Positive and negative terrains on northern Shaanxi Loess Plateau

The Loess positive and negative terrains （P-N terrains）, which are widely distributed on the Loess Plateau, are discussed for the first time by introducing its characteristic, demarcation as well as extraction method from high-resolution Digital Elevation Models. Using 5 m-resolution DEMs as original test data, P-N terrains of 48 geomorphological units in different parts of Shaanxi Loess Plateau are extracted accurately. Then six indicators for depicting the geomorphologic landscape and spatial configuration characteristic of P-N terrains are proposed. The spatial distribution rules of these indicators and the relationship between the P-N terrains and Loess relief are discussed for further understanding of Loess landforms. Finally, with the integration of P-N terrains and traditional terrain indices, a series of un-supervised classification methods are applied to make a proper landform classification in northern Shaanxi. Results show that P-N terrains are an effect clue to reveal energy and substance distribution rules on the Loess Plateau. A continuous change of P-N terrains from south to north in Shaanxi Loess Plateau shows an obvious spatial difference of Loess land-forms and the positive terrain area only accounted for 60.5% in this region. The P-N terrains participant landform classification method increases validity of the result, especially in the Loess tableland, Loess tableland-ridge and the Loess low-hill area. This research is significant on the study of Loess landforms with the Digital Terrains Analysis methods.

Quantifying spatial scale of positive and negative terrains pattern at watershed-scale:Case in soil and water conservation region on Loess Plateau

The positive and negative terrains(P-N terrains) widely distributed across China's Loess Plateau constitute the dual structure characteristic of loess landforms. Analysis of loess P-N terrains at the watershed scale can serve to elucidate the structural characteristics and spatial patterns of P-N terrains, which benefits a better understanding of watershed evolution and suitable scales for loess landform research. The Two-Term Local Quadrat Variance Analysis(TTLQV) is calculated as the average of the square of the difference between the block totals of all possible adjacent pairs of block size, which can be used to detect both the scale and the intensity of landscape patches(e.g., plant/animal communities and gully networks). In this study, we determined the latitudinal and longitudinal spatial scale of P-N terrain patterns within 104 uniformly distributed watersheds in our target soil and water conservation region. The results showed that TTLQV is very effective for examining the scale of P-N terrain patterns. There were apparently three types of P-N terrain pattern in latitudinal direction(i.e., Loess Tableland type, Loess Hill type, and Transitional Form between Sand and Loess type), whereas there were both lower and higher values for P-N terrain pattern scales in all loess landforms in the longitudinal direction. The P-N terrain pattern alsoclearly presented anisotropy, suggesting that gully networks in the main direction were well-developed while others were relatively undeveloped. In addition, the relationships between the first scales and controlling factors(i.e., gully density, nibble degree, watershed area, mean watershed slope, NDVI, precipitation, loess thickness, and loess landforms) revealed that the first scales are primarily controlled by watershed area and loess landforms. This may indicate that the current spatial pattern of P-N terrains is characterized by internal force. In selecting suitable study areas in China' Loess Plateau, it is crucial to understand four control variables: the spatial scale of the P-N terrain pattern, the watershed area, the main direction of the watershed, and the loess landforms.

Simulation on slope uncertainty derived from DEMs at different resolution levels:a case study in the Loess Plateau

Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as (0.00158+0.031S-0.0325)X-0.0045S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.

Characteristics and influencing factors of proximity distance index on the northern Shaanxi Loess Plateau in China

Topographic feature points and lines are the framework of topography,and their spatial distance relationship is an breakthrough in the study of topographical geometry,internal structure and development level.Proximity distance(PD)is an indicator to describe the distance between the gully source point(GSP)and the watershed boundary.In the upstream catchment area,PDs can be expressed by the streamline proximity distance(SPD),as well as by the horizontal proximity distance(HPD)and the vertical proximity distance(VPD)in the horizontal and vertical dimensions,respectively.The series of indicators(e.g.,SPD,HPD and VPD)are important for quantifying the geomorphological development process of a loess basin because of the headward erosion of loess gullies.In this study,the digital elevation model data with 5 m resolution and a digital topographic analysis method are used for the statistical analyses of the SPD,VPD and HPD in 50 sample areas of 6 geomorphic types in the Loess Plateau of northern Shaanxi.The spatial characteristics and the influencing factors are also analysed.Results show that:1)Central tendencies for the HPDs and the VPDs for the whole study area and the six typical loess landforms are evident.2)Spatial patterns of the HPDs and the VPDs exhibit evident trends and zonal distributions over the whole study area.3)The HPDs have a strong positive correlation with gully density(GD)and hypsometric integral.The VPDs also correlates with GD to an extent.Vegetation cover,mean annual precipitation and loess thickness have stronger effects on the VPD than on the HPD.

