Multi-period calibration of a semi-distributed hydrological model based on hydroclimatic clustering

  1. Get@NRC: Multi-period calibration of a semi-distributed hydrological model based on hydroclimatic clustering (Opens in a new window)
DOIResolve DOI:
AuthorSearch for: ; Search for: ; Search for: ; Search for:
Journal titleAdvances in Water Resources
Pages12921303; # of pages: 12
SubjectClimatic conditions; Continuous simulation; Flow condition; Fuzzy C mean; Hydroclimatic; Hydrological models; Hydrological response; Hydrological simulations; Hydrological system; Hydrological years; Input datas; Multi-period; Parameter set; Principal Components; Spatial heterogeneity; SWAT; SWAT model; Temporal dynamics; Temporal scale; Time varying; Calibration; Computer simulation; Dynamics; Filter banks; Principal component analysis; calibration; climate change; climate effect; data set; fuzzy mathematics; hydrological modeling; parameterization; principal component analysis; watershed; Canada
AbstractChanging climatic conditions contribute to a time varying nature of hydrological responses over different temporal scales. The temporal dynamics of hydrological systems bring uncertainties into hydrological simulation which are different to uncertainties from spatial heterogeneity of soil and land use. This study develops a new approach to improve the calibration of hydrological based on hydroclimatic similarities. Six climatic indexes are integrated using Principal Component Analysis and Fuzzy C-mean Clustering methods to transform hydrological years into hydroclimatic periods. Parameter sets of SWAT model are calibrated independently for each period and used together to generate continuous simulation for a prairie watershed in southern Canada. Results indicate that the multi-period model exhibits comprehensive advantages over the traditional single-period model under various flow conditions. The simulation ability of the model is improved through using period-specific parameter sets in fitting the observations to compensate for deficiencies in the model structure or input data. © 2011 Elsevier Ltd.
Publication date
AffiliationNational Research Council Canada (NRC-CNRC); NRC Institute for Research in Construction (IRC-IRC)
Peer reviewedYes
NPARC number21271440
Export citationExport as RIS
Report a correctionReport a correction
Record identifier463a9c6d-6237-48b5-9a73-95647049135c
Record created2014-03-24
Record modified2016-05-09
Bookmark and share
  • Share this page with Facebook (Opens in a new window)
  • Share this page with Twitter (Opens in a new window)
  • Share this page with Google+ (Opens in a new window)
  • Share this page with Delicious (Opens in a new window)
Date modified: