CNGI青海湖系统建设中的若干技术问题

CNGI 青海湖系统支撑青海湖区域的生态保护和多学科交叉融合的科研协作。针对青海湖基础设施种类众多的特点,我们发展了 IPv6 相关关键技术,应用于基础网络环境建设、数据传输、设备管理与状态监控等多个层面,并充分考虑了由此带来的安全隐患,制定了相应安全策略。这些技术可以支持多种传感器构成的 IPv6 网络,并支持 IPv6 的相关应用软件研发,促进大规模、跨领域复杂科学问题研究工作。     

Distribution, relative abundance, and prey demand by double-crested cormorants on Manitoulin Island lakes vs. Lake Huron Coast

An aerial distance sampling survey of double-crested cormorants (Phalacrocorax auritus) was conducted in the northern region of Lake Huron (North Channel; four largest lakes of Manitoulin Island; South Shore of Manitoulin Is. facing the main body of the lake) to assess the relative distribution, abundance and prey demand by cormorants on inland lake vs. coastal habitat. On a per area basis, the density (approx. 1-2 cormorants ? km^− 2) and prey demand (approx. 1.2 kg ha^− 1) of cormorants in the four inland lakes matched that of the North Channel. The South Shore had approximately half the density and prey demand as the other two areas. Cormorants on the inland lakes of Manitoulin Island represented 13% early in the season and a high of 33% of the total population for this region of Lake Huron later in the summer. Estimating regional distributions of cormorants within the Great Lakes basin is important because mapped nest colonies and nest counts are not representative of the actual distribution of foraging cormorants during and after the nesting season. There are two general conclusions to emerge from this survey. First, aquatic productivity from both Great Lakes coast and inland lakes contributes to trends in population and distribution of cormorants in the northern region of Lake Huron and perhaps elsewhere. Second, inland aquatic ecosystems are important throughout a season for foraging cormorants from the Great Lakes and may become more important as Great Lake productivity trends downward.     

基于遥感和GIS技术的青海湖环湖地区生态环境脆弱性评价

以青海湖环湖地区为研究区,从生态环境脆弱性的影响因子和脆弱性形成的结果表现入手,通过遥感与GIS技术提取出8项生态因子包括植被指数、土壤亮度和土壤湿度指数、高程和坡度以及气温降水和土地利用作为评价指标,利用层次分析法（AHP）计算各评价指标的权重,然后计算研究区综合脆弱度,并根据统计结果将脆弱度的大小划分为微度脆弱、轻度脆弱、中度脆弱和重度脆弱4个不同等级。结果表明：研究区轻度脆弱和中度脆弱所占面积比例较大,分别占到研究区陆地面积的35.2%和40.7%,说明该区总体环境质量较好。     

A second-order analytic solution for oscillatory wind-induced flow in an idealized shallow lake

We present a second-order analytic solution to the nonlinear depth-integrated shallow water equations for free-surface oscillatory wind-driven flow in an idealized lake. Expressing the solution as an asymptotic expansion in the dimensionless wave amplitude (ζ/h), which is considered to be a small parameter, enables simplification of the governing equations and permits the use of a perturbation approach to solve them.This analytic solution provides a benchmark for testing numerical models. In particular, the main merit of this solution is that it accounts for advective effects, which are typically omitted from analytic solutions of two-dimensional free surface flow. In order to retain these effects in an analytic solution, we restrict our attention to forcing from a monochromatic wind stress, consider a constant depth rectangular lake, and simplify the governing equations by omitting the Coriolis and eddy viscosity terms and using a linearised friction factor. As such, the analytic solution is of limited use for considering real world problems. Due to the complexity of the analytic solution computer code for this solution is available online.Our solution is valid for cases where changes in the water surface level are small compared with the depth of the lake, and the advective terms in the momentum equations are small compared with acceleration terms. We examine the validity of these assumptions for three test cases, and compare the second-order analytic solution to numerical results to verify an existing hydrodynamic model.     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

Dust source identification using MODIS: A comparison of techniques applied to the Lake Eyre Basin, Australia

The impact of mineral aerosol (dust) in the Earth's system depends on particle characteristics which are initially determined by the terrestrial sources from which the sediments are entrained. Remote sensing is an established method for the detection and mapping of dust events, and has recently been used to identify dust source locations with varying degrees of success. This paper compares and evaluates five principal methods, using MODIS Level 1B and MODIS Level 2 aerosol data, to: (a) differentiate dust (mineral aerosol) from non-dust, and (2) determine the extent to which they enable the source of the dust to be discerned. The five MODIS L1B methods used here are: (1) un-processed false colour composite (FCC), (2) brightness temperature difference, (3) Ackerman's (1997: J.Geophys. Res., 102, 17069-17080) procedure, (4) Miller's (2003:Geophys. Res. Lett. 30, 20, art.no.2071) dust enhancement algorithm and (5) Roskovensky and Liou's (2005: Geophys. Res. Lett. 32, L12809) dust differentiation algorithm; the aerosol product is MODIS Deep Blue (Hsu et al., 2004: IEEE Trans. Geosci. Rem. Sensing, 42, 557-569), which is optimised for use over bright surfaces (i.e. deserts). These are applied to four significant dust events from the Lake Eyre Basin, Australia. OMI AI was also examined for each event to provide an independent assessment of dust presence and plume location. All of the techniques were successful in detecting dust when compared to FCCs, but the most effective technique for source determination varied from event to event depending on factors such as cloud cover, dust plume mineralogy and surface reflectance. Significantly, to optimise dust detection using the MODIS L1B approaches, the recommended dust/non-dust thresholds had to be considerably adjusted on an event by event basis. MODIS L2 aerosol data retrievals were also found to vary in quality significantly between events; being affected in particular by cloud masking difficulties. In general, we find that OMI AI and MODIS AQUA L1B and L2 data are complementary; the former are ideal for initial dust detection, the latter can be used to both identify plumes and sources at high spatial resolution. Overall, approaches using brightness temperature difference (BT10-11) are the most consistently reliable technique for dust source identification in the Lake Eyre Basin. One reason for this is that this enclosed basin contains multiple dust sources with contrasting geochemical signatures. In this instance, BTD data are not affected significantly by perturbations in dust mineralogy. However, the other algorithms tested (including MODIS Deep Blue) were all influenced by ground surface reflectance or dust mineralogy; making it impossible to use one single MODIS L1B or L2 data type for all events (or even for a single multiple-plume event). There is, however, considerable potential to exploit this anomaly, and to use dust detection algorithms to obtain information about dust mineralogy.     

