农户尺度的黄土高原乡村干旱脆弱性及适应机理

doi:10.18306/dlkxjz.2017.10.010

摘要/Abstract

摘要：

干旱脆弱性及人类对干旱的适应机理分析是干旱及半干旱地区人地关系研究的重要内容,也是西北地区乡村人地系统可持续性研究的新视角。本文运用Turner脆弱性分析框架,将其改进应用到黄土高原乡村农户的干旱脆弱性及其适应领域,选取榆中县和长武县气象数据和农户调查数据,应用主成分分析、综合指数法、差异性分析和鲁棒性分析等方法分别对指标权重、农户干旱脆弱性指数及其差异性与脆弱性指数的不确定性进行分析与检验,并从适应能力、适应策略和适应模式三个层面揭示适应机理。主要结论为：①中连川乡农户干旱脆弱性指数大于洪家镇,且不同村落间农户干旱脆弱性指数差异显著;②农户干旱适应机理为暴露—敏感性影响农户收入,农户生计系统是适应干旱暴露扰动的决定因子,农户类型、生计方式、土地利用、灌溉设施和政策扶持的差异性产生不同的适应模式和适应效果;③农户干旱脆弱性指数排名出现频率较高且排名变化范围较小,具有较强的鲁棒性,表明农户干旱脆弱性计算结果具有稳健性。

关键词: 农户干旱脆弱性, 适应机理, 鲁棒性分析, 黄土高原

Abstract:

Analyzing vulnerability and adaptation to drought is an important part of the study on human-environment relationship in arid and semiarid regions. It has also become the new viewpoint of human-environment system sustainability research in the rural areas of northwestern China. This research adopted the framework of vulnerability analysis proposed by Turner and adapted it for analyzing rural household vulnerability and adaptation to drought on the Loess Plateau. It integrated and analyzed meteorological data and questionnaire survey to examine household drought vulnerability and difference and inspected the uncertainty of the results applying Principal Component Analysis, Difference Analysis, and Robustness Analysis methods. This study also revealed the mechanism of adaptation to drought with regard to adaptive capacity, adaptation strategies, and adaptation mode. The main results include: (1) there exist significant differences between the villages in drought vulnerability index values—the vulnerability value of Zhonglianchuan is higher than that of Hongjia; (2) with regard to adaptation mechanism, exposure-sensitivity influences farmer income, farmer livelihood system determinates adaptive capacity, and differences in the type of household, livelihood strategy, land use, irrigation facilities, and policy support generate different adaptation modes and consequence; (3) the high frequency and narrow range of household drought vulnerability index indicates relatively high robustness of the result.

Key words: rural household drought vulnerability, adaptation mechanism, robustness analysis, Loess Plateau

石育中, 王俊, 王子侨, 鲁大铭, 杨新军. 农户尺度的黄土高原乡村干旱脆弱性及适应机理[J]. 地理科学进展, 2017, 36(10): 1281-1293.

Yuzhong SHI, Jun WANG, Ziqiao WANG, Daming LU, Xinjun YANG. Rural household vulnerability to drought and adaptation mechanism on the Loess Plateau[J]. PROGRESS IN GEOGRAPHY, 2017, 36(10): 1281-1293.

