Retrieving leaf area index for coniferous forest in Xingguo County, China with Landsat ETM+ images

Spatial distributions of the leaf area index (LAI) needed for carbon cycle modeling in Xingguo County, China were estimated based on correlations between the field-measurements and vegetation indices (VIs). After making geometric and atmospheric corrections to two Landsat ETM+ images, one in January 2000 and the other in May 2003, three VIs (SR, NDVI, and RSR) were derived, and their separate correlations with ground LAI measurements were established. The correlation with RSR was the highest among the three VIs. The retrieved LAI values for January 2000 were lower than those for May 2003 because of a small seasonal variation in the coniferous forests (predominantly masson pine) and the decrease in the understorey vegetation during winter.     

基于Landsat／TM和ETM＋的理塘草地沙化趋势及其驱动力分析

文章利用1989、1994、2000和2005年的4期Landsat／TM,ETM＋遥感影像,在几何校正、辐射定标、大气校正的基础上计算了归一化植被指数（NDVI）,建立最小二乘法线性回归方程对多时相NDVI进行同化处理,基于二分模型提取植被覆盖度并转换成荒漠化指数（DI）,对理塘县城附近约103．1km2范围的分类研究结果表明：（1）分为无沙化、轻度、中度、重度和严重沙化5级,其中2005年中度、重度和严重沙化面积分别为2．562km2、2．925km2和1．576km2;中度沙化比1989年减少9．69％,重度和严重沙化分别增多35．79％和161．8％;（2）2005年中度以上沙化面积比1989年增加1．470km2,增加了26．3％,年增加率为1．47％;（3）沙化面积呈前期小、中期大幅增加、后期增加减缓的总体趋势;（4）降水量和风速因子的变化趋势有利于缓解沙化,气温变化趋势没有反映出对沙化的促进作用。人类活动是造成沙化趋于恶化的主要因素;（5）沙化增加趋势与同类研究结果一致。     

Mapping wetlands in the Lower Mekong Basin for wetland resource and conservation management using Landsat ETM images and field survey data

The Mekong River Basin is considered to be the second most species rich river basin in the world. The 795,000 km(2) catchment encompasses several ecoregions, incorporating biodiverse and productive wetland systems. Eighty percent of the rapidly expanding population of the Lower Mekong Basin (LMB), made up in part by Lao PDR, Thailand, Cambodia and Viet Nam, live in rural areas and are heavily reliant on wetland resources. As the populations of Cambodia and Lao PDR will double in the next 20 years, pressure on natural resources and particularly wetlands can only increase. For development planning, resource and conservation management to incorporate wetland issues, information on the distribution and character of Mekong wetlands is essential. The existing but outdated wetland maps were compiled from secondary landuse-landcover data, have limited coverage, poor thematic accuracy and no meta-data. Therefore the Mekong River Commission (MRC) undertook to produce new wetland coverage for the LMB. As resources, funding and regional capacity are limited, it was determined that the method applied should use existing facilities, be easily adaptable, and replicable locally. For the product to be useful it must be accepted by local governments and decision makers. The results must be of acceptable accuracy (>75%) and the methodology should be relatively understandable to non-experts. In the first stage of this exercise, field survey was conducted at five pilot sites covering a range of typical wetland habitats (MRC wetland classification) to supply data for a supervised classification of Landsat ETM images from the existing MRC archive. Images were analysed using ERDAS IMAGINE and applying Maximum Likelihood Classification. Field data were reserved to apply formal accuracy assessment to the final wetland habitat maps, with resulting accuracy ranging from 77 to 94%. The maps produced are now in use at a Provincial and National level in three countries for resource and conservation planning and management applications, including designation of a Ramsar wetland site of international importance.     

双流县金马河饮用水源地水质自动监测系统介绍

为了及时、准确地掌握金马河水质状况,预警重大或流域性水质污染事件,确保饮用水水源地安全,双流县于2008年建立了县级饮用水源水质自动监测系统。本文详细介绍了水质自动监测系统的组成和特点,为其他水质自动系统的构建提供了有益的参考。     

Modeling the Impacts of Farming Practices on Water Quality in the Little Miami River Basin

Since intensive farming practices are essential to produce enough food for the increasing population, farmers have been using more inorganic fertilizers, pesticides, and herbicides. Agricultural lands are currently one of the major sources of non-point source pollution. However, by changing farming practices in terms of tillage and crop rotation, the levels of contamination can be reduced and the quality of soil and water resources can be improved. Thus, there is a need to investigate the amalgamated hydrologic effects when various tillage and crop rotation practices are operated in tandem. In this study, the Soil Water Assessment Tool (SWAT) was utilized to evaluate the individual and combined impacts of various farming practices on flow, sediment, ammonia, and total phosphorus loads in the Little Miami River basin. The model was calibrated and validated using the 1990–1994 and 1980–1984 data sets, respectively. The simulated results revealed that the SWAT model provided a good simulation performance. For those tested farming scenarios, no-tillage (NT) offered more environmental benefits than moldboard plowing (MP). Flow, sediment, ammonia, and total phosphorus under NT were lower than those under MP. In terms of crop rotation, continuous soybean and corn–soybean rotation were able to reduce sediment, ammonia, and total phosphorus loads. When the combined effects of tillage and crop rotation were examined, it was found that NT with continuous soybean or corn–soybean rotation could greatly restrain the loss of sediments and nutrients to receiving waters. Since corn–soybean rotation provides higher economic revenue, a combination of NT and corn–soybean rotation can be a viable system for successful farming.     

