Roof Area Research Articles

PROBABILITY DENSITY BASED CLASSIFICATION AND RECONSTRUCTION OF ROOF STRUCTURES FROM 3D POINT CLOUDS

Abstract. 3D building models including roofs are a key prerequisite in many fields of applications such as the estimation of solar suitability of rooftops. The accurate reconstruction of roofs with dormers is sometimes challenging. Without careful separation of the dormer points from the points on the roof surface, the estimation of the roof areas is distorted in a most characteristic way, which then let the dormer points appear as white noise. The characteristic distortion of the density distribution of the defects by dormers in comparison to the expected normal distribution is the starting point of our method. We propose a hierarchical method which improves roof reconstruction from LiDAR point clouds in a model-based manner separating dormer points from roof points using classification methods. The key idea is to exploit probability density functions (PDFs) to reveal roof properties and design skilful features for a supervised learning method using support vector machines (SVMs). Properties of the PDFs of measures such as residuals of model-based estimated roof models are used among others. A clustering step leads to a semantic segmentation of the point cloud enabling subsequent reconstruction. The approach is tested based on real data as well as simulated point clouds. The latter allow for experiments for various roof and dormer types with different parameters using an implemented simulation toolbox which generates virtual buildings and synthetic point clouds.

Facade Integrated Photovoltaic, state of the art of Experimental Methodology

The concept of Building-integrated Photovoltaics (BIPV) is one of the most promising strategies to employ clean energy in the built environment. Up to now, the PVs have been applied mostly on roofs, but since the total roof area is insufficient, there is a need to integrate photovoltaics on building façades as well. This challenges not only the architectural design of a single building but also the visual image of urban environment, as photovoltaics have to harmonize with conventional building materials used on building facades as brick, concrete, wood, etc. Aiming to provide a foundation for research exploring facade-integration methods that will ensure successful architectural result, the paper presents a state of the art on façade integrated photovoltaics (FIPV) with focus on the experimental research methodology. It embraces both, theoretical research and PVs applications in building projects. As pure computer simulations are not recognized as an experimental methodology, papers conveying such generated results have not been included. In addition, the research that deals exclusively with energy aspects is omitted. The study is based on a comprehensive literature review. Advanced experimental methodologies from selected literature are described and categorized according to the scale (building or urban) and the transparency of the PVs (opaque or translucent). Then detailed features of PV experimental methods are demonstrated in structured tables for analysis and discussion. The study shows that even though solid scientific methods are used to evaluate single features of PVs, e.g. colour or reflectance, there is an obvious lack of methodology providing holistic assessment of Façade-integrated Photovoltaics, especially at the urban scale. The further research will lead toward developing of evaluation criteria framework (in interdisciplinary cooperation) and then provide a holistic methodology combining qualitative and quantitative methods for a successful FIPVs in urban context.

Penerapan teknologi pemanenan air hujan menuju desa mandiri air bersih di Pulau Merbau

One of the efforts to overcome the clean water crisis in the archipelago, one of them is Merbau Island, is to make a simple technology that is used to accommodate excess water during the rainy season and next, the water can be utilized for various purposes when it has been needed. The technology is rainwater storage building (PAH). This community service activity was conducted by making a model of PAH building at one of the residents’ houses and conducting a counselling activity to residents in relation to both of calculation and planning of the PAH building, and also the importance of consuming clean water. The purposes of this community service are to give an understanding and increasing knowledge about the needed for rainwater harvesting technology so that daily clean water needs will be fulfilled by basic infrastructure of the ideal PAH system based on independent-communities. The volume of this rainwater reservoir is needed at 3 m3 (3,000 litres) from the roof area of 36 m2. This rainwater is used to meet the needs of drinking, cooking and washing of 15 litres/person/day. The number of residents in the house is 5 people. The results obtained from this activity are the construction of rainwater reservoirs with a volume of 1,000 litres with good and correct rainwater harvesting system equipment. Thus the lack of 2,000 litres of rainwater storage must be managed independently by the homeowner.

DRAW AND ORDER – MODELESS INTERACTIVE ACQUISITION OF OUTLINES

Abstract. The representation of an object’s outline with polygons or more specific shapes is the first choice for interactive outline acquisition. Usually, an operator has to select appropriate tools to capture an object’s outline according to his or her notion of the shape with its underlying construction principles. We propose a modeless approach guided by geometric reasoning, i.e., the user does not have to select operation modes according to his or her model. To cope with modern input devices such as touch pens, styluses, or fingers, we consider strokes as input in arbitrary order. By approximating theses strokes with straight line segments, we obtain estimated levels of noise accounting for the uncertainty of the acquisition. These straight line segments are the basis for the subsequent hypothesis generation to recognize geometric relations. After identifying sets of consistent and nonredundant constraints, we enforce these constraints in an adjustment process. To demonstrate the usability of the proposed approach, we capture the outlines of buildings and roof areas in true orthophotos of a benchmark data set.

