基于ANUSPLIN的黄土丘陵区气象要素插值方法对比与评估

doi:10.13866/j.azr.2023.10.04

Abstract

Abstract:

Meteorological elements are the key factors used to assess the earth’s hydrothermal processes. Accurate acquisition of meteorological data is thus of great significance to the development of ecological protection systems and agricultural research. Loess hilly areas typically have hills and gullies, and consequently, the terrain seriously affects the interpolation of meteorological data and its accuracy. Based on the professional meteorological interpolation software ANUSPLIN, this study has used the daily temperature and rainfall data from 105 meteorological stations in and around the Yanhe River Basin from 2010 to 2021 as the basis, and three digital elevation models (DEM) with resolutions of 25 m, 90 m, and 1 km as covariables to interpolate the grid of temperature and precipitation in the loess hilly region. The spatiotemporal variation of precipitation was analyzed, and the applicability of the ANUSPLIN interpolation method in the loess hilly region evaluated. The results show that temperatures in the eastern extension area of the Yanhe River Basin were higher, when compared with those in the western area. The rainfall was lower in the central and northwestern regions when compared with the eastern regions. The distributions of temperature and rainfall were consistent with the laws of the previous meteorological station data. The ANUSPLIN model had a good adaptability to the spatial interpolation of temperature and rainfall in the loess hilly-gully region. In three different DEM resolution simulation scenarios, the accuracy of temperature interpolation was ranked as 25 m > 90 m > 1 km, and the rainfall interpolation accuracy was ranked as 90 m > 25 m > 1 km.

Key words: ANUSPLIN model, meteorological elements, loess hilly region, digital elevation data, evaluation

XIAO Xu, ZHENG Cheng, DING Chengqin, FAN Chenzhe, BAI Yuejiang, LIN Longchao, YAN Ting, GAO Yu, SHI Haijing. Comparative analysis of the temperatures and rainfall in loess hilly regions using the ANUSPLIN model[J].Arid Zone Research, 2023, 40(10): 1575-1582.

