地理科学进展  2015 , 34 (8): 1009-1018 https://doi.org/10.18306/dlkxjz.2015.08.008

农村发展

中国农村家庭的震后生活恢复过程研究

王瑛12, 林齐根12, 宋崇振12, 林乐12, 邹振华12, 陈浩1, 李娟1

1. 北京师范大学环境演变与自然灾害教育部重点实验室,北京 100875
2. 民政部—教育部减灾与应急管理研究院,北京 100875

Post-earthquake household recovery in rural China

WANG Ying12, LIN Qigen12, SONG Chongzhen12, LIN Le12, ZOU Zhenhua12, CHEN Hao1, LI Juan1

1. Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, Beijing 100875, China
2. Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China

版权声明:  2015 地理科学进展 《地理科学进展》杂志 版权所有

基金资助:  国家自然科学基金项目(41271544)“十二五”科技支撑计划项目(2012BAK10B03)

作者简介:

作者简介:王瑛(1974-),女,云南曲靖人,教授,主要从事灾后恢复和灾害风险评估研究,E-mail: wy@bnu.edu.cn

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摘要

灾后恢复是一个随时间不断变化发展的过程。本文以2008年四川汶川Ms8.0级地震为巨灾案例,2009年云南姚安Ms6.0级地震为中小型灾害案例,对农村灾区家庭进行随机入户调查。基于1094份有效问卷,运用恢复曲线,研究受灾家庭的生活恢复随时间变化的规律,对比不同灾害强度对恢复重建过程的影响。结果表明:家庭恢复过程具有明显的阶段性,根据恢复速率的变化,可分为应急期、恢复前期、恢复中期,恢复后期。巨灾和中小型灾害在恢复历时、恢复过程方面存在较大不同:中小型灾害生活恢复的过程相对较短,绝大多数重损家庭在灾后20个月完成恢复,中损家庭为18个月,二者相差较小;巨型灾害恢复过程整体历时较长,大多数中损家庭在灾后68个月才完成恢复,重损家庭的生活恢复整体滞后于中损家庭1年以上,并且随着时间的推移,受灾程度对恢复过程的影响越来越突出。

关键词: 震后 ; 生活恢复 ; 过程 ; 农村家庭 ; 恢复曲线 ; 中国

Abstract

Disaster recovery is a process that constantly changes over time. Using the 2008 Wenchuan Ms8.0 earthquake in Sichuan, China as a case of catastrophe, and the 2009 Yao'an Ms6.0 earthquake in Yunnan, China as a case of small and medium-sized disaster, a random household survey was conducted in the disaster-stricken rural areas. Based on 1094 valid questionnaires and the derived recovery curves and by comparing the effect of different disaster intensities on the process of restoration and reconstruction, this study examined how the earthquake-stricken families recovered over time. The findings of the research show that the process of household recovery clearly had different phases, and can be divided, according to the recovery rate, into emergency phase, early phase, middle phase, and late phase. A catastrophe differed from a small or medium-sized disaster in terms of recovery duration and recovery process: for a small or medium-sized disaster, the process of household recovery lasted 20 months for a severely affected family and 18 months for a moderately affected family, which means household recovery was relatively short. For a catastrophe, the process of household recovery lasted relatively long. The effect of the degree of influence on recovery process was increasingly more prominent. Recovery lasted 68 months for a moderately affected family from a catastrophe, while it takes one year longer for a severely affected family is about one year more, and thus become more difficult over time.

Keywords: post-earthquake ; domestic life recovery ; process ; rural households ; recovery curve

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王瑛, 林齐根, 宋崇振, 林乐, 邹振华, 陈浩, 李娟. 中国农村家庭的震后生活恢复过程研究[J]. , 2015, 34(8): 1009-1018 https://doi.org/10.18306/dlkxjz.2015.08.008

1 引言

根据灾害形成的3个过程(灾前、灾中、灾后),灾害管理周期可以分为灾前备灾、灾中应急、灾后恢复重建3个时期(史培军等, 2005)。其中灾后恢复重建工作尤为重要,灾区是地表各圈层相互作用最剧烈、人地关系最紧张的区域,灾后重建处置不当就可能成为影响社会和谐稳定的导火索,因此,科学合理的灾后恢复重建是协调灾区人地关系,促进灾区可持续发展的重要保障(王岱等, 2010; 樊杰等, 2014)。

灾后恢复重建是一个各种群体和机构(包括家庭、组织、企业、社区等)相互作用的过程,其目标就是使居民生活水平、经济发展水平和社会安全水平等恢复到(甚至超过)灾前的状态(Nigg, 1995; Mileti, 1999; Liu et al, 2008; Chang, 2010; Burton et al, 2011)。

许多研究表明,灾后恢复过程存在一定的时间阶段性,灾后恢复是有序的、可知的和可以预测的,每一个步骤在预定的时间段内有序发生(Haas et al, 1977; USDHS, 2004; Zhang et al, 2009; Smith, 2011)。根据恢复内容和恢复水平等,可将恢复重建过程分为不同的阶段。例如,城市灾后恢复过程可被划分为以下4个不同的阶段:①紧急救援阶段(emergency period),在灾后恢复过程中是一个很短的时期,但要求很强的灾害应对能力,以满足控制灾害破坏社会经济活动的需求;②恢复阶段(restoration period),是社会生活、生产能力的修补时期,使其满足基本的社会经济活动需求;③转移重建阶段(replacement reconstruction period),是灾后重建的过程,使社会经济活动达到或超过灾前水平;④ 纪念、更好和发展阶段(commemoration, betterment and development),是城市在灾后进一步发展和壮大的时期。上述4个阶段有时是相互重叠、交叉的。Kates等(2006)对上述理论加以应用,将卡特里娜飓风后新奥尔良的恢复重建进程分为应急(emergency)、恢复(restoration)、重建I(reconstruction I)、重建II(reconstruction II) 4个阶段。

从恢复内容上分,灾后恢复可分为:房屋恢复(Murao et al, 2007, 2010; Zhang et al, 2009)、生活恢复(Wang et al, 2012, 2014)、心理恢复(Toyabe et al, 2006; LaJoie et al, 2010)、人口恢复(Fussell et al, 2010; Stringfield, 2010; 高晓路等, 2010)和经济恢复(Robinson et al, 2008; Kuwata et al, 2010)。在上述恢复研究中,恢复曲线应用较为广泛。Schiff(1995)提出采用恢复曲线对生命线系统恢复的时间变化过程进行研究。Murao等(2007)利用中国台湾南投县的震后房屋恢复重建数据,绘制临时住所、公共设施、修复房屋、新房4种建筑类型的恢复曲线,发现不同类型房屋的时间恢复过程存在显著差异,因此,政府应制定有区别的重建规划。Murao等(2010)利用2004年印度洋海啸斯里兰卡灾区的跟踪调查数据和当地政府的恢复统计数据,绘制了灾区不同地区的居民转移安置房和永久性住房的恢复曲线,以这两类恢复曲线为工具,研究评价了斯里兰卡沿海各灾区的灾后平均恢复时间。Al-Nammari等(2009)对1989年洛马普列塔地震(Loma Prieta Earthquake)后古建筑恢复影响因素进行分析时,引入建筑物完成恢复时间,发现不同建筑结构、不同建筑功用、不同破坏级别的建筑物的恢复时间特征具有显著差异。Ganapati(2013)对土耳其Golcuk地区的灾后恢复采用的是永久性住房的恢复;Rathfon等(2013)对Punta Gorda在Charley飓风后的恢复研究也采用了房屋恢复。Kuwata等(2010)则将恢复曲线应用于商业恢复重建过程的研究,通过调查印度洋海啸影响区内的公司业主和相关人员,获得商业建筑、设备以及相关生命线工程的恢复重建数据,绘制与商业相关的建筑、设备、电力系统、供水系统等受损要素的恢复曲线,发现商业设施的恢复要滞后于相关生命线系统的恢复。

