Search

Highlights: [•] This paper examines the impacts of rain gauge densities on runoff simulations. [•] Variation of rain gauge densities impacts the areal mean rainfall considerably. [•] The locations of rain gauges impact the model performances considerably. [•] Great impacts on model performances occurring when rain gauges fall below 0.4 station per 1000km2. [Copyright &y& Elsevier]

Summary: In this study a rigorous evaluation and comparison of the difference in water balance simulations resulted from using different downscaling techniques, GCMs and hydrological models is performed in upper Hanjiang basin in China. The study consists of the following steps: (1) the NCEP/NCAR reanalysis data for the period 1961–2000 are used to calibrate and validate the statistical downscaling techniques, i.e. SSVM (Smooth Support Vector Machine) and SDSM (Statistical Downscaling Model); (2) the A2 emission scenarios from CGCM3 and HadCM3 for the same period are used as input to the statistical downscaling models; and (3) the downscaled local scale climate scenarios are then used as the input to the Xin-anjiang and HBV hydrological models. The results show that: (1) for the same GCM, the simulated runoffs vary greatly when using rainfall provided by different statistical downscaling techniques as the input to the hydrological models; (2) although most widely used statistics in the literature for evaluation of statistical downscaling methods show SDSM has better performance than SSVM in downscaling rainfall except the Nash–Sutcliffe efficiency (NSC) and root mean square error-observations standard deviation ratio (RSR), the runoff simulation efficiency driven by SDSM rainfall is far lower than by SSVM; and (3) by comparing different statistics in rainfall and runoff simulation, it can be concluded that NSC and RSR between simulated and observed rainfall can be used as key statistics to evaluate the statistical downscaling models’ performance when downscaled precipitation scenarios are used as input for hydrological models. [Copyright &y& Elsevier]

Abstract: Predicting hydrological variables in ungauged catchments has been singled out as one of the major issues in the hydrological sciences. In this study, the conceptual rainfall-runoff model, HBV, was applied to Dongjiang basin and its 13 sub-basins for the purposes of examining the applicability of this well-known model in south China and exploring the possibility of transferring the calibrated parameter values to ungauged basins. For testing the applicability of the model in gauged basins, the model was calibrated for a period of 1978–1983 and validated for a period of 1984–1988. For testing the transferability of parameter values to ungauged basins, two parameter regionalization methods – proxy-basins and global mean – were investigated. The results showed that: 1) the HBV model worked well in the Dongjiang basin with the average indexes of agreement (D) and coefficient of efficiency (ME), respectively, equal to 0.79 and 0.82 in the calibration period, and 0.76 and 0.78 in the validation period; 2) transferring the parameter values from basins that passed the cross-basin test with higher ME values to the hypothetical ungauged catchments produced acceptable results with an average ME value equals to 0.72; 3) compared with the proxy-basin method of parameter estimation, the model produced equally good results for the global mean method with an average ME value equals to 0.74 when using simple arithmetic mean values. Neither the area weighted mean method nor the Thiessen polygon method produced regional parameter values could markedly improve the accuracy of modeling results. It was concluded that both regionalization methods could effectively estimate parameters for ungauged catchments in the Dongjiang basin, and similar model performances were obtained. [Copyright &y& Elsevier]