Seasonal connections between meteoric water and streamflow generation along a mountain headwater stream     

Sam J. Leuthold  Stephanie A. Ewing  Robert A. Payn  Florence R. Miller  Stephan G. Custer 《水文研究》2021,35(2):e14029

In snowmelt-driven mountain watersheds, the hydrologic connectivity between meteoric waters and stream flow generation varies strongly with the season, reflecting variable connection to soil and groundwater storage within the watershed. This variable connectivity regulates how streamflow generation mechanisms transform the seasonal and elevational variation in oxygen and hydrogen isotopic composition (δ¹⁸O and δD) of meteoric precipitation. Thus, water isotopes in stream flow can signal immediate connectivity or more prolonged mixing, especially in high-relief mountainous catchments. We characterized δ¹⁸O and δD values in stream water along an elevational gradient in a mountain headwater catchment in southwestern Montana. Stream water isotopic compositions related most strongly to elevation between February and March, exhibiting higher δ¹⁸O and δD values with decreasing elevation. These elevational isotopic lapse rates likely reflect increased connection between stream flow and proximal snow-derived water sources heavily subject to elevational isotopic effects. These patterns disappeared during summer sampling, when consistently lower δ¹⁸O and δD values of stream water reflected contributions from snowmelt or colder rainfall, despite much higher δ¹⁸O and δD values expected in warmer seasonal rainfall. The consistently low isotopic values and absence of a trend with elevation during summer suggest lower connectivity between summer precipitation and stream flow generation as a consequence of drier soils and greater transpiration. As further evidence of intermittent seasonal connectivity between the stream and adjacent groundwaters, we observed a late-winter flush of nitrate into the stream at higher elevations, consistent with increased connection to accumulating mineralized nitrogen in riparian wetlands. This pattern was distinct from mid-summer patterns of nitrate loading at lower elevations that suggested heightened human recreational activity along the stream corridor. These observations provide insights linking stream flow generation and seasonal water storage in high elevation mountainous watersheds. Greater understanding of the connections between surface water, soil water and groundwater in these environments will help predict how the quality and quantity of mountain runoff will respond to changing climate and allow better informed water management decisions.  相似文献   

First Multi‐Isotopic (Pb‐Nd‐Sr‐Zn‐Cu‐Fe) Characterisation of Dust Reference Materials (ATD and BCR‐723): A Multi‐Column Chromatographic Method Optimised to Trace Mineral and Anthropogenic Dust Sources     

Aubry Vanderstraeten  Steeve Bonneville  Stefania Gili  Jeroen de Jong  Wendy Debouge  Philippe Claeys  Nadine Mattielli 《Geostandards and Geoanalytical Research》2020,44(2):307-329

Atmospheric dust is an integral component of the Earth system with major implications for the climate, biosphere and public health. In this context, identifying and quantifying the provenance and the processes generating the various types of dust found in the atmosphere is paramount. Isotopic signatures of Pb, Nd, Sr, Zn, Cu and Fe are commonly used as sensitive geochemical tracers. However, their combined use is limited by the lack of (a) a dedicated chromatographic protocol to separate the six elements of interest for low‐mass samples and (b) specific reference materials for dust. Indeed, our work shows that USGS rock reference materials BHVO‐2, AGV‐2 and G‐2 are not applicable as substitute reference materials for dust. We characterised the isotopic signatures of these six elements in dust reference materials ATD and BCR‐723, representatives of natural and urban environments, respectively. To achieve this, we developed a specific procedure for dust, applicable in the 4–25 mg mass range, to separate the six elements using a multi‐column ion‐exchange chromatographic method and MC‐ICP‐MS measurements.  相似文献   

地缘政治视角下中亚“颜色革命”易发程度分析     

李希雅  王礼茂 《世界地理研究》2019,28(6):42-49

基于地缘政治视角，分析本世纪初发生在原苏联地区“颜色革命”的诱发因素，认为美国根据其地缘战略格局对“颜色革命”发生地存在一定程度的主观选择性，国家内部经济、政治、社会等层面的矛盾也同样作为发生背景。在中亚地缘格局动态分析的基础上，结合中亚五国形势，从时间和空间双重维度对中亚地区未来发生“颜色革命”的可能性进行识别与评判，得出1) 整体来看，中亚近期内爆发“颜色革命”可能性较小，但从长远来看不能掉以轻心。2)土、乌未来稳定可期，塔、吉、哈需谨防“颜色革命”卷土重来。  相似文献   

