Unravelling the potential of global streamflow reanalysis in characterizing local flow regime.

Sci Total Environ

Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Civil Engineering, Sun Yat-Sen University, Guangzhou, China. Electronic address:

Published: September 2022

While global streamflow reanalysis provides valuable information for environmental modelling and management, it is not yet known how effective they are in characterizing the local flow regime. This paper presents a novel evaluation of the potential of streamflow reanalysis in the flow regime analysis by accounting for the effects of reservoir operation. Specifically, the indicators of hydrologic alteration (IHA) are used to characterize the five components of flow regime for both reservoir inflow and outflow; the performance of raw reanalysis is evaluated and the raw reanalysis is furthermore corrected by using the quantile mapping for improved flow regime analysis. The results of 35 major reservoirs in California show that raw reanalysis tends to be effective in characterizing the regime of reservoir inflow and that it is generally less effective in capturing outflow. For both inflow and outflow, the performance of raw reanalysis is beset by the existence of systematic errors. The quantile mapping is effective in error correction and therefore considerably improves the performances of reanalysis in characterizing the regime of not only reservoir inflow but also outflow. Nevertheless, for both reservoir inflow and outflow, the low flow part tends to be more difficult to handle than the high flow part. The evaluation conducted in this paper can serve as a roadmap for further exploitations of the potential of global streamflow reanalysis for flow regime analysis at regional and even continental scales.

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http://dx.doi.org/10.1016/j.scitotenv.2022.156125DOI Listing

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