Temporal and Spatial Variability of Water Supply Stress in the Haihe River Basin,Northern China1

Ji, Yuhe, Liding Chen, and Ranhao Sun, 2012. Temporal and Spatial Variability of Water Supply Stress in the Haihe River Basin, Northern China. Journal of the American Water Resources Association (JAWRA) 48(5): 999‐1007. DOI: 10.1111/j.1752‐1688.2012.00671.x Abstract: Water resources are becoming increasingly stressed under the influence of climate change and population growth in the Haihe River Basin, Northern China. Assessing the temporal and spatial variability of water supply stress is urgently needed to mitigate water crisis caused by water resource reallocation. Water supply and use data were compiled for the time period of 1998‐2003 in this synthesis study. The Water Supply Stress Index (WSSI) as defined as Water Demand/Water Supply was used to quantitate whether water supply could meet the demand of human activities across the study region. We found a large spatial gradient of water supply stress in the study region, being much higher in the eastern subbasins (ranging from 2.56 to 4.31) than the west subbasins (ranging from 0.56 to 1.92). The eastern plain region not only suffered more serious water supply stress but also had a much higher interannual variability than the western hilly region. The uneven spatial distribution of water supply stress might result from the distribution of land use, population, and climate. Future climate change and rapid economic development are likely to aggravate the existing water crisis in the study region.     

Analysis and assessment of heavy metal contamination in surface water and sediments: a case study from Luan River,Northern China

Concentrations of the heavy metals Cu, Ni, Pb, Zn, Cd, and Cr were examined in surface water and sediment from the Luan River inChina,. With a decline in Cu and Ni concentration found in surface water at downstream stations. This finding suggests that water currents are a major explanatory factor in heavy metal contamination. The abundance of Cr, Pb, and Cd observed in the middle reaches of the river indicates heavy metal contamination in local areas, although there was an obvious decrease in concentrations in the water downstream of the Daheiting Reservoir. The significant rising trend in Cu, Pb, and Ni seen the sediment farther away from the river also suggests that anthropogenic activities contribute to heavy metal pollution Sediments were therefore used as environmental indicators, with sediment assessment was conducted using the geo-accumulation index (I_geo) and the potential ecological risk index (RI). The I_geo values revealed that Cd (3.13) and Cr (2.39) had accumulated significantly in the Luan River. The RI values for most (89%) of the sampling stations were higher than 300, suggesting that sediment from the Luan River poses a severe ecological risk, with the potential ecological risks downstream higher than that in the upper and middle streams. Good correlations among Pb/Ni, Pb/Cd, Cu/Pb, and Cu/Cd in the water and Cr/Ni in the sediment were observed. Cluster analysis suggested that Cd may have various origins, being derived from anthropogenic sources.     

Assessment OF SURFACE WATER QUALITY at Large Watershed Scale: Land‐Use,Anthropogenic, and Administrative Impacts

Understanding the impacts that influence water quality is critical to the development of best management practices at the large watershed scale. This study describes the spatiotemporal variation in surface water quality and identifies their main impact in the Haihe River basin, China. Multivariate statistical techniques are applied to analyze the similarities among the sampling sites and to identify the main pollution sources in surface water. Results show that: (1) the basin can be clustered into two regions, water quality being better in the mountainous vs. plain regions; (2) water quality improves due to implementation of a strict state policy on environmental pollution control, prodded by the hosting of the Olympic games in the cities of Beijing and Tianjin; and (3) agricultural and residential land uses as well as livestock‐breeding are the main sources affecting water quality in the mountainous regions, whereas rural waste discharge — including domestic waste sewage, human and animal feces, and solid waste — significantly influences water quality in the plain regions. The waste discharge of industrial factories may be a significant source of water pollution in the plain regions. Results indicate that the environmental management from pollution sinks and sources, long‐lasting legal framework, and adequate economic incentives should be improved to optimize the large‐scale watershed management under the background of the rapid development of countries like China.     

