Node Overflow Research Articles

Runoff Control Performance of Three Typical Low-Impact Development Facilities: A Case Study of a Community in Beijing

The development of sponge cities advocates for sustainable urban rainwater management, effectively alleviating urban flood disasters, reducing non-point-source pollution, and promoting the recycling of rainwater resources. Low-Impact Development (LID) serves as a key strategy in this context, providing essential support for urban rainwater control and pollution reduction. To investigate the runoff control effects of LID measures and to reveal the relationship between facility runoff control performance and installation scale, this study focuses on a sponge community in Beijing. A SWMM model was constructed to analyze the rainwater flood control and pollutant load reduction effects of different LID facilities, including bio-retention cells, green roofs, and permeable pavements. Using evaluation indicators such as surface runoff, node overflow, and pollutant control rates, this study examined how facility performance varies with installation scale under different rainfall conditions. The combination scheme of LID equipment optimal configuration is designed by using multiple criteria decision analysis (MCDA) and cost–benefit theory. The results indicate significant differences in performance among the various LID facilities across different rainfall scenarios. Specifically, the optimal installation proportion for runoff and overflow control of permeable pavements were found to be between 30% and 70%. Green roofs demonstrate superior performance in handling extreme rainfall events, while bio-retention cells exhibit significant effectiveness in controlling Total Suspended Solids (TSSs). Through comprehensive performance evaluation, this study identified the optimal combination scale under a 3-year rainfall recurrence interval as 30% permeable pavements, 20% green roof, and 60% bio-retention cells. This combination effectively leverages the strengths of each facility, ensuring system stability and efficiency while also demonstrating optimal management efficiency in cost–benefit analyses. The findings of this research provide valuable insights for future urban water management and infrastructure development.

Urban flooding simulation and flood risk assessment based on the InfoWorks ICM model: A case study of the urban inland rivers in Zhengzhou, China.

Urban flooding intensifies with escalating urbanization. This study focuses on Xiong'er river as the study area and couples a 1D/2D urban flooding model using InfoWorks ICM (Integrated Catchment Modeling). Ten scenarios are set respectively with a rainfall return period of 5a 10a, 20a, 50a, and 100a, alongside rainfall durations of 1 and 24 h. Subsequently, the H-V (hazard-vulnerability) method was applied to evaluate urban flooding risk. Three indicators were selected for each of hazard factors and vulnerability factors. The relative weight values of each indicator factor were calculated using the AHP method. The result shows that (1) flood depth, rate, and duration escalate with longer rainfall return periods, yet decrease as the duration of rainfall increases; (2) as the rainfall return period lengthens, the proportion of node overflow rises, whereas it diminishes with longer rainfall durations, leading to an overall overloaded state in the pipeline network; and (3) the distribution in the research area is mainly low-risk areas, with very few extremely high-risk. Medium to high-risk areas are mainly distributed on both sides of the river, in densely built and low-lying urban areas. This study demonstrates that the model can accurately simulate urban flooding and provide insights for flood analyses in comparable regions.

Assessment of urban inundation and prediction of combined flood disaster in the middle reaches of Yellow river basin under extreme precipitation

