MODIFICATION OF NEILL'S EQUATION FOR STORM‐TIDE DESIGN FLOW ANALYSIS1

ABSTRACT: Design of bridges spanning tidal estuaries or bays requires an estimate of peak tidal flow. One common approach to estimating these flows (Neill's method) uses a first‐order approximation of uniform water surface rise in the water body. For larger water bodies, the assumptions of this method are decreasingly valid. This study develops a simple modification that accounts for the spatial variability in the response of tidal waterways to storm surge flows. The peak tidal flow predicted by Neill's equation is compared to the peak flow determined by numerical simulation of estuaries with simple geometries, ranging from 1 to 25 km in length, using the U.S. Army Corps of Engineers one‐dimensional unsteady flow model, UNET. Results indicate that, under certain conditions, it may be appropriate to apply a correction factor to the peak discharge and peak velocity predicted by Neill's method. An algorithm, developed by nonlinear regression, is presented for computing correction factors based on estuary length, shape, mean depth, and storm‐tide characteristics. The results should permit the design of more reliable, cost‐effective structures by providing more realistic estimates of the potential for bridge scour in tidal waterways, especially when a full solution of the unsteady flow equations is impractical.     

Archaeological management design

Like many environmental sciences, archaeology has its origins in an academic discipline. But organizational models derived from scholarly research are not adequate for large scale archaeological salvage excavations that must be carried out by many archaeologists within a short time. A non-traditional organization model, developed to parallel the organization of project engineering, is more responsive and can be designed to preserve the most significant traditional archaeological objectives.     

Reconstruction of the methane fluxes from the west Siberia gas fields by the 3D regional chemical transport model

A 3D mesoscale tropospheric photochemical transport model of high spatial resolution has been developed and used for assessment of the methane concentrations and methane emission in the West Siberian region of intensive mining of natural gas and oil deposits. The model is validated against the measurements of methane concentration at the surface and in the lower troposphere collected during July 1993 and June 1996 experiments. Comparison of the simulated and observed concentrations allowed to estimate that during the above periods the average natural methane fluxes were as high as 65 mg m⁻² day⁻¹. The anthropogenic methane fluxes (leakage from gas deposits) integrated over model domain during the same time period were about 20% of the total methane emission from relevant areas.     

Nest selection by snow petrels Pagodroma nivea in East Antarctica: Validating predictive habitat selection models at the continental scale

Little is known on the factors controlling distribution and abundance of snow petrels in Antarctica. Studying habitat selection through modeling may provide useful information on the relationships between this species and its environment, especially relevant in a climate change context, where habitat availability may change. Validating the predictive capability of habitat selection models with independent data is a vital step in assessing the performance of such models and their potential for predicting species’ distribution in poorly documented areas.From the results of ground surveys conducted in the Casey region (2002–2003, Wilkes Land, East Antarctica), habitat selection models based on a dataset of 4000 nests were created to predict the nesting distribution of snow petrels as a function of topography and substrate. In this study, the Casey models were tested at Mawson, 3800 km away from Casey. The location and characteristics of approximately 7700 snow petrel nests were collected during ground surveys (Summer 2004–2005). Using GIS, predictive maps of nest distribution were produced for the Mawson region with the models derived from the Casey datasets and predictions were compared to the observed data. Models performance was assessed using classification matrixes and Receiver operating characteristic (ROC) curves. Overall correct classification rates for the Casey models varied from 57% to 90%. However, two geomorphologically different sub-regions (coastal islands and inland mountains) were clearly distinguished in terms of habitat selection by Casey model predictions but also by the specific variations in coefficients of terms in new models, derived from the Mawson data sets. Observed variations in the snow petrel aggregations were found to be related to local habitat availability.We discuss the applicability of various types of models (GLM, CT) and investigate the effect of scale on the prediction of snow petrel habitats. While the Casey models created with data collected at the nest scale did not perform well at Mawson due to regional variations in nest micro-characteristics, the predictive performance of models created with data compiled at a coarser scale (habitat units) was satisfactory. Substrate type was the most robust predictor of nest presence between Casey and Mawson. This study demonstrate that it is possible to predict at the large scale the presence of snow petrel nests based on simple predictors such as topography and substrate, which can be obtained from aerial photography. Such methodologies have valuable applications in the management and conservation of this top predator and associated resources and may be applied to other Antarctic, Sub-Antarctic and lower latitudes species and in a variety of habitats.     

