Describing alpine lake influence on stream network temperatures: A statistical modelling approach     

Samuel P. Carlson  Geoffrey C. Poole 《水文研究》2021,35(3):e14072

Systematic variations in atmospheric heat exchange, surface residence time, and groundwater influx across montane stream networks commonly produce an increasing stream temperature trend with decreasing elevation. However, complex stream temperature profiles that differ from this common longitudinal trend also exist, suggesting that stream temperatures may be influenced by complex interactions among hydrologic and atmospheric processes. Lakes within stream networks form one potential source of temperature profile complexity due to the spatially variable contribution of lake-sourced water to stream flow. We investigated temperature profile complexity in a multi-season stream temperature dataset collected across a montane stream network containing many alpine lakes. This investigation was performed by making comparisons between multiple statistical models that used different combinations of stream and lake characteristics to represent specific hypotheses for the controls on stream temperature. The compared models included a set of models which used a topographically derived estimate of the hydrologic influence of lakes to separate and quantify the effects of stream elevation and lake source-water contributions to longitudinal stream temperature patterns. This source-water mixing model provided a parsimonious explanation for complex stream-network temperature patterns in the summer and autumn, and this approach may be further applicable to other systems where stream temperatures are influenced by multiple water sources. Simpler models that discounted lake effects were more optimal during the winter and spring, suggesting that complex patterns in stream temperature profiles may emerge and subside temporally, across seasons, in response to diversity of water temperatures from different sources.  相似文献   

Evaluation of riverbed magnetic susceptibility for mapping biogeochemical hot spots in groundwater-impacted rivers     

Chen Wang  Martin A. Briggs  Frederick D. Day-Lewis  Lee D. Slater 《水文研究》2021,35(5):e14184

Redox hot spots occurring as metal-rich anoxic groundwater discharges through oxic wetland and river sediments commonly result in the formation of iron (Fe) oxide precipitates. These redox-sensitive precipitates influence the release of nutrients and metals to surface water and can act as ‘contaminant sponges’ by absorbing toxic compounds. We explore the feasibility of a non-invasive, high-resolution magnetic susceptibility (MS) technique to efficiently map the spatial variations of magnetic Fe oxide precipitates in the shallow bed of three rivers impacted by anoxic groundwater discharge. Laboratory analyses on Mashpee River (MA, USA) sediments demonstrate the sensitivity of MS to sediment Fe concentrations. Field surveys in the Mashpee and Quashnet rivers (MA, USA) reveal several discrete high MS zones, which are associated with likely anoxic groundwater discharge as evaluated by riverbed temperature, vertical head gradient, and groundwater chemistry measurements. In the East River (CO, USA), widespread cobbles/rocks exhibit high background MS from geological ferrimagnetic minerals, thereby obscuring the relatively small enhancement of MS from groundwater induced Fe oxide precipitates. Our study suggests that, in settings with low geological sources of magnetic minerals such as lowland rivers and wetlands, MS may serve as a complementary tool to temperature methods for efficiently mapping Fe oxide accumulation zones due to anoxic groundwater discharges that may function as biogeochemical hot spots and water quality control points in gaining systems.  相似文献   

The information system of the French Peatland Observation Service: Service National d'Observation Tourbières – A valuable tool to assess the impact of global changes on the hydrology and biogeochemistry of temperate peatlands through long term monitoring     

Sébastien Gogo  Jean-Baptiste Paroissien  Fatima Laggoun-Défarge  Jean-Marc Antoine  Léonard Bernard-Jannin  Guillaume Bertrand  Philippe Binet  Stéphane Binet  Guillaume Bouger  Yohann Brossard  Thierry Camboulive  Jean-Pierre Caudal  Stéphane Chevrier  Geneviève Chiapiuso  Benoît D'Angelo  Pilar Durantez  Chris Flechard  André-Jean Francez  Didier Galop  Laure Gandois  Daniel Gilbert  Christophe Guimbaud  Louis Hinault  Adrien Jacotot  Franck Le Moing  Emilie Lerigoleur  Gaël Le Roux  Fabien Leroy  Alexandre Lhosmot  Qian Li  Elodie Machado Da Silva  Jean-Sébastien Moquet  Juanita Mora-Gomez  Laurent Perdereau  Thomas Rosset  Marie-Laure Toussaint 《水文研究》2021,35(6):e14244

