用户名: 密码: 验证码:
合肥市城市需水量预测研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
随着人口的增长和经济的高速发展,我国出现许多缺水城市,水资源供需矛盾日益加剧,需水量预测研究已成为当前水资源规划与管理研究中的重要课题之一。合肥市是安徽省省会,在国家推进中部崛起的大背景下,合肥市推出了“141”发展战略。因此,及时、科学地预测合肥市城市需水量,对有计划地指导水资源开发利用,促进合肥市水资源可持续利用和国民经济的可持续发展,顺利实施合肥市发展战略,具有重要的理论与现实意义。
     城市需水量包括生活需水量、工业需水量、生态环境需水量三个方面,其中,生态环境需水量的研究是当前城市需水预测的热点和难点。本文通过调研合肥市历史经济发展状况以及气象水文、历年供水等资料,对合肥市用水情况进行结构分析。在此基础上,借鉴已有研究成果,对三种需水量分别建立了相应的预测模型并对规划年作出预测。以人均综合生活用水量指标作为预测参数,经过多种模型拟合误差的对比分析,选择BP神经网络模型作为预测模型,再根据各规划年人口数预测出各规划年合肥市居民综合生活需水量;以工业产值作为预测参数,经过多种模型拟合误差的对比分析,选择GM(1,1)模型作为预测模型,再根据万元产值需水量预测出各规划年合肥市工业需水量;根据城市生态环境需水理论,将城市生态环境需水分为城市绿地需水量和河湖系统生态环境需水,综合考虑绿化灌溉、绿地植被蒸散、植被生长、维持植被生长的最小土壤含水量以及水面蒸发、河湖水库渗漏、河道基流、水体自身存在需水量等方面,分别建立了城市绿地和河湖系统生态环境需水量预测模型,从而预测出各规划年合肥市城市生态环境需水量以及城市最小生态环境需水量。
     最后依据城市总体规划中提出的可供水量进行了城市水资源的用水供需平衡分析,得出各规划年余缺水量,结果显示可供水资源能满足合肥市居民生活、工业及城市最小生态环境需水的要求,但城市生态环境需水不能完全满足,对此,提出了若干对策建议。
With the rising population and the fast growing economy, many cities are lack of water, the contradiction of water supply and demand aggravate. The research for forecasting urban water requirements has become an important issue of water resources planning and management. As the capital of Anhui province, under the background of promoting the growth of central cities, hence Hefei has carried out a development strategy in the name of "141" . In order to assure the sustainable utilization of water resources of Hefei and the sustainable development of national economy, forecasting urban water demand scientifically and immediately can guide the water resource development and utilization, which is of theoretical and practical importance.
     Urban water requirements include domestic water demand, industrial water demand and urban eco-environmental water requirements (UEEWR).The research on UEEWR is a popular and difficult problem of water demand prediction. Economic development status, weather and hydrology and yearly water supply were surveyed, and then water consumption in Hefei was analyzed. On that basis, prediction models of three water requirements were setup respectively with reference to current literatures, planning year was predicted as well. Different models are used for the prediction of water utilization per capita, after analyzing model fitting errors, BP nervous network methods were chosen and comprehensive domestic water demand was forecast according to the population in each planning year. With the industrial product as the prediction parameter, GM(1,1) model was selected through analyzing model fitting errors, then Hefei's industrial water demand was predicted on the basis of water demand of per 10 thousand yuan output. In accordance with its theory, UEEWR includes urban greenbelt system and urban rivers and lakes system. Considering plant irrigation and growth, evaporation and leakage, oil water requirements, water surface evaporation and leakage, lake maintenance and river channels base flow and so on, and then prediction models to forecast each planning year UEEWR and urban least eco-environmental water requirements (ULEEWR) were formed respectively.
     Based on the analysis of balance between water supply and demand presented in the city's overall planning, the amount of residue or lack of water in each planning year was obtained. The results showed that available water supply could satisfy water demand of local residents, industries and minimum ULEEWR in each planning year, but it could not satisfy UEEWR fully, then some measures and suggestions were proposed.
