Characterizing rainfall–groundwater dynamics in a hard‐rock aquifer system using time series,geographic information system and geostatistical modelling          下载免费PDF全文

Deepesh Machiwal  Madan K. Jha 《水文研究》2014,28(5):2824-2843

The aim of this study was to investigate rainfall–groundwater dynamics over space and annual time scales in a hard‐rock aquifer system of India by employing time series, geographic information system and geostatistical modelling techniques. Trends in 43‐year (1965–2007) annual rainfall time series of ten rainfall stations and 16‐year (1991–2006) pre‐monsoon and post‐monsoon groundwater levels of 140 sites were identified by using Mann–Kendall, Spearman rank order correlation and Kendall rank correlation tests. Trends were quantified by Kendall slope method. Furthermore, the study involves novelty of examining homogeneity of pre‐monsoon and post‐monsoon groundwater levels, for the first time, by applying seven tests. Regression analysis between rainfall and post‐monsoon groundwater levels was performed. The pre‐monsoon and post‐monsoon groundwater levels for four periods – 1991–1994, 1995–1998, 1999–2002 and 2003–2006 – were subjected to geographic information system‐based geostatistical modelling. The rainfall showed considerable spatiotemporal variations, with a declining trend at the Mavli rainfall station (p‐value < 0.05). The Levene's tests revealed spatial homogeneity of rainfall at α = 0.05. Regression analyses indicated significant relationships (r² > 0.5) between groundwater level and rainfall for eight rainfall stations. Non‐homogeneity and declining trends in the groundwater level, attributed to anthropogenic and hydrologic factors, were found at 5–61 more sites in pre‐monsoon compared with post‐monsoon season. The groundwater declining rates in phyllite–schist, gneiss, schist and granite formations were found to be 0.18, 0.26, 0.21 and 0.14 m year^?1 and 0.13, 0.19, 0.16 and 0.02 m year^?1 during the pre‐monsoon and post‐monsoon seasons, respectively. The geostatistical analyses for four time periods revealed linkages between the rainfall and groundwater levels. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

兼顾志愿者地理信息的国家应急测绘公众服务平台设计     

杨靓  黄蔚  查祝华  张红平 《测绘通报》2019,(9):147-151

随着互联网技术的进步和新一代网络信息传播模式的深入发展，志愿者地理信息的研究和应用日益广泛，但由于其规范性和均一性方面的缺陷，在应急公共服务领域，志愿者信息的有效利用依旧是亟需突破的难题。本文将重点介绍国家应急测绘公众服务平台设计思路和总体架构，并结合志愿者地理信息特点，探讨该类信息在国家应急测绘公众服务平台建设中的处理流程和应用模式，力求在应急信息资源共享和服务平台共建方面进行新的尝试，为我国突发事件应急体系建设提供有益实践。  相似文献   

基于水化学特征的“奥灰”地热流体水文地球化学演化机制研究——以济南东部章宁1地热井为例          下载免费PDF全文

程洪柱  成世才  王振涛 《山东国土资源》2019,35(8)

以章宁1地热井的研究为例,在分析地热水水文地球化学特征基础上,对地热水的化学成分形成进行了研究,并通过与相对补给径流区的西曹范、章桃1地下水水化学特征的比较,研究其演化机理。综合分析认为地热水为沉积岩溶滤水,属于中度变质水,地下水流经火成岩侵入体时溶解了大量的Cl~-及F~-,HSiO~-_3等微量元素,次为地下水与沿文祖断裂上升的深部热液的混合,导致地热水化学类型的改变。深部热液的水化学成分与济南东地热水与深部热液的混合比例有待进一步研究。  相似文献   

尼泊尔地震的NOAA卫星数据震前异常分析     

林岭  孔祥增  李南  熊攀 《地球信息科学学报》2018,20(8):1169-1177

发生地震时常伴随有地热辐射增强现象,这些异常信息隐藏于遥感卫星NOAA所捕获的地球射出长波辐射（OLR）数据中,目前多数研究还停留在对源数据的解读,缺乏有效的信息处理技术,致使大部分的OLR数据没有得到充分利用。因此,本文提出一种基于鞅理论的概率统计方法来识别异常特征算法,从有噪声的非结构化的源数据中提取出震前OLR数据异常变化特征序列,从时间序列和地域范围进行震前异常分析。本算法实验是以尼泊尔的在2014年9月至2015年7月期间（包括2015年4月25日Ms7.8大地震）发生的3次地震的OLR数据为例,实验结果显示震中区域的OLR数据在震前的2~3个月开始有显著的异常数据变化,通过分析发现数据显示数据异常在震前出现的时间长短与地震的大小相关,异常的发生区域与震区周围的地貌特征相关。这说明基于鞅理论的算法所提取的OLR数据异常点序列的确与地震发生的时间地点是有关系的。  相似文献   

内蒙古鲁新井田水文地质条件研究          下载免费PDF全文

赵志强  安美艳  高奎锋  王兆亮  王福芝 《山东国土资源》2018,34(6)

矿产资源开发导致了地下水失衡,地下水失衡又给矿产开发造成了极大的安全隐患,近年来,矿产资源开发与地下水环境保护之间的矛盾愈发凸显。通过对内蒙古鲁新井田典型的水文地质条件进行分析研究,分析采矿导致地下水失衡机理,深入剖析矿井开采充水条件及矿山开发对地下水环境的影响,合理提出了促进矿产开发与地下水保护相互协调的对策建议,为实现"采矿保水"协调统一提供了基础地质依据。为类似地区矿产开发过程中遵循自然规律,趋利避害,保障生产安全,保护地下水环境安全,实现资源绿色开发有较好的指导借鉴作用。  相似文献   