The Postoperative Morphometrics of Orbital and Maxillary Area for Craniosynostosis.

Purpose:One of the most characteristic features in premature craniosynostosis is fronto-orbital retrusion. The standardized surgical technique of fronto-orbital advancement (FOA) can treat this (some) deformity, such as bilateral coronal synostosis. The purpose of the study is to investigate an available method to assess the postoperative outcome of the craniofacial surgery.Methods:From 2010 to 2015, 6 pediatric patients were taken the FOA in the Department of Burn and Plastic Surgery in the Children‘s Hospital of Nanjing Medical University. All the patients were performed the computed tomography (CT) scan preoperatively and postoperatively. The CT databases were processed by DICOM files into MIMICS 16.0 software, which were automatically calculated into orbital volume and orbital roof and base surface area. T-test was used to compare measured values before and after surgery. P < 0.05 was considered statistically significant.Results:The average preoperative orbital volume was 13930.70 mm3, and the postoperative was 18578.67917 mm3. After operation, the volume of orbital was significantly increased (P < 0.05). The mean area of the orbital roof surface was 753.989025 mm preoperatively, and the postoperative was 1122.074583 mm. The difference was statistically significant (P < 0.05). The average area of the orbital base (S2) was 334.94 ± 91.76 mm2. After the FOA, the orbital base was 356.99 ± 114.21 mm2. P(S2) = 0.6072 > 0.05, there was no significant statistical difference.Conclusions:Fronto-orbital advancement can successfully improve morphological orbital deformities in children with premature craniosynostosis, but much less for maxillary. The computer-assisted technique can present a measurement of FOA preoperatively and postoperatively, which make the evaluation intuitive.

Modeling and Simulation of a Building towards Energy Efficiency

Residential buildings are the significant energy consumer of the India which is about 24% of the total energy consumption. Energy efficient buildings are the ideal solution to reduce energy consumption in the building sector. The energy efficient buildings can be achieved by incorporating passive features or renewable energy systems or both. The current work aims to perform a retrofitting analysis of an existing building into an energy efficient building. For performing the energy analysis REVIT 2017 tool is used. Using the REVIT 2017 tool building model is developed, building information are loaded and energy analyses are performed. The building is analyzed as two cases. The first case is to estimate energy performance of the existing building. The second case is to incorporate passive features and renewable energy system to the building and evaluate the energy performance. Existing building Energy Usage Intensity (EUI) was 193 kWh/m2/year. When passive features (Insulation, additional window glazing and efficient air conditioning systems) alone incorporated to the building the building EUI is reduced to 138 kWh/m2/year. Along with Passive features Photovoltaic modules with different efficiencies 16%, 18% and 20% are considered for renewable energy generation. The energy generation for the different PV modules for three different roof area (40%, 60% and 70% of total roof area) is evaluated. The energy usage intensity varies from 11.4 from -150 kWh/m2/year for the combination of different efficiency of PV module and the different % of roof area covered. The negative sign indicates the energy generation after the required energy usage. The payback period for only incorporating passive features is 6.3 years and while incorporating PV system with passive features is 9 years.

Predicting Heating and Cooling Loads in Energy-Efficient Buildings Using Two Hybrid Intelligent Models

Today, energy conservation is more and more stressed as great amounts of energy are being consumed for varying applications. This study aimed to evaluate the application of two robust evolutionary algorithms, namely genetic algorithm (GA) and imperialist competition algorithm (ICA) for optimizing the weights and biases of the artificial neural network (ANN) in the estimation of heating load (HL) and cooling load (CL) of the energy-efficient residential buildings. To this end, a proper dataset was provided composed of relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, glazing area distribution, as the HL and CL influential factors. The optimal structure of each model was achieved through a trial and error process and to evaluate the accuracy of the designed networks, we used three well-known accuracy criterions. As the result of applying GA and ICA, the performance error of ANN decreased respectively by 17.92% and 23.22% for the HL, and 21.13% and 24.53% for CL in the training phase, and 20.84% and 23.74% for HL, and 27.57% and 29.10% for CL in the testing phase. The mentioned results demonstrate the superiority of the ICA-ANN model compared to GA-ANN and ANN.

