Land use and water quality response in the northern region of Changxing County

In this paper, taking the northern region of Changxing County for example, with ammonia nitrogen as a pollution assessment index, we used an improved export coefficient method for estimate polluting load of non-point source pollution (NSP) and the social pollution survey data in the study area to estimate point source pollution. By comparing the total pollution output and the national surface water environmental quality standards find that the whole study area achieves the second water quality standard. However, Jiapu Township exceeds the water quality standards seriously because of the superfluous point source pollution. The water quality of other Townships is good. Further analysis showed that different types of land use and proportions in the northern region of Changxing County have a significant impact on the non-point source pollution, the general law is farmland contributes the largest share of the non-point source pollution output, followed by residential area and bare land, besides, with the increase in the proportion of forest and the decrease of farmland and residential area, the non-point source pollution reduces gradually. © 2010 IEEE.

Spatial patterns and driving forces of land use change in China during the early 21st century

Land use and land cover change as the core of coupled human-environment systems has become a potential field of land change science (LCS) in the study of global environmental change. Based on remotely sensed data of land use change with a spatial resolution of 1 km x 1 km on national scale among every 5 years, this paper designed a new dynamic regionalization according to the comprehensive characteristics of land use change including regional differentiation, physical, economic, and macro-policy factors as well. Spatial pattern of land use change and its driving forces were investigated in China in the early 21st century. To sum up, land use change pattern of this period was characterized by rapid changes in the whole country. Over the agricultural zones, e.g., Huang-Huai-Hai Plain, the southeast coastal areas and Sichuan Basin, a great proportion of fine arable land were engrossed owing to considerable expansion of the built-up and residential areas, resulting in decrease of paddy land area in southern China. The development of oasis agriculture in Northwest China and the reclamation in Northeast China led to a slight increase in arable land area in northern China. Due to the "Grain for Green" policy, forest area was significantly increased in the middle and western developing regions, where the vegetation coverage was substantially enlarged, likewise. This paper argued the main driving forces as the implementation of the strategy on land use and regional development, such as policies of "Western Development", "Revitalization of Northeast", coupled with rapidly economic development during this period.

The influence of topography and land use on water quality of Xiangxi River in Three Gorges Reservoir region

A self-organizing map (SOM) was used to cluster the water quality data of Xiangxi River in the Three Gorges Reservoir region. The results showed that 81 sampling sites could be divided into several groups representing different land use types. The forest dominated region had low concentrations of most nutrient variables except COD, whereas the agricultural region had high concentrations of NO3N, TN, Alkalinity, and Hardness. The sites downstream of an urban area were high in NH3N, NO2N, PO4P and TP. Redundancy analysis was used to identify the individual effects of topography and land use on river water quality. The results revealed that the watershed factors accounted for 61.7% variations of water quality in the Xiangxi River. Specifically, topographical characteristics explained 26.0% variations of water quality, land use explained 10.2%, and topography and land use together explained 25.5%. More than 50% of the variation in most water quality variables was explained by watershed characteristics. However, water quality variables which are strongly influenced by urban and industrial point source pollution (NH3N, NO2N, PO4P and TP) were not as well correlated with watershed characteristics.