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参考文献 50

[1]	鲍超, 方创琳. 2008. 干旱区水资源开发利用对生态环境影响的研究进展与展望[J]. 地理科学进展, 27(3): 38-46. doi: 10.11820/dlkxjz.2008.03.006
	[Bao C, Fang C L.2008. Impact of water resources exploitation and utilization on eco-environment in arid area: Progress and prospect[J]. Progress in Geography, 27(3): 38-46.] doi: 10.11820/dlkxjz.2008.03.006
[2]	程静, 陶建平. 2010. 全球气候变暖背景下农业干旱灾害与粮食安全: 基于西南五省面板数据的实证研究[J]. 经济地理, 30(9): 1524-1528.
	[Cheng J, Tao J P.2010. Agricultural drought disaster and food security under the background of global warming: Based on panel data of five provinces of Southwest China[J]. Economic Geography, 30(9): 1524-1528.]
[3]	高超, 金凤君, 雷军, 等. 2012. 干旱区绿洲城市经济系统脆弱性评价研究[J]. 经济地理, 32(8): 43-49.
	[Gao C, Jin F J, Lei J, et al.2012. Vulnerability assessment of economic system of oasis cities in arid area[J]. Economic Geography, 32(8): 43-49.]
[4]	郭永锐, 张捷. 2015. 社区恢复力研究进展及其地理学研究议题[J]. 地理科学进展, 34(1): 100-109. doi: 10.11820/dlkxjz.2015.01.012
	[Guo Y R, Zhang J.2015. Research progress and themes of geography on community resilience[J]. Progress in Geography, 34(1): 100-109.] doi: 10.11820/dlkxjz.2015.01.012
[5]	何斌, 武建军, 吕爱锋. 2010. 农业干旱风险研究进展[J]. 地理科学进展, 29(5): 557-564. doi: 10.11820/dlkxjz.2010.05.007
	[He B, Wu J J, Lv A F.2010. New advances in agricultural drought risk study[J]. Progress in Geography, 29(5): 557-564.] doi: 10.11820/dlkxjz.2010.05.007
[6]	黄晓军, 黄馨, 崔彩兰, 等. 2014. 社会脆弱性概念、分析框架与评价方法[J]. 地理科学进展, 33(11): 1512-1525. doi: 10.11820/dlkxjz.2014.10.008
	[Huang X J, Huang X, Cui C L, et al.2014. The concept, analytical framework and assessment method of social vulnerability[J]. Progress in Geography, 33(11): 1512-1525.] doi: 10.11820/dlkxjz.2014.10.008
[7]	蒋维, 王俊, 杨新军, 等. 2011. 黄土高原农村社会—生态系统体制转换初探: 以陕西省长武县洪家镇为例[J]. 人文地理, 26(1): 56-60.
	[Jiang W, Wang J, Yang X J, et al.2011. A study of regime shift of rural social-ecological system in Loess Plateau: A case study of Hongjia Town of Changwu County, Shaanxi Province[J]. Human Geography, 26(1): 56-60.]
[8]	李芬, 于文金, 张建新, 等. 2011. 干旱灾害评估研究进展[J]. 地理科学进展, 30(7): 891-898. doi: 10.11820/dlkxjz.2011.07.015
	[Li F, Yu W J, Zhang J X, et al.2011. Review of drought disaster evaluation[J]. Progress in Geography, 30(7): 891-898.] doi: 10.11820/dlkxjz.2011.07.015
[9]	刘卫东, 谭韧骠. 2009. 杭州城市蔓延评估体系及其治理对策[J]. 地理学报, 64(4): 417-425. doi: 10.3321/j.issn:0375-5444.2009.04.004
	[Liu W D, Tan R B.2009. Evaluation system and control mechanism of urban sprawl: A case study of Hangzhou[J]. Acta Geographica Sinica, 64(4): 417-425.] doi: 10.3321/j.issn:0375-5444.2009.04.004
[10]	龙花楼, 刘彦随, 张小林, 等. 2014. 农业地理与乡村发展研究新近进展[J]. 地理学报, 69(8): 1145-1158. doi: 10.11821/dlxb201408010
	[Long H L, Liu Y S, Zhang X L, et al.2014. Recent progress in agricultural geography and rural development research[J]. Acta Geographica Sinica, 69(8): 1145-1158.] doi: 10.11821/dlxb201408010
[11]	马琼, 张勃, 王东, 等. 2014. 1960-2012年甘肃黄土高原干旱时空变化特征分析: 基于标准化降水蒸散指数[J]. 资源科学, 36(9): 1834-1841.
	[Ma Q, Zhang B, Wang D, et al.2014. The temporal and spatial distribution of drought on the Loess Plateau based on the standardized precipitation evapotranspiration index from 1960 to 2012[J]. Resources Science, 36(9): 1834-1841.]
[12]	邱海军, 曹明明, 郝俊卿, 等. 2013. 1950-2010年中国干旱灾情频率—规模关系分析[J]. 地理科学, 33(5): 576-580.
	[Qiu H J, Cao M M, Hao J Q, et al.2013. Relationship between frequency and magnitude of drought damage in China in 1950-2010[J]. Scientia Geographica Sinica, 33(5): 576-580.]
[13]	王亚茹, 赵雪雁, 张钦, 等. 2016. 高寒生态脆弱区农户的气候变化适应策略: 以甘南高原为例[J]. 地理研究, 35(7): 1273-1287.
	[Wang Y R, Zhao X Y, Zhang Q, et al.2016. Farmers' climate change adaptation strategies in an ecologically vulnerable alpine region: A case of Gannan Plateau[J]. Geographical Research, 35(7): 1273-1287.]
[14]	杨新军, 张慧, 王子侨. 2015. 基于情景分析的西北农村社会-生态系统脆弱性研究: 以榆中县中连川乡为例[J]. 地理科学, 35(8): 952-959.
	[Yang X J, Zhang H, Wang Z Q.2015. Vulnerability assessment of rural social-ecological system based on scenario analysis: A case study of Zhonglianchuan Town in Yuzhong County[J]. Scientia Geographica Sinica, 35(8): 952-959.]
