离子型稀土矿区小流域级地表水氨氮治理工程效果分析及建议

我国南方离子型稀土矿山采用原地浸矿工艺,使用硫酸铵和碳酸铵作为浸矿剂和沉淀剂,导致离子型稀土矿区普遍出现地表水质氨氮超标。为了解决包含历史遗留矿山和停产稀土矿山的矿区地表水污染治理问题,赣州稀土集团有限公司自2018年起开展了国内首次针对离子型稀土矿山小流域级地表水氨氮污染的治理工程并长期运行。根据运行监测数据分析,在稀土矿山小流域设置氨氮污染水处理厂,能够解决整个小流域中稀土矿山带来的水体污染问题,实现稀土矿山有序开采与环境保护。但是在稀土矿山小流域级氨氮污水治理时也存在小流域地表水水质的大幅变化、水量的大幅变化、碳源缺少和经济成本压力大等问题,仍然需要继续探索多种优化治理技术。

新疆开都河、孔雀河流域人口承载容量研究

开都河、孔雀河流域是于新疆巴音郭楞蒙古自治州重要的粮、油、棉、瓜果、畜产及水产基地,也是开发新疆塔里木油田的前哨陈地。近年来,随着南疆油气资源勘探的突破性进展,石油大会战及大型石化基地建设指日可待。做为南疆油田开发及石化工业生产大本营的两河流域,其人口承载容量的研究,无疑地会对本区的经济发展和资源开发以及由此带来的人口变动等提供重要的超前性的政策参考。

南盘江流域不同类型水水文地球化学特征

根据南盘江流域不同类型水水样化学成分分析资料,分析了区内水的水化学特征。结果表明,不同类型水化学指标不同。地表水的pH,电导率和SO42-浓度较高,而HCO3-浓度和Ca2+浓度低;河水为湖水与地下河及泉水混合而成,水化学指标本应处于两者之间,但实际上电导率和SO42-浓度高于两者。地下水水化学类型均为HCO3-Ca型或HCO3-Ca.Mg型,为典型的岩溶水;地表水水化学类型复杂,是由于水体周边人类活动频繁,扰动了水体天然水化学特征。应在生态,工农业生产,生活等方面采取有效措施,遏制水体污染并治理。

五台坪上泉岩溶水系统划分研究

以山西省五台坪上泉岩溶水系统为例 ,介绍了岩溶水系统的概况 ,并对甲子湾泉、大湾泉、水泉弯泉等岩溶水系统作了明确划分 ,提出了岩溶水各亚系统间的相互关系。

Analysis of Surface and Ground Water Exchange in Two Different Watersheds

Water regime of Albanian rivers is a Mediterranean typical one. During the wet period, it flows 85%-90% of the annual flow and the dry period represents only 10%-15% of the annual amount. In this paper the water regime of the Semani and Vjosa River is analyzed. These are two rivers with total different hydro-geological characteristics. Vjosa river watershed is mainly composed of massif calcareous rocks that are streaky and karstifled. A totally different view is in the other river, in Seman where the impermeable rocks dominate. Even the distribution of the precipitation is quite different. In the Vjosa River the amount of the precipitation varies from 1,500 mm to 2,500 mm per year and in Semani River only 1,100 mm per year. The flow in the wet period is mainly a result of the precipitation and the minimum discharge occurs during the dry period representing the base flow that is the contribution from the groundwater. In this point of view the flow in the dry period is also an indicator of the underground water resource. During the dry period the watershed gives what it received and what has cumulated during the wet period. This is more evident in the case of a karstic watershed. The recession curves were analysed for all the hydrometric stations in both river basins and the parameters of these curves are evaluated. These results are analyzed and compared between the two different watersheds reflecting the differences on water exchange of surface and ground water. Finally, an assessment of groundwater resources in both hydro geological basins is worked out.

Application of multivariate statistical techniques in assessment of surface water quality in Second Songhua River basin,China

Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality data sets of the Second Songhua River(SSHR) basin in China,obtained during two years(2012-2013) of monitoring of 10 physicochemical parameters at 15 different sites.The results showed that most of physicochemical parameters varied significantly among the sampling sites.Three significant groups,highly polluted(HP),moderately polluted(MP) and less polluted(LP),of sampling sites were obtained through Hierarchical agglomerative CA on the basis of similarity of water quality characteristics.DA identified p H,F,DO,NH3-N,COD and VPhs were the most important parameters contributing to spatial variations of surface water quality.However,DA did not give a considerable data reduction(40% reduction).PCA/FA resulted in three,three and four latent factors explaining 70%,62% and 71% of the total variance in water quality data sets of HP,MP and LP regions,respectively.FA revealed that the SSHR water chemistry was strongly affected by anthropogenic activities(point sources:industrial effluents and wastewater treatment plants;non-point sources:domestic sewage,livestock operations and agricultural activities) and natural processes(seasonal effect,and natural inputs).PCA/FA in the whole basin showed the best results for data reduction because it used only two parameters(about 80% reduction) as the most important parameters to explain 72% of the data variation.Thus,this work illustrated the utility of multivariate statistical techniques for analysis and interpretation of datasets and,in water quality assessment,identification of pollution sources/factors and understanding spatial variations in water quality for effective stream water quality management.