引文
[1] 水利部南京水文水资源所,中国水利水电科学研究院水资源研究所.21世纪中国水供求[M].北京:中国水利水电出版社,1999
    [2] 张丽.水资源承载能力与生态需水量理论及应用[M].河南:黄河水利出版社,2005年5月
    [3] 戴慎志,陈践.城市给水排水工程规划[M].安徽:安徽科学技术出版社,1999年3月
    [4] 左其亭,窦明,吴泽宁.水资源规划与管理[M].北京:中国水利水电出版社,2005年5月
    [5] Gallagher D.R, Boland J.J, LePlastrier B.J et al. Methods for Forecasting Urban Water Demands. Australian:Australian water resources council, 1981
    [6] 牛慧恩.需水量预测研究评述[J].四川师范大学学报(自然科学版),1996,19(1):104~109
    [7] 马兴冠,傅金祥,李勇.水资源需水量预测研究[J].沈阳建筑工程学院学报(自然科学版),2002,18(4):135~138
    [8] Orit Wilchfort and Jay R.Lund. Shorting management modeling for urban water supply systems[J]. Journal of Water Resource Planning and Management, 1999, 123(4): 250~258
    [9] Zhou S.L, McMahon T.A, Walton A. Forecasting daily urban water demand:a ease study of Melbourne[J]. Journal of Hydrology, 2000, 236: 153~164
    [10] Jain A,Varshney A K, Joshi U CH.Short-Term Water Demand Forecast Modeling at IIT Kanpur Using Artificial Neural Networks. Water Resources Management, 2001, 15(5): 299~321
    [11] 杨芳,张宏伟,刘洪波.城市供水负荷短期预测方法[J].天津大学学报,2002,35(2):167~170
    [12] 张洪国,赵洪宾,李恩辕.城市用水量灰色预测[J].哈尔滨建筑大学学报(自然科学版),1998,31(4):32~37
    [13] 张鑫,蔡焕杰.区域生态需水量及水资源调控模式研究综述[J].西北农林科技大学学报,200l,29:84~88
    [14] 崔树彬.生态环境需水量一些问题的讨论[J].中国水利,2001,8:71~75
    [15] 吴国昌等.日本水资源丌发利用及保护[M].北京:中国环境科学出版社,1991
    [16] McMahon,T.A., Arenas,A.D..Methods of computation of low stream flow[J]. Paris,UNESCO Studies and reports in hydrology,1982,36:107
    [17] Falkenmark, M. Coping with water scarcity under rapid pollution growth[A]. Conference of SADC Minsters[C], Pretoria. 1995, 23~24
    [18] Gleick P.H.Water in crisis: paths to sustainable water use [J]. Ecological Applications. 1996,8(3): 571~579
    [19] Rashin,P.D,Hansen,E,Margolis,R.M.Water and sustainability:Global Patterns and long-range problems[J].Natural research forum, 1996, 20(1): 1~15
    [20] Whipple, et al. A Proposed Approach to Coordination of Water Resource development and Environment Regulations[J].Journal of the American Water Resources Association. 1999,35(4): 713~716
    [21] Baird A J,Wilby R L.Eco-hydrology: Plant and water in terrestrial and aquatic environments[M].London and New York: Routledge Press, 1999, 78~156
    [22] Sn.Dakova, Y.Uzunov, D.Mandadjiev. Low flow-the river's ecosystem Limiting factor[J], Ecological Engineering, 2000, (16): 167~174
