Examination of Various Feature Selection Approaches for Daily Precipitation Downscaling in Different Climates

To turn General Circulation Models (GCMs) projection toward better assessment, it is crucial to employ a downscaling process to get more reliability of their outputs. The data-driven based downscaling techniques recently have been used widely, and predictor selection is usually considered as the main challenge in these methods. Hence, this study aims to examine the most common approaches of feature selection in the downscaling of daily rainfall in two different climates in Iran. So, the measured daily rainfall and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) predictors were collected, and Support Vector Machine (SVM) was considered as downscaling methods. Also, a complete set of comparative tests considering all dimensions was employed to identify the best subset of predictors. Results indicated that the skill of various selection methods in different tests is significantly different. Despite a few partial superiorities viewed between selection models, they not presented an obvious distinction. However, regarding all related factors, it may be deduced that the Stepwise Regression Analysis (SRA) and Bayesian Model Averaging (BMA) are better than others. Also, the finding of this study showed that there are some weaknesses in the interpretation of SRA, so concerning this issue, it may be concluded that BMA has more reliable performance. Furthermore, results indicated that generally, the downscaling procedure has more accuracy in arid climate than cold-semi arid climate.

     

Optimal Design of LIDs in Urban Stormwater Systems Using a Harmony-Search Decision Support System

During the last years, climate changes and urbanization are causing huge urban pluvial flood events in many countries in the world, driving to both develop and apply effective and innovative approaches for the design and management of urban stormwater systems. The gradual urbanization is provoking the increase of impervious surfaces and, consequently, of surface runoff and velocity and the reduction of concentration times of watersheds, both increasing soil erosion and worsening the water quality as a consequence of the intensive contamination. In this field, Low Impact Development (LID) practices for urban runoff control can be intended as an effective approach to both improve the urban resilience against the flooding risk and assure environmental interventions to adequate the urban stormwater systems to both climate and land use changes. In this paper, a Decision Support System (DSS) for the optimal design of LIDs in urban watershed is presented and discussed. The procedure is tested on Fuorigrotta (IT) and Ponticelli (IT) urban watersheds, with the aim of assessing the effectiveness of LIDs application in reducing both the flooded and conveyed volumes, at the expense of cost-effective solutions.     

基于GI措施的城市雨水管理模型评析

鉴于模型应用的广泛性以及软件升级的可能性,评析了国内外近些年较为流行的8个基于绿色基础设施(GI)的城市雨水管理模型。分别从GI雨水水质和径流量控制、GI经济效益分析、GI雨水管理及经济分析集成模型3方面对模型进行分类;从GI实践的典型性、空间尺度、模型的算法、数据的输入和输出、用户界面和工具应用几个方面对模型进行详细阐释;从模型支持的GI类型、模拟方法、输入参数、模拟精度、应用范围几个方面比较了模型的不同属性;总结了几个典型模型在中国的应用情况,指出亟待解决的问题。针对目前模型的优缺点,提出未来雨水管理模型研发的方向和趋势。通过本研究,帮助城市雨水管理者和研究人员了解不同的基于GI措施的雨水管理模型的特征及用途,有助于他们在实践中根据自身需求恰当选用模型。     

基于SWMM的不同降水量对城市降雨径流TSS的影响分析

受物理、化学、生物等多重因素的影响,城市降雨径流水质的模拟研究比较模糊。以TSS(总悬浮固体量)为例,利用SWMM的污染物模块及其土地利用模块、污染物累积模块和污染物冲刷模块进行城市雨水径流水质模拟;考虑了不同土地利用情况对污染物的累积及冲刷的影响,针对不同的降水量,利用EMC法(平均浓度法)以及指数方程法进行污染物的冲刷模拟,指数方程法的模拟精度大于EMC法的模拟精度,与监测值更接近。指数方程法的模拟结果表明:当降水量小于2.5mm时,其TSS冲刷量增长幅度较缓;而当降水量大于3.5mm时,其TSS冲刷量呈显著线性增加关系,从而表明,降水量较大的降水事件对于TSS的冲刷量影响更为显著。     

Assessment of Extreme Precipitation in Future through Time-Invariant and Time-Varying Downscaling Approaches

