Rapid Assessment of Flood Damage and Community-Based Risk Mapping in Flood Diversion Area-Case Study in Wuhan, Hubei Province

Total Page:16

File Type:pdf, Size:1020Kb

Rapid Assessment of Flood Damage and Community-Based Risk Mapping in Flood Diversion Area-Case Study in Wuhan, Hubei Province Rapid Assessment of Flood Damage and Community-based Risk Mapping in Flood Diversion Area-Case Study in Wuhan, Hubei Province January, 2018 1 / 41 Contents 1. Project Overview ........................................................................................................................................................... 3 2. Introduction of the study case ................................................................................................................................. 3 2.1 Introduction of the 2016 Wuhan Floods ................................................................................................. 3 2.2 Introduction of Dujiatai Flood Diversion Area.................................................................................... 5 3. Review of previous studies ........................................................................................................................................ 6 4. Data and Methods ......................................................................................................................................................... 7 4.1 Technology roadmap of the project .......................................................................................................... 7 4.2 Data collection .................................................................................................................................................... 8 4.3 Methods for damage assessment .............................................................................................................. 11 4.4 Methods for risk assessment ...................................................................................................................... 12 4.5 Field investigation of the flood diversion area ................................................................................... 13 5. Results for flood damage assessment ................................................................................................................. 16 5.1 Rapid assessment of the flood disaster with remote sensing ........................................................ 16 5.2 Rapid assessment of the flood disaster with social media ............................................................. 20 5.3 GIS platform for flood rapid assessment ............................................................................................. 26 6. Results for flood risk assessment .......................................................................................................................... 30 6.1 Analytical risk mapping ............................................................................................................................... 30 6.2 Community-based risk mapping .............................................................................................................. 33 7. Conclusion and Discussion ...................................................................................................................................... 35 References ........................................................................................................................................................................... 36 Appendix .............................................................................................................................................................................. 38 2 / 41 1. Project Overview Wuhan, the largest city in Central China, is located at the confluence of the Hanshui and Yangtze rivers and thus has always been a hotspot of flood risk in China. During the 2016 summer, heavy rainstorms and great floods hit Wuhan and its surrounding areas, communities in both urban and rural regions were severely affected and thousands of people in flood diversion area were urgently evacuated, leaving 14 mortalities and 2.26 billion RMB Yuan of economic losses. In the southwest corner of Wuhan, there lies the Dujiatai Flood Diversion Area between Yangtze River and Han River, which is the low- lying rural areas near rivers or lakes that are deliberately flooded in emergencies in order to protect the city. Even though planned as restricted development region, the residents in flood diversion area also increase significantly in recent years. They face greater risk of flood and should be given particular attention during flooding. This project focuses on two major issues that are important and challenging for the flood- prone city of Wuhan and especially the flood diversion area. Firstly, it aims to develop models and tools for rapid assessment of flood damage using modern remote sensing and GIS technology, which is often urgently needed for evacuation and relief after the occurrence of the disaster. Secondly, this project highlights the community participation in disaster reduction and aims to promote the integration of expert’s knowledge and local experience. To achieve this goal, a new flood risk mapping method will be designed in the project that combines local community’s risk perception and traditional risk analysis mainly from expert’s opinion. This project is conducted by researchers from Wuhan University (WHU), China Meteorological Administration (CMA), Beijing Normal University (BNU), University of Southampton and Newcastle University. International cooperation is an important part of this project. It would promote the knowledge exchange and experience sharing in the field of flood risk reduction, and motivate the application of more advanced techniques of flood assessment and risk m apping for the communities in flood diversion area. 2. Introduction of the study case 2.1 Introduction of the 2016 Wuhan Floods The 2016 Wuhan floods lasted about a month from June 30 to the end of July with flooding emergencies evolving with time and space. The accumulated rainfall reached over 560 mm within a week from June 30 to July 6, and 757,000 people were affected with 14 killed during this period. Economic loss reached 2.26 billion Yuan RMB. Some important sites and events are shown in Figure 1 and the process and timeline are illustrated below. 