Propagating uncertainty from catchment experiments to estimates of streamflow reduction by invasive alien plants in southwestern South Africa

Long-term catchment experiments from South Africa have demonstrated that afforestation of grasslands and shrublands significantly reduces surface-water runoff. These results have guided the country's forestry policy and the implementation of a national Invasive Alien Plant (IAP) control programme for the past few decades. Unfortunately, woody IAP densities continue to increase, compounding existing threats to water security from population growth and climatic change. Decision makers need defensible estimates of the impacts of afforestation or invasions on runoff to weigh up alternative land use options, or guide investment of limited resources into ecosystem restoration through IAP clearing versus engineering-based water-augmentation schemes. Existing attempts to extrapolate the impacts observed in catchment afforestation experiments to broad-scale IAP impacts give no indication of uncertainty. Globally, the uncertainty inherent in the results from paired-catchment experiments is seldom propagated into subsequent analyses making use of these data. We present a fully reproducible Bayesian model that propagates uncertainty from input data to final estimates of changes in streamflow when extrapolating from catchment experiments to broader landscapes. We apply our model to South Africa's catchment experiment data, estimating streamflow losses to plantations and analogous plant invasions in the catchments of southwestern South Africa, including uncertainty. We estimate that regional streamflow is reduced by 304 million m³ or 4.14% annually as a result of IAPs, with an upper estimate of 408 million m³ (5.54%) and a lower estimate of 267 million m³ (3.63%). Our model quantifies uncertainty associated with all parameters and their contribution to overall uncertainty, helping guide future research needs. Acknowledging and quantifying inherent uncertainty enables more defensible decisions regarding water resource management.     

Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.     

Tracing the boundary layer sources of carbon monoxide in the Asian summer monsoon anticyclone using WRF-Chem

The Asian summer monsoon(ASM) anticyclone is a dominant feature of the circulation in the upper troposphere–lower stratosphere(UTLS) during boreal summer, which is found to have persistent maxima in carbon monoxide(CO). This enhancement is due to the upward transport of air with high CO from the planetary boundary layer(PBL), and confinement within the anticyclonic circulation. With rapid urbanization and industrialization, CO surface emissions are relatively high in the ASM region, especially in India and East China. To reveal the transport pathway of CO surface emissions over these two regions, and investigate the contribution of these to the CO distribution within the ASM anticyclone, a source sensitivity experiment was performed using the Weather Research and Forecasting(WRF) with chemistry model(WRFChem). According to the experiment results, the CO within the ASM anticyclone mostly comes from India, while the contribution from East China is insignificant. The result is mainly caused by the different transportation mechanisms. In India,CO transportation is primarily affected by convection. The surface air with high CO over India is directly transported to the upper troposphere, and then confined within the ASM anticyclone, leading to a maximum value in the UTLS region. The CO transportation over East China is affected by deep convection and large-scale circulation, resulting mainly in transportation to Korea, Japan, and the North Pacific Ocean, with little upward transport to the anticyclone, leading to a high CO value at215 h Pa over these regions.     

基坑抗隆起稳定安全系数的算法对比分析

基坑隆起变形破坏是一种常见的基坑失稳形式。基坑隆起变形量监测存在一定困难,基坑坑底抗隆起稳定性分析主要是计算安全系数。目前基坑抗隆起稳定安全系数计算方法主要有极限平衡、极限分析和强度折减等方法。结合工程算例,采用上述3种算法进行基坑抗隆起稳定安全系数计算,对比分析了各种计算方法的适用性。结果表明,极限平衡传统算法忽略的工程因素较多,计算结果过于保守,通过修正可以提高适用性。极限分析与强度折减的计算结果较为准确,但极限分析的破坏模式和强度折减中基坑稳定临界状态容许隆起量仍需进一步研究。     

中国产业结构优化路径与碳排放趋势预测

中国已进入产业结构深度调整时期,同时产业升级也是减排的主要途径之一.为此,本文通过构建分部门跨期优化模型,以需求驱动和产业部门供给为基础,假设中国的消费偏好模式不断向发达国家(如美国、欧盟和日本)趋近,对消费偏好导向下的产业结构优化方向及碳排放趋势进行了模拟研究.结果显示,中国的农业和衣食制造部门比重将呈下降趋势,其他服务业部门比重会不断提高.在中国当前消费偏好模式下,重工业、交通运输、化工和金属等高耗能部门的比重仍将增加,而转向美国消费偏好模式后,这些部门的比重都将下降.交通运输和化工部门比重在转向欧盟消费偏好模式后略有提高,转向日本偏好模式后交通运输部门比重将提高,而金属部门比重将下降.受产业结构调整和能源效率提高的影响,中国未来能源消费总量呈倒U型趋势:在中国、欧盟、日本和美国消费偏好模式驱动下,能源消费总量依次下降,对应的能源高峰在2810～2166 Mtoe之间,累积排放量在94～72.6GtC之间.美国的消费偏好模式由于倾向于低碳的服务业部门,因此更有利于节能减排.     

