广西防城港地区地下水现场测试数据集

广西防城港是我国华南沿海酸性地下水发育的典型地区,2013-2015年在该地区开展了地下水调查,获取了一批地下水现场测试数据。广西防城港地下水现场测试数据集包含丰水期和枯水期现场测试数据2个Excel数据表格。每个Excel数据表格包含调查点位置、地下水埋深、地下水类型、地下水物理和化学特征等地下水现场测试数据。本数据集共采集水点323组,分析结果表明防城港地区地下水以pH为5.50~6.50的偏酸性地下水为主,此结果不仅能为防城港地下水资源评价和开发提供资料支撑,还可为华南沿海酸性地下水的研究提供典型范例。     

基于TIGGE资料的集合成员优选方法

利用2007年6月8日—8月31日东亚地区TIGGE集合预报资料中欧洲中期天气预报中心(European Centre for Medium-range Weather Forecasts,ECMWF)和英国气象局(United Kingdom M et Office,UKM O)两个中心的地面2 m气温资料进行集合成员优选研究。结果表明,对于24~96 h预报,集合成员优选方法能够较好地选出预报技巧较高和预报技巧较低的集合成员。个例分析表明,在极端天气出现的地区,优选集合平均的预报优势较为明显。对比ECMWF和UKMO的集合成员优选结果发现,ECMWF的预报效果优于UKMO的预报效果。     

神东煤炭基地1:50 000活鸡兔幅矿区水文地质图数据集

本数据集在1：50 000活鸡兔图幅内综合应用了遥感、地面调查、物探、钻探,以及水化学同位素等多种方法进行数据采集,共完成2期遥感数据解译800 km²,地面调查点377个,丰水期、枯水期地下水水位统测240点次,抽水试验10组,水体样品采集共计127组,水文地质钻探累计进尺600 m。本数据集细化了工作区内第四系孔隙含水层、白垩系洛河组孔隙-裂隙含水层富水等级,填补了侏罗系安定组、直罗组水文地质信息的空白;同时,加入了与采煤相关的次生环境地质要素,并首次将浅层含水层疏干区较为准确地勾画出来,还建立了采煤影响下的地下水的循环模式,突出了矿区水文地质调查的特色。本数据集为矿区水文地质调查工作的规划、部署与总结提供常态化支持,对保障国家能源安全、生态安全具有重要的现实意义。     

一种动态构建Delaunay三角网的算法

Delaunay三角剖分算法是构建数字高程模（DEM）的主要算法。在分析现有的Delaunay三角剖分的3种算法之后,指出现有算法存在的不足。并提出一种TIN的动态建模方法,利用分块技术来改进搜索方法,大大提高了Delaunay三角网的构建速度。实验结果表明,此算法和前面3种算法相比,效率有了很大提高。     

天然气水合物客体分子与同位素组成特征及其地球化学应用

对1999-2011年间发表的全球18个地区(包括海洋、内陆海与湖泊、陆域冻土区)244件天然气水合物样品的气体分子与同位素组成数据进行了归纳与总结,结果发现:C1是自然界中天然气水合物的最主要组成成分,C2-C6烷烃和CO2也是其常见的客体分子,C6+、H2S等较少存在于水合物分解气中。海洋、内陆海与湖泊、陆域冻土区天然气水合物的客体分子种类存在一定的差异,且碳氢同位素的组成范围也比较宽泛。根据气体分子与同位素组成数据可有效判识天然气水合物的气体来源与成因类型,甚至在研究水合物形成与分解控制因素、气体迁移与成藏过程等方面也具有重要的指示作用。     

基于神经网络的全球三维温盐场重构技术研究

文章利用果蝇优化广义回归神经网络算法FOAGRNN (fruit fly optimization algorithm, FOA; generalized regression neural network, GRNN)对SODA (simple ocean data assimilation)再分析数据进行训练, 构建海表温度、盐度、海面高度与次表层温盐场之间的投影关系模型, 并在全球范围使用SODA和卫星遥感数据评估了模型的应用性能。首先, 利用独立的2016年SODA海表数据作为模型输入进行理想重构试验, 结果显示全球重构温、盐平均均方根误差(MRMSE)分别为0.36℃和0.08‰, 与世界海洋图集WOA13资料相比减小约50%和60%。然后, 利用卫星观测的海表信息作为模型输入进行实际应用试验, 并与Argo观测剖面进行比较评估。试验结果表明, 重构模型能有效表征海水温、盐特征, 其中重构温、盐MRMSE分别为0.79℃和0.16‰, 相比WOA气候态减小27%和11%。误差的垂向分布显示, 重构温度RMSE从海表向下迅速增大, 至100m达到峰值1.35℃, 而后又迅速回落,至250m处为0.81℃, 跃层往下不断减小; 重构盐度RMSE基本随深度增大而减小, 误差峰值位于25m附近, 约为0.25‰。此外, Argo浮标跟踪分析和区域水团统计结果也表明模型能够较好地刻画海洋三维温盐场的内部结构特征。     

