南四湖水体富营养化时空比较分析与评价

南四湖是南水北调东线工程重要的输水通道和调蓄湖泊之一,随着通水时间的临近,其水质安全和水体富营养化状况备受关注．根据2006、2007、2010和2011年4次32个采样点的南四湖水质空间分布监测数据,采用综合营养状态指数法进行评价．结果表明,4个监测年枯水期南四湖水体总体平均处于富营养轻度水平,在南四湖水质得到大幅度改善的情况下,各年营养水平变化不大;南阳湖和独山湖水体的综合营养状态指数出现下降趋势,而昭阳湖（下）和微山湖岛北水体的综合营养状态指数出现上升趋势,这与全湖总磷出现均一化趋势有关．2010-2011年除微山湖岛南水体处于中营养水平外,其他湖区水体均处于富营养轻度水平．对南四湖水质空间分布监测数据的分析表明,南四湖藻类水华的繁殖生长主要受水体中TP的制约．     

构建鄱阳湖生态经济区低碳农业发展的路径思考

在全球气候变暖的条件下,发展低碳农业已成为不可逆转的趋势。鄱阳湖生态经济区内农业碳资源比较丰富,且极具开发潜力,因此,低碳农业发展空间巨大。鄱阳湖生态经济区内各地政府要立足当地资源优势,充分挖掘当地农业碳资源,通过发展有机农业和循环农业,加大植树造林力度,加强湿地保护,促使农业由高碳向低碳有效转变。     

论鄱阳湖生态经济区农业产业化经营背景下农村职业教育的发展

《鄱阳湖生态经济区规划》是2009年12月国务院批准的国家区域性战略规划。《规划》中特别指出,要积极推进农业产业化经营以及大力发展职业技术教育。本文从教育功能的角度,阐述＂农村职业教育发展＂与＂推进鄱阳湖生态经济区农业产业化经营＂二者的相互关系。鄱阳湖生态经济区建设离不开农村职业教育的可持续发展。     

Analysing decadal land use/cover dynamics of the Lake Basaka catchment (Main Ethiopian Rift) using LANDSAT imagery and GIS

Development of accurate classification methods for rapidly changing catchments like that of Lake Basaka is fundamental to better understanding the catchment dynamics, which were not addressed in previous studies. Thus, the aim of this study was to map the decadal land use/cover (LUC) regimes of the Lake Basaka catchment, utilizing time series of LANDSAT images and to analyse the changes that occurred at different time periods. Both unsupervised and supervised image classification systems were utilized in Earth Resources Data Analysis System (ERDAS) Imagine (9.1). Appropriate pre‐ and postprocessing also was utilized. Seven major LUC classes were identified in the final land cover maps produced after the supervised (maximum likelihood) classification exercise. The analysis results indicated the Lake Basaka catchment had experienced a drastic change in its LUC conditions over the last 4–5 decades because of rapid increases in human settlement, deforestation, establishment of irrigation schemes and Awash National Park (ANP). Approximately 18 924 ha of forest and 4730 ha of grazing lands were devastated between 1973 and 2008. At the same time, there was a shift in land cover from forests/woodlands to open woodlands, shrub and grazing lands. The land cover classifications generally were achieved at a very high overall accuracy (84.34%) and overall kappa statistics (0.802), substantiating the value of using the classified LUC in this study as an input to hydrological models. This study results provide an opportunity to better understand and quantify the hydrological response regimes of the lake catchment from the perspective of changing LUC conditions during different hydrological periods and the resulting dynamics of the lake water balance.     

Phytoplankton biomass and primary production dynamics in Lake Kariba

The present study examined spatial, seasonal and depth variations in phytoplankton biomass and primary production (PP), compared with those reported for other tropical African lakes, to determine whether or not measured phytoplankton changes might be linked to climate warming. The biomass of three major phytoplankton classes (Cyanophyceae; Chlorophyceae; Bacillariophyceae) and net PP were measured during the midwinter and midsummer at six different depths at 35 sampling sites distributed across the lake’s five basins. A more rigorous sampling regime was used in the fifth basin, with phytoplankton biomass and PP rates measured every second month over a 24 month period at six different depths at ten sampling sites located in riverine and lacustrine waters. Cyanophyceae, which displayed a gradient of decreasing biomass from Basins 2 to 5, contributed 69% of the total phytoplankton biomass in the lake’s five basins during summer. This percentage was approximately four times greater than that contributed by the Bacillariophyceae and about ten times greater than that contributed by the Chlorophyceae. During winter, Bacillariophyceae biomass was equivalent to that of the Cyanophyceae, but displayed an opposing gradient of increasing biomass from Basins 1 to 3, with a subsequent biomass decline from Basins 3 to 5. Chlorophyceae exhibited no distinct biomass gradient across the five lake basins, being undetectable during winter. The biomass of all three phytoplankton classes and the net PP varied in magnitude and direction monthly between the lacustrine and riverine waters, with increasing water depth and with no distinct seasonal patterns being evident. The monthly variations in biomass were related to the thermal stratification cycle, hydrological gradients and the extent of water mixing, being similar to those reported for other tropical African lakes. It is noteworthy that total phytoplankton biomass and PP in Lake Kariba have declined by about 95% and 50%, respectively, since the 1980s. These declines correspond to an upward shift in the depth of the thermocline, associated with an average temperature increase of 1.9 °C and a 50% reduction in the depth of the euphotic zone, since the 1960s.     