Comparison of Different Generation Mechanisms of Free Convection between Two Stations on the Tibetan Plateau

Based on high-quality data from eddy covariance measurements at the Qomolangma Monitoring and Research Station for Atmosphere and Environment（QOMS） and the Southeast Tibet Monitoring and Research Station for Environment（SETS）,near-ground free convection conditions（FCCs） and their characteristics are investigated. At QOMS, strong thermal effects accompanied by lower wind speeds can easily trigger the occurrence of FCCs. The change of circulation from prevailing katabatic glacier winds to prevailing upslope winds and the oscillation of upslope winds due to cloud cover are the two main causes of decreases in wind speed at QOMS. The analysis of results from SETS shows that the most important trigger mechanism of FCCs is strong solar heating. Turbulence structural analysis using wavelet transform indicates that lowerfrequency turbulence near the ground emerges from the detected FCCs both at QOMS and at SETS. It should be noted that the heterogeneous underlying surface at SETS creates large-scale turbulence during periods without the occurrence of FCCs. Regarding datasets of all seasons, the distribution of FCCs presents different characteristics during monsoonal and non-monsoonal periods.

复杂区域地形条件下台地地震动放大效应研究

针对不规则地形地震动放大效应的相关规定大多以孤立地形为对象,但山区地形常以群山形式存在,相邻地形会影响地震波传播,从而改变地表运动规律。因此研究非孤立地形的地震动放大效应对山区建筑的抗震设计及提升震后灾害评估准确性具有重要意义。首先阐述了在泸定6.8级地震中磨西台地不利地段发生的典型地形放大效应。随后利用仿真手段深入探索了复杂区域地形(山脊、峡谷)对台地地震动放大系数的影响。从放大系数空间分布、加速度傅里叶谱及幅值比的角度进行量化研究,并通过大量变参分析获得复杂区域地形对台地表面的运动规律。结果表明,在某些情况下《抗规》低估了台地地形效应,放大系数建议值难以保证结构“大震不倒”,需进行调整和细化。此外,相邻山脊和峡谷对台地表面均有明显影响,不应被忽略,因此建议相关规范增加调整系数来考虑相邻地形之间相互影响。

基于地形梯度的青藏高原冰川分布格局及成因

目前,冰川分布与变化的影响机理还存在不确定机制。为探究地形因子对冰川分布格局的影响,本文以第6版Randolph冰川编目数据和NASADEM为数据源,运用均值变点法、分布指数和地理探测器等方法,对青藏高原冰川在地形起伏度、海拔、坡度和坡向等地形梯度上的分布格局及其与地形因子之间的响应关系进行分析。结果表明:(1)青藏高原冰川对坡向、坡度的适宜性较广,对地形起伏度、海拔的选择性较强,且在高地形起伏度、高海拔上呈现优势分布。(2)地形对冰川发育影响较大,各地形因子对冰川空间分布的影响显著不同。海拔和地形起伏度是控制冰川分布的主要因素,且交互探测结果表明二者共同作用对冰川空间分异性影响最大。(3)在海拔和地形起伏度梯度上,喜马拉雅山脉冰川优势分布范围最广,其次是喀喇昆仑山脉,其余10座山脉冰川的优势分布均呈近似正态分布,但不同山脉形态各异。

青藏高原东坡两次暴雨的MCS演变及机理对比分析

受MCS长时间影响下的暴雨天气在复杂地形区容易造成山洪等严重灾害,研究其特征及成因有助于更好地认识和防御类似的灾害天气。利用多源气象观测资料对青藏高原东坡复杂地形区2020年8月10—11日(过程1)和2021年8月4—5日(过程2)两次暴雨过程的降水特征和中尺度对流系统(MCS)演变特征及形成机理进行对比分析,结果表明:(1)两次过程均为弱天气尺度系统影响下的暖区暴雨天气过程,强降水落区均位于罗纯山脉西侧的平坝河谷地带,地形对强降水落区的影响十分明显;相较过程2,过程1降水强度更大、范围更广且降水落区更集中。(2)造成两次暴雨的MCS均在雅安西部的高海拔迎风坡初生,并在罗纯山西侧维持发展,但过程1的MCS尺度和强度更大、维持时间更长。(3)过程1的强降水主要由一尺度更大的对流性(积状云为主)MCS稳定少动造成,过程2则分别为两个相继发展的混合性(积云-层云混合)MCS经过同一地区造成。(4)两次过程中的MCS维持机制不同,过程1的主要机制为罗纯山地形强迫抬升作用下不断形成的深对流单体与原MCS_1A合并,使其长时间维持在罗纯山西侧,形成准静止后向建立型MCS回波带,同时地形对冷池出流的阻挡作用以及对暖湿气流的绕流作用也在一定程度上使得MCS_1A稳定少动。而过程2的MCS维持的主要机制为高海拔迎风坡地形反馈作用。

