Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10): a World Weather Research Programme Project

A World Weather Research Programme (WWRP) project entitled the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) was developed to be associated with the Vancouver 2010 Olympic and Paralympic Winter Games conducted between 12 February and 21 March 2010. The SNOW-V10 international team augmented the instrumentation associated with the Winter Games and several new numerical weather forecasting and nowcasting models were added. Both the additional observational and model data were available to the forecasters in real time. This was an excellent opportunity to demonstrate existing capability in nowcasting and to develop better techniques for short term (0–6 h) nowcasts of winter weather in complex terrain. Better techniques to forecast visibility, low cloud, wind gusts, precipitation rate and type were evaluated. The weather during the games was exceptionally variable with many periods of low visibility, low ceilings and precipitation in the form of both snow and rain. The data collected should improve our understanding of many physical phenomena such as the diabatic effects due to melting snow, wind flow around and over terrain, diurnal flow reversal in valleys associated with daytime heating, and precipitation reductions and increases due to local terrain. Many studies related to these phenomena are described in the Special Issue on SNOW-V10 for which this paper was written. Numerical weather prediction and nowcast models have been evaluated against the unique observational data set now available. It is anticipated that the data set and the knowledge learned as a result of SNOW-V10 will become a resource for other World Meteorological Organization member states who are interested in improving forecasts of winter weather.     

Adaptive Blending of Model and Observations for Automated Short-Range Forecasting: Examples from the Vancouver 2010 Olympic and Paralympic Winter Games

An automated short-range forecasting system, adaptive blending of observations and model (ABOM), was tested in real time during the 2010 Vancouver Olympic and Paralympic Winter Games in British Columbia. Data at 1-min time resolution were available from a newly established, dense network of surface observation stations. Climatological data were not available at these new stations. This, combined with output from new high-resolution numerical models, provided a unique and exciting setting to test nowcasting systems in mountainous terrain during winter weather conditions. The ABOM method blends extrapolations in time of recent local observations with numerical weather predictions (NWP) model predictions to generate short-range point forecasts of surface variables out to 6 h. The relative weights of the model forecast and the observation extrapolation are based on performance over recent history. The average performance of ABOM nowcasts during February and March 2010 was evaluated using standard scores and thresholds important for Olympic events. Significant improvements over the model forecasts alone were obtained for continuous variables such as temperature, relative humidity and wind speed. The small improvements to forecasts of variables such as visibility and ceiling, subject to discontinuous changes, are attributed to the persistence component of ABOM.     

2009—2017年太湖湖泛发生特征及其影响因素

湖泛是太湖蓝藻水华较为独特的灾害表征形式,也是危害湖泊生态服务功能的主要因素,认知其发生机制、演变特征对湖泊蓝藻水华灾害防控具有重要作用.本文基于2009-2017年江苏省水文部门逐年4-10月对太湖湖泛易发区现场巡查获得的湖泛发生状况数据,结合期间水质、入湖水量、营养盐负荷等环境条件变化监测,分析了太湖水域湖泛发生的时空变化特征,研究了湖泛发生前后的环境因子变化规律,探讨了湖泛强度年际波动成因.结果表明,2009-2017年太湖共发现面积超过0.01 km²的湖泛61起,年发生次数3~17次不等;湖泛发生位置主要集中在太湖湖西沿岸带,9年发生了32次,占总频次的一半以上;其次为梅梁湾;贡湖相对较少,而巡查的东部湖区未发现湖泛事件.通过对湖泛发生日与前10日的环境条件对比分析发现,湖泛发生前5天持续的高温、低压和低风速等气象条件有利于湖泛发生：气温连续高于25℃、气压低于101.0 kPa,有利于诱发湖泛;主导风向为东南风也有利于太湖西北部蓝藻水华严重区域的湖泛发生;大量蓝藻水华物质是湖泛发生的重要物质基础：湖泛发生前10日,湖体平均藻密度基本在1500万cells/L以上.湖泛发生强度还受前一年营养盐外源负荷的影响,湖泛发生频次较高的年份,前一年总磷和总氮营养盐入湖负荷也均处于较高水平.研究表明,尽管2007年无锡贡湖水厂发生饮用水危机以来太湖流域已经开展了大量的水环境治理工程,但是截至目前,太湖的湖泛发生风险仍处于较高水平,在营养盐还未控制到较低水平之前,太湖的湖泛巡查与防控仍是十分必要和艰巨的任务.     