Watershed Cities often face the dual flood risks of upstream floods and urban waterlogging. This compound disaster is caused by the interaction of multiple factors (topography, storms, upstream water and urban drainage, etc.), and is particularly affected by extreme rainfall events and the large and small drainage carrying capacity. To explore the combined effects of extreme rainfall and drainage systems, this study applied the Chicago rainfall hyetograph method and constructed design under different return periods. A comprehensive model combining the verified SWMM and LISFLOOD hydraulic models was utilised to build one-dimensional and two-dimensional coupled watershed urban flood models, simulating inundation depth and duration. By considering urban rainfall, runoff, topography, and drainage system characteristics, the flood processes under different extreme rainfall scenarios were simulated, and the node overflow and inundation depth were obtained. A flood risk assessment of watershed cities was conducted by combining methods such as the HR threshold method, evaluation level, and threshold division. In this study, Huyi District of Xi’an City, China, was used as the research area. The main research findings show: (1) the precipitation design values for different return periods were calculated based on the proposed method, with amount for a 100-year event being 87.196 mm, suitable for composite flood simulation; (2) applying the SWMM-LISFLOOD coupled model constructed for midstream urban areas ensured the accurate simulation of composite flood processes. Under different extreme rainfall return period scenarios, the percentage of flood inundation depth exceeding 1 m caused by multiple disaster factors increased from 0.73 % to 5.19 %; (3) extreme rainfall leads to different levels of internal flooding risk. When the return period of extreme rainfall is 5 years, the area inundated by composite floods in the research area is 67.21 km2. In comparison, when the return period of extreme rainfall is 50 years, the area inundated by composite floods in the research area significantly increases to a total inundation area of 286.85 km2. This study is expected to provide scientific references for flood prevention planning, composite disaster risk management, and urban resilience building in watershed urban areas while significantly impacting modern economic growth, social stability, and the safety of watershed cities.

Integrated modeling of urban mobility, flood inundation, and sewer hydrodynamics processes to support resilience assessment of urban drainage systems.

With the increasing frequency of extreme weather events and a deepening understanding of disasters, resilience has received widespread attention in urban drainage systems. The studies on the resilience assessment of urban drainage systems are mostly indirect assessments that did not simulate human behavior affected by rainfall or semi-quantitative assessments that did not build simulation models, but few research characterizes the processes between people and infrastructure to assess resilience directly. Our study developed a dynamic model that integrates urban mobility, flood inundation, and sewer hydrodynamics processes. The model can simulate the impact of rainfall on people's mobility behavior and the full process including runoff generation, runoff entering pipes, node overflow, flood migration, urban mobility, and residential water usage. Then, we assessed the resilience of the urban drainage system under rainfall events from the perspectives of property loss and urban mobility. The study found that the average percentage increase in commuting time under different return periods of rainfall ranged from 6.4 to 203.9%. Calculating the annual expectation of property loss and traffic obstruction, the study found that the annual expectation loss in urban mobility is 9.1% of the annual expectation of property loss if the rainfall is near the morning commuting peak.

Overflow Simulation and Optimization of a Drainage System in an Urban Area in the Northern Anhui Plain

Quantitative simulation of urban waterlogging using computer models is an effective technical means for urban storm water management, especially for predicting and preventing waterlogging. In this study, a city in the northern Anhui Plain, China, was selected as the study site. The Storm Water Management Model was applied to simulate the dynamic changes in the pipeline overload, node overflow, and discharge port runoff characteristics from three perspectives: surface runoff, pipe network transmission, and flow control of low-impact development. The operation of the rainwater pipe network under different return periods and the real-time operation of the rainwater pipe network were simulated to seek solutions to urban waterlogging problems caused by flat terrain and slow drainage. The results revealed that surface runoff is the primary source of rainfall in the study area, with a runoff coefficient of 0.599. The drainage pipe network was optimized by expanding the diameter of the pipe from ≤1.5 mm to ≥2 mm. The water reduction rate was more than 50%, and overload did not occur after optimization. Therefore, sinking green space technology and optimization methods for expanding a pipe diameter can reduce urban waterlogging.

Method for analyzing urban waterlogging mechanisms based on a 1D-2D water environment dynamic bidirectional coupling model

