湖泊富营养化遥感评价模型的建立方法

中国处于不同富营养状态的湖泊已达75%,湖泊富营养化监测已成为我国迫切需要解决的技术问题。遥感技术能够低成本地对水体实现大尺度、快速监测,实现传统点状监测到面状监测的延伸。充分考虑我国现有的湖泊富营养化评价方法、参评指标相互关系的同时,通过研究参评指标的光谱特性分析其遥感可行性,提出了从水体的叶绿素a和悬浮物浓度入手,综合评价湖泊富营养化的遥感评价方法。     

云龙湖水质调查与评价

对云龙湖水质进行了调查与评价.在云龙湖东湖、西湖区各设置3个采样点,监测水体中TN、TP、Imn、NH3-N、DO和SD指标;分别使用模糊识别法和湖泊综合营养指数对水体进行水质评价与富营养化评价,结果表明,云龙湖水质级别为III类,其中TN、TP超标明显,水体呈现中度富营养化;不同功能区水质差异明显,东湖区水质优于西湖...     

基于灰色聚类方法的湖泊营养状态综合评价

将湖泊水体的营养状态看作一个灰色系统，建立用于识别湖泊营养状态属性的灰色聚类综合评价模型，将水质级别作为一个灰类，水质状态作为灰色变量，根据灰色白化权函数聚类方法来确定水体营养状况归类。以太湖为例，基于分布全湖的20个监测点数据，运用灰色聚类法对其进行富营养状态综合评价，结果表明，监测时段太湖大部分水体基本处于中营养水平，局部湖面达到中度富营养状态，客观地反映了太湖湖区水体营养状况。     

湖泊富营养化遥感监测研究进展

通过对近年来国内外应用遥感技术对湖泊富营养化监测及评价的研究情况进行了广泛的收集和分析,简述了湖泊富营养化遥感监测的基本原理,总结了湖泊富营养化多光谱遥感与高光谱遥感成果,提出了今后的重点研究方向.     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取；提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列；发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性；构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测；在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

模糊数学在丹江口水库富营养化评价中的应用

丹江口水库是南水北调中线工程水源地,其水质安全将直接影响调水工程的成败。基于2013年6月的水质监测结果,通过对水质指标的聚类,将丹江口水库划分子库区,并尝试使用模糊数学方法进行水质富营养化评价。结果表明,丹江口库区可分为6个子库区,各库区在透明度、溶解氧、浊度、高锰酸盐指数、总磷、硝酸盐氮和叶绿素a等理化指标均有显著差异;富营养化评价显示,库区总体营养状态级别为中营养。其中,坝前区域(库区Ⅰ)和丹库主体部分(库区Ⅵ)营养状态级别为贫营养,汉库原河道区(库区Ⅱ)为中营养,汉江入库口(库区Ⅲ)、汉库最大库湾(库区Ⅳ)、丹江入库口(库区Ⅴ)为轻度富营养。模糊综合评价法较好反映出水质的模糊性、连续性,使评价结果更加准确可靠。     

淀山湖富营养化驱动力初探

通过2015—2019年在淀山湖布设5个采样点，监测总氮、总磷等12项水质指标，运用综合营养状态指数法和潜在性富营养化评价法对该水域富营养化水平进行分析，采用主成分分析法初步确定影响该水域富营养化水平的主要驱动因子。结果表明：监测期间淀山湖水质因子时空分布差异显著。综合营养状态指数法评价结果表明，淀山湖富营养化在轻—中度富营养化水平，并且季节变化规律明显；潜在性富营养化法评价结果表明，监测期间淀山湖以磷限制潜在性富营养为主。驱动因子分析表明硝酸盐氮是该水域富营养化最主要的驱动因子。     

洪泽湖水体富营养化时空分布特征与影响因素分析

通过2014年—2017年对洪泽湖12个水质断面定期调查,采用营养状态指数(TLI)综合评价其水体富营养状态,同时应用主成分分析方法(PCA)分析其富营养化状态的时空变化特征。结果表明,洪泽湖70%以上的调查断面水质全年处于轻度富营养化状态,夏季是其富营养化最严重的季节;洪泽湖年内水体水质差异较大,而其水华特征并未呈现明显差异;洪泽湖富营养化很大程度上受制于营养盐的积累程度,并与湖泊透明度呈现极显著的负相关关系(p0.001),与湖水pH值呈现极显著的正相关关系。     

