The purpose of this set of tutorials is to provide an example of how to develop and use HEC-HMS to perform a rapid post-wildfire watershed assessment. These tutorials use the HEC-HMS model developed for the Gallinas Creek Watershed in response to the Hermits Peak-Calf Canyon Fire that occurred in 2022 in New Mexico to illustrate the procedures. This assessment can be scaled based on the scope, schedule, and budget for the modeling effort. This example illustrates a case where a limited timeframe was available to generate post-wildfire hydrographs and debris yield estimates.

This tutorial group includes the following components:

  1. Watershed Burn Severity Calculation Procedure

  2. Gradation Curve Development Procedure

  3. Discharge-Frequency Curve Development Using HEC-SSP

  4. Pre & Post Wildfire Hydrology Modeling with HEC-HMS Procedure

  5. Debris Yield Modeling Using Erosion Methods in HEC-HMS

  6. Hydraulic Analysis Considerations to Compute Flood Inundation


The Hermits Peak Fire, located approximately 35 miles northeast of Santa Fe, New Mexico, initiated on April 4, 2022 in the Sangre de Cristo Mountains. On May 4, 2022, the New Mexico Wildfires were declared a major disaster by the President of the United States.  As of October 25, 2022, the fire burned 341,735 acres and was 100% contained. The fire burned 74% of the Gallinas Creek Watershed (19% with high severity, 25% with moderate severity, and 30% with low severity). The following monsoon season consisted of high intensity-short duration rainfall events which threatened to cause debris flows and increased flooding in areas affected by the fires. The US Army Corps of Engineers (USACE) Albuquerque District (SPA) received a request to provide assistance in response to the ongoing wildfires. SPA requested further assistance from the Los Angeles District (SPL), Sacramento District (SPK), and Hydrologic Engineering Center (HEC) to provide engineering and modeling support. To better understand the expected increase in peak flows and debris yields from the burned watersheds, modeling of pre- and post-fire conditions was performed using HEC-HMS and potential flood inundation was modeled using HEC-RAS.

Applications and Limitations

The HEC-HMS model for the Gallinas Creek Watershed was developed in an emergency setting with a limited timeframe and budget. Several simplifying assumptions were made to develop the model quickly. The model results were used with discretion to inform emergency planning and response actions. The methods presented in this tutorial produce results that have a high degree of uncertainty which may be appropriate for use in emergency applications or screening-level studies but may not contain an appropriate level of detail for designs or comprehensive studies.

Considerations Prior to Hydrologic and Hydraulic Model Development

Prior to developing hydrologic and hydraulic models for a post-wildfire watershed assessment, several considerations should be taken into account. These considerations include determining the modeling approach and desired outcomes, listed in more details below:

Consider the Scope, Schedule, and Budget

Consider the scope, schedule, and budget, and scale the modeling effort accordingly.

  1. In this case, a timeframe of approximately two months was available to model 1,069 square miles of watersheds and delineate floodplains for almost 387 miles of rivers.
  2. Approximately 40 hours were spent developing the Gallinas Creek Watershed model in HEC-HMS.

Determine the Extents of the Models

  1. In this case, the Hydrologic Unit Code (HUC) 12 delineation of the Gallinas Creek Watershed was used to define the hydrologic model extents.
  2. For the hydraulic model, population centers located adjacent to Gallinas Creek were used to define areas to include within the model extents.