青藏高原东侧复杂地形区极端降水研究进展

青藏高原东侧地形地貌多变,海拔高度起伏剧烈,陡峭而复杂地形下极端降水带来的气象灾害与地质次生灾害直接威胁着高原与下游地区,且这种独特的地形与地理位置,为极端降水的研究带来了巨大挑战。围绕青藏高原东侧复杂地形区极端降水,对近10 a降水数据观测分析新方法、极端降水气候演变特征和协同机制、云-降水物理特征及预报模拟和气候预估等方面取得的新进展进行了回顾,并就高原复杂地形区极端降水研究今后值得关注和思考的科学问题,从机器学习方法与多源降水数据结合以及高原地区降水资料的适用性研究、极端降水的气候变化特征与大气环流异常的机理研究、高原地区的云宏观特征和云微物理特征研究、气候模式历史模拟性能的评估及对未来极端降水模拟的预估研究等方面进行了展望。

基于三维地形扫描的坡沟系统侵蚀产沙监测方法对比

[目的]阐明不同算法在坡面侵蚀监测中的精度和适用性,进而为土壤侵蚀过程监测算法的选择和构建提供参考。[方法]于黄土丘陵沟壑区典型流域同一自然坡面建立5个小区进行径流冲刷试验,以TLS三维点云数据为基础,通过DEM of difference(DoD)、Cloud to Cloud(C2C)、Cloud to Mesh/Model(C2M)和Multiscale Model to Model Cloud Comparison(M3C2)等方法计算侵蚀产沙量,并分析了不同算法对于侵蚀产沙的监测差异。[结果]不确定性分析结果表明:M3C2平均不确定性最小,C2C,C2M次之,DoD最大。产沙结果表明:大流量(85,70,55 L/min)下,4种算法单场次和累计场次产沙量与实测产沙量之间有显著的线性关系(R 2>0.62,p<0.05),M3C2表现最优;小流量(40,25 L/min)下,单场计算产沙量与实测产沙量之间的线性关系不显著但累计产沙量与实测产沙量之间有显著的线性关系(R 2>0.91,p<0.05),DoD表现最优。侵蚀沉积空间分布特征表明:C2C,M3C2和DoD均能反映梁峁坡和沟谷坡侵蚀发展经历的两个阶段(快速发育和稳定发育),其中M3C2能够检测到细微的地形变化,但在TLS扫描盲区,M3C2由于在法线方向上未找到对应点会出现“空洞”。[结论]M3C2算法更适合监测复杂三维地形,但在扫描盲区仍会失效,未来应改进算法,有助于应对更加复杂和剧烈的地形变化。

基于UAV-SfM方法的黄土高原砒砂岩区侵蚀监测算法比较

[目的]为比较地形变化监测算法在黄土高原砒砂岩区的适用性。[方法]以皇甫川流域特拉沟一支沟为研究对象,采用无人机摄影测量技术获取2022年7月至2023年3月影像,结合SfM技术生成三维点云数据,比较分析[digital elevation model of difference(DoD)、cloud to cloud(C2C)、cloud to mesh(C2M)、multiscale model to model cloud comparison(M3C2)]等4种算法的侵蚀产沙监测精度,并分析点云密度变化对各方法精度的影响。[结果](1)4种常用算法在空间上都能监测到大幅度地表变化。其中,以M3C2算法的结果最优,线性拟合结果最好(R^(2)=0.953,p<0.01),且综合误差最小(MAE=0.0161 m,MRE=3.37%,RMSE=0.0194 m),C2M算法其次,DoD算法再次,而C2C算法结果最差。(2)通过比较,DoD算法仅适用于平坦区域的快速检测,坡度陡峭的区域监测侵蚀沉积量存在高估的现象。(3)M3C2和C2C算法对点云密度变化敏感,而C2M和DoD受点云密度变化影响较小。[结论]研究结果可为黄土高原砒砂岩地区基于UAV-SfM的侵蚀产沙监测方法的选择提供参考。

