我国南疆荒漠喀什-和田地区的畜牧业特点与发展战略

作者在对该地区进行实地考察的基础上,研究了位于新疆南部荒漠最西部两个地区的自然环境和经济条件后,指出该地区畜牧业的 4个基本特点,概括了该地区畜牧业与生态环境以及牧业生产条件之间的关系。地处内陆,极端干旱,周围高山环绕,绿洲经济与绿洲农业发达,对该地区畜牧业的现状与发展有深刻影响。从而作者提出了该地区发展畜牧业的方向与战略。指出今后应以发展集约化的平原绿洲畜牧业为主体。改革饲养方式,加强饲料生产,提高畜群生产水平,近期商品性生产的发展要与自给性生产的发展相结合。使我国这一特殊类型地区的畜牧业得以顺利发展。     

1960-2016年中国北方地区极端干湿事件演变特征

基于中国北方地区424个气象站点1960-2016年的日气象数据础,应用FAO Penman-Monteith模型计算潜在蒸散（ET₀）,基于降水量和潜在蒸散计算湿润指数,对湿润指数进行标准化后统计极端干湿事件频率,分析极端干湿事件频率的空间变化趋势、多时间尺度演变特征以及ENSO事件对极端干湿事件变化趋势的影响。结果表明：北方极端干旱和极端湿润事件频率分别呈显著下降和显著上升趋势,年际倾向率分别为-0.10次/10年和0.13次/10年。空间上,极端干旱频率整体呈减少趋势,包括青藏高原、西北和东北地区。西北极端干旱频率减少速率较大,青藏高原中部、新疆北部和东北北部部分站点极端湿润频率增加幅度较大。各年代中,华北极端干旱多发,东北和青藏高原极端湿润多发。季节上,分区极端干旱发生概率均大于极端湿润发生概率,华北极端干旱发生概率最高,青藏高原极端湿润发生概率最高。ENSO与湿润指数存在滞后性的关系。El Niño翌年,气候偏湿润的年份较多;La Nina翌年,气候偏干旱的年份较多。SSTA与翌年湿润指数在年际和夏季两个时间尺度上存在显著的正相关关系。     

野外极端低温环境人体皮肤温度变化研究

为明确不同极端低温环境与防护装备下,日间清醒和夜间睡眠状态下各部位皮肤温度变化特征,在-16 ℃～-30 ℃极端低温环境下,采用皮温测量系统对实验对象5个代表性部位（胸部、手臂、大腿、小腿和脚趾）皮肤温度进行测试。结果表明:日间测试胸部温度相对最高,大腿和小腿在实验中后期出现温度反转。夜间除脚趾外,各部位皮肤温度变化差异较小,大腿温度相对最高,小腿温度与其他部位分离。研究结果可为低温环境下防护服研发与保暖效果评价提供参考。     

历史传染病疫情的环境与气候特征初探及对新冠肺炎疫情的思考

新型冠状病毒肺炎（COVID-19,简称“新冠肺炎”）疫情的暴发与流行对人类社会安全造成严重危害,同时也考验着世界各国公共卫生系统应对大型突发性传染病的防控能力.对历史传染病疫情暴发和流行的环境与气候特征进行总结,对于新冠肺炎疫情的科学研究及防控具有重要的参考价值.结果表明:①历史上人际传播的冠状病毒科、正粘病毒科传染病多暴发于北半球亚热带季风气候地区及冬春季节,而黄病毒科传染病多暴发在热带地区及高温多雨的夏秋季节.②全球变暖和极端天气催生影响传染病的暴发及传播.③人类对生态系统平衡的影响,迫使病毒宿主栖息地迁移和不同病毒宿主聚集,增加病毒变异概率和传染病暴发风险.在此基础上,提出了对新冠肺炎疫情的思考,认为适宜的气候因素可能利于疫情的暴发与流行,而热带国家疫情的暴发则说明需要重新审视气候、环境条件及生态因素对新型冠状病毒的影响.研究结果将为新冠肺炎疫情的防控和未来传染病疫情的预测及阻断提供参考和借鉴.      

西北干旱荒漠生态区脆弱性动态监测及驱动因子定量分析

全球气候变化和人类活动双重胁迫下,西北干旱荒漠生态区的脆弱生态系统发生了深刻变化。论文在充分考虑研究区生态环境背景特征（沙漠化、盐渍化、风力侵蚀、干旱等灾害严重）的基础上,引入极端气候灾害因子（指示气候变化）和大尺度景观格局指数（指示人类活动对生态景观的干扰）,构建了西北干旱荒漠生态区的生态脆弱性评价体系,并对研究区2000—2013年的生态脆弱性时空变化格局及其驱动机制进行了定量分析和讨论。研究结果表明：西北干旱荒漠生态区的生态脆弱性总体上处于中-重度脆弱状态;其生态脆弱性空间分布格局总体上呈现自东向西递减的趋势,西部局部地区则呈现“E”字型格局,该分布格局主要受西北内陆地区大气环流以及三山夹两盆的特殊地貌影响;2000—2013年,西北干旱荒漠生态区生态脆弱性呈现减小趋势,其生态脆弱性变化状况受气温、降水以及人类活动影响显著。研究成果可以为西北干旱荒漠生态区的生态保护和治理提供决策支持。     

