[1]李 军,赵玉竹,邓 梅.基于DEM的山地地理可照时数空间分布估算统计模型--以重庆为例[J].山地学报,2019,(02):284-294.[doi:10.16089/j.cnki.1008-2786.000422]
　LI Jun,ZHAO Yuzhu,DENG Mei.The Statistical Model for Estimating Spatial Distribution of Possible Sunshine Duration Based on DEM in Mountain Area: A Case Study in Chongqing, China[J].Mountain Research,2019,(02):284-294.[doi:10.16089/j.cnki.1008-2786.000422]
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基于DEM的山地地理可照时数空间分布估算统计模型--以重庆为例()
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2019年02期
页码:
284-294
栏目:
山地技术
出版日期:
2019-04-25

文章信息/Info

Title:
The Statistical Model for Estimating Spatial Distribution of Possible Sunshine Duration Based on DEM in Mountain Area: A Case Study in Chongqing, China
文章编号:
1008-2786-(2019)2-284-11
作者:
李 军1; 2; 3; 赵玉竹1; 邓 梅1
1.重庆师范大学 地理与旅游学院,重庆 401331; 2.重庆市高校GIS应用研究重点实验室,重庆 401331; 3.三峡库区地表过程与环境遥感重庆市重点实验室,重庆 401331
Author(s):
LI Jun1; 2; 3;  ZHAO Yuzhu1;  DENG Mei1
1.College of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China; 2. Key Laboratory of GIS Application of Chongqing, Chongqing 401331,China; 3. Chongqing Key Laboratory of Earth Surface Processes and Environmental Remote Sensing in Three Gorges Reservoir Area, Chongqing 401331,China
关键词:
可照时数;  空间分布;  重庆;  地形因子;  统计模型
Keywords:
Possible sunshine duration;  spatial distribution;  Chongqing;  topographic factors;  statistical model
分类号:
P208; TP311
DOI:
10.16089/j.cnki.1008-2786.000422
文献标志码:
A
摘要:
为了建立合理、准确且便于估算和应用的山地地理可照时数空间分布模型,本文以重庆为例,首先利用分布式模型估算了30 a平均年和各月可照时数,并利用基于气象行业标准得到的理论值进行了验证; 其次,以栅格单元为统计样本,建立了基于地形尺度的可照时数估算的统计模型。结果表明:(1)基于分布式模型的模拟结果具有较高可信度,除10月外,其他各月和年的相对误差均小于10%,且东北和东南部的相对误差较中西部高。(2)西部方山丘陵区的可照时数高,中部平行岭谷区次之,东北和东南部低。冬季可照时数的空间异质性最大,夏季次之,春秋季接近,均较小。(3)各月和年可照时数与主要地理和地形因子之间的相关关系均表现为极显著性,各月复相关系数在0.7929～0.8277,年复相关系数为0.8522。(4)重庆可照时数估算统计模型在一定程度上简化了分布式模型的计算步骤和计算量,便于其应用,并可为其他地区估算可照时数提供方法参考。
Abstract:
Possible sunshine duration(PSD)is one of important parameters for the study of ecosystem process models and hydrological models. It is defined as its astronomical and geographic factors with no atmospheric influence and only hill shadow is taken into account on its spatial distribution. Therefore, it varies from locality to locality in rugged lands due to height, aspect, slope and the obstruction created by the landforms in immediate surroundings. Establishing an accurate and easy-to-use PSD spatial distribution model is of great theoretical and practical significance to the solar energy resource assessment and radiation balance study. In this paper, firstly, we estimated average monthly and annual PSD during 1981-2010 in Chongqing using a distributed model based on DEM. Then the result was verified by the theoretical value based on an assessment method(QX/T 89-2008)for solar energy resource. Next, the spatial distribution character of PSD with topographic factors was analyzed. Moreover, a statistical model for estimating spatial distribution of PSD were constructed based on statistics of pixels. The result showed:(1)the numerical simulation results based on the distributed model were creditable and the relative error for other monthly except October and annual PSD was less than 10%. The relative error of PSD in the northeast and southeast of Chongqing was higher than that in the middle and western of Chongqing.(2)PSD in the western hills of Chongqing was highest, next was in the central parallel ridge valley area of Chongqing, and the lowest value was in the northeast and southeast of Chongqing. The maximum spatial heterogeneity of PSD in winter was the largest, next was in summer, and the smaller value was in spring and autumn.(3)The relationship between PSD and the major geographical and topographic factors was highly significant. The correlation coefficient of the monthly model varied from 0.7929 to 0.8277 and the value of the annual model was 0.8522.(4)To some extent, the statistical model we constructed simplified the calculation steps and computation of the distribution model, and was easy to be applied in some relevant studies. Moreover, it also can provide a method reference for other areas to estimate PSD.

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备注/Memo

备注/Memo:
收稿日期(Received date):2018-10-19; 改回日期(Accepted date):2019-04-09
基金项目(Foundation item):重庆市前沿与应用基础研究计划一般项目(cstc2015jcyjA00028); 国家自然科学基金(41807498)。[Chongqing Frontier and Applied Basic Research Program(cstc2015jcyjA00028); National Natural Science Foundation of China(41807498)]
作者简介(Biography):李军(1974-),男,博士,副研究员,主要研究方向:农业遥感和地理信息系统应用研究。[LI Jun(1974-), male, Ph.D., associate professor, research on agricultural remote sensing, geographic information system and its application] E-mail: junli@cqnu.edu.cn
更新日期/Last Update: 2019-03-30