Runoff reduction due to environmental changes in the Sanchuanhe river basin

Recently, runoff in many river basins in China has been decreasing. Therefore, the role that climate change and human activities are playing in this decrease is currently of interest. In this study, we evaluated an assessment method that was designed to quantitatively separate the effects of climate change and human activities on runoff in river basins. Specifically, we calibrated the SIMHYD rainfall runoff model using naturally recorded hydro-meteorologic data pertaining to the Sanchuanhe River basin and then determined the effects of climate change and human activities on runoff by comparing the estimated natural runoff that occurred during the period in which humans disturbed the basin to the runoff that occurred during the period prior to disturbance by humans. The results of this study revealed that the S1MHYD rainfall runoff model performs well for estimating monthly discharge. In addition, we found that absolute runoff reductions have increased in response to human activities and climate change, with average reductions of 70.1% and 29.9% in total runoff being caused by human activities and climate change, respectively. Taken together, the results of this study indicate that human activities are the primary cause of runoff reduction in the Sanchuanhe River basin.     

Exploring the sensitivity of coastal inundation modelling to DEM vertical error

As sea level is projected to rise throughout the twenty-first century due to climate change, there is a need to ensure that sea level rise (SLR) models accurately and defensibly represent future flood inundation levels to allow for effective coastal zone management. Digital elevation models (DEMs) are integral to SLR modelling, but are subject to error, including in their vertical resolution. Error in DEMs leads to uncertainty in the output of SLR inundation models, which if not considered, may result in poor coastal management decisions. However, DEM error is not usually described in detail by DEM suppliers; commonly only the RMSE is reported. This research explores the impact of stated vertical error in delineating zones of inundation in two locations along the Devon, United Kingdom, coastline (Exe and Otter Estuaries). We explore the consequences of needing to make assumptions about the distribution of error in the absence of detailed error data using a 1 m, publically available composite DEM with a maximum RMSE of 0.15 m, typical of recent LiDAR-derived DEMs. We compare uncertainty using two methods (i) the NOAA inundation uncertainty mapping method which assumes a normal distribution of error and (ii) a hydrologically correct bathtub method where the DEM is uniformly perturbed between the upper and lower bounds of a 95% linear error in 500 Monte Carlo Simulations (HBM+MCS). The NOAA method produced a broader zone of uncertainty (an increase of 134.9% on the HBM+MCS method), which is particularly evident in the flatter topography of the upper estuaries. The HBM+MCS method generates a narrower band of uncertainty for these flatter areas, but very similar extents where shorelines are steeper. The differences in inundation extents produced by the methods relate to a number of underpinning assumptions, and particularly, how the stated RMSE is interpreted and used to represent error in a practical sense. Unlike the NOAA method, the HBM+MCS model is computationally intensive, depending on the areas under consideration and the number of iterations. We therefore used the HBM+ MCS method to derive a regression relationship between elevation and inundation probability for the Exe Estuary. We then apply this to the adjacent Otter Estuary and show that it can defensibly reproduce zones of inundation uncertainty, avoiding the computationally intensive step of the HBM+MCS. The equation-derived zone of uncertainty was 112.1% larger than the HBM+MCS method, compared to the NOAA method which produced an uncertain area 423.9% larger. Each approach has advantages and disadvantages and requires value judgements to be made. Their use underscores the need for transparency in assumptions and communications of outputs. We urge DEM publishers to move beyond provision of a generalised RMSE and provide more detailed estimates of spatial error and complete metadata, including locations of ground control points and associated land cover.     

南昌地区建设用地空间扩展的广义转移概率模型建设与应用研究

对南昌地区城市发育约束因素的分析的基础上,基于非城市像元所处的城市化梯度、距离最近建成区斑块的距离、最近建成区斑块的规模、边缘像元的邻域水平等4个城市景观格局因子和道路及地形等两个社会经济和自然影响因子,构建了广义转移概率模型,并开展了相关的动态模拟研究。表明,与传统模拟方法相比,该模型具有比较理想的精度水平,模拟结果能够很好地反映南昌地区今后城市建设用地发展趋势,提出的模型手段改进设计获得了令人满意的效果,是对现行城市景观动态模拟研究工作的一个重要的方法论补充和完善。     

金塔绿洲风场与温湿场特征的数值模拟

使用美国NCAR新版MM5V3.6非静力平衡模式,采用三重嵌套的降尺度方法,模拟研究了甘肃河西走廊金塔绿洲风场与温湿场特征。结果表明:由于绿洲的存在,绿洲沙漠系统产生的次级环流对局地环流有一定影响;平流作用将沙漠中的干热空气送向绿洲,绿洲近地层会出现逆温,感热向地表输送;沙漠上由于临近绿洲的水汽平流作用,上层大气湿度比低层更大,这就是逆湿现象。     

天然裂缝影响下的花岗岩水力裂缝扩展数值模拟

水力压裂技术是成功实现干热岩资源开发利用的重要手段之一,数值模拟技术能够精准预测水力裂缝扩展。针对典型花岗岩,借助黏性单元法,分别模拟了致密花岗岩和天然裂缝存在情况下的水力裂缝扩展特征,得出以下结论:致密花岗岩的水力裂缝形态单一,天然裂缝的存在增加了压裂后裂缝的复杂性;致密花岗岩水力裂缝拓展主要分为憋压和拓展两个交替往复的阶段,当存在天然裂隙时,水力压裂过程会变得复杂;天然裂缝存在时,水力裂缝的缝长和缝宽分别为致密花岗岩的5.7倍和1.7倍;缝网的形成需要借助复杂的压裂工艺实现。研究结果可以为增强型地热系统(EGS)储层水力刺激工作提供理论支持。     

