分布式城市需水预测模型研究及应用

发布时间：2018-03-09 03:32

本文选题：分布式城市需水预测模型　切入点：建设用地　出处：《中国水利水电科学研究院》2017年硕士论文　论文类型：学位论文

【摘要】：城市需水量的预测在城市供排水网络规划中具有重要意义。传统的需水预测方法包括水量指标法和概率统计法及系统工程模型广泛应用于城市需水量的预测,但存在一些不足之处。利用不同水量指标法预测得到的城市需水量结果差别较大,水量指标的选取具有一定的主观性。概率统计法及系统工程模型预测得到的城市需水量结果空间尺度有限,难以满足城市供排水网络规划的要求。城市建设用地需水过程和城市建设用地单元类型密切相关,不同建设用地类型之间对水资源的需求强度存在显著差异。文章基于八类城市建设用地类型与三类主要城市需水类型的空间联系,利用城市历年土地利用数据、人口数据及需水量数据,建立了分布式的城市需水预测模型。文章应用分布式城市需水预测模型对厦门市2020年城市需水量进行了预测,利用PEST软件率定了厦门市建设用地单元的需水参数,分析了参数的合理性,预测得到了厦门市2020年城市建成区的需水量及其空间分布。结果表明厦门市2020年的城市需水总量将达到36657万吨,比2014年增长24.17%;居民用地和工业用地的需水强度大于其他建设用地类型,厦门岛内居民用地的需水强度远大于厦门市其他行政区居民用地的需水强度;厦门市城市建成区需水量的空间分布与人口密度具有很好的相关性,不同建设用地类型上需水强度差异明显。此外,文章利用分布式城市需水预测模型预测得到的厦门市2020年城市建成区需水量数据,选取厦门岛内的一片城市典型汇水区,计算了典型汇水区内的自然排水量及人工排水量,并根据典型汇水区的自然排水量及人工排水量数据计算了典型汇水区雨污分流制管网及雨污合流制管网模式下的污水管网排水量。
[Abstract]:The prediction of urban water demand is of great significance in urban water supply and drainage network planning. Traditional water demand forecasting methods include water quantity index method, probability statistics method and system engineering model, which are widely used in urban water demand prediction. However, there are some shortcomings. The results of urban water demand predicted by different water index methods are quite different. The selection of water demand index is subjective. The spatial scale of urban water demand predicted by probabilistic statistical method and system engineering model is limited. It is difficult to meet the requirements of urban water supply and drainage network planning. The process of water demand for urban construction land is closely related to the type of urban construction land unit. There are significant differences in the demand intensity of water resources among different types of construction land. Based on the spatial relationship between the eight types of urban construction land types and the three main types of urban water demand, the paper makes use of the land use data of past years. Based on the population data and water demand data, a distributed urban water demand forecasting model is established in this paper. In 2020, the urban water demand of Xiamen is forecasted by using the distributed urban water demand forecasting model. The water requirement parameters of construction land units in Xiamen are determined by using PEST software, and the rationality of the parameters is analyzed. The water demand and its spatial distribution of the urban built-up area in Xiamen on 2020 are predicted. The results show that the total water demand of Xiamen on 2020 will reach 366.57 million tons. Compared with 2014, the water demand intensity of residential land and industrial land is higher than that of other types of construction land, and the water demand intensity of residential land in Xiamen Island is much higher than that of residential land in other districts of Xiamen. There is a good correlation between the spatial distribution of water demand and population density in urban built-up areas of Xiamen, and there are obvious differences in water demand intensity among different construction land types. Based on the water demand data of urban built-up area in Xiamen in 2020, a typical catchment area in Xiamen Island is selected, and the natural and artificial water discharges in typical catchment area are calculated. According to the data of natural and artificial drainage in typical catchment area, the drainage capacity of sewage pipe network in typical catchment area is calculated.
【学位授予单位】：中国水利水电科学研究院
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TV213.4

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