基于DEM的清水河分布式水文模型

对于以冰雪融水和雨水混合补给为主的西北山区流域,需要结合山区特点建立分布式水文模型。通过取塔里木河流域中的清水河水系为研究区域,采用300 m×300 m DEM数据进行流域河网水系提取,同时用DEM数据对参数进行分布式异化,建立冰雪融水与降雨相结合的分布式水文模型。分析模拟结果表明:夏季模拟径流主峰值与实测径流值较为接近,而冬春季节两者之间的差别较大,反映了西北山区流域冰雪融水和雨水混合补给为主的特点;进而开拓塔里木河区域应用该类模型的可行性。     

基于DEM的分布式水文模型构建方法

基于 DEM的分布式水文模型是现代水文学同高科技 (如计算机技术、 3S技术等 )相结合的产物 ,是研究变化环境下水文循环与水资源演化规律的理想工具 ,代表了水文模型的最新发展方向。从 DEM的特性出发 ,本文探讨并总结了分布式水文模型的特点、建模思路和模型基本结构框图。在流域离散化方面 ,重点介绍了分布式水文模型常用的三种单元划分方法 ;最后 ,针对分布式水文模型构建问题 ,从“输入模块”、“单元水文模型”、“河网汇流模型”三方面 ,阐述了分布式水文模型微结构构建方法。     

基于DEM的沟谷系统提取算法综述

该文对近20多a来基于栅格数字高程模型(DEM)提取沟谷系统的方法与技术进行了综述。将沟谷系统提取方法归纳为三类：局部方法、全局方法、局部与全局相结合的方法，比较了各类方法的优缺点。分别综述与比较了提取沟谷系统的三个主要问题——水流路径的确定、洼地的处理以及累计汇流阈值的确定的解决算法以及存在的不足。笔者认为要使这方面的研究走向真正的实用化，必须借助其它的信息，利用人工智能和模式识别等多种手段来实现自动提取。     

基于气温变化的简易融雪模型研究

在干旱区,冰雪融化是水资源形成的主要来源,为此,积雪资源的形成、转化与利用是新疆水资源开发利用研究的重要内容,而水文模型是水资源形成与转化量确定的关键途径。以中国科学院天山积雪站野外试验区为研究基地,以气象数据为自变量,以融雪量为因变量,研究了基于气温变化的融雪模型,并对所建单因素简易模型进行了率定和验证,同时分析了试验区多年融雪变化规律以及融雪对气温的响应过程。结果表明：在一定的低温状态下,冬季仍有融雪发生,在天山山区本项目研究流域积雪消融的日平均气温临界值约为-7℃,当日平均气温低于-7℃时,融雪基本处于暂停状态,体现了干旱区融雪特征。在模型方面,基于气温构建的单因素简易融雪模型在模拟山区融雪量时呈现出良好的代表性,在率定期（2016—2020年）,融雪量观测值与模拟值间的相关性参数偏差、平均绝对误差、均方根误差、纳什效率系数和决定分别为-0.037、0.367、0.482、0.870和0.876;而验证期的值分别为-0.210、0.292、0.577、0.845和0.811。验证期的模拟结果和相关性系数显示,该模型的模拟值与观测值具有良好的一致性和稳定性,其优点是通过易获取的气象...     

基于DEM的分布式水文模型在大尺度流域应用研究

本文选取空间大尺度黄河河源区流域为研究对象,利用分布式水文模型进行径流量模拟,采用1976～1985年唐乃亥水文站逐年、月实测径流资料进行参数率定,确定模型的基本参数,得到了较好的模拟效果。模拟结果表明气候变化是引起黄河河源区径流变化的主要原因。在80～90年代的20年间,黄河河源区由气候变化引起径流减少62.11亿m3,占径流变化总量的108.72%,由土地覆被变化引起径流增加5.73亿m3,增加量占径流变化总量的10.03%。     

一种基于TIN的DEM表面插值模型

针对目前基于TIN的DEM存在的表面模型单一、表面不光滑、达不到更高的精度等问题,该文利用二元泰勒公式、顶点法向量、插值函数等,提出一种基于TIN的DEM表面插值模型,并利用数学曲面评估模型精度。结果表明,该模型具有较好的光滑效果和精度,扩展了基于TIN的DEM表达方式,为DEM的应用提供了更多的选择。     