统计数据表明,地震灾害是中国死亡人数最多、损失最大的自然灾害,对农村地区居民影响尤为严重(王瑛, 2012)。《民政部自然灾害救助应急工作规程》的灾害分级响应机制根据地震灾害造成的死亡人数、转移安置人口和倒塌损坏房屋等损失,分4个自然灾害救助应急响应等级,分别对应特别重大、重大、较大、一般地震灾害。其中,特别重大地震灾害为巨灾,重大地震灾害为大灾,而较大和一般地震灾害为中小型地震灾害。对于巨震,无论是1976年的唐山地震,还是2008年的汶川地震,中国的灾后援助方式都是举国援助模式(刘则华, 2008)。汶川震后恢复更是世界罕见的一次举全国之力,动员范围最广、投入力量最大、援建速度最快的灾后恢复重建工作。对于中小级别的地震,由于影响区域小、程度相对轻,采用的是政府帮助灾区进行短期恢复,拨付的救灾资金主要用于灾区的应急阶段,灾民重建房屋的资金大部分还要依靠自己筹措。例如云南自2000年来的多次Ms5-6级地震,对于地震中倒塌房屋的灾民只提供少量的房屋重建补助。

此外,地震对农村居民的住房造成巨大破坏,震后的恢复过程较其他灾害更长,但其恢复重建过程相对其他灾害简单,因此,地震灾害后的恢复重建易于评估和建立模型,地震灾害的恢复重建在中国灾害救助中极具研究代表性。

恢复重建进程中的居民生活恢复和生计恢复更值得人们关注(Olshansky, 2005)。因为家庭的日常生活恢复是经济恢复、心理恢复的基础。根据《中国自然灾害救助条例》的定义,灾后生活恢复是指让受灾家庭的衣、食、住、医方面的需求满足程度恢复到和灾前一样。对于“是否已经恢复到震前状态”这个问题,由受损家庭自我评判,因为只有受灾者才真正了解自己灾前的生活状况,亲身体验到家庭生活的恢复与否。

综上,本文以2008年四川汶川Ms8.0级地震、2009年云南姚安Ms6.0级地震为案例,对这两次地震中的重灾区内房屋受损家庭进行随机入户调查,记录这些家庭的房屋受损级别、生活恢复的时间节点,研究其生活恢复随时间变化的规律,对比不同灾害强度对恢复重建过程的影响,为国家和地区制定科学合理的灾后恢复重建管理提供理论基础。

2 数据源与方法

2.1 研究区的地震灾害

云南省、四川省是中国乃至亚洲的地震高发区之一。2000-2013年间,云南省发生过35次Ms5-6级地震,5次Ms6级以上地震;四川省发生49次Ms5-6级地震,11次Ms6级以上地震。

2008年5月12日,四川省汶川县映秀镇发生Ms8.0级地震,极震区烈度Ⅺ度,涉及四川、甘肃、陕西、重庆等10个省区市417个县(市、区)。灾区总面积约50万km2,其中极重灾区、重灾区面积13万km2,造成69227人遇难、17923人失踪,直接经济损失高达8451亿多元,引发的崩塌、滑坡、泥石流、堰塞湖等次生灾害举世罕见(刘则华, 2008)。

2009年7月9日,云南省姚安县官屯乡发生Ms6.0级地震,极震区烈度Ⅷ度。地震波及周边31个乡镇,有1人死亡,328人受伤,直接经济损失27亿元(郑通彦等, 2010)。

根据地震烈度分布图,本文选择四川汶川地震中的极震区汶川县耿达乡、银杏乡、映秀镇、水磨镇、漩口镇、绵虒镇,北川县擂鼓镇、桂溪乡、陈家坝、禹里等10余个乡镇(下文简称“四川灾区”)进行调查。选择云南姚安地震中的极震区姚安县官屯、栋川、左门、光禄、新街5个乡镇(下文简称“云南灾区”)进行入户问卷调查。

2.2 数据获取

对云南姚安地震,本文采用三次跟踪调查。第一次调查时,询问家庭“从衣、食、住、行4个方面来评价,家庭生活是否已经恢复到震前状态”,如果这个家庭回答已经恢复,则接着询问该家庭的具体恢复时间;如果尚未恢复,则在第二次调查时再次询问该问题;依此类推,逐步将所有家庭的恢复时间调查记录下来。姚安地震为中小型地震灾害,家庭恢复时间较短,因此,调查时间分别选择了2009年8月、2010年8月和2011年1月,即姚安地震后的1月、1年和1.5年。调查的家庭从云南民政厅建设的“姚安灾情统计数据库”随机抽取,数据库记录有姚安地震灾区每户受损家庭的详细信息,包括户主联系方式、地点、房屋受损情况、补助时间、金额等,故姚安地震的三次跟踪调查较为成功。

汶川地震为巨灾,考虑到其家庭恢复时间较为漫长,本文共进行了二次调查:第一次在2012年8月(震后4年),对地震烈度最高的北川县、汶川县400户家庭进行了预调查;第二次调查在2014年1月(震后5年8个月),对北川县和汶川县的800多户家庭进行了调查,本文的分析数据基于第二次调查的结果。由于2个县的多数家庭在地震中房屋都受损,因此,汶川地震调查采用在灾区随机入户的调查方式,调查时间选在春节前10天,外出务工人员已经返乡在家,问卷回收率高。

本文的调查由作者和当地的在校大学生完成。为了使调查结果能真实地体现被调查者的意愿,作者不仅在调查前对他们进行专业知识培训,并且让每位调查员每次所调查的家庭基本一致,从而保证跟踪调查的连续性。此外,每次调查时,作者会随机抽查,跟随调查员一起入户调查,尽量减少调查员的主观性。

2.3 调查样本基本情况

云南姚安地震的中损和重损家庭分别为6645和2997户,根据预调查数据,两类家庭恢复时间标准差分别为10.8和13.1周。经过随机抽样方法计算最小样本量,按90%置信水平、最大误差2周,则中损、重损家庭最小样本量分别应为115和79户。

四川汶川地震,根据《四川统计年鉴》数据,2007年底汶川县和北川县总户数分别为27523和41211户(按人口总数和户均人口折算得到)。根据预调查数据,灾区受损家庭的恢复时间标准差为46周。按90%置信水平、最大误差4周,汶川县、北川县的最小样本量分别应为361和363户。由于缺少两个县中损、重损家庭的总户数,故未计算其不同受损家庭的最小样本量。

根据上述最小样本需求量要求,进行了随机抽样调查。跟踪调查云南姚安县500户家庭,并以周为单位记录其恢复时间,共回收有效问卷358份,其中重损家庭121户、中损家庭237户。四川汶川重灾区共调查了900户家庭,以月为单位记录其恢复时间,共回收有效问卷736份,其中汶川县363份、北川县373份。云南姚安地震调查受访者平均年龄为42岁,91%的受访者年龄在15~65岁之间,88%为家庭户主或其配偶;四川汶川地震调查受访者平均年龄为48岁,85%的受访者年龄在15~65岁之间,81%为家庭户主或其配偶,以确保受访者对受访家庭情况有充分的了解。总计有效问卷1094份,调查样本及调查的恢复时间基本情况见表1所示。

表1   样本基本情况

Tab.1   Basic information of the surveyed households

中损家庭重损家庭
家庭总数/户有效问卷数/份恢复时间
均值/周
恢复时间
标准差/周
家庭总数/户有效问卷数/份恢复时间
均值/周
恢复时间
标准差/周
云南灾区664523719.4712.79299712131.8524.65
四川灾区汶川/4567.9257.9327523*31877.8856.27
北川/6371.6476.1241211*31086.1669.96

*为各县总家庭户数。

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表1可知,无论是云南灾区,还是四川灾区,重损家庭的恢复时间平均值都大于中损家庭。除云南灾区中损家庭外,其他三类家庭的标准差都很大,这说明即使是相同类别内,各个家庭的恢复时间仍存在较大差别,需要进行更具体的分析。

2.4 研究方法

本文采用“家庭恢复率(R)”指标来衡量受损地区的总体恢复情况,定义为:灾区已经完成灾后恢复的家庭数占总受损家庭数的比率。恢复率的计算公式如下:

