干旱区土壤盐渍化灾害预警——以渭-库绿洲为例

doi:10.7522/j.issn.1000-694X.2015.00067

摘要/Abstract

摘要： 针对中国西北干旱区普遍存在的土壤盐渍化，以渭干河-库车河绿洲TM影像数据，建立BP神经网络结合Adaboost算法的土壤盐渍化预警度评价模型。首先，根据研究区实际情况设置该模型的4个预警指标（地下水埋深、海拔、盐分指数、归一化干旱指数），分别提取其连续表面信息，结合BP神经网络作为弱预测器进行预测，将通过不同训练集得到的弱预测器结果结合成强预测器。在利用该模型训练样本时，依据各评价因子对分类结果的贡献率调整其权重，预测的结果能客观反映每个评价因子对该地区土壤盐渍化的贡献程度。结果表明，研究区警情总体情况较严重，绿洲北部内部耕地周围的荒地以及含水量少的区域，盐渍化危险度较高。

关键词: 干旱区, 盐渍化, 预警, BP, Adaboost预测器

Abstract: Aiming at the prevailing northwest arid zone of soil salinization, the paper selected the Ugan-Kuqa River Oasis as studied area and TM image as data source to establish BP neural network combined with Adaboost algorithm evaluation soil salinization warning model. First, according to the actual conditions of the area set up four warning indicators of the model: groundwater depth, elevation, salinity index, normalized Drought Index, and extracted its continuous surface information, made BP neural network as a weak predictor to predict, different training obtained results are combined into a strong predictor when using the model of training samples, according to the classification results of each evaluation factor in the share of the contribution rate to adjust their weights, the predicted outcome will be fair objectively reflect each evaluation factor's contribution for the soil salinization in the region, the experimental results show that the overall situation in the study area is more serious alarm, wasteland and water content inside a small area of arable land around the northern oasis, salinization have hazard higher degree. This paper from the point of view of soil salinization warning to conduct a preliminary study and lay a foundation for further study in the future salinization warning.

Key words: arid zone, salinization, warning, BP, Adaboost predictor

中图分类号:

X87
S156.4

丁建丽, 陈文倩, 陈芸. 干旱区土壤盐渍化灾害预警——以渭-库绿洲为例[J]. 中国沙漠, 2016, 36(4): 1079-1086.

Ding Jianli, Niu Zengyi, Li Yanhua. Soil Salinization Disaster Warning in Arid Zones: A case study in the Ugan-Kuqa Oasis[J]. JOURNAL OF DESERT RESEARCH, 2016, 36(4): 1079-1086.

参考文献

[1] 朱庭芸.灌区土壤盐渍化防治[M].北京:农业出版社,1992:32-38.
[2] 翁永玲,宫鹏.土壤盐渍化遥感应用研究进展[J].地理科学,2006(3):369-375.
[3] 依力亚斯江·努尔麦麦提,丁建丽,塔西甫拉提·特依拜,等.基于支持向量机分类的遥感土壤盐渍化信息监测[J].水土保持研究,2007(4):209-214,222.
[4] Taylor G R,Mah A H.Characterization of saline soils using airborne radar imagery[J].Remote Sensing of Environment,1996,57(3):127-142.
[5] Abbas A.Characterizing soil salinity in irrigated agriculture using a remote sensing approach[J].Physics and Chemistry of the Earth,2013,55-57:43-52.
[6] Adam D M.Detecting soil salinity changes in irrigated vertisols by electrical resistivity prospection during a desalinisation experiment[J].Agricultural Water Management,2012,109(9):1-10.
[7] Michot D,Walter C.Digital assessment of soil-salinity dynamics after a major flood in the Niger River valley[J].Geoderma,2013,207-208:193-204.
[8] Ding J L,Yu D L.Monitoring and evaluating spatial variability of soil salinity in dry and wet seasons in the Werigan Kuqa Oasis,China,using remote sensing and electromagnetic induction instruments[J].Geoderma,2014,235-236:316-322.
[9] Boyd H,Roel H,Patrick M,et al.Energy and land use impacts of sustainable transportation scenarios[J].Journal of Cleaner Production,2005,13:1309-1319.
[10] 买买提·沙吾提,塔西甫拉提·特依拜,丁建丽,等.基于GIS的干旱区土壤盐渍化敏感性评价-以渭干河-库车河三角洲绿洲为例[J].资源科学,2012,34(2):353-358.
[11] 周在明,张光辉,王金哲,等.环渤海低平原区土壤盐渍化风险的多元指示克立格评价[J].水利学报,2011,10:1144-1151.
[12] 姚荣江,杨劲松,陈小兵,等.苏北海涂围垦区土壤质量模糊综合评价[J].中国农业科学,2009,42(6):2019-2027.
[13] Michael J,Grundy D.Silburn M.A risk framework for preventing salinity[J].Environmental Hazards,2007,7:97-105.
[14] 刘海霞.应用BP Adaboost预测器的新疆土壤盐渍[D].乌鲁木齐:新疆大学,2012.
[15] Douaoui A E K,Nicolas H.Detecting salinity hazards within a semiarid context by means of combining soil and remote-sensing data[J].Geoderma,2006,134:217-230.
[16] 谢姆斯叶·艾尼瓦尔,塔西甫拉提·特依拜,王宏卫,等.人工智能计算技术在新疆干旱区典型绿洲土壤盐分预测中的应用[J].中国沙漠,2014,34(1):153-161.
[17] 伍漫春,丁建丽,王高峰,基于地表温度-植被指数特征空间的区域土壤水分反演[J].中国沙漠,2012,32(1):145-154
[18] 张飞,塔西甫拉提·特依拜,丁建丽,等.塔里木盆地北缘绿洲土地利用与生态系统服务价值的时空变化研究[J].中国沙漠,2009,29(5):933-941.
[19] 姚远,丁建丽,张芳,等.基于电磁感应技术的塔里木盆地北缘绿洲土壤盐分空间变异特性[J].中国沙漠,2014,34(3):765-772.
[20] 王雪梅,柴仲平,塔西甫拉提·特依拜,等.干旱区土壤盐渍化及其影响因子分析[J].土壤,2009,41(3):477-482.
[21] 王飞,丁建丽,哈学萍,等.干旱区盐渍地景观危险度评价方法-以新疆渭干河-库车河流域为例[J].自然灾害学报,2012(5):79-87.
[22] 孙凤琪.AdaBoost集成神经网络在冲击地压预报中的应用[J].吉林大学学报,2009,27(1):79-81.
[23] 葛启发,冯夏庭.基于AdaBoost组合学习方法的岩爆分类预测研究[J].岩土力学,2008,29(4):943-948.
[24] 文峰,王小川,郁磊,等.MATLAB中文论坛,MATAB神经网络30个案例分析[M].北京:北京航天航空大学出版社,2010:45-52.
[25] 吕云海,海米提·依米提,刘国华,等.于田绿洲土壤含盐量与地下水关系分析[J].新疆农业科学,2009,46(5):1093-1097.
[26] 庞国锦,王涛,孙家欢,等.基于高光谱的民勤土壤盐分定量分析[J].中国沙漠,2014,34(4):1073-1079.
[27] 吴会胜,刘兆礼.基于影像光谱特征分析的盐碱地遥感地图研究-以吉林省大安市为例[J].农业系统科学与综合研究,2007,23(2):178-182.
[28] 冯海霞,秦其明,李滨勇,等.基于SWIR-Red光谱特征空间的农田干旱监测新方法[J].光谱学与光谱分析,2011,31(11):3069-3073.