含硬包体试样在破裂孕育过程中波速场的变化

含硬包体混凝土试样在底面支撑侧面双轴加压至主破裂的情况下波速场的变化图象为：加压初期,试样上的纵波平均速度在４１７５～４６１５ｍ／ｓ之间变化,随着压力升高,出现小于４１７５ｍ／ｓ的低速区,但范围甚小,位置在两个包体之间。随后出现大于４６１５ｍ／ｓ的高速区,范围大致与包体位置一致。随着σ１的增加,低速区在逐渐变大,高速区逐步减小后又重新变大,高速区与低速区在平面上相互重叠,在空间上看,高速区被低速区包围着。临近主破裂时,低速区变小并逐步形成条带,高速区也变小,主要集中在靠近未来出现破裂的一个包体位置上。最终的破裂面出现在此高速区与低速条带交界附近,包体也局部破裂了。     

Experimental Research on Flooding Oil by Water Imbibition in Tight Sandstone Oil Reservoir

<正>1 Introduction In recent years,tight oil reservoir has become one of the hot areas of oil and gas exploration and development.Exploration practice shows the technically mineable resources of tight oil in China is(20~25)×10~8t,which has broad prospects for exploitation.However,the natural productivity of single well in tight sandstone oil reservoirs     

过去百年青海和西藏耕地空间格局重建及其时空变化

网格化的历史土地利用/覆被数据集,可为历史气候变化和碳循环研究提供基础数据。本文估算了1910年,并订正了1950-2000年青海和西藏的省域耕地面积数据;基于现代耕地空间格局,量化了海拔高程和地面坡度与耕地空间分布之间的关系,构建了历史耕地网格化重建模型。将1910、1960、1980和2000年的省域耕地面积数据带入网格化重建模型,得到了4个时间断面的耕地空间格局。结果表明:青藏两省耕地面积1910-1950年稳定,1950-1980年快速增加,1980-2000年基本稳定,略有降低。就空间格局而言,1960-1980年,河湟谷地和"一江两河"地区土地开垦范围的扩张和垦殖强度的增长在过去百年最为明显。模型检验表明,模型重建的2000年耕地空间格局与2000年遥感数据相关系数达0.92。     

青藏高原河谷地区历史时期耕地格局重建方法探讨——以河湟谷地为例

青藏高原受其特殊自然地理环境条件的限制,耕地主要分布在自然环境条件相对优越的河谷地区,人为因素对耕地分布范围的作用和影响极其微弱,尤其是在历史时期生产力水平较低的前提下,耕地的空间分布主要取决于土地的宜垦程度。本文将影响青藏高原河谷地区耕地分布的因子按其性质分为限制性因子和非限制性因子,并以此为基础排除了高原河谷地区不适宜耕作的地区,在适宜耕作的地区根据土地的宜垦程度,按"先优后劣"的原则将历史时期的耕地数据分配到空间上。选取青藏高原农业发展历史悠久的河谷地区之一河湟谷地作为实例,重建该区1726年耕地空间格局。将重建结果与已有的M模型重建结果进行对比分析,两者重建的耕地在空间分布上呈现出一致性,但重建结果在垦殖范围与垦殖强度上存在一定的差异;M模型的重建主要是以现代耕地分布格局为基础重建,忽略了现代耕地空间分布受现代农业技术的影响;而本文模型则是从低生产力水平前提下影响历史时期耕地分布的因子出发,重建结果更具合理性。     

Comprehensive Evaluation of the Suitability of Agricultural Land in Myanmar

Myanmar is a country with an economy based on agriculture. It has rich agricultural resources and great potential for development. The development of agriculture in Myanmar is becoming increasingly important to international food security. Assessments of agricultural land resources in Myanmar are the basis for the country’s agricultural development and for food security evaluations. In this paper we used the MaxEnt model to analyze the relationship between the suitability of land for agricultural reclamation and the main environmental variables in Myanmar, and then constructed a model to comprehensively evaluate the suitability of land for agriculture in Myanmar. The results show that: 1) the overall accuracy of the MaxEnt model is high (AUC>0.8), which means there is a high correlation between the database of selected environmental indicators and the true distribution of cultivated land in Myanmar. 2) Soil depth is the most important factor affecting the suitability of land for agriculture in Myanmar. When the thickness of soil layer is less than 100 cm, the suitability of land for agriculture is low. With respect to topographic conditions, slope is the main factor affecting suitability. When the slope is greater than 20 degrees, the suitability of land for agriculture is low. With respect to climate conditions, precipitation is the main influencing factor. There is a positive correlation between river network density and land suitability. 3) Currently, 400 000 km² of the land resources in Myanmar are suitable for agriculture, and of this amount 290 000 km² are highly suitable, accounting for nearly 40% of the country's land area. The highly suitable land is distributed mainly in Magway, Sagaing, Ayeyarwady and Yangon provinces. The provinces are also important grain production areas in Myanmar, and this serves to validate the effectiveness of the method used in this paper.     

