Qiang Zhang

Monthly sediment load and streamflow series spanning 1963–2004 from four hydrological stations situation in the main stem of the Yangtze River, China, are analysed using scanning t‐test and the simple two‐phase linear regression scheme. Results indicate significant changes in the sediment load and streamflow from the upper reach to the lower reach of the Yangtze River. Relatively consistent positive coherency relations can be detected between streamflow and sediment load in the upper reach and negative coherency in the middle and lower reaches. Interestingly, negative coherency is found mainly for larger time scales. Changes in sediment load are the result mainly of human influence; specifically, the construction of water reservoirs may be the major cause of negative coherency. Accentuating the human influence from the upper to the lower reach results in inconsistent correlations between sediment load and streamflow. Decreasing sediment load being observed in recent years has the potential to alter the topographical properties of the river channel and the consequent development and recession of the Yangtze Delta. Results of this study are of practical significance for river channel management and evaluation of the influence of human activities on the hydrological regimes of large rivers. Copyright © 2012 John Wiley & Sons, Ltd.

This study attempted to address statistical properties and forecast of daily urban water consumption in Hong Kong from 1990 to 2007. A statistical model was formulated to differentiate the effects of five factors on water use, i.e., trend, seasonality, climatic regression, calendar effect, and autoregression. The postulate of the statistical model is that total water use is made up of base, seasonal, and calendrical water use. Daily urban water consumption in Hong Kong from 1990 to 2001 was modeled and the developed statistical model explains 83% of the variance with six factors: trend (8%), seasonality (27%), climatic regression (2%), day‐of‐the‐week effect (17%), holiday effect (17%), and autoregression (12%). The model was further validated using an independent data set from 2002 to 2007, yielding a R² of 76%. The results indicated good performance of the developed statistical model in depicting the temporal variations of the urban water use in Hong Kong, offering an improved insight into urban utilization of water resources and acting as the theoretical support for effective urban water resource management in Hong Kong under the changing environment.