R(T)=t=0TgtMt=0,1,2,3,,T(1)

式中:R(T)为T时的灾区恢复率,t为恢复时间,以周为单位;gtt时完成恢复的家庭数;M为灾区受损家庭总数。本文的恢复都是指受损家庭的生活恢复到震前状态,因此“恢复时间t”是指从地震发生直到受损家庭搬入震后常住房屋并且生活恢复到震前状态的时间。

由式(1)可知,恢复率R是一个随时间累积渐变的过程量,它可以清晰地反映灾区的恢复情况随着时间的变化。如前所述,恢复曲线非常准确直观地描述了一个区域的灾后恢复过程。

3 震后生活恢复的阶段划分

3.1 云南灾区的生活恢复曲线及阶段划分

将调查数据代入式(1),计算得到各个时间点的灾区恢复率。以t为横轴,恢复率R为纵轴,绘制姚安地震灾区的家庭生活恢复曲线,其中t以“周”为单位,这样可以较详细的记录家庭生活恢复的实际情况,如图1a-1b所示。

图1   不同破坏级别的震后家庭生活恢复曲线

Fig.1   Post-earthquake household livelihood recovery curves for different housing damage levels

Haas等(1977)从灾后的社会经济出发,将城市的灾后恢复划分为4个不同的阶段,但未给出每个阶段的具体时间。根据图2的恢复曲线形态、以及恢复速率的变化,本文将家庭生活恢复过程分为4个阶段,分别为:①应急期(R1),是指灾害发生,恢复重建尚未开始的一段转换调整时期;②恢复前期(R2),是指正式恢复的前期;③恢复期(R3)中期,是恢复重建的中期;④恢复后期(R4),是震后家庭生活恢复的最后阶段。

由于受损程度不同,图2a-2b的阶段划分略有不同,因为中损家庭的房屋恢复以修复为主,耗时少,容易完成;而重损家庭房屋恢复以重建为主,耗时长,不易完成。因此在各个阶段的时间划分上,二者略有差异。具体为:

(1) 应急期(R1)的时间范围为0~2(5)周(即,中损家庭恢复时间0~2周,重损家庭为0~5周,下同)。这段期间只有很少家庭开始恢复,大多数家庭仍处于未恢复状态。在该阶段末期,中损家庭有25%完成恢复,重损家庭有5%完成恢复。

(2) 恢复前期(R2)的时间范围为2(5)~24周。在此期间,受损家庭逐渐随着时间的增长缓慢恢复。在该阶段末期,中损家庭有50%完成恢复,重损家庭有30%完成恢复。

(3) 恢复中期(R3)的时间范围为24~34周。该期间的时间较短,但恢复速度很快。在该阶段末期,中损家庭和重损家庭完成恢复的比例分别为80%、90%。

(4) 恢复后期(R4)的时间范围为34~72(80)周。该阶段内恢复曲线趋于平缓,灾区受损家庭生活恢复全部完成。

图2   不同受损家庭生活恢复曲线拟合结果

Fig.2   Household livelihood recovery fitting curves for different housing damage levels

3.2 四川灾区的生活恢复曲线及阶段划分

根据对汶川地震汶川县、北川县灾区的调查数据,计算恢复率,绘制恢复曲线,如图1c-1d所示。

从恢复曲线形态、速率上看,汶川灾区的家庭生活恢复过程同样也可以分为4个阶段,分别为:应急期(R1)、恢复前期(R2)、恢复中期(R3)、恢复后期(R4)。其中,中损与重损家庭的生活恢复过程存在一些差异,4个恢复阶段的综合划分如下:

(1) 应急期(R1)的时间范围为0~16周。这段期间只有很少家庭开始恢复,大多数家庭仍处于未恢复状态。在该阶段末期,中损家庭有16%完成恢复,重损家庭有13%完成恢复。

(2) 恢复前期(R2)的时间范围为16~88(100)周。在此期间,受损家庭相对快速恢复。中损家庭在88周左右已经有60%左右家庭完成恢复;重损家庭在100周时也有55%以上家庭完成恢复。

(3) 恢复中期(R3)的时间范围为88(100)~164(188)周。在此期间,受损家庭逐渐恢复。中损家庭在164周左右已经有85%左右家庭完成恢复。汶川县与北川县的重损家庭的恢复在此期间产生较大分化,北川县相对滞后,在188周时,汶川县、北川县的恢复率分别为90%、76%。

(4) 恢复后期(R4)的时间范围为164(188)~272(>272)周。该阶段内恢复曲线趋于平缓,灾区受损家庭生活恢复缓慢完成。本文调查时间为灾后270周,中损家庭93%以上恢复,故可认为已基本完成恢复;但汶川县和北川县的重损家庭恢复率分别为93%、84%,故可认为其恢复仍未完成。

3.3 巨灾与中小灾的生活恢复过程差异

表2为姚安地震、汶川地震灾民的恢复阶段划分,以及各个阶段所对应的恢复时间和恢复速度(指单位时间内恢复率的变化)。

表2   震后家庭生活恢复的阶段划分

Tab.2   Post-earthquake household recovery phases

中度破坏严重破坏
云南灾区四川灾区云南灾区四川灾区
时间点/周恢复速度/(%/周)时间点/周恢复速度/(%/周)时间点/周恢复速度/(%/周)时间点/周恢复速度/(%/周)
应急期(R1)0~26.250~160.610~50.500~160.64
恢复前期(R2)2~242.0716~880.635~241.4516~1000.57
恢复中期(R3)24~343.0288~1640.2924~344.25100~1880.25
恢复后期(R4)34~720.38164~2720.0834~800.49188~272<0.07

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对比上述两个地震灾区的各个恢复阶段,有以下特点:

(1) 各阶段的恢复速度变化基本相同。应急期的恢复速度较快;恢复前期和中期的速度逐渐降低;恢复后期,恢复速度最慢。略有不同的是,云南灾区重损家庭在应急期的恢复速度较慢,原因是姚安地震在汶川地震后1年发生,尚未确定救助政策究竟是否与四川汶川地震相同,还是沿袭云南过去的政策?因此,应急期的恢复速度较慢,但在救助政策确定后,居民的恢复速度开始快速增长,在恢复中期,出现了最高恢复速度。

(2) 云南灾区中损家庭恢复历时72周(1年6个月),比重损家庭快8周(2个月);四川灾区同样存在这一规律。说明家庭的受损程度对恢复时间长短存在影响,家庭受灾程度轻,所需投入的房屋修缮成本也较低,恢复就较为容易。

(3) 云南灾区中损、重损家庭的恢复率在应急期、恢复前期几乎相同,在恢复中期、后期逐渐出现差别。说明中小灾害后的恢复重建,由于整个恢复期较短,受灾程度对恢复过程的影响相对较弱。

(4) 无论是中损家庭还是重损家庭,四川灾区的各个恢复阶段时间都远远长于云南灾区,恢复速度十分缓慢,每周的恢复率均小于1%。因此,云南灾区的家庭生活恢复过程历时约为80周(1年8个月),而四川灾区的家庭生活恢复过程则大于270周(5年7个月)。

(5) 四川灾区重损家庭的恢复在各个阶段都慢于中损家庭,恢复前期阶段慢12周(3个月);恢复中期慢24周(6个月),说明两类家庭的恢复差距越来越大。由于本文调查时,尚有部分重损家庭未完成恢复,故四川灾区重损家庭恢复后期的时间点尚不能确定。根据上述2个阶段的差距推测,重损家庭的生活恢复大约还需48周(12个月),即到2015年1月。说明巨型灾害后,在漫长的恢复过程中,受灾程度对恢复过程的影响越来越大,重损家庭的生活恢复更为艰难。