新疆北疆地区融雪洪水灾害预警模型的建立与验证

结合新疆北疆地区春季融雪洪水的特点以及当地的经济、社会现状,将影响新疆春季融雪洪水灾害大小的主要因素划分为自然、经济、人口、防洪设施贡献四大类因子,对这四大类因子进一步细化,经过量化处理成为相应的指数,综合各类指数,构建出度量融雪洪水灾害大小的预警指数模型.采用呼图壁县军塘湖流域历史洪水灾害资料对该预警指数模型进行验证,得到较好的效果.通过对导致预警产生偏差的影响因素进行分析表明,由于经济因子指数的估计受主观影响较强,该模型无法验证北疆地区所有情况.随着监测的不断深入,并与积雪遥感监测相结合可以进一步提高模型的预测精度.总之,该预警模型的建立有助于新疆春季积雪的监测和评估,可以有效减少春季洪水损失,保护当地人民生命财产安全,为融雪洪水的预警提供决策依据,具有显著的社会效益和经济效益.     

基于DEM的并行可照时间模型研究

可照时间是影响太阳辐射计算的重要参数。随着研究区域的增大、DEM分辨率与精度的不断提高,亟须借助并行技术满足用户对可照时间模拟的时间响应需求。该文针对栅格数据提出了一种通用有效的数据划分及结果融合策略,首次提出并行可照时间计算模型。实验表明该模型具有较好的可移植性,当处理节点数为64时,最优加速比高达16,在计算时间及加速比方面体现出优势。基于黄土高原地区90m×90m分辨率SRTM数据,计算了四季及全年可照时间,分析了可照时间的空间分布特征,表现为季节不对称性及非地带性分布规律。     

基于DEM的地形单元多样性指数及其算法

在阐述地形信息表达研究进展的基础上,提出基于DEM地形单元多样性指数的概念和算法。地形单元多样性指数综合了高程、坡度、坡位、坡向、汇流量和水域信息等要素。其算法集成地形位置指数和地形湿度指数算法,采用图层叠加分析,设定分类、分级指标,进行重分类组合,划分地形单元类型,利用窗口分析法计算地形单元多样性指数。以四川省为试验区,利用精度为100 m的DEM数据和水域分布数据进行模拟计算,地形单元划分为13种典型类型,统计窗口半径设为900 m,计算出的多样性指数值小于0.5的区域仅占总面积的11%,大于0.75的区域达57%,符合实验区地形特征,并对算法进行了可行性分析和验证。结果表明,该算法提取的地形单元多样性指数可以有效反映地表形态的多样性特征及其变化。该研究结果为进一步探讨基于DEM地表形态信息的概念体系,以及从微观到宏观的地形信息空间分析研究创造了条件。     

无人机航摄生成DEM的高程点快速提取算法

无人机航空摄影技术在近年来得到了迅速的发展,无人机具有起降方便,分辨率高,响应速度快的特点,在抢险救灾,地质灾害监测等方面发挥了重要作用。无人机航空摄影生成的地形图中的高程点提取是地形图制作的重要步骤,本文提出了一种自适应的地形图高程点提取算法,相对于传统的算法,具有精确度高,计算简单,实用性强等特点。该算法的基础是数学形态学中的图像膨胀算法。本文将此算法用于陕西省丹凤县和紫阳县的无人机航摄生成的地形图中,提取了符合要求的高程点。结果表明,提取的高程点完全满足了地形图的要求,说明了该算法的准确性和实用性。     

