喀斯特地区月均降水协克里金插值方法研究——以贵州省为例
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摘要
喀斯特山区地形复杂,地势起伏大,降水量时空分布不均匀,尤其是丰水期降水量的分布直接影响当地经济作物的生长,也是地质灾害发生的诱因.以贵州省77个气象站点30 a(1981—2010年)丰水期月均降雨量为基础数据,分析了地形因素(海拔、坡度和坡向)和气象因素(站点压强及相对湿度)与贵州省降水的相关性,并对4种协克里金插值模型方法进行了对比研究.结果表明:采用Pearson相关性分析得出坡向与研究区降水相关性最强,相关系数为0.998.综合对比不同协克里金半变异函数模型(稳定模型、指数模型、球面模型和高斯模型)预测值和实测值的结果表明球面模型的偏差均值最小(MAE=-0.000 4),一致性系数最优(RMSE=0.864).采用球面模型的协克里金插值是进行贵州省降水插值的最好方法,这为更有效地识别出喀斯特地区丰水期降水空间分布提供基础.
The geographical condition of Karst mountainous areas is complicated,which,together with the influence of obvious peak clusters,causes an unbalance of the spatial and temporal distribution of rainfalls.In particular,the distribution of precipitation in wet season has a direct impact on local economic crop growth and the occurrence of geological disasters.Based on the 77 weather stations in Guizhou within 30 years( 1981—2010),and on the data of monthly precipitation in analysis of the terrain factors( elevation,gradient,slope direction) and meteorological factors( site pressure,relative humidity,sea level pressure) and the correlation of rainfall in Karst region,Guizhou Province,four Kriging interpolation methods have been explored in light of a comparative study.The results show that firstly,when using Pearson correlation analysis correlation between precipitation and various factors,respectively,the slope is 0. 998,and the slope is of strongest correlation with precipitation. Secondly,through the association and the different half the variation function model( stable model,index model,spherical model and gaussian model) contrast,it is found that the mean difference between spherical model is minimum( MAE =-0.000 4),and the consistency coefficient of optimal is best( RMSE = 0.864).Results from comprehensive comparisons of different model predicted values and measured values show that the best way to carry out interpolation of precipitation in Guizhou Karst area is applying Co-Kriging interpolation with semi variation functioning as the spherical model,which can help enhance the efficiency in identifying the spatial distribution of preoccupation in Karst area during wet season.
The geographical condition of Karst mountainous areas is complicated,which,together with the influence of obvious peak clusters,causes an unbalance of the spatial and temporal distribution of rainfalls.In particular,the distribution of precipitation in wet season has a direct impact on local economic crop growth and the occurrence of geological disasters.Based on the 77 weather stations in Guizhou within 30 years( 1981—2010),and on the data of monthly precipitation in analysis of the terrain factors( elevation,gradient,slope direction) and meteorological factors( site pressure,relative humidity,sea level pressure) and the correlation of rainfall in Karst region,Guizhou Province,four Kriging interpolation methods have been explored in light of a comparative study.The results show that firstly,when using Pearson correlation analysis correlation between precipitation and various factors,respectively,the slope is 0. 998,and the slope is of strongest correlation with precipitation. Secondly,through the association and the different half the variation function model( stable model,index model,spherical model and gaussian model) contrast,it is found that the mean difference between spherical model is minimum( MAE =-0.000 4),and the consistency coefficient of optimal is best( RMSE = 0.864).Results from comprehensive comparisons of different model predicted values and measured values show that the best way to carry out interpolation of precipitation in Guizhou Karst area is applying Co-Kriging interpolation with semi variation functioning as the spherical model,which can help enhance the efficiency in identifying the spatial distribution of preoccupation in Karst area during wet season.
引文
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[16]李文华.云南省山区气候的空间插值研究[J].测绘与空间地理信息,2010,33(3):18-25.LI W H.The study on spatial interpolation of temperature in mountain area of Yunnan province[J].Geomatics&Spatial Information Technology,2010,33(3):18-25.
[17]王庆,马倩倩,夏艳玲,等.最近50年来山东地区夏季降水的时空变化及其影响因素研究[J].地理科学,2014,34(2):220-228.WANG Q,MA Q Q,XIA Y L,et al.Spatial-temporal variations and influential factors of summer precipitation in Shandong region during the last 50 years[J].Scientia Geographica Sinica,2014,34(2):220-228.
[18]李宗发.贵州喀斯特地貌分区[J].贵州地质,2011,28(3):177-181.LI Z F.Division of karst landform in Guizhou[J].Guizhou Geology,2011,28(3):177-181.
[19]周德全,刘秀明,姜立君,等.贵州高原层状地貌与高原抬升[J].地球与环境,2005,33(2):79-84.ZHOU D Q,LIU X M,JIANG L J,et al.Step-like landforms and uplift of Guizhou plateau[J].Earth and Environment,2005,33(2):79-84.
[20]曾怀恩,黄声享.基于Kriging方法的空间数据插值研究[J].测绘工程,2007,16(5):5-9.ZENG H E,HUANG S X.Research on spatial data interpolation based on krging interpolation[J].Engineering of Surveying and Mapping,2007.16(5):5-9.
