Comparison of NCEP-CFSR and CMADS for Hydrological Modelling Using SWAT in the Muda River Basin, Malaysia (original) (raw)
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Acta Horticulturae, 2017
Paddy rice is an important food crop in Malaysia providing food for the nation and yet its water demand is relatively high compared with the other crops. Increasing the problem are concerns about uncertainties in crop water demands, rainfall patterns and stream flows owing to climate change effects. Thus, predicting flows while accounting for climate change is critical in future. However, due to poor meteorological records in many catchments, a previous study presented a new meteorological data set gridded from daily observation data countrywide. In this study, the stream flow simulation for the Bernam River Basin was assessed using this data set as inputs to the soil and water assessment tool (SWAT) model. Flow calibration was done for 17 years and validation was performed for 8 years. The results showed that simulated values matched well with enhanced data values with (), NSE and PBIAS being 0.67, 0.62 and-9.4 for the calibration period and 0.62, 0.61 and-4.2 for the validation period. The study shows that the new data is applicable in the Bernam watershed, and that the SWAT model was able to predict flows reasonably well with these data, thus can be used to study future impacts on stream flow of this river.
Precipitation and temperature are significant inputs for hydrological models. Currently, many satellite and reanalysis precipitation and air temperature datasets exist at different spatio-temporal resolutions at a global and quasi-global scale. This study evaluated the performances of three open-access precipitation datasets (gauge-adjusted research-grade Global Satellite Mapping of Precipitation (GSMaP_Gauge), Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), Climate Forecast System Reanalysis(CFSR)) and CFSR air temperature dataset in driving the Soil and Water Assessment Tool (SWAT) model required for the monthly simulation of streamflow in the upper Shiyang River Basin of northwest China. After a thorough comparison of six model scenarios with different combinations of precipitation and air temperature inputs, the following conclusions were drawn: (1) Although the precipitation products had similar spatial patterns, however, CFSR differs significantly by s...
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Quaternary International, 2010
Available online xxx a b s t r a c t Gridded climate data sets are widely used in the analysis, modeling and forecasting of the consequences of climate change. The objective of this study is to compare the impact of different climate datasets (station vs. gridded) on the parameterization of a hydrological model (developed using SWAT2005) of the River Xiangxi, the largest tributary of Yangtze River in the Hubei part of the Three Gorges Reservoir. Climate data used in this study derive from two sources: point daily observations from the Xingshan meteorological station (STN) and gridded (0.5 Â 0.5 ) monthly observations of the CRU TS3.0 global dataset (CRU) downscaled to daily data using a weather generator. Data from 1970 to 1974 were applied for sensitivity analyses and autocalibration and subsequently validate hindcasts over the period [1976][1977][1978][1979][1980][1981][1982][1983][1984][1985][1986]. Despite there being only slight differences in mean annual precipitation (1003 mm vs. 1052 mm) between STN and CRU, the data differ more in their estimates of the number of rain days (136 vs. 112) and wet days standard deviation (11.75 mm vs. 18.49 mm). The mean, maximum and minimum temperatures from CRU are all lower than those from STN. SWAT parameter sensitivity analysis results show slight differences in the relative rank of the most sensitive parameters, with the differences mainly caused by the lower temperature and more intensive rainfall in CRU relative to STN. Autocalibrated parameters showed very similar values, except for the surface runoff lag coefficient which is higher for the CRU dataset compared to that derived from the STN dataset. Statistic results for discharge simulated based on CRU compared rather well with that based on STN CRU as evaluated using the standard statistics of the Nash-Sutcliffe efficiency, coefficient of determination, and percent error. The sensitivity analysis and autocalibration tool embedded in SWAT2005 is a powerful utility in hydrological modeling of the River Xiangxi, and the CRU dataset appears to be appropriate for application to hydrological modeling in this case, thus providing a good basis for climate change studies.
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Journal of Hydroinformatics, 2015
High-resolution satellite precipitation products, which can provide a reasonable depiction of the spatial extent of rainfall, have been increasingly used to model hydrological processes. In this study, we introduced important satellite rainfall data – Fengyun (FY) precipitation product, and evaluated the data through streamflow simulation using the Soil and Water Assessment Tool model in Huifa River basin, China. Three precipitation inputs were conducted to investigate the simulation performance of the FY precipitation product: (1) available rain gauges within the watershed; (2) pixel values of FY-2 precipitation products nearest to the geographic centers of the subbasins; and (3) mean values of FY-2 precipitation pixels within the subbasins. The results showed that good model performance (defined as: NSE > 0.75; Nash–Sutcliffe efficiency: NSE) was achieved for all precipitation inputs both in the calibration and validation period. Best streamflow simulation was obtained when the ...
Journal of Hydrometeorology, 2014
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