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A multimodel comparison for assessing water temperatures under changing climate conditions via the equilibrium temperature concept: case study of the Middle Loire River,France

This paper investigates three categories of models that are derived from the equilibrium temperature concept to estimate water temperatures in the Loire River in France and the sensitivity to changes in hydrology and climate. We test the models' individual performances for simulating water temperatures and assess the variability of the thermal responses under the extreme changing climate scenarios that are projected for 2081–2100. We attempt to identify the most reliable models for studying the impact of climate change on river temperature (T_w). Six models are based on a linear relationship between air temperatures (T_a) and equilibrium temperatures (T_e), six depend on a logistic relationship, and six rely on the closure of heat budgets. For each category, three approaches that account for the river's thermal exchange coefficient are tested. In addition to air temperatures, an index of day length is incorporated to compute equilibrium temperatures. Each model is analysed in terms of its ability to simulate the seasonal patterns of river temperatures and heat peaks. We found that including the day length as a covariate in regression‐based approaches improves the performance in comparison with classical approaches that use only T_a. Moreover, the regression‐based models that rely on the logistic relationship between T_e and T_a exhibit root mean square errors comparable (0.90 °C) with those obtained with a classical five‐term heat budget model (0.82 °C), despite a small number of required forcing variables. In contrast, the regressive models that are based on a linear relationship T_e = f(T_a) fail to simulate the heat peaks and are not advisable for climate change studies. The regression‐based approaches that are based on a logistic relationship and the heat balance approaches generate notably similar responses to the projected climate changes scenarios. This similarity suggests that sophisticated thermal models are not preferable to cruder ones, which are less time‐consuming and require fewer input data. Copyright © 2012 John Wiley & Sons, Ltd.     

Probabilistic modelling of auto-correlation characteristics of heterogeneous slopes

Spatial variability of soil materials has long been recognised as an important factor influencing the reliability of geo-structures. This study stochastically investigates the influence of spatial variability of shear strength on the stability of heterogeneous slopes, focusing on the auto-correlation function, auto-correlation distance and cross-correlation between soil parameters. The finite element method is merged with the random field theory to probabilistically evaluate factor of safety and probability of failure via Monte-Carlo simulations. The simulation procedure is explained in detail with suggestions on improving efficiency of the Monte-Carlo process. A simple procedure to create cross-correlation between random variables, which allows direct comparison of the influence of each strength variable, is discussed. The results show that the auto-correlation distance and cross-correlation can significantly influence slope stability, while the choice of auto-correlation function only has a minor effect. An equation relating the probability of failure with the auto-correlation distance is suggested in light of the analyses performed in this work and other results from the literature.     

Phytoremediation of heavy metal‐contaminated water and sediment by Eleocharis acicularis

Phytoremediation is an environmental remediation technique that takes advantage of plant physiology and metabolism. The unique property of heavy metal hyperaccumulation by the macrophyte Eleocharis acicularis is of great significance in the phytoremediation of water and sediments contaminated by heavy metals at mine sites. In this study, a field cultivation experiment was performed to examine the applicability of E. acicularis to the remediation of water contaminated by heavy metals. The highest concentrations of heavy metals in the shoots of E. acicularis were 20 200 mg Cu/kg, 14 200 mg Zn/kg, 1740 mg As/kg, 894 mg Pb/kg, and 239 mg Cd/kg. The concentrations of Cu, Zn, As, Cd, and Pb in the shoots correlate with their concentrations in the soil in a log‐linear fashion. The bioconcentration factor for these elements decreases log‐linearly with increasing concentration in the soil. The results indicate the ability of E. acicularis to hyperaccumulate Cu, Zn, As, and Cd under natural conditions, making it a good candidate species for the phytoremediation of water contaminated by heavy metals.     

