Application of error analysis to a Marsh Hydrology Model

Application of error analysis to a Marsh Hydrology Model The contribution of errors on individual parameters to uncertainties in model predictions is studied in a hydrologic model of a marsh. Daily values of water level and storage are calculated in the model as a function of precipitation, storm runoff from the urban watershed, physical properties of soil, groundwater movement, and daily values of evapotranspiration. Errors associated with each parameter were propagated through the model calculations by Monte Carlo simulation. The distribution of each hydrologic parameter, considered as a random variable, was specified by mean, variance, maximum, and minimum values. Random numbers drawn from these distributions were used to simulate 244 days of water level and storage in the marsh. Errors for the marsh model are bounded, returning toward zero rather than growing monotonically through time. Although the simulations show considerable error for some days, the overall behavior of the model is robust. The seasonal contribution of specific parameters has important implications for model calibration and validation. Our analysis indicates that Monte Carlo analysis using actual estimates of parameter error leads to different conclusions than sensitivity analysis. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Water Resources Research Wiley

Application of error analysis to a Marsh Hydrology Model

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Publisher
Wiley
Copyright
Copyright © 1980 by the American Geophysical Union.
ISSN
0043-1397
eISSN
1944-7973
D.O.I.
10.1029/WR016i004p00659
Publisher site
See Article on Publisher Site

Abstract

The contribution of errors on individual parameters to uncertainties in model predictions is studied in a hydrologic model of a marsh. Daily values of water level and storage are calculated in the model as a function of precipitation, storm runoff from the urban watershed, physical properties of soil, groundwater movement, and daily values of evapotranspiration. Errors associated with each parameter were propagated through the model calculations by Monte Carlo simulation. The distribution of each hydrologic parameter, considered as a random variable, was specified by mean, variance, maximum, and minimum values. Random numbers drawn from these distributions were used to simulate 244 days of water level and storage in the marsh. Errors for the marsh model are bounded, returning toward zero rather than growing monotonically through time. Although the simulations show considerable error for some days, the overall behavior of the model is robust. The seasonal contribution of specific parameters has important implications for model calibration and validation. Our analysis indicates that Monte Carlo analysis using actual estimates of parameter error leads to different conclusions than sensitivity analysis.

Journal

Water Resources ResearchWiley

Published: Aug 1, 1980

References

  • Stochastic analysis of steady state groundwater flow in a bounded domain, 1, One‐dimensional simulations
    Smith, Smith; Freeze, Freeze

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