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Modeling Postfire Response and Recovery using the Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS) 1
Author(s) -
Cydzik Kristina,
Hogue Terri S.
Publication year - 2009
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2009.00317.x
Subject(s) - environmental science , watershed , storm , hydrology (agriculture) , surface runoff , hydrological modelling , hec hms , geology , climatology , ecology , geotechnical engineering , oceanography , machine learning , computer science , biology
This paper investigates application of the Army Corps of Engineers’ Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS) to a burned watershed in San Bernardino County, California. We evaluate the HEC‐HMS’ ability to simulate discharge in prefire and postfire conditions in a semi arid watershed and the necessary parameterizations for modeling hydrologic response during the immediate, and subsequent recovery, period after a wildfire. The model is applied to City Creek watershed, which was 90% burned during the Old Fire of October 2003. An optimal spatial resolution for the HEC‐HMS model was chosen based on an initial sensitivity analysis of subbasin configurations and related model performance. Five prefire storms were calibrated for the selected model resolution, defining a set of parameters that reasonably simulate prefire conditions. Six postfire storms, two from each of the following rainy (winter) seasons were then selected to simulate postfire response and evaluate relative changes in parameter values and model behavior. There were clear trends in the postfire parameters [initial abstractions ( I a ), curve number (CN), and lag time] that reveal significant (and expected) changes in watershed behavior. CN returns to prefire (baseline) values by the end of Year 2, while I a approaches baseline by the end of the third rainy season. However, lag time remains significantly lower than prefire values throughout the three‐year study period. Our results indicate that recovery of soil conditions and related runoff response is not entirely evidenced by the end of the study period (three rainy seasons postfire). Understanding the evolution of the land surface and related hydrologic properties during the highly dynamic postfire period, and accounting for these changes in model parameterizations, will allow for more accurate and reliable discharge simulations in both the immediate, and subsequent, rainy seasons following fire.