A model integrating geo-information and self-organizing map (SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals (As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows: (1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd. (2) As and Pb had a similar topo-logical distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements. (3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers, factories, and ore zones. (4) The variations of contamination index (CI) followed the trend of construction land (1.353) > forestland (1.267) > cropland (1.175) > grassland (1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.
Groundwater is a resource under stress. In both developed and developing countries, it has been found that increasing human influence has led to the contamination of the groundwater resource. To understand the magnitude of this problem, a study was conducted in 58 wards within Northern part of Kolkata, India, where water samples from tube wells were collected and analysed on essential drinking water quality parameters, prescribed by WHO. Using Principal component analysis, and Water quality index mapping, the aforementioned results have been interpreted. This has helped to depict that not only is the groundwater unsuitable for drinking, but that the parametric values have a tendency to increase abruptly within the shortest of ranges, indicating urban pollution as the root cause of contamination. This paper shall thus discuss the spatial change in groundwater quality in northern Kolkata and suggest measures which might be implemented to secure a sustainable future for the city. 相似文献
This paper focuses on the heavy metal enrichment and heavy metal pollution degree associated with mining activities in some crops and the soils of different parent materials in the Xiaoqinling Gold Belt. According to the geochemical analysis results of the soils observed in the gold belt, the soils are most highly enriched in Pb, followed by Cr, Cu, and Zn. Furthermore, they are relatively poor in Hg, Cd, and As. It is also shown that the heavy metals in all kinds of soils have the same geochemical characteristics in the gold belt. As for the crops (such as corn and wheat) in the gold belt, Zn and Cu are the most abundant elements, followed by Pb and Cr. Meanwhile, Hg, Cd, and As were found to have relatively low concentrations in the crops. The heavy metals in wheat and corn have the same geochemical characteristics in the gold belt in general. Compared to the aeolian loess soils and the crops therein, heavy metals are more enriched in diluvial and alluvial soils and the crops therein. As shown by relevant studies, the Hg, Pb, Cd, Cu, and Zn pollution are mainly caused by mining activities. Corn and wheat in the gold belt have a high tendency of risk exposure to heavy metal pollution since they are mostly affected by mining activities and feature high background values of heavy metal concentrations. Furthermore, wheat is more liable to be enriched in heavy metals than corn is grown in all types of soils. The Hg pollution in soils leads to Hg accumulation, increasing the risk of Hg uptake in crops, and further affecting human health. This study will provide a scientific basis for the control and management of heavy metals in farmland soils of mining areas. 相似文献
Groundwater is a key factor controlling the growth of vegetation in desert riparian systems. It is important to recognise how groundwater changes affect the riparian forest ecosystem. This information will not only help us to understand the ecological and hydrological process of the riparian forest but also provide support for ecological recovery of riparian forests and water-resources management of arid inland river basins. This study aims to estimate the suitability of the Water Vegetation Energy and Solute Modelling(WAVES) model to simulate the Ejina Desert riparian forest ecosystem changes,China, to assess effects of groundwater-depth change on the canopy leaf area index(LAI) and water budgets, and to ascertain the suitable groundwater depth for preserving the stability and structure of desert riparian forest. Results demonstrated that the WAVES model can simulate changes to ecological and hydrological processes. The annual mean water consumption of a Tamarix chinensis riparian forest was less than that of a Populus euphratica riparian forest, and the canopy LAI of the desert riparian forest should increase as groundwater depth decreases. Groundwater changes could significantly influence water budgets for T. chinensis and P. euphratica riparian forests and show the positive and negative effects on vegetation growth and water budgets of riparian forests. Maintaining the annual mean groundwater depth at around 1.7-2.7 m is critical for healthy riparian forest growth. This study highlights the importance of considering groundwater-change impacts on desert riparian vegetation and water-balance applications in ecological restoration and efficient water-resource management in the Heihe River Basin. 相似文献
The Shenandoah Watershed Study (established in 1979) and the Virginia Trout Stream Sensitivity Study (established in 1987) serve to increase understanding of hydrological and biogeochemical changes in western Virginia mountain streams that occur in response to acidic deposition and other ecosystem stressors. The SWAS-VTSSS program has evolved over its 40+ year history to consist of a temporally robust and spatially stratified monitoring framework. Currently stream water is sampled for water quality bi-hourly during high-flow events at three sites and weekly at four sites within Shenandoah National Park (SHEN), and quarterly at 72 sites and on an approximately decadal frequency at ~450 sites within the wider western Virginia Appalachian region. Stream water is evaluated for pH, acid neutralizing capacity (ANC), base cations (calcium, magnesium, sodium and potassium ion), acid anions (sulphate, nitrate and chloride), silica, ammonium, and conductivity with a subset of samples evaluated for monomeric aluminium and dissolved organic carbon. Hourly stream discharge (four sites) and in-situ measurements of conductivity, water and air temperature (three sites) are also measured within SHEN. Here we provide an overview and timeline of the SWAS-VTSSS stream water monitoring program, summarize the field and laboratory methods, describe the water chemistry and hydrologic data sets, and document major watershed disturbances that have occurred during the program history. Website links and instructions are provided to access the stream chemistry and time-series monitoring data in open-access federal databases. The purpose of this publication is to promote awareness of these unique, long-term data sets for wider use in catchment studies. The water chemistry and hydrologic data can be used to investigate a wide range of biogeochemical research questions and provide key inputs for models of these headwater stream ecosystems. SWAS-VTSSS is an ongoing program and quality assured data sets are uploaded to the databases annually. 相似文献