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Effect of Distinct Evaluation Objectives on Different Precipitation Downscaling Methods and the Corresponding Potential Impacts on Catchment Runoff Modelling

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Abstract

As an essential tool to bridge the gap between climatic output and hydrological input, the precipitation spatial downscaling (PSD) method exhibits divergent performance in terms of different evaluation objectives. This study compared and analysed the performance of the three PSD methods using two evaluation objectives - precipitation (P) and possible effective precipitation (PEP), and evaluated the effect of different downscaled precipitation on regional flow simulation by constructing an ideal model and a real case based on the Vertical Mixed Runoff (VMR) model. Results show that when the evaluation objective changes from P to PEP, the Artificial Neural Network replaces the Weather Research & Forecasting Model as the dominant PSD model. In spatial analysis, the statistical PSD models perform significantly better when using PEP, compared to P. In temporal analysis, the PEP biases are more stable compared to the P biases from the same PSD model. The validation in the ideal case and the actual basin further proves that taking PEP as the evaluation objective can improve the reliability of the PSD method selection for hydrological research.

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Data Availability

The observation of daily precipitation and evaporation from the year 2006 to 2017 are openly available from the National Meteorological Information Center at http://data.cma.cn. All the climate datasets are from the NCAR Community Earth System Model (CESM CMIP5) datasets at https://rda.ucar.edu/datasets/ds316.1/.

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Acknowledgements

The study is financially supported by the National Key Research and Development Program of China (2019YFC0409000), the National Natural Science Foundation of China (52179011), and the Fundamental Research Funds for the Central Universities (2019B41014). Besides, this paper was supported by the High Performance Computing Platform of Hohai University, China.

Funding

The study was financially supported by the National Key Research and Development Program of China (Grant number 2019YFC0409000), the National Natural Science Foundation of China (Grant number 52179011), the Fundamental Research Funds for the Central Universities (Grant number 2019B41014).

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Authors and Affiliations

  1. College of Hydrology and Water Resources, Hohai University, Nanjing, Jiangsu, China

    Xumin Zhang, Simin Qu, Jijie Shen, Yingbing Chen, Peng Jiang & Peng Shi

  2. The Experimental Teaching Center of Water Resources, Hohai University, Nanjing, Jiangsu, China

    Simin Qu, Peng Jiang & Peng Shi

  3. Department of Aquatic Ecosystem Analysis and Management, Helmholtz Centre for Environmental Research – UFZ, Magdeburg, Germany

    Xiaoqiang Yang

  4. Department of Ecohydrology and Biogeochemistry, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, Germany

    Xiaoqiang Yang

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  1. Xumin Zhang
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Xumin Zhang, Simin Qu and Jijie Shen. The first draft of the manuscript was written by Xumin Zhang. Yingbing Chen, Xiaoqiang Yang, Peng Jiang and Peng Shi commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Peng Shi.

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Appendix

Appendix

Fig. 5
figure 5

The curve of Similarity level and Number of clustering

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Table 3 The parameters of VMR model
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Table 4 Mean Absolute Deviation Statistics Table of Average Daily Runoff (mm/day)
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Zhang, X., Qu, S., Shen, J. et al. Effect of Distinct Evaluation Objectives on Different Precipitation Downscaling Methods and the Corresponding Potential Impacts on Catchment Runoff Modelling. Water Resour Manage 37, 1913–1930 (2023). https://doi.org/10.1007/s11269-023-03462-8

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