夏季西北干旱气候形成的数值模拟——高原地形和环流场等的影响

为了进一步检验和修改本文部分作者先前初步提出的影响夏季西北干旱气候形成的因子及如何相互作用形成西北干旱气候的物理图像，本文继续用一全球大气环流谱模式，设计了５组试验，利用ＥＣＭＷＦ的格点分析值资料，进行了数值模拟。结果表明，青藏高原隆升和环流差异是形成西北干旱气候的重要因子，已提出的西北干旱气候形成的物理图像大体是正确的。

高原地形对四川盆地西部突发性暴雨影响的数值试验

用η模式对１９９５年８月２４日四川盆地西部一次突发性暴雨进行了数值模拟和地形减半、无地形数值试验。由对数值模拟与试验的结果分析得出：（１）青藏高原地形有利于高原东麓暴雨区的扩大与强度加大。（２）高原地形对其以北的天气系统南伸和以南的天气系统北扩有阻碍作用。（３）高原地形可影响高原附近以东地区的物理特征场分布，从而影响暴雨区的位置与强度。

青藏高原复杂地形区雷达估测降水方法研究

青藏高原地形复杂,雷达波束遮挡严重,零度层亮带及以上冰相过程对降水估测的影响显著,至今为止尚没有适合于青藏高原的雷达估测降水方法。利用2008—2010年汛期青海西宁雷达和雨量站资料,在对资料进行质量控制的基础上,根据雨量计观测的总雨量与雷达估测总雨量相等的条件,建立适合于青藏高原地区各类型降水的气候Z-R关系,并利用雨量计对雷达估测的降水进行校准。结果表明,新建立的适合青藏高原地区的气候Z-R关系可以减小常规经验Z-R关系对降水的严重低估;在亮带区,应先进行亮度层亮带的订正,再用适合的Z-R关系(Z=29R1.6)估测降水;对亮带区的高反射率因子进行亮带识别和订正,并用各类型降水相应的Z-R关系估测降水,可以减小雷达估测降水的误差,提高雷达估测降水的精度;平均校准法可以避免测站稀少和单个测站随机误差大而造成的校准不稳定,进一步提高青藏高原测站稀少地区的降水估测精度。

从水汽角度对青藏高原东南侧高空探测布局的分析

水汽是大气探测最关心的要素之一。从青藏高原东南侧出发,以NCEP再分析资料为基础,利用水汽气候诊断方法结合区域地形研究了该区域的水汽分布、输送与辐合辐散特征,并讨论了探空站布局。水汽输送分布与大气可降水季节差异均表明,青藏高原东南侧是夏、秋季东亚季风和南亚季风影响的季风过渡区,也是东亚地区最主要的水汽通道之一,尤其在秋、冬、春季此通道的水汽输送更为关键。青藏高原东南侧的大气可降水量比西南侧明显要大,这与低纬高原和青藏高原南侧南凸弧形构成的地形组合有着密切关系。青藏高原东南侧地形对水汽辐合、辐散的影响具有复杂性和特殊性,既有经向、纬向差异也有高低层差异。复杂的水汽分布及输送特征需要加强水汽探测。通过对水汽探测关键区的量化研究表明,滇西北—藏东南—缅北地区、滇东—黔西地区以及滇西南地区是观测需求较为显著的区域。

典型黄土地貌类型区的地形复杂度分形研究

黄土高原地貌形态与地形复杂度自南向北有序变化,构成了举世瞩目的独特的地理景观。选择陕西省南北剖面六个典型黄土地貌样区为基本实验区,以其1∶1万栅格DEM为数据源,探讨典型黄土地貌类型区的地形复杂度分形与空间分异特征。首先提出的元分维模型方法,以计算得到的DEM元分维值作为特征指标,研究样区的地形复杂度问题。这种通过滑动窗口的扩展分维分析方法,既可以用于分析该区域不同尺度下的地形复杂度变化情况,也可以探讨区域的局部单元复杂程度及其空间分布,从而不再局限于对全区域的单一分维评价。以此为基础,进一步应用元分维谱方法,研究地貌网格单元的元分维分级分布情况。实验结果表明:以绥德和延川为代表的黄土峁状丘陵沟壑区最为复杂,以宜君和甘泉为代表的梁状丘陵沟壑区居中,而以淳化为代表的黄土塬区和以神木为代表的风沙黄土过渡区最为平缓。实验进一步证明了扩展分形方法在黄土地貌研究中的可行性。

