主成分回归模型在农业需水量预测中的应用

农业需水量的准确预测对区域发展具有十分重要的意义。农业需水量受多重因素的影响,且这些因素大多存在较强的相关性。通过介绍主成分分析法的原理和计算分析,以实例（z市1998--2010年农业用水资料）建立回归模型对需水量进行预测。结果表明,该模型应用于农业用水量预测,其结果与当地实际情况较吻合,模型的拟合程度和预测准确度均较好。     

基于集对分析原理的城市需水量预测模型及其应用

城市需水量预测对合理分配水资源起着重要作用,但城市需水量本身的影响因素众多,其预测是典型的不确定性问题。集对分析是处理不确定问题的新方法,它通过联系度展示了研究对象间关系的详细结构,对处理不确定性问题十分有效。采用集对分析相似预测法,结合集对分析同异反模式中的"择近原则"和相似分析法中相似的历史原因产生相似结果的原则,在预测过程中将需水量时间序列作为需水量的影响因子,利用一定时长的历史数据来建立基于集对分析原理的相似预测法模型。通过对克拉玛依市三坪地区需水量的预测发现,集对分析相似预测法不但计算简单,而且精度优于传统的ARIMA模型。     

基于遥感技术的艾比湖储水量和需水量研究

艾比湖湖水很浅,湖底平坦,沉积着巨厚的细沙和淤泥。依据自身特征及其他因素,针对艾比湖水量的收支情况,建立艾比湖的储水量和需水量的数学模型。其中艾比湖湖面面积数据是重要参数之一,利用遥感技术,采用资源卫星影像,结合Modis数据,解译提取获得。通过艾比湖储水量和需水量数据可以进一步预测艾比湖湖面面积的变化趋势,对本地区的生态及农业生产具有指征意义,为决策层制定防治对策提供科学依据。     

大通河流域调水后生态环境影响的初步评价

文章在阐明大通河流域近中期水平年 (2 0 30年 )与远景年 (2 0 5 0年 )需水量 (或耗水量 )预测以及规划外调水量的基础上 ,经过调查研究 ,针对大通河流域调水后对生态环境的影响进行了初步分析与评价     

秦皇岛市工业企业需水量零增长预期分析

本文在对“九五”期间秦皇岛市工业用水情况认真分析的基础上,按照秦皇岛市“十五”计划和2010年远景目标对秦皇岛市2005年和2010年未来工业企业需水量进行了预测;同时对2020年和2030年进行了展望,综合分析预测的结果,提出了节水措施的建议,并对工业需水量的零增长进行了预期分析。     

基于生态环境需水量的城市等级研究

近年来生态环境需水量成为区域(或流域)水资源及相关领域的研究热点.依据城市生态环境需水量的影响因素提出了城市等级划分的原则、指标体系和评判方法,其中指标体系由1个目标层、5个准则层和16个单项指标构成,并选择水资源优越的安徽省六安市为研究区.根据2008年统计资料,运用模糊综合评价方法对该城市等级进行了判定,结果为:六安城区所属城市级别为Ⅲ级,即中等城市,符合实际情况,说明该指标体系及其方法科学可行.同时,对影响城市等级的瓶颈因素进行了讨论.     

秦皇岛市居民生活和公用事业用水量预测

本文在对“九五”期间秦皇岛市城市生活、公用事业水情况认真分析的基础上,按秦皇岛市“十五”计划和2010年远景目标对秦皇岛市2005年和2010年未来城市生活需水量和城市公用事业用水量进行了预测;同时对2020年和2030年进行了展望;综合分析预测的结果,提出了节水的建议,并对需水量的零增长期进行了预期分析。本文的研究结果对秦皇岛市水资源可持续利用及国民经济和社会发展规划的制订有积极的意义。     

AERMOD模型在大气环境影响评价中的应用

通过实例,对AERMOD在大气环境影响评价中的应用进行讨论。根据2007年1月～12月达州市地面和高空气象数据、项目所在地的地形资料,应用AERMOD预测模型建立了空气扩散模型,对工程的大气环境影响进行了预测与评价。结果表明:AERMOD空气扩散模型实现了评价区域二维地形向三维地形的可视化转变,预测浓度分布能够反映出污染源分布和气象场变化以及地形等对大气污染物迁移和扩散的影响。     

土地市场景气指标体系及评价模型的建立

以徐州市为例建立了土地市场景气指标体系及评价模型。首先在建立指标体系时运用定性的方法对大量指标进行了初选,然后用主成分分析法确定土地市场景气指标体系,并运用层次分析法确定各指标的权重。在建立景气评价模型时,分析了传统扩散指数模型的缺陷,提出了合理的改进模型。同时,针对扩散指数与合成指数反映的土地市场运行状况之间的差异,引入了精度比较概念,在此基础上选择精度较高的指数进行土地市场景气状况评价。最后运用建立的评价模型对徐州市2001-2006年土地市场景气状况进行了评价,并对2007年徐州市土地市场运行状况进行了预测。分析表明,建立的景气指标体系及其评价模型能够较准确地评价和预测土地市场景气状况．     