上述差别的原因,就是二者的灾害强度不一样,造成的影响范围不同。姚安地震的震级为Ms 6.0,只造成1个县的5个乡镇受到影响;汶川地震的震级为Ms 8.0,造成了3个省46个重灾县的影响。因此,尽管2个灾区调查家庭的受灾程度相同,但在恢复重建过程中,受到外界的影响程度截然不同:地震对汶川县、北川县的整个县域经济造成了几乎毁灭性的打击,对相邻区域的经济也有重大影响,因此,四川灾区受灾居民的恢复是双重恢复,他们既需要完成本区域经济社会的恢复,还需要完成自己家庭的恢复。

4 恢复曲线的模型化表达

国内外学者结合其研究成果,提出了恢复过程的描述模型和改进模型(王本楠, 1988; Miles et al, 2006)。从图1的震后家庭生活恢复曲线可见,曲线从某个固定点出发,其增长速率单调增加,达到一定数值后,增长速率下降,渐进地趋于某个稳定值。这一规律与广泛存在于生物种群和社会学领域中的“S型增长”特征极为相似,该类曲线可称为“S型增长曲线”。

“S型增长”是在有限资源条件下群体发展变化的基本规律。因为在自然界中,环境条件是有限的,当种群数量达到环境条件所允许的最大值时,种群数量将停止增长,保持相对稳定。震后家庭恢复的本质也是在遭受地震打击后,家庭通过内部和外部的各种资源使其生活恢复到灾前水平的过程,这个过程不可避免地也要受到有限资源的限制,因此灾后家庭恢复曲线是“S型增长曲线”。

通过数理模型对实际恢复曲线数据进行模型化表达,能使恢复曲线更具实用性。常用的S型曲线模型包括经典Logistic增长模型、Gompertz模型。两个拟合模型的基本公式如下所示:

经典Logistic增长模型: R(t)=11+ae-bt(2)

Gompertz曲线模型: R(t)=abt(3)

式中:R(t)为家庭恢复率,t为恢复完成时间,ab为待定参数。

本文分别使用以上两种S型曲线模型对恢复数据进行拟合,选择最佳匹配模型。根据以上公式,以云南、四川灾区中损家庭、重损家庭的恢复为例,拟合不同破坏级别下、不同灾区的恢复数据,其结果如表3所示。由表3中的拟合优度可以看出,两种模型的拟合效果都较好,在云南和四川灾区不同损失级别的拟合优度略有差异。

表3   Logistic模型与Gompertz模型拟合结果

Tab.3   Simulation results of the Logistic model and the Gompertz model

模型名称ab残差平方和拟合优度Pearson 相关系数Sig.
云南中损Logistic5.6310.4560.0530.9720.9860.000
Gompertz0.1100.7220.0590.9690.9850.000
云南重损Logistic69.7010.6690.0610.9860.9950.000
Gompertz0.000010.6370.0670.9850.9940.000
汶川中损Logistic3.9750.0800.1560.9610.9840.000
Gompertz0.1460.9400.0810.9800.9910.000
汶川重损Logistic6.7080.0970.0860.9840.9940.000
Gompertz0.0730.9310.0310.9940.9980.000
北川中损Logistic3.9650.0800.2580.9370.9720.000
Gompertz0.1410.9390.1470.9640.9840.000
北川重损Logistic4.2990.0570.2000.9460.9740.000
Gompertz0.1350.9580.0970.9740.9870.000

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经典Logistic模型、Gompertz模型与实际恢复数据之间的Pearson相关系数值都在0.9以上,表明其对实际恢复数据具有良好的表达效果,并都通过了0.05显著性水平的F检验,具有统计学意义。由此可以认为两种模型都能较好拟合震后居民的生活恢复过程。Gompertz模型与Logisitic模型的区别在于:前者更适合于过程发展先快后慢的曲线拟合。从表3可见,Gompertz模型在较好满足高数据拟合优度与高相关性同时,对四川灾区的拟合残差最小,能更好描述区域的恢复过程情况。因此,本文选取Gompertz模型作为震区家庭的生活恢复曲线理论模型,分别构建中损家庭(云南、汶川、北川)、重损家庭(云南、汶川、北川)的震后生活恢复曲线模型,分别如式(4)-(9)所示:

云南中损家庭生活恢复模型: R2(t)=0.110.722t(4)

汶川中损家庭生活恢复模型: R3(t)=0.1410.939t(5)

北川中损家庭生活恢复模型: R5(t)=0.0730.931t(6)

云南重损家庭生活恢复模型: R4(t)=0.000010.637t(7)

汶川重损家庭生活恢复模型: R5(t)=0.0730.931t(8)

北川重损家庭生活恢复模型: R6(t)=0.1350.985t(9)

震区家庭恢复曲线模型拟合结果如图2a-2b所示。模拟曲线很好地表达了原始数据的S型特征及阶段性特征。图2a中,汶川、北川中损家庭模型的系数差别较小,曲线几乎重合;但图2b中,不仅云南与汶川、北川重损家庭的恢复曲线有差别,汶川、北川之间也有较大差别。这说明家庭生活恢复过程还与区域背景有较大关系,有待更深入的研究。

将本文结果与其他灾害的恢复曲线模型相对比,基本形式相同,但模型里的参数有差别。例如Murao等(2010)采用了Gompertz曲线模型模拟印度洋海啸的恢复曲线,恢复曲线的系数分别为a=3.36E-11,b=0.489。a与本文式(7)较接近,表明云南地震恢复过程与其恢复过程较接近。但a与本文其他公式差异较大,如汶川地震恢复过程均较大地滞后于印度洋海啸恢复的过程。但是由于该文的恢复是指房屋建成,与本文的生活恢复不同,因此,不同灾害类型的恢复过程模型中ab的变化,还需要更多的案例研究。

5 结论与讨论

农村家庭的震后恢复重建是中国自然灾害救助工作的重要内容。本文以2008年四川汶川Ms8.0级地震为巨灾案例,2009年云南姚安Ms6.0级地震为中小型灾害案例,对重灾区内的房屋受损家庭进行随机入户调查,记录这些家庭的房屋受损级别、完成恢复的时间节点。同时引入了恢复曲线,研究受灾家庭的生活恢复随时间变化的规律,对比不同灾害强度对恢复重建过程的影响。

研究发现家庭恢复过程具有明显的阶段性,根据恢复速率的变化,可以将恢复过程分为应急期、恢复前期、恢复中期,恢复后期。应急期的恢复速度较快;恢复前期和中期的速度逐渐降低;恢复后期,恢复速度最慢。

此外,巨灾和中小型灾害的恢复历时、恢复过程存在较大不同。中小型灾害,家庭生活恢复过程历时1年8个月,其中中损家庭的恢复过程略短,大约1年6个月;受灾程度对恢复过程的影响相对较弱,巨型灾害,恢复过程历时较长,中损家庭的恢复大约为5年8个月,重损家庭的恢复在各个阶段都慢于中损家庭:恢复前期阶段慢12周(3个月),恢复中期慢24周(6个月)。说明两类家庭的恢复差距越来越大,受灾程度对恢复过程的影响越来越突出,重损家庭的生活恢复随时间的推移,变得更为艰难。

本文还根据两个灾区恢复曲线的S型特征对其进行了曲线模拟,通过对比多种S型特征模型拟合效果,提出Gompertz模型可以较好地拟合灾后家庭生活的恢复过程。本文的研究结果从一个侧面说明:对于巨灾,举国体制的恢复重建援助是十分有必要的,巨灾受灾区的居民恢复是双重恢复,既需要完成本区域经济社会的恢复,还需要完成自己家庭的恢复。如果外界不对其进行有效援助,这个地区的恢复将更为漫长、艰难。

有学者认为灾后恢复是一个复杂的、多维的和非线性的动力过程、没有明确的终点(Nigg, 1995; Liu et al, 2008)。虽然汶川地震距今已6年多,但对于地震灾区尚未恢复家庭,仍然需要政府、社会的持续关注。

云南农业大学王楠稀、张可,四川大学况银丽、谢齐、赵旺、葛颖蕾、刘超等同学参与本文的问卷调查,谨致谢忱!

The authors have declared that no competing interests exist.


参考文献

[1] 樊杰, 王传胜, 汤青, . 2014.