Figures/Tables 3

References 34

[1]	刘志红, Tim R McVicar, Van Niel T G, 等. 专用气候数据空间插值软件ANUSPLIN及其应用[J]. 气象, 2008, 34(2): 92-100.
	[Liu Zhihong, Tim R McVicar, Van Niel T G, et al. Introduction of the professional interpolation software for meteorology data: ANUSPLIN[J]. Meteorological Monthly, 2008, 34(2): 92-100.]
[2]	贺倩, 汪明, 刘凯. 基于机器学习的气温要素空间插值[J]. 高原气象, 2022, 41(3): 733-748. doi: 10.7522/j.issn.1000-0534.2021.000007
	[He Qian, Wang Ming, Liu Kai. Spatial interpolation of air temperature based on machine learning[J]. Plateau Meteorology, 2022, 41(3): 733-748.] doi: 10.7522/j.issn.1000-0534.2021.000007
[3]	梅晓丹, 李丹, 王强, 等. 基于ANUSPLIN的小兴安岭地区降水格点数据空间插值[J]. 测绘与空间地理信息, 2021, 44(12): 6-10.
	[Mei Xiaodan, Li Dan, Wang Qiang, et al. Spatial interpolation of precipitation grid point data in Xiaoxing’anling region based on ANUSPLIN[J]. Geomatics & Spatial Information Technology, 2021, 44(12): 6-10.]
[4]	任宾宾, 王平, 邱绍柱, 等. 基于Co-kriging的呼伦贝尔市2018年降水量空间分布特征模拟及插值精度分析[J]. 西南大学学报(自然科学版), 2021, 43(11): 162-171.
	[Ren Binbin, Wang Ping, Qiu Shaozhu, et al. Simulation of spatial distribution characteristics of precipitation in Hulunbeier City in 2018 and an analysis of interpolation accuracy based on Collaborative kriging model[J]. Journal of Southwest University(Natural Science Edition), 2021, 43(11): 162-171.]
[5]	Hutchinson M F. 2004. ANUSPLIN Version 4.3 User Guide. The Australian National University, Centre for Resource and Environmental Studies, Canberra.
[6]	Chazdon R L. Beyond deforestation: Restoring forests and ecosystem services on degraded lands[J]. Science, 2008, 320(5882): 1458-1460. doi: 10.1126/science.1155365 pmid: 18556551
[7]	Zhang Xiaotao, Kang Shaozhong, Zhang Lu, et al. Spatial variation of climatology monthly crop reference evapotranspiration and sensitivity coefficients in Shiyang river basin of Northwest China[J]. Agricultural Water Management, 2010, 97(10): 1506-1516. doi: 10.1016/j.agwat.2010.05.004
[8]	Guo Binbin, Zhang Jing, Xu Tingbao, et al. Assessment of multiple precipitation interpolation methods and uncertainty analysis of hydrological models in Chaohe River basin, China[J]. Water Research Commission, 2022, 48(3): 324-334.
[9]	张晓影, 叶彬, 刘海婧, 等. 基于小波功率谱和Anusplin的江苏省近58年来降水时空变化分析[J]. 水电能源科学, 2022, 40(1): 6-9.
	[Zhang Xiaoying, Ye Bin, Liu Haijing, et al. Spatial and temporal variation of precipitation in Jiangsu Province in recent 58 years based on wavelet power spectrum and Anusplin[J]. Water Resources and Power, 2022, 40(1): 6-9.]
[10]	钱永兰, 吕厚荃, 张艳红. 基于ANUSPLIN软件的逐日气象要素插值方法应用与评估[J]. 气象与环境学报, 2010, 26(2): 7-15.
	[Qian Yonglan, Lv Houquan, Zhang Yanhong. Application and assessment of spatial interpolation method of daily meteorological elements based on ANUSPLIN software[J]. Journal of Meteorology and Environment, 2010, 26(2): 7-15.]
[11]	Guo Binbin, Zhang Jing, Meng Xianyong, et al. Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN[J]. Scientific Reports, 2020, 10(1): 81. doi: 10.1038/s41598-019-57078-3 pmid: 31919374
[12]	贾文雄. 祁连山气候的空间差异与地理位置和地形的关系[J]. 干旱区研究, 2010, 27(4): 607-615.
	[Jia Wenxiong. Study on the relationship between regional climatic difference a geographical location and terrain in Qilian Mountains[J]. Arid Zone Research, 2010, 27(4): 607-615.]
