Delivery of nutrients and seston from the Muskegon River Watershed to near shore Lake Michigan

Drowned river mouth lakes are major features of coastal Great Lakes habitats and may influence nutrient and organic matter contributions from watersheds to near shore coastal zones. In May through October 2003, we measured loads of nutrients, surficial sediment, and seston to track the delivery of riverine-derived materials from the lower Muskegon River Watershed (MRW) into the near shore area of southeast Lake Michigan. Nutrient flux data indicated that seasonal loads of 1800 metric tons (MT) of particulate organic carbon, 3400 MT of dissolved organic carbon, and 24 MT of total phosphorus were discharged from the lower Muskegon River, with approximately 33% of TP load and 53% of the POC load intercepted within the drowned river mouth terminus, Muskegon Lake. Carbon: phosphorus molar ratios of seston in Muskegon River (C:P = 187) and Muskegon Lake (C:P = 176) were lower than in Lake Michigan (C:P = 334), indicating phosphorus limitation of phytoplankton in near shore Lake Michigan. Isotopic signatures of seston collected in Muskegon Lake were depleted in δ¹³C (− 30.8 ± 1.6‰) relative to the isotope signatures of seston from Lake Michigan (− 26.2 ± 1.3‰) or the mouth of the Muskegon River (− 28.1 ± 0.5‰), likely due to the presence of biogenic methane in Muskegon Lake. Seston δ¹⁵N increased on a strong east-to-west gradient within Muskegon Lake, indicating significant microbial processing of nutrients. The extent of nutrient uptake in Muskegon Lake altered the chemical and isotopic characterization of seston flowing into Lake Michigan from Muskegon River.     

Postglacial lake shoreline surveys and lacustrine paleobiotic records in northern Bruce and Grey counties,Ontario, Canada

Northern Grey and Bruce counties are situated centrally in the Lake Huron basin of the Great Lakes area of North America and are similarly central to the area of glacial Lake Algonquin, the largest glacial lake of the Great Lakes area. Ten survey traverses at sites in northern Grey and Bruce counties have documented the continuation of Lake Algonquin and Nipissing phase shorelines onto the Bruce Peninsula from previous work to the east. The Algonquin shoreline near 240 m ASL (above sea level) rises northward above land high enough to record it near Lion's Head. The Nipissing shoreline at 191 m ASL defines a shallow strait across the Bruce Peninsula near Ferndale, which was flooded temporarily at the maximum of the Nipissing transgression, separating northern Bruce Peninsula from the mainland. Uplift and Port Huron outlet downcutting later rejoined the island to the mainland as it is today. Raised beaches define Algonquin and Nipissing regressions by uplift using the Port Huron outlet. Paleobiotic records in a sand dune at Oliphant (molluscs), a Nipissing shorebluff along Sucker Creek (molluscs) and several sites in the former Nipissing shallow water strait near Ferndale (molluscs, ostracodes, plant macrofossils), provide paleoenvironmental data and supplement prior pollen studies at Lake Charles, Slough of Despond, and Hope Bay. Lake Algonquin deep water rhythmite clays are barren of fossils, whereas Nipissing shallow water silts are fossiliferous.     

Determinants of temperature in small coastal embayments of Lake Ontario

Along 25 km of the Lake Ontario shoreline near Toronto, Ontario, small coastal embayments (0.4–32 ha) have been constructed or modified by lake-infilling to restore warmwater fish habitat. The variation in thermal habitat quality for warmwater fishes among these embayments is very high; temperatures range from those found within a small pond to those of much cooler Lake Ontario. Since meteorological conditions and surface heat fluxes are almost identical, the temperature variation among embayments must be caused by differences in bathymetry or exchange with Lake Ontario. However, a previous study on these embayments found paradoxically that temperatures were not strongly associated with channel size or embayment bathymetry. This paper resolves the paradox by showing that flushing times for almost all of the constructed embayments were less than 1 day, and often less than 12 h. With so little time to warm within the embayments, water temperatures of almost all embayments remained very close to the temperatures of the adjacent lake waters. The coldest embayments connected directly to open Lake Ontario and warmer embayments connected to Lake Ontario through other embayments or protected harbors, where the inflowing water from Lake Ontario had already substantially warmed. To allow embayments along the exposed shoreline of Toronto to reach acceptable temperatures for warmwater fish, we use heat budgets to calculate that average summer flushing times must be increased from their current length of 1.5 to 5.5 h to approximately 30 h. Such changes could be achieved through large reductions in the channel cross section.     

白洋淀流域分布式水文模型开发与验证

针对白洋淀流域水资源保护工作开发了分布式水文模型WEP-L模型。WEP-L模型是对流域水循环过程与能量循环过程的综合模拟,具有较高的模拟精度。对白洋淀流域1956 } 2000年的径流模拟计算表明:主要水文站的相对误差在5%以内,Nash-Sutcliffe效率系数在0. 8以上,可以用于白洋淀流域的水文循环分析。     

CAS理论在滇池流域水资源配置中的应用

基于复杂适应系统（CAS—Complex Adaptive System）理论,研究滇池流域水资源配置系统的演化机制,描述滇池复杂适应水资源配置系统“学习”的特点和本质、各用水及供水主体的影响因素和反应规则。随后,建立了滇池流域水资源配置的CAS模型。基于此模型,利用Matlab优化平台,预测了不同规划年滇池流域各部门的需水量,给出了流域仅在滇池水域与掌鸠河云龙水库供水条件下的水资源配置结果。最后,分析了利用CAS理论研究流域水资源配置的优越性,并给出了相应的结论。     

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.     

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。