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DOI	10.1007/s11600-018-0226-y
	Analysis of deterministic and geostatistical interpolation techniques for mapping meteorological variables at large watershed scales
	Amini, Mohammad Amin 1; Torkan, Ghazale 2; Eslamian, Saeid 3; Zareian, Mohammad Javad 4; Adamowski, Jan Franklin 5
通讯作者	Amini, Mohammad Amin
来源期刊	ACTA GEOPHYSICA
ISSN	1895-6572
EISSN	1895-7455
出版年	2019
卷号	67 期号:1 页码:191-203
英文摘要	The widely scattered pattern of meteorological stations in large watersheds and remote locations, along with a need to estimate meteorological data for point sites or areas where little or no data have been recorded, has encouraged the development and implementation of spatial interpolation techniques. The various interpolation techniques featured in GIS software allow for the extraction of this new information from spatially distinct point data. Since no one interpolation method can be accurate in all regions, each method must be evaluated prior to each geographically distinct application. Many methods have been used for interpolating minimum temperature (Tmin), maximum temperature (Tmax) and precipitation data; however, only a few methods have been used in the Zayandeh-Rud River basin, Iran, and no comparison of methods has ever been carried out in the area. The accuracies of six spatial interpolation methods [Inverse Distance Weighting, Natural Neighbor (NN), Regularized Spline, Tension Spline, Ordinary Kriging, Universal Kriging] were compared in this study simultaneously, and the best method for mapping monthly precipitation and temperature extremes was determined in a large semi-arid watershed with high temperature and rainfall variation. A cross-validation technique and long-term (1970-2014) average monthly Tmin, Tmax and precipitation data from meteorological stations within the basin were used to identify the best interpolation method for each variable dataset. For Tmin, Kriging (Gaussian) proved to be the most accurate interpolation method (MAE=1.827 degrees C), whereas, for Tmax and precipitation the NN method performed best (MAE=1.178 degrees C and 0.5241mm, respectively). Accordingly, these variable-optimized interpolation methods were used to define spatial patterns of newly generated climatic maps.
英文关键词	Precipitation Sensitivity analysis Spatial interpolation Temperature Zayandeh-Rud River basin
类型	Article
语种	英语
国家	Iran ; Canada
收录类别	SCI-E
WOS记录号	WOS:000459978000014
WOS关键词	SPATIAL INTERPOLATION ; AIR-TEMPERATURE ; COMPLEX TERRAIN ; RAINFALL ; PRECIPITATION ; VARIABILITY ; RESOLUTION ; BASIN
WOS类目	Geochemistry & Geophysics
WOS研究方向	Geochemistry & Geophysics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/213841
作者单位	1.Tarbiat Modares Univ, Dept Water Resources Management, Coll Agr, Tehran, Iran; 2.Univ Tehran, Dept Water Resources Management, Coll Agr, Tehran, Iran; 3.Isfahan Univ Technol, Dept Water Engn, Coll Agr, Esfahan, Iran; 4.Minist Energy, Water Res Inst WRI, Dept Water Resources Res, Tehran, Iran; 5.McGill Univ, Dept Bioresource Engn, Ste Anne De Bellevue, PQ, Canada
推荐引用方式 GB/T 7714	Amini, Mohammad Amin,Torkan, Ghazale,Eslamian, Saeid,et al. Analysis of deterministic and geostatistical interpolation techniques for mapping meteorological variables at large watershed scales[J],2019,67(1):191-203.
APA	Amini, Mohammad Amin,Torkan, Ghazale,Eslamian, Saeid,Zareian, Mohammad Javad,&Adamowski, Jan Franklin.(2019).Analysis of deterministic and geostatistical interpolation techniques for mapping meteorological variables at large watershed scales.ACTA GEOPHYSICA,67(1),191-203.
MLA	Amini, Mohammad Amin,et al."Analysis of deterministic and geostatistical interpolation techniques for mapping meteorological variables at large watershed scales".ACTA GEOPHYSICA 67.1(2019):191-203.