灰色理论及改良方法对我国垃圾产量的预测

为了给城市环境规划提供理论依据,需要对城市生活垃圾产量进行预测,以期揭示其变化规律和发展趋势。本文对三种预测模型进行对比分析研究,并通过灰色关联度分析,选取与垃圾产量最为相关的5个因素,建立了包括多个因素指标的GM(1,1)预测方程的多元线性回归综合模型。该模型考虑了城市生活垃圾产量的主要影响因素,得到的拟合数据比较理想,预测模型和结果也更为合理可信。     

Quantifying the influence of environmental and water conservation attitudes on household end use water consumption

Within the research field of urban water demand management, understanding the link between environmental and water conservation attitudes and observed end use water consumption has been limited. Through a mixed method research design incorporating field-based smart metering technology and questionnaire surveys, this paper reveals the relationship between environmental and water conservation attitudes and a domestic water end use break down for 132 detached households located in Gold Coast city, Australia. Using confirmatory factor analysis, attitudinal factors were developed and refined; households were then categorised based on these factors through cluster analysis technique. Results indicated that residents with very positive environmental and water conservation attitudes consumed significantly less water in total and across the behaviourally influenced end uses of shower, clothes washer, irrigation and tap, than those with moderately positive attitudinal concern. The paper concluded with implications for urban water demand management planning, policy and practice.     

A Multi‐Scale Analysis of Low‐Rise Apartment Water Demand through Integration of Water Consumption,Land Use,and Demographic Data

Over the past decades, multi‐unit housing developments have been vastly expanded across urban areas due to the population growth. To properly supply water to this growing sector, it is essential to understand the determinants of its water use. However, this task has largely remained unexplored through the empirical study of water demand mainly due to the scarcity of data in this sector. This study integrated apartment water consumption, property characteristics, weather, water pricing, and census microdata to overcome this issue. Using a rich source of GIS‐based urban databases in Auckland, New Zealand, the study developed a large dataset containing the information of 18,000 low‐rise apartments to evaluate the determinants of water use both in the household scale and aggregated scale. The household‐scale demand analysis helped to assess the heterogeneity in responses to the demand drivers specifically water price across different consumer groups, whereas the aggregated analysis revealed the determinants behind the spatial variation in water demand at the census area unit level. Through applying panel data models, the study revealed the household size as the most important determinant of apartment water use in Auckland, where other socioeconomic factors, building features, and water pricing were not significant determinants. This knowledge of determinants of water demand can help water planners to better manage water demand in the compact urban environments.     

OPTIMIZATION IN MUNICIPAL WATER SUPPLY SYSTEM DESIGN1

ABSTRACT. The design of a municipal water supply system may involve utilizing singly or in combination a conventional water supply, a desalted water supply, and a supply from a recharged aquifer reservoir. Optimization of the design requires a model formulated in a way that modern methods of systems analysis can be used. This study concerns the formulation, solution, and evaluation of a mathematical model of a municipal water supply system that includes a supply from a variable quality output desalting plant. The combined system is operated in conjunction with an artificially recharged aquifer reservoir. Also considered are short periods of water shortages. The model is set up in an approximate linear programming format, and the optimum solution (minimum cost) is found. The model is tested by applying it to the design of a supply system to meet the 1985 estimated water demand of the city of Lincoln, Nebraska. Results of this test indicate that the artificial reservoir and the existing conventional supply system are capable of supplying that demand during all but the peak period. An electrodialysis desalting system is used in this analysis. It is competitive only when the length of transmission pipeline for a conventional supply system approaches 90 miles. The model is formulated in a general way so that it can be applied to almost all situations encountered in municipal water supply design, as well as to the specific system designated for this study.     

Factors affecting the variability of household water use in Melbourne,Australia

This study investigates the variability of household water use in Melbourne with the aim of improving the current understanding of factors affecting residential water use. This understanding is critical to predicting household water demand, particularly at an appropriate spatial and temporal resolution to support Integrated Urban Water Management based planning and to improve the understanding on how different household water demands respond to demand management strategies. The study used two sets of data each collected from 837 households under significantly different water use conditions in the years 2003 and 2011. Data from each household consist of the household characteristics and quarterly metre readings. Ordinary Least Square regression analysis followed by detailed analysis of each factor was used to identify key factors affecting household water use. The variables studied are household size, typology of dwelling, appliance efficiency, presence of children under 12 years, presence of children aged between 12 and 18 years, tenancy, dwelling age, presence of swimming pool, evaporative cooler, and dishwasher. All of them except presence of children aged between 12 and 18 years, tenancy and dwelling age were identified as variables that contribute to the variability of household water use in Melbourne. The study also found that the explanatory capacity of these variables increases with decreasing water use. This paper also discusses the significance of the explanatory variables, their impact and how they vary over the seasons and years. The variables found in this study can be used to inform improved prediction and modelling of residential water demand. The paper also explores other possible drivers to explain residential water use in light of the moderate explanatory capacity of the variables selected for this study thus, provides useful insights into future research into water demand modelling.     

