[1]HUANG Yanwei,LI Ying,ZHU Honglei,et al.Application of CFSR Dataset to Hydrological Simulation of Huifa River Basin[J].Research of Soil and Water Conservation,2021,28(01):300-306.
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Application of CFSR Dataset to Hydrological Simulation of Huifa River Basin
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
28
Number of periods:
2021 01
Page number:
300-306
Column:
Public date:
2021-01-10
- Title:
- Application of CFSR Dataset to Hydrological Simulation of Huifa River Basin
- CLC:
- P333
- DOI:
- -
- Abstract:
- Climate forecast system reanalysis(CFSR)is a global reanalysis data product retrieved by the U. S. National Environmental Prediction Center using the global prediction system, which includes the temperature, precipitation, wind speed, solar radiation and relative humidity data from 1979 to 2014. In previous studies, the influence of meteorological factors other than precipitation in CFSR dataset on the accuracy of basin water cycle simulation was seldom considered. On the basis of comparing the accuracy of CFSR dataset with the measured meteorological data, we used SWAT model to evaluate the suitability of CFSR dataset in Huifa River Basin from the perspectives of runoff and evapotranspiration simulation. The results showed that:(1)in terms of runoff simulation, the ranges of the daily and monthly scale R2 and NS produced by the CFSR dataset were 0.57～0.71 and 0.72～0.82, respectively, both of which performed well; CFSR dataset overestimated spring runoff to a certain extent, with a relative error of 32.61%;(2)using CFSR dataset as model input, the simulated PET and ET were higher than the results of the measured meteorological data; even if the precipitation data in CFSR were replaced by the measured precipitation data, ET was still overestimated to a certain extent. In conclusion, when applying CFSR dataset to watershed water cycle simulation, the accuracy of each meteorological factor in CFSR and its impact on the simulation results of each component of water cycle should be comprehensively evaluated. Comprehensive correction of each element in the dataset may lead to more accurate simulation results.
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Last Update:
2021-01-15