Skill of a time-varying downscaling approach, namely Time-Varying Downscaling Model (TVDM), against time-invariant Statistical Downscaling Model (SDSM) approach for the assessment of precipitation extremes in the future is explored. The downscaled precipitation is also compared with a Regional Climate Model (RCM) product obtained from Coordinated Regional Climate Downscaling Experiment (CORDEX). The potential of downscaling the extreme events is assessed considering Bhadra basin in India as the study area through different models (SDSM, TVDM and RCM) during historical period (calibration: 1951–2005, testing: 2006–2012). Next, the changes in precipitation extremes during future period (2006–2035) have been assessed with respect to the observed baseline period (1971–2000), for different Representative Concentration Pathway (RCP) scenarios. All the models indicate an increasing trend in the precipitation, for the monsoon months and maximum increase is noticed using RCP8.5. The annual precipitation during the future period (RCP8.5) is likely to increase by 7.6% (TVDM) and 4.2% (SDSM) in the study basin. An increase in magnitude and number of extreme events during the future period is also noticed. Such events are expected to be doubled in number in the first quarter of the year (January–March). Moreover, the time-invariant relationship (in SDSM) between causal-target variables is needed to be switched with time-varying (TVDM). This study proves that the time-varying property in TVDM is more beneficial since its performance is better than SDSM and RCM outputs in identifying the extreme events during model calibration and testing periods. Thus, the TVDM is a better tool for assessing the extreme events.

     

邯郸市城区雨洪及其资源化利用分析

结合华北山前平原城区雨洪预报、资源利用关键技术研究课题和邯郸市雨洪资源状况,分析了城市雨洪资源化利用必要性,介绍了雨洪资源利用的进展,分析城区不同下垫面雨洪水质变化规律,提出了城市雨洪利用的主要措施。     

Flooding Control and Hydro-Energy Assessment for Urban Stormwater Drainage Systems under Climate Change: Framework Development and Case Study

Flooding issue and energy shortage have become the common concerns impeding the urban development under climate change scenarios. Exploiting potential hydro-energy from urban stormwater drainage system (USDS) has multiple beneficial perspectives for controlling flooding, relieving energy shortage and mitigating the greenhouse gases emission, which has not yet been systematically investigated in previous works. In this paper, a systematical analysis framework is developed to design the flooding risk control measures and to assess the feasibility and capacity of the hydro-energy development in USDS. The GCMs and HBV models, integrated within the SWMM computation platform, are adopted to simulate the hydrological and hydraulic processes during rainfall events, with the results used to manage the flooding situation and evaluate the energy generation capacity under the influences of both historical and future climate changes. The framework is then applied to a practical case in Tung Chung town of Hong Kong. The analysis result shows that, in the studied area, it is significant and worthwhile to develop the hydro-energy in USDS, which is evidenced to be beneficial to the energy generation and the flooding risk control as well as water resources management in the urban drainage system. The developed method and obtained results of this study may provide a new perspective and technical guide for effective USDS management and operation.

     

Modeling and Management of Urban Stormwater Runoff Quality: A Review

Nonpoint source (NPS) pollution from urban runoff has been established as a major cause of receiving water degradation. In an effort to control this problem, new regulations have been passed in the U.S.A. and federal, state, and local agencies are devising urban runoff management programs. This paper reviews recent regulations and studies related to urban stormwater runoff control and planning in the U.S.A.; discusses fundamentals of urban NPS pollution including transport processes and types and sources of pollutants; reviews current hydrologic and water quality mathematical models used in the U.S.A.; presents case studies in both modeling and management; and describes fundamentals of Best Management Practices (BMPs) in urban runoff control. Finally, it summarizes future research needs.     

Comparison of Two Different Adaptive Neuro-Fuzzy Inference Systems in Modelling Daily Reference Evapotranspiration

This study compares two different adaptive neuro-fuzzy inference systems, adaptive neuro-fuzzy inference system (ANFIS) with grid partition (GP) method and ANFIS with subtractive clustering (SC) method, in modeling daily reference evapotranspiration (ET ₀ ). Daily climatic data including air temperature, solar radiation, relative humidity and wind speed from Adana Station, Turkey were used as inputs to the fuzzy models to estimate daily ET ₀ values obtained using FAO 56 Penman Monteith (PM) method. In the first part of the study, the effect of each climatic variable on FAO 56 PM ET ₀ was investigated by using fuzzy models. Wind speed was found to be the most effective variable in modeling ET ₀ . In the second part of the study, the effect of missing data on training, validation and test accuracy of the neuro-fuzzy models was examined. It was found that the ANFIS-GP model was not affected by missing data while the test accuracy of the ANFIS-SC model slightly decreases by increasing missing data’s percent. In the third part of the study, the effect of training data length on training, validation and test accuracy of the ANFIS models was investigated. It was found that training data length did not significantly affect the accuracy of ANFIS models in modeling daily ET ₀ . ANFIS-SC model was found to be more sensitive to the training data length than the ANFIS-GP model. In the fourth part of the study, both ANFIS models were compared with the following empirical models and their calibrated versions; Valiantzas’ equations, Turc, Hargreaves and Ritchie. Comparison results indicated that the three-and four-input ANFIS models performed better than the corresponding empirical equations in modeling ET ₀ while the calibrated two-parameter Ritchie and Valiantzas’ equations were found to be better than the two-input ANFIS models.     