3 / 41 Figure 1. Important sites and events during the 2016 Wuhan Floods (1) July 1 On July 1st, in the northeast part of Wuhan, the water level of Jushui River reached 33.35 meters, exceeding the guaranteed water level with 0.24 meters, and caused severe burst in the phoenix section of the river, greatly threatening Xinzhou District downstream. (2) July 5 After several days of persistent heavy rains, the main districts of Wuhan suffered severe waterlogging. The traffic was disrupted and some communities were severely flooded, especially for those near the South Lake. In addition, thousands of residents in Xiaosi Town (rural area in the southwest) were emergently evacuated in the night of July 5th, as their home would be severely inundated according to the early warning. (3) July 6 Emergency of seepage was found in the main levee of the Yangtze River and if it was not 4 / 41 handled in time, the water in the Yangtze River would directly rush into the main district of Wuhan city and caused disastrous consequences. Premier Li Keqiang inspected the emergency site and demanded more efforts to fight against the floods. (4) July 14 The dyke and separation of Liangzi Lake and Niushan Lake was successfully demolished with blasting on July 14th. This was the emergency measure in response to high water level and great threat of Liangzi Lake. Five hours after the blasting, the water level in Liangzi Lake dropped by 0.17 meter. (5) July 8 and July 21 Great danger of breaching was found in the Tongjiahu Lake on July 8th and 21st. It is near the Tianhe International Airport, and if the water in the lake spilled out, the airport would be severely damaged and it would seriously affect the air transportation. At the end there was luckily no dike breach. 2.2 Introduction of Dujiatai Flood Diversion Area Dujiatai Flood Diversion Area, located in the southwest of Wuhan, is designated to protect Wuhan from the threat of peak discharge from Han River coinciding with high water lever in the Yangtze River (Figure 2). Once enabled, it can store extra floodwater of 1.6 billion cubic meters, which will greatly relieve the flood pressure of the Han River. It is low-lying area between Yangtze River and Han River, and was natural floodplain wetland in history. Now it has a total area of 614 square kilometers and involves 21 villages with total population of 160 thousand from Xiantao city, Caidian and Hannan District of Wuhan. Since its completion in 1956, Dujiatai Flood Diversion project has been used 19 times, and has regulated flood water of 19.125 billion cubic meters. It has played a huge role in guaranteeing flood control and security in the lower reaches of Han River and Wuhan city. From June 30 to July 5 2016, torrential rain hit the Caidian District with accumulated rainfall of 382.2 mm, and it rained 264.7 mm in a single day of July 5th, which is the highest amount of rainfall ever recorded on a single day at this location. Several dangerous situations were found in many places of this region and the water lever in Chen Lake increased over 40 cm and it was still rising, making several breaches in the dike. In the night of July 5th, the local government decided to take emergency measures: 12,000 residents from 12 villages of the Xiaosi Town within the Dujiatai Flood Diversion Area were emergently evacuated as water level was predicted to exceed its historical records and there was high potential of overtopping
Recommended publications
  • Spatiotemporal Evolution of Lakes Under Rapid Urbanization: a Case Study in Wuhan, China
    water Article Spatiotemporal Evolution of Lakes under Rapid Urbanization: A Case Study in Wuhan, China Chao Wen 1, Qingming Zhan 1,* , De Zhan 2, Huang Zhao 2 and Chen Yang 3 1 School of Urban Design, Wuhan University, Wuhan 430072, China; [email protected] 2 China Construction Third Bureau Green Industry Investment Co., Ltd., Wuhan 430072, China; [email protected] (D.Z.); [email protected] (H.Z.) 3 College of Urban and Environmental Sciences, Peking University, Beijing 100871, China; [email protected] * Correspondence: [email protected]; Tel.: +86-139-956-686-39 Abstract: The impact of urbanization on lakes in the urban context has aroused continuous attention from the public. However, the long-term evolution of lakes in a certain megacity and the heterogeneity of the spatial relationship between related influencing factors and lake changes are rarely discussed. The evolution of 58 lakes in Wuhan, China from 1990 to 2019 was analyzed from three aspects of lake area, lake landscape, and lakefront ecology, respectively. The Multi-Scale Geographic Weighted Regression model (MGWR) was then used to analyze the impact of related influencing factors on lake area change. The investigation found that the total area of 58 lakes decreased by 15.3%. A worsening trend was found regarding lake landscape with the five landscape indexes of lakes dropping; in contrast, lakefront ecology saw a gradual recovery with variations in the remote sensing ecological index (RSEI) in the lakefront area. The MGWR regression results showed that, on the whole, the increase in Gross Domestic Product (GDP), RSEI in the lakefront area, precipitation, and humidity Citation: Wen, C.; Zhan, Q.; Zhan, contributed to lake restoration.
