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A Hybrid of Copula Prediction and Time Series Computation to Estimate Stream Discharge Based on Precipitation Data

Formally Refereed

Abstract

Stream discharge is a key hydrological factor for water supply planning, wetland loss investigation,ecological service assessment, and climate change impact estimation. Conceptually, stream discharge is expected to be highly and positively related to precipitation. In reality, however, such a relationship may be weakerbecause precipitation characteristics are affected by local climate of watersheds. For many watersheds aroundthe world, a vast amount of precipitation data are readily available but the stream discharge data are very lim-ited or unavailable. It would be time-saving and cost-effective to predict stream discharge based on precipitationdata. Unfortunately, this task is very difficult to achieve using the traditional methods. Although the copulamethod is able to establish a good relationship (or a good dependence structure) between discharges and precipi-tations, this relationship does not include the time series process, and thus is impractical for applications.Therefore, a hybrid of copula prediciton and time series computation was developed (with detailed procedures)here to estimate stream discharge based on precipitation data. The method was validated using the measureddaily discharges with the good statistical measures, that is, the Kandell's τ(0.42-0.44), normalized root meansquare error (2.19-2.28 m3/s), andR2(0.66-0.84). This study suggests that the hybrid method is a useful tool topredict stream discharges based on precipitation data.

Keywords

algorithm, copula, discharge, method, precipitation, watershed

Citation

Ouyang, Ying. 2022. A Hybrid of Copula Prediction and Time Series Computation to Estimate Stream Discharge Based on Precipitation Data. JAWRA Journal of the American Water Resources Association. 58(3): 471-484. https://doi.org/10.1111/1752-1688.13003.
Citations
https://www.fs.usda.gov/research/treesearch/64550