土壤天然热释光测量在寻找滑坡体边界中的应用研究

土壤天然热释光测量方法是一种累积型测氡方法。由于累积测氡时间长,其灵敏度和异常的重现性远比一般累积测氡及其子体方法好,因此,在地质领域得到了广泛的应用。在寻找滑坡体边界的应用中,取得的测量效果明显,表明该方法经济有效。     

鄱阳湖流域径流模型

流域径流是鄱阳湖主要来水,建立鄱阳湖流域径流模型对揭示湖泊水量平衡及其受流域自然和人类活动的影响具有重要意义.针对鄱阳湖-流域系统的特点:流域面积大(16.22×104km2)、多条入湖河流、湖滨区坡面入湖径流等,研究了相应的模拟方法,建立了考虑流域土壤属性和土地利用空间变化的鄱阳湖流域分布式径流模型.采用6个水文站1991-2001年的实测河道径流对模型进行了率定和验证.结果显示,模型整体模拟精度较高.其中,赣江、信江和饶河均取得了较好的模拟结果,月效率系数为0.82-0.95;抚河和修水模拟精度略低,为0.65-0.78.模型揭示了研究时段内年平均入湖径流总量为1623×108m3,其中,赣江最多,占47%,其次为信江和抚河,分别占13%和12%,湖滨区坡面入湖径流约占4%,其余24%来自饶河、修水以及其它入湖支流.模型将用于评估流域下垫面或气候变化引起的入湖水量变化,为湖泊水量平衡计算提供依据.     

青藏高原近地层低压系统移动路径及其特征

利用ECMWF 600 hPa高度场加密逐月再分析资料,分析了强、弱季风年高原近地层低压系统的移动路径及其特征。研究结果表明：低压系统于4月在青海省西南部形成,5月沿西南方向移入西藏地区,此后低压系统呈南北向波动西移,直至到达“西至点”后转向东退于10月衰减消散;强季风年低压系统中心强度总体上较弱季风年强。强季风年低压系统移动路径偏北,南北向波动振幅较小,弱季风年低压系统移动路径偏南,南北向波动振幅较大,呈“V”形分布;孕育初生阶段低压系统的形成过程在弱季风年出现“反复”现象;发展成熟阶段高原近地层低压系统南侧印度上空低压系统形成,并且强季风年较弱季风年形成时间偏迟,位置偏南;衰减消亡阶段高原近地层低压系统西北侧的高压系统减弱消散,10月东伸高压脊的脊点在弱季风年较强季风年偏东。     

两种统计降尺度方法在秦岭山地的适用性

基于ASD（automated statistical downscaling）统计降尺度模型提供的多元线性回归和岭回归两种统计降尺度方法,采用RCP4.5（representative concentration pathways 4.5）和RCP8.5情景下全球气候模式MPI-ESM-LR输出的预报因子数据、NCEP/NCAR再分析数据和秦岭山地周边10个气象站观测数据,评估两种统计降尺度方法在秦岭山地的适用性及预估秦岭山地未来3个时期（2006-2040年、2041-2070年和2071-2100年）的平均气温和降水。结果表明:率定期和验证期内,两种统计降尺度方法均可以较好地模拟研究区域的平均气温和降水的变化特征,且多元线性回归的模拟效果优于岭回归。在未来气候情景下,两种统计降尺度方法预估的研究区域平均气温均呈明显上升趋势,气温增幅随辐射强迫增加而增大。降水方面,21世纪未来3个时期降水均呈不明显减少趋势,但季节分配发生变化。综合考虑两种统计降尺度方法在秦岭山地对平均气温和降水的模拟效果和情景预估结果,认为多元线性回归降尺度方法更适用于秦岭山地气候变化的降尺度预估研究。     

商业化背景下古村落旅游景观生产 ——以安徽宏村为例

以安徽省古村落宏村为例,采用参与式观察和半结构访谈的方法对其旅游景观的生产方式与机制进行研究。结果发现,随着商业化发展,宏村旅游景观生产由原来单一的文物古建保护向更趋复杂化转变,针对3种不同类型的旅游景观采取相应的生产方式。宏村旅游景观生产背后是多种力量参与的生产机制：政府与开发商强强联合,是旅游景观生产的主导力量;当地居民依然扎根宏村,是旅游景观生产的核心灵魂;景区商家热衷于打造“店铺景观”,是旅游景观生产的积极分子;外来游客提出的改进建议则是宏村旅游景观生产的重要参考。4种力量集团本着对各自利益的谋求,彼此间相互合作,影响宏村旅游景观生产的最终结果。最后提出,古村落旅游景观生产需要还原原住居民生活化场景,借旅游商业化发展之势,建立均衡、可持续的景观生产机制与合理的利益分配体系或许是古村落旅游景观生产的正解。     

