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Abstract

Changes in river discharge regimes are regarded as the primary drivers of change of many in-stream ecological processes. While a lot of assessments addressing the hydrological alteration caused by human activities have been conducted for many river basins worldwide, a comprehensive analysis of hydrological alteration over major river basins worldwide under climate change is still limited to date. This study aims to address multi-dimensional hydrological alterations (alterations of multiple river flow characteristics) under climate change for four major rivers on three continents, by means of a consolidated framework consisting of two hydrological models, bias-corrected scenarios from five general circulation models (GCMs), and three Representative Concentration Pathways (RCPs) scenarios. The multi-dimensional hydrological alterations are quantified via the general Indicators of Hydrological Alteration approach (IHA) and two modified IHA methods based on dimensionality reduction. The reliability and advantages for the modified IHA methods are also analyzed. The results show that: (1) A modified IHA method (“NR-IHA method”) where the selected non-redundant IHA indices are basin specific is a valid alternative to the conventional IHA method for evaluating flow regime alteration, in consideration that high agreements in the simulated overall flow regimes alteration degree between it and the conventional IHA method are found during historical and future scenario periods, over four basins (the Upper Yellow River, the Lena River, the Tagus River and the Upper Amazon River). (2) Climate change is expected to remarkably alter overall flow regimes in the Tagus River and Upper Yellow River, especially at the end of the 21st century and under high RCP scenarios, whereas the dominant alteration extent tends to be low in the Lena River and Upper Amazon River in the two future periods. (3) The modified IHA method, preventing double-counting some aspects of the flow regime when assessing alteration degree of overall flow regimes, can save 65 % computation time and is more efficient than the conventional IHA method. It could be beneficial to figure out adaptive countermeasures for water resource management and restoration of eco-environmental systems under climate change.