济南市岩溶水动态变化的神经网络模拟及泉水喷涌趋势预测

本文根据影响岩溶水位的因素,利用改进的BP神经网络建立一个能够反映济南市泉域岩溶地下水动态变化的随机模型,并进行检验,与运用多元回归模型预测的结果相比较,结果表明:BP神经网络模型进行岩溶地下水动态变化预测是可行的,该模型具有较强的学习、容错和联想功能,对岩溶地下水动态变化的预测精度大大的提高。最后在模拟的基础上,又对泉水喷涌的宏观趋势作了进一步的预测和分析。     

郑州市城区深部基岩层热储特征分析

通过对郑州市城区深部基岩层热储的岩性、构造、热源及盖层条件分析研究,总结了该区热储特征,并首次提出了断裂循环型带状热储构造网络体系的构思,这对该区今后深部基岩层热储的研究具有一定的参考意义。     

关于城市交通地理信息系统模型设计的思考与改进

GIS—T模型是建立城市交通地理信息系统的主体,本文对现有GIS—T模型进行了简单的分析与评价,并且为了增加政府与公众做出决策的正确性,提出了路径畅通可靠度模型、城市交通综合指数模型、交通出行指数模型三个数学模型,以达到量化城市交通与完善GIS—T模型的目的。     

Determining the equivalent permeability tensor for fractured rock masses using a stochastic REV approach: Method and application to the field data from Sellafield,UK

A numerical procedure to determine the equivalent permeability tensor of a fractured rock is presented, using a stochastic REV (Representative Elementary Volume) concept that uses multiple realizations of stochastic DFN (Discrete Fracture Network) models. Ten square DFN models are generated using the Monte Carlo simulations of the fracture system based on the data obtained from a site characterization program at Sellafield, Cumbria, UK. Smaller models with varying sizes of from 0.25 m×0.25 m to 10 m×10 m are extracted from the generated DFN models and are used as two-dimensional geometrical models for calculation of equivalent permeability tensor. The DFN models are also rotated in 30º intervals to evaluate the tensor characteristics of calculated directional permeability. Results show that the variance of the calculated permeability values decreases significantly as the side lengths of the DFN models increase, which justifies the existence of a REV. The REV side length found in this analysis is about 5 m and 8 m with 20% and 10% acceptable variations, respectively. The calculated directional permeability values at the REV size have tensor characteristic that is confirmed by a close approximation of an ellipse in a polar plot of the reciprocal of square roots of the directional permeability.

大凌河流域MIKE BASIN水资源模型

Mike Basin模型是一个集总式综合河网模拟系统,与GIS系统全面链接,具备清楚的数据与模型结构,支持水资源综合管理的参与式对话和矛盾解决方案。它由两个模型单元组成:水文模型(NAM)和水资源分配模型(MIKE BASIN)。它是认识和分析流域水资源状况,进行流域水资源综合管理规划十分重要的工具。本文从模型数据的需求、分析与应用以及参数的率定,较详细地阐述了大凌河流域MIKE BASIN水资源模型的建立过程,为其他用户进行模型的建立提供了借鉴。     

浅谈新疆测震台网传输链路的改造

要做到IP到台站有很多种方式可选,根据新疆测震台网各台站的现状列举了7类不同的数据传输方式,这些数据传输方式在新疆测震台网中均得到应用,也都达到IP到台站的目的.分别对这些数据传输链路的原理及优缺点进行阐述,并结合目前各台站具体情况作链路适用性的相关分析,希望能够对其他省局台网的台站通信链路设计、改造起到参考.     

一种新的网络中层管理者方案

提出一种新的基于 Ｓ Ｎ Ｍ Ｐｖ２ 的中层管理者方案以弥补 Ｍ２ Ｍ Ｍ Ｉ Ｂ的不足,其轮询方法和报警机制优于现有同类产品,且具有更好的安全性和互操作性。     

基于遥感数据的夏玉米高温热害监测评估

玉米作为一种重要的粮食作物,其产量对于国家粮食安全的影响至关重要。该文结合遥感与地面实测气温数据,基于地表温度与气温具有显著的线性相关关系,构建我国夏玉米主产区高温热害评估模型,并对该模型进行精度检验。结果表明：平原区域日平均气温的模拟结果决定系数在0.8以上,达到0.001显著性水平,均方根误差在1.8℃左右的小范围内波动;平原区域精度略高,山区精度略低（均方根误差为2.4℃）。利用该模型对2008—2018年黄淮海夏玉米主产区高温热害进行评估,发现2017年和2018年夏玉米受高温热害影响最严重,高温热害区主要分布在河北省东南部、河南省大部以及山东省西部,该结果与实际情况相符。     

Creating adaptive social-ecological fit: The role of regional actors in the governance of Sea-level rise adaptation in San Francisco bay

Sea level rise is one of the most pressing climate adaptation issues around the world. Often, coastal communities are interdependent in their exposure to sea level rise – if one builds a seawall, it will push water to another – and would benefit from a coordinated adaptive response. The literature on social-ecological systems (SES) calls for actors placed at higher levels of governance (e.g. regional government in a metropolitan area) to improve coordination between local managers by serving as brokers. However, we lack empirical insight on how higher-level actors might improve coordination in practice, and theoretical development on the implications of their intermediation. To address these gaps, we study the case of adaptation to sea level rise in the San Francisco Bay Area. We build a social-ecological network of social actors and shoreline segments using original survey data and simulated scenarios of tidal and traffic interdependencies between shoreline segments. We perform a frequency analysis of network motifs that operationalize social-ecological ‘fit’ in the context of the Bay Area. We find that regional actors and non-governmental organizations increase social-ecological fit by providing intermediation between actors who work on different shoreline segments, whether interdependent or not. This shows that these actors provide adaptive social-ecological fit, future-proofing the Bay Area to current and future climate adaptation challenges.     

运用人工神经网络作汛期降水预报

本文提出汛期降水预报的人工神经网络方法，并选择一组标样进行了具体分析，预报成功率达100％，结果表明，该方法性能良好，可望成为汛期降水预报的有效手段。