基于GWR模型的河北省土壤水分空间分异研究
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摘要
为研究环境因素对土壤水分空间分异的影响,利用2013—2017年SMOS Level-3土壤水分数据,选取降水、DEM、坡度、植被、地表温度为影响土壤水分的环境因子,对河北省土壤水分进行了空间自相关分析,建立了河北省土壤含水量与影响因子之间的地理加权模型,将GWR模型与一般线性回归模型对比,分析了影响因子在空间上对土壤水分作用的异质特征。结果表明:河北省土壤含水量具有空间异质性,集聚特征明显。GWR模型的拟合效果在拟合优度和空间分布上都远远优于OLS模型。GWR模型的拟合优度R2比OLS模型提高了43%,GWR模型对土壤水分影响因子的解释能力比OLS模型提高了34.6%,GWR模型的残差平方和、AIC值均远远小于OLS模型。研究区影响因子对土壤水分的作用参数具有空间分异特征,影响因子的作用程度也不同,DEM影响最大,其次是坡度、地表温度、降水、NDVI。各因子在空间上对土壤水分既有负向又有局部正向的作用,但在大部分范围里都呈负向影响。研究成果对研究区的精准农业发展、水土保持利用和生态建设具有重要意义。
In order to study the influence of environmental factors on the spatial differentiation of soil moisture in Hebei Province,SMOS Level-3 soil moisture data from 2013 to 2017 were used to select precipitation,DEM,slope,vegetation,and land surface temperature as environmental factors affecting soil moisture.Spatial autocorrelation analysis of soil moisture in Hebei Province was conducted to establish the geographically weighted regression model between soil moisture contents and impact factors.The GWR model was compared with the general linear regression model to analyze the heterogeneity of the effect of the influencing factors on soil moisture in space.The results showed that the soil moisture in Hebei Province had spatial heterogeneity and obvious agglomeration characteristics.The fitting effect of GWR model was far better than the OLS model in terms of fitting goodness and spatial distribution.The fitting goodness(R2)of the GWR model was 43% higher than that of the OLS model.The ability of the GWR model to explain the soil moisture impact factor was 34.6% higher than that of the OLS model.The residual square sum and AIC value of the GWR model were much smaller than those of OLS model.The effect parameters of the impact factors on soil moisture in the study area had spatial differentiation characteristics,and the degrees of influence of the influence factors were also different with DEM having the greatest impact followed by slope gradient,land surface temperature,precipitation,and NDVI.Each factor had both negative and positive effects on soil moisture in space,but it had the negative effect in most areas.The research results are of great significance to the development of precision agriculture,soil and water conservation,resource utilization,and ecological construction in the study area.
In order to study the influence of environmental factors on the spatial differentiation of soil moisture in Hebei Province,SMOS Level-3 soil moisture data from 2013 to 2017 were used to select precipitation,DEM,slope,vegetation,and land surface temperature as environmental factors affecting soil moisture.Spatial autocorrelation analysis of soil moisture in Hebei Province was conducted to establish the geographically weighted regression model between soil moisture contents and impact factors.The GWR model was compared with the general linear regression model to analyze the heterogeneity of the effect of the influencing factors on soil moisture in space.The results showed that the soil moisture in Hebei Province had spatial heterogeneity and obvious agglomeration characteristics.The fitting effect of GWR model was far better than the OLS model in terms of fitting goodness and spatial distribution.The fitting goodness(R2)of the GWR model was 43% higher than that of the OLS model.The ability of the GWR model to explain the soil moisture impact factor was 34.6% higher than that of the OLS model.The residual square sum and AIC value of the GWR model were much smaller than those of OLS model.The effect parameters of the impact factors on soil moisture in the study area had spatial differentiation characteristics,and the degrees of influence of the influence factors were also different with DEM having the greatest impact followed by slope gradient,land surface temperature,precipitation,and NDVI.Each factor had both negative and positive effects on soil moisture in space,but it had the negative effect in most areas.The research results are of great significance to the development of precision agriculture,soil and water conservation,resource utilization,and ecological construction in the study area.
引文
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[5]邱扬,傅伯杰,王军,等.黄土丘陵小流域土壤水分的空间异质性及其影响因子[J].应用生态学报,2001,1(5):715-720.
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[11]高海峰,白军红,王庆改,等.霍林河下游典型洪泛区湿地土壤pH值和土壤含水量分布特征[J].水土保持研究,2011,18(1):268-271.
[12]段良霞,黄明斌,张洛丹,等.黄土高原沟壑区坡地土壤水分状态空间模拟[J].水科学进展,2015,26(5):649-659.
[13]袁玉芸,瓦哈甫·哈力克,关靖云,等.基于GWR模型的于田绿洲土壤表层盐分空间分异及其影响因子[J].应用生态学报,2016,27(10):3273-3282.
