The ability to simulate coupled energy and water fluxes over large continental river basins, in particular streamflow, was largely nonexistent a decade ago. Since then, macroscale hydrological models (MHMs) have been developed, which predict such fluxes at continental and subcontinental scales. Because the runoff formulation in MHMs must be parameterized because of the large spatial scale at which they are implemented, some calibration of model parameters is inevitably necessary. However, calibration is a time-consuming process and quickly becomes infeasible when the modeled area or the number of basins increases. A methodology for model parameter transfer is described that limits the number of basins requiring direct calibration. Parameters initially were estimated for nine large river basins. As a first attempt to transfer parameters, the global land area was grouped by climate zone, and model parameters were transferred within zones. The transferred parameters were then used to simulate the water balance in 17 other continental river basins. Although the parameter transfer approach did not reduce the bias and root-mean-square error (rmse) for each individual basin, in aggregate the transferred parameters reduced the relative (monthly) rmse from 121% to 96% and the mean bias from 41% to 36%. Subsequent direct calibration of all basins further reduced the relative rmse to an average of 70% and the bias to 12%. After transferring the parameters globally, the mean annual global runoff increased 9.4% and evapotranspiration decreased by 5.0% in comparison with an earlier global simulation using uncalibrated parameters. On a continental basis, the changes in runoff and evapotranspiration were much larger. A diagnosis of simulation errors for four basins with particularly poor results showed that most of the error was attributable to bias in the Global Precipitation Climatology Project precipitation products used to drive the MHM.
|Original language||English (US)|
|Number of pages||17|
|Journal||Journal of Climate|
|State||Published - Aug 1 2001|
All Science Journal Classification (ASJC) codes
- Atmospheric Science