复杂地形对长江流域太阳总辐射的影响(英文)

Global solar radiation(GSR) is the most direct source and form of global energy, and calculation of its quantity is highly complex due to influences of local topography and terrain inter-shielding. Digital elevation model(DEM) data as a representation of the complex terrain and multiplicity condition produces a series of topographic factors(e.g. slope, aspect, etc.). Based on 1 km resolution DEM data, meteorological observations and NOAA-AVHRR remote sensing data, a distributed model for the calculation of GSR over rugged terrain within the Yangtze River Basin has been developed. The overarching model permits calculation of astronomical solar radiation for rugged topography and comprises a distributed direct solar radiation model, a distributed diffuse radiation model and a distributed terrain reflectance radiation model. Using the developed model, a quantitative simulation of the GSR space distribution and visualization has been undertaken, with results subsequently analyzed with respect to locality and terrain. Analyses suggest that GSR magnitude is seasonally affected, while the degree of influence was found to increase in concurrence with increasing altitude. Moreover, GSR magnitude exhibited clear spatial variation with respect to the dominant local aspect; GSR values associated with the sunny southern slopes were significantly greater than those associated with shaded slopes. Error analysis indicates a mean absolute error of 12.983 MJm-2 and a mean relative error of 3.608%, while the results based on a site authentication procedure display an absolute error of 22.621 MJm-2 and a relative error of 4.626%.     

复杂地形下长江流域太阳总辐射的分布式模拟

利用长江流域气象站1960-2005年的观测资料(包括常规气象站点资料和辐射站点资料)、NOAA-AVHRR遥感数据(反演地表反照率),以1km×1km的数字高程模型(DEM)反映地形状况的主要数据,通过基于DEM数据的起伏地形下天文辐射模型和地形开阔度模型,分别建立了长江流域太阳直接辐射、散射辐射和地形反射辐射分布式模型,实现了长江流域太阳总辐射模拟,并对总辐射模拟结果进行了时空分布规律分析和对其受季节、纬度、地形因子(高度、坡度和坡向等)影响的局部规律分析,以及模拟结果的误差分析和站点验证分析。结果显示:太阳总辐射在季节上受影响的程度依次是春季>冬季>夏季>秋季;随着高度、坡度、纬度的增加,太阳总辐射受坡向影响的程度呈增强趋势,从坡向上看,向阳山坡(偏南坡)对太阳总辐射量明显高于背阴坡(偏北坡)。模拟的平均绝对误差为13.04177MJm^-2,相对误差平均值3.655%,用站点验证方法显示:模拟绝对误差为22.667MJm^-2,相对误差为4.867%。     

中国三种太阳辐射起始数据分布式模拟

天文辐射、干洁大气总辐射和湿洁大气总辐射是太阳辐射模拟的3种重要起始数据。依托Iqbal Model C和起伏地形下干/湿洁大气总辐射模型,实现了水平面和起伏地形下干/湿洁大气总辐射分布式模拟。以DEM数据作为地形的综合反映,结合常规气象资料,计算了水平面和起伏地形下中国1 km×1 km分辨率日天文辐射量、干洁大气总辐射量、湿洁大气总辐射量的空间分布,并对3种太阳辐射起始数据的时空分布特征做了对比分析。结果表明：3种辐射量均遵循随纬向变化的宏观分布规律;水平面干/湿洁大气总辐射量的分布体现了海拔的影响,水平面湿洁大气总辐射量的分布还体现了水汽分布的影响;起伏地形下的3种辐射量能很好的体现坡度、坡向和地形之间相互遮蔽等局部地形特征对辐射量的影响;以干/湿洁大气总辐射作为起始数据,将有助于提高太阳总辐射的模拟精度。     

基于DEM的黄河流域天文辐射空间分布

基于1 km×1 km分辨率的数字高程模型(DEM) 数据,利用建立的起伏地形下天文辐射分布式计算模型,计算了黄河流域1 km×1 km分辨率各月天文辐射的空间分布。结果表明:局部地形对黄河流域年和四季天文辐射的空间分布影响明显;在太阳高度角较低的冬季,地理和地形因子对天文辐射的影响相当强烈,山区天文辐射的空间差异大,1月份向阳山坡(偏南坡) 天文辐射可为背阴山坡(偏北坡) 的2~3倍,极端天文辐射的差异可达10倍以上;而在太阳高度角较高的夏季,天文辐射空间差异较小,7月份不同地形极端天文辐射的差异仅在16%左右;四季中,地形对天文辐射影响的程度为冬季>秋季>春季>夏季。     

起伏地形下黄河流域太阳直接辐射分布式模拟

1 Introduction Directsolarradiation (DSR)isthe key com ponentofthe globalradiation reaching the Earth.For the influence of terrain factors,calculation of DSR quantity of rugged terrain is considerably com plex (Oliphantetal.,2003). The solarradiation quan…     

起伏地形下黄河流域太阳直接辐射分布式模式

基于数字高程模型(DEM)数据和气象站观测资料建立了起伏地形下太阳直接辐射分布式计算模型,模型充分考虑了地形因子(坡向、坡度、地形相互遮蔽)对起伏地形下太阳直接辐射空间分布的影响;以1km×1km分辨率的DEM数据作为地形的综合反映,计算了起伏地形下黄河流域1km×1km分辨率太阳直接辐射的空间分布;深入分析了起伏地形下太阳直接辐射受地理、地形因子影响的变化规律.结果表明受地形起伏和坡向、坡度等局地地形因子的影响,山区年太阳直接辐射量的空间差异比较明显,向阳山坡(偏南坡)的年直接辐射量明显高于背阴山坡(偏北坡).     

