共查询到17条相似文献，搜索用时 265 毫秒
1.
复杂山区小流域径流模拟影响因素分析 总被引：5，自引：1，他引：4
为探讨子流域划分与DEM分辨率对于地形和地表状况比较复杂的山区小流域径流模拟的影响,利用分布式水文模型SWAT(Soil and Water Assessment Tool)对复杂山区小流域进行径流模拟,从不同的子流域划分条件下分析了子流域划分对径流模拟的影响及其变化趋势.然后通过对原有的DEM(Digital Elevation Model)进行重采样生成不同格网大小的DEM作为模型输入,研究不同DEM分辨率对复杂山区小流域径流模拟的影响.研究表明:(1)存在一个比较合理的子流域划分方案使径流深比较稳定;(2)存在一个合适的DEM分辨率使模拟得到的径流深比较稳定;(3)山区复杂流域环境,要求更加精细的子流域划分才能获得(1)中的稳定径流深. 相似文献
2.
3.
DEM是构建分布式水文模型的重要输入。以岷江上游为研究区,基于8种不同空间分辨率DEM构建SWAT模型,研究分析DEM空间分辨率对流域水文特征提取及径流模拟影响。研究表明,DEM空间分辨率越低,洪峰模拟精度越低,模拟流量与实测流量间的误差越大,曲线吻合度越低;DEM空间分辨率由25m降低到200m时,径流模拟误差变化不明显,而DEM空间分辨率由200m降低到3 200m时模拟误差显著增大;另外,DEM空间分辨率与径流总量的模拟精度间未表现出显著相关性。 相似文献
4.
《地下水》2021,(1)
数字高程模型(DEM)空间分辨率的精准确定,对于提高分布式水文模型输入水文信息的可靠性和有效性意义显著。文章选择北洛河流域典型区域作为研究对象,基于7种不同的DEM空间分辨率,利用ARCGIS软件,分别提取水文特征信息;在新安江模型物理参数意义研究的基础上,利用槽蓄曲线的坡度K和流量比重系数X之间的相关关系,确定参数,进行水文模拟;根据交口、状头水文站的实测数据,对模拟结果进行对比验证,结果表明:DEM空间分辨率越低,提取的水文特征信息越少;洪峰的模拟精度在分辨率200m之前减低缓慢,200m之后大幅降低。对比分析不同分辨率对水文模拟的影响,进而确定满足实际洪水预报的DEM分辨率大小。 相似文献
5.
6.
7.
TOPMODEL是目前被广泛应用的半分布式流域水文模型,它以地形为基础的特点使得DEM的空间分辨率成为影响模型模拟结果准确性的重要参数。不同分辨率的DEM将计算出不同的地形指数ln(α/tanβ)分布,其作为TOPMODEL的地形参数直接影响着模型的模拟结果。以10 m分辨率的DEM为原始数据,生成10~1 000 m等17种分辨率的DEM,使用地形信息熵的概念,比较不同分辨率的DEM对地形信息提取的影响。假设TOPMODEL在10 m分辨率的DEM计算的流量过程线为观测值,对比了不同分辨率的DEM对流量过程线和Nash效率系数产生的变化。对于所研究的流域,150 m分辨率是建立TOPMODEL模型的最佳值,300 m分辨率是保证模型结果有效的基本要求。使用Monte Carlo方法计算TOPMODEL中参数对DEM分辨率的敏感性,指出在模型的5个参数中,只有饱和导水系数T0对DEM分辨率敏感。 相似文献
8.
DEM数据源及分辨率会影响流域特征参数的提取,进而影响水文模拟结果.将ASTER 30 m DEM、SRTM 90 m DEM及基于ASTER 30 m DEM的40 m、50 m、60 m、70 m、80 m、90 m重采样DEM作为HEC-geoHMS模型输入,提取流域特征,采用HEC-HMS模型,以西笤溪流域为研究区域,分析2011年6月和2011年8—9月的两场降雨径流过程中,DEM数据源和分辨率对水文模拟输出的影响.研究结果表明,两次径流模拟结果与实测数据拟合都较好,模型确定性系数都大于0.82,但是单峰的洪水模拟效果总体更好,基于SRTM 90 m的模型确定性系数比基于ASTER 30 m DEM、重采样90 m DEM的模型确定性系数都大.基于重采样DEM的模型确定性系数变化较大,而且与分辨率的变化呈非线性关系.在HEC-HMS的模拟中,基于ASTER 30 m DEM和基于SRTM 90 m DEM的模拟输出结果相对误差相差3%~5%,基于SRTM 90 m DEM和基于重采样90 m DEM的模拟输出结果相对误差相差2%~4%,基于重采样DEM的模拟输出结果相对误差相差最大达到了11%. 相似文献
9.