Land Cover Status in the Koshi River Basin,Central Himalayas

The Koshi River Basin is in the middle of the Himalayas, a tributary of the Ganges River and a very important cross-border watershed. Across the basin there are large changes in altitude, habitat complexity, ecosystem integrity, land cover diversity and regional difference and this area is sensitive to global climate change. Based on Landsat TM images, vegetation mapping, field investigations and 3S technology, we compiled high-precision land cover data for the Koshi River Basin and analyzed current land cover characteristics. We found that from source to downstream, land cover in the Koshi River Basin in 2010 was composed of water body (glacier), bare land, sparse vegetation, grassland, wetland, shrubland, forest, cropland, water body (river or lake) and built-up areas. Among them, grassland, forest, bare land and cropland are the main types, accounting for 25.83%, 21.19%, 19.31% and 15.09% of the basin’s area respectively. The composition and structure of the Koshi River Basin land cover types are different between southern and northern slopes. The north slope is dominated by grassland, bare land and glacier; forest, bare land and glacier are mainly found on northern slopes. Northern slopes contain nearly seven times more grassland than southern slopes; while 97.13% of forest is located on southern slopes. Grassland area on northern slope is 6.67 times than on southern slope. The vertical distribution of major land cover types has obvious zonal characteristics. Land cover types from low to high altitudes are cropland, forest, Shrubland and mixed cropland, grassland, sparse vegetation, bare land and water bodies. These results provide a scientific basis for the study of land use and cover change in a critical region and will inform ecosystem protection, sustainability and management in this and other alpine transboundary basins.     

基于NPP数据和样区对比法的青藏高原自然保护区保护成效分析

在青藏高原选择11个代表性自然保护区,基于高寒草地植被净初级生产力（Net Primary Production,简写NPP）变化过程数据,比较分析了自然保护区与其相邻等面积区域的NPP变化差异;采用样区对比法,在自然保护区内外选取21组对比样区,比较自然保护区建立前后及其内外的生态状况,评估了自然保护区的保护成效。研究表明：1. 1982-2009年间,82%的代表性自然保护区NPP比保护区周邻区域及青藏高原的平均水平低,反映了自然保护区的生态系统状况更为脆弱;2. 在代表性自然保护区中,曼则塘自然保护区的NPP增长趋势最为明显,塔什库尔干野生动物自然保护区的NPP增长趋势最弱;除色林错自然保护区外,以草甸和湿地为主的自然保护区NPP增速明显高于以草原与荒漠草地为主的自然保护区;3. 代表性样区的研究发现：① 自然保护区内76%以上的样区和国家级保护区内82%以上的样区NPP增加幅度明显高于保护区外对应样区的增幅;② 取得明显保护效果的有中昆仑、长沙贡玛、若尔盖和色林错等自然保护区;曼则塘自然保护区的东南部边缘地区和塔什库尔干野生动物自然保护区的北部边缘地区的效果不明显,可能与保护区及其周邻地区人类扰动增强密切相关;③ 高寒草甸类型自然保护区的保护效果最为显著,高寒草原类型自然保护区的保护效果较差。本研究展示了样区对比法在评估大区域生态变化中所具有的独特优势,其关键在于科学设计样区并进行合理的空间抽样。     

青藏高原东北部河湟谷地1726 年耕地格局重建

整理、校正了1726 年（雍正四年）河湟谷地历史文献中的田亩数据,并在GIS技术的支持下建立了该区1726 年具有空间属性（2 km×2 km）的耕地分布格局。结果显示：1726 年河湟谷地耕地总面积为1.427×10³ km²,其中番地占64.7%,屯科秋站垦地占35.3%。河湟谷地虽然面积较大,但受自然环境条件的限制,可耕之地较少,该区仅有47%的网格具有耕地分布,耕地集中分布在湟水河干流区及大通河中游地区和龙羊峡以下的黄河谷地。从耕地垦殖强度分析,受自然环境条件和政治格局的双重影响,1726 年该区整体垦殖率较低,全区仅有1.4%的耕地网格垦殖率在40%以上,而68.3%的耕地网格垦殖率在10%以下,正处在广泛的开荒垦殖阶段。垦殖强度在空间分布上也存在明显差异,其中西宁县整体垦殖率水平最高,其耕地网格平均垦殖率达到了13.5%。     

波浪骑士数据在高度计有效波高检验中的再处理

以2011年10～11月南海现场试验得到的9次波浪骑士测量数据,进行波浪骑士再处理与默认计算结果比对。比对结果表明两者平均误差为0.16m,均方根误差为0.32m,分析产生误差的原因在于波浪骑士默认计算有效波高时间段的中心与卫星过境时间不统一和未进行数据质量控制。研究表明在卫星高度计有效波高产品检验中,波浪骑士测量的有效波高需要进行再处理,以达到减少卫星高度计有效波高检验误差的目的。     

The trend on runoff variations in the Lhasa River Basin

Taking the Lhasa River Basin above Lhasa hydrological station in Tibetan Plateau as a study area, the characteristics of the annual and monthly mean runoff during 1956?2003 were analyzed, based on the hydro-data of the two hydrological stations (Lhasa and Tanggya) and the meteorological data of the three meteorological stations (Damxung, Lhasa and Tanggya). The trends and the change points of runoff and climate from 1956 to 2003 were detected using the nonparametric Mann-Kendall test and Pettitt-Mann-Whitney change-point statistics. The correlations between runoff and climate change were analyzed using multiple linear regression. The major results could be summarized as follows: (1) The annual mean runoff during the last 50 years is characterized by a great fluctuation and a positive trend with two change points (around 1970 and the early 1980s), after which the runoff tended to in-crease and was increasing intensively in the last 20 years. Besides, the monthly mean runoff with a positive trend is centralized in winter half-year (November to April) and some other months (May, July and September). (2) The trends of the climate change in the study area are generally consistent with the trend of the runoff, but the leading climate factors which aroused the runoff variation are distinct. Precipitation is the dominant factor influencing the annual and monthly mean runoff in summer half year, while temperature is the primary factor in winter season.