基于Logistic回归分析的土壤盐渍化易发性评价——以新疆南疆塔里木灌区为例

doi:10.12118/j.issn.1000-6060.2023.073

摘要/Abstract

摘要：

新疆南疆（简称南疆）的土地资源利用潜力巨大，是我国重要的后备耕地资源供给区，开展土壤盐渍化易发性评价，对于南疆增水增地选区与土地分区分类治理具有重要参考意义。以南疆塔里木灌区为研究对象，基于地下水溶解性固体总量（TDS）、地下水埋深、土壤质地、地貌类型、土地利用类型、土壤含盐量等实地调查数据，采用数据驱动方式的证据权进行土壤盐渍化单因素空间相关性分析，并通过Logistic回归模型进行多因素综合定量评价土壤盐渍化易发性。结果表明：（1）高的地下水TDS、浅的地下水埋深、细颗粒的土壤质地以及地貌类型中的冲（湖）积平原、土地利用类型中的草地与高土壤含盐量地区表现出较高的正空间相关性。（2）灌区冲积平原内的古河道，湖积平原内的古湖沼等槽型、封闭洼地是土壤盐渍化高易发区，面积约29 km²，占灌区总面积的1.3%;灌区农田周边的弃耕地为土壤盐渍化中易发区，面积约453 km²，占灌区总面积的20.5%;灌区周边广阔的沙漠及水域为土壤盐渍化低易发区，面积约1726 km²，占灌区总面积的78.2%。（3）综合模型评价置信度结果及野外实地调查现状表明，Logistic回归模型综合定量评价土壤盐渍化易发性的结果准确可靠，为土壤盐渍化易发性评价提供了新思路，也为南疆地区土壤盐渍化防治和后备耕地资源选区提供了科学依据。

关键词: 土壤盐渍化, Logistic回归分析, 易发性评价, 塔里木灌区, 新疆南疆

Abstract:

The southern region of Xinjiang has great potential for land resource utilization and is a crucial reserve supplying cultivated land resources in China. Evaluating soil salinization susceptibility in this area is necessary, as it aids in making informed decisions regarding water and land selection and land zoning management in southern Xinjiang. Sources, including total dissolved solids (TDS) in groundwater, groundwater depth, soil texture, geomorphic type, land-use type, and soil salt content, were collected via field surveys. By employing data-driven evidence weight, the spatial correlations of a single factor contributing to soil salinization were analyzed, followed by a multifactor comprehensive quantitative evaluation of soil salinization using a Logistic regression model. The results showed the following: (1) Shallow groundwater depth, high groundwater TDS, fine-grained soil, alluvial (lacustrine) plain geomorphology, and grassland land-use types showed strong positive spatial correlation with high soil salt content. (2) High soil salinization-prone areas were identified, encompassing the ancient channel in the alluvial plain and ancient lake marsh in the lacustrine plain, covering ~29 km² and accounting for 1.3% of the total area. Additionally, abandoned farmland around the irrigated area was a prone area of soil salinization, covering ~453 km², accounting for 20.5% of the total area. In contrast, the vast desert and water areas around the irrigated area exhibited a low salinization-prone area of ~1726 km², accounting for 78.2% of the total irrigated area. (3) The comprehensive evaluation using the Logistic regression model was validated with field investigation, affirming its accuracy and reliability. This comprehensive quantitative assessment of soil salinization susceptibility provides a scientific basis for soil salinization prevention and control measures and for making informed decisions regarding the selection of reserved cultivated land resources in southern Xinjiang.

Key words: soil salinization, Logistic regression analysis, susceptibility evaluation, Tarim irrigation area, southern Xinjiang

蒋磊, 刘小龙, 郭帅, 何亮, 邢建磊, 郭俊杰. 基于Logistic回归分析的土壤盐渍化易发性评价——以新疆南疆塔里木灌区为例[J]. 干旱区地理, 2023, 46(11): 1858-1867.