    [Show full text]
  • Landscape Analysis of Geographical Names in Hubei Province, China
    Entropy 2014, 16, 6313-6337; doi:10.3390/e16126313 OPEN ACCESS entropy ISSN 1099-4300 www.mdpi.com/journal/entropy Article Landscape Analysis of Geographical Names in Hubei Province, China Xixi Chen 1, Tao Hu 1, Fu Ren 1,2,*, Deng Chen 1, Lan Li 1 and Nan Gao 1 1 School of Resource and Environment Science, Wuhan University, Luoyu Road 129, Wuhan 430079, China; E-Mails: [email protected] (X.C.); [email protected] (T.H.); [email protected] (D.C.); [email protected] (L.L.); [email protected] (N.G.) 2 Key Laboratory of Geographical Information System, Ministry of Education, Wuhan University, Luoyu Road 129, Wuhan 430079, China * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel: +86-27-87664557; Fax: +86-27-68778893. External Editor: Hwa-Lung Yu Received: 20 July 2014; in revised form: 31 October 2014 / Accepted: 26 November 2014 / Published: 1 December 2014 Abstract: Hubei Province is the hub of communications in central China, which directly determines its strategic position in the country’s development. Additionally, Hubei Province is well-known for its diverse landforms, including mountains, hills, mounds and plains. This area is called “The Province of Thousand Lakes” due to the abundance of water resources. Geographical names are exclusive names given to physical or anthropogenic geographic entities at specific spatial locations and are important signs by which humans understand natural and human activities. In this study, geographic information systems (GIS) technology is adopted to establish a geodatabase of geographical names with particular characteristics in Hubei Province and extract certain geomorphologic and environmental factors.
    [Show full text]
  • Four Decades of Wetland Changes of the Largest Freshwater Lake in China: Possible Linkage to the Three Gorges Dam?
    Remote Sensing of Environment 176 (2016) 43–55 Contents lists available at ScienceDirect Remote Sensing of Environment journal homepage: www.elsevier.com/locate/rse Four decades of wetland changes of the largest freshwater lake in China: Possible linkage to the Three Gorges Dam? Lian Feng a, Xingxing Han a, Chuanmin Hu b, Xiaoling Chen a,⁎ a State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China b College of Marine Science, University of South Florida, 140 Seventh Avenue South, St. Petersburg, FL 33701, USA article info abstract Article history: Wetlands provide important ecosystem functions for water alteration and conservation of bio-diversity, yet they Received 17 March 2015 are vulnerable to both human activities and climate changes. Using four decades of Landsat and HJ-1A/1B satel- Received in revised form 10 December 2015 lites observations and recently developed classification algorithms, long-term wetland changes in Poyang Lake, Accepted 17 January 2016 the largest freshwater lake of China, have been investigated in this study. In dry seasons, while the transitions Available online xxxx from mudflat to vegetation and vice versa were comparable before 2001, vegetation area increased by 2 Keywords: 620.8 km (16.6% of the lake area) between 2001 and 2013. In wet seasons, although no obvious land cover Poyang Lake changes were observed between 1977 and 2003, ~30% of the Nanjishan Wetland National Nature Reserve Wetland (NWNNR) in the south lake changed from water to emerged plant during 2003 and 2014. The changing rate of Three Gorges Dam the Normalized Difference Vegetation Index (NDVI) in dry seasons showed that the vegetation in the lake center Wetland vegetation regions flourished, while the growth of vegetation in the off-water areas was stressed.