太湖小时尺度水面蒸发特征及3种模型模拟效果对比

小时尺度水面蒸发可影响水面大气边界层热力和动力结构,分析湖泊小时尺度水面蒸发主要影响因素,选取准确模拟其特征的蒸发模型,将有助于改善流域天气预报和空气质量预报.基于太湖避风港站2012—2013年通量、辐射和气象观测数据,分析太湖小时尺度水面蒸发主要影响因子和3个模型(传统质量传输模型、Granger and Hedstrom经验模型、DYRESM模型)的模拟效果.结果表明:影响太湖小时尺度水面蒸发的主要因子为水气界面水汽压差和风速的乘积,而非净辐射.传统质量传输模型、Granger and Hedstrom经验模型、DYRESM模型模拟值与全年实测值的一致性系数分别为0.92、0.87和0.89,均方根误差分别为28.35、41.58和38.26 W/m~2.传统质量传输模型对太湖小时尺度水面蒸发的日变化和季节动态模拟效果最佳,其夜间模拟相对误差小于3%,除秋季外,其他季节的模拟绝对误差均小于4 W/m~2.Granger and Hedstrom经验模型系统性地高估太湖潜热通量,在大气较为稳定的午后(高估22~32 W/m~2)和冬季(高估72%)高估最为明显,模拟效果最差.DYRESM模型也系统地高估太湖潜热通量,模拟效果居中.考虑水汽交换系数随风速的变化特征将有助于改善传统质量传输模型和DYRESM模型对太湖小时尺度水面蒸发的模拟精度.     

洪泽湖风生流对风场和水位变化响应特征

深入认识大型湖泊在不同风速、风向和水位下三维风生流结构特征对于湖泊污染控制、生态恢复及资源的开发利用具有重要意义.本文在构建笛卡尔坐标系下洪泽湖三维水动力模型的基础上,利用2次全湖30个点位流场监测数据验证了模型精度.基于1975-2020年长系列风场观测数据,确定了洪泽湖典型风速风向.在此基础上,模拟了16种不同风向,13种不同风速和20种不同水位工况条件下洪泽湖三维风生流结构.结果表明：水动力模型可以较好地刻画洪泽湖三维湖流变化特征.洪泽湖风生流结构随风向变化呈现出较大空间差异.风生流流速随着风速的升高呈加速上升趋势,其中表层水体流速上升幅度远高于其他水层.在2.4 m/s东风驱动下,溧河洼、成子湖和南部湖区垂向平均流速随着水位上升呈先升高后降低的趋势,3个湖区分别在12.7、12.4和12.2 m水位下流速达到最大值.     

A Procedure for Calculating Extreme Characteristics of the Northern Caspian Sea Level

A procedure is proposed for calculating extreme characteristics of the level of a sea with allowance for positive and negative setups. Analysis is made of past storm events in the Northern Caspian Sea that have caused strong setups. Sixty-three storm weather patterns are chosen from a period of 45 years. Time ring synoptic maps are used to digitize the atmospheric pressure fields and calculate the field of its gradient and the wind near water surface. Based on these data, the sea level values and currents are calculated through two- and three-dimensional hydrodynamic models. A probabilistic model along with computer-aided data treatment procedures are used to calculate the fields of extreme characteristics of the sea level at the Lagan gage with the occurrence of once per N years at the average Caspian Sea level of 27 m below SL.     