JIANG Lei, LIU Xiaolong, GUO Shuai, HE Liang, XING Jianlei, GUO Junjie. Evaluation of soil salinization susceptibility based on Logistic regression analysis: A case of Tarim irrigation area in southern Xinjiang[J]. Arid Land Geography, 2023, 46(11): 1858-1867.

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参考文献 32

[1]	李丽君, 张小清, 陈长清, 等. 近20 a塔里木河下游输水对生态环境的影响[J]. 干旱区地理, 2018, 41(2): 238-247.
	[ Li Lijun, Zhang Xiaoqing, Chen Changqing, et al. Ecological effects of water conveyance on the lower reaches of Tarim River in recent twenty years[J]. Arid Land Geography, 2018, 41(2): 238-247. ]
[2]	杨红梅, 徐海量, 樊自立, 等. 塔里木河下游表层土壤盐分空间变异和格局分析[J]. 中国沙漠, 2010, 30(3): 564-570.
	[ Yang Hongmei, Xu Hailiang, Fan Zili, et al. Spatial variability and pattern of surface soil salinity in the lower reaches of the Tarim River[J]. Journal of Desert Research, 2010, 30(3): 564-570. ]
[3]	田长彦, 买文选, 赵振勇. 新疆干旱区盐碱地生态治理关键技术研究[J]. 生态学报, 2016, 36(22): 7064-7068.
	[ Tian Changyan, Mai Wenxuan, Zhao Zhenyong. Study on key technologies of ecological management of saline alkali land in arid area of Xinjiang[J]. Acta Ecologica Sinica, 2016, 36(22): 7064-7068. ]
[4]	赵振勇, 田长彦, 张科, 等. 盐碱地生物改良与盐生植物资源综合利用[J]. 高科技与产业化, 2020(9): 64-66.
	[ Zhao Zhenyong, Tian Changyan, Zhang Ke, et al. Biological improvement of saline-alkali land and comprehensive utilization of halophyte resources[J]. High-Technology & Commercialization, 2020(9): 64-66. ]
[5]	Tomaz A, Palma P, Fialho S, et al. Risk assessment of irrigation-related soil salinization and sodification in Mediterranean areas[J]. Water, 2020, 12(12): 3569, doi: 10.3390/w12123569.
[6]	Castro F C, Araújo J F, dos Santos A M. Susceptibility to soil salinization in the quilombola community of Cupira-Santa Maria da Boa Vista-Pernambuco-Brazil[J]. Catena, 2019, 179: 175-183. doi: 10.1016/j.catena.2019.04.005
[7]	Ma L G, Ma F L, Li J D, et al. Characterizing and modeling regional-scale variations in soil salinity in the arid oasis of Tarim Basin, China[J]. Geoderma, 2017, 305: 1-11. doi: 10.1016/j.geoderma.2017.05.016
[8]	Alexandre C, Borralho T, Durão A. Evaluation of salinization and sodification in irrigated areas with limited soil data: Case study in southern Portugal[J]. Spanish Journal of Soil Science, 2018, 8: 102-120.
[9]	谢聪慧, 吴世新, 林娟, 等. 基于PSO-PNN模型的喀什噶尔绿洲耕地盐渍化分析[J]. 干旱区地理, 2022, 45(5): 1547-1558.
	[ Xie Conghui, Wu Shixin, Lin Juan, et al. Analysis of cultivated land salinization in Kashgar Oasis based on PSO-PNN model[J]. Arid Land Geography, 2022, 45(5): 1547-1558. ]
[10]	姚远, 丁建丽, 张芳, 等. 基于遥感的塔里木盆地北缘绿洲干湿季土地盐渍化监测[J]. 应用生态学报, 2013, 24(11): 3213-3220. pmid: 24564152
	[ Yao Yuan, Ding Jianli, Zhang Fang, et al. Monitoring of soil salinization in northern Tarim Basin, Xinjiang of China in dry and wet seasons based on remote sensing[J]. Chinese Journal of Applied Ecology, 2013, 24(11): 3213-3220. ] pmid: 24564152
[11]	Grundy M J, Silburn D M, Chamberlain T. A risk framework for preventing salinity[J]. Environmental Hazards, 2007, 7(2): 97-105. doi: 10.1016/j.envhaz.2007.07.004
