Status of Automatic Calibration for Hydrologic Models: Comparison with Multilevel Expert Calibration
- 1 April 1999
- journal article
- Published by American Society of Civil Engineers (ASCE) in Journal of Hydrologic Engineering
- Vol. 4 (2), 135-143
- https://doi.org/10.1061/(asce)1084-0699(1999)4:2(135)
Abstract
The usefulness of a hydrologic model depends on how well the model is calibrated. Therefore, the calibration procedure must be conducted carefully to maximize the reliability of the model. In general, manual procedures for calibration can be extremely time-consuming and frustrating, and this has been a major factor inhibiting the widespread use of the more sophisticated and complex hydrologic models. A global optimization algorithm entitled shuffled complex evolution recently was developed that has proved to be consistent, effective, and efficient in locating the globally optimal model parameters of a hydrologic model. In this paper, the capability of the shuffled complex evolution automatic procedure is compared with the interactive multilevel calibration multistage semiautomated method developed for calibration of the Sacramento soil moisture accounting streamflow forecasting model of the U.S. National Weather Service. The results suggest that the state of the art in automatic calibration now can be expected to perform with a level of skill approaching that of a well-trained hydrologist. This enables the hydrologist to take advantage of the power of automated methods to obtain good parameter estimates that are consistent with the historical data and to then use personal judgment to refine these estimates and account for other factors and knowledge not incorporated easily into the automated procedure. The analysis also suggests that simple split-sample testing of model performance is not capable of reliably indicating the existence of model divergence and that more robust performance evaluation criteria are needed.Keywords
This publication has 32 references indexed in Scilit:
- The quest for more powerful validation of conceptual catchment modelsWater Resources Research, 1997
- Efficient subspace probabilistic parameter optimization for catchment modelsWater Resources Research, 1997
- Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration dataJournal of Hydrology, 1996
- Optimal use of the SCE-UA global optimization method for calibrating watershed modelsJournal of Hydrology, 1994
- Parameter identification for a runoff model for forest roadsWater Resources Research, 1994
- Effective and efficient global optimization for conceptual rainfall‐runoff modelsWater Resources Research, 1992
- Membership-set estimation using random scanning and principal component analysisMathematics and Computers in Simulation, 1990
- On the validity of first-order prediction limits for conceptual hydrologic modelsJournal of Hydrology, 1988
- The relationship between data and the precision of parameter estimates of hydrologic modelsJournal of Hydrology, 1985
- River flow forecasting through conceptual models part I — A discussion of principlesJournal of Hydrology, 1970