Evaluation of Regionalization Methods for Hourly Continuous Streamflow Simulation Using Distributed Models in Boreal Catchments.

Regionalization for prediction in ungauged basins at hourly resolution is important for water resources management (e.g., floods and hydropeaking). In the research reported in this paper, calibration of 26 catchments (39-3,090 km²) in mid-Norway was performed using hourly records and three spatially distributed (1 × 1 km²) precipitation-runoff models, as follows: (1) first-order nonlinear system model, (2) Hydrologiska Byråns Vattenballansavdelning (HBV) model, and (3) basic grid model. Four regionalization methods for each model [(1) parameter set yielding maximum regional weighted average performance measures (PMs), (2) regional median of optimal parameters, (3) nearest neighbor (NN), and (4) physical similarity (PS)] were evaluated and compared with three benchmarks. Parameter transfer from best regional donor and from an ideal best arbitrary single-donor, and local calibration (LC) were as benchmarks. The PS attributes include hypsometric curves, land use, drainage density, catchment area, terrain slope, bedrock geology, soil type, and combination of all. Comprehensive evaluation of single-donors and multidonors, simple benchmarks, and more advanced regionalization methods using multimodels, two PMs, and their statistical evaluation indicate that the identification of regionalization methods is dependent on the models, the PM, and their statistical evaluation. In general, the hypsometric curves, land use, and best regional donor methods performed better for the Nash-Sutcliffe efficiency based on boxplots and regional median values of both the Nash-Sutcliffe efficiency and relative deterioration or improvement of the Nash-Sutcliffe efficiency from the LC due to the regionalization. The methods also performed better for the individual catchments. The terrain slope, regional median of optimal parameters, maximum regional weighted average, and best regional donor methods performed better for the natural-logarithm-transformed streamflow (i.e., regarding the Nash-Sutcliffe efficiency) based on the same evaluation criteria. Similar performance to the more advanced regionalization methods of transfer of homogeneous parameter sets across the whole region from the best regional donor for both Nash-Sutcliffe efficiency and natural-logarithm-transformed streamflow (i.e., regarding the Nash-Sutcliffe efficiency) indicate the potential of the simple regionalization approach for predicting runoff response in the region. [ABSTRACT FROM AUTHOR]