Determine Modeling Software and the Desired Results

  1. In this case, a HEC-HMS hydrologic model was used to compute pre- and post-wildfire hydrographs and debris yield estimates for the Gallinas Creek Watershed.
  2. A 2D HEC-RAS hydraulic model was used to compute flood inundation along Gallinas Creek in the more populated areas. Unsteady flow hydrographs computed in HEC-HMS, bulked to include the effects of debris, were used as inflow boundary conditions for the 2D HEC-RAS model.
    1. A 1D HEC-RAS model also could have been used to compute flood inundation along Gallinas Creek.
    2. A list of considerations for deciding between developing a 1D or 2D model is provided here: https://www.hec.usace.army.mil/confluence/rasdocs/r2dum/latest/steady-vs-unsteady-flow-and-1d-vs-2d-modeling/1d-vs-2d-hydraulic-modeling
  3. Identify handoff points between the hydrologic and hydraulic models where flow hydrographs from the hydrologic model will serve as inflow boundary conditions in the hydraulic model. Identify points of interest where data output from the model is needed.
    1. Ensure Break Points are placed in the HEC-HMS model at the handoff points and points of interest, so the elements are delineated accordingly.
    2. Develop a naming convention to be used in both models to clearly specify which flow hydrographs should be applied to each inflow boundary condition.
    3. Determine if and how local flows will be accounted for in the hydraulic model.
      1. In 1D HEC-RAS models, local flows can be added to a cross section through lateral inflow hydrograph boundary conditions, following the guidance provided here: https://www.hec.usace.army.mil/confluence/rasdocs/rasum/latest/performing-a-1d-unsteady-flow-analysis/entering-and-editing-unsteady-flow-data/boundary-conditions#id-.BoundaryConditionsv6.1-LateralInflowHydrographlateral-inflow-hydrograph
      2. In 2D HEC-RAS models, local flows can be added through flow hydrographs applied to internal boundary conditions, following the guidance provided here: https://www.hec.usace.army.mil/confluence/rasdocs/r2dum/latest/boundary-and-initial-conditions-for-2d-flow-areas/internal-boundary-conditions

Identify Available Data for Model Development and Calibration

  1. Data needed for model development and calibration may include stream flow and stage gages, precipitation gages, observed high water marks, debris volumes in detention basins.
  2. In this case, the following data sources were used:
    1. Terrain: USGS 3D Elevation Program (3DEP), 10 meter Digital Elevation Model (DEM).
    2. Precipitation: NOAA Atlas 14 precipitation frequency grids, annual maximum series.
    3. Stream Flow: USGS stream gage 15-minute, daily, and annual peaks.
    4. Burn Severity Maps: Provided by the US Forest Service BAER team.
    5. Bridge Information: Six bridge details were included on the Gallinas Creek. Bridge drawings were obtained from the New Mexico Department of Transportation and the relevant information was transcribed into the model.
    6. Soil: Gridded Soil Survey Geographic (gSSURGO) database.

Determine the Modeling Approach

  1. Determine which events will be modeled (historic or frequency events).
    1. In this case, a range of frequency events were modeled using a hypothetical storm meteorologic model in HEC-HMS.
      1. If estimating debris yield using HEC-HMS, the meteorological model selected will need to be compatible with the debris yield method. Some debris yield methods are related to flow while other methods are related to rainfall intensity.
      2. In this case, the hypothetical storm with precipitation-frequency grids was appropriate for use with the flow-based debris yield methods.
    2. In the HEC-RAS model, the 1% annual exceedance probability (AEP) event was modeled.
  2. Determine if the models will be calibrated given the availability of time, budget, and data.
    1. In this case, the pre-wildfire HEC-HMS model frequency event peak flows were calibrated to a discharge-frequency curve developed in HEC-SSP using observed data from a stream flow gage within the Gallinas Creek Watershed.
    2. The HEC-RAS model was not calibrated.

Determine How to Represent Post-Wildfire Conditions

Fires not only affect the vegetation canopy, but also impact the soils. The post-fire hydrologic model therefore needs to account for the reduced precipitation interception by the vegetation canopy and the forest litter/duff zone, the increased susceptibility of the soil from raindrop impact, and the decreased infiltration of the soils because of changes to the soil properties.