Understanding the Role of Urban Road Surface Characteristics in influencing Stormwater Quality

Urban road surfaces are one of the most important stormwater pollution sources. Asphalt and concrete road surfaces are typical road types in China and have different characteristics such as roughness, textures and infiltration rates. This could lead to differences of collecting and retaining pollutants. In this context, designing stormwater treatment for different road surfaces respectively is crucial to effectively minimize the stormwater deterioration. This closely depends on an in-depth understanding of stormwater quality characteristics on urban road surfaces. This research study investigated the stormwater quality characteristics on typical asphalt and concrete surfaces. The research outcomes show that road surface characteristics could play a more important role in influencing the resulting stormwater runoff quality than rainfall characteristics. Additionally, asphalt surface due to the relatively rough nature could play a more important role in influencing the overall pollutant export characteristics from urban road surfaces. It is also noted that there are notable differences in pollutant wash-off processes on different surfaces, where the wash-off process on asphalt surfaces tends to be a transport limiting process, while the wash-off process on concrete surfaces tends to be a source limiting process. These results can contribute to stormwater treatment design enhancement for urban roads such as treatment placement, rainfall event selection and water quality estimation.     

Assessment of the Impact of Stormwater Characteristics on Clogging in Stormwater Filters

Hydraulic conductivity of granular filter media and its evolution over time is a key design parameter for stormwater filtration and infiltration systems that are now widely used in management of polluted urban runoff. In fact, clogging of filter media is recognised as the main limiting factor of these stormwater treatment systems. This paper focuses on the effect of stormwater characteristics on the clogging of stormwater filters. Effect of five different operational regimes has been tested in this study of sediment concentration; pollutant concentrations; stormwater sediment size; loading rate and stormwater loading/dosing regime and compared with the Base case. For each operational condition, five column replicates were tested. Results suggest that sediment concentration in stormwater is a significant parameter affecting hydraulic and treatment performance, eventually affecting longevity of these stormwater treatment systems. Further, the size of sediments (and their relation to the size of filter media grains) in stormwater was found to be an important parameter to be considered in design of coarse filters with high infiltration rates that are used for stormwater treatment. As expected, the addition of metals and nutrients had limited or no contribution to changes in hydraulic or sediment removal performance of the studied stormwater filters. Whilst loading rate was found to be an important parameter affecting the hydraulic and treatment performance of these systems, any variation in the stormwater loading regime had a limited effect on their performance. This study therefore develops an understanding of the effect of catchment characteristics on design of filters and hence their longevity and maintenance needs.     

Sustainable Design of Urban Stormwater Drainage Systems by Implementing Detention Tank and LID Measures for Flooding Risk Control and Water Quality Management

Water Resources Management - With the increasing emphasis and application of the flooding control and mitigation measures of detention tank (DT) and low impact development (LID) in urban stormwater...     

火电厂主厂房不同布置方式下地震反应对比分析

大型火力发电厂是重要的生命线工程,主厂房传统的布置方式采用三连式布置方式,而新的布置方式采用汽机房和煤仓问交叉布置方式.用有限元分析软件对两种布置方式进行反应谱分析,从而对两种布置方式在不同地震烈度条件下的主厂房的层间剪力、层问位移及层间位移角进行对比分析.结果表明,在不同地震烈度条件下,主厂房采用交叉布置方式时,主厂...     

Inadequacy of Land Use and Impervious Area Fraction for Determining Urban Stormwater Quality

Urban stormwater quality is multifaceted and the use of a limited number of factors to represent catchment characteristics may not be adequate to explain the complexity of water quality response to a rainfall event or site-to-site differences in stormwater quality modelling. This paper presents the outcomes of a research study which investigated the adequacy of using land use and impervious area fraction only, to represent catchment characteristics in urban stormwater quality modelling. The research outcomes confirmed the inadequacy of the use of these two parameters alone to represent urban catchment characteristics in stormwater quality prediction. Urban form also needs to be taken into consideration as it was found have an important impact on stormwater quality by influencing pollutant generation, build-up and wash-off. Urban form refers to characteristics related to an urban development such as road layout, spatial distribution of urban areas and urban design features.     

Assessing the Impact of Urban Development and On-Site Stormwater Detention on Regional Hydrology Using Monte Carlo Simulated Rainfall

Water Resources Management - Urban development is a contributor to increased peak runoff and adverse hydrologic effects in regional catchments. On-Site Stormwater Detention (OSD) is a common way to...     