鲁甸地震灾后重建的综合地理分析与对策研讨

[J]. 地理科学进展, 33(8): 1011-1018.

https://doi.org/10.11820/dlkxjz.2014.08.001      URL      [本文引用: 1]      摘要

地震灾区是地表各圈层相互作用最剧烈、人地关系最紧张的区域.深入开展综合地理研究对于协调这一区域的人地关系,促进区域可持续发展有着重大的意义.本文 首先对鲁甸灾前的资源环境特点与区域发展特征进行了评价和分析,发现该地区生态环境脆弱、人口密度大、贫困面广、生产生活对资源的依赖程度高、资源环境长 期处于超载状态.进而,针对性地提出了尽早启动资源环境承载能力评价,科学制定重建规划,体制机制创新,以及开展整个青藏高原边缘地带及近邻地区的防灾减 灾系统研究和整体规划等对策建议.

[Fan J, Wang C S, Tang Q, et al.2014.

Comprehensive geographic analysis and discussion on strategies for postearthquake recovery and reconstruction in Ludian, Yunnan Province

[J]. Progress in Geography, 33(8): 1011-1018.]

https://doi.org/10.11820/dlkxjz.2014.08.001      URL      [本文引用: 1]      摘要

地震灾区是地表各圈层相互作用最剧烈、人地关系最紧张的区域.深入开展综合地理研究对于协调这一区域的人地关系,促进区域可持续发展有着重大的意义.本文 首先对鲁甸灾前的资源环境特点与区域发展特征进行了评价和分析,发现该地区生态环境脆弱、人口密度大、贫困面广、生产生活对资源的依赖程度高、资源环境长 期处于超载状态.进而,针对性地提出了尽早启动资源环境承载能力评价,科学制定重建规划,体制机制创新,以及开展整个青藏高原边缘地带及近邻地区的防灾减 灾系统研究和整体规划等对策建议.
[2] 高晓路, 陈田, 樊杰. 2010.

汶川地震灾后重建地区的人口容量分析

[J]. 地理学报, 65(2): 164-176.

https://doi.org/10.11821/xb201002004      URL      [本文引用: 1]      摘要

As one of the kernel parts of Assessment of Regional Carrying Capacity of the Wenchuan Earthquake Struck Areas, this study developed a decision-making model for estimating the population capacity of the involved townships and cities based on the assessment of the suitability for reconstruction of the areas. It identified the critical constraints of population capacity and analyzed the spatial differentiations of the post-quake development conditions across different regions. The expected levels of urbanization, family incomes and income structures, levels of land output, and the reliance of agricultural population on arable lands are estimated by regions. With these parameters, the population capacities of townships and cities under several scenarios were estimated. According to the status of over-population, the townships and cities were classified and relevant policy suggestions on post-quake resettlement were presented.

[Gao X L, Chen T, Fan J.2010.

Population capacity in the Wenchuan Earthquake reconstruction areas

[J]. Acta Geographica Sinica, 65(2): 164-176.]

https://doi.org/10.11821/xb201002004      URL      [本文引用: 1]      摘要

As one of the kernel parts of Assessment of Regional Carrying Capacity of the Wenchuan Earthquake Struck Areas, this study developed a decision-making model for estimating the population capacity of the involved townships and cities based on the assessment of the suitability for reconstruction of the areas. It identified the critical constraints of population capacity and analyzed the spatial differentiations of the post-quake development conditions across different regions. The expected levels of urbanization, family incomes and income structures, levels of land output, and the reliance of agricultural population on arable lands are estimated by regions. With these parameters, the population capacities of townships and cities under several scenarios were estimated. According to the status of over-population, the townships and cities were classified and relevant policy suggestions on post-quake resettlement were presented.
[3] 刘则华. 2008.

在全国抗震救灾总结表彰大会上的讲话

[N/OL]. 人民日报, 2008-10-09[2014-11-25]. .

URL      [本文引用: 2]     

[Liu Z H. 2008.

Speech on national summary and commendation conference of earthquake relief work

[N/OL]. People's Daily, 2008-10-09[2014-11-25]. .]

URL      [本文引用: 2]     

[4] 史培军, 郭卫平, 李保俊, . 2005.

减灾与可持续发展模式: 从第二次世界减灾大会看中国减灾战略的调整

[J]. 自然灾害学报, 14(3): 1-7.

https://doi.org/10.3969/j.issn.1004-4574.2005.03.001      URL      [本文引用: 1]      摘要

简要介绍了2005年1月17 日-22日在日本神户召开的世界减灾大会的基本内容,并着重论述了当前国际减灾领域的重要进展和发展趋向,就减灾与可持续发展作了系统的论证,提出了我国 减灾领域近期发展的主要方向。从世界减灾大会的各项议程和各类论坛可以看出,未来世界减灾的战略可以概括如下加强减灾能力建设是促进区域可持续发展的核心 任务,全面推进社区减灾体系的建设是实现未来10年减灾目标的关键任务;建立与灾害风险共存的经济与社会体系,必须把减灾与区域发展有机地整合起来,寻求 除害与兴利并举的可持续发展模式,建设接受一定风险水平的安全社区体系;重视包括全球气候变化、经济全球化、世界城镇化等自然与人文过程引发或孕育的新的 灾害风险;建立满足区域减灾目标需要的预警系统,加强减灾信息共享,充分利用现有的减灾资源。针对国际减灾发展趋向,提出了中国减灾战略调整的建议,即实 施“区域减灾”、“综合减灾”、“科教减灾”、“提高区域减灾能力”和“加强减灾科技能力建设”。

[Shi P J, Guo W P, Li B J, et al.2005.

Disaster reduction and sustainable development: adjustment of disaster reduction strategies of China based on the 2nd World Conference on Disaster Reduction

[J]. Journal of Natural Disasters, 14(3): 1-7.]

https://doi.org/10.3969/j.issn.1004-4574.2005.03.001      URL      [本文引用: 1]      摘要

简要介绍了2005年1月17 日-22日在日本神户召开的世界减灾大会的基本内容,并着重论述了当前国际减灾领域的重要进展和发展趋向,就减灾与可持续发展作了系统的论证,提出了我国 减灾领域近期发展的主要方向。从世界减灾大会的各项议程和各类论坛可以看出,未来世界减灾的战略可以概括如下加强减灾能力建设是促进区域可持续发展的核心 任务,全面推进社区减灾体系的建设是实现未来10年减灾目标的关键任务;建立与灾害风险共存的经济与社会体系,必须把减灾与区域发展有机地整合起来,寻求 除害与兴利并举的可持续发展模式,建设接受一定风险水平的安全社区体系;重视包括全球气候变化、经济全球化、世界城镇化等自然与人文过程引发或孕育的新的 灾害风险;建立满足区域减灾目标需要的预警系统,加强减灾信息共享,充分利用现有的减灾资源。针对国际减灾发展趋向,提出了中国减灾战略调整的建议,即实 施“区域减灾”、“综合减灾”、“科教减灾”、“提高区域减灾能力”和“加强减灾科技能力建设”。
[5] 王本楠. 1988.

S-型增长曲线的最小二乘拟合: 方法比较

[J]. 北京林业大学学报, 10(增刊): 59-65.

URL      [本文引用: 1]      摘要

Logistic equation is the most famous model describing S-sha-ped growth curve of single population. It was first discovered in 1838 by the Dutch Mathematical-Biologist Verhulst. For one and a half century it almost the unique form expressing growth curve when a population is growing in a limited space. Recently, A new model concerning the growth of single population has been derived by Cui and Lawson. This model was based on the absorption theory of chemical kinetics and can explain the relationship between population increment and limited resources. In this paper, we try to discuss the method of least square fitting S-shaped curve, and compare the method with the others.

[Wang B N.1988.

The method non-linear least squares fitting S-shaped models

[J]. Journal of Beijing Forestry University, 10(S): 59-65.]