Assessing rainwater harvesting systems and reliability analysis of storage tanks: a monitoring study and system simulation

AbstractThis study applied a simulation model to evaluate the reliability of rainwater harvesting systems (RWHs) and the potential for rainwater storage was investigated in three different buildings. The results indicated that the tank stores 97.7% of the run‐off from the gym roof. Modelling the volume of the tank connected to the gym roof showed that 100% reliability can not be achieved for a roof with a relatively small area. The reliability for a tank larger than 2600 L was independent of the size of the tank. Maximum reliability of the RWHs was 70% of the total days of the year for a tank volume of 10 000 L, 300 m2 roof area and daily demand of 300 L (60% demand). Minimum reliability was 3% of the total days of the year for a tank volume of 1000 L, 100 m2 roof area and a daily demand of 1000 L (80% demand).

Numerical Investigation of Multi-SDBD Plasma Actuators for Controlling Fluctuating Wind Load on Building Roofs

The present research aims to explore, by large-eddy simulation (LES), the potentiality and mechanism of multiple surface dielectric barrier discharge (multi-SDBD) plasma actuators to manipulate mean and fluctuating wind loads on a low-rise building. Three actuator configurations are located on the roof to induce directional wall jets in different directions. The effects of these configurations on flow structure and wind loads are studied in absence and presence of approaching flow. Results show that all subgrid-scale models can obtain accurate roof pressure, and for the diffusion and convection terms, the bounded central differencing scheme can provide more accurate predictions for the roof pressure. The control impact of active actuators gradually weakens with the increase of the approaching flow velocity. The direction of the wall jet can determine the position of the limited roof region with the reduced mean pressure coefficient. The multi-SDBD actuators continue to absorb the upstream flow and blow this flow downstream, meaning the wall jet exerts strong pressure on the local roof area at the end of the jet, which results in a significant reduction of the mean pressure coefficient. Furthermore, the counter-rotating vortices caused by the wall jet restrain the size and strength of the vortex shedding, thereby achieving the purpose of reducing the fluctuating pressure coefficient. Further analysis of the instantaneous vorticity fields indicates that the intensity and size of streamwise shedding vortices can be restrained by small-scale spanwise vortices induced by the plasma actuators. Under the action of the wall jet blowing from the trailing edge to the leading edge, the fluctuating lift and drag coefficients can be reduced by over 15% and the fluctuating pressure coefficient can be reduced by about 20% from the no actuation situation.

Performance of single-sloped pitched roof cadmium telluride (CdTe) building-integrated photovoltaic system in tropical weather conditions

BackgroundThis paper investigates the performance of a single-sloped pitched roof building-integrated photovoltaic (SSPR-BIPV) system. A typical rural building having a roof area of 60 sq. m is considered for the study. It was observed that the considered roof area could accommodate, nearly 7 kW BIPV system, and on the other side, most buildings seen in Malaysia are of the roof based constructed at different roof pitches. Considering this, a SSPR-BIPV is proposed and analyzed in seven different pitched roofs (the steepness of roof slopes are 15°, 18°, 22°, 30°, 35°, 40°, and 45°) under the tropical weather conditions in Malaysia.Results and discussionAs per the study constraints, the 7 kW CdTe BIPV under seven different pitched roofs is capable of generating electricity within the range of 9510 to 7710 kWh. Performance ratio and energy losses for seven pitched roofs were identified to be in the range of 74.92 to 76.37% and − 23.63 to − 25.08% respectively. From the results, it is observed that in a BIPV system, as the building roof pitch increases, the energy yields and performance ratios tend to decrease, thereby increasing the overall energy losses.ConclusionHence, this study reveals that there exists a considerable influence of pitched roof over the BIPV performance and suggests using lower roof pitch angles during the installation of BIPV roof especially in the case tropical weather conditions.