Human Influences on Water Quality in Great Lakes Coastal Wetlands

A better understanding of relationships between human activities and water chemistry is needed to identify and manage sources of anthropogenic stress in Great Lakes coastal wetlands. The objective of the study described in this article was to characterize relationships between water chemistry and multiple classes of human activity (agriculture, population and development, point source pollution, and atmospheric deposition). We also evaluated the influence of geomorphology and biogeographic factors on stressor-water quality relationships. We collected water chemistry data from 98 coastal wetlands distributed along the United States shoreline of the Laurentian Great Lakes and GIS-based stressor data from the associated drainage basin to examine stressor-water quality relationships. The sampling captured broad ranges (1.5–2 orders of magnitude) in total phosphorus (TP), total nitrogen (TN), dissolved inorganic nitrogen (DIN), total suspended solids (TSS), chlorophyll a (Chl a), and chloride; concentrations were strongly correlated with stressor metrics. Hierarchical partitioning and all-subsets regression analyses were used to evaluate the independent influence of different stressor classes on water quality and to identify best predictive models. Results showed that all categories of stress influenced water quality and that the relative influence of different classes of disturbance varied among water quality parameters. Chloride exhibited the strongest relationships with stressors followed in order by TN, Chl a, TP, TSS, and DIN. In general, coarse scale classification of wetlands by morphology (three wetland classes: riverine, protected, open coastal) and biogeography (two ecoprovinces: Eastern Broadleaf Forest [EBF] and Laurentian Mixed Forest [LMF]) did not improve predictive models. This study provides strong evidence of the link between water chemistry and human stress in Great Lakes coastal wetlands and can be used to inform management efforts to improve water quality in Great Lakes coastal ecosystems.     

因子分析法在江安河地表水水质评价中的应用

因子分析法是主成份分析方法的推广和深化，是把原来多个变量化为少数几个综合指标的一种统计方法。本文通过该法对江安河四川大学双流校区段水质进行了评价，结果表明，该水体受到了不同程度的有机物污染，其中非离子氨、阴离子洗涤剂、化学耗氧量，溶解氧所占的负荷最大。     

多级模糊模式识别方法用于河流水质评价

应用多级模糊模式识别模型进行水质量分类评价,克服了最大隶属度原则所不适用的地方,而且以相对隶属度、隶属函数为基础理论,使隶属度、隶属函数的计算更容易。建立了多级模糊模式识别模型,并应用于汾河水质分类评价中,应用结果表明,该方法合理、可行。     

洪泽湖底栖动物群落结构及水质季节变化分析

为阐明洪泽湖底栖动物的群落结构及水质变化状况,采用生物多样性指数法、综合污染指数、CCA分析等方法,对洪泽湖的底栖动物群落结构空间布局及其水质状况进行了季度调查,探究环境因子对底栖动物生长的影响规律.结果 表明:(1)底栖动物种类以甲壳纲、多毛纲、双壳纲为主;(2) CPI分析表明,TN、TP是洪泽湖主要的超地表水Ⅲ类...     

A Water Quality Index Applied to an International Shared River Basin: The Case of the Douro River

A Water Quality Index (WQI) is a numeric expression used to evaluate the quality of a given water body and to be easily understood by managers. In this study, a modified nine-parameter Scottish WQI was used to assess the monthly water quality of the Douro River during a 10-year period (1992–2001), scaled from zero (lowest) to 100% (highest). The 98,000 km² of the Douro River international watershed is the largest in the Iberian Peninsula, split between upstream Spain (80%) and downstream Portugal (20%). Three locations were surveyed: at the Portuguese–Spanish border, 350 km from the river mouth; 180 km from the mouth, where the river becomes exclusively Portuguese; and 21 km from the mouth. The water received by Portugal from Spain showed the poorest quality (WQI 47.3 ± 0.7%); quality increased steadily downstream, up to 61.7 ± 0.7%. In general, the water quality at all three sites was medium to poor. Seasonally, water quality decreased from winter to summer, but no statistical relationship between quality and discharge rate could be established. Depending on the location, different parameters were responsible for the episodic decline of quality: high conductivity and low oxygen content in the uppermost reservoir, and fecal coliform contamination downstream. This study shows the need to enforce the existing international bilateral agreements and to implement the European Water Quality Directive in order to improve the water quantity and quality received by the downstream country of a shared watershed, especially because two million inhabitants use the water from the last river location as their only source of drinking water.     

水污染指数法在湘江长沙段支流水质评价中的应用分析

以湘江长沙段支流17个常规监测断面2016～2018年水质监测数据为基础,运用水污染指数法对其水质状况进行评价,并与单因子评价法、综合污染指数法的评价结果进行比较分析.结果 表明:水污染指数法能够同时满足水质类别评价和水质定量评价,且评价结果与传统方法基本保持一致,该方法在湘江长沙段主要支流水质评价中具有较好的适用性.     

