地下水埋深空间插值方法比较和空间变异性研究
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摘要
为准确获取区域内地下水埋深空间分布特征以及在水土环境变迁下其年际动态变化规律。以甘肃景泰川电力提灌灌区为研究区,以2015年的16个监测井测得的地下水埋深数据为基础,采用Arc GIS软件中的空间插值模块分别运用反距离权重法、样条函数法、趋势面法以及普通克里金法对区域内地下水埋深数据进行空间插值,并采用交叉验证法和误差矩阵评价方法选取地下水埋深最优插值方法。运用最优插值方法对研究区1994、2001、2008和2015年的地下水埋深观测数据进行空间插值。结果表明:普通克里金(球面函数)插值精度最高,能准确反映地下水埋深时空变异规律及分布特征。研究区地下水位埋深总体上表现为西南低东北高的特征,呈现由西南到东北逐渐升高的趋势,研究区地下水埋深最小值每年都在减小,浅埋深区域逐年增加,地下水埋深平均值2015年较1994年减小了4.85 m,表明整个研究区地下水埋深都在持续抬升,但研究区内,地下水埋深最大值变化较小。该结果表明在水土环境变迁下研究区地下水埋深呈现出逐年升高的趋势,对研究区盐渍化土壤的水盐调控及地下水资源合理开发利用具有重要意义。
In order to accurately obtain the spatial distribution characteristics of groundwater depth in the region and its interannual dynamics under the change of soil and water environment,in this paper,the Jingtaichuan electric power irrigation area in Gansu Province is taken as the research area,based on the groundwater depth data measured by 16 monitoring wells in 2015 and applying the spatial interpolation module in Arc GIS software,and the inverse distance weight method,the spline function method,the trend surface method and the ordinary kriging method are used to interpolate the groundwater depth data in the region,and the cross-validation method and the error matrix evaluation method are used to select the optimal groundwater depth interpolation method.Spatial interpolation of groundwater depth observation data in the study areas in 1994,2001,2008 and 2015 is conducted by using the optimal interpolation method.The results show that the ordinary Kriging(spherical function) has the highest interpolation precision and can accurately reflect the temporal and spatial variability and distribution characteristics of groundwater depth;the buried depth of groundwater level in the study area is generally characterized by southwest low and northeast high,showing a trend of increasing from southwest to northeast;the minimum depth of groundwater depth in the study area is decreasing every year,and the shallow buried depth is increasing year by year;the mean value of the2015 year decreased by 4.85 m than the 1994 year,indicating that the groundwater depth in the whole study area is continuously rising,but the maximum variation of groundwater depth in the study area is small.This result shows that the groundwater depth in the study area shows an increasing trend year by year in the change of water and soil environment,which is of great significance to the regulation of water and salt in salinized soil and the rational development and utilization of groundwater resources in the study area.
In order to accurately obtain the spatial distribution characteristics of groundwater depth in the region and its interannual dynamics under the change of soil and water environment,in this paper,the Jingtaichuan electric power irrigation area in Gansu Province is taken as the research area,based on the groundwater depth data measured by 16 monitoring wells in 2015 and applying the spatial interpolation module in Arc GIS software,and the inverse distance weight method,the spline function method,the trend surface method and the ordinary kriging method are used to interpolate the groundwater depth data in the region,and the cross-validation method and the error matrix evaluation method are used to select the optimal groundwater depth interpolation method.Spatial interpolation of groundwater depth observation data in the study areas in 1994,2001,2008 and 2015 is conducted by using the optimal interpolation method.The results show that the ordinary Kriging(spherical function) has the highest interpolation precision and can accurately reflect the temporal and spatial variability and distribution characteristics of groundwater depth;the buried depth of groundwater level in the study area is generally characterized by southwest low and northeast high,showing a trend of increasing from southwest to northeast;the minimum depth of groundwater depth in the study area is decreasing every year,and the shallow buried depth is increasing year by year;the mean value of the2015 year decreased by 4.85 m than the 1994 year,indicating that the groundwater depth in the whole study area is continuously rising,but the maximum variation of groundwater depth in the study area is small.This result shows that the groundwater depth in the study area shows an increasing trend year by year in the change of water and soil environment,which is of great significance to the regulation of water and salt in salinized soil and the rational development and utilization of groundwater resources in the study area.