射向标定测量中角度平差方法探讨

射向标定测量只需要提供方位角成果,为了消除测距误差对方位角的影响,在数据处理时只对观测水平角进行平差。比较各种平差方法,并通过实例分析得出,对观测水平角进行间接平差最为方便实用。对多次实测数据进行统计,通过闭合差估计出:射向标定测量中测角中误差为1″左右,基准方位角的精度水平在1.2″左右。     

Oyster patch reefs as indicators of fossil hydrocarbon seeps induced by synsedimentary faults

The Late Jurassic deposits of the Boulonnais area (N-France) represent the proximal lateral-equivalent of the Kimmeridge Clay Formation; they accumulated on a clastic-dominated ramp subject to synsedimentary faulting as a result of the Atlantic Ocean rifting. In the Gris-Nez Cape area, i.e., close to the northern border fault zone of the Jurassic basin, the Late Jurassic sequence contains small-dimensioned oyster patch reefs (<1 m) that are specifically observed at the base of an abrupt deepening trend in the depositional sequence induced by well-defined pulses of normal fault activity. Petrographic analysis of these patch reefs shows that they are exclusively composed of Nanogyra nana embedded in a microsparitic calcite matrix. ™¹³C measurements, carried out within both the matrix and the shells, display significantly lower values in the matrix compared to the oyster shells which suggests that the carbonate matrix precipitation was involving a carbon source different from marine dissolved inorganic carbon, most probably related to sulfate reduction, which is evidenced by light ™³⁴S in pyrites. Similarities but also differences with lucinid-rich bioconstructions, namely, the Late Jurassic pseudo-bioherms of Beauvoisin (SE-France) suggest that the patch reefs developed at hydrocarbon seeps are related to synsedimentary faults. The extensional block-faulting segmentation of the northern margin of the Boulonnais Basin in Late Jurassic times is thus believed to have induced a sort of small-dimension hydrocarbon seepage field, recorded by the patch reef distribution.     

北京市电网雷害分布规律及风险评估

根据1996—2009年北京市逐日电网灾害资料分析了北京市电网雷害的发生规律, 结果显示:北京市电网雷害存在季节变化和日变化特征。结合同期气象观测站的雷暴日资料、北京市各区县的经济和人口密度特征提出了电网雷害概率、电网雷害频度、电网雷害密度、经济易损模数和生命易损模数作为北京市电网雷害风险评估指标。在此基础上,采用4级分区法对上述电网雷害易损性评估指标进行分级,并将北京市各区县按照5个电网雷害评估指标的所属等级值累加,得到电网雷害综合易损风险评估的评估系数。结果表明:北京地区电网雷害高风险区集中在北京城区中心附近,山区和山前迎风坡地带尽管电网雷害频次较高,但电网雷害风险却相对较低。     

UL-Isomap based nonlinear dimensionality reduction for hyperspectral imagery classification

The paper proposes an upgraded landmark-Isometric mapping (UL-Isomap) method to solve the two problems of landmark selection and computational complexity in dimensionality reduction using landmark Isometric mapping (LIsomap) for hyperspectral imagery (HSI) classification. First, the vector quantization method is introduced to select proper landmarks for HSI data. The approach considers the variations in local density of pixels in the spectral space. It locates the unique landmarks representing the geometric structures of HSI data. Then, random projections are used to reduce the bands of HSI data. After that, the new method incorporates the Recursive Lanczos Bisection (RLB) algorithm to construct the fast approximate k-nearest neighbor graph. The RLB algorithm accompanied with random projections improves the speed of neighbor searching in UL-Isomap. After constructing the geodesic distance graph between landmarks and all pixels, the method uses a fast randomized low-rank approximate method to speed up the eigenvalue decomposition of the inner-product matrix in multidimensional scaling. Manifold coordinates of landmarks are then computed. Manifold coordinates of non-landmarks are computed through the pseudo inverse transformation of landmark coordinates. Five experiments on two different HSI datasets are run to test the new UL-Isomap method. Experimental results show that UL-Isomap surpasses LIsomap, both in the overall classification accuracy (OCA) and in computational speed, with a speed over 5 times faster. Moreover, the UL-Isomap method, when compared against the Isometric mapping (Isomap) method, obtains only slightly lower OCAs.     

Mainstreaming local perceptions of hurricane risk into policymaking: A case study of community GIS in Mexico

This article suggests a framework for incorporating and communicating local perceptions of hurricane risk into policymaking through a case study conducted at El Zapotito commune in the State of Veracruz, Mexico. The authors constructed a geographical information system (GIS)-based model to quantify and spatially assess specific household-level vulnerabilities from information generated through interviews. This research developed a household vulnerability index applied to a participatory GIS to map vulnerability to hurricane hazard. The results indicate that infrastructural weaknesses are the most important factor contributing to vulnerability, explaining on their own 72.2% of the variation in the vulnerability patterns. These findings are corroborated by a vulnerability and capacity assessment (VCA), which shows that the community lacks strategies to cope with unsafe housing. It is suggested that linking community participation with modern techniques to analyse risk can empower communities and mobilise their capacities to address very specific vulnerabilities.