Quantifying the space – time variability of water balance components in an agricultural basin using a process-based hydrologic model and the Budyko framework
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Quantifying the space – time variability of water balance components in an agricultural basin using a process-based hydrologic model and the Budyko framework

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  • Journal Title:
    Science of The Total Environment
  • Personal Author:
  • NOAA Program & Office:
    OAR (Oceanic and Atmospheric Research)
  • Description:
    Process-based distributed hydrologic models (PBHMs), which link watershed characteristics with process representations, are useful tools to evaluate distributed and ensemble hydrologic responses of a basin to climate inputs. However, complexities associated with parameter interactions and their spatial heterogeneity may introduce high uncertainty in the parameterization of a PBHM. The Budyko curve framework offers an effective approach for evaluating the variability in the water balance components from a PBHM and can be used to explore the link between model performance with parameter heterogeneities and the Budyko curve characteristics. In this work a PBHM was calibrated using a multi-site calibration strategy, which was built upon a step-wise calibration algorithm combined with multiple calibration targets including river discharges, evapotranspiration and ground water heads, to reduce compensation errors caused by component interactions. This strategy was used for the Kalamazoo River watershed in Michigan, USA, with obvious physiographic and land surface heterogeneities. The Budyko framework characterized the water balance variability at the sub-watershed scale; two empirical methods were used to evaluate the calibrated PBHM parameters using Budyko-estimated values and to assess the physical relevance of the parameters. The relative infiltration capacity is found to play an important role in affecting the spatial variability of the annual water balance of this watershed. This work brings out the importance of optimizing calibration strategies by linking catchment heterogeneities with processes reasoning in order to understand the underlying hydrologic controls.
  • Keywords:
  • Source:
    Science of The Total Environment, 676, 176-189
  • DOI:
  • ISSN:
    0048-9697
  • Format:
    PDF
  • Publisher:
    Elsevier BV
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA12OAR4320071
  • Rights Information:
    Accepted Manuscript
  • Compliance:
    Library
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