[13]	谭剑波, 李爱农, 雷光斌. 青藏高原东南缘气象要素Anusplin和Cokriging空间插值对比分析[J]. 高原气象, 2016, 35(4): 875-886. doi: 10.7522/j.issn.1000-0534.2015.00037
	[Tan Jianbo, Li Ainong, Lei Guangbin. Contrast on Anusplin and Cokriging meteorological spatial interpolation in southeastern margin of Qinghai-Xizang Plateau[J]. Plateau Meteorology, 2016, 35(4): 875-886.] doi: 10.7522/j.issn.1000-0534.2015.00037
[14]	张彩霞, 杨勤科, 段建军. 一种高质量的数字高程模型(DEM)建立方法——ANUDEM法[J]. 中国农学通报, 2005, 21(12): 411-415.
	[Zhang Caixia, Yang Qinke, Duan Jianjun. A method to build high quality DEMs-ANUDEM method[J]. Chinese Agricultural Science Bulletin, 2005, 21(12): 411-415.]
[15]	赵冠华, 刘正佳, 胡云锋, 等. DEM的不确定性对温度插值精度的影响[J]. 地理与地理信息科学, 2016, 32(2): 21-26.
	[Zhao Guanhua, Liu Zhengjia, Hu Yunfeng, et al. Impacts of DEM uncertainty on temperature interpolation accuracy[J]. Geography and Geo-Information Science, 2016, 32(2): 21-26.]
[16]	Cuervo-Robayo A P, Tellez-Valdes O, Gomez-Albores A. et al. An update of high-resolution monthly climate surfaces for Mexico[J]. International Journal of Climatology, 2014, 34(7): 2427-2437. doi: 10.1002/joc.2014.34.issue-7
[17]	刘正佳, 于兴修, 王丝丝, 等. 薄盘光滑样条插值中三种协变量方法的降水量插值精度比较[J]. 地理科学进展, 2012, 31(1): 56-62. doi: 10.11820/dlkxjz.2012.01.008
	[Liu Zhengjia, Yu Xingxiu, Wang Sisi, et al. Comparative analysis of three covariates methods in thin-plate smoothing splines for interpolating precipitation[J]. Progress in Geography, 2012, 31(1): 56-62.] doi: 10.11820/dlkxjz.2012.01.008
[18]	刘林, 李国文, 冻芳芳, 等. 基于ANUSPLIN模型的不同分辨率DEM场景下江西省降雨量插值对比分析[J]. 江西水利科技, 2021, 47(2): 116-121.
	[Liu Lin, Li Guowen, Dong Fangfang, et al. Contrastive analysis of precipitation interpolation in Jiangxi Province under different resolution DEM scenes based on ANUSPLIN model[J]. Jiangxi Hydraulic Science & Technology, 2021, 47(2): 116-121.]
[19]	蒋婷婷. 黄土丘陵沟壑区延河流域土壤侵蚀时空变化与驱动因素研究[D]. 合肥: 安徽理工大学, 2021.
	[Jiang Tingting. Temporal and Spatial Changes and Driving Factors of Soil Erosion in Yanhe River Basin in Loess Hilly and Gully Region[D]. Hefei: Anhui University of Science& Technology, 2021.]
[20]	刘春利, 杨勤科, 谢红霞. 延河流域降雨侵蚀力时空分布特征[J]. 环境科学, 2010, 31(4): 850-857.
	[Liu Chunli, Yang Qinke, Xie Hongxia. Spatial and temporal distribution of rainfall erosivity in Yanhe River Basin[J]. Environmental Science, 2010, 31(4): 850-857.]
[21]	赫晓慧, 温仲明. 小流域地形因子影响下的土壤水分空间变异性研究[J]. 水土保持研究, 2008, 67(2): 80-83, 87.
	[He Xiaohui, Wen Zhongming. Spatial variability of soil water controlled by the topographic factors[J]. Research of Soil and Water Conservation, 2008, 67(2): 80-83, 87.]
[22]	郑诚, 温仲明, 郭倩, 等. 基于MaxEnt模型的延河流域草本植物适生分布与功能性状分析[J]. 生态学报, 2021, 41(17): 6825-6835.
	[Zheng Cheng, Wen Zhongming, Guo Qin, et al. Analysis of suitability distribution and functional traits of common herb species in Yanhe River catchment based on MaxEnt model[J]. Acta Ecologica Sinica, 2021, 41(17): 6825-6835.]
[23]	孟清, 白红英, 郭少壮. 基于Anusplin秦岭地区近50多年来的降水时空变化[J]. 水土保持研究, 2020, 27(2): 206-212.
	[Meng Qing, Bai Hongying, Guo Shaozhuang. Spatial-temporal variation of precipitation in Qinling area in recent 50 years based on the Anusplin[J]. Research of Soil and Water Conservation, 2020, 27(2): 206-212.]