Comparing environmental influences on coral bleaching across and within species using clustered binomial regression

Differential susceptibility among reef-building coral species can lead to community shifts and loss of diversity as a result of temperature-induced mass bleaching events. We evaluate environmental influences on coral colony bleaching over an 8-year period in the Florida Keys, USA. Clustered binomial regression is used to develop models incorporating taxon-specific responses to the environment in order to identify conditions and species for which bleaching is likely to be severe. By building three separate models incorporating environment, community composition, and taxon-specific responses to environment, we show observed prevalence of bleaching reflects an interaction between community composition and local environmental conditions. Environmental variables, including elevated sea temperature, solar radiation, and reef depth, explained 90% and 78% of variability in colony bleaching across space and time, respectively. The effects of environmental variables were only partially explained (33% of variability) by corresponding differences in community composition. Taxon-specific models indicated individual coral species responded differently to local environmental conditions and had different sensitivities to temperature-induced bleaching. For many coral species, but not all, bleaching was exacerbated by high solar radiation. A 25% reduction in the probability of bleaching in shallow locations for one species may reflect an ability to acclimatize to local conditions. Overall, model results indicate predictions of coral bleaching require knowledge of not just the environmental conditions or community composition, but the responses of individual species to the environment. Model development provides a useful tool for coral reef management by quantifying the influence of the local environment on individual species bleaching sensitivities, identifying susceptible species, and predicting the likelihood of mass bleaching events with changing environmental conditions.     

ANAFORE: A stand-scale process-based forest model that includes wood tissue development and labile carbon storage in trees

A stand-scale forest model has been developed that dynamically simulates, besides carbon (C) and water (H₂O) fluxes, wood tissue development from physiological principles. The forest stand is described as consisting of trees of different size cohorts (for example, dominant, co-dominant and suppressed trees), either of the same or of different species (deciduous or coniferous). Half-hourly C and H₂O fluxes are modeled at the leaf, tree and stand level. In addition to total growth and yield, the model simulates the daily evolution of tracheid or vessel biomass and radius, parenchyma and branch development. From these data early and latewood biomass, wood tissue composition and density are calculated. Simulation of the labile C stored in the living tissues allows for simulation of trans-seasonal and trans-yearly effects, and improved simulations of long-term effects of environmental stresses on growth. A sensitivity analysis was performed to indicate the main parameters influencing simulated stem growth and wood quality at the tree and stand level. Case studies were performed for a temperate pine forest to illustrate the main model functioning and, more in particular, the simulation of the wood quality. The results indicate that the ANAFORE model is a useful tool for simultaneous analyses of wood quality development and forest ecosystem functioning.     

湟水河小流域地下水脆弱性评价

湟水河地处西北高原干旱地区,针对其流域地下水的特点,选取包气带介质、水位埋深、含水层介质、含水层厚度、净补给量和地形坡度共6个指标并运用三标度AHP法为各个指标赋予权重,构建了改进的DRASTIC模型。运用改进DRASTIC模型对湟水河的小流域范围的地下水脆弱性进行了评价。结果表明,湟水河沿岸的部分地区和西堡村附近地下水脆弱性高,地下水易受到污染。与传统DRASTIC模型相比,改进模型与实际情况更加吻合。     