《地下水》2015,(5)
在土壤侵蚀、水文分析等诸多领域,坡度是重要的地形因子。目前坡度主要是基于DEM(数字高程模型)提取的,其精度受DEM分辨率影响。研究运用地统计学相关原理和方法,选取陕北绥德韭园沟流域为研究区,基于不同分辨率(10 m,30 m,50 m,90 m)的坡度数据,在ENVI环境下通过IDL编程构建不同分辨率坡度变异函数,通过独立结构模型(ISM,Independent Structures Model)对坡度数据的变异函数进行模拟和分析,给出DEM分辨率变化过程中坡度变化的机理性解释。研究表明,较高频的坡度信息层受分辨率的影响较大,其信息的损失是坡度随分辨衰减的主要原因。 相似文献
10.
11.
地形特征(如高程和坡度)和水文特征(如河流长度和河流坡度)是分布式流域水文水质模型的基础输入参数,用于量化描述模型模拟流域的自然特征。这些特征参数的准确性直接影响水文水质过程模拟的准确性。应用数字高程模型(Digital Elevation Model,DEM)在4个不同地形的子流域研究了10种不同分辨率DEM对平均高程、流域面积、坡度、河流坡度、最长河长等参数的影响。结果表明,随着DEM分辨率降低,流域地形变缓,流域平均坡度逐渐减小;随着DEM网格分辨率的变化,子流域划分范围和河道位置也都可能发生变化,且该变化在地形起伏较小的丘陵平原地区较明显,子流域集水面积和河长进一步随之改变;河流坡度随DEM分辨率降低则呈无规则变化。从地形和水文参数两方面揭示了DEM 分辨率在分布式流域模型中的不确定性影响。 相似文献
12.
Determining the optimum cell size of digital elevation model for hydrologic application 总被引：1，自引：0，他引：1
Scale is one of the most important but unsolved issues in various scientific disciplines that deal with spatial data. The
arbitrary choice of grid cell size for contour interpolated digital elevation models (DEM) is one of the major sources of
uncertainty in the hydrologic modelling process. In this paper, an attempt was made to identify methods for determining an
optimum cell size for a contour interpolated DEM in prior to hydrologic modelling. Twenty-meter interval contour lines were
used to generate DEMs of five different resolutions, viz., 30, 45, 60, 75, and 90 m using TOPOGRID algorithm. The obtained DEMs were explored for their intrinsic quality using four
different methods, i.e., sink analysis, fractal dimension of derived stream network, entropy measurement and semivariogram
modelling. These methods were applied to determine the level artifacts (interpolation error) in DEM surface as well as derived
stream network, spatial information content and spatial variability respectively. The results indicated that a 90 m cell size
is sufficient to capture the terrain variability for subsequent hydrologic modelling in the study area. The significance of
this research work is that it provides methods which DEM users can apply to select an appropriate DEM cell size in prior to
detailed hydrologic modelling. 相似文献
13.
Digital elevation models (DEMs) are widely used in the studies related to hydrological modeling. It provides spatially distributed topographical information which helps in the extraction of stream networks. Currently, DEMs obtained through spaceborne remote sensing platforms are increasingly utilized for stream network extraction. However, it is necessary to understand the quality of the derived products and their related issues. Therefore, a comparative study based on stream network extraction in geographical information system (GIS) is performed on such DEMs for two different terrains. Performance metrics such as root mean square error (RMSE), mean absolute error (MAE), standard deviation (SD) of error, correctness index (CI), and figure of merit (FM) are used for the DEM evaluation. The DEMs with finer spatial resolution performed better than coarser resolutions in all the performance indices. It is also observed that the derived stream network from the DEMs having same 30-m spatial resolution (ASTER and CartoDEM) has varying degree of errors. The positional errors of the streams are found to be less for the regions with steep slopes compared to flat terrain. 相似文献
14.
基于坡地水文学、GIS空间分析原理、流域侵蚀地貌学等理论方法,对小流域坡长提取及不同坡长计算方法进行对比研究.并基于格网DEM分析目前国内外坡长的不同算法,来揭示坡长在小流域的空间分布规律. 相似文献
15.
