腾冲热海火山地热区近期水热爆炸的阶段性演化特征

水热爆炸是活动性地热田的典型显示。腾冲热海火山地热区历史上曾发生过强烈的水热爆炸活动，但前期一度沉寂。1993年以来水热爆炸活动再度活跃。在过去十年间，研究区内发生过较大的爆炸喷发事件20余次，且规模越来越大。本文根据对爆炸形成泉点的选出气体化学和氦同位素组成的测试结果，研究了区内近期水热爆炸活动的演化特征。逸出气体化学和氦同位素组成特征指示，区内近期引发水热爆炸活动的气体源区有从浅层、中层向深层发展的趋势；作者认为，区内未来可能发生更大规模的爆炸活动，其危险性应引起高度关注。     

黄河流域天然径流量突变性与周期性特征

突变性和周期性是水文时间序列的两个重要特征。黄河流域面积广阔，各区域水文水资源系统演变规律各不相同，它们的突变和周期变化及其形成的物理机制遍异，因此系统分析各区域水资源突变性和周期性特征及其影响机制具有重要意义。把黄河流域划分为15个区域，计算出各区域1951—1998年的年天然径流量系列。利用Mann-Kendall非参数检验方法检测黄河流域各区域年天然径流量的突变年份，结果表明各区域的突变年份不完全一致，主要在1953—1955年、1979—1983年、1991—1993年等发生了突变，这些突变与北半球气候突变具有一致性，且由于下垫面改变、人类活动等影响而复杂化。利用Morlet小波分析各区域年天然径流量的变化周期，发现主要存在3～4a、7～9a、11a的周期，形成这些周期的物理因子有太阳黑子、海—气相互作用和下垫面因素等。通过分析黄河流域主要产流区不同时段小波系数变化，发现20世纪80年代之后年径流量主要以短周期变化。     

四川某矿山边坡失稳机理及稳定性评价

四川某矿山开采边坡迄今已有30余年,随采区规模的逐渐扩大,在矿区南坡构成一典型的顺层开挖边坡,因矿层中夹有不同数量的软弱夹层,在边坡前缘破坏坡角、并加上降雨及爆破振动影响,时常发生颁层滑坡,不仅给矿山人民生命财产带来严重危害,而且也严重制约矿山的正常发展。通过对典型开挖边坡所在部位的工程地质条件凋查,在确定影响边坡稳定的主要控制因素和边界条件的基础上。考虑四种工况条件下的稳定性分析和评价,为矿山下一步施工提出了较为合理的开挖方案。     

青藏高原的水塔功能

青藏高原是维持我国乃至东亚地区生态系统的重要水塔。高原平均海拔在4000m以上,与周边地区形成了巨大的地势差。高原东南部不仅具有丰富的降水,而且在3500m以上以冰川雪被形态储存了巨大的水资源,因此,高原具有重要的水塔功能。基于高原潜在输出总水量和不同海拔区域水体所具有的势能两个方面,建立了高原水塔功能的模型,从而利用GIS方法,通过对我国1∶400万系列图和相关资料的统计分析,计算出高原不同高度带贮存的大气降水、冰川储水量、湖泊水量以及工农业用水量。计算结果表明,青藏高原冰川湖泊的淡水储量达39921×108m3,其中冰川储水量为39228×108m3,可利用湖泊储水量为693×108m3,平均每年由降水获得的水资源量为8495×108m3,高原工农业用水量为129×108m3。因此,高原的输出水量即出境河川径流量为6870×108m3。高原储水主要分布在海拔3000～5000m间,与高原周围相比,平均势差在2000～4000m间,最大的势差达5500m。水体具有巨大的势能,在势能的作用下,自然向周边区域输送汇集,维持着周边地区的生态过程和社会经济活动,因此,青藏高原的水塔功能对于周边地区的生态系统和社会经济系统是极其重要的。     

中国兴凯湖北岸平原晚全新世花粉记录及泥炭沼泽形成

通过兴凯湖北岸平原泥炭剖面高分辩率花粉分析研究，对晚全新世花粉划分4个组合带。XKH-4组合时期(1857～1746aB．P．)为沼泽发育前期，这一时期花粉浓度小，陆生草本植物占优势，气候干冷。XKH-3组合时期(1746～1287aB．P．)为沼泽发育早期，这一时期花粉浓度较大，且水生植物花粉含量为剖面最高，喜温落叶阔叶植物大发展时期，气候温和湿润。XKH-2组合时期(1287～602aB．P．)为沼泽发育中期，这一时期花粉浓度最小，但以陆生草本植物为主，木本植物为辅，水生植物急剧减少，针叶植物出现两次高峰，气候向冷干方向发展。XKH-1组合时期(602aB．P．至今)为沼泽发育盛期，这一时期花粉浓度最大，陆生草本植物大发展时期，气候波动较大。     

洪湖的环境变迁与生态保护

洪湖历史上经历了多次变迁，在同类型湖泊中表现出其生态的复杂性和多样性。通过分析洪湖从成湖以来所发生的的湖泊环境变化，阐述了人类活动对洪湖环境带来的一系列生态问题，对洪湖生态环境的恢复与优化提出对策与建议；同时，对于洪湖省级湿地自然保护区的建设和管理提出了科学的、可操作的具体措施。     

Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".     

The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

基于多模态感知的水下目标检测应用构想

水下目标检测在海洋生物研究、考古探索、军事防御等多领域广泛应用,随着人工智能快速发展,水下目标检测也朝着无人化、智能化发展。深度学习采用神经网络挖掘信息特征,在速度和精度上均表现出优异的性能,成为了计算机视觉技术的主流算法,然而水下环境复杂,将其应用于水下图像目标检测仍存在较大的挑战。水下目标各模态信息互补,特征丰富,有利于目标检测识别,因此结合应用场景调研现有技术,然后设计基于深度学习的多模态水下目标检测系统,同时对比分析了现有关键技术的优缺点,最后对多模态目标检测系统未来发展进行总结与展望,具有重要意义。     

基于YOLO算法的海洋中尺度涡三维结构构建

海洋中尺度涡是一种常见的中尺度海洋现象,研究海洋中尺度涡的分布及运动特性对航运、气候、军事等具有重要作用,海洋中尺度涡的识别是海洋学和计算机科学领域的一个热门研究课题。运用深度学习的方法和框架,对中尺度涡的二维识别和三维结构构建展开研究分析。首先,获取全球海洋再分析数据并进行流线可视化,构建涡旋流线数据集;其次,利用YOLO v5s卷积神经网络对涡旋流线数据集进行训练,并对南海区域中尺度涡进行有效检测。实验结果表明,YOLO v5s训练后得到最优模型经过测试,平均检测精度均值达到了86.10%;最后,根据涡旋检测结果,对检测出的同时刻不同深度的涡旋判断是否属于同一涡旋,确定后进行该涡旋的三维结构构建。