Abstract. It is increasingly recognized that the land-use change, especially urbanization has influenced hydrological attributes intensely. Flood characteristics variation could likewise increase flood risks and pose higher demand on water management. The paper aims to evaluate temporal and spatial processes of urbanization affecting flood events at catchment level. The study sites were Xiaoqinhe catchment and its sub-catchments, a part of lower Yellow river basin in northern China. Historic cities Jinan and Zibo in the area have experienced dramatic urban expansion in recent decades, about 5 % growth of urban build-up area annually from 1990s to 2010s, and also pressed alarm for increasing flood disasters. In the paper, a HEC-HMS model was set up to simulate flood processes for different land-use scenarios. The possible effects of urbanization on flood characteristics were checked in study catchment and its sub-catchments.

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The per capita ecological footprint (EF) is one of the most widely recognized measures of environmental sustainability. It aims to quantify the Earth's biological resources required to support human activity. In this paper, we summarize relevant previous literature, and present five factors that influence per capita EF. These factors are: National gross domestic product (GDP), urbanization (independent of economic development), distribution of income (measured by the Gini coefficient), export dependence (measured by the percentage of exports to total GDP), and service intensity (measured by the percentage of service to total GDP). A new ecological footprint model based on a support vector machine (SVM), which is a machine-learning method based on the structural risk minimization principle from statistical learning theory was conducted to calculate the per capita EF of 24 nations using data from 123 nations. The calculation accuracy was measured by average absolute error and average relative error. They were 0.004883 and 0.351078% respectively. Our results demonstrate that the EF model based on SVM has good calculation performance.

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Geographic Information System (GIS) has provided viable tool to generate, manipulate, and spatially organize disparate for distributed modeling of large amount of data of watershed and land uses. Despite extensive achievement to point sources control, public attention has been diverted for the last decades towards non-point sources pollution (NPSP) of river / Lakes watersheds and watersheds. The utilization of large amount of agrochemicals regarding potential growth of crops and vegetables to meet the requirement for increasing rate of population has caused the contribution of diffused pollutants in the water bodies. Besides the loss of fertile soils, pesticides from agriculture results diffuse loss of nitrogen (N) and phosphorus (P), which are essential input for crop and animal production. Environmentalist and scientist have developed various methods and strategies for the quantification of NPSP. For instance various modeling