Distributions-oriented wind forecast verification by a hidden Markov model for multivariate circular–linear data

Winds from the North–West quadrant and lack of precipitation are known to lead to an increase of PM10 concentrations over a residential neighborhood in the city of Taranto (Italy). In 2012 the local government prescribed a reduction of industrial emissions by 10% every time such meteorological conditions are forecasted 72 h in advance. Wind forecasting is addressed using the Weather Research and Forecasting (WRF) atmospheric simulation system by the Regional Environmental Protection Agency. In the context of distributions-oriented forecast verification, we propose a comprehensive model-based inferential approach to investigate the ability of the WRF system to forecast the local wind speed and direction allowing different performances for unknown weather regimes. Ground-observed and WRF-forecasted wind speed and direction at a relevant location are jointly modeled as a 4-dimensional time series with an unknown finite number of states characterized by homogeneous distributional behavior. The proposed model relies on a mixture of joint projected and skew normal distributions with time-dependent states, where the temporal evolution of the state membership follows a first order Markov process. Parameter estimates, including the number of states, are obtained by a Bayesian MCMC-based method. Results provide useful insights on the performance of WRF forecasts in relation to different combinations of wind speed and direction.     

Nowcasting with INCA During SNOW-V10

A Central-European nowcasting system which has been developed for use in mountainous terrain is tested in the Whistler/Vancouver area as part of the SNOW-V10 experiment. The integrated nowcasting through comprehensive analysis system provides hourly updated gridded forecasts of temperature, humidity, and wind, as well as precipitation forecasts which are updated every 15 min. It is based on numerical weather prediction (NWP) output and real-time surface weather station and radar data. Verification of temperature, relative humidity, and wind against surface stations shows that forecast errors are significantly reduced in the nowcasting range compared to those of the driving NWP model. The main contribution to the improvement comes from the implicit bias correction due to use of the latest observations. Relative humidity shows the longest lasting effect, with >50 % reduction of mean absolute error up to +4 h. For temperature and wind speed this percentage is reached after +2 and +3 h, respectively. Two cases of precipitation nowcasting are discussed and verified qualitatively.     

水体浊度对风速、风向及其时间累积效应的响应——以太湖贡湖湾为例

水体浊度是影响水下光场及营养盐循环的关键要素之一,其变化过程与水生生态环境演变关系密切.基于2015-2016年7个时段于太湖贡湖湾内外的金墅和上山村两站点的水体浊度及东山气象站的逐时风场数据,利用分位统计等方法,探讨了风速、风向及时间累积效应对水体浊度的影响.结果表明：在以风场驱动为主要动力来源的大型浅水湖泊中,春、秋两季水体浊度的变化频率高于夏、冬两季,且春季变率更为突出;冬季风场和水体浊度的变率均较夏季明显.风场（包括风速、风向及其累积时间）是影响水体浊度变化的关键因素.其中风速是主要决定性因子;风向对水体浊度有较明显的影响,其通过对风速效应的修正进而影响水体浊度,该修正作用可用三角函数表征;水体浊度变化同时还受前期风场累积的影响,其前期时间累积效应的有效时段为2~10 h.该研究给出了风速、风向及风场累积效应的耦合对水体浊度的影响模型,有助于弄清风场对水体浊度变化的影响机制.     

