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

doi:10.13287/j.1001-9332.201610.022

应用生态学报 ›› 2016, Vol. 27 ›› Issue (10): 3273-3282.doi: 10.13287/j.1001-9332.201610.022

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

袁玉芸¹, 瓦哈甫·哈力克^1,2*, 关靖云^1,3, 卢龙辉^1,3, 张琴琴^1,3

¹新疆大学绿洲生态教育部重点实验室, 乌鲁木齐 830046;
²新疆大学资源与环境科学学院, 乌鲁木齐 830046;
³新疆大学旅游学院, 乌鲁木齐 830046;

收稿日期:2016-03-14 发布日期:2016-10-18
通讯作者: * E-mail: wahap@xju.edu.cn
作者简介:袁玉芸,女,1991年生,硕士研究生. 主要从事干旱区资源与环境研究. E-mail: 1429439851@qq.com
基金资助:
本文由国家自然科学基金项目(U1138303)资助

Spatial differentiation and impact factors of Yutian Oasis’s soil surface salt based on GWR model

YUAN Yu-yun¹, WAHAP Halik^1,2*, GUAN Jing-yun^1,3, LU Long-hui^1,3, ZHANG Qin-qin^1,3

¹Ministry of Education Key Laboraotory for Oasis Ecosystem, Xinjing University, Urumqi 830046, China;
²College of Resource and Environment Science, Xinjiang University, Urumqi 830046, China;
³College of Tourism Management, Xingjiang University, Urumqi 830046, China;

Received:2016-03-14 Published:2016-10-18
Contact: * E-mail: wahap@xju.edu.cn
Supported by:
This work was supported by the National Natural Science Fundation of China (U1138303).

摘要/Abstract

摘要： 以于田绿洲为研究靶区,利用24个采样点的土壤表层盐分数据,选取9个与土壤表层盐分密切相关的影响因子,结合空间自相关、传统回归分析和地理加权回归模型,分析表土盐分的空间分布特征及其影响因子的空间分异.结果表明:于田绿洲表土盐分在空间上并非随机分布,而是存在较强的空间依赖关系,空间自相关指数为0.479.地下水矿化度、地下水埋深、高程和温度是影响干旱区平原绿洲表土积盐的主要因子,这些因子具有空间异质性,选取的9个环境变量中除土壤pH值外,其他变量对表土盐分的影响强度均存在显著的空间分异.GWR模型对存在空间非平稳性数据的解释能力和估计精度都优于OLS模型,而且在模型估计参数的可视化上具有明显优势.

Abstract: In this paper, topsoil salinity data gathered from 24 sampling sites in the Yutian Oasis were used, nine different kinds of environmental variables closely related to soil salinity were selec-ted as influencing factors, then, the spatial distribution characteristics of topsoil salinity and spatial heterogeneity of influencing factors were analyzed by combining the spatial autocorrelation with traditional regression analysis and geographically weighted regression model. Results showed that the topsoil salinity in Yutian Oasis was not of random distribution but had strong spatial dependence, and the spatial autocorrelation index for topsoil salinity was 0.479. Groundwater salinity, groundwater depth, elevation and temperature were the main factors influencing topsoil salt accumulation in arid land oases and they were spatially heterogeneous. The nine selected environmental variables except soil pH had significant influences on topsoil salinity with spatial disparity. GWR model was superior to the OLS model on interpretation and estimation of spatial non-stationary data, also had a remarkable advantage in visualization of modeling parameters.

袁玉芸, 瓦哈甫·哈力克, 关靖云, 卢龙辉, 张琴琴. 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.

YUAN Yu-yun, WAHAP Halik, GUAN Jing-yun, LU Long-hui, ZHANG Qin-qin. Spatial differentiation and impact factors of Yutian Oasis’s soil surface salt based on GWR model[J]. Chinese Journal of Applied Ecology, 2016, 27(10): 3273-3282.

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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

Spatial differentiation and impact factors of Yutian Oasis’s soil surface salt based on GWR model

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