Algorithms - Generalized Likelihood Uncertainty Estimation (GLUE)

The OSTRICH generalize likelihood uncertainty estimation (GLUE) uncertainty algorithm

Initial Publication:

Modified:

This algorithm seeks to identify behavioral parameters set by randomly sampling and evaluating alternative parameter sets. The following optional group will configure the GLUE algorithm and will be processed if [ProgramType] is set to “GLUE”. 

BeginGLUE
SamplesPerIter    [nper]
NumBehavioral     [nsols]
MaxSamples        [nevals]
Threshold         [fmax]
EndGLUE

BeginGLUE
SamplesPerIter    10
NumBehavioral     10
MaxSamples        100
Threshold         1000
EndGLUE

Figure 1: General Format (left) and Example (right) of the GLUE Group

Where BeginGLUE and EndGLUE are parsing tags that wrap a set of algorithm configuration variables. These variables are described below:

  • SamplesPerIter: This variable controls the frequency of output within the OSTRICH run record. The current best solution will be reported after every SamplesPerIter model evaluations. The current number of behavioral solutions that have been discovered will also be reported. The default value is 10.
  • NumBehavioral: The desired number of behavioral solutions. The GLUE algorithm will halt if the desired number of behavioral solutions has been found or if the computational budget (i.e. MaxSamples) has been exhausted. The default value is 10.
  • MaxSamples: The maximum number of model evaluations allowed before the GLUE search is terminated. The default value is 100. However, studies have shown that GLUE can require 100,000 or more evaluations to discover a sufficiently representative number of behavioral samples.
  • Threshold: The threshold for separating behavioral and non-behavioral parameter sets. Parameter sets with corresponding objective function values less than the threshold will be considered behavioral. The default value is 1000.

References

Beven, K.,Binley, A. 1992. The future of distributed models: model calibration and uncertainty prediction. Hydrological Processes 6, 279-298.

Stedinger, J. R., Vogel, R. M., Lee, S. U.,Batchelder, R. 2008. Appraisal of the generalized likelihood uncertainty estimation (GLUE) method. Water Resources Research 44.