A study of the connection between tropical cyclone track and intensity errors in the WRF model

This study examines the dependence of the tropical cyclone (TC) intensity errors on the track errors in the Weather Research and Forecasting (WRF-ARW) model. By using the National Centers for Environmental Prediction global final analysis as the initial and boundary conditions for cloud-resolving simulations of TC cases that have small track errors, it is found that the 2- and 3-day intensity errors in the North Atlantic basin can be reduced to 15 and 19 % when the track errors decrease to 55 and 76 %, respectively, whereas the 1-day intensity error shows no significant reduction despite more than 30 % decrease of the 1-day track error. For the North-Western Pacific basin, the percentage of intensity reduction is somewhat similar with the 2- and 3-day intensity errors improved by about 15 and 19 %, respectively. This suggests that future improvement of the TC track forecast skill in the WRF-ARW model will be beneficial to the intensity forecast. However, the substantially smaller percentages of intensity improvement than those of the track error improvement indicate that ambient environment tends to play a less important role in determining the TC intensity as compared to other factors related to the vortex initialization or physics representations in the WRF-ARW model.     

基于越南遥感时间序列数据的湄公河三角洲土地利用及河岸变化检测研究

通过采用先进的遥感技术,基于光学和雷达时间序列卫星影像（陆地卫星,SPOT和雷达卫星）,本文对金瓯半岛（位于湄公河三角洲南部）土地覆被变化及湄公河河岸侵蚀情况进行了检测研究。鉴于金瓯半岛典型的土地覆被类型为红树林,通过对1973-2008年红树林遥感影像分析发现,近年来红树林林地面积急剧下降,超过一半的红树林已经转变为虾养殖场。与此同时,检测发现湄公河河岸已经被严重侵蚀,且侵蚀趋势正加速恶化。具体而言,田河和口河的左右两岸被认为是遭受严重侵蚀的热点区域。本文以1966-1968年地形图作为基准线数据,与1989-2009年卫星影像数据进行比照分析,此外采用数字海岸线分析系统（DSAS）模型对未来变化趋势进行了预测。     

水电项目对越南硒圣河地区社会经济发展及环境保护的影响

硒圣河是湄公河的主要分支之一,其集水区地形条件和水资源量均对水电开发十分有利。此外,无论从物种多样性还是生物量来看,硒圣河水生生物资源非常丰富。鱼类是当地人们的重要食物来源,粗略估计鱼类物种数量可能在200-300种之间,目前具有详细记录的鱼类大约为120种。截至目前,从越南境内硒圣河上游至越-柬边界总共开发了6个水电项目,兴建了一座4A级硒圣调蓄水库。流经柬埔寨的硒圣河部分,依据发展规划将兴建3座水电站,即硒圣5号电站（硒圣1号电站以下）、硒圣3号电站、硒圣2号电站。硒圣河水电项目对区域（越南和柬埔寨）社会经济的影响体现在：为地处偏远和困难的集水区创造了新的能源资源,改善了交通系统和农村地区的生活条件。与此同时,这些水电项目也对该区域自然环境产生了重大影响。例如,改变了下游流动机理变化,导致下游河道淤积,对沿河生态系统也产生了一定影响。     

Detection of DCO+ in a circumstellar disk

We report the first detection of DCO⁺ in a circumstellar disk. The DCO⁺ J=5–4 line at 360.169 GHz is observed with the 15 m James Clerk Maxwell Telescope in the disk around the pre-main sequence star TW Hya. Together with measurements of the HCO⁺ and H¹³CO⁺ J=4–3 lines, this allows an accurate determination of the DCO⁺/HCO⁺ ratio in this disk. The inferred value of0.035±0.005 is close to that found in cold pre-stellar cores and is somewhat higher than that measured in the envelope around the low-mass proto star IRAS 16293-2422. It is also close to the DCN/HCN ratio obtained for pristine cometary material in the jet of comet Hale-Bopp. The observed DCO⁺/HCO⁺ ratio for TW Hya is consistent with theoretical models of disks which consider gas-phase fractionation processes within a realistic 2-D temperature distribution and which include the effects of freeze-out onto grains. This revised version was published online in July 2006 with corrections to the Cover Date.