URL      [本文引用: 1]      摘要

Logistic equation is the most famous model describing S-sha-ped growth curve of single population. It was first discovered in 1838 by the Dutch Mathematical-Biologist Verhulst. For one and a half century it almost the unique form expressing growth curve when a population is growing in a limited space. Recently, A new model concerning the growth of single population has been derived by Cui and Lawson. This model was based on the absorption theory of chemical kinetics and can explain the relationship between population increment and limited resources. In this paper, we try to discuss the method of least square fitting S-shaped curve, and compare the method with the others.
[6] 王岱, 张文忠, 余建辉. 2010.

国外重大自然灾害区域重建规划的理念和启示

[J]. 地理科学进展, 29(10): 1153-1161.

https://doi.org/10.11820/dlkxjz.2010.10.001      URL      [本文引用: 1]      摘要

The plan of rehabilitation and reconstruction is an important foundation for the advancement of restaration and reconstruction in disaster affected areas.It is of great significance for the promotion of the capability of disaster prevention,restoration and reconstruction and the continuous improvement of the theory and methods for restaoration and reconstruction.Through a great plenty of literatures and materials published by international organizations,this study analyzes and summarizes the developed concept and ideas as well as the implementations of restoration and reconstruction in the areas affected respectively by the Great Hanshin Earthquake in 1995,the Sumatra Earthquake and Tsunami in the Indian Ocean in 2004,and the Hurricane Katrina in 2005.Finally,this study points out that in the process of restoration and reconstruction in China,more efforts should be made in two aspects,which are attention/reflection of publics' desire and construction of intangible environment.

[Wang D, Zhang W Z, Yu J H.2010.

Concept and inspiration from the plans of restoration and reconstruction in foreign countries for areas affected by large-scale natural disasters

[J]. Progress in Geography, 29(10): 1153-1161.]

https://doi.org/10.11820/dlkxjz.2010.10.001      URL      [本文引用: 1]      摘要

The plan of rehabilitation and reconstruction is an important foundation for the advancement of restaration and reconstruction in disaster affected areas.It is of great significance for the promotion of the capability of disaster prevention,restoration and reconstruction and the continuous improvement of the theory and methods for restaoration and reconstruction.Through a great plenty of literatures and materials published by international organizations,this study analyzes and summarizes the developed concept and ideas as well as the implementations of restoration and reconstruction in the areas affected respectively by the Great Hanshin Earthquake in 1995,the Sumatra Earthquake and Tsunami in the Indian Ocean in 2004,and the Hurricane Katrina in 2005.Finally,this study points out that in the process of restoration and reconstruction in China,more efforts should be made in two aspects,which are attention/reflection of publics' desire and construction of intangible environment.
[7] 王瑛. 2012. 中国农村地震灾害脆弱性研究[M]. 北京: 科学出版社.

[本文引用: 2]     

[Wang Y.2012. The research on the vulnerability of earthquake disaster in rural region of China[M]. Beijing, China: Science Press.]

[本文引用: 2]     

[8] 郑通彦, 李洋, 侯建盛, . 2010.

2009年中国大陆地震灾害损失述评

[J]. 灾害学, 25(4): 96-101.

https://doi.org/10.3724/SP.J.1084.2010.00199      URL      [本文引用: 1]      摘要

Based on the earthquake catalog with magnitude over 5. 0 and reports of earthquake disaster evaluation provided by related provincial earthquake administrations,the key data and characteristics of earthquake disasters in mainland China in 2009 are summarized and the related data of earthquake disasters from 1990 to 2009 in mainland China are compared.

[Zheng T Y, Li Y, Hou J S, et al.2010.

A review of earthquake disasters loss in mainland China in 2009

[J]. Journal of Catastrophology, 25(4): 96-101.]

https://doi.org/10.3724/SP.J.1084.2010.00199      URL      [本文引用: 1]      摘要

Based on the earthquake catalog with magnitude over 5. 0 and reports of earthquake disaster evaluation provided by related provincial earthquake administrations,the key data and characteristics of earthquake disasters in mainland China in 2009 are summarized and the related data of earthquake disasters from 1990 to 2009 in mainland China are compared.
[9] Al-Nammari F M, Lindell M K.2009.

Earthquake recovery of historic buildings: exploring cost and time needs

[J]. Disasters, 33(3): 457-481.

https://doi.org/10.1111/j.1467-7717.2008.01083.x.      URL      PMID: 19178547      摘要

Disaster recovery of historic buildings has rarely been investigated even though the available literature indicates that they face special challenges. This study examines buildings' recovery time and cost to determine whether their functions (that is, their use) and their status (historic or non-historic) affect these outcomes. The study uses data from the city of San Francisco after the 1989 Loma Prieta earthquake to examine the recovery of historic buildings owned by public agencies and non-governmental organisations. The results show that recovery cost is affected by damage level, construction type and historic status, whereas recovery time is affected by the same variables and also by building function. The study points to the importance of pre-incident recovery planning, especially for building functions that have shown delayed recovery. Also, the study calls attention to the importance of further investigations into the challenges facing historic building recovery.
[10] Burton C, Mitchell J T, Cutter S L.2011.

Evaluating post-Katrina recovery in Mississippi using repeat photography

[J]. Disasters, 35(3): 488-509.

https://doi.org/10.1111/j.1467-7717.2010.01227.x      URL      PMID: 21272057      [本文引用: 1]      摘要

Hurricane Katrina of August 2005 had extensive consequences for the state of Mississippi in the United States. Widespread infrastructure and property damage, massive social dislocation, and ecological loss remain among the many challenges faced by communities as they work towards `normalcy'. This study employs repeat photography to understand differential recovery from Hurricane Katrina in Mississippi. Revealing change with conventional landscape photography, a process known as repeat photography, is common in the natural sciences. Simply stated, repeat photography is the practice of re-photographing the same scene as it appears in an earlier photograph. Photographs were taken at 131 sites every six months over a three-year period. Each photograph was assigned a recovery score and a spatially interpolated recovery surface was generated for each time period. The mapped and graphed results show disparities in the progression of recovery: some communities quickly entered the rebuilding process whereas others have lagged far behind.
[11] Chang S E.2010.

Urban disaster recovery: a measurement framework and its application to the 1995 Kobe earthquake

[J]. Disasters, 34(2): 303-327.

https://doi.org/10.1111/j.1467-7717.2009.01130.x      URL      PMID: 19863570      [本文引用: 1]      摘要

This paper provides a framework for assessing empirical patterns of urban disaster recovery through the use of statistical indicators. Such a framework is needed to develop systematic knowledge on how cities recover from disasters. The proposed framework addresses such issues as defining recovery, filtering out exogenous influences unrelated to the disaster, and making comparisons across disparate areas or events. It is applied to document how Kobe City, Japan, recovered from the catastrophic 1995 earthquake. Findings indicate that while aggregate population regained pre-disaster levels in ten years, population had shifted away from the older urban core. Economic recovery was characterised by a three to four year temporary boost in reconstruction activities, followed by settlement at a level some ten per cent below pre-disaster levels. Other long-term effects included substantial losses of port activity and sectoral shifts toward services and large businesses. These patterns of change and disparity generally accelerated pre-disaster trends.
[12] Fussell E, Sastry N, VanLandingham M.2010.

Race, socioeconomic status, and return migration to New Orleans after Hurricane Katrina

[J]. Population and Environment, 31(1-3): 20-42.

https://doi.org/10.1007/s11111-009-0092-2      URL      PMID: 20440381      [本文引用: 1]      摘要

Hurricane Katrina struck New Orleans on the 29th of August 2005 and displaced virtually the entire population of the city. Soon after, observers predicted the city would become whiter and wealthier as a result of selective return migration, although challenges related to sampling and data collection in a post-disaster environment have hampered evaluation of these hypotheses. In this article, we investigate return to the city by displaced residents over a period of approximately 14聽months following the storm, describing overall return rates and examining differences in return rates by race and socioeconomic status. We use unique data from a representative sample of pre-Katrina New Orleans residents collected in the Displaced New Orleans Residents Pilot Survey. We find that black residents returned to the city at a much slower pace than white residents even after controlling for socioeconomic status and demographic characteristics. However, the racial disparity disappears after controlling for housing damage. We conclude that blacks tended to live in areas that experienced greater flooding and hence suffered more severe housing damage which, in turn, led to their delayed return to the city. The full-scale survey of displaced residents being fielded in 2009鈥2010 will show whether the repopulation of the city was selective over a longer period.
[13] Ganapati N E.2013.