Control Measure Effects on the Effluent Quality from Extensive Green Roofs Based on Stabilized Sludge Recycling

Substrate type is an important factor affecting the quality of water deriving from rainfall onto extensively green roofed areas. Here, stabilized sludge was used as the main nutrient component of the substrate combined with biochar and a dual-substrate structure. Five green roof pilot facilities were constructed, and the effect of control measures on effluent quality was analyzed. The results showed that the stabilized sludge dosage was 3%, and the annual average mass concentrations of total nitrogen (TN) and nitrate nitrogen (NO3--N) were 3.27 mg·L-1 and 1.61 mg·L-1. The use of stabilized sludge as a nutrient component under real rainfall and temperature conditions in Shanghai did not cause significant leaching of TN and NO3--N. In order to further improve the quality of the effluent, biochar was used as an amendment measure. As a result, the concentrations of TN and NO3--N in the effluent were decreased to 2.16 mg·L-1 and 1.38 mg·L-1, respectively. Using an adsorption layer of pumice can alleviate the leaching of total phosphorus (TP) and chemical oxygen demand (COD). For the total nitrogen budget of each pilot facility, the retained TN was about 55% of the original TN after one year of operation. Thus, stabilized sludge could be used as a nutrient substrate to meet the long-term requirements of plants. In the substrate with biochar, the retained TN in the substrate and the NO3--N concentration in the effluent was decreased, which was related to the mineralization of organics during dry periods and the enhancement of denitrification during rainfall periods. Stabilized sludge was not a polluting source of N but was a source of P. Using biochar and a dual-substrate structure can effectively reduce the TN and COD load of the tested green roof facilities.

Rainwater harvesting in Jordan: potential water saving, optimal tank sizing and economic analysis

ABSTRACT This paper presents an integrated approach regarding rainwater harvesting that includes investigating potential water savings, optimal tank sizing and cost-benefit analysis at different rainfall zones in Jordan. It is found that a maximum of 30.5 × 106 m3/year of rainwater can be collected from the roofs of residential buildings which is approximately 8% of the total supply for the year 2015. In addition, water harvesting yields and optimal tank size are calculated for any roof area in different rainfall zones in Jordan. Benefit-cost analyses results revealed that pear shape tanks will be economically feasible in all rainfall zones when a 1 $US/m3 is assigned as a cost of water saving. Concrete tanks will not be economically feasible at this cost. Payback period analysis indicates that the costs associated with the installation of rainwater harvesting systems could be equalized within 5–45 years depending on the rainfall condition, roof size, price of water savings and tank type.

Implementing green roof technology: an investigation of the effects on energy demand, fuel consumption, and pollutant emission

This study investigated the effect of green roofing on energy and fuel saving and the consequent reduction in pollutant emissions in Mashhad in the hot period of the year. The DesignBuilder software package was used to model and simulate a sedum-vegetated green roof with 10-cm-thick dry soil on a 350-square meter building. The reduction in cooling load (energy saved during the hot period of the year) due to this green roof was estimated to 7.9 kWh/m2 year. The rest of the estimations were performed based on three scenarios where the roof area available for the implementation of green roof projects in the city was assumed to be 7.8, 45, and 96 million square meters, respectively. In these scenarios, the total energy saving in the hot period of the year was estimated to 61,620, 355,500, and 758,400 MWh, respectively. It was also found that the reduced consumption of fuel in power plants because of the reduced demand for energy would result in 0.7–9 million dollars’ worth of cost-saving every year. The results of the scenario analysis showed that the emission reductions due to the implementation of green roofs would be in the range of 17.5 and 299.3 (ton/year) for PM10, 17.3 and 215.8 (ton/year) for CO, 154.9 and 1905.9 (ton/year) for NOx, and 280 and 3445.9 (ton/year) for SO2. The total reduction in the environmental damage costs of pollutant emissions in the three scenarios was estimated to 2.45, 14.21 and 30.32 million dollars per year, respectively.

Optimum tank size for a rainwater harvesting system: Case study for Northern Cyprus

The available freshwater is limited on earth. On the other hand, available water resources on earth have been depleting and being polluted due to climate change and population growth. In order to reduce the risk of water scarcity and water resources contamination, Integrated water resources management (IWRM) is required. IWRM is a concept to manage water resources that aims to balance economic efficiency, social equity, and environmental sustainability. When rainwater harvesting systems (RWHS), one of the techniques of IWRM, are implemented, the stress on water resources is reduced. Since the installation cost of rainwater harvesting systems significantly depends on the size of the rainwater storage tanks, in the implementation of rainwater harvesting, the selection of tank size is one of the main concerns for the feasibility of the system. This study aims to investigate the feasibility of domestic rainwater harvesting systems for a single house. In order to find the optimum storage tank size of the rainwater harvesting system, a linear programming (LP) optimization model is employed. As a case study, the LP model is applied to six regions from semi-arid Eastern Mediterranean island Northern Cyprus, where water resources are limited. The model considers thirty-seven years monthly rainfall data, the roof area of the building, the water consumption per capita, the discount rate, the cost of the rainwater storage tank, and the number of residents. The results of the selected study areas show that the implementation of the RWHS for a single house is infeasible due to the substantial installation costs and maintenance expenses. The financial losses caused by the implementation of the RWHS are found higher than the installation costs and maintenance expenses for all regions. In addition to economic analyses, environmental benefits of the RWHS should be included into the feasibility analysis.