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province,southern China

Rainfall erosivity, which shows a potential risk of soil loss caused by water erosion, is an important factor in soil erosion process. In consideration of the critical condition of soil erosion induced by rainfall in Guangdong Province of southern China, this study analyzed the spatial and temporal variations in rainfall erosivity based on daily rainfall data observed at 25 meteorological stations during the period of 1960–2011. The methods of global spatial autocorrelation, kriging interpolation, Mann–Kendall test, and continuous wavelet transform were used. Results revealed that the annual rainfall erosivity in Guangdong Province, which spatially varied with the maximum level observed in June, was classified as high erosivity with two peaks that occur in spring and summer. In the direction of south–north, mean annual rainfall erosivity, which showed significant relationships with mean annual rainfall and latitude, gradually decreased with the high values mainly distributed in the coastal area and the low values mainly occurring in the lowlands of northwestern Guangdong. Meanwhile, a significant positive spatial autocorrelation which implied a clustered pattern was observed for annual rainfall erosivity. The spatial distribution of seasonal rainfall erosivity exhibited clustering tendencies, except spring erosivity with Moran’s I and Z values of 0.1 and 1.04, respectively. The spatial distribution of monthly rainfall erosivity presented clustered patterns in January–March and July–October as well as random patterns in the remaining months. The temporal trend of mean rainfall erosivity in Guangdong Province showed no statistically significant trend at the annual, seasonal, and monthly scales. However, at each station, 1 out of 25 stations exhibited a statistically significant trend at the annual scale; 4 stations located around the Pearl River Delta presented significant trends in summer at the seasonal scale; significant trends were observed in March (increasing trends at 3 stations), June (increasing trends at 4 stations located in the Beijiang River Basin), and October (decreasing trends at 4 stations) at the monthly scale. In accordance with the mean annual rainfall over Guangdong Province, the mean annual rainfall erosivity showed two significant periodicities of 3–6 and 10–12 years at a confidence level of 95 %. In conclusion, the results of this study provide insights into the spatiotemporal variation in rainfall erosivity in Guangdong Province and support for agrolandscape planning and water and soil conservation efforts in this region.     

A methodology for estimating business interruption loss caused by flood disasters: insights from business surveys after Tokai Heavy Rain in Japan

This study proposes a probabilistic methodology for estimating the business interruption loss of industrial sectors as an extension of current methodology. The functional forms and parameters are selected and calibrated based on survey data obtained from businesses located in the inundated area at the time of the 2000 Tokai Heavy Rain in Japan. The Tokai Heavy Rain was a rare event that hit a densely populated and industrialized area. In the estimation of business interruption losses, functional fragility curves and accelerated failure time models are selected to estimate the extent of damage to production capacity and production recovery time. Significant explanatory variables, such as inundation depth, distinct vulnerability, and the resilience characteristics of each sector, as well as the accuracy of fit of the model, are analyzed in the study. The function obtained and the estimated parameters can be utilized as benchmarks in estimating the probabilistic distribution of business interruption losses, especially in the case of urban flood disasters.

     

全媒体时代地理信息传播模式的研究

全媒体时代的到来,实现了受众身份的重构,信息发布门槛的降低,让公众真正参与到信息的传播中。地理信息作为信息的种属分支,势必会在全媒体时代的浪潮中发生变化。本文针对全媒体时代下地理信息的传播模式进行了研究,从传播学的视角,以信息的传播理论为基础,对地理信息传播模式的变迁进行了分析,并构建了全媒体时代下去中心化、辐射扩散式的传播模式。结合全媒体的特点从传播主体、内容、形式、受众和方式上分析了地理信息的传播特征,对当下地理信息传播态势和所存在的问题进行了研究和展望。     

高原地区ERA40与NCEPI再分析资料对比分析

利用ERA40、NCEPI (NCEP/NCAR version Ⅰ)再分析资料以及高原地区的探空资料和1979年青藏高原地区第1次气象科学试验资料,详细的比较了高原地区位势高度的特征.结果表明,两套再分析资料在高原地区具有一定的相似性,但仍存在着明显的差别.相比较而言,高原北部地区ERA40再分析资料除1980-19...     

Estimation of property loss and business interruption loss caused by storm surge inundation due to climate change: a case of Typhoon Vera revisit

This paper estimates property loss and business interruption loss under scenarios of storm surge inundation to explore the economic impact of climate change on Ise Bay, Japan. Scenarios-based analyses are conducted with respect to Typhoon Vera, which caused the most severe storm surge in the recorded history of Japan in 1959. Four different hazard scenarios are chosen from a series of typhoon storm surge inundation simulations: Typhoon Vera’s landfall with respect to the condition of the past seawall; Typhoon Vera’s landfall with respect to the condition of the current seawall; intensifying Typhoon Vera, but retaining its original tracks; and intensifying Typhoon Vera, but choosing the worst tracks from various possible typhoon tracks. Our economic loss estimation takes advantage of fine geographical scale census and economic census data that enable us to understand the spatial distribution of property loss and business interruption loss as well as identify the most potentially affected areas and business sectors on a sub-city scale. By comparing the property loss and business interruption loss caused by different hazard scenarios, the effect of different seawalls is evaluated and the economic impact of future climate change is estimated. The results indicate that although the current seawall can considerably reduce the scale of losses, climate change can cause Ise Bay to experience more serious storm surge inundation. Moreover, the resulting economic losses would increase significantly owing to a combination of climate change and the worst track scenario. It is, therefore, necessary to consider more countermeasures to adapt to climate change in this area.