Leveraging ensemble meteorological forcing data to improve parameter estimation of hydrologic models

As continental to global scale high-resolution meteorological datasets continue to be developed, there are sufficient meteorological datasets available now for modellers to construct a historical forcing ensemble. The forcing ensemble can be a collection of multiple deterministic meteorological datasets or come from an ensemble meteorological dataset. In hydrological model calibration, the forcing ensemble can be used to represent forcing data uncertainty. This study examines the potential of using the forcing ensemble to identify more robust parameters through model calibration. Specifically, we compare an ensemble forcing-based calibration with two deterministic forcing-based calibrations and investigate their flow simulation and parameter estimation properties and the ability to resist poor-quality forcings. The comparison experiment is conducted with a six-parameter hydrological model for 30 synthetic studies and 20 real data studies to provide a better assessment of the average performance of the deterministic and ensemble forcing-based calibrations. Results show that the ensemble forcing-based calibration generates parameter estimates that are less biased and have higher frequency of covering the true parameter values than the deterministic forcing-based calibration does. Using a forcing ensemble in model calibration reduces the risk of inaccurate flow simulation caused by poor-quality meteorological inputs, and improves the reliability and overall simulation skill of ensemble simulation results. The poor-quality meteorological inputs can be effectively filtered out via our ensemble forcing-based calibration methodology and thus discarded in any post-calibration model applications. The proposed ensemble forcing-based calibration method can be considered as a more generalized framework to include parameter and forcing uncertainties in model calibration.     

CANOPEX: A Canadian hydrometeorological watershed database

Over the past few years, many international initiatives and collaborations were launched to improve and share knowledge in hydrology research. Large databases allowed finding patterns and relationships across regions and scales. This paper introduces the Canadian model parameter experiment (CANOPEX) database, which is adapted from the US MOPEX project data and methods. The CANOPEX database includes meteorological and hydrometric data as well as watershed boundaries for 698 basins. Two sets of basin‐averaged meteorological data (Maximum and minimum temperature and precipitation) are provided. The first dataset is directly taken from Environment Canada's weather stations whereas the second is extracted from the Natural Resources Canada gridded climate data product. Data are provided in MOPEX and Matlab formats. CANOPEX watersheds are well distributed over Canada, which allows investigating a variety of physiological and climatological conditions. The CANOPEX database can be used in a variety of hydrologic research projects such as climate change impact studies, model comparisons, multi‐modelling, ensemble streamflow prediction and model parameter estimation. CANOPEX could be used to generalize findings to other cold climate catchments as well as assess the robustness of research methodologies and procedures. Copyright © 2016 John Wiley & Sons, Ltd.     

Global land mapping of satellite-observed CO2 total columns using spatio-temporal geostatistics

ABSTRACT

This study presents an approach for generating a global land mapping dataset of the satellite measurements of CO₂ total column (XCO₂) using spatio-temporal geostatistics, which makes full use of the joint spatial and temporal dependencies between observations. The mapping approach considers the latitude-zonal seasonal cycles and spatio-temporal correlation structure of XCO₂, and obtains global land maps of XCO₂, with a spatial grid resolution of 1° latitude by 1° longitude and temporal resolution of 3 days. We evaluate the accuracy and uncertainty of the mapping dataset in the following three ways: (1) in cross-validation, the mapping approach results in a high correlation coefficient of 0.94 between the predictions and observations, (2) in comparison with ground truth provided by the Total Carbon Column Observing Network (TCCON), the predicted XCO₂ time series and those from TCCON sites are in good agreement, with an overall bias of 0.01?ppm and a standard deviation of the difference of 1.22?ppm and (3) in comparison with model simulations, the spatio-temporal variability of XCO₂ between the mapping dataset and simulations from the CT2013 and GEOS-Chem are generally consistent. The generated mapping XCO₂ data in this study provides a new global geospatial dataset in global understanding of greenhouse gases dynamics and global warming.     

基于ArcGISEngine的多源数据拓扑检查研究

在许多数据管理软件中,拓扑检查是必不可少的功能,数据管理软件往往会管理来自多个数据源的数据,而ArcGISEngine中要实现拓扑检查,必须将数据统一存放到一个要素集下,故需要有一个数据拷贝的过程,本文在对ArcGIS拓扑关系介绍的基础上,介绍如何实现基于ArcGISEngine的多源数据拓扑检查,为类似数据管理系统的开发提供参考。