    [Show full text]
  • Contingent Valuation of Yangtze Finless Porpoises in Poyang Lake, China Dong, Yanyan
    Contingent Valuation of Yangtze Finless Porpoises in Poyang Lake, China An der Wirtschaftswissenschaftlichen Fakultät der Universität Leipzig eingereichte DISSERTATION zur Erlangung des akademischen Grades Doktor der Wirtschaftswissenschaft (Dr. rer. pol.) vorgelegt von Yanyan Dong Master der Ingenieurwissenschaft. Leipzig, im September 2010 Acknowledgements This study has been conducted during my stay at the Department of Economics at the Helmholtz Center for Environmental research from September 2007 to December 2010. I would like to take this opportunity to express my gratitude to the following people: First and foremost, I would like to express my sincere gratitude to Professor Dr. Bernd Hansjürgens for his supervision and guidance. With his kind help, I received the precious chance to do my PhD study in UFZ. Also I have been receiving his continuous support during the entire time of my research stay. He provides lots of thorough and constructive suggestions on my dissertation. Secondly, I would like to thank Professor Dr. -Ing. Rober Holländer for his willingness to supervise me and his continuous support so that I can deliver my thesis at the University of Leipzig. Thirdly, I am heartily thankful to Dr. Nele Lienhoop, who helped me a lot complete the writing of this dissertation. She was always there to meet and talk about my ideas and to ask me good questions to help me. Furthermore, there are lots of other people who I would like to thank: Ms. Sara Herkle provided the survey data collected in Leipzig and Halle, Germany. Without these data, my thesis could not have been completed. It is my great honor to thank Professor John B.
    [Show full text]
  • Exploring the Impact of Real Estate Policy on Real Estate Trading Using the Time Series Analysis
    The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3/W10, 2020 International Conference on Geomatics in the Big Data Era (ICGBD), 15–17 November 2019, Guilin, Guangxi, China EXPLORING THE IMPACT OF REAL ESTATE POLICY ON REAL ESTATE TRADING USING THE TIME SERIES ANALYSIS Shiwei Shao*, Xin Huang, Lixia Xiao, Hui Liu Wuhan Land Resource and Urban Planning Information Center, Wuhan, China, [email protected] KEY WORDS: Time series analysis, Real estate, Policy analysis, Turning point detection ABSTRACT: Housing price is a major issue affecting people's lives, but also closely related to the interests of the people themselves. Housing prices are affected by various factors, such as economic factors, population size factors, social factors, national policy factors, the internal factors of real estate and environmental factors. With the deepening of urbanization and the agglomeration of urban population in China, housing prices have been further accelerated. The Chinese government has also introduced a series of policies to limit real estate transactions and affect property prices. This paper also aims to explore a time series analysis method to analyse the impact of real estate policies on real estate prices. Firstly, the article searches for policy factors related to real estate through government official channels such as state, Prefecture and city, and analyses key words related to policy by means of natural language processing. Then, the real estate registration volume, transaction volume and transaction house price data which are arranged into time series are modelled using ARIMA time series model, and the data are processed according to scatter plot, autocorrelation function and partial autocorrelation function graph of the model to identify its stationarity.
    [Show full text]
  • Exploring the Spatial Pattern of Urban Block Development Based on POI Analysis: a Case Study in Wuhan, China
    sustainability Article Exploring the Spatial Pattern of Urban Block Development Based on POI Analysis: A Case Study in Wuhan, China Hailing Xu, Jianghong Zhu * and Zhanqi Wang School of Public Administration, China University of Geosciences, Wuhan 430074, China; [email protected] (H.X.); [email protected] (Z.W.) * Correspondence: [email protected]; Tel.: +86-1339-715-7676 Received: 3 November 2019; Accepted: 4 December 2019; Published: 6 December 2019 Abstract: As a kind of geospatial big data, point of interest (POI) with useful information has become a hot research topic. Compared with traditional methods, big data has great potential in developing a more accurate method for identifying the urban spatial pattern. This paper uses diversity index and kernel density analysis of POI data on several types of urban infrastructure to investigate the identification of urban block development stages in Wuhan, and divides them into the primary, growth, and mature stage. Its accuracy is verified by exploring urban micro-centers. Results show that: (1) the spatial pattern of urban blocks in Wuhan presents the distribution of “mature blocks concentrated like a core, growth blocks distributed like two wings, and primary blocks with wide range distributed surround”; (2) areas with more connected construction land and streets with better socio-economic status tend to have a higher level of maturity, vice versa; (3) balancing the number of micro-centers at different stages is beneficial to promote the flattened urban development of Wuhan in the future. The research proves that this method is feasible, and it is also applicable to the study of urban spatial pattern in other cities.
