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题名: 基于DEM和实测河网的河流编码算法研究与实现
其他题名: Research and Implement of River Coding Algorithm Based on DEM and Surveyed River Network
作者: 曾凡华
导师: 胡静涛
分类号: TP311.12
关键词: 河流编码 ; 实测河网 ; 数字高程模型 ; Pfafstetter编码规则 ; 流量计算
索取号: TP311.12/Z22/2010
学位专业: 计算机应用技术
学位类别: 硕士
答辩日期: 2010-06-03
授予单位: 中国科学院沈阳自动化研究所
学位授予地点: 中国科学院沈阳自动化研究所
作者部门: 工业信息学研究室
中文摘要: 当前,国内水环境污染十分严重,尤其是江河流域普遍遭到污染。水利部对全国700余条共约10万km长的河流开展的水资源质量评价结果表明:水质污染严重而不能用于灌溉(即劣于Ⅴ类)的河段约占10.6%;水体己丧失使用价值,受到污染(相当于Ⅳ,Ⅴ类)的河段约占46.5%;城市河流污染形势更为严重。监测数据显示,在14个大中型城市河段中,63.8%的河段污染较重,为Ⅳ类甚至V类水质。在47个环保重点河段中,29.8%属于V类水质。辽河流域、海河流域、淮河流域的城市地表水水质尤其差。全国7大水系国家环境公报数据表明,辽河、海河污染严重,淮河水质很差,黄河水质不容乐观,松花江水质较差。因此,建立河流管理、监测体系就成为亟待解决的问题。而准确的河流管理及监测体系的建立依赖于河流环保信息化建设。河流编码标准化是河流环保信息化建设中重要的技术基础工作,是实现河流环保信息化的基本前提。所以研究适合我国河网的编码标准就具有十分重要的意义。河流编码的方法主要有三种:①采用随机码的河流编码;② Pfafstetter数字编码;③基于二叉树的河流编码。其中随机码的河流编码方法不能精确的表达河流拓扑结构,而基于二叉树的河流编码则编码较长,且不利于上下游的识别。Pfafstetter编码则能很好的表达河流的拓扑结构,易识别河段上下游关系,在国外成熟的编码系统中得到了广泛应用。 本文在研究了Pfafstetter编码规则优缺点基础上,根据我国河网的实际复杂性,对Pfafstetter编码编码规则进行了扩展,使之适合我国河网的实际编码工作需要。具体扩展包括了首层两位编码,分叉河段的编码方法,以及湖泊、水库的编码方法。在完成编码方法扩展之后,还研究了编码方法扩展之后上下游识别的算法。   另外,基于扩展的编码方案,还对编码算法进行了相关的研究,具体包括河网数据的预处理,实测河网流量的确定,河网拓扑结构的表达,递归编码算法等。在流量计算方面,提出了基于实测河网与DEM相结合来进行流量计算的思想,较准确的得出了实测河网各个河段的流域面积。设计了三个层次的数据结构,来分别表示节点、水系、流域,准确的表达了河网的拓扑结构。在最终的编码中,设计了递归的河网编码算法,完成了对河网各个层次的编码。 最后根据扩展的编码方案和编码算法研究结果,设计并实现了自动编码系统,并将这套系统应用到长江流域、辽河流域等河网编码中。通过编码结果验证编码方案和编码算法的正确性及有效性。
英文摘要: Currently, national water environment pollution is very serious; especially river basins were generally polluted. The river water quality assessment carried out by Ministry of Water Resources for more than 700 rivers which are about 100000 km long shows that: rivers which were polluted so serious that can not be used for irrigation (i.e. inferior to Ⅴ class) reaches approximately 10.6%; rivers which were polluted and lost value (the equivalent of Ⅳ,Ⅴ class) reach about 46.5%. City river pollution situation are worse. Monitoring data shows that in 14 large and medium cities' rivers, 63.8% of the rivers are seriously polluted, and ware Ⅳ even Ⅴ class. In the 47 key environmental protection rivers, 29.8% belong to class Ⅴ. Liaohe River, Haihe River and Huaihe River's city surface water was particularly poor. The 7 Big River National Environmental Bulletin data shows that Liaohe River and Haihe River pollution are serious, Huaihe River water quality is poor, Yellow River water quality is not optimistic, and Songhua River water quality is pool. Therefore, the establishment of river management and monitoring system has became a serious problem which must be solved quickly. The establishment of accurate river management and monitoring system depends on the river environmental information construction. River coding standardization is the important technology base work of river environmental information. Therefore, the research of river coding standard for our country is of great significance. There are three main coding methods: ① random code river coding; ② Pfafstetter digital coding; ③ coding based on binary coding; Random coding method can not accurately represent rivers topology, while based on binary tree river coding method's code is long, and is not conducive to the identification of upstream and downstream. Pfafstetter coding method can represent the river topological structure very well, and is easy to identify the relationship between the upstream and downstream reaches, and has been widely used in foreign mature coding systems. Based on the study of Pfafstetter coding rule’s advantages and disadvantages and according to the actual complexity of national river, this paper extended the Pfafstetter coding rules to fit the actual national river network coding needs. Specific extensions include first layer coding using two bits, the coding method for forked river, and coding methods for lakes and reservoirs. After completing the expansion of river coding, the upstream and downstream recognition algorithms after extended were also studied. In addition, based on extended coding method, coding algorithm was studied, specifically including the river network data preprocessing, determination of the surveyed river flow, river network topology expression, and recursive coding algorithm. In the flow calculations, a thought based on the combination of DEM and surveyed river was proposed, and obtained more accurately river basin area for all the reaches. Three levels data structure were designed to represent nodes, water system and basin, therefore the river network topology was accurately represented. In the final code, the design of the recursive encoding algorithm was designed to complete coding various levels of river networks.  Finally, according to the extended coding method and coding algorithm studied results, an automated coding system was designed and implemented, and the system was applied in Yangtze River, Liaohe River and other river networks coding. The coding results verified the correctness and effectiveness of the coding method and coding algorithm.
语种: 中文
产权排序: 1
内容类型: 学位论文
URI标识: http://ir.sia.cn/handle/173321/9346
Appears in Collections:工业信息学研究室_学位论文

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Recommended Citation:
曾凡华.基于DEM和实测河网的河流编码算法研究与实现.[硕士学位论文].中国科学院沈阳自动化研究所.2010
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