冷泉活动区气泡羽状流数值模型研究

羽状流对天然气水合物的识别起到了间接指示作用,为研究冷泉活动区气泡羽状流产生的地震响应,需建立符合实际羽状流特征的模型。为此,参考实际羽状流赋存状态,结合含气泡水体特征,在已建立模型基础上,从羽状流气泡的垂直运移规律、分布特点及羽状流外观特征上对模型进行了改进,先后获得3个羽状流模型,最后的模型Ⅲ更接近实际羽状流赋存特征。通过与实际羽状流的对比,讨论分析了模型Ⅲ的合理性,并得出结论：所建模型体现了实际羽状流气泡的本质特征,并包含了更为复杂的气泡含量变化,可用于进一步深入研究羽状流地震响应特征,也为气泡羽状流的地震识别及天然气水合物的相关研究提供了较好的数值模型。     

高频浅地层剖面技术在海底管道探测中的应用

在海底管道的探测中,为获知海管在海底的真实赋存状态,确定其埋藏深度或悬跨高度,多使用高频浅地层剖面仪等传统声学设备。但在海底斜坡、凹坑、凸起等不平整地层处,由于设备自身原理造成的地层探测界面偏移、图像失真及资料多解性问题仍困扰着工程人员。通过正演模拟的方法探究高频浅地层剖面仪在海底特殊地层处海管检测的波场传播特征,探讨资料的解释陷阱,并提出了解决方案。研究结果表明,利用浅地层剖面仪探测管道在海底的赋存状态,应将探测图像与海底地形、地貌、沉积物运移等因素结合起来综合考虑,把探测图像回归到真实海底环境中,以准确评价海底管道的安全状态。     

距离法定量评价储层地质模型的不确定性

针对目前常用的储层地质模型不确定性评价方法存在的主要问题,提出了先用距离函数计算模型之间的差异,再以差异的大小来判断不确定性大小的方法.以WZ油田西区为例,采用相控物性参数建模技术,利用顺序高斯模拟方法建立渗透率的三维模型.对各种度量差异的距离函数进行对比研究和分析,结果显示曼哈顿距离函数和欧氏距离函数能较好地刻画模型之间的差异.选用欧氏距离函数计算模型之间的差异,其原理是先计算每两个模型之间相对应的每一网格节点的渗透率值差的平方和,然后取平方根,得到一个表征各模型之间差异的矩阵.根据该矩阵可得到各个模型之间的差异程度,差异越大,不确定性就越大.最后通过对比模型过井剖面图分析结果与距离矩阵分析结果,说明了本方法的正确性,结果显示该方法能有效评价随机模拟生成的储层地质模型的不确定性.     

基于热力耦合数值模拟的膨胀土深基坑变形特性研究

膨胀土的胀缩特性、裂隙性、超固结性常对膨胀土地层中的工程建设造成不良影响,以热-力耦合数值模拟为基础对膨胀土深基坑开挖过程中的受力变形特性进行研究。首先由室内试验测定原状膨胀土的膨胀力,然后以FLAC3D热-力耦合模块模拟一环刀土样推导目标膨胀力下的膨胀系数,最后以扬州某膨胀土深基坑为例,计算上述膨胀系数下深基坑在开挖过程中的受力变形特性,并与基坑实测数据进行了对比。结果表明：（1）围护结构侧向变形轮廓线为鱼腹型,最大侧向变形位置发生在开挖面以上一定范围内,最大侧向变形值大致为（0.15%～0.30%）H;（2）立柱隆沉曲线平缓,数值大致处于（-0.04%～0.14%）H;（3）墙后地表沉降槽呈型,影响范围达到了2.5He以外,最大地表沉降值为vm=（0.05%～0.15%）H,最大地表沉降与最大围护结构侧向变形的关系约为vm=（0.33～0.56）hm;（4）土压力值均处于视土压力包络线范围以内,大致为1.07He。     

基于L-M神经网络的陡崖层状危岩失稳模式预测

明确危岩变形失稳模式是预防和治理研究的前提,但如今的传统预测方法存在成本高昂、实用性不强等缺点,尤其是在强烈地震诱发下。本文采用基于Levenberg-Marquardt法的神经网络结构,并借助三维离散元数值模拟手段,综合考虑了陡崖层状危岩的节理倾角、危岩边长、危岩高宽比、危岩堆积层数等影响变形失稳模式因素,以危岩变形失稳模式为研究对象,影响因素为切入点,建立了陡崖层状危岩变形失稳模式预测的神经网络模型。并基于由数值模拟计算得到的危岩变形失稳模式样本训练所建立的神经网络,最后分析了该预测模型的准确性。结果表明：该模型具有较好的学习和泛化能力,预测精度达到86.7%,验证了基于Levenberg-Marquardt法的神经网络预测危岩变形失稳模式的方法是有效且实际可行的。