基于超像元词包特征和主动学习的高分遥感影像变化检测     

杨进一  徐伟铭  王成军  翁谦 《地球信息科学学报》2019,21(10):1594-1607

为解决高分辨率遥感影像变化检测中存在底层特征缺乏语义信息、像元级的检测结果存在“椒盐”现象以及监督分类中样本标注自动化程度较低,本文提出一种基于超像元词包特征和主动学习的变化检测方法。首先采用熵率分割算法获取叠加影像的超像元对象;其次提取两期影像像元点对间的邻近相关影像特征（相关度、斜率和截距）和顾及邻域的纹理变化强度特征（均值、方差、同质性和相异性）,经线性组合作为像元点对的底层特征;然后基于像元点对底层特征利用BOW模型构建超像元词包特征,并采用一种改进标注策略的主动学习方法从无标记样本池中优选信息量较大的样本,且自动标注样本类别;最后训练分类器模型完成变化检测。通过选用2组不同地区的GF-2影像和Worldview-Ⅱ影像作为数据源进行实验,实验结果中2组数据集的F1分数分别为0.8714、0.8554,正确率分别为0.9148、0.9022,漏检率分别为0.1681、0.1868,误检率分别为0.0852、0.0978。结果表明,该法能有效识别变化区域、提高变化检测精度。此外,传统主动学习方法与改进标注策略的主动学习方法的学习曲线对比显示,改进的标注策略可在较低精度损失下,有效提高样本标注自动化程度。  相似文献   

利用InSAR资料反演宁洱Ms6.4地震震源参数及库仑应力变化     

陈晨月  冯光财  高华  杨怀宁 《大地测量与地球动力学》2019,39(3):295-301

首先利用ALOS PALSAR数据，通过D-InSAR技术获取2007-06-03云南宁洱MS6.4地震的同震形变场，然后基于Okada弹性半空间位错模型反演该地震的断层几何以及精细滑动分布，最后计算宁洱地震后周边断层的静态库仑应力变化。结果表明，形变主要集中在西盘，最大视线向形变量为51.6 cm；反演得到的震源位置为23.05°N、101.02°E，深度3 km，断层走向145°，倾向49.5°，平均滑动角153°，发震断层为NNW向普洱断裂，断层活动以右旋走滑为主，兼具逆冲分量；断层面最大滑动量为1.2 m，反演得到的震级为MW619。基于库仑应力场发现，磨黑断裂处于库仑应力增加区域，而2014年景谷地震位于负值区域。结合实地考察资料和反演结果表明，宁洱地震为浅源地震，但断层并未出露地表。  相似文献   

基于GPS和水准数据的微粒群算法联合反演祁连山北缘断裂三维滑动速率     

刘杰 《大地测量与地球动力学》2019,39(9):906-909

将微粒群算法与位错理论模型相结合，采用中国地壳运动观测网络提供的青藏高原地区2001~2004年GPS测量数据和2000~2006年水准测量数据，通过常规定权和附有相对权比的方法对祁连山北缘断裂的三维滑动速率进行联合反演，并与蚁群算法反演结果进行对比。结果表明，微粒群算法收敛速度快、稳定性高，结合经典位错理论模型，是一种可以有效求解断层三维滑动速率反演问题的优化算法，在大地测量反演领域极具应用潜力。  相似文献   

烃源岩不同性质有机酸的分离及其检测方法     

杜佳宗  何蓓  蔡进功  雷天柱  刘庆  谢忠怀 《高校地质学报》2020,26(5):540-548

烃源岩中的有机酸来源于有机质，但有机质具有不同的赋存形式，有机酸具有不同性质，这将影响有机酸与不同赋存有机质的关系，进而影响分离和检测方法。文章在总结前人对有机质赋存形式和有机酸性质等特征的基础上，提出烃源岩中的有机酸并以非单一的形式存在，具有水溶性、脂溶性和难溶性有机酸三种类型，游离有机质中存在水溶性和脂溶性有机酸，而结合有机质中存在水溶性、脂溶性和难溶性有机酸。因此在检测方法上需采取分步分离的方法，且根据有机酸的性质选取合适的检测方法，即水溶性有机酸利用离子色谱检测，索氏抽提得到的脂溶性有机酸利用气相色谱—质谱检测，通过酸解抽提残渣得到的难溶性有机酸利用红外光谱检测，全面系统地认识烃源岩中有机酸含量和类型等特征。这对进一步探讨烃源岩各种类型有机酸特征和演化规律，深化烃源岩有机质生烃以及有机—无机相互作用等机理都具有重要意义。  相似文献   