[15]	喻忠磊. 杨新军, 杨涛. 2013. 乡村农户适应旅游发展的模式及影响机制: 以秦岭金丝峡景区为例[J]. 地理学报, 68(8): 1143-1156.
	[Yu Z L, Yang X J, Yang T.2013. Exploring conditions, determinants and mechanisms of rural households' adaptability to tourism development: A case study of Jinsixia in Qinling Mountains[J]. Acta Geographica Sinica, 68(8): 1143-1156.]
[16]	Alshehri S A, Rezgui Y, Li H J.2015. Disaster community resilience assessment method: A consensus-based Delphi and AHP approach[J]. Natural Hazards, 78(1): 395-416. doi: 10.1007/s11069-015-1719-5
[17]	Aryal S, Cockfield G, Maraseni T N.2014. Vulnerability of Himalayan transhumant communities to climate change[J]. Climatic Change, 125(2): 193-208. doi: 10.1007/s10584-014-1157-5
[18]	Ashraf M, Routray J K, Saeed M.2014. Determinants of farmers' choice of coping and adaptation measures to the drought hazard in Northwest Balochistan, Pakistan[J]. Natural Hazards, 73(3): 1451-1473. doi: 10.1007/s11069-014-1149-9
[19]	Bizimana J P, Twarabamenye E, Kienberger S.2015. Assessing the social vulnerability to malaria in Rwanda[J]. Malaria Journal, 14(1): 2. doi: 10.1186/1475-2875-14-2 pmid: 25566988
[20]	Brooks N, Adger W N, Kelly P M.2005. The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation[J]. Global Environmental Change, 15(2): 151-163. doi: 10.1016/j.gloenvcha.2004.12.006
[21]	de Grosbois D, Plummer R.2015. Problematizing water vulnerability indices at a local level: A critical review and proposed solution[J]. Water Resources Management, 29(14): 5015-5035. doi: 10.1007/s11269-015-1101-0
[22]	Derbile E K.2013. Reducing vulnerability of rain-fed agriculture to drought through indigenous knowledge systems in North-eastern Ghana[J]. International Journal of Climate Change Strategies and Management, 5(1): 71-94. doi: 10.1108/17568691311299372
[23]	Eakin H, Bojórquez-Tapia L A.2008. Insights into the composition of household vulnerability from multicriteria decision analysis[J]. Global Environmental Change, 18(1): 112-127. doi: 10.1016/j.gloenvcha.2007.09.001
[24]	Fang Y P, Zhao C, Rasul G, et al.2016. Rural household vulnerability and strategies for improvement: An empirical analysis based on time series[J]. Habitat International, 53: 254-264. doi: 10.1016/j.habitatint.2015.11.035
[25]	Gbetibouo G A, Ringler C.2009. Mapping South African farming sector vulnerability to climate change and variability: A subnational assessment[R]. IFPRI Discussion Papers 00885.
[26]	Harrison P A, Holman I P, Berry P M.2015. Assessing cross-sectoral climate change impacts, vulnerability and adaptation: An introduction to the CLIMSAVE project[J]. Climatic Change, 128(3-4): 153-167. doi: 10.1007/s10584-015-1324-3
[27]	Hiete M, Merz M, Comes T, et al.2012. Trapezoidal fuzzy DEMATEL method to analyze and correct for relations between variables in a composite indicator for disaster resilience[J]. OR Spectrum, 34(4): 971-995. doi: 10.1007/s00291-011-0269-9
[28]	Hung L S, Wang C M, Yarnal B.2016. Vulnerability of families and households to natural hazards: A case study of storm surge flooding in Sarasota County, Florida[J]. Applied Geography, 76: 184-197. doi: 10.1016/j.apgeog.2016.09.021
[29]	Imperiale A J, Vanclay F.2016. Experiencing local community resilience in action: Learning from post-disaster communities[J]. Journal of Rural Studies, 47: 204-219. doi: 10.1016/j.jrurstud.2016.08.002
[30]	Khayyati M, Aazami M.2016. Drought impact assessment on rural livelihood systems in Iran[J]. Ecological Indicators, 69: 850-858. doi: 10.1016/j.ecolind.2016.05.039
[31]	Kondyli J.2010. Measurement and evaluation of sustainable development: A composite indicator for the islands of the North Aegean region, Greece[J]. Environmental Impact Assessment Review, 30(6): 347-356. doi: 10.1016/j.eiar.2009.08.006
[32]	Lei Y D, Wang J A, Yue Y J, et al.2014. Rethinking the relationships of vulnerability, resilience, and adaptation from a disaster risk perspective[J]. Natural Hazards, 70(1): 609-627. doi: 10.1007/s11069-013-0831-7
