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Preprints
https://doi.org/10.5194/essd-2019-178
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-178
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 07 Nov 2019

Submitted as: data description paper | 07 Nov 2019

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A revised version of this preprint is currently under review for the journal ESSD.

Development of Asia Pacific Weather Statistics (APWS) dataset for use in Soil and Water Assessment Tool (SWAT) simulation

Uttam Ghimire, Taimoor Akhtar, Narayan Shrestha, and Prasad Daggupati Uttam Ghimire et al.
  • College of Engineering and Physical Sciences, University of Guelph, Ontario, N1G2W1, Canada

Abstract. The application of Soil and Water Assessment Tool (SWAT) for hydrological modelling in Asia Pacific region is immense. However, a robust modelling practice is often constrained by limited amount and quality of weather data. In such conditions, SWAT uses an inherent statistical weather generator to generate synthetic series of weather inputs for which, long-term precise weather statistics are needed. This study presents a high-resolution Asia Pacific Weather Statistics (APWS) dataset in a format ready to be used in SWAT simulations.

The APWS dataset consists of rainfall statistics from Asian Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) project at 0.25° and remaining weather statistics from Climate Forecast System Reanalysis (CFSR) at 0.38°. The utility of APWS is evaluated by comparing its performance with established CFSR statistics for daily flow simulation in two river basins of South Asia; Narayani in Nepal and Wangchhu in Bhutan. The comparison is done on different precipitation data availability scenarios, where for each scenario, a specified percentage of historical precipitation data is removed and replaced by synthetic precipitation data, generated by SWAT’s inherent weather generator with weather statistics from i) APWS and ii) CFSR independently.

The results indicated a clear outperformance of APWS over CFSR dataset in rainfall reconstruction, especially in the smaller sub-basins. Statistics like probability of wet day following wet day, mean monthly rainfall and number of rainy days were found sensitive for better reconstruction of rainfalls series in the study river basins, inferring the advantage of using precise rainfall statistics. The APWS dataset is expected to contribute in better reconstruction of weather series needed for hydrological modeling using SWAT in the Asia Pacific region, and is publicly available at https://hydra-water.shinyapps.io/APWS/ or https://doi.org/10.5281/zenodo.3460766 (Ghimire et al., 2019).

Uttam Ghimire et al.

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Uttam Ghimire et al.

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APWS Web Portal U. Ghimire, T. Akhtar, N. Shrestha, and P. Daggupati https://doi.org/10.5281/zenodo.3460766

Uttam Ghimire et al.

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Short summary
The lack of availability of detailed historical weather data is a significant hindrance to development of robust hydrological models for the Asia Pacific (AP) Region. The Soil and Water Assessment Tool (SWAT) is a popular model in the region that fills weather data gaps in data scarce scenarios. This paper presents the Asia Pacific Weather Statistics (APWS) dataset, that is designed for SWAT and provides a more accurate weather data gap filling mechanism than SWAT's default dataset.
The lack of availability of detailed historical weather data is a significant hindrance to...
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