Major Ecosystems in China: Dynamics and Challenges for Sustainable Management

Ecosystems, though impacted by global environmental change, can also contribute to the adaptation and mitigation of such large scale changes. Therefore, sustainable ecosystem management is crucial in reaching a sustainable future for the biosphere. Based on the published literature and publicly accessible data, this paper discussed the status and trends of forest, grassland, and wetland ecosystems in China that play important roles in the ecological integrity and human welfare of the nation. Ecological degradation has been observed in these ecosystems at various levels and geographic locations. Biophysical (e.g., climate change) and socioeconomic factors (e.g., intensive human use) are the main reasons for ecosystem degradation with the latter factors serving as the dominant driving forces. The three broad categories of ecosystems in China have partially recovered from degradation thanks to large scale ecological restoration projects implemented in the last few decades. China, as the largest and most populated developing nation, still faces huge challenges regarding ecosystem management in a changing and globalizing world. To further improve ecosystem management in China, four recommendations were proposed, including: (1) advance ecosystem management towards an application-oriented, multidisciplinary science; (2) establish a well-functioning national ecological monitoring and data sharing mechanism; (3) develop impact and effectiveness assessment approaches for policies, plans, and ecological restoration projects; and (4) promote legal and institutional innovations to balance the intrinsic needs of ecological and socioeconomic systems. Any change in China’s ecosystem management approach towards a more sustainable one will benefit the whole world. Therefore, international collaborations on ecological and environmental issues need to be expanded.     

Surface-enhanced Raman scattering for mixing state characterization of individual fine particles during a haze episode in Beijing, China

The nondestructive characterization of the mixing state of individual fine particles using the traditional single particle analysis technique remains a challenge. In this study, fine particles were collected during haze events under different pollution levels from September 5 to 11 2017 in Beijing, China. A nondestructive surface-enhanced Raman scattering (SERS) technique was employed to investigate the morphology, chemical composition, and mixing state of the multiple components in the individual fine particles. Optical image and SERS spectral analysis results show that soot existing in the form of opaque material was predominant during clear periods (PM_2.5 ≤ 75 µg/m³). During polluted periods (PM_2.5 > 75 µg/m³), opaque particles mixed with transparent particles (nitrates and sulfates) were generally observed. Direct classical least squares analysis further identified the relative abundances of the three major components of the single particles: soot (69.18%), nitrates (28.71%), and sulfates (2.11%). A negative correlation was observed between the abundance of soot and the mass concentration of PM_2.5. Furthermore, mapping analysis revealed that on hazy days, PM_2.5 existed as a core-shell structure with soot surrounded by nitrates and sulfates. This mixing state analysis method for individual PM_2.5 particles provides information regarding chemical composition and haze formation mechanisms, and has the potential to facilitate the formulation of haze prevention and control policies.     

Modeling the non-point source pollution risks by combing pollutant sources,precipitation, and landscape structure

Traditional models of nutrient simulation usually focus on the pollutant sources and precipitation, lacking the quantification of landscape structure. We developed a new prediction model of pollution risks by combing pollutant sources, precipitation, and landscape structure, which was defined as the source-precipitation-landscape model (SPLM). The SPLM was applied to simulate the non-point source (NPS) total nitrogen (TN) exports in one of the largest river basins in China (the Haihe River Basin, HRB). TN concentrations of 35 sampling catchments in 2013 were used to test the accuracy of the SPLM. Simulated results showed that (1) the SPLM had a relative high accuracy in the simulation of NPS TN export and intensity, especially for TN intensity. (2) The mean TN export and intensity of all the 1578 catchments in the HRB were 441.97 t and 2.08 t/km², respectively. (3) The TN export intensities differed greatly among the sub-basins in the HRB, ranging from 0.64 to 6.81 t/km². On the whole, the TN export intensities of the plain sub-basins (e.g., the Tuhaimajia River, the Heilonggang River, and the Beisihe River) were much higher than those of mountainous sub-basins (e.g., the Yongding River, the Beisanhe River, and the Luanhe River). (4) The contributions to TN exports, from high to low, were land use (38.82%), livestock husbandry (33.57%), and rural population (27.61%). Among all the ten pollution sources, arable land (30.87%), rural population (27.61%), and large livestock (17.73%) had the top three contributions to TN exports. This study provides a feasible tool for policymakers and administrators to develop workable management measures for the mitigation of NPS pollution. This SPLM can be extended to other regions in a rapid urbanization context.