    [Show full text]
  • Spatial Statistics and Influencing Factors of the Novel Coronavirus
    Spatial statistics and inuencing factors of the novel coronavirus pneumonia 2019 epidemic in Hubei Province, China Yongzhu Xiong ( [email protected] ) Institute of Resources and Environmental Informatics Systems, Jiaying University https://orcid.org/0000-0002-4417-6409 Yunpeng Wang Guangzhou Institute of Geochemistry, Chinese Academy of Sciences Feng Chen College of Computer and Information Engineering, Xiamen University of Technology Mingyong Zhu Institute of Resources and Environmental Informatics Systems, Jiaying University Research Article Keywords: novel coronavirus pneumonia (NCP), spatial autocorrelation, inuencing factor, spatial statistics, Wuhan Posted Date: April 6th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-16858/v2 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published on May 31st, 2020. See the published version at https://doi.org/10.3390/ijerph17113903. Page 1/25 Abstract An in-depth understanding of the spatiotemporal dynamic characteristics of infectious diseases could be helpful for epidemic prevention and control. Based on the novel coronavirus pneumonia (NCP) data published on ocial websites, GIS spatial statistics and Pearson correlation methods were used to analyze the spatial autocorrelation and inuencing factors of the 2019 NCP epidemic from January 30, 2020 to February 18, 2020. The following results were obtained. (1) During the study period, Hubei Province was the only signicant cluster area and hotspot of cumulative conrmed cases of NCP infection at the provincial level in China. (2) The NCP epidemic in China had a very signicant global spatial autocorrelation at the prefecture-city level, and Wuhan was the signicant hotspot and cluster city for cumulative conrmed NCP cases in the whole country.
    [Show full text]
  • Distribution of COVID-19 Morbidity Rate in Association with Social and Economic Factors in Wuhan, China: Implications for Urban Development
    International Journal of Environmental Research and Public Health Article Distribution of COVID-19 Morbidity Rate in Association with Social and Economic Factors in Wuhan, China: Implications for Urban Development Heyuan You 1,2,*, Xin Wu 1 and Xuxu Guo 1 1 School of Public Administration, Zhejiang University of Finance and Economics, Hangzhou 310018, China; [email protected] (X.W.); [email protected] (X.G.) 2 Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA * Correspondence: [email protected]; Tel.: +865-7186735200 Received: 14 April 2020; Accepted: 11 May 2020; Published: 14 May 2020 Abstract: Social and economic factors relate to the prevention and control of infectious diseases. The purpose of this paper was to assess the distribution of COVID-19 morbidity rate in association with social and economic factors and discuss the implications for urban development that help to control infectious diseases. This study was a cross-sectional study. In this study, social and economic factors were classified into three dimensions: built environment, economic activities, and public service status. The method applied in this study was the spatial regression analysis. In the 13 districts in Wuhan, the spatial regression analysis was applied. The results showed that: 1) increasing population density, construction land area proportion, value-added of tertiary industry per unit of land area, total retail sales of consumer goods per unit of land area, public green space density, aged population density were associated with an increased COVID-19 morbidity rate due to the positive characteristics of estimated coefficients of these variables.
    [Show full text]
  • Minimum Wage Standards in China August 11, 2020
    Minimum Wage Standards in China August 11, 2020 Contents Heilongjiang ................................................................................................................................................. 3 Jilin ............................................................................................................................................................... 3 Liaoning ........................................................................................................................................................ 4 Inner Mongolia Autonomous Region ........................................................................................................... 7 Beijing......................................................................................................................................................... 10 Hebei ........................................................................................................................................................... 11 Henan .......................................................................................................................................................... 13 Shandong .................................................................................................................................................... 14 Shanxi ......................................................................................................................................................... 16 Shaanxi ......................................................................................................................................................
    [Show full text]
  • Wuhan Is the Capital of Hubei Province, People's Republic of China, and Is the Most Populous City in Central China
    Wuhan is the capital of Hubei province, People's Republic of China, and is the most populous city in central China. It lies at the east of Jianghan Plain, and the intersection of the middle reaches of the Yangtze and Han River. Arising out of the conglomeration of three boroughs, Wuchang, Hankou, and Hanyang, Wuhan is known as "the nine provinces' leading thoroughfare"; it is a major transportation hub, with dozens of railways, roads and expressways passing through the city. The city of Wuhan, first termed as such in 1927, has a population of approximately 9,100,000 people (2006), with about 6,100,000 residents in its urban area. In the 1920s, Wuhan was the capital of a leftist Kuomintang (KMT) government led by Wang Jingwei in opposition to Chiang Kai-shek, now Wuhan is recognized as the political, economic, financial, cultural, and educational and transportation center of central China. Tourism: Replica instruments of ancient originals are played at the Hubei Provincial Museum. A replica set of bronze concert bells is in the background and a set of stone chimes is to the rightWuchang has the largest lake within a city in China, the East Lake, as well as the South Lake. The Hubei Provincial Museum includes many artifacts excavated from ancient tombs, including a concert bell set (bianzhong). A dance and orchestral show is frequently performed here, using reproductions of the original instruments. The Rock and Bonsai Museum includes a mounted platybelodon skeleton, many unique stones, a quartz crystal the size of an automobile, and an outdoor garden with miniature trees in the penjing ("Chinese Bonsai") style.