过去40年太湖剧烈的湖泊物理环境变化及其潜在生态环境意义

过去40年,全球气候变暖、辐射变暗和变亮、风速减弱、气候异常波动等自然环境变化以及筑坝建闸、岸堤硬质化和调水引流等强烈人类活动势必会深刻改变太湖湖泊物理环境和过程,驱动湖泊生态系统演化.基于历史文献、档案数据以及气象水文和透明度等长期观测数据,本文系统梳理了太湖气温、水温、风速、水位和透明度等物理环境空间分布和长期变化特征,探讨了气温和风速、水位和透明度相互协同作用机制及其潜在生态环境意义.受全球变化和城市化等影响,过去40年太湖气温和水温呈现显著升高趋势,而近地面风速则表现为持续下降,湖泊增温和风速下降有利于藻类生长和蓝藻水华漂浮聚集,某种程度上增加了蓝藻水华出现频次和集聚的面积.为防洪和满足流域日益增长的水资源需求,闸坝管控和调水引流使太湖水位呈现缓慢增加趋势,而入湖污染物增加和富营养化则造成水体透明度逐渐下降,致使透明度与水位(水深)的比值明显降低,减少了湖底可利用光强,恶化水下光环境,在一定程度上驱动了太湖水生植被和草型生态系统退化.湖泊物理环境长期变化逐渐拓展了太湖藻型生境空间而压缩了草型生境空间,加剧了草型生态系统向藻型生态系统转化和增强了藻型生态系统的自我长期维持.太湖湖泊物理环境的显著变化也会部分抵消流域营养盐削减和湖体营养盐下降对藻类生物量和蓝藻水华的控制,增加了太湖蓝藻水华防控和湖泊富营养化治理的难度.这意味着未来流域控源截污需要更加严格的标准,而湖泊水位等物理环境的有效管控是应对藻华加剧和恢复草型生态系统的适应性管理策略.     

太湖波浪数值模拟

在太湖实际波浪观测的基础上,采用率定验证后的第三代动谱平衡方程,考虑实际水底地形、波浪折射、浅化、反射、破碎、湖流等条件下,对太湖波浪进行数值模拟,研究太湖波浪的主要影响因素.结果表明:SWAN模型可以较好地模拟风作用下太湖风浪的生成和传播过程,模型在太湖应用是合适的;波高、波长、波周期等波浪参数在太湖的分布与风速、风向、水深等因素密切相关;在相同风向、不同风速情况下,太湖波浪发展至稳定状态的时间不一样;在不同风向,相同风速持续作用下,有效波高达到稳定的时间差不多,变化趋势也比较相同.说明波浪的发展不光取决于风速的大小,还同风的持续吹的时间和风区长度有关.     

A simulation model of blowout development

Blowouts are the main feature of wind erosion in the dunes along the Dutch coast. A number of characteristics, such as their growth against the prevailing wind and the spontaneous stabilization when certain dimensions are reached, are believed to be caused by a prominent quality of the southwest wind, viz. its gustiness. This hypothesis is tested in a two-dimensional computer model which simulates the effect of wind gusts on a sandy surface along the main axis of the blowout. A number of constraints based on field observations are built into the model. The results closely resemble the longitudinal section of the blowout.     

滇池蓝藻水华发生频率与气象因子的关系

蓝藻水华暴发是在一定的营养、气候、水文条件和生态环境下形成的藻类过度繁殖和聚集的现象,是水体环境因子(如总氮、总磷、pH值、溶解氧)和气象因子综合作用的结果.然而滇池周年性水华暴发标志着滇池蓝藻水华在当前水质条件下,气象因子为关键影响因子.为了进一步探究滇池蓝藻水华发生与气象因子的规律,本文利用2010-2011年滇池蓝藻水华遥感监测资料与周边地面气象站逐月资料,研究滇池蓝藻水华月发生频率与月气象因子的关系.结果显示,滇池蓝藻水华发生频率与平均气温、最低气温、平均风速、累计日照时数和降雨量等气象因子均表现为显著相关,其中与日照时数和风速呈显著负相关.各因子中与风速的相关系数最高,说明滇池各月蓝藻水华发生频率高低与风速关系最为密切,进一步验证了在具备蓝藻水华发生所需营养盐条件下,水体稳定性对蓝藻水华发生的影响更为重要的结论.以上结果可为科学预测蓝藻水华发生,并采取相应措施减少其带来的影响提供理论依据.     