阶梯小水电站开发对永定河水质影响及防治对策

随着近年工业的发展,工业对电需求量急剧增加。永定县小水电站无节制开发,已对永定河水体造成一定的污染。监测结果表明,小水电站所在的河段水质比永定河其它断面污染严重,已经满足不了永定水环境功能区划的要求。     

Assessment of the Water Quality and Ecosystem Health of the Great Barrier Reef (Australia): Conceptual Models

Run-off containing increased concentrations of sediment, nutrients, and pesticides from land-based anthropogenic activities is a significant influence on water quality and the ecologic conditions of nearshore areas of the Great Barrier Reef World Heritage Area, Australia. The potential and actual impacts of increased pollutant concentrations range from bioaccumulation of contaminants and decreased photosynthetic capacity to major shifts in community structure and health of mangrove, coral reef, and seagrass ecosystems. A detailed conceptual model underpins and illustrates the links between the main anthropogenic pressures or threats (dry-land cattle grazing and intensive sugar cane cropping) and the production of key contaminants or stressors of Great Barrier Reef water quality. The conceptual model also includes longer-term threats to Great Barrier Reef water quality and ecosystem health, such as global climate change, that will potentially confound direct model interrelationships. The model recognises that system-specific attributes, such as monsoonal wind direction, rainfall intensity, and flood plume residence times, will act as system filters to modify the effects of any water-quality system stressor. The model also summarises key ecosystem responses in ecosystem health that can be monitored through indicators at catchment, riverine, and marine scales. Selected indicators include riverine and marine water quality, inshore coral reef and seagrass status, and biota pollutant burdens. These indicators have been adopted as components of a long-term monitoring program to enable assessment of the effectiveness of change in catchment-management practices in improving Great Barrier Reef (and adjacent catchment) water quality under the Queensland and Australian Governments’ Reef Water Quality Protection Plan.     

青竹江水环境耗氧污染物含量分布特征及质量评价

本文对青竹江水环境中耗氧污染物(CODCr、BOD5和NH3-N)含量分布特征进行了探讨,并对青竹江的水质质量进行评价。结果表明,青竹江从上游到下游水体中污染物含量为增加趋势,在时间上也存在一定的变化,枯水期水体中污染物含量高于平水期和丰水期,目前青竹江综合水质可满足Ⅱ类水质标准要求。     

小管径配水管网水质模型脆弱性研究

小管径配水管网水质模型模拟结果精度高.但由于管网工况的复杂性,水质模型预测结果具有不确定性.通过定义水质模型的本质脆弱性,建立脆弱性分析模型,采用指标评价法研究模型在不同验证工况下的脆弱性,可以有效降低水质模型预测风险、构建水质模型失效“防火墙”,为帮助供水企业更为广泛地应用模型预测水质提供理论依据.     

“十一五”期间常州市水环境质量变化关联分析

深入考察水环境质量变化的情况、分析水环境质量变化的规律,需要比较分析水环境质量的变化及与社会经济发展、自然条件的相关性,才能更准确地把握水环境的变化轨迹。对常州市＂十一五＂期间水环境环境质量变化与社会经济发展及水资源量等指标进行比较和相关性分析。结果表明：＂十一五＂期间,常州市通过大力开展主要污染物减排,调整产业结构,加强污水集中处理力度等有效措施,主要污染物排放量明显下降,水环境质量明显改善。     

Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique

Artificial neural networks (ANNs) are being used increasingly to predict and forecast water resources' variables. The feed-forward neural network modeling technique is the most widely used ANN type in water resources applications. The main purpose of the study is to investigate the abilities of an artificial neural networks' (ANNs) model to improve the accuracy of the biological oxygen demand (BOD) estimation. Many of the water quality variables (chemical oxygen demand, temperature, dissolved oxygen, water flow, chlorophyll a and nutrients, ammonia, nitrite, nitrate) that affect biological oxygen demand concentrations were collected at 11 sampling sites in the Melen River Basin during 2001-2002. To develop an ANN model for estimating BOD, the available data set was partitioned into a training set and a test set according to station. In order to reach an optimum amount of hidden layer nodes, nodes 2, 3, 5, 10 were tested. Within this range, the ANN architecture having 8 inputs and 1 hidden layer with 3 nodes gives the best choice. Comparison of results reveals that the ANN model gives reasonable estimates for the BOD prediction.     

武汉市某小型浅水人工湖泊水质季节性变化研究

对武汉市某小型浅水人工湖泊水质进行一年的理化监测并分析,结果显示：COD、BOD5均有季节性变化的规律;气温的变化影响湖水及底泥中微生物的活性;天然降水量不同对湖水稀释程度不同;底泥的污染物释放量受温度影响;该水体可生化性差。据此,提出保护湖水的措施。     

河网水质模型研究进展

纵观水质模型的研究、应用及相关科学的发展,本文针对现有的水质模型做了分析评价,简要介绍了河网水质模型的未来研究趋势,并提出了几点建议。