the precipitation data for bookkeeping.
  • The file's name indicates the precipitation data source, the date when the storm begins, and that it is the largest event (rank 001) above a selected threshold (T) 

Below are three views available in HEC-DSSVue of one of the hourly grids from a storm. The metadata contains the start date of the event occurrence and the coordinates of the identified center of the storm. Typically, the center is the grid cell with the highest 72-hour accumulation. When hydrologic processes that rely on temperature are included in the simulation process, for example snowmelt, temperature data corresponding to the event time window should also be included in a separate DSS file.