published_or_final_version / Real Estate and Construction / Master / Master of Science in Construction Project Management

在中国，绝大多数煤矿事故主要是由煤矿瓦斯和煤矿突水造成。统计数据显示，目前煤矿水灾引起的直接经济损失已经排在了所有煤矿灾害之前，煤矿水灾已经日益成为最危险的一种煤矿灾害。现阶段在煤矿完全方面主要目标就是尽量减少发生煤矿瓦斯爆炸和水灾的隐患。因此，对于预防和处理煤矿水灾来说，设计一种快速且准确的煤矿水灾的风险评价方法是非常急需的。传统的风险评价方法需要进行大量的广泛的地质调查来寻找地表裂隙等引起煤矿水灾的分险源。这些裂隙主要是因为地面形变造成，这种地面形变在煤矿区一般是由于地下采矿活动或者煤火造成塌陷引起的，或者两者共同作用引起的。一般情况下，煤矿区地处偏远，高海拔，不宜居住的地方，尤其是有煤火的地方，更加不易进行全面地调查。因此，我们认为使用卫星遥感数据对煤矿区大范围周期性的监测，并及时提取与煤矿水灾相关的信息进行风险分析的方法相对与传统方式来说更为便捷，更为及时。经过对乌达煤矿区的野外调查，我们确定了一些会引起乌达煤矿水灾的致灾因素，例如煤火，剥挖坑，渣堆等特有的因素。 / 本论文提出一个利用遥感，地理信息技术以及水文模型相结合的煤矿区水灾分险评估模型。在这个模型中，首先根据地质和水文数据确定了14个引起该地区水灾灾害的主要影响因素。通过野外调查，专家组一致认为降雨，特别是大暴雨，剥挖坑和地表裂隙是乌达煤矿区最重要的几个因素。分析野外调查成果，可以发现煤火和沉降与试验区地表裂隙有着正相关性。因此在这个模型中，引入煤火和沉降信息来代替实际地表裂隙情况。煤火和沉降信息可以通过多种遥感数据获得。在获得所有致灾因素的信息后，结合专家组的意见，通过层次分析法（AHP）来建立致灾因素的层次并通过成对比较矩阵计算各个致灾因素的权重。最后，通过模型计算得到最终的煤矿区风险评估图。本文得到的结果与神华（北京）遥感勘查有限责任公司实地调查后形成的风险评估图进行对比，结果显示风险分布基本相同。本文也探讨了可能造成两者差异的原因。最后，针对某一高风险区进行实地的钻孔和地震探测验证，结果显示该地区的致灾因素特征明显，具备高风险特性。 / 验证结果表明，本文提出的方法是具有可操作性的且准确高效，具有一定的煤矿水灾预测作用。我们希望该方法通过进一步的改进，能够应用到实际的煤矿水灾风险评价预测中去。 / In China, coal mine accidents were mainly caused by gas and water inrush. Recently, the direct economic loss caused by coal mine flood has been ranked the first among all kinds of coal mine disasters. Reducing water inrush accidents become the main direction and aiming of coal mine security control. From the statistics of coal mine disasters, we learned that the coal mine flood disasters have become the most dangerous mine disaster. There is, therefore, an urgent need to design and provide a coal mine flood risk assessment timely and accurately for mine companies to prevent and deal with the coal mine flood. Traditional approaches investigate the geological condition and find out the exactly numbers and width of fissures caused by coal mining or coal fires burnt. However, the shortcomings of these methods are time consuming, difficult to repeat, and costly to apply over large areas, especially, for many coal mine area located in isolated region, high up in the mountains, in dense forests, and other inhospitable terrains. Hence the use of GIS technology and remote sensing data, particularly satellite remote sensing with a capability of repeated observation of the earth surface, was considered as a very effective approach to detect, analyze and monitor information of mine flood in coal mine area over a large areas. / In this research a risk assessment model was proposed to assess the mine flood risk in Wuda coal mine area using RS, GIS techniques and basic hydrological model. First of all, we analyzed the major factors causing coal mine flood in Wuda coal field, based on the geological and hydrological data. According to the investigated material and the experiences from geologists and coal mining experts, four main criteria including water sources, surface condition, water conductors and water containers as well as fourteen factors were selected to participate the assessment, among which, rainfall, stripping digging pits and fissures were considered as the three main factors to cause mine flood in Wuda coal mine area. The rainfall and sinks information were easily to derive. However, the fissures information was difficult to obtain. Based on the analysis of investigation, the positive correlation between fissures and coal fires or subsidence was obtained. Therefore, the coal fire factor and ground subsidence factor were imported to indicate the fissures information. Then, a method for deriving these impact factors was proposed for coal mine flood risk assessment model. After obtaining the all factors related information, the weights of these factors were calculated by pair-wise comparison method, which depend on the specialists’ opinions. A risk assessment analysis approach based on AHP