DEM分辨率对分布式水沙过程模拟具有重要影响,然而,产生影响的内部机制尚不明确。改进水沙物理模型CASC2D-SED的结构,将坡度由DEM在模型内部直接提取改为由模块单独计算,并将坡度设计为模型的独立输入参数,通过单独改变坡度参数来研究坡度对水沙模拟DEM尺度效应的影响。基于改进的CASC2D-SED模型,以内蒙古准格尔旗沙圪堵镇附近的一个小流域为研究对象,以无人机航测的1m分辨率DEM数据、野外实测与室内实验获得的土壤特性数据、土地利用数据和降雨数据为基础,采用3种水沙模拟方案进行多象元尺度的水沙过程模拟,进而探索水沙过程模拟的DEM尺度效应及发生机制。研究表明:⑴在4~20m GRID分辨率区间模拟的径流量位于323.18m3和411.43m3之间,波动不大;⑵2~20m GRID分辨率区间内,模拟的侵蚀流量在3.43m3和65.61m3间变化,波动很大;(3)坡度和径流路径是水文过程模拟DEM尺度效应的两个对立影响因子,是水文过程模拟DEM尺度效应不明显的主要原因;⑷DEM尺度效应对侵蚀输沙具有重要影响,地形坡度是侵蚀输沙DEM尺度效应的主要控制因子;⑸地形坡度随DEM分辨率降低而发生的空间上的波动变化是侵蚀输沙量随DEM分辨率降低而波动变化的原因。 相似文献
16.
Automated extraction of watershed boundary and drainage network from SRTM and comparison with Survey of India toposheet 总被引：1，自引：0，他引：1
The recent development of digital representation has stimulated the development of automatic extraction of topographic and hydrologic information from digital elevation model input, using geographic information system (GIS) and hydrologic models that integrate multiple databases within a minimal time. The objective of this investigation is to compare the drainage extracted from Shuttle Radar Topography Mission (SRTM) data with the drainage digitized from topographic data (1:50,000) and also to draw attention to the functions of an add-on tool in ArcGIS 9.2 (Arc Hydro v.2) of Kuttiyadi River basin. The analysis reveals that the watershed extracted from the SRTM digital elevation model (DEM) (90 m resolution) is having an area of 668 km2 and that from toposheet is 676 km2. The river mouth in the drainage network from the SRTM DEM is found to be shifted to the northern side from where it actually exists. The drainage network from SRTM DEM at stream threshold 15 (0.0002 % of maximum flow accumulation) is delivering best results than the other threshold value in comparison with the drainage pattern derived from toposheets. The study reveals the importance, reliability, and quaintness of drainage network and watershed derived from the SRTM using the Arc Hydro Tool, an extension for Environmental Systems Research Institute ArcGIS. The advantage of the Arc Hydro Tool is that it would help a novice with little GIS knowledge to run the model to obtain watershed and drainage network. 相似文献
17.
GIS and ANN-based spatial prediction of DOC in river networks: a case study in Dongjiang, Southern China 总被引：1，自引：0，他引：1
Yingchun Fu Yaolong Zhao Yongrui Zhang Taisheng Guo Ziwei He Jingyi Chen 《Environmental Earth Sciences》2013,68(5):1495-1505
This paper investigates the use of an artificial neural network (ANN) model to predict dissolved organic carbon (DOC) in a river network and evaluates the impacts of watershed characteristics on stream DOC. Samples and relevant environmental variables were obtained from field sampling at 28 hydrological response units (HRUs) and a MODIS/SRTM DEM satellite image. HRUs can provide reliable spatial interpolation for filling data gaps and incorporate potential spatial correlation among observations in each ANN neuron. The process and results of neural network modeling were assessed by deterministic and statistical methods and spatial regression kriging. The spatial prediction results show that ANN, using improved back propagation algorithms of 7-15-1 architecture, was the optimal network, by which predictions maintained most of the original spatial variation and eliminated smoothing effects of RK. The sum of the relative contributions of four sensitive variables, including soil organic carbon density, geographic longitude, surface runoff and Chl a in river water, was >75 %. A minor prediction error of ~6 % was found in HRUs of open shrublands, but HRUs of urban and croplands had an error of 24–30 %. This pattern exemplifies anthropogenic impacts in urban areas on stream DOC and agricultural activities in croplands. The usefulness of ANN modeling-based GIS in this study is demonstrated by depiction of spatial variation of stream DOC and indicates the benefits of understanding sensitive factors for watershed impact assessments. 相似文献