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A Protocol for Conducting Rainfall Simulation to Study Soil Runoff
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[Parameter uncertainty analysis for urban rainfall runoff modelling].

Jin-Liang Huang1, Jie Lin, Peng-Fei Du

  • 1Fujian Provincial Key Laboratory of Coastal Ecology and Environmental Studies, Xiamen University, Xiamen 361005, China. jlhuang@xmu.edu.cn

Huan Jing Ke Xue= Huanjing Kexue
|September 26, 2012
PubMed
Summary
This summary is machine-generated.

This study identified key parameters for urban stormwater runoff modeling using SWMM. Dstore-Imperv, Curve Number (CN), and Dstore-Perv were most influential in hydrological and hydraulic processes.

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Area of Science:

  • Environmental Engineering
  • Hydrology
  • Urban Planning

Background:

  • Urban stormwater runoff modeling is crucial for managing water resources and mitigating pollution.
  • Parameter uncertainty analysis is essential for improving the accuracy and reliability of these models.
  • The Storm Water Management Model (SWMM) is widely used for urban hydrological and water quality simulations.

Purpose of the Study:

  • To perform parameter uncertainty analysis for urban stormwater runoff modeling.
  • To identify and assess the sensitivity of model parameters using Monte-Carlo sampling and Regionalized Sensitivity Analysis (RSA).
  • To evaluate parameter identifiability in both hydrological/hydraulic and water quality modules of SWMM.

Main Methods:

  • Utilized the Storm Water Management Model (SWMM) for urban stormwater runoff simulation.
  • Employed Monte-Carlo sampling to generate parameter ensembles.
  • Applied the Regionalized Sensitivity Analysis (RSA) algorithm to determine parameter identifiability and sensitivity.

Main Results:

  • Identified Dstore-Imperv, Dstore-Perv, and Curve Number (CN) as the most identifiable parameters in the hydrological and hydraulic module, with Dstore-Imperv > CN > Dstore-Perv.
  • In the water quality module, Coefficient and Exponent of the exponent washoff model, and Max. Buildup of the saturation buildup model were found to be identifiable parameters.
  • Rate constant parameters showed lower identifiability compared to Max. Buildup, Coefficient, and Exponent.

Conclusions:

  • Dstore-Imperv, CN, and Dstore-Perv are critical parameters for accurate hydrological and hydraulic modeling of urban stormwater runoff.
  • Specific parameters within the exponent washoff and saturation buildup models are key for reliable water quality predictions.
  • The study provides a robust framework for parameter uncertainty analysis in SWMM, enhancing its application in urban water management.