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Toward improved calibration of hydrologic models: Combining the strengths of manual and automatic methods
Author(s) -
Boyle Douglas P.,
Gupta Hoshin V.,
Sorooshian Soroosh
Publication year - 2000
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2000wr900207
Subject(s) - computer science , calibration , hydrograph , aggregate (composite) , range (aeronautics) , key (lock) , statistic , hydrological modelling , data mining , engineering , statistics , mathematics , geology , ecology , materials science , computer security , climatology , surface runoff , composite material , biology , aerospace engineering
Automatic methods for model calibration seek to take advantage of the speed and power of digital computers, while being objective and relatively easy to implement. However, they do not provide parameter estimates and hydrograph simulations that are considered acceptable by the hydrologists responsible for operational forecasting and have therefore not entered into widespread use. In contrast, the manual approach which has been developed and refined over the years to result in excellent model calibrations is complicated and highly labor‐intensive, and the expertise acquired by one individual with a specific model is not easily transferred to another person (or model). In this paper, we propose a hybrid approach that combines the strengths of each. A multicriteria formulation is used to “model” the evaluation techniques and strategies used in manual calibration, and the resulting optimization problem is solved by means of a computerized algorithm. The new approach provides a stronger test of model performance than methods that use a single overall statistic to aggregate model errors over a large range of hydrologie behaviors. The power of the new approach is illustrated by means of a case study using the Sacramento Soil Moisture Accounting model.