Mitigating and adapting to global changes requires a better understanding of the response of the Biosphere to these environmental variations. Human disturbances and their effects act in the long term (decades to centuries) and consequently, a similar time frame is needed to fully understand the hydrological and biogeochemical functioning of a natural system. To this end, the ‘Centre National de la Recherche Scientifique’ (CNRS) promotes and certifies long-term monitoring tools called national observation services or ‘Service National d'Observation’ (SNO) in a large range of hydrological and biogeochemical systems (e.g., cryosphere, catchments, aquifers). The SNO investigating peatlands, the SNO ‘Tourbières’, was certified in 2011 ( https://www.sno-tourbieres.cnrs.fr/ ). Peatlands are mostly found in the high latitudes of the northern hemisphere and French peatlands are located in the southern part of this area. Thus, they are located in environmental conditions that will occur in northern peatlands in coming decades or centuries and can be considered as sentinels. The SNO Tourbières is composed of four peatlands: La Guette (lowland central France), Landemarais (lowland oceanic western France), Frasne (upland continental eastern France) and Bernadouze (upland southern France). Thirty target variables are monitored to study the hydrological and biogeochemical functioning of the sites. They are grouped into four datasets: hydrology, fluvial export of organic matter, greenhouse gas fluxes and meteorology/soil physics. The data from all sites follow a common processing chain from the sensors to the public repository. The raw data are stored on an FTP server. After operator or automatic processing, data are stored in a database, from which a web application extracts the data to make them available ( https://data-snot.cnrs.fr/data-access/ ). Each year at least, an archive of each dataset is stored in Zenodo, with a digital object identifier (DOI) attribution ( https://zenodo.org/communities/sno_tourbieres_data/ ).  相似文献   

The Bear Brook Watershed in Maine: Multi-decadal whole-watershed experimental acidification     

Kaizad F. Patel  Ivan J. Fernandez  Sarah J. Nelson  Stephen A. Norton  Cheryl J. Spencer 《水文研究》2021,35(5):e14147

The Bear Brook Watershed in Maine (BBWM) is a long-term research site established to study the response of forest ecosystem function to environmental disturbances of chronic acidic deposition and ecosystem nitrogen enrichment. Starting in 1989, the West Bear (treated) watershed received bimonthly applications of ammonium sulfate [(NH₄)₂SO₄] fertilizer from above the canopy, whereas East Bear (reference) received ambient deposition. The treatments were stopped in 2016, marking the beginning of the recovery phase. Research at the site has focused on soils, streams, and vegetation. Here, we describe data collected over three decades at the BBWM—input and stream output nutrient fluxes, quantitative soil pits and soil chemistry, and soil temperature and moisture.  相似文献   

基于随机森林模型的农业电子商务浅析——洛川苹果网络销售问题与对策     

张晓涵  马敏飞  杨联安 《地下水》2020,(1):119-122

随着互联网产业的飞速发展,电子商务开始进入农业领域。以电子商务起步较早的"洛川苹果"作为研究对象进行调研。基于随机森林模型的决策树集成算法,对农业网络销售体系整体进行数据分析,模型构建,从问题表象出发挖掘其在不同部分的影响因子,最终基于影响因素解决问题,提出合理化建议:加强农村基础设施建设、健全农村公共服务体系以及完善农村电子商务培训制度等,因地制宜,推进农业电子商务的健康发展。  相似文献   

基于小波变换与神经网络的石羊河流域夏季地温预测模型研究   总被引：1，自引：1，他引：0  

贾东于  李开明  聂晓英  袁春霞  李清峰  高福元 《冰川冻土》2020,42(2):412-422

地温变化在气候反馈效应中起着重要作用， 理解地温及其与影响因素之间的时空关系对预测全球温度变化至关重要。利用1998 - 2017年石羊河流域的逐日常规气象观测资料， 采用小波分析结合BP（Back Propagation）神经网络构建了石羊河流域夏季地温预报模型， 结果表明： 日平均地温预测效果在不同站点均为最佳， 其中预测值和观测值的相关系数均大于0.87， 3 ℃以内的预测概率均大于84%。其中， 民勤地区地温预测效果最好， 预测值和观测值的相关系数达到0.91， 3 ℃以内的预测概率达到86%。日最高地温的预测值与观测值的相关系数高于0.8， 但误差平方和、 标准差较大。永昌地区日最高地温的模拟效果最好， 3 ℃以内的预测概率达到83%。日最低地温的预测与观测值的平均相关系数高于0.66， 3 ℃以内的预报概率高于83%， 但预测值略低。其中， 武威地区日最低地温的预测效果最好， 预测值与观测值的相关系数为0.72， 3 ℃以内的预测概率达到94%。研究成果可为有效弥补干旱、 半干旱区地温观测资料缺失和探讨其与局地气候的关系提供一些参考。  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   

基于主成分分析法和监测数据的阿尔泰山采金废弃矿区人工恢复措施效益分析          下载免费PDF全文

艾沙江·艾力  徐海量  苑塏烨 《干旱区地理》2019,42(2):288-294

本文以阿尔泰山两河源保护区采金废弃矿区为研究区，从地形、土壤、水分和地表植被4个方面出发，结合矿区现有条件，设置11种恢复措施，选取丰富度指数、优势度指数、多样性指数、均匀度指数、生物量、植被盖度、物种数及土石比等7个评价指标，采用主成分分析法，得出不同恢复措施的主成分得分及生态效益排名。结果表明，单一恢复措施，如推平、羊群驻扎、泥浆等基本上是从某一个方面来考虑生态恢复的，存在一定的缺陷，恢复效益排名比较靠后；多种措施相结合，不仅能改善土壤环境，也会引起植物群落多样性格局的变化，生态恢复效益很好；同一种恢复措施，施行年限越长恢复效果越好。  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