Restoration of small lakes through cooperative management: A suitable strategy for poverty‐laden areas in developing countries?

Lake Rupa is a small, subtropical, shallow lake with a surface area of 100 ha situated 600 m a.s.l. in Central Himalaya, Nepal. This degraded lake was studied between 2000 and 2006, with the goal of determining whether or not it could be restored by a community‐based cooperative of local people living in its catchment. Main threats to the lake, its aquatic life and its very existence include encroachment by excessive aquatic vegetation, sedimentation, and low in‐lake concentrations of dissolved oxygen (DO). Small lakes (≤ 500 ha) are relatively prone to the process of ‘succession and climax’, although they also can be of social, environmental and ecological importance. Thus, their disappearance could spark social chaos and disorder in areas already having to cope with other rapid environmental changes. This means that credible mechanisms for revitalizing or protecting small lakes are an important goal. Accordingly, a lake cooperative of 329 households living in close vicinity to Lake Rupa was formed in 2002, by prioritizing traditional fishers, women and other deprived community members with the goals of respecting the citizenry and equity. Following the cooperative's campaigns directed at weed removal and fish stocking, encroachment of vegetation on the lake margins was halted, its aquatic weeds became under control, and its fisheries improved. In addition to the cooperative's restoration activities, several water quality parameters, including water transparency and DO and chlorophyll‐a concentrations, were monitored on a monthly basis. The measured water transparency was inconsistent, exhibiting large variations between 2000 and 2003. Relatively low, but consistent, values, however, were measured after 2004. The results imply that the removal of weeds, and sufficient nutrients and solar radiation are subsequently available to the lake's phytoplankton communities. Supporting this notion is that the chlorophyll‐a concentration spiked to 205 µg L⁻¹ in November 2006, the water transparency became consistent, and the DO concentration increased to >3.8 mg L⁻¹ during the critical months (March–May) after 2004. These water quality indicators indicated improvement in the degraded Lake Rupa, suggesting that the establishment of cooperatives such as that highlighted in this study could be a powerful and sustainable mechanism for restoring degraded lakes in similar socioeconomic settings by maintaining equity, by connecting communities with their resources, and by facilitating integrity, equity, citizenry and social justice.     

叶绿素荧光量子产量的MODIS遥感算法

从荧光量子产量的原理出发,利用 MODIS 卫星数据建立了一种估算量子产量的算法--φ算法.通过 2006 年 3 月 23 日渤海和北黄海的 MODIS 数据计算了荧光量子产量,并与叶绿素荧光效率(cFE)产品进行了比较.结果表明,φ算法是一种更精确的荧光量子产量的估算算法,它有效地避免了 CFE 存在的几个误差来源:包括未考虑浮游植物的"包裹效应"、使用 412nm 的离水辐亮度反演的浮游植物吸收系数以及积分深度过浅.CFE在大部分海域出现负值,还出现了某些高估点;在有效数据范围内,两者存在明显的线性相关关系.φ算法估算的量子产量最高值在0.05左右,这与其它海区测量的值域范围基本一致.除辽东湾东北部和部分近岸水域外,大部分离岸水域在0.001～0.02的范围内.通过对φ算法的误差来源分析,认为发展一种新的反演 678nm 比吸收系数和平均吸收系数的波段比值算法是可行的,也是改进φ算法精度的有效方法.     

遗传-BP神经网络法预测叶绿素a浓度变化

基于2009年—2010年对临江河回水区水质指标的监测数据,采用遗传算法结合BP神经网络的方法对回水区的叶绿素a(Chl-a)浓度变化进行动态模拟预测。通过灰色关联法确定了对Chl-a浓度有显著影响的指标与网络输入变量,即水温、DO、流速、透明度(SD)、TP、CODMn及Chl-a。模拟结果表明,遗传-BP神经网络的预测值和实测值吻合较好,其相对误差约为9.8%,模型可良好地用于次级河流回水区叶绿素a浓度的短期预测。预测结果表明,在春末夏初季节,当水库蓄水位为150～160 m时,临江河回水区富营养化潜势较高,尤其应注重临江河该时段富营养化的防控工作。     

磁化处理对水中藻类的去除效果研究

采用强磁场对藻类含量高的水体进行磁化处理,探讨了磁化处理过程中水样流速、循环时间、藻类初始浓度对磁化处理效果的影响。研究发现磁化处理对藻类的去除有明显的效果,通过对各个影响因素的研究表明在水样流速为3．78m/s,循环时间为360min时,藻类的去除效果比较好。     