Influence of survey strategy and interpolation model on DEM quality

Accurate characterisation of morphology is critical to many studies in the field of geomorphology, particularly those dealing with changes over time. Digital elevation models (DEMs) are commonly used to represent morphology in three dimensions. The quality of the DEM is largely a function of the accuracy of individual survey points, field survey strategy, and the method of interpolation. Recommendations concerning field survey strategy and appropriate methods of interpolation are currently lacking. Furthermore, the majority of studies to date consider error to be uniform across a surface. This study quantifies survey strategy and interpolation error for a gravel bar on the River Nent, Blagill, Cumbria, UK. Five sampling strategies were compared: (i) cross section; (ii) bar outline only; (iii) bar and chute outline; (iv) bar and chute outline with spot heights; and (v) aerial LiDAR equivalent, derived from degraded terrestrial laser scan (TLS) data. Digital Elevation Models were then produced using five different common interpolation algorithms. Each resultant DEM was differentiated from a terrestrial laser scan of the gravel bar surface in order to define the spatial distribution of vertical and volumetric error. Overall triangulation with linear interpolation (TIN) or point kriging appeared to provide the best interpolators for the bar surface. Lowest error on average was found for the simulated aerial LiDAR survey strategy, regardless of interpolation technique. However, comparably low errors were also found for the bar-chute-spot sampling strategy when TINs or point kriging was used as the interpolator. The magnitude of the errors between survey strategy exceeded those found between interpolation technique for a specific survey strategy. Strong relationships between local surface topographic variation (as defined by the standard deviation of vertical elevations in a 0.2-m diameter moving window), and DEM errors were also found, with much greater errors found at slope breaks such as bank edges. A series of curves are presented that demonstrate these relationships for each interpolation and survey strategy. The simulated aerial LiDAR data set displayed the lowest errors across the flatter surfaces; however, sharp slope breaks are better modelled by the morphologically based survey strategy. The curves presented have general application to spatially distributed data of river beds and may be applied to standard deviation grids to predict spatial error within a surface, depending upon sampling strategy and interpolation algorithm.     

基于DEM的黄土塬形态特征分析及发育阶段划分

基于DEM的地形分析方法已被广泛应用于地貌学研究中,但当前研究以定性或半定量居多,利用各类参数对大面积区域的量化分析研究较少。本文以黄土高原为研究区,利用GIS 及DEM地形分析方法,将坡度小于15°的正地貌提取出来,然后利用坡度与起伏度结合分析得到黄土塬顶面,两者相减得到黄土塬坡面,最终提取黄土塬1106 个;选取黄土塬核心区的106 个样本,分别计算坡面平均坡度、顶面长短轴比、沟壑密度、顶面与底面比、地面裂度5 个指标,然后对其分别进行等级划分,计算5 个指标的几何平均值,作为评价研究区黄土塬相对年龄的指标;对组合指标（I）进行分析后,将其划分为3 级,分别为早期（I<1.74）、中期（1.74≤I<2.12）和晚期（I≥2.12）。研究结果显示,在黄土塬的不同发育阶段,各个形态指标整体上存在差异,各子类型内部也存在发育先后不一致的情况。在对黄土塬各子类型计算发育阶段指数之后发现,从黄土塬、黄土残塬到黄土梁塬,I值逐渐增大。形态指标的有序变化与前人研究所得的黄土地貌发育过程十分一致。     

Effects of DEM resolution and source on soil erosion modelling: a case study using the WEPP model

Digital elevation models (DEMs) vary in resolution and accuracy by the production method. DEMs with different resolutions and accuracies can generate varied topographic and hydrological features, which can in turn affect predictions by soil erosion models, such as the WEPP (Water Erosion Prediction Project) model. This study investigates the effects of DEMs on deriving topographic and hydrological attributes, and on predicting watershed erosion using WEPP v2006.5. Six DEMs at three resolutions from three sources were prepared for two small forested watersheds located in northern Idaho, USA. These DEMs were used to calculate topographic and hydrological parameters that served as inputs to WEPP. The model results of sediment yields and runoffs were compared with field observations. For both watersheds, DEMs with different resolutions and sources generated varied watershed shapes and structures, which in turn led to different extracted hill slope and channel lengths and gradients, and produced substantially different erosion predictions by WEPP.     

基于DEM-NDVI的高山植被带定量刻划

根据不同高山植被类型具有不同归一化植被指数响应的特点,通过对NDVI的分析来定量刻划高山植被带的海拔分布。首先,利用DEM、NDVI构建DEM-NDVI散点分布图;然后,结合地面调查资料与WorldView-2高分遥感影像对DEM-NDVI散点分布图进行统计回归分析;最后,利用分析结果定量刻划高山植被垂直分带结构。将该方法应用于四川卧龙大熊猫保护区的卧龙关沟,结果表明：① NDVI随海拔升高而呈“Z”字形变化;② DEM-NDVI散点图比样本点DEM-NDVI分布图能更完全地表达高山植被NDVI随高程变化的特征;③ 卧龙关沟东北坡高山植被带海拔高度为3255~4415 m,西南坡高山植被带海拔高度为3193~4473 m,与地面调查得到的区域代表植被的分布高度基本一致。     