     

Assessment of the redistribution of soil carbon using a new index—a case study in the Haihe River Basin,North China

Soil carbon redistribution is an important process in the terrestrial carbon cycle. This study describes a new index, soil carbon redistribution (SCR) index, that can be used to assess long-term soil carbon redistribution at a large watershed scale. The new index is based on the theoretical preconditions that soil carbon redistribution is mainly controlled by vegetation type, precipitation, topography/slope, and soil carbon concentration. The Haihe River Basin served as an example for this analysis. The SCR index was calculated, and a GIS-based map shows its spatial patterns. The results suggested that soil carbon was usually prone to being carried away from mountainous regions with natural vegetation, while it was prone to deposition in the plain and plateau regions with cultivated vegetation. The methods in the paper offer a tool that can be used to quantify the potential risk where soil carbon is prone to being carried away and deposited in a large watershed.     

滦河流域鲫鱼体内重金属分布及风险评价

采集滦河流域鲫鱼样本并分析重金属元素(Cu、Zn、Cr、Pb、As、Cd)在其体内的分布特征及食用风险。实验结果表明鲫鱼体内重金属含量由高到低顺序为ZnCrCuPbAsCd,蓄积器官主要为肝脏和鳃部,Cu和Cr主要蓄积在肝脏,Zn、Pb、Cd主要富集在鳃部,As的蓄积器官随地域变化,而且下游样本中各组织器官重金属含量下游高于上游。针对鲫鱼肌肉的评价表明,Zn、Cr、Pb含量超出《无公害食品水产品中有毒有害物质限量》(NY5073—2006)、《食品污染物限量》(GB2762—2012)和《食品中锌限量卫生标准》(GB 13106—1991)规定的标准限值,超出倍数依次为Cr(3.34)Pb(2.24)Cd(1.15)。基于目标危险系数法(THQ)评价结果表明鲫鱼肌肉组织单一重金属THQ值均小于1,As导致的健康风险最高,Cr最低;总风险系数(TTHQ)显示下游的溯河(TTHQ=1.263)与陡河(TTHQ=1.381)存在食用风险,风险比重较高的元素是As、Pb、Zn。     

Effect of Land-Use Patterns on Total Nitrogen Concentration in the Upstream Regions of the Haihe River Basin, China

Nutrient loading into rivers is generally increased by human-induced land-use changes and can lead to increased surface water pollution. Understanding the extent to which land-use patterns influence nutrient loading is critical to the development of best-management practices aimed at water-quality improvement. In this study, we investigated total nitrogen (total N) concentration as a function of land-use patterns and compared the relative significance of the identified land-use variables for 26 upstream watersheds of the Haihe River basin. Seven land-use intensity and nine landscape complexity variables were selected to form the land-use pattern metrics on the landscape scale. After analyzing the significance of the land-use pattern metrics, we obtained five dominant principal components: human-induced land-use intensity, landscape patch-area complexity, area-weighted landscape patch-shape complexity, forest and grassland area, and landscape patch-shape complexity. A linear regression model with a stepwise selection protocol was used to identify an optimal set of land-use pattern predictors. The resulting contributions to the total N concentration were 50% (human-induced land-use intensity), 23.13% (landscape patch-shape complexity), 14.38% (forest and grassland area), and 12.50% (landscape patch-area complexity), respectively. The regression model using land-use measurements can explain 87% of total N variability in the upstream regions of Haihe River. The results indicated that human-related land-use factors, such as residential areas, population, and road density, had the most significant effect on N concentration. The agricultural area (30.1% of the study region) was not found to be significantly correlated with total N concentration due to little irrigative farmland and rainfall. Results of the study could help us understand the implications of potential land-use changes that often occur as a result of the rapid development in China.