4.3 Article

Event and Continuous Hydrologic Modeling with HEC-HMS

期刊

出版社

ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)0733-9437(2009)135:1(119)

关键词

Watersheds; Hydrologic models; Geographic information systems; Runoff

资金

  1. Michigan Department of Environmental Quality
  2. Grand Valley State University

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Event hydrologic modeling reveals how a basin responds to an individual rainfall event (e. g., quantity of surface runoff, peak, timing of the peak, detention). In contrast, continuous hydrologic modeling synthesizes hydrologic processes and phenomena (i.e., synthetic responses of the basin to a number of rain events and their cumulative effects) over a longer time period that includes both wet and dry conditions. Thus, fine-scale event hydrologic modeling is particularly useful for understanding detailed hydrologic processes and identifying the relevant parameters that can be further used for coarse-scale continuous modeling, especially when long-term intensive monitoring data are not available or the data are incomplete. Joint event and continuous hydrologic modeling with the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) is discussed in this technical note and an application to the Mona Lake watershed in west Michigan is presented. Specifically, four rainfall events were selected for calibrating/verifying the event model and identifying model parameters. The calibrated parameters were then used in the continuous hydrologic model. The Soil Conservation Service curve number and soil moisture accounting methods in HEC-HMS were used for simulating surface runoff in the event and continuous models, respectively, and the relationship between the two rainfall-runoff models was analyzed. The simulations provided hydrologic details about quantity, variability, and sources of runoff in the watershed. The model output suggests that the fine-scale (5 min time step) event hydrologic modeling, supported by intensive field data, is useful for improving the coarse-scale (hourly time step) continuous modeling by providing more accurate and well-calibrated parameters.

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