Measuring the processes and outcomes of post-disaster housing recovery: lessons from Gölcük, Turkey

[J]. Natural Hazards, 65(3): 1783-1799.

https://doi.org/10.1007/s11069-012-0442-8      URL      摘要

Despite a growing literature on post-disaster recovery, our understanding of how housing recovery is measured remains limited. This paper is a step in filling the gap in the literature by presenting an overview of how recovery organizations measured post-disaster permanent housing recovery in G02lcük, Turkey, following the August 17, 1999 earthquake. Based on in-depth interviews, focus groups, participant observation, and review of secondary sources, the paper highlights the limitations of measuring housing recovery as the number of permanent housing units built in a timely manner. It suggests that recovery organizations need to measure post-disaster housing recovery by developing context-specific, process- and outcome-oriented measures. In the case of G02lcük, process-oriented measures could have been related to the land appropriation, public participation processes, and inter-organizational collaboration while outcome-oriented measures could have been related to the level of satisfaction with homes built and equity among the housing beneficiaries. Copyright Springer Science+Business Media Dordrecht 2013
[14] Haas J E, Kates R W, Bowden M J.1977. Reconstruction following disaster[M]. Cambridge, MA: MIT Press.

[本文引用: 2]     

[15] Kates R W, Colten C E, Laska S, et al.2006.

Reconstruction of New Orleans after Hurricane Katrina: a research perspective

[J]. Proceedings of the National Academy of Sciences of the United States of America, 103(40): 14653-14660.

[16] Kuwata Y, Takada S.2010.

Business restoration related to lifeline after tsunami disaster

[J]. Journal of Earthquake and Tsunami, 4(2): 73-81.

https://doi.org/10.1142/S1793431110000789      URL      [本文引用: 1]      摘要

This paper proposes a method to evaluate functionality of a business after a tsunami disaster. This method has several modules such as damage estimation of business base (building, equipments, and lifeline) caused by tsunami hazard, restoration ratio-to-time model for business base, and the functionality of the business introduced by facility restoration and its influence to the business. As a case study, the tsunami impact to industries and its subsequent restoration process were studied based on an interview survey in southern Sri Lanka after the 2004 Indian Ocean earthquake and tsunami, and the survey results were applied to the proposed model. Results of application showed that buildings and equipments were slowly restored when they were extensively damaged or flooded. Further, the business restoration depends more heavily on the business facilities restoration than the lifeline restoration, when the business facilities are flooded with tsunami inundation higher than 1 m.
[17] LaJoie A S, Sprang G, McKinney W P.2010.

Long-term effects of Hurricane Katrina on the psychological well-being of evacuees

[J]. Disasters, 34(4): 1031-1044.

https://doi.org/10.1111/j.1467-7717.2010.01181.x      URL      PMID: 20572850      [本文引用: 1]      摘要

Hurricane Katrina of August 2005 forced more than one million people to evacuate the Gulf Coast of the United States. This study examines the psychological health and well-being of a subset of evacuees to determine the prevalence of ongoing mental health problems. Interviews were conducted with 101 adults who evacuated to Louisville, Kentucky, and were living in the state at the one-year anniversary of the event or had recently returned to the Gulf Coast. The psychological health and well-being of respondents was evaluated using several well-validated measures. More than one-half met the criteria for post-traumatic stress disorder and a majority were suffering from depression and anxiety. The mean quality of life score was 0.6 on a scale from 0&ndash;1, suggesting that adaptation and return to pre-hurricane well-being had not occurred 12 months after the storm. The potential for long-term psychological damage exists in this sample of Hurricane Katrina evacuees. Results suggest other evacuees may also be at heightened risk.
[18] Liu A, Plyer A.2008.

The New Orleans index: tracking recovery of New Orleans and the metro area[R]. New Orleans and Washington DC: Greater New Orleans Community Data Center in Collaboration with the

Brookings Institution.

[本文引用: 2]     

[19] Miles S B, Chang S E.2006.

Modeling community recovery from earthquakes

[J]. Earthquake Spectra, 22(2): 439-458.

[本文引用: 1]     

[20] Mileti D S.1999. Disasters by design: a reassessment of natural hazards in the United States[M]. Washington, DC: Joseph Henry Press.

URL      [本文引用: 1]      摘要

Summary of the book, which emphasizes on the fact that natural disasters and technological hazards that may accompany them are not problems that can be solved in isolation. Rather, they are symptoms of broader and more basic problems. Losses from hazards -and the fact that the nation cannot seem to reduce them-result from shrotsighted and narrow conceptions of the human relationship to the natural environment. To redress those shortcomings, the nation must shift to a policy of "sustainable hazard mitigation". This concept links wise management of natural resources with local economic and social resiliency, viewing hazard mitigation as an integral part of a much larger context. Many aspects of this strategy were implicit in the recommendations formulated by White and Haas a quarter-century ago. Bu to head off the continued rise in tolls from disasters, those principles must become more explicit. This summary, and the report on wich it is based, reflect the efforts of over a hundred experts who have worked and debated since 1994 to take stock of American's relationship to hazards past, present, and-most importantly-future. Those contributions have been used to outline a comprehensive approach to enhancing society's ability to reduce the costs of disaster. It briefly reefers to the roots of the problem, the fostering local sustainability, the mitigation tools, the essential steps to be followed ant the key role of the hazards community
[21] Murao O, Mitsuda Y, Miyamoto A, et al.2007.

Recovery curves and digital city of Chi-Chi as urban recovery digital archives[C]//Proceedings of the 2nd International Conference on Urban Disaster Reduction (CD-ROM). Taipei,

China: Earthquake Engineering Research Institute: 27-29.

[本文引用: 1]     

[22] Murao O, Nakazato H.2010.

Recovery curves for housing reconstruction in Sri Lanka after the 2004 Indian Ocean Tsunami

[J]. Journal of Earthquake and Tsunami, 4(2): 51-60.

https://doi.org/10.1142/S1793431110000765      URL      [本文引用: 1]      摘要

On the 26th of December 2004, the Tsunami damaged to five provinces in Sri Lanka and more than 40,000 people were displaced, lost, or killed within a short time. After the tsunami, the Government provided three types of houses for the victims (temporary shelters, transitional houses, and permanent houses). The authors conducted several field surveys and interviews in the damaged area to investigate the recovery conditions, and obtained dataset, which had been collected for 13 months since December 2004 by Rebuilding and Development Agency. It shows the construction status of transitional house and permanent house in the damaged areas. This paper demonstrates recovery curves for the transitional houses and the permanent houses. With the aim of constructing post-earthquake recovery curves for Sri Lanka, the factors of time (months) and completion ratio of building construction are used. The obtained curves quantitatively clarify the regional differences in the completion dates and processes of construction. The proposed quantitative methodology will be used for other damaged countries due to the 2004 Indian Ocean Tsunami. It means that this kind of analysis is essential for investigating post-disaster recovery process because it enables comparative studies of urban/rural planning among different types of post-disaster recovery processes throughout the world.
[23] Nigg J M.1995.

Disaster recovery as a social process[C]//Milke M. Wellington after the quake: the challenge of rebuilding cities

. Wellington, New Zealand: Wellington Earthquake Commission and the Centre for Advanced Engineering: 81-92.

[本文引用: 2]     

[24] Olshansky R B.2005.

Toward a theory of community recovery from disaster: a review of existing literature[C]//Proceedings of the 1st international conference of urban disaster reduction

. Kobe, Japan: Japan Institute of Social Safety Science: 18-20.

[本文引用: 1]     

[25] Rathfon D, Davidson R, Bevington J, et al.2013.

