太湖生态环境演化及其原因分析

太湖地处长江下游三角洲,水域面积为2338km²,平均水深1.9m,最大水深不足2.6m,为一典型的大型浅水湖泊。太湖流域地势平坦,河网密布,河湖水力关系复杂。其主要补给径流来自西南部的天目山区及西部的宜溧河流域。每年夏天,大部分入湖洪水通过位于东太湖的太浦河及东北部的望虞河分别排入黄浦江与长江,由于出入湖河道的特殊位置,使得太湖南部的换水周期较短而北部较长。近几十年来,太湖由于污染而逐步呈现富营养化特征,污染物主要来自北部的无锡市和常州市,通过河道排入太湖北部的五里湖与梅梁湾,因此上述两地的水质较南部差。在东太湖,水产养殖对水环境的影响很大,亦呈现出富营养化特征,并殃及该地区的供水,加之该地区为太湖主要的泄洪通道,因此泥沙淤积严重,而且水生植物生长旺盛,呈现出明显的沼泽化趋势;在太湖四周地区,由于湖泊围垦和水利工程建设,其污染净化能力将降低,从而加速水环境恶化的趋势。太湖所面临这些问题,有待于强化湖泊科学管理来解决。     

不同采样率水位同震响应能力及其特征分析

分析同种仪器不同采样率水位资料同震响应记录情况,发现存在很大差异,不但形态上明显不同,响应能力及响应幅度上也差别很大.在此基础上认为,秒采样率数据能更好记录同震响应.指出,为了记录到真实完整可靠的同震响应,观测仪器应在采样率、数据存储容量、GPS授时、触发阈值、时值及分钟值取值方式等方面作改进.最后指出,同震响应分析可能是今后地震分析预报有所突破的一个研究方向.     

Predicting Diel,Diurnal and Nocturnal Dynamics of Dissolved Oxygen and Chlorophyll‐a Using Regression Models and Neural Networks

Human‐induced and natural interruptions with continuous streams of observational data necessitate the development of gap‐filling and prediction strategies towards better understanding, monitoring and management of aquatic systems. This study quantified the efficacy of multiple non‐linear regression (MNLR) versus artificial neural network (ANN) models as well as the temporal partitioning of diurnal versus nocturnal data for the predictions of chlorophyll‐a (chl‐a) and dissolved oxygen (DO) dynamics. The temporal partitioning increased the predictive performances of the best MNLR models of diurnal DO by 45% and nocturnal DO by 4%, relative to the best diel MNLR model of diel DO ($r_{{\rm adj}}^{2} = 68.8\%$ ). The ANN‐based predictions had a higher predictive power than the MNLR‐based predictions for both chl‐a and DO except for diurnal DO dynamics. The best ANNs based on independent validations were multilayer perceptron (MLP) for diel chl‐a, generalized feedforward (GFF) for diurnal and nocturnal chl‐a, MLP for diel DO, GFF for diurnal DO, and MLP for nocturnal DO.     

Application of a Bayesian model to infer the contribution of coalbed natural gas produced water to the Powder River,Wyoming and Montana

The Powder River Basin (PRB) of Wyoming and Montana contains significant coal and coal bed natural gas (CBNG) resources. CBNG extraction requires the production of large volumes of water, much of which is discharged into existing drainages. Compared to surface waters, the CBNG produced water is high in sodium relative to calcium and magnesium, elevating the sodium adsorption ratio (SAR). To mitigate the possible impact this produced water may have on the quality of surface water used for irrigation, the State of Montana passed water anti‐degradation legislation, which could affect CBNG production in Wyoming. In this study, we sought to determine the proportion of CBNG produced water discharged to tributaries that reaches the Powder River by implementing a four end‐member mixing model within a Bayesian statistical framework. The model accounts for the ⁸⁷Sr/⁸⁶Sr, δ¹³C_DIC, [Sr] and [DIC] of CBNG produced water and surface water interacting with the three primary lithologies exposed in the PRB. The model estimates the relative contribution of the end members to the river water, while incorporating uncertainty associated with measurement and process error. Model results confirm that both of the tributaries associated with high CBNG activity are mostly composed of CBNG produced water (70–100%). The model indicates that up to 50% of the Powder River is composed of CBNG produced water downstream from the CBNG tributaries, decreasing with distance by dilution from non‐CBNG impacted tributaries from the point sources to ~10–20% at the Montana border. This amount of CBNG produced water does not significantly affect the SAR or electrical conductivity of the Powder River in Montana. Copyright © 2013 John Wiley & Sons, Ltd.     