[33]	Li Y, Conway D, Wu Y J, et al.2013. Rural livelihoods and climate variability in Ningxia, Northwest China[J]. Climatic Change, 119(3-4): 891-904. doi: 10.1007/s10584-013-0765-9
[34]	Lindoso D P, Rocha J D, Debortoli N, et al.2014. Integrated assessment of smallholder farming's vulnerability to drought in the Brazilian Semi-arid: A case study in Ceará[J]. Climatic Change, 127(1): 93-105. doi: 10.1007/s10584-014-1116-1
[35]	Liu X Q, Wang Y L, Peng J, et al.2013. Assessing vulnerability to drought based on exposure, sensitivity and adaptive capacity: A case study in middle Inner Mongolia of China[J]. Chinese Geographical Science, 23(1): 13-25. doi: 10.1007/s11769-012-0583-4
[36]	Merritt W S, Patch B, Reddy V R, et al.2016. Modelling livelihoods and household resilience to droughts using Bayesian networks[J]. Environment, Development and Sustainability, 18(2): 315-346. doi: 10.1007/s10668-015-9650-1
[37]	Naumann G, Barbosa P, Garrote L, et al.2013. Exploring drought vulnerability in Africa: An indicator based analysis to inform early warning systems[J]. Hydrology and Earth System Sciences Discussions, 10(10): 12217-12254. doi: 10.5194/hess-18-1591-2014
[38]	Perch-Nielsen S L.2010. The vulnerability of beach tourism to climate change: An index approach[J]. Climatic Change, 100(3-4): 579-606. doi: 10.1007/s10584-009-9692-1
[39]	Piya L, Joshi N P, Maharjan K L.2016. Vulnerability of Chepang households to climate change and extremes in the Mid-Hills of Nepal[J]. Climatic Change, 135(3-4): 521-537. doi: 10.1007/s10584-015-1572-2
[40]	Ryu J, Lee D K, Park C, et al.2016. Assessment of the vulnerability of industrial parks to flood in South Korea[J]. Natural Hazards, 82(2): 811-825. doi: 10.1007/s11069-016-2222-3
[41]	Saisana M, Saltelli A, Tarantola S.2005. Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators[J]. Journal of the Royal Statistical Society: Statistics in Society, 168(2): 307-323. doi: 10.1111/j.1467-985X.2005.00350.x
[42]	Şener E, Şener Ş.2015. Evaluation of groundwater vulnerability to pollution using fuzzy analytic hierarchy process method[J]. Environmental Earth Sciences, 73(12): 8405-8424. doi: 10.1007/s12665-014-4001-3
[43]	Singh R K, Murty H R, Gupta S K, et al.2012. An overview of sustainability assessment methodologies[J]. Ecological Indicators, 15(1): 281-299. doi: 10.1016/j.ecolind.2008.05.011
[44]	Tánago I G, Urquijo J, Blauhut V, et al.2016. Learning from experience: A systematic review of assessments of vulnerability to drought[J]. Natural Hazards, 80(2): 951-973. doi: 10.1007/s11069-015-2006-1
[45]	Tate E.2012. Social vulnerability indices: A comparative assessment using uncertainty and sensitivity analysis[J]. Natural Hazards, 63(2): 325-347. doi: 10.1007/s11069-012-0152-2
[46]	Thomas T, Jaiswal R K, Galkate R, et al.2016. Drought indicators-based integrated assessment of drought vulnerability: A case study of Bundelkhand droughts in central India[J]. Natural Hazards, 81(3): 1627-1652. doi: 10.1007/s11069-016-2149-8
[47]	Turner II B L, Kasperson R E, Matson P A, et al.2003. A framework for vulnerability analysis in sustainability science[J]. Proceedings of the National Academy of Sciences of the United States of America, 100(14): 8074-8079. doi: 10.1073/pnas.1231335100 pmid: 12792023
[48]	Udmale P D, Ichikawa Y, Manandhar S, et al.2015. How did the 2012 drought affect rural livelihoods in vulnerable areas? Empirical evidence from India[J]. International Journal of Disaster Risk Reduction, 13: 454-469. doi: 10.1016/j.ijdrr.2015.08.002
[49]	Wittrock V, Kulshreshtha S N, Wheaton E.2011. Canadian prairie rural communities: Their vulnerabilities and adaptive capacities to drought[J]. Mitigation and Adaptation Strategies for Global Change, 16(3): 267-290. doi: 10.1007/s11027-010-9262-x
[50]	Wu D, Yan D H, Yang G Y, et al.2013. Assessment on agricultural drought vulnerability in the Yellow River basin based on a fuzzy clustering iterative model[J]. Natural Hazards, 67(2): 919-936. doi: 10.1007/s11069-013-0617-y