山区地形开阔度的分布式模型

 地形开阔度是影响山地辐射平衡及其分量的重要地形因子,是山区散射辐射、地形反射辐射等计算的重要参数。在复杂的地形条件下,地形开阔度的计算很难用数学公式描述。 利用数字高程模型（DEM）,全面考虑了坡地自身遮蔽和周围地形相互遮蔽的影响,提出了山区地形开阔度的分布式模型和算法。以1 km×1 km分辨率的DEM数据作为地形的综合反映,计算了起伏地形下中国地形开阔度的空间分布。同时,利用100 m和1 km两个分辨率的DEM数据,从不同DEM分辨率和不同地貌类型两个方面探讨了地形开阔度的空间尺度效应,阐明了区域地形开阔度随地形地貌和空间分辨率的变化规律。所提供的山地开阔度的数据可作为基础地理数据供相关研究应用。     

起伏地形下黄河流域太阳直接辐射分布式模拟

基于数字高程模型(DEM)数据和气象站观测资料建立了起伏地形下太阳直接辐射分布式计算模型,模型充分考虑了地形因子(坡向、坡度、地形相互遮蔽)对起伏地形下太阳直接辐射空间分布的影响;以1km×1km分辨率的DEM数据作为地形的综合反映,计算了起伏地形下黄河流域1km×1km分辨率太阳直接辐射的空间分布;深入分析了起伏地形下太阳直接辐射受地理、地形因子影响的变化规律。结果表明:受地形起伏和坡向、坡度等局地地形因子的影响,山区年太阳直接辐射量的空间差异比较明显,向阳山坡(偏南坡)的年直接辐射量明显高于背阴山坡(偏北坡)     

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

1IntroductionDistributed watershed hydrological model has become one of the hot topics in hydrology for its predominance in reflecting the influence of the spatial distributed features of terrains on hydrological processes (Wan etal., 2001; Abbott etal., 1986; Beven etal., 1992). However its demands on the spatio-temporal changeful surface elements such as solar radiation, precipitation, temperature etc. are strict. Being the limitations of observation techniques, data availability and study …     

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.     

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.     

贵州高原复杂地形下太阳总辐射精细空间分布

海拔、坡度、坡向以及周围地形遮蔽作用,造成山区各部位接受到的太阳辐射能有很大差异. 在前人研究的基础上,对以前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天文辐射的影响,基于数字高程模型(DEM)数据,研制了以复杂地形下天文辐射为起始数据的复杂地形下太阳总辐射的分布式模型,在模型中还考虑了散射辐射的各向异性及坡地反射辐射对复杂地形下太阳总辐射的影响.应用100 m×100 m分辨率的DEM数据及气象站常规观测气象资料,计算了贵州高原复杂地形下100 m×100 m分辨率的复杂地形下太阳总辐射.结果表明:(1) 局地地形因子如坡度、坡向、地形遮蔽等对太阳总辐射影响显著,地形对复杂地形下太阳总辐射的影响是不容忽视的.(2)在缺乏复杂地形下坡面考察资料的情况下,建立以常规气象站观测资料为主的物理经验统计模型是实现细网格辐射资源计算的可行途径.     

晴空下山区太阳辐射模拟

由于太阳辐射在山区的空间分布情况较为复杂,在Arcgis,Envi和C++基础上,提出了一个晴空条件下估算山区太阳辐射分布的模型。在借鉴国内外太阳辐射研究成果基础上充分考虑了地形因素和大气状况,利用Modtran大气辐射传输模型、DEM和Modis反照率数据建立了山区太阳辐射计算模型。以黑河上游山区为试验区,利用该模型模拟得到了黑河上游山区的太阳辐射,分析了坡度、坡向、海拔对太阳辐射空间分布的影响,并利用实测值对模型进行了验证,结果表明：该模型可较好地反映研究区内山区太阳总辐射的分布,可用于山区太阳辐射的估算。     

基于地形的福建省太阳辐射模拟计算及评估

取分布式模拟方法,利用福建省69个气象站1971—2007年日照资料及100 m×100 m分辨率的高程数据,计算了福建省范围内历年1—12月的太阳辐射量.结果表明,福建省年太阳总辐射主要在3 800~5 300 MJ/m2之间,年太阳直接辐射在1 800~2 800 MJ/m2之间;月太阳辐射介于230~590 MJ/m2之间,其中6—9月为一年中辐射较高的4个月份.太阳辐射的高值区主要位于福建东南部的莆田、泉州、厦门、漳州4市的沿海一带,年太阳总辐射超过4 500 MJ/m2,年太阳直接辐射超过2 100 MJ/m2.此外,受地形及地表特征的影响,位于福建北部的南平市的部分地区太阳辐射也相对较高.     