    [Show full text]
  • Associating the COVID-19 Severity with Urban Factors: a Case Study of Wuhan
    Associating the COVID-19 Severity with Urban Factors: A Case Study of Wuhan Xin Li School of Architecture and Civil Engineering, Xiamen University Lin Zhou School of Urban Design, Wuhan University Tao Jia ( [email protected] ) Wuhan University Ran Peng School of Civil Engineering and Architecture, Wuhan Institute of Technology Xiongwu Fu Wuhan Landuse and Urban Spatial Planning Research Center Yuliang Zou School of Public Health, Wuhan University Research Keywords: COVID-19, Weibo, epidemic pattern, spatial analysis, urban factors Posted Date: June 18th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-34863/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/28 Abstract Wuhan encountered a serious attack in the rst round of the COVID-19 pandemic which has resulted in serious worldwide consequences politically and economically. Based on the Weibo help data, we inferred the spatial distribution pattern of the epidemic situation and its impacts. Seven urban factors, i.e. urban growth, general hospital, commercial facilities, subway station, landuse mixture, aging ratio, and road density, were selected for validation with the ordinary linear model, and the former six presented globally signicant association with the epidemic severity; thereafter, the geographically weighted regression model was further adopted for local test to identify their unevenly distributed effects in urban space. Among the six, the place where general hospitals exert effects on epidemic situation highly is associated with their distribution and density; commercial facilities appear the most prevalently distributed factor over the city; newly developed residential quarters with high-rise buildings face greater risks, mainly distributed around the waterfront area of Hanyang and Wuchang; the inuence of subway stations concentrates at the adjacency place where the three towns meet and near-terminal locations; aging ratio dominantly affects the hinterland of Hankou in a broader extent than other areas in the city.
    [Show full text]
  • Hubei Jinzhou Historic Town Restoration
    SFG1138 V2 G.H.P.Z.J.Z. No. 2606 Public Disclosure Authorized World Bank Financed Hubei Jingzhou Historic Town Restoration and Protection Project Public Disclosure Authorized Environmental and Social Impact Assessment Report Public Disclosure Authorized Public Disclosure Authorized Hubei Academy of Environmental Sciences May 2015 G.H.P.Z.J.Z. No. 2606 World Bank Financed Hubei Jingzhou Historic Town Restoration and Protection Project Environmental and Social Impact Assessment Report (For Appraisal) President : Zhang Gang Vice President : Li Songbing Chief Engineer : Zhang Bin Director of EIAC : Liu Zhe Agency : Hubei Academy of Environmental Sciences Address : No. 338 Bayi Road, Wuhan City Post Code : 430072 Tel : 027-87654413 E-mail : [email protected] Hubei Academy of Environmental Sciences May 2015 World Bank Financed Hubei Jingzhou Historic Project name : Town Restoration and Protection Project Assessment Hubei Academy of Environmental Sciences : agency (official seal) Legal : Zhang Gang (name seal) representative Project leader : Liu Zhe Wang Cong Project : Li Songbing approver Contributors and assignment of responsibilities Member Certificate No. Assignment of responsibilities/chapters Signature Liu Zhe A26060231000 Preface, General, Retrospective evaluation Wang Project Analysis, Analysis of Impact on A26060089 Cong Associated Area Environmental Protection Measures, Kou A26060290700 Environmental Management Plan, Analysis Xueyong of Environment and Economic Profit & Loss Environmental Impact Prediction and Analysis, Public Consultation and Yu Jian A26060370900 Information Publicity, Conclusion and suggestions Luo Comparative Analysis of the Schemes, A26060056 Feng Analysis of Impact on Associated Area Revision checklist Chapter and No. Opinions from World Bank Revised content Page No. According to the content of the latest feasibility report, the Improve the environemental total project investment, assessmentreport according to the project content, earthwork 1 revised version.
    [Show full text]