Multi-Objective Optimal Design of Detention Tanks in the Urban Stormwater Drainage System: LID Implementation and Analysis

Under the influences of climate change and rapid urbanization, extreme rainfall events become more and more intensive and the urban flooding issues have been frequently faced in many cities in the world. Previous practical and scientific experiences have demonstrated that appropriate utilization of detention facilities and low impact development (LID) devices for urban region design could be important and effective ways to the flooding control and drainage service management of an urban stormwater drainage system (USDS). This paper investigates the optimal design and application of detention tank network and LID devices for achieving these multiple objectives in the USDS. The framework and method of LID-based multi-objective optimal design of detention tanks in USDS is first developed in this study, and a practical case in SA city of China is then taken for the application. The results of this study confirm the feasibility and validity of the proposed methodological framework for the LID-based multi-objective optimal design of detention tanks in the USDS. Specifically, both total investment costs and flooding risk have been greatly reduced by the optimal implementation of the detention tank and LID measures. Meanwhile, the results indicate that the LID devices may have global effect to the flooding control and the detention tanks can be locally efficient to reduce the flooding risk. Finally, the findings of this study are discussed in the paper for their practical implications to the practical design and management of USDS.     

城市堤防建设加固融资办法探讨

文章介绍了湖南省县级以上城市堤防规则以及建设性情况，分析了城市堤防建设加固的性质和任务．提出了融资建设加固的措施和途径，为城市防洪工程建设提供了一定的参考。     

Many-Objective Optimization of Sustainable Drainage Systems in Urban Areas with Different Surface Slopes

Water Resources Management - Sustainable urban drainage systems are multi-functional nature-based solutions that can facilitate flood management in urban catchments while improving stormwater...     

Multi-objective Optimal Design of Detention Tanks in the Urban Stormwater Drainage System: Uncertainty and Sensitivity Analysis

Design of detention tanks becomes important to the flooding control and drainage service management of an urban stormwater drainage system (USDS). While the hydrological and hydraulic models and methods have been widely developed in the literature for the optimal design and management of USDS, there is not yet a general methodological framework that is applicable for all practical systems. This is mainly because of various complexities in practical USDS, such as different design objectives (i.e., multi-objective design) and local design criteria and policies, as well as variety of inevitable uncertainties in the system. Previous work by the authors has focused on the first two aspects, in which a viable design framework has been developed and applied for multi-objective optimal design of detention tanks in the USDS under conditions of different local design criteria; and this paper deals with the third factor, aiming to explore and extend further the optimal design methodological framework to USDS with uncertainties. A real-life USDS in China is applied for this investigation. Uncertainty analysis is firstly conducted to characterize the importance of different uncertainty factors considered in the studied system. The uncertainty analysis result is thereafter incorporated into the previously developed multi-objective optimal design framework, in which the Monte-Carlo simulation method is adopted for the stochastic process investigation. The case application and analysis indicate different influences of uncertainty factors in the system to the multi-objective design results of detention tanks (total cost and flooding risk) in the studied USDS. The results and findings of this study are also discussed in the paper for their practical implications to the design and management of USDS.     

An Uncertainty-Based Regional Comparative Analysis on the Performance of Different Bias Correction Methods in Statistical Downscaling of Precipitation

Statistical downscaling of General Circulation Models (GCM) simulations is widely used for projecting precipitation at different spatiotemporal scales. However, the downscaling process is linked with different source of uncertainty including structural/parametric uncertainty of the model and output uncertainty. This research proposes a novel framework to assess the parametric uncertainty of downscaling model, and used this framework to assess the performance of different bias correction methods linked to the regression-based statistical downscaling model. The used downscaling framework in the current paper is Statistical Downscaling Model (SDSM). The conventional bias correction method linked with SDSM is the Variance InFlation method (VIF), this paper substitutes this method with three different bias correction methods including Local Intensity Scaling (LOCI), Power Transformation (PT), and Quantile Mapping (QM) to assess the associated parametric and global uncertainty of each method in different climate by using a new approach. The proposed method is applied to six different stations located in Iran and United States with different climate status. Average Relative Interval Length (ARIL), P-level, and Normalized Uncertainty Efficiency (NUE) are used as uncertainty indicators to evaluate the results. Results represent that in every assessed climate class, LOCI, and PT, work better than conventional VIF in both amount and occurrence modules of SDSM framework. More precisely, LOCI works better in station that has wet summer, while PT performs well in the stations where there is no or very limited precipitation in summer. Substituting LOCI with VIF, result in increasing the value of NUE by at least factor of 3 in occurrence and amount model which means the significant reduction in structural uncertainty. Also applying PT in arid regions improves the NUE indicator at least by factor 2 in occurrence and amount model and by factor 3 in output uncertainty assessment, and results in less parametric and output uncertainty. Results illustrate the important role of bias correction approaches in reducing structural, and output uncertainty and improving the statistical efficiency of the downscaling model.