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[15] Yu G,Di L,Yang W.Downscaling of Global Soil Moisture using Auxiliary Data[C]∥Geoscience and Remote Sensing Symposium.IGARSS 2008.IEEE International.IEEE,2008:230-233.
[16]李小英,段争虎.基于SMOS的黄土高原区域尺度表层土壤水分时空变化[J].中国沙漠,2014,34(1):133-139.
[17]陈建,张韧,王辉赞,等.Matlab对基于二进制—XML混合格式的SMOS盐度数据的提取方法与实现[J].海洋通报,2011,30(6):692-696.
[18]张洁.基于GWR模型的城市住宅地价空间分异研究[D].杭州:浙江大学,2012.
[19]韩雅,朱文博,李双成.基于GWR模型的中国NDVI与气候因子的相关分析[J].北京大学学报:自然科学版,2016,52(6):1125-1133.
[20] Brunsdon C,Fotheringham S,Charlton M.Geographically weighted regression[J].Journal of the Royal Statistical Society:Series D,1998,47(3):431-443.
[21] Akaike H.Information theory and an extension of the maximum likelihood principle∥Petrov B N,Csaki F.Second international symposium on information theory.Budapest:Academiai Kiado,1973:267-281.
[22]陈彦光.基于Moran统计量的空间自相关理论发展和方法改进[J].地理研究,2009,28(6):1449-1463.
[23] Lee.Spatial Association Measures for all ESDA-GIS Framework:Developments,Significance Tests,and Applications to Spatio-Temporal Income Dynamics of U.S.Labor Market Areas,1969—1999[D].Ohio:the Ohio State University,2004.
[24] Hawley M E,Jackson T J,Mc Cuen R H.Surface soil moisture on a small agricultural watershed[J].Journal of Hydrology,1983,62:179-200.
[25] Henninger D L,Petersen G W,Engman E T.Surface soil moisture within a watershed:Variations,factors influencing,and relationship to surface run off[J].Soil Science Society of America Journal,1976,40:773-776.
[26] Nyberg L.Spatial variability of soil water content in the covered catchment of Gardsjon,Sweden[J].Hydrological Processes,1996,10:89-103.
[27] Famiglietti J S,Rudnicki J W,Rodell M.Variability in surface moisture content a long a hillslope transect:Rattlesnake Hill,Texas[J].Journal of Hydrology,1998,210:259-281.
[28]黄明斌,康绍忠,李玉山.黄土高原沟壑区森林和草地小流域水文行为的比较研究[J].自然资源学报,1999,14(3):226-231.
[29]邱扬,傅伯杰,王军,等.土壤水分时空变异及其与环境因子的关系[J].生态学杂志,2007,26(1):100-107.
[30]赵晓光,吴发启.黄土高原坡耕地土壤水分主要受控因子研究[J].水土保持通报,1999,19(1):10-14.
[31]邱扬,傅伯杰,王军,等.黄土丘陵小流域土壤水分时空分异与环境关系的数量分析[J].生态学报,2000,20(5):741-747.
[32]高红贝,邵明安.温度对土壤水分运动基本参数的影响[J].水科学进展,2011,22(4):484-494.
[33]高红贝,邵明安.干旱区降雨过程对土壤水分与温度变化影响研究[J].灌溉排水学报,2011,30(1):40-45.
[34] Yang Q,Fu B,Wang J,et al.Spatiotemporal prediction of soil moisture content using multiple-linear regression in a small catchment of the Loess Plateau,China[J].Catena,2003,54(1):173-195.
[35]侯喜禄,白岗栓,曹清玉.刺槐、柠条、沙棘林土壤入渗及抗冲性对比试验[J].水土保持学报,1995,9(3):90-95.
[2]赵永宏,刘贤德,张学龙,等.祁连山区亚高山灌丛土壤含水量的空间分布与月份变化规律[J].自然资源学报,2016,31(4):672-681.
[3]侯建秀,张元明,陶冶,等.沙漠水渠人工固沙区沙蒿和沙拐枣灌丛的土壤水分特征对比[J].干旱地区农业研究,2011,29(4):164-167.
[4]陈书林,刘元波,温作民.卫星遥感反演土壤水分研究综述[J].地球科学进展,2012,27(11):1192-1203.
[5]邱扬,傅伯杰,王军,等.黄土丘陵小流域土壤水分的空间异质性及其影响因子[J].应用生态学报,2001,1(5):715-720.
[6]魏凤英,张京江.华北地区干旱的气候背景及其前兆强信号[J].气象学报,2003,61(3):354-363.
[7] Burns T T,Berg A A,Cockburn J,et al.Regional scale spatial and temporal variability of soil moisture in a prairie region[J].Hydrological Processes,2016,30(20):3639-3649.
[8]赵世伟,周印东,吴金水.子午岭北部不同植被类型土壤水分特征研究[J].水土保持学报,2002,16(4):119-122.
