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Global flood management is a major issue for most cities which have to deal with worsening factors such as climate change and fast urban growth. Computer models have been used to model and understand urban flooding on a local scale in cities (25–50 km2). It has been practically impossible to model bigger cities in one go in sufficiently high resolution due to the heavy computations involved. The present paper describes a new modelling approach for urban flooding which allows modelling on large city scale (1000 km2) while keeping sufficient resolution, e.g. 5 m or 10 m grid. The multicell approach is applied for the city of Beijing for July 21st, 2012 flood event. Model results are compared to testimonials from the 2012 event. Comparison to traditional 2D urban flood computations shows that the multicell approach is much faster than standard detailed models while keeping a suitable level of precision. [ABSTRACT FROM AUTHOR]

Climate change and human activities have changed a number of characteristics of river flow in the northwest of China. Numerous problems such as water resource shortage, drying up of rivers, water pollution are the direct consequences of these changes. In this paper, we used the example of Yulin city in northwest China to assess the spatio-temporal characteristics and driving forces of annual river flow changes. Our research was based on the long-term time series of hydrological data from 1956 to 2005, to analyse annual flow in four main rivers (Kuye River, Tuwei River, Wuding River and Jialu River). The river flow depends upon the runoff characteristics of the river catchment, therefore we used variation ratio, variation index, unevenness, Runoff-Concentration Degree (RCD) and Runoff-Concentration Period (RCP) to determine the change in runoff characteristics of the four main rivers flows of the Yulin city. We tested the tendency of runoff by the Mann-Kendall non-parameter statistical method to obtain the temporal evolution law. At the same time, Kriging spatial interpolation and GIS were used to derive the spatial evolution law. The dates of climate change (precipitation) and human activities were also used to calculate the driving forces for annual runoff changes of the rivers’ catchments. Through the accumulation curves and multi-recursive techniques, we built the correlation between precipitation and runoff. The driving factors for annual runoff change were then calculated by using the runoff coefficient method. Results showed that the distribution of annual runoff was uneven and had a small accumulation in July and August, especially in Kuye River, and there seemed to be a significant reducing trend in annual runoff. Isolines and the thematic map of Mann-Kendall tests U(R) revealed that the Tuwei River's catchment is the most affected catchment, with annual runoff substantially changed. At the 5% significance level, precipitation did not significantly drop compared with annual runoff. We also found that precipitation is not the only factor responsible for the decreased annual runoff. Therefore we included human activities affect in this case study by using the past 25 years land use, water conservancy and urbanisation data. We discriminated the impacts of climate change and human activities on the surface runoff by multi-recursive analysis method and runoff coefficient method. The results showed that human activities are the direct cause for the changes of river runoff. The results of the study also revealed that the Wuding and Jialu rivers had the most and the least changes in the runoff respectively; this phenomenon should be seriously considered for future water resources planning and management. [ABSTRACT FROM PUBLISHER]