    [23] Armbruster J T. An infiltration index useful in estimating low-flow characteristics of drainage basins. J.Res.USDS, 1976, 4(5): 533~538
    [24] Geoffrey E.Petts. Water allocation to protect river ecosystems[J]. Regulated rivers: research and management. 1996(12): 353~365
    [25] FREND: Flow Regimes from Experimental and Network Data Ⅰ:Hydro-logical Studies Ⅱ. Hydrological Data[M], Data[M],Wallingford,UK,1989
    [26] FRIEND: Flow Regimes from International Experimental and Network Data[R]. IAHS publicationNo.221, 1994, 525
    [27] 汤奇成.绿洲的发展与水资源的合理利用[J].干旱区资源与环境,1995,9(3):107~112
    [28] 贾宝全,慈龙骏.新疆生态用水量初步估算[J].生态学报,2000,20(2):243~250
    [29] 王礼先.植被生态建设与生态用水—西北地区为例[J].水土保持研究,2000,7(3):5~7
    [30] 王芳,王浩,陈敏捷等.中国西北地区生态需水研究(2)——基于遥感和地理信息系统技术的区域生态需水计算及分析[J].自然资源学报,2002,17(2):129~137
    [31] 刘昌明,何希吾等.中国21世纪水问题方略[M].北京:科学出版社,1998
    [32] 李丽娟,郑红星.海滦河流域河流系统生态需水量计算[J].地理学报,2000,55(4):495~500
    [33] 中国工程院.中国可持续发展水资源战略研究综合报告[M].北京:中国水利水电出版社,1999年6月
    [34] 姜翠玲,范晓秋.城市生态环境需水量的计算方法[J].河海大学学报(自 然科学版),2004,32(1):14~17
    [35] 乔光建,高守忠,赵永旗.邢台市生态环境需水量分析[J].南水北调与水利科技,2002,23(6):27~32
    [36] 杨志峰,崔宝山等.生态环境需水量理论、方法和实践[M].北京:科学出版社,2003年3月
    [37] 黄永基,陈晓军.我国水资源需求管理现状及发展趋势分析[J].水科学进展,2000,(6):215~220
    [38] 张雅君,刘全胜.需水量预测方法的评析与择优[J].水科学进展,2001,(7):27~29
    [39] 柯礼丹.人均综合用水量预测需水量[J].地下水,2004(26):1~5
    [40] 潘红宇.时间序列分析[M].北京:对外经济贸易大学出版社,2006年1月
    [41] 华伯泉.经济预测的统计方法[M].北京:统计出版社,1988年
    [42] 何书元.应用时间序列分析[M].北京:北京大学出版社,2003年9月
    [43] 邓聚龙.灰色预测与决策[M].武汉:华中理工大学出版社,1992.
    [44] 张雅君,刘全胜.城市需水量灰色预测的探讨[J].中国给水排水,2002,(18):79~81
    [45] 王忠.城市工业需水量预测方法简介[J].安徽建筑,2003,(3):85~86
    [46] 满广生,徐得潜,陈国炜等.城镇工业用水量预测方法研究[J].合肥工业大学学报,2002,(4):204~207
    [47] 倪晋仁,崔树彬,李天宏等.论河流生态环境需水[J].水利学报,2002,(9):14~19,26
    [48] 章家恩,徐琪.城市土壤的形成特征及其保护[J].土壤,1997,(4):189~193
    [49] 吕明强,都金康.城市水文与水资源导论[M].北京:中国科学技术出版社,1993年
    [50] 王伟编著.人工神经网络原理:入门与应用[M].北京:北京航空航天大学出版社,1995年11月
    [51] 党建武编著.神经网络技术及应用[M].北京:中国铁道出版社,2000年7月
    [52] 高隽.人工神经网络原理与仿真实例[M].北京:机械工业出版社,2003年8月
    [53] 合肥市人民政府.合肥市近期建设规划(2006-2010)
    [54] 合肥市人民政府.合肥市城市总体规划(2006-2020)
    [55] 安徽省水利厅,安徽省环境保护局编.安徽省水功能区划[M].北京:中国水利水电出版社,2004年3月
    [56] 中国水利年鉴编辑委员会编.中国水利年鉴(2004)[M].北京:中国水利 水电出版社,2005年
    [57] 周开利,康耀红.神经网络模型及其MATLAB仿真程序设计[M].北京:清华大学出版社,2005年7月
    [58] 合肥市统计局.合肥市统计年鉴(1995-2005)

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700