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a b s t r a c tThe floc formation, structure and strength remain a problematic topic to be addressed clearly to guide the flocculator design. To study the relationship among floc structure, strength, size distribution, and fractal dimensions, the alum-kaolin flocs formed under different coagulation stages and mechanisms were investigated at various agitation rates. A new method based on the fractal theory was employed to analyze the strength of flocs. The relationship between fractal dimensions and floc size distribution was then discussed with controlled experiments, providing comparison between calculation results of the new method and the strength factor as well. The results show that both size and fractal dimension of flocs decrease with increasing shear rate. The floc strength follows the hierarchy: gradually increased shear rate from 40 rpm to 60 rpm > stable 60 rpm shear rate > gradually decreased shear rate from 60 rpm to 40 rpm > stable 40 rpm shear rate. Flocs formed under gradual shear increasing could easily re-flocculate and recover their strength after breakage.

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Global Climate Models (GCMs) can provide essential meteorological data as inputs for simulating and assessing the impact of climate change on catchment hydrology. However, downscaling of GCM outputs is often required due to their coarse spatial and temporal resolution. As an effective downscaling method, stochastic weather generators can reproduce daily sequences with statistically similar statistical characteristics. Most weather generators can only simulate single-site meteorological data, which are spatially uncorrelated. Therefore, this study introduces a method for multi-site precipitation downscaling based on a combination of a single-site stochastic weather generator, CLIGEN (CLImate GENerator), and a modified shuffle procedure constrained with multi-model ensemble GCM monthly precipitation outputs. The applicability of the downscaling method is demonstrated in the Huangfuchuan Basin (arid to semi-arid climate) for a historical period (1976–2005) and a projection period (2021–2070, historical, the representative concentration path (RCP) 2.6, RCP4.5, RCP4.8 scenarios) to generate spatially correlated daily precipitation. The results show that the proposed downscaling method can accurately simulate the mean of daily, monthly and annual precipitation and the wet spell lengths, and the inter-station correlation among 10 sites in the basin. In addition, this combination method generated the projected precipitation and showed an increasing trend for future years. These findings could help us better cope with the potential risks of climate change.