System dynamics modeling for municipal water demand estimation in an urban region under uncertain economic impacts

Accurate prediction of municipal water demand is critically important to water utilities in fast-growing urban regions for drinking water system planning, design, and water utility asset management. Achieving the desired prediction accuracy is challenging, however, because the forecasting model must simultaneously consider a variety of factors associated with climate changes, economic development, population growth and migration, and even consumer behavioral patterns. Traditional forecasting models such as multivariate regression and time series analysis, as well as advanced modeling techniques (e.g., expert systems and artificial neural networks), are often applied for either short- or long-term water demand projections, yet few can adequately manage the dynamics of a water supply system because of the limitations in modeling structures. Potential challenges also arise from a lack of long and continuous historical records of water demand and its dependent variables. The objectives of this study were to (1) thoroughly review water demand forecasting models over the past five decades, and (2) propose a new system dynamics model to reflect the intrinsic relationship between water demand and macroeconomic environment using out-of-sample estimation for long-term municipal water demand forecasts in a fast-growing urban region. This system dynamics model is based on a coupled modeling structure that takes into account the interactions among economic and social dimensions, offering a realistic platform for practical use. Practical implementation of this water demand forecasting tool was assessed by using a case study under the most recent alternate fluctuations of economic boom and downturn environments.     

Smart meters for enhanced water supply network modelling and infrastructure planning

To design water distribution network infrastructure, water utilities formulate daily demand profiles and peaking factors. However, traditional methods of developing such profiles and peaking factors, necessary to carry out water distribution network modelling, are often founded on a number of assumptions on how top-down bulk water consumption is attributed to customer connections and outdated demand information that does not reflect present consumption trends; meaning infrastructure is often unnecessarily overdesigned. The recent advent of high resolution smart water meters allows for a new novel methodology for using the continuous ‘big data’ generated by these meter fleets to create evidence-based water demand curves suitable for use in network models. To demonstrate the application of the developed method, high resolution water consumption data from households fitted with smart water meters were collected from the South East Queensland and Hervey Bay regions in Australia. Average day (AD), peak day (PD) and mean day maximum month (MDMM) demand curves, often used in water supply network modelling, were developed from the herein created methodology using both individual end-use level and hourly demand patterns from the smart meters. The resulting modelled water demand patterns for AD, PD and MDMM had morning and evening peaks occurring earlier and lower main peaks (AD: 12%; PD: 20%; MDMM: 33%) than the currently used demand profiles of the regions’ water utility. The paper concludes with a discussion on the implications of widespread smart water metering systems for enhanced water distribution infrastructure planning and management as well as the benefits to customers.     

塔里木盆地南缘和田地区生活用水地下水质分析

干旱区水资源短缺，生产用水、生态用水与人民群众的生活用水矛盾突出。针对和田地区农村改水的地下饮用水状况的分析和评价，结果表明，地下饮用水的色度、浑浊度以及砷、泵、镉、铬、铅、硝酸盐等超标率均为零。总硬度、Cl^-、SO4^2-及F^-等指标的超标率较高，而这些物质的存在对于水质的理化性状影响较大，并因此而引发人体健康教育改变。和田地区总体饮用I级水的人口数量多，但局部的超标水依然存在。应通过对区域自然地理状况和人文因素的系统研究和科学论证，加强水源保护，改进卫生条件和卫生观念，建立农村饮水监测网，加强系统监测、监督和管理，以保障人民群众安全的生活用水。     

人工神经网络法预测城市用水量

城市用水量的预测结果,对于城市规划、供水系统的管理及改扩建有着重要的意义,寻求科学合理的预测模型是保障预测结果准确可靠的关键。针对这一问题,利用人工神经网络理论建立了BP（Back—Propagation,反向传播算法）网络预测模型,该模型考虑了反映社会、经济的两个影响因素人口和工业产值对用水量需求的影响,具备系统决策功能。通过实例证明该模型是一种行之有效的用水量预测模型。     

Rainwater reuse supply and demand response in urban elementary school of different districts in Taipei

This study primarily assesses rainwater supply and demand for Taipei City elementary school to develop a method to derive the rainwater reuse system. This work will help planners build water reuse systems for the sites, and facilitate the water demand of school. This study also analyzes rainfall records from fifteen weather stations in Taipei City to evaluate the rainfall changes in the region's morphology, and measures the rainfall supply in the sub-district of Taipei. The effect of water demand factors is also analyzed with linear regressions applied to estimate the change in monthly water demand for Taipei elementary schools. This work assumes that 35% of total water demand can replaced with rainwater. This work creates an active model for comparisons of each Taipei elementary site rainwater supply trend, demand drift, and maximum rainwater use percentage based on the rainwater reuse system. The efficacy of implementing rainwater reuse in Taipei is identified.