  1. With the SCS loss and transform approaches, these are accounted for by increasing the CN and decreasing the lag time. Increasing the CN translates to more surface runoff. More water on the surface results in higher velocities and shorter lag times.
  2. There are a number of methods available to adjust CN post-wildfire (see the following USDA web site for more information. These are briefly described below by geography:
    1. Montana: Cerrelli (2005) provides guidance for selecting post-fire CN based on burn severity and hydrologic soil group. This is based on experience with wildfires in the Bitteroot National Forest.
    2. Northern Plains: This includes Montana, northern Idaho, North Dakota, and the northern portion of South Dakota (U.S. Forest Service region 1). Guidance from U.S. Forest Service suggesting that high burn severity with water repellent soils should have a CN between 93-98 and high burn severity areas without water repellent soils should have a CN between 90 and 95.
    3. New Mexico: Livingston et al. (2005) describes an approach to transform CN after a wildfire based on experience with the 2000 Cerro Grande fire near Los Alamos, NM and the 2002 Long Mesa Fire near Mesa Verde National Park, CO.
    4. Arizona: U.S. Forest Service shared post-wildfire CNs used to estimate peak flow from the 2003 Aspen Fire. The values selected depend upon hydrologic soil group and burn severity. Note that this is not a comparison to actual watershed results.
    5. Utah: U.S. Forest Service shared guidance their BAER teams used to describe post-wildfire CN selection for the 2006 Warm Fire, UT and the 2007 Salt Creek Fire. The 2007 Salt Creek Fire used rules of thumb based on burn severity (e.g., high burn severity = pre fire NM + 15, moderate burn severity = pre fire CN +10, low burn severity = pre-fire CN + 5). The 2006 Warm Fire had a pre-fire CN of 80 and adjusted the CN post-wildfire for the high burn severity to 90 and the moderate burn severity to 85. The low burn severity stayed the same.
  3. To represent the post-wildfire hydrologic conditions, the basin loss and transform parameters need to be adjusted with measured flow data if data is available.
    1. In this case, a regionally specific approach to adjusting the CN values for the post-wildfire condition was taken based on a relationship developed in a study conducted by Livingston et al. in 2005 in New Mexico. The post-fire lag times were calculated based on the post-fire CN values.
  4. Due to the removal of vegetation and subsequent decrease in infiltration caused by wildfires, the debris yield from the watershed is expected to increase.
    1. Debris yield from the watershed can be estimated using several different methods in HEC-HMS.
      1. The subbasin surface erosion methods available in HEC-HMS are outlined here: https://www.hec.usace.army.mil/confluence/hmsdocs/hmsum/latest/erosion-and-sediment-transport/subbasin-sediment
      2. In this case, the debris yield (load and volume of debris) for the watershed was estimated in the HEC-HMS model using the LA Debris Equation 2-5 for each frequency event. The volume of water was estimated from the post-wildfire hydrograph for each frequency event. These values were used to compute a bulking factor to account for the debris expected to be generated as a result of the wildfire.
    2. The increase in debris yield from the burned watershed is expected to result in debris flows in rivers and streams.
      1. To account for the increase in volume due to the debris, inflow hydrographs can be multiplied by a bulking factor.
        1. In this case, the computed bulking factor from the HEC-HMS results was applied to the clear water post-wildfire hydrographs to bulk the flow for inundation mapping in HEC-RAS.
      2. As the volume of debris within water increases, the fluid begins to behave under the assumptions of non-Newtonian physics. The HEC-RAS modeling software (version 6.0 and later) contains the ability to model non-Newtonian debris flows and compute debris flow inundation.
        1. The debris yield and water volume from the HEC-HMS results can be used to compute the volumetric concentration for the watershed, which is an input parameter required for debris flow modeling in HEC-RAS.
        2. Non-Newtonian methods can be applied to 1D and 2D HEC-RAS models. The main limitation of the 1D non-Newtonian HEC-RAS model is that the computed water surface is constant across a cross section which does not show any debris mounding or runup that may occur. A 2D HEC-RAS model is able to capture these effects.
      3. When computing debris flow inundation in urban settings in HEC-RAS, modeling culverts, bridges, floating debris, and debris blockages, and adjusting roughness values should be considered. For the Gallinas 2D HEC-RAS model, the main bridges were included, as was a simplified diversion structure to an off-channel reservoir (Storrie Lake), but culverts and low water crossings were not. Simulations accounting for debris blocking the bridges was also not considered.



Livingston, R., Earles, T., and Wright, K., 2005. Los Alamos Post-Fire Watershed Recovery: A Curve-Number-Based Evaluation. Watershed Management Conference 2005, ASCE Library. https://ascelibrary.org/doi/10.1061/40763%28178%2941