Correcting for the influence of frozen lakes in satellite microwave radiometer observations through application of a microwave emission model

The spatial resolution of passive microwave observations from space is of the order of tens of kilometers with currently available instruments, such as the Special Sensor Microwave/Imager (SSM/I) and Advanced Microwave Scanning Radiometer (AMSR-E). The large field of view of these instruments dictates that the observed brightness temperature can originate from heterogeneous land cover, with different vegetation and surface properties.In this study, we assess the influence of freshwater lakes on the observed brightness temperature of AMSR-E in winter conditions. The study focuses on the geographic region of Finland, where lakes account for 10% of the total terrestrial area. We present a method to mitigate for the influence of lakes through forward modeling of snow covered lakes, as a part of a microwave emission simulation scheme of space-borne observations. We apply a forward model to predict brightness temperatures of snow covered sceneries over several winter seasons, using available data on snow cover, vegetation and lake ice cover to set the forward model input parameters. Comparison of model estimates with space-borne observations shows that the modeling accuracy improves in the majority of examined cases when lakes are accounted for, with respect to the case where lakes are not included in the simulation. Moreover, we present a method for applying the correction to the retrieval of Snow Water Equivalent (SWE) in lake-rich areas, using a numerical inversion method of the forward model. In a comparison to available independent validation data on SWE, also the retrieval accuracy is seen to improve when applying the influence of snow covered lakes in the emission model.     

Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China

Productive wetland systems at land-water interfaces that provide unique ecosystem services are challenging to study because of water dynamics, complex surface cover and constrained field access. We applied object-based image analysis and supervised classification to four 32-m Beijing-1 microsatellite images to examine broad-scale surface cover composition and its change during November 2007-March 2008 low water season at Poyang Lake, the largest freshwater lake-wetland system in China (> 4000 km²). We proposed a novel method for semi-automated selection of training objects in this heterogeneous landscape using extreme values of spectral indices (SIs) estimated from satellite data. Dynamics of the major wetland cover types (Water, Mudflat, Vegetation and Sand) were investigated both as transitions among primary classes based on maximum membership value, and as changes in memberships to all classes even under no change in a primary class. Fuzzy classification accuracy was evaluated as match frequencies between classification outcome and a) the best reference candidate class (MAX function) and b) any acceptable reference class (RIGHT function). MAX-based accuracy was relatively high for Vegetation (≥ 90%), Water (≥ 82%), Mudflat (≥ 76%) and the smallest-area Sand (≥ 75%) in all scenes; these scores improved with the RIGHT function to 87-100%. Classification uncertainty assessed as the proportion of fuzzy object area within a class at a given fuzzy threshold value was the highest for all classes in November 2007, and consistently higher for Mudflat than for other classes in all scenes. Vegetation was the dominant class in all scenes, occupying 41.2-49.3% of the study area. Object memberships to Vegetation mostly declined from November 2007 to February 2008 and increased substantially only in February-March 2008, possibly reflecting growing season conditions and grazing. Spatial extent of Water both declined and increased during the study period, reflecting precipitation and hydrological events. The “fuzziest” Mudflat class was involved in major detected transitions among classes and declined in classification accuracy by March 2008, representing a key target for finer-scale research. Future work should introduce Vegetation sub-classes reflecting differences in phenology and alternative methods to discriminate Mudflat from other classes. Results can be used to guide field sampling and top-down landscape analyses in this wetland.     

环鄱阳湖区域污染净化型农业产业化发展模式构想

在环鄱阳湖区域实施污染净化型农业的产业化是控制湖区面源污染,实现经济转型的重要策略。本文论述了污染净化型农业特点及其在鄱阳湖实施产业化的有利条件,提出了适合鄱阳湖区域特色的污染净化型农业产业化模式。     

浮选柱处理滇池污水的工艺初探

针对滇池水污染的状况和治理现状，对目前国内采用ICEAS工艺的污水处理厂脱氮除磷效果不佳的现状，此工艺采用浮选柱作为浮选设备，并采用充以臭氧等新的技术，能更有效地解决滇池污水中的氮、磷、有机悬浮物、COD污染物，预计会有很好的研究价值和应用前景。