Spatial Distribution and Seasonal Variations of Heavy Metal Contamination in Surface Waters of Liaohe River, Northeast China

Heavy metal pollutants are a worldwide concern due to slow decomposition, biocondensation, and negative effects on human health. We investigated seasonal and spatial variations of the five heavy metals and evaluated their health risk in the Liaohe River, Northeast China. A total of 324 surface water samples collected from 2009 to 2010 were analyzed. Levels(high to low) of heavy metals in the Liaohe River were: zinc(Zn) > chromium(Cr) > copper(Cu) > cadmium(Cd) > mercury(Hg). Spatial and seasonal changes impacting concentrations of Cu and Zn were significant, but not significant for Cr, Cd and Hg. The highest concentrations of heavy metals were: Hg at Liuheqiao, Cu at Fudedian, Zn at Tongjiangkou, Cr at Mahushan, and Cd at Shenglitang. The highest concentrations of Hg and Cr were found in the wet period, Cu and Cd in the level period, and Zn in the dry period. The surface water of a tributary was an important accumulation site for heavy metals. Health risks from carcinogens and non-carcinogens increased from upstream to downstream in the mainstream of the Liaohe River. The total health risk for one person in the Liaohe River exceeded acceptable levels. The total health risk was the greatest during the wet period and least in the dry period. Among the five heavy metals in the Liaohe River, Cr posed the greatest single health risk.

Application of a Coupled Land Surface-Hydrological Model to Flood Simulation in the Huaihe River Basin of China

A hydrological simulation in the Huaihe River Basin(HRB) was investigated using two different models: a coupled land surface hydrological model(CLHMS), and a large-scale hydrological model(LSX-HMS). The NCEP-NCAR reanalysis dataset and observed precipitation data were used as meteorological inputs. The simulation results from both models were compared in terms of flood processes forecasting during high flow periods in the summers of 2003 and 2007, and partial high flow periods in 2000. The comparison results showed that the simulated streamflow by CLHMS model agreed well with the observations with Nash-Sutcliffe coefficients larger than 0.76, in both periods of 2000 at Lutaizi and Bengbu stations in the HRB, while the skill of the LSX-HMS model was relatively poor. The simulation results for the high flow periods in 2003 and 2007 suggested that the CLHMS model can simulate both the peak time and intensity of the hydrological processes, while the LSX-HMS model provides a delayed flood peak. These results demonstrated the importance of considering the coupling between the land surface and hydrological module in achieving better predictions for hydrological processes, and CLHMS was proven to be a promising model for future applications in flood simulation and forecasting.

Projected changes in mean and interannual variability of surface water over continental China

Five General Circulation Model(GCM) climate projections under the RCP8.5 emission scenario were used to drive the Variable Infiltration Capacity(VIC) hydrologic model to investigate the impacts of climate change on hydrologic cycle over continental China in the 21 st century. The bias-corrected climatic variables were generated for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change(IPCC AR5) by the Inter-Sectoral Impact Model Intercomparison Project(ISIMIP). Results showed much larger fractional changes of annual mean Evapotranspiration(ET) per unit warming than the corresponding fractional changes of Precipitation(P) per unit warming across the country, especially for South China, which led to a notable decrease of surface water variability(P-E). Specifically, negative trends for annual mean runoff up to -0.33%/ year and soil moisture trends varying between -0.02% to -0.13%/year were found for most river basins across China. Coincidentally, interannual variability for both runoff and soil moisture exhibited significant positive trends for almost all river basins across China, implying an increase in extremes relative to the mean conditions. Noticeably, the largest positive trends for runoff variability and soil moisture variability, which were up to 0.41%/year and 0.90%/year, both occurred in Southwest China. In addition to the regional contrast, intra-seasonal variation was also large for the runoff mean and runoff variability changes, but small for the soil moisture mean and variability changes. Our results suggest that future climate change could further exacerbate existing water-related risks(e.g., floods and droughts) across China as indicated by the marked decrease of surface water amounts combined with a steady increase of interannual variability throughout the 21 st century. This study highlights the regional contrast and intra-seasonal variations for the projected hydrologic changes and could provide a multi-scale guidance for assessing effective adaptation strategies for China on a river basin, regional, or as a whole.