[12]	Zhou D, Lin Z L, Liu L M, et al. Assessing secondary soil salinization risk based on the PSR sustainability framework[J]. Journal of Environmental Management, 2013, 128: 642-654. doi: 10.1016/j.jenvman.2013.06.025 pmid: 23845958
[13]	牛增懿, 丁建丽, 李艳华, 等. 基于高分一号影像的土壤盐渍化信息提取方法[J]. 干旱区地理, 2016, 39(1): 171-181.
	[ Niu Zengyi, Ding Jianli, Li Yanhua, et al. Soil salinization information extraction method based on GF-1 image[J]. Arid Land Geography, 2016, 39(1): 171-181. ]
[14]	蒋磊, 赵毅, 张鹏伟, 等. 基于氢氧稳定同位素特征的潜水蒸发影响程度研究[J]. 干旱区研究, 2022, 39(6): 1793-1800.
	[ Jiang Lei, Zhao Yi, Zhang Pengwei, et al. Study on influence degree of phreatic evaporation based on hydrogen and oxygen isotope characteristics[J]. Arid Zone Research, 2022, 39(6): 1793-1800. ]
[15]	周龙, 杨鹏年, 王永鹏, 等. 塔里木河下游河段耗水特征与输水方式演变研究[J]. 干旱区研究, 2022, 39(1): 144-154.
	[ Zhou Long, Yang Pengnian, Wang Yongpeng, et al. Characteristics of water consumption and the evolution of water delivery methods in the lower reach of the Tarim River[J]. Arid Zone Research, 2022, 39(1): 144-154. ]
[16]	马松增, 史明昌, 杨贵森, 等. 基于GIS的土地利用时空动态变化分析——以塔里木盆地农垦区为例[J]. 水土保持研究, 2013, 20(1): 177-181.
	[ Ma Songzeng, Shi Mingchang, Yang Guisen, et al. Analysis on spatiotemporal change of land use based on GlS technology: Taking Xinjiang Tarim Basin as an example[J]. Research of Soil and Water Conservation, 2013, 20(1): 177-181. ]
[17]	陈亚宁, 崔旺诚, 李卫红, 等. 塔里木河的水资源利用与生态保护[J]. 地理学报, 2003, 58(2): 215-222. doi: 10.11821/xb200302008
	[ Chen Yaning, Cui Wang cheng, Li Weihong, et al. Utilization of water resources and ecological protection in the Tarim River[J]. Acta Geographica Sinica, 2003, 58(2): 215-222. ] doi: 10.11821/xb200302008
[18]	谢海霞, 龚江, 何帅. 膜下滴灌农田灌溉量对土壤盐分类型的影响[J]. 河南农业科学, 2013, 42(8): 45-47.
	[ Xie Haixia, Gong Jiang, He Shuai. Influence of irrigation amount of mulched drip irrigation on type of soil salt[J]. Journal of Henan Agricultural Sciences, 2013, 42(8): 45-47. ]
[19]	陈亚宁, 陈忠升. 干旱区绿洲演变与适宜发展规模研究——以塔里木河流域为例[J]. 中国生态农业学报, 2013, 21(1): 134-140.
	[ Chen Yaning, Chen Zhongsheng. Analysis of oasis evolution and suitable development scale for arid regions: A case study of the Tarim River Basin[J]. Chinese Journal of Eco-Agriculture, 2013, 21(1): 134-140. ]
[20]	王雪冬, 张超彪, 王翠, 等. 基于Logistic回归与随机森林的和龙市地质灾害易发性评价[J]. 吉林大学学报(地球科学版), 2022, 52(6): 1957-1970.
	[ Wang Xuedong, Zhang Chaobiao, Wang Cui, et al. Geological disaster susceptibility in Helong City based on Logistic regression and random forest[J]. Journal of Jilin University (Earth Science Edition), 2022, 52(6): 1957-1970. ]
[21]	阿如旱, 都来, 盛艳, 等. 基于Logistic回归模型的内蒙古多伦县土地沙漠化驱动力分析[J]. 干旱区地理, 2019, 42(1): 137-143.
	[ Aruhan, Du Lai, Sheng Yan, et al. Driving forces on land desertification in Duolun County lnner Mongolia based on Logistic regress model[J]. Arid Land Geography, 2019, 42(1): 137-143. ]
[22]	高会, 谭莉梅, 刘鹏, 等. 基于二分类Logistic回归模型的太行山丘陵区县域耕地资源潜力估算[J]. 中国生态农业学报, 2017, 25(4): 490-497.
