Literature DB >> 34225158

Attribution of streamflow changes across the globe based on the Budyko framework.

Jianyu Liu1, Yuanyuan You2, Qiang Zhang3, Xihui Gu4.   

Abstract

Differentiating and clarifying the driving factors behind streamflow changes are critical for highlighting hydrological responses to changing environments. However, due to the limited number of hydrological stations, the dominant factor controlling global observed streamflow change remains unclear and intensely debated. Here, we revisit this scientific issue by using the most comprehensive dataset to attribute the observed global streamflow changes during 1960-2014. The results suggest that other factors than precipitation (P) and potential evaporation (E0) are the most important contributors to global observed streamflow changes, which dominate streamflow change for 48.9-50.9% of the stations. In contrast, the dominant factor translated into P in 72.3-72.9% of stations when using reconstructed streamflow datasets, in agreement with most previous global assessments. These differences indicate that streamflow attributions using reconstructed streamflow might overestimate the effects of P while underestimating the roles of other factors, such as the vegetation and human impact. At the global scale, the other factors affected by many catchment characteristics and their impacts on streamflow change have remarkable regional differences. This study highlights the necessity to apply the observed data in streamflow attribution to avoid biased conclusions regarding the dominant factor of streamflow changes.
Copyright © 2021. Published by Elsevier B.V.

Entities:  

Keywords:  Attribution analysis; Dominant factor; Global streamflow; Observed streamflow

Year:  2021        PMID: 34225158     DOI: 10.1016/j.scitotenv.2021.148662

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Attribution Assessment and Prediction of Runoff Change in the Han River Basin, China.

Authors:  Mengru Wei; Zhe Yuan; Jijun Xu; Mengqi Shi; Xin Wen
Journal:  Int J Environ Res Public Health       Date:  2022-02-18       Impact factor: 3.390

  1 in total

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