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Title: Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty

Journal Article · · Water Resources Research
DOI:https://doi.org/10.1002/2015WR018266· OSTI ID:1327118
 [1];  [1];  [2]
  1. Washington State Univ., Richland, WA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
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In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. Furthermore, the results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); State of Washington Water Research Center
Grant/Contract Number:
AC05-76RL01830; G11AP20113
OSTI ID:
1327118
Alternate ID(s):
OSTI ID: 1402274
Report Number(s):
PNNL-SA-113964; KP1703030
Journal Information:
Water Resources Research, Vol. 52, Issue 4; ISSN 0043-1397
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 7 works
Citation information provided by
Web of Science

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Related Subjects

54 ENVIRONMENTAL SCIENCES
diagnostic modeling
structural uncertainty
Hierarchical Mixture of Experts
model averaging
model adequacy