	[ Gao Hui, Tan Limei, Liu Peng, et al. Estimation of arable land resources potential in hilly area of Taihang Mountain based on binary Logistic regression model[J]. Chinese Journal of Eco-Agriculture, 2017, 25(4): 490-497. ]
[23]	樊芷吟, 苟晓峰, 秦明月, 等. 基于信息量模型与Logistic回归模型耦合的地质灾害易发性评价[J]. 工程地质学报, 2018, 26(2): 340-347.
	[ Fan Zhiyin, Gou Xiaofeng, Qin Mingyue, et al. Information and Logistic regression models based coupling analysis for susceptibility of geological hazards[J]. Journal of Engineering Geology, 2018, 26(2): 340-347. ]
[24]	黄湘, 陈亚宁, 马建新. 西北干旱区典型流域生态系统服务价值变化[J]. 自然资源学报, 2011, 26(8): 1364-1376. doi: 10.11849/zrzyxb.2011.08.011
	[ Huang Xiang, Chen Yaning, Ma Jianxin. Analysis of the ecosystem services value of the typical river basin in desert areas of northwest China[J]. Journal of Natural Resources, 2011, 26(8): 1364-1376. ] doi: 10.11849/zrzyxb.2011.08.011
[25]	邓铭江, 樊自立, 徐海量, 等. 塔里木河流域生态功能区划研究[J]. 干旱区地理, 2017, 40(4): 705-717.
	[ Deng Mingjiang, Fan Zili, Xu Hailiang, et al. Ecological function regionalization of Tarim River Basin[J]. Arid Zone Research, 2017, 40(4): 705-717. ]
[26]	Seydehmet J, Lü G H, Abliz A, et al. Irrigation salinity risk assessment and mapping in arid oasis, northwest China[J]. Water, 2018, 10(7): 966, doi: 10.3390/w10070966.
[27]	Bouksila F, Bahri A, Berndtsson R, et al. Assessment of soil salinization risks under irrigation with brackish water in semiarid Tunisia[J]. Environmental and Experimental Botany, 2013, 92: 176-185. doi: 10.1016/j.envexpbot.2012.06.002
[28]	Kosmas C, Kairis O, Karavitis C, et al. Evaluation and selection of indicators for land degradation and desertification monitoring: Methodological approach[J]. Environmental Management, 2014, 54: 951-970. pmid: 23797485
[29]	史晓杰, 张玉, 孙涛, 等. 基于遗传人工神经网络的土壤盐渍化敏感性分析模型[J]. 水文地质工程地质, 2008(4): 116-119.
	[ Shi Xiaojie, Zhang Yu, Sun Tao, et al. Soil salinization sensitivity analysis model based on genetic artificial neural network[J]. Hydrogeology & Engineering Geology, 2008(4): 116-119. ]
[30]	谷新保, 虎胆·吐马尔白, 翟永先, 等. 主成分分析法在膜下滴灌不同年限棉田土壤表层盐渍化评价中的应用[J]. 新疆农业科学, 2009, 46(5): 935-940.
	[ Guo Xinbao, Tumaerbai Hudan, Zhai Yongxian, et al. Application of salinization evaluation to soil upper layer of cotton field under film irrigation by main component analytical method in different years[J]. Hydrogeology & Engineering Geology, 2009, 46(5): 935-940. ]
[31]	王水献, 董新光, 刘丰. 层次分析法在新疆平原灌区土壤盐渍化研究中的应用[J]. 干旱区资源与环境, 2007, 21(4): 111-116.
	[ Wang Shuixian, Dong Xinguang, Liu Feng, et al. Application of analytic hierarchy process on the soil salinization in irrigation areas of Xinjiang plain[J]. Journal of Arid Land Resources and Environment, 2007, 21(4): 111-116. ]
[32]	陈朝亮, 张文君, 钱静, 等. 基于改进Logistic回归模型在地质灾害评价中的应用[J]. 环境科学与技术, 2019, 42(4): 188-193, 213.
	[ Chen Caoliang, Zhang Wenjun, Qian Jing, et al. Application of improved Logistic regression model in geological hazard evaluation[J]. Environmental Science & Technology, 2019, 42(4): 188-193, 213. ]