基于SRTM DEM的祁连山自然保护区地形特征研究

基于研究区的SRTM DEM模型,应用ArcGIS10.5空间分析模块及Excel、SPSS数据统计分析功能,采用均值变点分析法确定地形起伏度的邻域分析最佳统计单元;提取了研究区高程、地形起伏度、地形坡度、地表粗糙度和地表切割度5个地形因子,以分析研究区的地形特征。结果表明:研究区地形起伏度最佳统计单元为11像元×11像元(0.98km²),地形起伏度为0～1 216 m。研究区包含13种地貌类型,87.28%的区域为中海拔,中海拔平原、台地、丘陵为主要地貌类型。走廊南山、冷龙岭、乌鞘岭和龙首山地平行分布,台地、丘陵穿插其中,地形复杂。研究结果为进一步探索自然保护区的生态保护、开发利用等具体问题提供了基础数据支持。     

基于DEM的黄河流域天文辐射空间分布

Based on the developed distributed model for calculating astronomical solar radiation (ASR), monthly ASR with a resolution of 1 km× 1 km for the rugged terrains of Yellow River Basin was calculated, with DEM data as the general characterization of terrain. This model gives an all-sided consideration on factors that influence the ASR. Results suggest that (1) Annual ASR has a progressive decrease trend from south to north; (2) the magnitude order of seasonal ASR is: summer＞spring＞autumn＞winter; (3) topographical factors have robust effect on the spatial distribution of ASR, particularly in winter when a lower sun elevation angle exists; (4) the ASR of slopes with a sunny exposure is generally 2 or 3 times that of slopes with a shading exposure and the extreme difference of ASR for different terrains is over 10 times in January; (5) the spatial differences of ASR are relatively small in summer when a higher sun elevation angle exists and the extremedifference of ASR for different terrains is only 16% in July; and (6) the sequence of topographical influence strength is: winter＞autumn＞spring＞summer.     

Uncertainty modeling and analysis of surface area calculation based on a regular grid digital elevation model (DEM)

In the field of digital terrain analysis (DTA), the principle and method of uncertainty in surface area calculation (SAC) have not been deeply developed and need to be further studied. This paper considers the uncertainty of data sources from the digital elevation model (DEM) and SAC in DTA to perform the following investigations: (a) truncation error (TE) modeling and analysis, (b) modeling and analysis of SAC propagation error (PE) by using Monte-Carlo simulation techniques and spatial autocorrelation error to simulate DEM uncertainty. The simulation experiments show that (a) without the introduction of the DEM error, higher DEM resolution and lower terrain complexity lead to smaller TE and absolute error (AE); (b) with the introduction of the DEM error, the DEM resolution and terrain complexity influence the AE and standard deviation (SD) of the SAC, but the trends by which the two values change may be not consistent; and (c) the spatial distribution of the introduced random error determines the size and degree of the deviation between the calculated result and the true value of the surface area. This study provides insights regarding the principle and method of uncertainty in SACs in geographic information science (GIScience) and provides guidance to quantify SAC uncertainty.     

Simulation of astronomical solar radiation over Yellow River Basin based on DEM

Based on the developed distributed model for calculating astronomical solar radiation (ASR), monthly ASR with a resolution of 1 km×1 km for the rugged terrains of Yellow River Basin was calculated, with DEM data as the general characterization of terrain. This model gives an all-sided consideration on factors that influence the ASR. Results suggest that (1) Annual ASR has a progressive decrease trend from south to north; (2) the magnitude order of seasonal ASR is: summer>spring>autumn>winter; (3) topographical factors have robust effect on the spatial distribution of ASR, particularly in winter when a lower sun elevation angle exists; (4) the ASR of slopes with a sunny exposure is generally 2 or 3 times that of slopes with a shading exposure and the extreme difference of ASR for different terrains is over 10 times in January; (5) the spatial differences of ASR are relatively small in summer when a higher sun elevation angle exists and the extreme difference of ASR for different terrains is only 16% in July; and (6) the sequence of topographical influence strength is: winter>autumn>spring>summer.