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    MELPF version 1: Modeling Error Learning based Post-Processor Framework for Hydrologic Models Accuracy Improvement

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    Author
    Wu, Rui; Yang, Lei; Chen, Chao; Ahmad, Sajjad; Dascalu, Sergiu M.; Harris, Frederick C. Jr
    Abstract
    This paper studies how to improve the accuracy of hydrologic models using machine-learning models as postprocessors and presents possibilities to reduce the workload to create an accurate hydrologic model by removing the calibration step. It is often challenging to develop an accurate hydrologic model due to the time-consuming model calibration procedure and the nonstationarity of hydrologic data. Our findings show that the errors of hydrologic models are correlated with model inputs. Thus motivated, we propose a modeling-error-learning-based post-processor framework by leveraging this correlation to improve the accuracy of a hydrologic model. The key idea is to predict the differences (errors) between the observed values and the hydrologic model predictions by using machine-learning techniques. To tackle the nonstationarity issue of hydrologic data, a moving window-based machine-learning approach is proposed to enhance the machine-learning error predictions by identifying the local stationarity of the data using a stationarity measure developed based on the Hilbert–Huang transform. Two hydrologic models, the Precipitation–Runoff Modeling System (PRMS) and the Hydrologic Modeling System (HEC-HMS), are used to evaluate the proposed framework. Two case studies are provided to exhibit the improved performance over the original model using multiple statistical metrics.
    URI
    http://hdl.handle.net/10342/8233
    Date
    2019-09-23
    Citation:
    APA:
    Wu, Rui, & Yang, Lei, & Chen, Chao, & Ahmad, Sajjad, & Dascalu, Sergiu M., & Harris, Frederick C. Jr. (September 2019). MELPF version 1: Modeling Error Learning based Post-Processor Framework for Hydrologic Models Accuracy Improvement. Geoscientific Model Development, (4115–4131. Retrieved from http://hdl.handle.net/10342/8233

    Display/Hide MLA, Chicago and APA citation formats.

    MLA:
    Wu, Rui, and Yang, Lei, and Chen, Chao, and Ahmad, Sajjad, and Dascalu, Sergiu M., and Harris, Frederick C. Jr. "MELPF version 1: Modeling Error Learning based Post-Processor Framework for Hydrologic Models Accuracy Improvement". Geoscientific Model Development. . (4115–4131.), September 2019. February 24, 2021. http://hdl.handle.net/10342/8233.
    Chicago:
    Wu, Rui and Yang, Lei and Chen, Chao and Ahmad, Sajjad and Dascalu, Sergiu M. and Harris, Frederick C. Jr, "MELPF version 1: Modeling Error Learning based Post-Processor Framework for Hydrologic Models Accuracy Improvement," Geoscientific Model Development 12, no. (September 2019), http://hdl.handle.net/10342/8233 (accessed February 24, 2021).
    AMA:
    Wu, Rui, Yang, Lei, Chen, Chao, Ahmad, Sajjad, Dascalu, Sergiu M., Harris, Frederick C. Jr. MELPF version 1: Modeling Error Learning based Post-Processor Framework for Hydrologic Models Accuracy Improvement. Geoscientific Model Development. September 2019; 12() 4115–4131. http://hdl.handle.net/10342/8233. Accessed February 24, 2021.
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