Performance analysis of radiation and electricity yield in a photovoltaic panel integrated greenhouse using the radiation and thermal models

The agricultural photovoltaic panel integrated greenhouse (PVIG) are attempted to improve the utilization of solar energy for sustainable agriculture. This study proposes a numerical method to predict the radiation distribution and the electricity yield of a PVIG throughout the year using 3D radiation model and thermal model. The radiation model is validated in a PVIG in the southeast of China with 36 rooftop PV panels of straight-line layout and the PV array covering 25% of the greenhouse roof area. According to simulation of conventional greenhouse and PVIG with straight-line (La), crisscross (Lb) and checkerboard (Lc) PV panels’ layouts, the performance of different PVIG is evaluated in terms of the non-uniformity of the radiation distribution, the radiation intensity and the electricity yield of PV panels. The non-uniformity of the hourly radiation under the La layout is not much different from the layout Lb and Lc, and the cumulative weekly radiation under the layout of La is increased by 8.3% and 12.7% in the experimental PVIG, respectively. The thermal model of PV panels mounted on the greenhouse roof is developed to accurately predict the PV electricity yield, considering the impact of greenhouses and external environments on PV panels. In contrast to the layouts of La and Lb, the annual electricity yield of PV panels with the layout of Lc raises by 3.2 and 2.2 kWh m−2 respectively. Compared with conventional greenhouse, the distribution and intensity of cumulative weekly radiation are not significantly affected by the optimal PV array covering 25% of the greenhouse roof area. These results indicate that the 3D radiation model and thermal model can be used as an efficient tool to optimize the performance of PVIG.

Estimating the Heating Load of Buildings for Smart City Planning Using a Novel Artificial Intelligence Technique PSO-XGBoost

In this study, a novel technique to support smart city planning in estimating and controlling the heating load (HL) of buildings, was proposed, namely PSO-XGBoost. Accordingly, the extreme gradient boosting machine (XGBoost) was developed to estimate HL first; then, the particle swarm optimization (PSO) algorithm was applied to optimize the performance of the XGBoost model. The classical XGBoost model, support vector machine (SVM), random forest (RF), Gaussian process (GP), and classification and regression trees (CART) models were also investigated and developed to predict the HL of building systems, and compared with the proposed PSO-XGBoost model; 837 investigations of buildings were considered and analyzed with many influential factors, such as glazing area distribution (GAD), glazing area (GA), orientation (O), overall height (OH), roof area (RA), wall area (WA), surface area (SA), and relative compactness (RC). Mean absolute percentage error (MAPE), root-mean-squared error (RMSE), variance account for (VAF), mean absolute error (MAE), and determination coefficient (R2), were used as the statistical criteria for evaluating the performance of the above models. The color intensity, as well as the ranking method, were also used to compare and evaluate the models. The results showed that the proposed PSO-XGBoost model was the most robust technique for estimating the HL of building systems. The remaining models (i.e., XGBoost, SVM, RF, GP, and CART) yielded more mediocre performance through RMSE, MAE, R2, VAF, and MAPE metrics. Another finding of this study also indicated that OH, RA, WA, and SA were the most critical parameters for the accuracy of the proposed PSO-XGBoost model. They should be particularly interested in smart city planning as well as the optimization of smart cities.

Optimization calculation of stope structure parameters based on Mathews stabilization graph method

Mathews stability graphic method, based on the rock classification system, measures the stability of the ore roof area of a relatively simple calculation method and provides a theoretical basis for mine rational design stope structure size parameters. In this study, we used a large-scale tungsten mine in Jiangxi Province as the engineering background and performed on-site engineering geological surveys and indoor ore rock mechanics tests in the middle section of mine 417 to obtain multiple engineering quality indicators for the mines and surrounding rocks. The Mathews stability map method and Barton limit span theory were used. The reasonable size range of the exposed face of the stope was calculated by performing theoretical analysis on the ultimate span. Then, FLAC3D calculation and analysis software were used for the simulation of the stope structure, and the most reasonable design of the exposed surface dimension was selected and used as reference for ensuring the safe production of the mine.