[24]	贾洋, 崔鹏. 高山区多时间尺度Anusplin气温插值精度对比分析[J]. 高原气象, 2018, 37(3): 757-766. doi: 10.7522/j.issn.1000-0534.2017.00072
	[Jia Yang, Cui Peng. Contrastive analysis of temperature interpolation at different time scales in the Alpine region by Anusplin[J]. Plateau Meteorology, 2018, 37(3): 757-766.] doi: 10.7522/j.issn.1000-0534.2017.00072
[25]	刘丙霞, 邵明安. 黄土区退耕草地小尺度土壤水分空间异质性[J]. 中国水土保持科学, 2012, 10(4): 60-65.
	[Liu Binxia, Shao Ming’an. Soil water content heterogeneity at small-scale on degraded grasslands in loess plateau[J]. Science of Soil and Water Conservation, 2012, 10(4): 60-65.]
[26]	Douda J, Doudova-Kochankova J, Boublik Karel, et al. Plant species coexistence at local scale in temperate swamp forest: Test of habitat heterogeneity hypothesis[J]. Oecologia, 2012, 169(2): 523-534. doi: 10.1007/s00442-011-2211-x pmid: 22139430
[27]	Fahrig L. Effects of habitat fragmentation on biodiversity[J]. Annual Review of Ecology, Evolution, and Systematics, 2003, 34(1): 487-515. doi: 10.1146/ecolsys.2003.34.issue-1
[28]	陈亚宁, 李玉朋, 李稚, 等. 全球气候变化对干旱区影响分析[J]. 地球科学进展, 2022, 37(2): 111-119. doi: 10.11867/j.issn.1001-8166.2022.006
	[Chen Yaning, Li Yupeng, Li Zhi, et al. Analysis of impacts of global climate change on dryland areas[J]. Advances in Earth Science, 2022, 37(2): 111-119.] doi: 10.11867/j.issn.1001-8166.2022.006
[29]	Cheng Jiayi, Li Qingxiang, Chao Liya, et al. Development of high resolution and homogenized gridded land surface air temperature data: A case study over Pan-East Asia[J]. Frontiers in Environmental Science, 2020, 8: 588570. doi: 10.3389/fenvs.2020.588570
[30]	罗宇, 尹殿胜, 穆兴民, 等. 延河流域实际蒸散发时空特征及影响因素分析[J]. 中国水土保持科学, 2021, 19(4): 51-59.
	[Luo Yu, Yin Diansheng, Mu Xingmin, et al. Analysis of temporal and spatial characteristics of actual evapotranspiration and its influence factors in Yanhe River Basin[J]. Science of Soil and Water Conservation, 2021, 19(4): 51-59.]
[31]	刘强, 穆兴民, 赵广举, 等. 延河流域水沙变化及其对降水和土地利用变化的响应[J]. 干旱区资源与环境, 2021, 35(7): 129-135.
	[Liu Qiang, Mu Xingmin, Zhao Guangju, et al. Runoff and sediment change and their responses to precipitation and land use change in Yanhe River Basin[J]. Journal of Arid Land Resources and Environment, 2021, 35(7): 129-135.]
[32]	任朝霞, 王丽霞. 1974—2004年延河流域气候变化特征分析[J]. 安徽农业科学, 2011, 39(34): 21280-21281, 21286.
	[Ren Zhaoxia, Wang Lixia. Study on characteristics of climate variation in Yanhe Watershed during 1974 to 2004[J]. Journal of Anhui Agricultural Sciences, 2011, 39(34): 21280-21281, 21286.]
[33]	赵美亮, 曹广超, 赵青林, 等. 气候及土地利用变化对大通河源区水文要素空间分布的影响[J]. 干旱区研究, 2023, 40(3): 381-391.
	[Zhao Meiliang, Cao Guangchao, Zhao Qinglin, et al. Effects of climate and land use change on the spatial distribution of hydrological factors in the source region of Datong River[J]. Arid Zone Research, 2023, 40(3): 381-391.]
[34]	陆福志, 鹿化煜. 秦岭—大巴山高分辨率气温和降水格点数据集的建立及其对区域气候的指示[J]. 地理学报, 2019, 74(5): 875-888. doi: 10.11821/dlxb201905003
	[Lu Fuzhi, Lu Huayu. A high-resolution grid dataset of air temperature and precipitation for Qinling-Daba Mountains in central China and its implications for regional climate[J]. Acta Geographica Sinica, 2019, 74(5): 875-888.] doi: 10.11821/dlxb201905003