Developing constitutive models from EPR‐based self‐learning finite element analysis          下载免费PDF全文

Ali Nassr  Akbar Javadi  Asaad Faramarzi 《国际地质力学数值与分析法杂志》2018,42(3):401-417

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.  相似文献   

Socio-hydrological framework for investigating farmers’ activities affecting the shrinkage of Urmia Lake; hybrid data mining and agent-based modelling     

Parsa Pouladi  Amir Molajou  Mohammad Hadi Afshar 《水文科学杂志》2020,65(8):1249-1261

ABSTRACT

Developing a general framework to capture the complexities associated with the non-linear and adaptive nature of farmers facing water resources scarcity is a challenging problem. This paper integrates agent-based modelling (ABM) and a data mining method to develop a hybrid socio-hydrological framework to provide future insights for policy-makers. The data associated with the farmers’ main characteristics were collected through field surveys and interviews. Afterwards, the association rule was employed to discover the main patterns representing the farmers’ agricultural decisions. The discovered patterns were then used as the behavioural rules in ABM to simulate the agricultural activities. The proposed framework has been was applied to explore the interactions between agricultural activities and the main river feeding the Urmia-Lake, Iran. The outcomes indicate that farmers’ acquisitive traits and belongings have significant impacts on their socio-hydrological interactions. The reported values of the efficiency criteria may support the satisfactory performance of the proposed framework.  相似文献   

Detection of coffee berry necrosis by digital image processing of landsat 8 oli satellite imagery     

《International Journal of Applied Earth Observation and Geoinformation》2020

Coffee berry necrosis is a fungal disease that, at a high level, significantly affects coffee productivity. With the advent of surface mapping satellites, it was possible to obtain information about the spectral signature of the crop on a time scale pertinent to the monitoring and detection of plant phenological changes. The objective of this paper was to define the best machine learning algorithm that is able to classify the incidence CBN as a function of Landsat 8 OLI images in different atmospheric correction methods. Landsat 8 OLI images were acquired at the dates closest to sampling anthracnose field data at three times corresponding to grain filling period and were submitted to atmospheric corrections by DOS, ATCOR, and 6SV methods. The images classified by the algorithms of machine learning, Random Forest, Multilayer Perceptron and Naive Bayes were tested 30 times in random sampling. Given the overall accuracy of each test, the algorithms were evaluated using the Friedman and Nemenyi tests to identify the statistical difference in the treatments. The obtained results indicated that the overall accuracy and the balanced accuracy index were on an average around 0.55 and 0.45, respectively, for the Naive Bayes and Multilayer Perceptron algorithms in the ATCOR atmospheric correction. According to the Friedman and Nemenyi tests, both algorithms were defined as the best classifiers. These results demonstrate that Landsat 8 OLI images were able to identify an incidence of the coffee berry necrosis by means of machine learning techniques, a fact that cannot be observed by the Pearson correlation.  相似文献   

湖南仁里超大型钽铌矿床工作进展及找矿思路     

杨世珍  周芳春  李建斌  刘翔  李建康  黄志飚  苏俊男  李鹏 《中国地质调查》2020,7(4):28-36

湖南仁里超大型钽铌矿床钽铌铍矿资源丰富,Ta₂O₅资源量达到了超大型规模,BeO资源量达到了大型规模。为进一步研究湖南仁里超大型钽铌矿床稀有金属的赋存特征、成矿规律及矿产资源综合利用前景,开展了地球化学分析、电子探针、包裹体、同位素测年及可选性试验等研究工作,通过系统梳理仁里超大型钽铌矿床的工作进展,进一步探讨了该矿床的下一步找矿思路。仁里钽铌矿床共(伴)生矿种多,稀有金属综合回收率及矿产资源采选综合利用率高,具有极大的开发利用价值,可作为绿色、环保、无尾矿范例进行高效勘查与开发。仁里矿区钽铌铍矿资源丰富,具有较好的找矿潜力,加大地质勘查资金投入有望取得钽铌铍锂等稀有金属找矿新进展。下一步应对矿区2、3、5、6号主矿脉深部矿体进行控制,力争取得钽铌铍矿找矿突破,同时加强对矿区西部或西南部隐伏锂辉石白云母钠长石伟晶岩的研究工作,力争取得锂辉石白云母钠长石伟晶岩型锂矿找矿突破。  相似文献   

移动轨迹聚类方法研究综述   总被引：6，自引：2，他引：4  

牟乃夏  徐玉静  张恒才  陈洁  张灵先  刘希亮 《测绘通报》2018,(1):1-7

轨迹数据是人类移动行为的表征,能够映射出人的出行模式和社会属性等信息。怎样有效挖掘轨迹数据蕴藏的人类活动规律一直是研究的热点。通过轨迹聚类发现行为相似的类簇,从而探究群体的移动模式是轨迹挖掘和深度应用常见的方法之一。本文首先根据轨迹数据的特点,将轨迹数据模型分为轨迹点模型和轨迹段模型,并据此定义相应的相似性度量：空间相似性度量和时空相似性度量;然后,对两类模型的聚类方法进行了综述,并总结不同聚类算法的优缺点,以期为不同应用选取聚类算法提供科学依据;最后对移动轨迹数据聚类方法研究的发展趋势进行了讨论。  相似文献