青藏高原东侧陡峭地形对一次强降水天气过程的影响

利用高分辨率中尺度模式分析资料,研究了青藏高原东侧陡峭地形对一次暴雨天气发生发展的影响。结果显示,青藏高原地形对大气环流的动力阻挡作用形成了本次暴雨过程的水汽输送通道,青藏高原东侧陡峭地形结构造成了四川西北部和黄河上游的强水汽辐合中心,并使低层高能舌和能量锋区位于海拔较低的四川盆地,在四川盆地对流层低层建立起位势不稳定层结。青藏高原东侧陡峭地形结构引起了低层偏东气流强烈的垂直上升运动,最强的垂直上升运动出现在东西风垂直切变与陡峭地形交汇处,激发不稳定能量释放,促使强对流猛烈发展,暴雨过程中高原东侧还有一个中尺度涡旋的发生发展相伴。青藏高原东侧暴雨区最显著的热力特征是高温高湿区域仅出现在对流层低层,最显著的动力特征是强涡度柱也仅出现在对流层低层。

基于神经网络的地面坡度与其他地形定量因子关联性分析——以黄土高原丘陵沟壑区实验为例

不同的地形因子从不同侧面反映地面的起伏特征或空间变异,各因子之间所存在的相互关联、相互制约、相互影响的程度与特征,在很大程度上揭示了地形发育与空间变异的内在本质,因而是地形学研究的重要内容。他以黄土高原丘陵沟壑区的16个样本地区为实验样区,以高分辨率、高精度的1:1万比例尺DEM为基准数据,应用BP神经网络模型,探讨地面坡度与其他地形因子之间的关联性特征。实验结果表明,利用神经网络分析方法可以有效评价地形因子对地面平均坡度的关联性。该研究方法为进行地貌多定量指标的的选择和多因子之间关联性的量化提供了一种新的方法。

基于GIS的起伏地形下天文辐射分布式模型——以贵州高原为例

天文辐射是辐射计算、太阳能资源评估及其他相关研究领域重要的起始参量,由于坡度、坡向和地形之间相互遮蔽等局地地形因子的影响,使实际起伏地形下获得的天文辐射与水平面上获得的天文辐射有一定差异。确定实际起伏地形下天文辐射是比较困难的。应用数字高程模型（DEM）数据和地理信息系统（G IS）,建立起伏地形下天文辐射分布式计算模型,计算了起伏地形下贵州高原100 m×100 m分辨率天文辐射精细空间分布,分析了局地地形因子对起伏地形下天文辐射的影响。结果表明：（1）贵州高原起伏地形下天文辐射的空间分布具有明显的地域分布特征。（2）贵州高原起伏地形下天文辐射年总量平均为481.7～13 041.8 M J/m2,1月、7月天文辐射分别为0.0～1 244.7 M J/m2、0.0～1 264.8 M J/m2。（3）局地地形因子对起伏地形下天文辐射空间分布的影响随季节和纬度变化,虽然坡度、坡向和地形遮蔽对天文辐射的影响,在太阳高度角较低的1月比太阳高度角较高的7月相对较大,但因为7月水平面获得的天文辐射的强度相对较大,7月局地地形对天文辐射的影响依然显著。因此,贵州高原起伏地形对天文辐射的影响是不容忽视的。

贵州高原复杂地形下月平均日最低气温分布式模拟研究

在前人研究的基础上,对以前计算平均日最低气温的模型进行了一些改进,考虑了坡度、坡向和地形相互遮蔽作用对复杂地形下太阳总辐射的影响,基于数字高程模型(DEM)数据,研制了复杂地形下海拔高度、太阳总辐射、日照百分率为参数的月平均日最低气温的分布式模型。应用100 m×100m分辨率的DEM数据、1960—2000年贵州省及周边102个气象站常规气象要素观测资料以及NOAA-AVHRR观测资料、10个气象站的太阳辐射量资料,计算了贵州高原复杂地形下各月及年平均日最低气温空间分布。结果表明:(1)局地地形因子对贵州地区月平均日最低气温的影响较大,月平均日最低气温纬向分布不明显。贵州高原复杂地形下年平均日最低气温大部分地区介于7.5～12.4℃之间,1月平均日最低气温大部分介于-0.6～4.1℃之间,7月平均日最低气温大部分介于15.6～21.3℃之间。(2)月平均日最低气温随海拔高度的增加而降低。南坡随坡度的增大而升高;北坡随坡度的增大而降低。在坡向影响上,1～5月、10～12月偏北坡月平均日最低气温偏低,偏南坡月平均日最低气温偏高;7～8月因太阳高度较高,因此出现相反的情况,北坡高于南坡。