极端海况下AUV水环境模拟及定位控制研究

目的优化PID控制器,实现AUV在极端海况下的定位控制。方法本文基于Blendermann风载荷系数计算公式与ITTC双参数波浪谱及漂移力计算公式,在Matlab中建立极端海况风浪模型,对极端海况进行环境模拟;利用Simulink平台搭建基于PID控制器的AUV动力定位控制系统,优化PID控制器参数,对AUV进行定位控制研究。结果在该控制作用下,AUV仍由定位原点顺利抵达目标位置,在PID控制器作用下,系统约100s后达到目标位置状态附近进行微调,整体超调量约8%,在严峻的风浪环境中展现出理想的控制性能。结论本研究成功模拟了AUV的极端工作环境,并搭建了动力定位仿真台架,基于优化后的PID控制器实现了AUV在极端海况下的定位控制,为自主潜航器在恶劣环境中的作业能力保障及控制器设计研究提供了参考。     

Identifying extremely large values using composite sample data

Quantifying a composite sample results in a loss of information on the values of the constituent individual samples. As a consequence of this information loss, it is impossible to identify individual samples having large values, based on composite sample measurements alone. However, under certain circumstances, it is possible to identify individual samples having large values without exhaustively measuring all individual samples. In addition to composite sample measurements, a few additional measurements on carefully selected individual samples are sufficient to identify the individual samples having large values. In this paper, we present a statistical method to recover extremely large individual sample values using composite sample measurements. An application to site characterization is used to illustrate the method.The paper has been prepared with partial support from the United States Environmental Protection Agency Number CR815273. The contents have not been subject to Agency review and therefore do not necessarily reflect the views or policies of the Agency and no official endorsement should be inferred.     

Geomorphological consequences of fraquent and infrequent rainfall and hydrological events in Pyrennez Mountains of Spain

Various aspects of pluviometric andhydrological events have been studiedworldwide, one of which is the geomorphichazards as the intensity of the eventsexceeds various geomorphic thresholds.During the last few years, rainstorms ofdifferent intensities have occurred in theCentral Spanish Pyrenees, including one ofexceptional character. Large, historicaldebris flows have been studied, as well asthe actual sediment transport in smallexperimental catchments. This study showsthat during the most frequent eventssuspended sediment transport is the commongeomorphic process. Bedload is mobilizedseveral times per year while small rockavalanches and channelized debris flowshave a return period of at least 5 years.Hillslope debris flows are triggered byrainfall events with a 25–30 year returnperiod. Reactivation of large, deep massmovements is linked to rainfalls of around100 year return period (between 130 and160 mm in 24 hours). Catastrophicgeomorphic processes occur whenprecipitation exceeds a 100 year returnperiod, as was the case of the Biescascampsite disaster. Geomorphic processestriggered by intense rainfall events havecaused major damage and human disastersbut the hazards have been reduced by theintroduction of several control measures,including reforestation, the constructionof check-dams, canalization of riversegments and improved flood forecasting.     

基于LLE-ELM的矿井瓦斯涌出量预测方法研究

基于局部线性嵌入(Locally Linear Embedding,LLE)算法和极限学习机(Extreme Learning Machine,ELM)神经网络建立矿井瓦斯涌出量预测模型,该预测模型运用LLE算法对矿井瓦斯涌出量影响因素样本进行数据挖掘,得到降维后的有效因子,再将这些有效因子作为ELM神经网络的输入层进行训练和预测。利用某矿井的实测数据进行实例分析,结果表明该预测模型预测速度快,精度高,能够用于矿井瓦斯涌出量预测。     

MULTIVARIATE EXTREME VALUE DISTRIBUTION WITH MIXED GUMBEL MARGINALS1

ABSTRACT: Bivariate and trivariate distributions have been derived from the logistic model for the multivariate extreme value distribution. Marginals in the models are extreme value type I distributions for two-component mixture variables (mixed Gumbel distribution). This paper is a continuation of the previous works on multivariate distribution in hydrology. Interest is focused on the analysis of floods which are generated by different types of storms. The construction of their corresponding probability distributions and density functions are described. In order to obtain the parameters of such a bivariate or trivariate distribution, a generalized maximum likelihood estimation procedure is proposed to allow for the cases of samples with different lengths of record. A region in Northern Mexico with 42 gauging stations, grouped into two homogeneous regions, has been selected to apply the models. Results produced by the multivariate distributions have been compared with those obtained by the Normal, log-Normal-2, log-Normal-3, Gamma-2, Gamma-3, log-Pearson-3, Gumbel, TCEV and General Extreme Value distributions. Goodness of fit is measured by the criterion of standard error of fit. Results suggest that the proposed models are a suitable option to be considered when performing flood frequency analysis.