Comparative analysis of the temperatures and rainfall in loess hilly regions using the ANUSPLIN model

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 3

References 34

Related Articles 15

Metrics

Comments

Recommended 0

[1]	ZHANG Sheng, ZHANG Tao, DUAN Wenyu, XU Li, Gu Jinyang, ZHANG Wei, LI Simin. Evaluation of the environmental quality of surface water in Chengde using improved methods [J]. Arid Zone Research, 2024, 41(1): 50-59.
[2]	MA Zhengang,LI Lili,ZHANG Jungui. Comparative study on water area changes and influencing factors in the Guanting and Miyun reservoirs [J]. Arid Zone Research, 2023, 40(8): 1229-1239.
[3]	SONG Jiajia, LI Gangtie, GUO Jingjie, GU Zhonghou, LIU Kun, LI Zhilong, KANG Xia. Population structure and dynamic analysis of natural Juniperus rigida in a loess hilly area [J]. Arid Zone Research, 2023, 40(8): 1304-1311.
[4]	CUI Shuai, XU Qiang, YUAN Shuang, PU Chuanhao, CHEN Wanlin, JI Xu. Evaluation of Dongzhi Loess Plateau Gully development based on combined entropy weight Rank-Sum Ratio method [J]. Arid Zone Research, 2023, 40(3): 481-491.
[5]	WANG Yunpeng, LI Hongying, YAO Yubi, LI Dongliang, FAN Qiwei, LIU Xiangping. Multi-time scale change characteristics and influencing factors of total solar radiation in Dunhuang City [J]. Arid Zone Research, 2023, 40(12): 1885-1897.
[6]	LI Erchen, ZHANG Yu, YUAN Guanghui. Quantify the impacts of four land cover types on surface temperature in the Heihe River Basin [J]. Arid Zone Research, 2023, 40(1): 30-38.
[7]	HUANG Zhou,YANG Guang,SU Jun,LI Xiaolong,LIU Bing,HE Xinlin,QIAO Changlu,LI Pengfei,WANG Chunxia,ZHAO Li. Soil quality evaluation of returning farmland to Manas River irrigation area under the constraints of the“Three Red Lines” strategy of water resources [J]. Arid Zone Research, 2022, 39(6): 1942-1951.
[8]	WANG Yonghui,YE Xiaojuan,PAN Hongzhong,BAI Yu,DONG Defu,YAO Huaming. Construction of climate warming and humidification evaluation index and its application in Qinghai Province [J]. Arid Zone Research, 2022, 39(5): 1437-1448.
[9]	LI Xuening,XU Xianying,ZHENG Guiheng,MA Quanlin,ZHANG Yunian,LIU Hujun,ZHAO Peng,YANG Xuemei. A health evaluation of a Haloxylon ammodendron plantation in the Shiyang River lower reaches [J]. Arid Zone Research, 2022, 39(3): 872-882.
[10]	TIAN Xiaoxia,WEI Xiaofeng,WEI Hao,XU Mingshuang,MAO Peichun. Comprehensive evaluation of drought tolerance of six forage species at the seedling stage [J]. Arid Zone Research, 2022, 39(3): 978-985.
[11]	BAI Fan,ZHOU Jinlong,ZENG Yanyan. Hydrochemical characteristics and quality of groundwater in the plains of the Turpan Basin [J]. Arid Zone Research, 2022, 39(2): 419-428.
[12]	JIANG Wei,XI Haiyang,CHENG Wenju,LIU Qin. Evaluation of the operation and management of rural drinking water safety projects in Gansu Province [J]. Arid Zone Research, 2022, 39(1): 301-311.
[13]	WU Xia,JIANG Zhiwei,MENG Rong,LI Yunfei,SUN Xiaohan. Variation characteristics of solar radiation and the interaction with meteorological elements in the Hetao Plain [J]. Arid Zone Research, 2022, 39(1): 41-53.
[14]	TANG Dong,CHENG Ping,YANG Jianjun,LI Hong,SUN Jianwen,WANG Kai. Physiological responses of plants to drought stress in the Northern Piedmont, Tianshan Mountains [J]. Arid Zone Research, 2021, 38(6): 1683-1694.
[15]	FAN Xianglong,LYU Xin,ZHANG Ze,GAO Pan,ZHANG Qiang,YIN Caixia,YI Xiang. Soil nutrient evaluation of cotton field based on distance clustering and K-means dynamic clustering [J]. Arid Zone Research, 2021, 38(4): 980-989.