综合遥感与地面观测的巢湖水体富营养化评价

提出一种将地面观测数据空间插值与遥感反演结合的湖泊富营养化评价方法与业务化运行模式。对叶绿素a等可反演参数利用遥感影像反演,并利用实测值校正获得高精度反演结果;对总磷等不易反演参数采用空间插值获取全湖区数据,采用综合营养指数法对巢湖富营养化状态进行反演,获得2015年5月12日巢湖富营养化状态空间分布情况。结果表明,巢湖全湖为轻度和中度富营养化状态,呈现出西半湖高于东半湖的总体空间分布趋势。结合相关数据对巢湖富营养化成因进行推断,认为南淝河等上游河流各类营养物质输入量较大是造成西半湖北部富营养化严重的主要成因;西南部杭埠河等河流氮磷输入量较大,但其他营养物质输入较少,使得该区域总体呈现出富营养化程度偏低的现象。     

巢湖富营养化遥感监测

以巢湖为研究区,通过对蓝藻水华暴发程度与其光谱反射率之间关系的研究,确定MOD IS遥感影像识别水华暴发级别的阈值,对4类不同暴发程度蓝藻水华光谱特征进行遥感识别;进而确立巢湖水体富营养化评价方法,建立巢湖富营养化遥感反演模型,为实时监控巢湖水质,预警蓝藻水华暴发提供技术支持。     

GIS技术在东昌湖水质评价中的应用

利用GPS定位对东昌湖进行水样采集,把水质数据和坐标联系在一起,测定的结果利用GIS技术进行克里格插值.在用一部分数据验证其准确性之后,把全部水质数据以图的形式呈现出来,进行分析评价,通过与湖泊营养类型标准对比得出东昌湖大部分湖区出现富营养化现象,污染严重.证明GIS技术可以很好地应用于湖泊水质研究.     

淀山湖水质状况及富营养化评价

对2001年—2007年淀山湖水质监测结果进行了分析和评价。结果表明,淀山湖的水质均未达到Ⅱ类水质标准,主要超标项目为氨氮、TP、TN、石油类、IMn、COD和BOD5。综合营养状态指数为60.79～63.57,均处于中度富营养状态,chla与石油类和透明度具有很好的相关性,与TP具有较好的负相关性,与BOD5具有一定的负相关性,与水温、DO、IMn、COD、氨氮、TN的相关性不显著。chla季节变化较为明显。     

Selection of appropriate sampling stations in a lake through mapping

Much valuable information is obtained from water quality measurements and monitoring of lakes around the world. A powerful tool is the use of mapping techniques, as it offers potential use in water quality research. Both remote sensing techniques and traditional water quality monitoring are required to collect data at sampling stations. This study suggests another approach to determine the most appropriate distribution of sampling stations in water reservoirs that will be mapped for water quality parameters. Tests were conducted for the proposed approach for Secchi disc depth (SDD), chlorophyll-a, turbidity and suspended solids parameters in Lake Beysehir, Turkey. Results of analysis are available for a total of 30 sampling stations in August 2006. Ten sampling stations were used to model Lake Beysehir while the others were used for validation of the model. Sampling stations that offered the best representation of the lake for each parameter were determined. Then, the best representative sampling stations for all parameters in the study were determined. Moreover, in order to confirm the accuracy of these re-determined sampling stations, modelling was performed on the results of the analysis of June 2006, and it was found that the values obtained from the re-determined sampling stations were acceptable.     

Spatial and Temporal Variations of Eutrophication in Western Chaohu Lake, China

Chaohu Lake is one of the five largest fresh lakes in China. Now it is one of the three most eutrophic lakes of China attracting more and more attention in the world-wide-concern. From Zhongmiao Temple to Qitouzui Cape, the lake is divided into two parts. The eutrophication state of the lake western part is more serious than that of the eastern part, mainly because the former is the final place of industrial and municipal wastewater from Hefei City, the capital of Anhui Province. Through six routine national sampling sites of the Western Chaohu Lake, we analyzed the yearly variation of eutrophication from 1984 to 2004, the monthly variation from 2001 to 2004 and the spatial distribution and variation of the six sampling sites in the year 1992, 1996, 2000 and 2004 with Trophic State Index (TSI). The main reasons for Chaohu Lake eutrophication and the spatial and temporal variations of eutrophication in Western Chaohu Lake were discussed.     