[21]李新,程国栋,卢玲.青藏高原气温分布的空间插值方法比较[J].高原气象,2003,22(6):565-573.LI X,CHENG G D,LU L.Comparison study of spatial interpolation methods of air temperature over QinhaiXizang plateau[J].Plateau Meteorology,2003,22(6):565-573.
[22]季青,余明.基于协同克里格插值法的年均温空间插值的参数选择研究[J].首都师范大学学报:自然科学版,2010,31(4):81-87.JI Q,YU M.Study of parameters setting of ordinary Cokriging interpretation to average annual temperature[J].Journal of Captical Normal University:Natural Sciences Edition,2010,31(4):81-87.
[23]彭彬,周艳莲,高苹,等.气温插值中不同空间差值方法的适用性分析—以江苏省为例[J].地球信息科学学报,2011,13(4):539-548.PENG B,ZHOU Y L,GAO P,et al.Suitability Assessment of Different Interpolation Methods in the Gridding Process of Station Collected Air Temperature:A Case Study in Jiangsu Province,China[J].Journal Of GeoInformation Science,2011,13(4):539-548.
[24]傅抱璞.地形和海拔高度对降水的影响[J].地理学报,1992,47(4):302-314.FU B P.The effects of topography and elevation on precipitation[J].Acta Geographica Sinica,1992,47(4):302-314.
[25]廖菲,洪延超,郑国光.地形对降水的影响研究概述[J].气象科技,2007,35(3):309-316.LIAO F,HONG Y C,ZHENG G G.Study on the influence of topography on precipitation[J].Meteorological Science and Technology,2007,35(3):309-316.
[26]严小冬,金建德,雷云.近50年贵州降水时空分布分析[J].贵州气象,2004,28(S1):3-7.YAN X D,JIN J D,LEI Y.Analysis of spatial and temporal distribution of precipitation in Guizhou in recent50 years[J].Journal of Guizhou Meteorology,2004,28(S1):3-7.
[2]朱蕾,黄敬风.山区县域尺度降水量空间插值方法比较[J].农业工程学报,2007,23(7):80-85.ZHU L,HUANG J F.Comparison of spatial interpolation method for precipitation of mountain areas in country scale[J].Transactions of the Chinese Society of Agricultural Engineering,2007,23(7):80-85.
[3]孔云峰,仝文伟.降水量地面观测数据空间探索与插值方法探讨[J].地理研究,2008,27(5):1 097-1 108.KONG Y F,TONG W W.Spatial exploration and interpolation of the surface precipitation data[J].Geographical Research,2008,27(5):1 097-1 108.
[4]刘光猛,汪云甲,张海荣,等.空间分析中几种插值方法的比较研究[J].地理信息世界,2011,6(6):41-45.LIU G M,WANG Y J,ZHANG H R,et al.Comparative study of several interpolation methods on spatial analysis[J].Geomatics World.2011,6(6):41-45.
[5]邓晓斌.基于Arc GIS两种空间插值方法的比较[J].地理空间信息,2008,6(6):85-87.DENG X B.Comparison between two space interpolation methods based on Arc GIS[J].Geospatial Information,2008,6(6):85-87.
[6]DALY C.Guidelines for assessing the suitability of spatial climate data sets[J].International Journal of Climatology,2006,26(6):707-721.
[7]卢燕宇,吴必文,田红,等.基于Kriging插值的1961—2005年淮河流域降水时空演变特征分析[J].长江流域资源与环境,2011,20(5):567-573.LU Y Y,WU B W,TIAN H,et al.Spatial and temporal variability characteristics of precipitation in Huai River basin during 1961—2005[J].Resources and Environment in the Yangtze Basin,2011,20(5):567-573.
[8]邵晓梅,严昌荣,魏红兵.基于Kriging插值的黄河流域降水时空分布格局[J].中国农业气象,2006,27(2):65-69.SHAO X M,YAN C R,WEI H B.Spatial and temporal structure of precipitation in the Yellow River basin based on Kriging method[J].Chinese Journal of Agrometeorology,2006,27(2):65-69.
[9]鲁振宇,杨太保,郭万钦.降水空间插值方法应用研究—以黄河源区为例[J].兰州大学学报:自然科学版,2006,42(4):11-14.LU Z Y,YANG T B,GUO W Q.Application of spatial interpolation method of precipitation:a case study of the Yellow River source area[J].Journal of Lanzhou University:Nature Sciences Edition,2006,42(4):11-14.
[10]于洋,卫伟,陈利顶,等.黄土高原年均降水量空间插值及其方法研究[J].应用生态学报,2015,26(4):999-1 006.YU Y,WEI W,CHEN L D,et al.Spatial difference of average annual precipitation in the Loess Plateau and its method[J].Journal of Applied Ecology,2015,26(4):999-1 006.