Urban waterlogging is a significant global issue. To achieve precisely control urban waterlogging and enhance our understanding of its causes, a novel study method was introduced. This method is based on a dynamic bidirectional coupling model that combines 1D-2D hydrodynamic and water quality simulations. The waterlogging phenomenon in densely populated metropolitan areas of Changzhi city, China, was studied. This study focused on investigating the process involved in waterlogging formation, particularly overflow at nodes induced by the design of the topological structure of the pipe network, constraints on the capacity of the underground drainage system, and the surface runoff accumulation. The complex interplay among these elements and their possible influences on waterlogging formation were clarified. The results indicated notable spatial and temporal variation in the waterlogging formation process in densely populated urban areas. Node overflow in the drainage system emerged as the key influencing factor in the waterlogging formation process, accounting for up to 71% of the total water accumulation at the peak time. The peak lag time of waterlogging during events with short return periods was primarily determined by the rainfall peak moment. In contrast, the peak time of waterlogging during events with long return periods was influenced by the rainfall peak moment, drainage capacity and topological structure of the pipe network. Notably, the access of inflow from both upstream and downstream segments of the pipe network drainage system significantly impacted the peak time of waterlogging, with upstream water potentially delaying the peak time substantially. This study not only provides new insights into urban waterlogging mechanisms but also provides practical guidance for optimizing urban drainage systems, urban planning, and disaster risk management.

Operation Risk Simulation and Interaction Impact of Stormwater and Sewage Systems Based on Storm Water Management Model

With the increasing urbanization rate, higher demand is placed on drainage systems, necessitating analysis of their risk profiles. While many studies focus on the individual hydraulic modeling of stormwater and wastewater systems when considering operational risks, they often overlook the exacerbating effects of combined stormwater and wastewater flows on each other’s risks. In this study, we constructed a model of the combined stormwater and wastewater drainage system in Lijiao, Guangdong Province. We analyzed the operational risks of both stormwater and sewage networks in different scenarios, focusing on full-load pipes, overload pipes, node overflows, and minimum flow velocities. Furthermore, we compared the exacerbating effects of sewage and stormwater on each other’s network operational risks. Simulation results indicated that, for sewage networks with combined sewer sections, the lengths of full-load pipes and overload pipes increased by an average of 27.4% and 16.3%, respectively, during rainy weather scenarios compared to dry weather. After considering the inflow of sewage into combined sewer sections, the average length of full-load pipes increased by 3.8 km, overload pipe length increased by 1.1 km, and overflow volume increased by 2.26 × 104 m3. As the return period of rainfall events increases, these inter-system impacts gradually diminish. Therefore, when modeling drainage systems and assessing operational risks, particularly during low return period rainfall events, the inclusion of both stormwater and sewage in combined sewer networks should be comprehensively considered.

Optimized Design of Sponge-Type Comprehensive Pipe Corridor Rainwater Chamber Based on NSGA-III Algorithm

Currently, most of the studies using optimization algorithms to mitigate the urban flooding problem have no more than three optimization objectives, and few of them take the operation status of the traditional drainage system as one of the optimization objectives, which is not conducive to the overall design of the city. This study proposes to mitigate the urban flooding problem by using a sponge-type comprehensive pipe corridor rainwater chamber. A four-objective optimization model is established by coupling the Storm Water Management Model (SWMM) and the Non-dominated Sorting Genetic Algorithm-III (NSGA-III), and two traditional drainage system state indicators (pipe overload time, node overflow volume), surface runoff coefficient, and total investment cost are selected as the optimization objectives for solving the problem. The results show that (1) the reduction rates of surface runoff coefficient, pipe overload time, and node overflow volume rate by the optimization model are 37.015–56.917%, 81.538–91.435%, and 51.578–84.963%, respectively; and the total investment cost is RMB 4.311–4.501 billion. (2) The effectiveness of combining SWMM and NSGA-III for an optimization solution is verified, and the relationship between the four objectives is explored. The study may provide useful information for urban flood control.

Urban waterlogging control: A novel method to urban drainage pipes reconstruction, systematic and automated

Reconstruction of the drainage system is an important measure for urban waterlogging control. For the drainage system of the community, factors such as upstream pipeline water capacity and downstream bottleneck pipeline are often neglected in the process of network reconstruction. Only the network in the waterlogged area is reformed, which is lack of systematicness, and may lead to the failure of waterlogging control. To solve this problem, the Storm Water Management Model (SWMM 5.1) is used to analyze the rationality of the current pipe network reconstruction methods using three indicators: the maximum overflow depth, the maximum overflow volume, and the conduit surcharge. And a new reconstruction method for drainage pipe networks is developed by R programming. The results show that the current pipe network reconstruction method is still insufficient to achieve the goal of eliminating node overflow. For different rainfall conditions, there are still existing low-risk areas, with maximum overflow depth can reach up to 0.15 m and maximum overflow volume can reach up to 7.12 m3. The novel developed drainage pipe network reconstruction method (optimizing pipe network) can effectively identify the bottleneck pipes, and by repeatedly expanding the bottleneck pipes, the goal of node overflow can be achieved under a given rainfall event.