扎龙湿地丹顶鹤繁殖栖息地的选择及扩散

景观演变对野生动物栖息地质量和连接度造成的影响,一直是威胁全球生物多样性保护的关键问题,开展扎龙湿地丹顶鹤（Grus japonensis）繁殖栖息地选择及繁殖期生境间的扩散研究,对野生丹顶鹤的保护具有重要的意义。首先利用需要“出现点”的生态位MAXENT模型,进行适宜栖息地选择研究。从水源、食物、干扰、隐蔽物四个方面选择明水面距离、土壤湿度、NDVI、道路距离和居民地距离五个环境变量作为丹顶鹤繁殖栖息地选择的影响因子,预测扎龙保护区可供丹顶鹤进行营巢繁殖的栖息地分布,并分析各影响因子的反应曲线。结果显示：丹顶鹤易于选择远离道路和居民地干扰且靠近明水面的区域作为营巢栖息地,栖息地土壤湿度较高并且植被覆盖较多。从MAXENT模型中提取了38个适宜栖息地斑块,基于电路理论模拟丹顶鹤繁殖期失去飞行能力时的多路径扩散,最大电流密度图突出了可能的“夹点”,模拟出具有一定宽度范围的连接区域,可供丹顶鹤在繁殖期间进行扩散。累积电流密度图突出了在维持网络连通性方面起到积极作用的斑块,并进行面积加权来评估适宜栖息地斑块的综合重要性。结果表明,在MAXENT模型预测出的适宜栖息地斑块基础上,考虑丹顶鹤繁殖期的迁移扩散行为,利用累积电流密度面积加权来评估适宜栖息地斑块的综合重要性,得到的适宜性等级更符合丹顶鹤真实巢址的分布。研究成果可为保护区丹顶鹤栖息繁殖生境的恢复和保护提供科学依据。     

基于TUV模式的对流层光解速率影响因子的研究

应用TUV辐射传输模式进行了一系列的敏感性试验,以期确定影响对流层O₃和NO₂光解速率的关键性因子.结果表明,气溶胶的光学性质对光解速率的影响存在明显差异.在气溶胶光学厚度（AOD）一定的情况下,散射性越强,近地面光解速率越大;当AOD从0.5增加至2.5,J[O¹D]和J[NO₂]极大值分别下降30.3%和13.1%.光解速率对较小的云光学厚度的变化比较敏感.云对J[NO₂]的影响存在明显的时间差异,在早晨和傍晚,J[NO₂]的衰减可以达到12%,而午时,J[NO₂]的衰减不足4%;在垂直方向上,云层的存在能够减小通过云层的光化辐射通量,有效降低云下光解速率,而云滴的后向散射特性能增大云上的光解速率.臭氧能够吸收300nm左右的紫外辐射,因而臭氧柱浓度变化对J[O¹D]有显著的影响,臭氧柱浓度从200DU增加至400DU,J[O¹D]极大值下降了53.1%,J[NO₂]极大值仅降低了1.0%.同时发现,气溶胶和云相对位置的改变对光解速率的垂直分布有较大的影响,气溶胶在云上时,高层的光解速率明显增大,且气溶胶的散射性越强,光解速率的增幅越大;当吸收性气溶胶位于云上时,使得高层光化辐射通量大量衰减,此时云层对于光解速率的影响比较微弱.     

Development and validation of abiotic ligand model for nickel toxicity to wheat (Triticum aestivum)

A terrestrial biotic ligand model (t-BLM) was developed to predict nickel toxicity to wheat (Triticum aestivum) root elongation in hydroponic solutions. The competitive effects of five major cations (Ca²⁺, Mg²⁺, Na⁺, K⁺ and H⁺) on Ni toxicity were investigated and Mg²⁺ was found to be a strong competitor, while H²⁺ showed less competing effect. Besides free Ni²⁺, the toxicity induced by the species NiHCO₃⁺ was non-neglect able at pH > 7 because NiHCO₃⁺ occupied a significant fraction of total Ni under such condition. Thus, a t-BLM including Ni²⁺, NiHCO₃⁺, Mg²⁺, and H⁺ could successfully predict the nickel toxicity to wheat root elongation and it performed better prediction than the conventional free ion activity model. In addition, the model was examined with two sets of independent experiments, which contained multiple cations and low-molecular-weight organic acids to mimic the rhizo-sphere condition. The developed t-BLM well predicted nickel toxicity in both experiments since it can account in both complexation and competition effects, suggesting its potential to be used in a complicated matrix like soil solution. This study provides direct evidence that the t-BLM is a reliable method for the risk assessment of nickel in terrestrial system.