	维度	初始指标层		优化指标层	权重
脆弱性	暴露	年平均降水年最长连续未降水天数年平均气温		年平均降水年最长连续未降水天数年平均气温	0.63 0.61 0.48
	敏感性	粮食产量畜果蔬收入比例获取水资源的途径是否为雨养农业		粮食产量畜果蔬收入比例获取水资源的途径	0.59 0.50 -0.64
	适应能力	物质资本	住房条件、家庭手机数量、与道路的距离	住房类型最高学历存款生计多样性社会网络	0.28 -0.20 0.22 0.38 0.19
		自然资本	粮食种植面积、经济林种植面积、果蔬种植面积、灌溉面积
		人力资本	最高学历、依赖比例、培训次数
		金融资本	家庭人均收入、存款、生计多样性、牲畜禽的数量
		社会资本	社会网络、信贷途径、社会扶助

村名	E	S	AC	V	R_v	村名	E	S	AC	V	R_v
风口村_洪	0.556	-1.453	0.430	-1.327	1	山兴村_洪	0.556	-0.990	0.115	-0.549	12
关路村_洪	0.556	-1.400	0.374	-1.218	2	康家窑_中	-0.513	-0.229	-0.145	-0.597	13
回朝村_洪	0.556	-1.348	0.417	-1.209	3	西翻岔_中	-0.513	0.169	0.001	-0.345	14
王东村_洪	0.556	-1.404	0.350	-1.198	4	鞑靼窑_中	-0.513	1.286	-0.556	1.329	15
公主村_洪	0.556	-1.351	0.322	-1.117	5	高窑沟_中	-0.513	1.975	-0.913	2.375	16
上柳村_洪	0.556	-1.402	0.231	-1.077	6	满都沟_中	-0.513	2.931	-0.307	2.725	17
庄里村_洪	0.556	-1.407	0.132	-0.983	7	张家圈_中	-0.513	2.346	-0.952	2.785	18
姜曹村_洪	0.556	-1.425	0.102	-0.971	8	坟固湾_中	-0.513	3.136	-0.541	3.164	19
孔头村_洪	0.556	-1.357	0.156	-0.957	9	细岭子_中	-0.513	3.519	-0.488	3.494	20
下柳村_洪	0.556	-1.359	0.057	-0.860	10	撒拉沟_中	-0.513	3.949	-0.595	4.031	21
曹公村_洪	0.556	-1.261	-0.072	-0.633	11

	方差方程的Levene检验		均值方程的t检验
	F	Sig.	t	df	Sig.	均值差值	标准误差值
E 假设方差相等假设方差不相等	4.63	0.04	72.04 61.83	19.00 8.00	0.00 0.00	1.07 1.07	0.00 0.00
S 假设方差相等假设方差不相等	24.65	0.00	-8.25 -7.10	19.00 8.08	0.00 0.00	-3.47 -3.47	0.42 0.49
AC 假设方差相等假设方差不相等	2.64	0.12	6.81 6.22	19.00 11.07	0.00 0.00	0.72 0.72	0.11 0.12
V 假设方差相等假设方差不相等	20.48	0.00	-6.54 -5.65	19.00 8.25	0.00 0.00	-3.12 -3.12	0.48 0.55

	方差方程的Levene检验		均值方程的t检验
	F	Sig.	t	df	Sig.	均值差值	标准误差值
B 假设方差相等假设方差不相等	3.651	0.071	1.065 0.939	19 9.155	0.300 0.372	0.313 0.313	0.029 0.033
E 假设方差相等假设方差不相等	2.878	0.106	2.928 2.666	19 10.828	0.009 0.022	0.257 0.257	0.088 0.096
S 假设方差相等假设方差不相等	0.095	0.762	6.372 6.030	19 13.358	0.000 0.000	0.383 0.383	0.060 0.064
L 假设方差相等假设方差不相等	17.223	0.001	7.885 6.788	19 8.111	0.000 0.000	0.368 0.368	0.047 0.054
SN 假设方差相等假设方差不相等	0.115	0.738	0.533 0.542	19 18.379	0.600 0.594	0.020 0.020	0.037 0.036