Water quality assessment of a tropical coastal lake system using multivariate cluster,principal component and factor analysis

Statistical techniques represent a reliable tool for classifying, modelling and interpreting surface water quality monitoring data, particularly for lakes. The complexity associated with the analysis of a large number of measured variables, however, is a major problem in water quality assessments. Multivariate analysis, such as cluster analysis and factor analysis (FA), was utilized in this study for the analysis of water quality data (including water discharges and 28 water quality parameters) for Akkulam–Veli Lake, a tropical coastal lake system in Kerala, India. This lake is partially divided into two sub‐systems, namely Veli Lake and Akkulam Lake. Akkulam Lake exhibits freshwater characteristics, in contrast to Veli Lake, which exhibits saline water characteristics because of its close proximity to the sea. Thus, studying this lake provides insights into water quality variations in both a freshwater and saline water lake in a tropical region. Water quality patterns and variations in Akkulam–Vela Lake over three seasons, including pre‐monsoon (PRM), monsoon (MON) and post‐monsoon (POM), also were studied, utilizing multivariate techniques. The organic pollution factor played a significant role on lake water quality during PRM. The influence of organic pollution tends to decrease during MON and POM, a particular situation faced by urban lakes in tropical regions. Polluted stretches in a lake system during different seasons can easily be ascertained by hierarchical cluster analysis. Further, the factors affecting a lake system as a whole, as well as for a particular sampling site, can easily be identified by FA. Improved water quality can be observed during POM. Akkulam and Vela lakes exhibit a wide variation in water quality during all seasons, a finding that corroborates a water flow obstruction from Akkulam Lake to Veli Lake because of the bund existing between the two lakes. The location of the bund is identified as the major reason for different hydrochemical processes in A–V Lake.     

鄱阳湖湖区三站点水质评价及其变化特征研究

应用模糊综合定量评价法对鄱阳湖星子站、都昌站、棠荫站区域的水质进行了评价,以3个指标(氨氮、高锰酸盐指数、总磷)作为评价因子,建立评价矩阵,计算出因子权重,得出特征指数,最后评价出水质级别,该方法能够得到其它方法难以达到的客观性和综合性。水质监测数据和评价结果表明:2003-2008年鄱阳湖3站点水质状况尚属良好,大部分时期在Ⅱ、Ⅲ类水平,但也有部分时段超标;在劣于Ⅱ类水的情况下,3个站点所在区域枯水期水质均比丰水期和平水期差。     

吉林查干湖生态景观水域建设的基本思路和技术方法

吉林查干湖对生态景观水域建设进行了科学定位,利用大型水利工程引水和补水维持生态水量,保持陆地-水域生态系统的联通,形成和保留水-岸过渡带,实行水量-水位-水质调控、拦截入湖污染物,控制湖内局部污染源,开辟和开发沿湖第四系潜水上游地质天窗湖泡,采用了多项生态友好型工程材料和技术来保护和恢复水岸生态系统,获得了预期效果,也为水域生态景观建设提供了借鉴。     

南四湖水质空间分布特征分析与改善效果评估

根据南四湖2006年、2007年、2010年和2011年4次90个采样点的水质空间分布监测数据,采用Surfer 8.0软件绘制南四湖水质空间分布等值线图,进行南四湖及分湖区水质指标的综合比较分析和平均综合污染指数的计算与污染控制效果评估。结果表明:南四湖COD、NH3-N、TP、TN和CODMn等指标的空间分布具有北高南低的非均一性特点;2010—2011年比2006—2007年枯水期各水质指标的平均浓度下降率为38.3%,整体提高了1～2个水质类别;按GB 3838—2002《地表水环境质量标准》中Ⅲ类标准相应的平均综合污染指数进行评价,达标和基本达标湖区的比例达到63.3%;2010—2011年枯水期南四湖主要污染物分担率由大到小排序依次为TP、COD、TN、CODMn、NH3-N;水质平均综合污染指数与电导率存在很好的相关性和北高南低的污染特点,说明南四湖水污染物仍然以外源排放为主。     

南四湖表层底泥重金属空间分布及污染程度评价

测试南四湖湖区29个表层底泥中重金属Hg、Cd、Cr、Pb、Ni、Cu、Zn和类金属As的质量比,得到南四湖湖区重金属污染的空间分布特征。结合地质积累指数法和潜在生态风险指数法,对南四湖重金属污染程度进行评价。结果表明,南四湖已受到重金属元素的污染,属于中等程度污染湖泊,其中以As、Hg、Cd、Pb元素污染严重。除了As、Cd元素在下级湖表层底泥中的质量比略高外,其他重金属元素在上级湖的污染程度普遍比在下级湖的高;二级坝以北的昭阳湖湖区潜在生态危害最为严重,其次是南阳湖、微山湖、独山湖和二级坝以南的昭阳湖湖区。