[9]赵琛,张兰慧,李金麟,等.黑河上游土壤含水量的空间分布与环境因子的关系[J].兰州大学学报:自然科学版,2014,50(3):338-347.
[10]闫利爽,黄方,常帅,等.松辽平原西部地表土壤水分时空变化与影响因素分析[J].东北师大学报:自然科学版,2017,49(4):128-133.
[11]高海峰,白军红,王庆改,等.霍林河下游典型洪泛区湿地土壤pH值和土壤含水量分布特征[J].水土保持研究,2011,18(1):268-271.
[12]段良霞,黄明斌,张洛丹,等.黄土高原沟壑区坡地土壤水分状态空间模拟[J].水科学进展,2015,26(5):649-659.
[13]袁玉芸,瓦哈甫·哈力克,关靖云,等.基于GWR模型的于田绿洲土壤表层盐分空间分异及其影响因子[J].应用生态学报,2016,27(10):3273-3282.
[14] Lesage J P.A Family of Geographically Weighted Regression Models[M]∥Advances in Spatial Econometrics.Berlin:Springer Berlin Heidelberg,2004:241-264.
[15] Yu G,Di L,Yang W.Downscaling of Global Soil Moisture using Auxiliary Data[C]∥Geoscience and Remote Sensing Symposium.IGARSS 2008.IEEE International.IEEE,2008:230-233.
[16]李小英,段争虎.基于SMOS的黄土高原区域尺度表层土壤水分时空变化[J].中国沙漠,2014,34(1):133-139.
[17]陈建,张韧,王辉赞,等.Matlab对基于二进制—XML混合格式的SMOS盐度数据的提取方法与实现[J].海洋通报,2011,30(6):692-696.
[18]张洁.基于GWR模型的城市住宅地价空间分异研究[D].杭州:浙江大学,2012.
[19]韩雅,朱文博,李双成.基于GWR模型的中国NDVI与气候因子的相关分析[J].北京大学学报:自然科学版,2016,52(6):1125-1133.
[20] Brunsdon C,Fotheringham S,Charlton M.Geographically weighted regression[J].Journal of the Royal Statistical Society:Series D,1998,47(3):431-443.
[21] Akaike H.Information theory and an extension of the maximum likelihood principle∥Petrov B N,Csaki F.Second international symposium on information theory.Budapest:Academiai Kiado,1973:267-281.
[22]陈彦光.基于Moran统计量的空间自相关理论发展和方法改进[J].地理研究,2009,28(6):1449-1463.
[23] Lee.Spatial Association Measures for all ESDA-GIS Framework:Developments,Significance Tests,and Applications to Spatio-Temporal Income Dynamics of U.S.Labor Market Areas,1969—1999[D].Ohio:the Ohio State University,2004.
[24] Hawley M E,Jackson T J,Mc Cuen R H.Surface soil moisture on a small agricultural watershed[J].Journal of Hydrology,1983,62:179-200.
[25] Henninger D L,Petersen G W,Engman E T.Surface soil moisture within a watershed:Variations,factors influencing,and relationship to surface run off[J].Soil Science Society of America Journal,1976,40:773-776.
[26] Nyberg L.Spatial variability of soil water content in the covered catchment of Gardsjon,Sweden[J].Hydrological Processes,1996,10:89-103.
[27] Famiglietti J S,Rudnicki J W,Rodell M.Variability in surface moisture content a long a hillslope transect:Rattlesnake Hill,Texas[J].Journal of Hydrology,1998,210:259-281.
[28]黄明斌,康绍忠,李玉山.黄土高原沟壑区森林和草地小流域水文行为的比较研究[J].自然资源学报,1999,14(3):226-231.
[29]邱扬,傅伯杰,王军,等.土壤水分时空变异及其与环境因子的关系[J].生态学杂志,2007,26(1):100-107.
[30]赵晓光,吴发启.黄土高原坡耕地土壤水分主要受控因子研究[J].水土保持通报,1999,19(1):10-14.
[31]邱扬,傅伯杰,王军,等.黄土丘陵小流域土壤水分时空分异与环境关系的数量分析[J].生态学报,2000,20(5):741-747.
[32]高红贝,邵明安.温度对土壤水分运动基本参数的影响[J].水科学进展,2011,22(4):484-494.
[33]高红贝,邵明安.干旱区降雨过程对土壤水分与温度变化影响研究[J].灌溉排水学报,2011,30(1):40-45.
[34] Yang Q,Fu B,Wang J,et al.Spatiotemporal prediction of soil moisture content using multiple-linear regression in a small catchment of the Loess Plateau,China[J].Catena,2003,54(1):173-195.
[35]侯喜禄,白岗栓,曹清玉.刺槐、柠条、沙棘林土壤入渗及抗冲性对比试验[J].水土保持学报,1995,9(3):90-95.