was created for combining these factors and calculating the results. / Finally, based on the result from risk assessment model, a risk assessment indication map was generated using GIS software. By comparing our assessment result with the Wuda coal flood risk map from Shenhua Group, we noticed that the distribution and levels of coal mine flood risk are similar. Some other auxiliary techniques, for instance, the geological drilling and geological radar detection, were used to validate the result of our study. These techniques also proved the final result is reasonable and acceptable. After the investigation and evaluation, some conclusions and suggestions, were proposed for coal mine companies to avoid or reduce the risk from coal mine flood. / The results indicate that the methodology is effective and practical; thus, it has the potential to forecast the ood risk for coal mine ood risk management. Therefore, it can be used as a final risk assessment model for mine flooding in coal fire area. In the future, we will conduct such risk analysis to mitigate the impact from coal mine flood disasters. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Wang, Shengxiao. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 162-174). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese. / Abstract --- p.i / TABLE OF CONTENT --- p.vi / LIST OF TABLES --- p.ix / LIST OF FIGURES --- p.x / Acknowledgements --- p.xiii / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Coal mine disasters in China --- p.1 / Chapter 1.2 --- Coal mine flood in China --- p.4 / Chapter 1.3 --- Background of Wuda coal mine area --- p.6 / Chapter 1.4 --- Research objectives --- p.9 / Chapter 1.5 --- Structure of the thesis --- p.11 / Chapter 2. --- Background --- p.12 / Chapter 2.1 --- Coal mine flood --- p.12 / Chapter 2.1.1 --- Classification of coal mine flood --- p.12 / Chapter 2.1.2 --- Current rescuing situation of coal mine flood --- p.13 / Chapter 2.2 --- The Longwall coal mining --- p.14 / Chapter 2.3 --- Coal mining Subsidence --- p.19 / Chapter 2.3.1 --- Subsidence Mechanisms --- p.19 / Chapter 2.3.2 --- Subsidence and Fissures --- p.20 / Chapter 2.3.3 --- Previous investigations --- p.22 / Chapter 2.4 --- Coal fire and fissures --- p.24 / Chapter 2.4.1 --- Definition and Classification --- p.24 / Chapter 2.4.2 --- Combustionmechanism --- p.27 / Chapter 2.4.3 --- Production of coal fire - Minerals and Burnt rock --- p.29 / Chapter 2.4.4 --- Ground temperature related to the coal fire --- p.31 / Chapter 2.4.5 --- Fissures caused by Coal fire --- p.32 / Chapter 2.4.6 --- Detecting Coal Fires Using Remote Sensing --- p.34 / Chapter 2.5 --- Assessment methods review --- p.37 / Chapter 3. --- Description of the study areas & data sets --- p.39 / Chapter 3.1 --- Study area --- p.39 / Chapter 3.2 --- Geography --- p.40 / Chapter 3.2.1 --- Geographical position --- p.40 / Chapter 3.2.2 --- Climate --- p.41 / Chapter 3.3 --- Geology --- p.42 / Chapter 3.3.1 --- Geology structure --- p.42 / Chapter 3.3.2 --- The stratigraphy of coal --- p.43 / Chapter 3.4 --- Hydrology --- p.46 / Chapter 3.4.1 --- Hydrogeological characteristics --- p.46 / Chapter 3.4.2 --- Surface hydrological characteristics --- p.46 / Chapter 3.5 --- Three major coal mine overviews of the assessment area --- p.48 / Chapter 3.5.1 --- Suhaitu coal mine --- p.48 / Chapter 3.5.2 --- Huangbaici coal --- p.51 / Chapter 3.5.3 --- Wuhushan coal --- p.53 / Chapter 3.6 --- Data available --- p.55 / Chapter 3.6.1 --- Data available for this research --- p.55 / Chapter 3.6.2 --- Collection materials and data for reference --- p.55 / Chapter 4. --- Investigation and Analysis of Risk Factors --- p.57 / Chapter 4.1 --- Currentstatus of Wuda Coalfield --- p.57 / Chapter 4.2 --- Water source --- p.58 / Chapter 4.2.1 --- Rain fall --- p.58 / Chapter 4.3 --- Surface Condition --- p.59 / Chapter 4.3.1 --- Flood ditches and surfacerunoff --- p.59 / Chapter 4.3.2 --- Stripping digging pits --- p.61 / Chapter 4.3.3 --- Slag heap --- p.67 / Chapter 4.3.4 --- Water yield of three main coal mine --- p.71 / Chapter 4.4 --- Water conductors investigation --- p.72 / Chapter 4.4.1 --- Faults --- p.73 / Chapter 4.4.2 --- Fissures investigation --- p.75 / Chapter 4.4.3 --- Investigation and analysis of fissures --- p.81 / Chapter 4.4.4 --- Abandoned tunnel and (illegal) private coal mine --- p.83 / Chapter 4.4.5 --- Subsurface Detection- Geological radar --- p.84 / Chapter 5. --- Methodology and Information acquisition --- p.87 / Chapter 5.1 --- Evaluation Index System --- p.87 / Chapter 5.1.1 --- Methodologies in Establishing the Evaluation Index System --- p.87 / Chapter 5.1.2 --- Principles for Establishing Evaluation Index System --- p.88 / Chapter 5.1.3 --- Method in Establishing Evaluation Index System --- p.89 / Chapter 5.1.4 --- Flow chart --- p.90 / Chapter 5.2 --- Storm Rainfall Design --- p.91 / Chapter 5.3 --- Drainage network and fill sinks extraction --- p.94 / Chapter 5.3.1 --- Surfacerunoff model --- p.94 / Chapter 5.3.2 --- Fill Sinks (peaks) --- p.96 / Chapter 5.3.3 --- Flow Direction --- p.97 / Chapter 5.3.4 --- Flow accumulation --- p.98 / Chapter 5.4 --- Traditional methods of derived Fissures area and depth --- p.101 / Chapter 5.5 --- The method of obtaining coal fire information --- p.103 / Chapter 5.5.1 --- Remote sensing data --- p.105 / Chapter 5.5.2 --- Land use classification --- p.105 / Chapter 5.5.3 --- Temperatureretrieval based on TM/ETM+ --- p.107 / Chapter 5.5.4 --- Results of coal fire retrieval --- p.110 / Chapter 5.6 --- The method of obtaining coal mine subsidence area --- p.113 / Chapter 5.7 --- Illegal private coal mine detecting --- p.115 / Chapter 5.8 --- The Analytic Hierarchy Process (AHP) --- p.118 / Chapter 5.8.1 --- Introduction of AHP --- p.118 / Chapter 5.8.2 --- The procedure of AHP --- p.120 / Chapter 6. --- Evaluation and validation --- p.122 / Chapter 6.1 --- Workflow --- p.122 / Chapter 6.2 --- Develop a decision hierarchy structure --- p.122 / Chapter 6.2.1 --- Choosing evaluation indicator --- p.123 / Chapter 6.3 --- Weights distribution --- p.124 / Chapter 6.3.1 --- Establishment of comparison matrix --- p.125 / Chapter 6.3.2 --- Weight Calculation and Consistency Check --- p.127 / Chapter 6.3.3 --- Global weight calculation and global consistency check --- p.131 / Chapter 6.4 --- Data Preparation and Classification --- p.133 / Chapter 6.4.1 --- Rainfall classification --- p.134 / Chapter 6.4.2 --- Classification of surface condition --- p.135 / Chapter 6.4.3 --- Classification of conductor --- p.138 / Chapter 6.5 --- Result of Factor weight overlay --- p.140 / Chapter 6.4.1. --- Results --- p.140 / Chapter 6.4.2 --- Compare with Risk Map from Shenhua Group --- p.143 / Chapter 6.4.3 --- Fieldwork Validation --- p.145 / Chapter 7. --- Conclusions and suggestions --- p.150 / Chapter 7.1 --- Results and conclusions --- p.150 / Chapter 7.2 --- Eliminate potentialdangerous source --- p.152 / Chapter 7.3 --- Flood prevention measures recommended --- p.153 / Chapter 7.3.1 --- Mainly measures for flood prevention --- p.154 / Chapter 7.3.2 --- General prevention and control of surface water --- p.155 / Chapter 7.3.3 --- Establish mechanisms and systems to prevent coal mine flood --- p.156 / Chapter 7.3.4 --- Strengthen the basic work to prevent coal mine accidents --- p.158 / Chapter 7.3.5 --- Investigation and remediation work to prevent coal mine accidents --- p.159 / Chapter 7.4 --- Future work --- p.160 / References --- p.162

published_or_final_version / Public Administration / Master / Master of Public Administration