A comparative analysis of DEM‐based models to estimate the solar radiation in mountainous terrain

Daily solar radiation estimates of four up‐to‐date solar radiation models (Solar Analyst, r.sun, SRAD and Solei‐32), based on a digital elevation model (DEM), have been evaluated and compared in a Mediterranean environment characterized by a complex topography. The models' estimates were evaluated against 40 days of radiometric data collected in 14 stations. Analyzed sky conditions ranged from completely overcast conditions to clear skies. Additionally, the role of the spatial resolution of the DEM has been evaluated through the use of two different resolutions: 20 and 100 m. Results showed that, under clear‐sky conditions, the daily solar radiation variability in the study area may be reasonably estimated with mean bias errors under 10% and root mean square error values of around 15%. On the other hand, results proved that the reliability of the estimates substantially decreases under overcast conditions for some of the solar radiation models. Regarding the role of the DEM spatial resolution, results suggested that the reliability of the estimates for complex topography areas under clear‐sky conditions improves using a higher spatial resolution.     

DEM误差对滑坡危险性评价模型的影响

基于数字高程模型(DEM)计算得到的坡度、坡向等地形属性是滑坡危险性评价模型的重要输入数据, DEM误差会导致地形属性计算结果不确定性, 进而影响滑坡危险性评价模型的结果。本文选择基于专家知识的滑坡危险性评价模型和逻辑斯第回归模型, 采用蒙特卡洛模拟方法, 研究DEM误差所导致的滑坡危险性评价模型结果不确定性。研究区位于长江中上游的重庆开县, 采用5 m分辨率的DEM, 以序贯高斯模拟方法模拟了不同大小(误差标准差为1 m、7.5 m、15 m)和空间自相关性(变程为0 m、30 m、60 m、120 m)的12 类DEM误差场参与滑坡危险性评价。每次模拟包括100 个实现, 通过对每次模拟分别计算滑坡危险性评价结果的标准差图层和分类一致性百分比图层, 用以评价结果不确定性。评价结果表明, 在不同的DEM精度下, 两个滑坡危险性评价模型所得结果的总体不确定性随空间自相关程度的变化趋势并不相同。当DEM空间自相关性程度不同时, 基于专家知识的滑坡危险性评价模型的评价结果总体不确定随着DEM误差增加而呈现不同的变化趋势, 而逻辑斯第回归模型的评价结果总体不确定性随着DEM误差大小增加而单调增加。从评价结果总体不确定性角度而言, 总体上逻辑斯第回归模型比基于专家知识的滑坡危险性评价模型更加依赖于DEM数据质量。     

规则格网DEM坡度坡向算法的比较分析

DEM的主要用途之一就是提取坡度和坡向。目前基于格网DEM的坡度坡向算法比较多,正确分析和评价现有算法是当前较为关心的问题。通过对格网DEM的算法进行了简要的归纳,然后对坡度坡向算法进行了理论分析。并通过实验对相关的结论进行了验证。本研究澄清了目前有关DEM坡度坡向算法中存在的一些问题,对实际应用有一定的指导意义。     

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.     

DEM地形信息量计算的不确定性研究

DEM地形信息量的准确度量是判定DEM数据应用适宜性与限制性关键。以黄土丘陵沟壑区DEM及其派生的坡度、坡向DTM为例进行实验,研究子集划分与分级数对DEM信息量估算精度的影响。结果表明,DEM地形信息量是实际地形信息和子集划分策略共同作用的结果,现有DEM信息量计算存在不确定性,DEM子集划分算法和分级数的选择直接影响DEM信息量的计算结果。文章借助最大熵定理的基本思路构建DEM地形信息量分级判定模型,可客观获得连续型栅格地形数据在信息量计算上最优分级,为有效估算DEM地形信息量提供科学依据。     

贵州高原复杂地形下月平均日最高气温分布式模拟

在前人研究的基础上,对以前的模型进行改进,考虑了坡度、坡向和地形相互遮蔽作用对复杂地形下天文辐射的影响,基于数字高程模型(DEM)数据,建立以天文辐射为起始数据的复杂地形下月平均日最高气温的分布式模型,在模型中考虑了海拔高度、复杂地形下太阳总辐射、日照百分率对月平均日最高气温的影响.以贵州高原为例.应用100m×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,计算了贵州高原各月及年平均日最高气温精细空间分布.结果表明:(1)坡度、坡向、地形遮蔽对月平均日最高气温的影响较大,由于局地地形因子的影响,复杂地形下月平均日最高气温的空间分布具有明显的地域分布特征,局地地形对月平均日最高气温的影响是不容忽视的.(2)季节不同,局地地形因子对复杂地形下月平均日最高气温空间分布的影响不同,冬半年大于夏半年.月平均日最高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高气温偏低,偏南坡月平均日最高气温偏高;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.