[11]曹杰,陶云,段旭.云南5月强降水天气与亚洲季风变化的关系[J].云南大学学报:自然科学版,2002,24(5):361-365.CAO J,TAO Y,DUAN X.The relationship between May heavy precipitation an Asian monsoon in Yunnan[J].Journal of Yunnan University:Nature Sciences Edition,2002,24(5):361-365.
[12]孟庆香,刘国彬,杨勤科.黄土高原降水量的空间插值方法研究[J].西北农林科技大学学报:自然科学版,2006,34(3):83-88.MENG Q X,LIU G B,YANG Q K.Research on spatial interpolation methods of pricipitation on loess plateau[J].Journal of Northwest A&F University:Natural Sciences Edition,2006,34(3):83-88.
[13]陶云,何群.云南降水量时空分布特征对气候变暖的响应[J].云南大学学报:自然科学版,2008,30(6):587-595.TAO Y,HE Q.The response of temporal and spatial distribution of precipitation to climate warming in Yunnan[J].Journal of Yunnan University:Natural Sciences Edition,2008,30(6):587-595.
[14]陈贺,李原园,杨志峰,等.地形因素对降水分布影响的研究[J].水土保持研究,2007,14(1):119-122.CHEN H,LI Y Y,YANG Z F,et al.Research on the relationship between terrain factors and precipitation[J].Research of Soil and Water Conservation,2007,14(1):119-122.
[15]周国莲,晏红明.云南近40年降水量的时空分布特征[J].云南大学学报:自然科学版,2007,29(1):55-61.ZHOU G L,YAN H M.Spatial and temporal distribution characteristics of precipitation in Yunnan in recent40 years[J].Journal of Yunnan University:Natural Sciences Edition,2007,29(1):55-61.
[16]李文华.云南省山区气候的空间插值研究[J].测绘与空间地理信息,2010,33(3):18-25.LI W H.The study on spatial interpolation of temperature in mountain area of Yunnan province[J].Geomatics&Spatial Information Technology,2010,33(3):18-25.
[17]王庆,马倩倩,夏艳玲,等.最近50年来山东地区夏季降水的时空变化及其影响因素研究[J].地理科学,2014,34(2):220-228.WANG Q,MA Q Q,XIA Y L,et al.Spatial-temporal variations and influential factors of summer precipitation in Shandong region during the last 50 years[J].Scientia Geographica Sinica,2014,34(2):220-228.
[18]李宗发.贵州喀斯特地貌分区[J].贵州地质,2011,28(3):177-181.LI Z F.Division of karst landform in Guizhou[J].Guizhou Geology,2011,28(3):177-181.
[19]周德全,刘秀明,姜立君,等.贵州高原层状地貌与高原抬升[J].地球与环境,2005,33(2):79-84.ZHOU D Q,LIU X M,JIANG L J,et al.Step-like landforms and uplift of Guizhou plateau[J].Earth and Environment,2005,33(2):79-84.
[20]曾怀恩,黄声享.基于Kriging方法的空间数据插值研究[J].测绘工程,2007,16(5):5-9.ZENG H E,HUANG S X.Research on spatial data interpolation based on krging interpolation[J].Engineering of Surveying and Mapping,2007.16(5):5-9.
[21]李新,程国栋,卢玲.青藏高原气温分布的空间插值方法比较[J].高原气象,2003,22(6):565-573.LI X,CHENG G D,LU L.Comparison study of spatial interpolation methods of air temperature over QinhaiXizang plateau[J].Plateau Meteorology,2003,22(6):565-573.
[22]季青,余明.基于协同克里格插值法的年均温空间插值的参数选择研究[J].首都师范大学学报:自然科学版,2010,31(4):81-87.JI Q,YU M.Study of parameters setting of ordinary Cokriging interpretation to average annual temperature[J].Journal of Captical Normal University:Natural Sciences Edition,2010,31(4):81-87.
[23]彭彬,周艳莲,高苹,等.气温插值中不同空间差值方法的适用性分析—以江苏省为例[J].地球信息科学学报,2011,13(4):539-548.PENG B,ZHOU Y L,GAO P,et al.Suitability Assessment of Different Interpolation Methods in the Gridding Process of Station Collected Air Temperature:A Case Study in Jiangsu Province,China[J].Journal Of GeoInformation Science,2011,13(4):539-548.
[24]傅抱璞.地形和海拔高度对降水的影响[J].地理学报,1992,47(4):302-314.FU B P.The effects of topography and elevation on precipitation[J].Acta Geographica Sinica,1992,47(4):302-314.
[25]廖菲,洪延超,郑国光.地形对降水的影响研究概述[J].气象科技,2007,35(3):309-316.LIAO F,HONG Y C,ZHENG G G.Study on the influence of topography on precipitation[J].Meteorological Science and Technology,2007,35(3):309-316.
[26]严小冬,金建德,雷云.近50年贵州降水时空分布分析[J].贵州气象,2004,28(S1):3-7.YAN X D,JIN J D,LEI Y.Analysis of spatial and temporal distribution of precipitation in Guizhou in recent50 years[J].Journal of Guizhou Meteorology,2004,28(S1):3-7.