A New Integrated Weighted Model in SNOW-V10: Verification of Categorical Variables

This paper presents the verification results for nowcasts of seven categorical variables from an integrated weighted model (INTW) and the underlying numerical weather prediction (NWP) models. Nowcasting, or short range forecasting (0–6 h), over complex terrain with sufficient accuracy is highly desirable but a very challenging task. A weighting, evaluation, bias correction and integration system (WEBIS) for generating nowcasts by integrating NWP forecasts and high frequency observations was used during the Vancouver 2010 Olympic and Paralympic Winter Games as part of the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) project. Forecast data from Canadian high-resolution deterministic NWP system with three nested grids (at 15-, 2.5- and 1-km horizontal grid-spacing) were selected as background gridded data for generating the integrated nowcasts. Seven forecast variables of temperature, relative humidity, wind speed, wind gust, visibility, ceiling and precipitation rate are treated as categorical variables for verifying the integrated weighted forecasts. By analyzing the verification of forecasts from INTW and the NWP models among 15 sites, the integrated weighted model was found to produce more accurate forecasts for the 7 selected forecast variables, regardless of location. This is based on the multi-categorical Heidke skill scores for the test period 12 February to 21 March 2010.     

风场对鄱阳湖丰水期表层蓝藻密度的影响

目前,在风场对蓝藻的影响研究方面,国内针对太湖、滇池、巢湖等浅水湖泊的研究较多,针对鄱阳湖的研究则多集中于蓝藻群落特征及其与营养盐之间的关系。近年来,作为长江流域重要的通江湖泊,处于轻度富营养化状态的鄱阳湖水体蓝藻水华在局部库湾和部分水域出现,风场如何影响鄱阳湖表层蓝藻密度是一个值得探讨的问题。2019-2021年,在鄱阳湖布设13~49个采样点,于平水期、丰水期和枯水期现场采集各个点位表层水样、藻类、风场和流场数据,分析风场对鄱阳湖丰水期表层蓝藻密度的影响。结果表明,2019-2021年鄱阳湖丰水期风速与表层蓝藻密度呈显著正相关性,风场对水体的充分混合及驱动水体形成的风生流是促进蓝藻生长的原因之一。在流速较高(>0.05 m/s)的区域,无论风速高于还是低于临界风速(3~4 m/s),鄱阳湖表层蓝藻密度的空间分布受流场的影响更大;在流速较低(<0.05 m/s)的区域,风速在临界风速以下时,鄱阳湖表层蓝藻密度的空间分布受风场影响更大。2019-2021年鄱阳湖丰水期蓝藻密度超过水华暴发的阈值,但在高风速高流速的共同作用下未能发生大范围的蓝藻水华,仅能在风速适宜(<3~4 m/s)、流速较低(<0.05 m/s)的内湾、尾闾区等区域发生小面积的蓝藻水华。鄱阳湖丰水期水体处于长江顶托的低流速且微风条件下时,发生大面积蓝藻水华的概率可能会明显上升。     

Evaluation of dam overtopping probability induced by flood and wind

This study develops a probability-based methodology to evaluate dam overtopping probability that accounts for the uncertainties arising from wind speed and peak flood. A wind speed frequency model and flood frequency analysis, including various distribution types and uncertainties in their parameters, are presented. Furthermore, dam overtopping probabilities based on monthly maximum (MMax) series models are compared with those of the annual maximum (AMax) series models. An efficient sampling scheme, which is a combination of importance sampling (IS) and Latin Hypercube sampling (LHS) methods, is proposed to generate samples of peak flow rate and wind speed especially for rare events. Reservoir routing, which incorporates operation rules, wind setup, and run-up, is used to evaluate dam overtopping probability.     