Quantitative assessment of post-disaster housing recovery: a case study of Punta Gorda, Florida, after Hurricane Charley

[J]. Disasters, 37(2): 333-355.

https://doi.org/10.1111/j.1467-7717.2012.01305.x      URL      PMID: 23278508      摘要

Abstract Quantitative assessment of post-disaster housing recovery is critical to enhancing understanding of the process and improving the decisions that shape it. Nevertheless, few comprehensive empirical evaluations of post-disaster housing recovery have been conducted, and no standard measurement methods exist. This paper presents a quantitative assessment of housing recovery in Punta Gorda, Florida, United States, following Hurricane Charley of August 2004, including an overview of the phases of housing recovery, progression of recovery over time, alternative trajectories of recovery, differential recovery, incorporation of mitigation, and effe
[26] Robinson L, Jarvie J K.2008.

Post-disaster community tourism recovery: the tsunami and Arugam Bay, Sri Lanka

[J]. Disasters, 32(4): 631-645.

https://doi.org/10.1111/j.1467-7717.2008.01058.x      URL      PMID: 18479472      [本文引用: 1]      摘要

Tourism is highly vulnerable to external, non-controllable events. A natural disaster can affect the local tourism industry in numerous ways, and such events are particularly devastating for small communities whose local economy is heavily dependent on the sector. Loss of infrastructure plus negative media stories can have long-term ramifications for the destination. In spite of the economic im...
[27] Schiff A J.1995.

Northridge earthquake: lifeline performance and post-earthquake response

[M]. Reston, VA: American Society of Civil Engineers Publications.

[28] Smith G.2011.

Planning for post-disaster recovery: a review of the United States disaster assistance framework

[M]. Virginia, US: Public Entity Risk Institute.

[本文引用: 1]     

[29] Stringfield J D.2010.

Higher ground: an exploratory analysis of characteristics affecting returning populations after Hurricane Katrina

[J]. Population and Environment, 31(1-3): 43-63.

https://doi.org/10.1007/s11111-009-0095-z      URL      [本文引用: 1]      摘要

As a natural and social disaster, Hurricane Katrina has changed how we view disaster experiences from a social, environmental, and demographic perspective. While much literature has concentrated upon descriptive population changes in the wake of the disaster, less attention has been directed toward how certain population characteristics have affected some Katrina evacuee鈥檚 ability to recover in the post-disaster period. This study utilizes a series of logistic regressions upon Current Population Survey data to lend inferential insight into how population groups prone to social and environmental vulnerability have been differentially enabled to return or not-return to their pre-disaster residence. The results validate descriptive findings that Black/African American and impoverished populations have less probability for return, though this relationship may not be as simple as initially supposed. Further, the results suggest that the increase in Hispanic populations in the area may in fact be a non-native one, and some popular conceptions of vulnerability may not seem to be applicable to the unique circumstances surrounding migration from the Gulf Coast. These findings suggest complexity in population relationships in the Gulf Coast not immediately apparent from descriptive level analysis and challenges for ongoing evaluation of the recovery and measurement of Hurricane Katrina -affected areas.
[30] Toyabe S, Shioiri T, Kuwabara H, et al.2006.

Impaired psychological recovery in the elderly after the Niigata-Chuetsu Earthquake in Japan: a population-based study

[J]. BMC Public Health, 6(1): 230.

https://doi.org/10.1186/1471-2458-6-230      URL      PMID: 1592306      [本文引用: 1]      摘要

Psychological distress was measured using the 12-item General Health Questionnaire (GHQ-12) in 2,083 subjects (69% response rate) who were living in transient housing five months after the earthquake. GHQ-12 was scored using the original method, Likert scoring and corrected method. The subjects were asked to assess their psychological status before the earthquake, their psychological status at the most stressful time after the earthquake and their psychological status at five months after the earthquake. Exploratory and confirmatory factor analysis was used to reveal the factor structure of GHQ12. Multiple regression analysis was performed to analyze the relationship between various background factors and GHQ-12 score and its subscale.GHQ-12 scores were significantly elevated at the most stressful time and they were significantly high even at five months after the earthquake. Factor analysis revealed that a model consisting of two factors (social dysfunction and dysphoria) using corrected GHQ scoring showed a high level of goodness-of-fit. Multiple regression analysis revealed that age of subjects affected GHQ-12 scores. GHQ-12 score as well as its factor 'social dysfunction' scale were increased with increasing age of subjects at five months after the earthquake.Impaired psychological recovery was observed even at five months after the Niigata-Chuetsu Earthquake in the elderly. The elderly were more affected by matters relating to coping with daily problems.An earthquake measuring 6.8 on the Richter scale struck the Niigata-Chuetsu region of Japan at 5.56 P.M. on the 23rd of October, 2004. The earthquake was followed by sustained occurrence of numerous aftershocks, one of which measuring 5.0 occurred even on 28th of December, 2004. The earthquake and the following aftershocks left more than 4,500 injured and 120,000 houses completely or partially destroyed. About 100,000 people were displaced from their homes, and some of them moved into temporary housing. Because
[31] USDHS(United States Department of Homeland Security). 2004.

National incident management system

[R]. Washington, DC: USDHS.

[本文引用: 1]     

[32] Wang Y, Chen H, Li J.2012.

Factors affecting earthquake recovery: the Yao'an earthquake of China

[J]. Natural Hazards, 64(1): 37-53.

https://doi.org/10.1007/s11069-012-0224-3      URL      摘要

Households vary in their ability to deal with disasters, and this may lead to different recovery results. Aiming to examine this differentiation, this paper studied the 2009 Yao鈥檃n earthquake in China. Surveys of 200 destroyed rural households were conducted in field investigations and follow-ups at 1聽month, 1聽year, and 1.5聽years after the earthquake. The results showed a clear difference in recovery, the households observably being classified into five groups. These are the O group, which has different recovery time and economic cost from the other four; and the special group, comprising E L T O and E O T L (vulnerable during recovery); E H T O (strong during recovery); and E L T S (neither vulnerable nor strong). Logistic regression analysis revealed that differentiation in recovery patterns arose from the combined effect of demographic factors and external assistance provided to households. Lower income is the root cause of vulnerability in some households during the recovery process. However, other factors cause recovery differences between the two vulnerable groups, causing the economic recovery cost of the E L T O group to be lower, and the recovery time of the E O T L group to be longer. There was consensus that external assistance had an impact on all households. The more provided and the earlier it arrived, the lower the cost for recovery and the shorter the recovery time. This study shows that research on group differentiation of recovery is useful in understanding post-earthquake recovery processes and calls for taking group differentiation considerations into account in post-disaster recovery resource allocation practices.
[33] Wang Y, Li J, Chen H, et al.2014.

The time process of post-earthquake recovery: the Yao'an earthquake in China

[J]. Disasters, 38(4): 774-789.

https://doi.org/10.1111/disa.12083      URL      PMID: 25196336      [本文引用: 1]      摘要

Post-disaster recovery is a constantly changing and developing process. The authors conducted three real-name follow-up surveys at 1, 12 and 18 months after the Yao'an earthquake, which had a surface wave magnitude of 6.0. They also calculated recovery ratios at different times and drew post-earthquake domestic life recovery curves. Based on the recovery curves, the time trajectory of domestic life recovery takes on an approximate S-type development and change process. The recovery time process of domestic life can be divided into four periods: emergency period (weeks 0–2(5)), early recovery period (weeks 2(5)–
[34] Zhang Y, Peacock W G.2009.

Planning for housing recovery? lessons learned from Hurricane Andrew

[J]. Journal of the American Planning Association, 76(1): 5-24.

https://doi.org/10.1080/01944360903294556      URL      [本文引用: 2]      摘要

is a professor in the Department of Landscape Architecture and Urban Planning and the Sustainable Coastal Margins Program, director of the Hazard Reduction and Recovery Center, interim executive associate dean of the College of Architecture, and the Rodney L. Dockery Endowed Professor in Housing and the Homeless at Texas A&M University. His research focuses on long-term housing recovery, hazard mitigation, and community resiliency.

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