Exploration of remotely sensed forest structure and ultrasonic range sensor metrics to improve empirical snow models

Current methods to estimate snow accumulation and ablation at the plot and watershed levels can be improved as new technologies offer alternative approaches to more accurately monitor snow dynamics and their drivers. Here we conduct a meta‐analysis of snow and vegetation data collected in British Columbia to explore the relationships between a wide range of forest structure variables – obtained from Light Detection and Ranging (LiDAR), hemispherical photography (HP) and Landsat Thematic Mapper – and several indicators of snow accumulation and ablation estimated from manual snow surveys and ultrasonic range sensors. By merging and standardizing all the ground plot information available in the study area, we demonstrate how LiDAR‐derived forest cover above 0.5 m was the variable explaining the highest percentage of absolute peak snow water equivalent (SWE) (33%), while HP‐derived leaf area index and gap fraction (45° angle of view) were the best potential predictors of snow ablation rate (explaining 57% of variance). This study reveals how continuous SWE data from ultrasonic sensors are fundamental to obtain statistically significant relationships between snow indicators and structural metrics by increasing mean r² by 20% when compared to manual surveys. The relationships between vegetation and spectral indices from Landsat and snow indicators, not explored before, were almost as high as those shown by LiDAR or HP and thus point towards a new line of research with important practical implications. While the use of different data sources from two snow seasons prevented us from developing models with predictive capacity, a large sample size helped to identify outliers that weakened the relationships and suggest improvements for future research. A concise overview of the limitations of this and previous studies is provided along with propositions to consistently improve experimental designs to take advantage of remote sensing technologies, and better represent spatial and temporal variations of snow. Copyright © 2013 John Wiley & Sons, Ltd.     

水管倾斜仪的快速标定方法

根据以前维护水管倾斜仪的一些经验,总结了一套快速标定水管仪的方法,在牡丹江地震台取得了成功。     

双重介质含水层中井水位潮汐相位滞后现象的理论分析

简略地介绍了双重介质含水层模型;推导出引潮力作用下双重介质含水层中渗流运动的偏微分方程;将此泛定的方程与潜水的Boulton方程进行数学类比,从而得出一个新的迟后给水项,为解释固体潮致井水位振荡相位滞后现象奠定了物理基础;通过对该泛定方程的分析,还发现该迟后给水项与深部含水层中存在的一种潮汐液流振荡现象有关．     

海底热流长期观测系统研制进展

浅海和俯冲海沟等海域,不仅是矿产和油气资源主潜力区,也是构造地震频发区,其浅表热流和深部温度信息对于了解板块俯冲和岩浆活动等过程至关重要.这些区域浅层地温场和热流场受到底水温度波动（BTV）强烈扰动,其背景热流需由长期观测来获取.在全面分析了国内外海底热流长期观测技术特点后,我们提出了系缆式海底热流长期观测方案,2013年起陆续开展了部分核心技术的预研究及一系列海底、湖底及浅孔试验.结果表明：（1）自主研制的长周期低功耗微型测温单元,在2~36℃的环境下可连续观测1年;系缆式投放与回收方案即使在地形陡峭、1.5 kn流速及无动力定位等条件下仍然可行.（2）南海北部BTV总体随水深变浅而增强,在浅水区对浅层地温场扰动不可忽略.例如,在水深2600~3200 m和850~1200 m海域分别为0.025~0.053℃（17天内）、0.182~0.417℃（2天内）,而台西南盆地北坡（水深763 m）夏季的海底热流由浅表的0.69 W·m^-2转变为0.83 m以深的-0.25~-0.05 W·m^-2.（3）兴伊措和湖光岩玛珥湖BTV向深部传导过程中其幅度逐渐减弱、相位滞后,进而导致热流方向与强度随季节发生变化.而康定中谷浅层（7 m内）地温在不同深度处同步波动,且冬高（35~36℃）夏低（28~32℃）.推测为夏季大量降雨所致;其热流浅部低（0.504 W·m^-2）深部高（0.901 W·m^-2）,指示着鲜水河断裂带深部热流体上涌.这些预研究工作为后续系缆式海底热流长期观测系统的正式研制与应用奠定了扎实基础.

     

Investigation on the relation between the gravity anomaly，crustal deformation and underground water

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大同镇川堡井水位阶变与地震关系初析

统计了大同镇川堡井１９８８年６月～１９９１年１２月原始记录曲线的水位阶变资料，认为该井水位阶变可能反映了口泉断裂的蠕动，也反映了两次大同—阳高地震前应力应变作用的过程。