叶绿素a测定方法改进的探讨

本文根据《水质监测》(第四版)等资料提供的操作方法,对水样预处理、不同的提取时间等几方面提出了自己试验中的心得体会,采用三色分光法来计算水中叶绿素a的含量。并就质控措施提出建议。     

影响分光光度法检测藻类叶绿素a的因素

目的为检测藻类叶绿素a提供可借鉴的依据.方法采用玻璃离心管与塑料离心管,待测液样在分光光度计中稳定不同时间,在叶绿素a提取过程中对液样加以冷藏的方法,进行对比试验.结果塑料离心管测得的水样叶绿素a值,比用玻璃离心管测得的值平均高30.1%.液样在分光光度计中稳定时间0~5 min内,叶绿素a值随稳定时间延长而提高,5 min以后提高速度减缓.冷藏时间在6 h以内,叶绿素a值平均增加1.92μg.(L.h)-1,6 h以后,叶绿素a值增加速度减缓.结论塑料材料对叶绿素a值测定有干扰作用,采用塑料离心管测得的水样叶绿素a值偏高,建议用玻璃离心管.待测液样在分光光度计中的稳定时间对藻类叶绿素a值的测定有影响,如果稳定时间过短,会使测定结果偏低.适合的稳定时间为10~20 min,在叶绿素a提取过程中,将液样适当进行冷藏,可使叶绿素a充分溶解于溶液中,适合的冷藏时间为6~8 h,供分光光度法检测藻类叶绿素a参考.     

基于GF-1/WFV的钱塘江叶绿素a和总悬浮物浓度遥感估算

为了探究高分一号(GF-1)卫星对河流水体水质参数遥感反演的效果,使用GF-1卫星数据的16 m分辨率的GF-1/WFV传感器数据和地面实测数据,基于地面实测光谱反射率数据模拟WFV波段组合,构建水体叶绿素a和总悬浮物浓度遥感模型,从而对钱塘江流域杭州段水体水质参数进行估算。研究结果表明:基于B1-B3差值的二次多项式模型可用于叶绿素a浓度估算(R²=0.83,RMSE=0.74 μg/L),基于B3波段的二次多项式模型可用于总悬浮物浓度的估算(R²=0.92,RMSE=1 mg/L);通过模型应用于准同步的GF-1/WFV数据,较好反映了低潮位钱塘江杭州段水体叶绿素a和总悬浮物浓度的空间分布,为高分一号卫星数据遥感监测钱塘江水色参数做出了有益的探索性工作。研究方法及结果对其他流域河流水色遥感研究具有参考价值。     

原位叶绿素a精密测量方案设计

叶绿素a原位监测在海洋生态系统健康评估与碳循环过程研究中有重要价值。设计了一套原位叶绿素a的精密测量方案,以交流调制检测为基本方法,开发了交流模拟放大通路,使用开关检波系统完成最后的检波。噪声测试实验表明系统电流分辨力达到186.27 fA。通过仿真和对比实验证明了开关检波系统具有很强的频率选择特性,在系统噪声抑制方面起重要作用。标准叶绿素标定实验表明在0～30μg/L内系统线性度良好,用直线拟合R2=0.998 5,检测灵敏度S=0.008 1μg/L,满足使用需求。     

13~2-N-(2-羟乙基)-15~3-N-(2-羟乙基)-17~3-甲氧羰基二氢卟吩e6-13~1-15~2-二酰胺的合成工艺及光学性质研究

本文以叶绿素-a为起始原料,经取代,加成等反应合成了一种新型叶绿素二氢卟吩衍生物132-N-(2-羟乙基)-153N-(2-羟乙基)-173-甲氧羰基二氢卟吩e6-131-152-二酰胺(Chlorin Amide e6,简称CAE),其化学结构均经UV-Vis,1H NMR,13C NMR及元素分析予以证实。通过对CAE合成工艺研究找到了最佳合成条件,并对光学性质和合成反应机理进行了研究。     

基于灰色关联分析-GA-BP模型的叶绿素a含量预测

为提高水体叶绿素a预测精度和收敛速率,提出一种基于灰色关联度分析和遗传算法优化BP神经网络预测水体叶绿素a的方法。即先采用灰色关联度分析法选取合适的水质指标作为输入因子,然后优化网络隐含层的结构参数,引入遗传算法优化BP神经网络的初始权值和阈值,最后以预测太湖叶绿素a为例进行比较分析。结果表明,优化神经网络隐含层数能进一步提高网络的预测精度、缩短训练时间;灰色关联分析-GA-BP模型相较于BP、GA-BP模型具有更高的预测精度和收敛速度,可为控制水环境监测和决策平台提供科学依据。