Qiandao Lake (Xin’an Jiang reservoir) plays a significant role in drinking water supply for eastern China, and it is an attractive tourist destination. Three multivariate statistical methods were comprehensively applied to assess the spatial and temporal variations in water quality as well as potential pollution sources in Qiandao Lake. Data sets of nine parameters from 12 monitoring sites during 2010–2013 were obtained for analysis. Cluster analysis (CA) was applied to classify the 12 sampling sites into three groups (Groups A, B and C) and the 12 monitoring months into two clusters (April-July, and the remaining months). Discriminant analysis (DA) identified Secchi disc depth, dissolved oxygen, permanganate index and total phosphorus as the significant variables for distinguishing variations of different years, with 79.9% correct assignments. Dissolved oxygen, pH and chlorophyll-a were determined to discriminate between the two sampling periods classified by CA, with 87.8% correct assignments. For spatial variation, DA identified Secchi disc depth and ammonia nitrogen as the significant discriminating parameters, with 81.6% correct assignments. Principal component analysis (PCA) identified organic pollution, nutrient pollution, domestic sewage, and agricultural and surface runoff as the primary pollution sources, explaining 84.58%, 81.61% and 78.68% of the total variance in Groups A, B and C, respectively. These results demonstrate the effectiveness of integrated use of CA, DA and PCA for reservoir water quality evaluation and could assist managers in improving water resources management.

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources.

The eastern coastal region of China has been experiencing rapid urbanization which has imposed great challenges on soil resources, characterized by soil sealing and fragmented soil landscapes. Taking Zhejiang Province—a fairly economically-developed and highly-urbanized region in eastern China—as a case study, a practical framework that integrates remote sensing, GIS, soil quality assessment and landscape analysis was employed to track and analyze the rapid urbanization process and spatiotemporal dynamics of soil sealing and landscape change from 1990 to 2010. Meanwhile, this paper qualitatively explored the regional inequality and characteristics in soil sealing intensity among cities of different geo-zones in Zhejiang Province. Results showed that total area of 6420 km² had been sealed during the past two decades for the entire study area, which represents 6.2% of the provincial area. Among these sealed soils, 68.6% are fertile soils located in flat plains, such as Paddy soils. Soil landscapes became more fragmented and dispersed in distribution, more irregular and complex in shape, and less dominant and diverse in soil type, as evidenced by the constant change of various spatial landscape metrics. What is more, different geo-zones exhibited significant differences in dynamics of soil sealing intensity, soil composition and soil landscape patterns. The permanent loss of valuable soil resource and increasing fragmented soil landscape patterns concomitant with rapid urbanization processes may inevitably bring about potential threats to regional soil resources and food security.

To investigate the effect of arable land protection policies in China, a practical framework that integrates geographic information systems (GIS), soil quality assessment and landscape metrics analysis was employed to track and analyze arable land transformations and landscape changes in response to rampant urbanization within the Ningbo region (China) from 2005 to 2013. The results showed that arable land loss and degradation have continued, despite the development of a comprehensive legal framework for arable land protection. The implementation of arable land protection policies is judged to be effective, but not entirely successful, because it guarantees the overall amount of arable land but does not consider soil quality and spatial distribution. In addition, there are distinct variations in arable land change dynamics between two temporal intervals. From 2005–2009, the transformation of arable land was diversified, with intensified conversion among arable land, built-up land, water and orchards. Moreover, many new arable land parcels were adjacent to built-up land, and are in danger of being occupied again through urban sprawl. By 2009–2013, most of the arable land was occupied by urban expansion, whereas a majority of newly increased arable land was reclaimed from coastal tideland. Although the newly increased arable land was contiguous and far from the urban area, it is of poor quality and has limited use. The permanent loss of high-quality arable land due to intensified urban sprawl may threaten sustainable development and food security on a larger scale.

It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006–2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.