“引江济淮”工程对安徽菜子湖水龄分布的影响

菜子湖是"引江济淮"工程的重要输水通道,其水体输运和物质交换将因输水工程发生改变.本文基于环境流体水动力学模型（EFDC）建立了菜子湖水龄模型,在将模型与实测水文数据验证满足精度的前提下,设计14种方案计算菜子湖在季风影响下的水龄,工程实施期间菜子湖在丰、平、枯季的水龄与流场,以及枯水季调水情景下同风速8种风向和强风向3种风速时的水龄.数值试验的模拟结果表明：菜子湖湖体水龄分布具有时空差异性,无风条件下,春、夏、秋、冬季的湖体的平均水龄分别为120.93、33.19、92.92、101.48 d,而在季风影响下,春、夏、秋、冬季平均水龄分别为75.23、32.45、81.80、66.16 d;西部L2湖水龄较长,东部L1湖和南部L3湖水龄较短;输水工程将改变L1和L3湖的流场,对L2湖流场几乎无影响;输水工程实施后,菜子湖水龄分布主要受风场及输水影响,不同风向对菜子湖各湖区影响不同,西南风有助于L1湖水体交换,北风有助于L2湖水体交换,东风有助于L3湖水体交换,而当风向为东北风时,3个湖区水龄均较小;枯水季调水有利于L1湖和L3湖水体交换,但对L2湖水体交换作用不明显.     

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, Kain-Fritsch and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, root-mean-squares error (RMSE), and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation. Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the CPSs for different synoptic situations.     

基于高频高光谱近感观测量化风对蓝藻水华的影响

全球气候变化显著影响湖泊理化环境和生态系统演化,对生态系统服务造成负面影响甚至引发生态系统灾变,其中风速下降可能促使富营养化湖泊蓝藻水华的暴发和水面漂浮集聚。以往由于较低的观测频次,往往很难精细量化风对蓝藻水华的影响。利用陆基高光谱近感观测技术,基于分钟小时尺度开展周年高频观测,通过对6—10月蓝藻生长期太湖表层水体叶绿素a浓度统计分析,量化蓝藻水华高频动态变化特征,确定蓝藻水华漂浮集聚的风速阈值。研究发现,随着风速的下降,水体表层叶绿素a浓度随之增加,蓝藻水华出现概率也随之增加。概率分析显示,当近地面风速小于2.5 m/s时,湖泊表层比较容易形成明显肉眼可见的蓝藻水华,藻华发生概率为55.1%。长时间持续的低风速容易诱发蓝藻水华形成和漂浮集聚,强风浪事件后低风速出现1～2天叶绿素a往往就能恢复以往较高水平,这为管理者有效防控蓝藻水华提供了新视角。长期气象观测显示,气候变化影响下太湖地区风速呈现显著下降趋势,增加了蓝藻竞争优势和发生概率,有助于其在表面漂浮集聚。在未来的气候变化情景下,如果风速继续呈现下降趋势,在营养盐条件不变情况下湖泊表层蓝藻水华发生概率可能还会上升,增加蓝藻水华防控...     

“引江济星”工程及风场环境影响广东肇庆星湖水龄分布特征

目前大量景观类湖泊在人工布局下呈现形状不规整的特点,容易造成湖湾水体滞留形成死水区,水质恶化问题日益突出,本文以星湖为研究区域,建立基于环境流体生态动力学(EFDC)模型的星湖水动力—风场耦合模型,以水龄作为衡量水体交换速率的指标,设计12种工况模拟计算不同出入湖通道布局及流量配比、"引江济星"工程和风场对星湖水龄时空分布的影响.结果表明:星湖水龄存在季节性和空间性分布差异,春季主导风向与湖体流动主方向互斥,抑制了波海湖水体交换,导致水龄在春季较长,而秋季南西南季风促进中心湖等水体交换,致使水龄偏短,也反映出风向的影响存在湖区空间异质性,风向为南东南时星湖整体水龄最小;入湖口通道布局及流量配比对湖区水体交换速率存在影响,以外坑为波海湖入湖口且波海湖、中心湖、仙女湖入流比为4∶3∶3时,星湖整体水龄最小,拟建的青莲湖出水口和仙女湖出水口能有效加快青莲湖东北部和仙女湖东南部的水体交换速率;综合考虑调水引流效益、经济投资、生态开发和占地的成本,方案二为最优调水引流方案.本研究强调入湖口布局、流量大小和比例、及风场等因素对城市内湖水体置换的影响,为人为干扰下的景观湖泊的治理和管控提供科学支撑.