引文
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[18]王春颖,尚松浩,毛晓敏,等.区域地下水位插值的整体-局部组合方法[J].农业工程学报,2011,27(8):63-68.
[19]马轩龙,李春娥,陈全功.基于GIS的气象要素空间插值方法研究[J].草业科学,2008,25(11):13-19.
[20]Sun R H,Liu Q L,Chen L D.Study on Precipitation Interpolation Based on the Geostatistical Analyst Method[J].Journal of China Hydrology,2010,30(1):14-13.
[21]李佳,段平,吕海洋,等.基于改进的逐点交叉验证的RBF形态参数优化方法及其空间插值实验[J].地理与地理信息科学,2016,32(3):39-42.
[22]邬伦,吴小娟,肖晨超,等.五种常用降水量插值方法误差时空分布特征研究---以深圳市为例[J].地理与地理信息科学,2010,26(3):19-24.
[2]张琳,刘彩虹,卞建民.大安灌区地下水动态特征及灌区实施后的生态环境响应[J].节水灌溉,2012,(4):43-45.
[3]闫侃.干旱条件下灌区地下水水盐动态分析及预测[D].陕西杨凌:西北农林科技大学,2010.
[4]李亮,史海滨,贾锦凤,等.内蒙古河套灌区荒地水盐运移规律模拟[J].农业工程学报,2010,26(1):31-35.
[5]阮本清,许凤冉,蒋任飞.基于球状模型参数的地下水水位空间变异特性及其演化规律分析[J].水利学报,2008,39(5):573-579.
[6]邓康婕,魏晓妹,降亚楠,等.基于地统计学的泾惠渠灌区地下水位时空变异性研究[J].灌溉排水学报,2015,34(3):75-80.
[7]蒋庆.疏勒河灌区地下水埋深空间插值方法比较[J].节水灌溉,2013,(7):62-64.
[8]马欢,岳德鹏,YANG,等.基于数据同化的地下水埋深插值研究[J].农业机械学报,2017,48(4):206-214.
[9]王辉.景电灌区开发建设对区域生态环境的影响[J].生态学报,1999,19(3):371-375.
[10]徐存东,王小振,王燕.扬水灌区封闭型水文地质单元的地下水盐动态研究[J].灌溉排水学报,2010,29(2):105-108.
[11]张志杰,杨树青,史海滨,等.内蒙古河套灌区灌溉入渗对地下水的补给规律及补给系数[J].农业工程学报,2011,27(3):61-66.
[12]张智印.贵德拉西瓦灌区引水灌溉对地下水环境的影响研究[D].西安:西北大学,2014.
[13]江冠军,刘芳,唐泽军.石羊河流域井灌区土壤水分深层渗漏研究[J].灌溉排水学报,2009,28(6):91-93.
[14]Wu T,Li Y.Spatial interpolation of temperature in the United States using residual kriging[J].Applied Geography,2013,44(4):112-120.
[15]Kolyaie S,Yaghooti M,Majidi G.Analysis and simulation of wireless signal propagation applying geostatistical interpolation techniques[C]∥International Symposium on Mobile Mapping Technology.2011:307-317.
[16]Xu Z,Zhou T.On sparse interpolation and the design of deterministic interpolation points[J].DOT:10.1137/13094596X,2013,36(4).
[17]王克晓,陈伟涛,李显巨,等.空间插值方法模拟地下水空间分布适宜性探讨---以敦煌盆地东湖保护区为例[J].甘肃地质,2017,(4):48-51.
[18]王春颖,尚松浩,毛晓敏,等.区域地下水位插值的整体-局部组合方法[J].农业工程学报,2011,27(8):63-68.
[19]马轩龙,李春娥,陈全功.基于GIS的气象要素空间插值方法研究[J].草业科学,2008,25(11):13-19.
[20]Sun R H,Liu Q L,Chen L D.Study on Precipitation Interpolation Based on the Geostatistical Analyst Method[J].Journal of China Hydrology,2010,30(1):14-13.
[21]李佳,段平,吕海洋,等.基于改进的逐点交叉验证的RBF形态参数优化方法及其空间插值实验[J].地理与地理信息科学,2016,32(3):39-42.
[22]邬伦,吴小娟,肖晨超,等.五种常用降水量插值方法误差时空分布特征研究---以深圳市为例[J].地理与地理信息科学,2010,26(3):19-24.
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