Water Resources Professional Project Reports

Document Type

Report

Publication Date

Spring 2018

Abstract

Recent changes in climate have resulted in a decrease in precipitation and snowpack amounts and increased temperatures in the western United States. As the climate warms, there are also changes to runoff amounts and water availability. Drier and warmer conditions coupled with forest management practices have led to an increase in the frequency and size of forest fires. The 2000 Cerro Grande fire in Los Alamos, New Mexico burned over 43,000 acres and 200 structures. Eleven years later, the Las Conchas fire burned over 156,000 acres and 100 structures, including areas previously burned in 2000, and was considered the largest fire in New Mexico’s history. Both fires burned ponderosa, juniper, piñon and mixed conifer forests, resulting in dramatic decreases in vegetation, changes to surface soils, and alterations to the hydrologic cycle (decreased evapotranspiration, decreased infiltration, increased runoff volume and peak discharge, and decreased time to peak discharge) in surrounding watersheds. The frequency of large, intense “mega-fires” are predicted to increase, thus there is a potential for more post-fire flood damage and more surface water resources to be altered due to water quality issues. Burned Area Emergency Response (BAER) teams need to determine the flash-flood danger quickly to protect residents, fire fighters, BAER-team field personnel, and property at risk. The USGS developed an analytical method for predicting post-fire peak stormwater discharges using data collected from eight different fires throughout the western United States. This method included three methodologies: Level 1, Level 2, and Level 3 equations and each was used to predict post-Las Conchas peak discharges in watersheds across Los Alamos National Laboratory. Then, predicted peak discharges were compared to measured peak discharges. The accuracy of the three methods developed by the USGS, which require varying levels of data input and pre-processing effort were compared. Two other prediction methods, Automated Geospatial Watershed Assessment tool (AGWA), and the Rule of Thumb method by Kuyumjian were also used to calculate post-wildfire peak discharges. Each of the other three methods chosen, vary in amount of input data required, data processing and analysis times as well as usage preference by BAER teams. The three methods cover a wide range of prediction methods that could be used by or are currently used by BAER teams for post-fire peak-flow predictions. The results varied by canyon and precipitation intensity. Although there was no clear method that was accurate at predicting discharge for both low and high intensity precipitation events. The Kuyumjian equation worked well in majority of the canyons and required the least amount of pre-processing effort to get a discharge value. Considering the amount of pre-processing required for the data is significant with the other methods and the results were not consistently close to the measured discharge values, the Kuyumjian equation is a best method of the methods used.

Keywords

wildfire, fire prediction methods, New Mexico, forest fire

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