An Automatic Method for Detecting Transients and Variable Sources in AST3 Survey Based on Image Subtraction and Random Forest     

《Chinese Astronomy and Astrophysics》2020,44(1):41-60

AST3-2 (the second Antarctic Survey Telescope) is located in Antarctic Dome A, the loftiest ice dome on the Antarctic Plateau. It produces a huge amount of observational data which require a more efficient data reduction program to be developed. Also the data transmission in Antarctica is much difficult, thus it is necessary to perform data reduction and detect variable and transient sources remotely and automatically in Antarctica, but this attempt is restricted by the unsatisfactory performance of the low power consumption computer in Antarctica. For realizing this purpose, to develop a new method based on the existing image subtraction method and random forest algorithm, taking the AST3-2 2016 dataset as the test sample, becomes an alternative choice. This method performs image subtraction on the dataset, then applies the principle component analysis to extract the features of residual images. Random forest is used as a machine learning classifier, and in the test a recall rate of 97% is resulted for the positive sample. Our work has verified the feasibility and accuracy of this method, and finally found out a batch of candidates for variable stars in the AST3-2 2016 dataset.  相似文献   

Gully erosion spatial modelling: Role of machine learning algorithms in selection of the best controlling factors and modelling process     

《地学前缘(英文版)》2020,11(6):2207-2219

This investigation assessed the efficacy of 10 widely used machine learning algorithms (MLA) comprising the least absolute shrinkage and selection operator (LASSO), generalized linear model (GLM), stepwise generalized linear model (SGLM), elastic net (ENET), partial least square (PLS), ridge regression, support vector machine (SVM), classification and regression trees (CART), bagged CART, and random forest (RF) for gully erosion susceptibility mapping (GESM) in Iran. The location of 462 previously existing gully erosion sites were mapped through widespread field investigations, of which 70% (323) and 30% (139) of observations were arbitrarily divided for algorithm calibration and validation. Twelve controlling factors for gully erosion, namely, soil texture, annual mean rainfall, digital elevation model (DEM), drainage density, slope, lithology, topographic wetness index (TWI), distance from rivers, aspect, distance from roads, plan curvature, and profile curvature were ranked in terms of their importance using each MLA. The MLA were compared using a training dataset for gully erosion and statistical measures such as RMSE (root mean square error), MAE (mean absolute error), and R-squared. Based on the comparisons among MLA, the RF algorithm exhibited the minimum RMSE and MAE and the maximum value of R-squared, and was therefore selected as the best model. The variable importance evaluation using the RF model revealed that distance from rivers had the highest significance in influencing the occurrence of gully erosion whereas plan curvature had the least importance. According to the GESM generated using RF, most of the study area is predicted to have a low (53.72%) or moderate (29.65%) susceptibility to gully erosion, whereas only a small area is identified to have a high (12.56%) or very high (4.07%) susceptibility. The outcome generated by RF model is validated using the ROC (Receiver Operating Characteristics) curve approach, which returned an area under the curve (AUC) of 0.985, proving the excellent forecasting ability of the model. The GESM prepared using the RF algorithm can aid decision-makers in targeting remedial actions for minimizing the damage caused by gully erosion.  相似文献   

BDS卫星差分码偏差稳定性分析及其短期预报     

梅登奎  闻德保 《大地测量与地球动力学》2020,40(7):746-750

利用MGEX(multi-GNSS experiment)发布的BDS卫星差分码偏差(differential code bias, DCB)产品，比较分析不同太阳活动水平下BDS卫星DCB产品的稳定性变化特性，并采用差分自回归移动平均(auto-regressive integrated moving average, ARIMA)时间序列预测模型，实现不同太阳活动水平下BDS卫星DCB的短期预报。结果表明，在太阳活动高年，BDS卫星DCB日解值稳定度、月稳定性均明显低于太阳活动低年，且不同卫星星座类型的BDS卫星DCB稳定性也存在差异；ARIMA时间序列预报结果与MGEX发布值符合程度较好，优于多项式拟合法预测结果。  相似文献