单因素分类		单元数	盐渍化点	W⁺	W⁺方差	W^-	W^-方差	C值	C值方差	显著性指标
地下水TDS	<1 g·L^-1	793	26	0.10	0.20	-0.06	0.16	0.15	0.26	0.60
	1~3 g·L^-1	40	1	-0.18	1.01	0.00	0.13	-0.18	1.02	-0.18
	3~10 g·L^-1	616	12	-0.44	0.29	0.13	0.14	-0.57	0.32	-1.76
	>10 g·L^-1	760	27	0.18	0.20	-0.11	0.16	0.29	0.25	1.13
地下水埋深	<2 m	927	39	0.36	0.16	-0.36	0.19	0.71	0.25	2.81
	2~5 m	652	16	-0.20	0.25	0.07	0.14	-0.28	0.29	-0.95
	5~10 m	459	11	-0.23	0.31	0.05	0.14	-0.28	0.33	-0.83
	>10 m	171	0	0.00	0.00	0.00	0.00	0.00	0.00	0.00
土壤质地	砂土	628	3	-1.86	0.58	0.30	0.13	-2.16	0.59	-3.64
	壤质砂土	808	27	0.12	0.20	-0.07	0.16	0.19	0.25	0.74
	砂质壤土	6	1	1.85	1.09	-0.01	0.13	1.86	1.10	1.69
	粉砂质黏土	33	3	1.18	0.61	-0.03	0.13	1.21	0.62	1.96
	黏土	622	32	0.57	0.18	-0.34	0.17	0.91	0.25	3.62
地貌类型	冲积平原	59	5	1.11	0.47	-0.05	0.13	1.16	0.49	2.39
	湖积平原	1446	57	0.29	0.14	-0.95	0.34	1.24	0.36	3.42
	风积沙漠	588	4	-1.50	0.50	0.26	0.13	-1.76	0.52	-3.40
土地利用类型	耕地	385	8	-0.37	0.36	0.06	0.13	-0.44	0.38	-1.15
	园地	134	6	0.61	0.70	-0.01	0.13	0.62	0.71	0.86
	林地	20	2	1.31	1.06	-0.01	0.13	1.32	1.07	1.24
	草地	190	22	1.45	0.23	-0.32	0.15	1.77	0.27	6.48
	建设用地	69	2	-0.03	0.72	0.00	0.13	-0.04	0.73	-0.05
	其他土地	1204	26	-0.08	0.63	-0.01	0.14	-0.07	0.66	0.06