In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics

Yang, Yuan; Pan, Ming; Beck, Hylke E.; Fisher, Colby K.; Beighley, R. Edward; Kao, Shih‐Chieh; Hong, Yang; Wood, Eric F.

doi:10.1029/2018WR024178

In Quest of Calibration Density and Consistency in Hydrologic Modeling: Distributed Parameter Calibration against Streamflow Characteristics

Journal Article · Fri Aug 30 00:00:00 EDT 2019 · Water Resources Research

DOI:https://doi.org/10.1029/2018WR024178· OSTI ID:1606834

^[1]; ^[2]; ^[2]; ^[2]; Beighley, R. Edward ^[3]; ^[4]; Hong, Yang ^[5]; ^[2]

Tsinghua Univ., Beijing (China); Princeton Univ., NJ (United States)
Princeton Univ., NJ (United States)
Northeastern Univ., Boston, MA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Tsinghua Univ., Beijing (China); Univ. of Oklahoma, Norman, OK (United States)

Conventional basin-by-basin approaches to calibrate hydrologic models are limited to gauged basins and typically result in spatially discontinuous parameter fields. Moreover, the consequent low calibration density in space falls seriously behind the need from present-day applications like high resolution river hydrodynamic modeling. In this study we calibrated three key parameters of the Variable Infiltration Capacity (VIC) model at every 1/8° grid-cell using machine learning-based maps of four streamflow characteristics for the conterminous United States (CONUS), with a total of 52,663 grid-cells. This new calibration approach, as an alternative to parameter regionalization, applied to ungauged regions too. A key difference made here is that we tried to regionalize physical variables (streamflow characteristics) instead of model parameters whose behavior may often be less well understood. The resulting parameter fields no longer presented any spatial discontinuities and the patterns corresponded well with climate characteristics, such as aridity and runoff ratio. The calibrated parameters were evaluated against observed streamflow from 704/648 (calibration/validation period) small-to-medium-sized catchments used to derive the streamflow characteristics, 3941/3809 (calibration/validation period) small-to-medium-sized catchments not used to derive the streamflow characteristics as well as five large basins. Comparisons indicated marked improvements in bias and Nash-Sutcliffe efficiency. Model performance was still poor in arid and semiarid regions, which is mostly due to both model structural and forcing deficiencies. Although the performance gain was limited by the relative small number of parameters to calibrate, the study and results here served as a proof-of-concept for a new promising approach for fine-scale hydrologic model calibrations.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1606834

Journal Information:: Water Resources Research, Journal Name: Water Resources Research Journal Issue: 9 Vol. 55; ISSN 0043-1397

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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