A Comparative Study of PSO-ANN, GA-ANN, ICA-ANN, and ABC-ANN in Estimating the Heating Load of Buildings’ Energy Efficiency for Smart City Planning

Energy-efficiency is one of the critical issues in smart cities. It is an essential basis for optimizing smart cities planning. This study proposed four new artificial intelligence (AI) techniques for forecasting the heating load of buildings’ energy efficiency based on the potential of artificial neural network (ANN) and meta-heuristics algorithms, including artificial bee colony (ABC) optimization, particle swarm optimization (PSO), imperialist competitive algorithm (ICA), and genetic algorithm (GA). They were abbreviated as ABC-ANN, PSO-ANN, ICA-ANN, and GA-ANN models; 837 buildings were considered and analyzed based on the influential parameters, such as glazing area distribution (GLAD), glazing area (GLA), orientation (O), overall height (OH), roof area (RA), wall area (WA), surface area (SA), relative compactness (RC), for estimating heating load (HL). Three statistical criteria, such as root-mean-squared error (RMSE), coefficient determination (R2), and mean absolute error (MAE), were used to assess the potential of the aforementioned models. The results indicated that the GA-ANN model provided the highest performance in estimating the heating load of buildings’ energy efficiency, with an RMSE of 1.625, R2 of 0.980, and MAE of 0.798. The remaining models (i.e., PSO-ANN, ICA-ANN, ABC-ANN) yielded lower performance with RMSE of 1.932, 1.982, 1.878; R2 of 0.972, 0.970, 0.973; MAE of 1.027, 0.980, 0.957, respectively.

Comparison of solar thermal and solar electric space heating and cooling systems for buildings in different climatic regions

Solar thermal and Photovoltaic (PV) systems can save significant amount of non-renewable energy that are utilized to satisfy the energy services for buildings. The falling prices of PV in recent years increased the attractiveness of PV systems. The purpose of this research is to develop a systematic methodology for fair technical and economical comparison of reference and solar assisted systems. For this reason, the annual energy requirements for heating, cooling and DHW for a selected dormitory building under five representative climatic conditions were evaluated using the Hourly Analysis Program (HAP). At the same time, solar thermal and PV systems have been designed and simulated for the same building using Sketchup, Trnsys and PVsyst. Finally, a systematic comparison between the solar systems and five conventional systems have been carried out in terms of primary energy ratio, and Levelized Cost Of Energy (LCOE). For the case of Amman, solar thermal and electric systems achieved a non-renewable primary energy savings of 29% and 100%, respectively, whereas, they achieved LCOE savings of 15% and 62%, respectively compared to the best conventional system. The selection of the best solution for a given project requires a full understanding of the system performance and the interaction of its components rather than the technology efficiency only. This system performance depends on the building envelope, load patterns, availability of solar radiation, roof area availability, energy prices, and policies. Thus, a case-by-case analysis should be done for each project in each climatic region.

Evaluating Sponge City volume capture ratio at the catchment scale using SWMM

China has begun a rapid move towards Sponge City implementation, which will include widespread installation of various Low Impact Development (LID) stormwater infrastructure. Ambitious goals have been set for all Sponge Cities, including a target capture rate of 80–85% of annual precipitation in Beijing. However, there has so far been limited investigation into whether these goals are obtainable at the catchment scale given the physical restrictions of the existing urban landscape. This paper demonstrates the use of long-term continuous hydrologic modelling to evaluate the potential of meeting rainfall capture goals over a long time period for a case study area in Beijing. Detailed land cover classification derived from satellite imagery aided in the parameterization of a SWMM (Stormwater Management Model) model representing a 133 km2 urban study area. The calibrated and validated model demonstrated satisfactory agreement between computed and observed runoff for a variety of precipitation events ranging from 10 to 207 mm. A synthetic high resolution rainfall time series was generated from historic daily observations then used as input to run the model continuously for a 35 year period. Feasible LID model scenarios based on varying degrees of implementation of rain gardens, permeable pavements and green roofs were compared in terms of their potential volume capture of annual rainfall. Modelling results demonstrated that the conversion of 30% of roof area to green roof, 10% of green areas to rain gardens and 35% of paved areas to permeable pavement could increase the baseline volume capture ratio from 59.9% to 82.2%, indicating that Sponge City goals can be met within the case study area with realistic levels of LID implementation. This study provides a decision-making basis for future planning in the study area.