The feasibility of monitoring wilderness lake chemistry with remote sensing methods

Wilderness lakes in the U.S. are at risk to the effects of atmospheric pollution. The results of the EPA Western Lake Survey, for example, show that many of the lakes in the West have very low concentrations of dissolved constituents, and are sensitive to acidification. Lakes located in wilderness areas were found to be particularly sensitive: median ANC values of 91.4 eq/1 compared to 282.7 eq/1 in non-wilderness areas. Sampling remote wilderness lakes is difficult and expensive. For example, the cost of sampling each lake in the National surface water survey was about $ 4000 per lake. Remote sensing methods may provide an alternative means of monitoring the chemistry of wilderness lakes. This study defines the feasibility of the remote monitoring of lake chemistry in the Adirondack Park region of New York by comparing measured lake chemistry with field reflectance measurements, remote reflectance measurements from aircraft and satellite and laboratory and airborne laser fluorosensor data.Water samples collected from a representative population of Adirondack Park lakes were analyzed for pH, acid neutralizing capacity (ANC), dissolved organic carbon (DOC), total reactive aluminum and plant pigment concentration concurrent with the collection of remote sensing data. Lake parameters estimated from field reflectance measurements which directly effect lake optical properties, total pigments, DOC, and turbidity were estimated with less error and more precision than those parameters not directly related to lake optics, pH, ANC and A1 concentration. Results from airborne MSS and Landsat MSS data produced lower R² values than estimates using field reflectance.The concentration of DOC can be estimated remotely by using laser fluorosensing. The spectral-fluorescence properties of DOC were correlated with the pH and aluminum concentrations in the lake water. Remotely measurable DOC fluorescence spectra were used to estimate DOC, H, and A1 concentrations.Of the methods investigated, laser fluorosensing shows the most promise for the remote prediction of lake DOC, hydrogen ion and aluminum concentration in Adirondack lakes while reflectance measures may be used to estimate lake chlorophyll, DOC and transparency. Given the large number of wilderness lakes and the difficulty of sampling in remote wilderness, remote sensing methods may provide an alternative, while less precise, method of monitoring lake chemistry. The applicability of these findings to lakes in other wilderness areas is unknown. Similar studies of the feasibility of monitoring Western wilderness lake chemistry with remote sensing methods are being initiated.Supported by an A. W. Mellon Foundation Grant to Dr. G. E. Likens while a student in the Section of Ecology and Systematics, Cornell University, Ithaca, NY and a Fellow of the Institute for Ecosystem Studies, New York Botanical Garden, Mary Flagler Cary Arboretum, Millbrook, NY.Contribution from Fourth World Wilderness Congress-Acid Rain Symposium, Denver (Estes Park), Colorado, September 11–18, 1987.     

抚仙湖、星云湖与杞麓湖营养状态演变及突变分析

为科学评价抚仙湖、星云湖和杞麓湖(简称三湖)营养状态及其变化趋势,基于三湖1991—2015年水质数据,采用综合营养状态指数法评价其富营养化水平,通过Mann-Kendall(Sneyers)方法判识三湖富营养化趋势及突变时间。结果表明:三湖都存在水质恶化现象,其综合营养状态指数及各分项指数均呈变差趋势,表征其营养物质在增加。三湖的营养化水平和演变时间存在显著差异,抚仙湖处于贫营养,星云湖由中营养转变为富营养,杞麓湖表现为中度-重度富营养化;抚仙湖和杞麓湖分别在2004、2011年出现突变点,星云湖自2000年后综合营养状态指数显著增加。基于三湖营养状态演变及趋势,结合变化特征及相关情况的讨论,提出对抚仙湖的管理应减少农业化肥和农药排放,对星云湖和杞麓湖的管理应削减高污染工矿企业排放等。