Prediction of Future Urban Rainfall and Waterlogging Scenarios Based on CMIP6: A Case Study of Beijing Urban Area

Extreme weather events will become more frequent and severe as a result of climate change, necessitating an immediate need for cities to adapt to future climate change. Therefore, the prediction of future precipitation and waterlogging is of utmost importance. Using Beijing as an example, the simulation capability of different models was evaluated, and the optimal model for the study area was screened using Taylor diagrams and interannual variability scores, along with actual monthly precipitation data from Chinese weather stations from 1994 to 2014 and historical monthly precipitation data from 10 coupled models from Coupled Model Intercomparison Project Phase 6 (CMIP6). The SWMM model was then used to simulate future rainfall and waterlogging scenarios for the study area using precipitation forecast data for 2020–2050 from the best model to investigate the impact of climate change on future rainfall and waterlogging in urban areas. CMIP6 brings together the most recent simulation data from major climate models on a global scale, providing a broader and more diverse range of model results and thereby making future predictions more accurate and dependable, and its findings provide a theoretical foundation for the emergency management of and scientific responses to urban flooding events. The following major conclusions were reached: 1. The best-performing models are EC-Earth3, GFDL-ESM4, and MPI- ESM1-2-HR. EC-Earth3 is a modular Earth system model developed collaboratively by a European consortium. MPI-ESM1-2 is a climate precipitation prediction model developed in Germany and promoted for global application, whereas the GFDL-ESM4 model was developed in the United States and is currently employed for global climate precipitation simulations. 2. Under future climate circumstances, the total annual precipitation in the example region simulated by all three models increases by a maximum of 40%. 3. Under future climatic conditions, urban surface runoff and nodal overflow in the study area will be more significant. The node overflow will become more severe with the increase in climate scenario oppression, and the potential overflow nodes will account for 1.5%, 2.7%, and 2.9% of the total number of nodes under the SSP1–2.6, SSP2–4.5, and SSP5–8.5 scenarios, respectively. 4. In the future, the effectiveness of stormwater drainage systems may diminish. To increase climate change resilience, the impacts of climate change should be considered when planning the scope of stormwater optimization and the integrated improvement of gray–green–blue facilities.

Model-Predicted Control System for the Real-Time Operation of an Urban Drainage System to Mitigate Urban Flood Risk: A Case Study in the Liede River Catchment, Guangzhou, China

A model-predicted control (MPC) system, which is based on a storm water management model (SWMM) and uses a multi-objective particle swarm optimization algorithm, is developed and applied to optimize the real-time operation of an urban drainage system (UDS) in the Liede River catchment, Guangzhou, China. By comparing the results of three control scenarios (i.e., the original control scenario, the current MPC, and the ideal MPC) under three typical rainfall events, the results demonstrate that the MPC system can effectively mitigate urban flood risk in engineering applications and the decision-making of the MPC system is valid. By comparing the control results of the MPC system under different rainfall return periods (e.g., 1, 2, 3, 5, and 10 years), it is found that compared with the original control scenario, the total overflow is reduced by 10%, the total overflow time is reduced by 10%, or the node overflow start time is delayed by an average of 10 minutes, and the real-time control of the MPC system is only effective when the return period of the rainfall is less than three years. It is important to explore different ways of combining the MPC system and feasible capital measures to cope with urban flood risk and challenges of climate change in future works (e.g., mean sea level rise and intense rainfall).

Urban Pluvial Flood Modeling by Coupling Raster-Based Two-Dimensional Hydrodynamic Model and SWMM

Urban flood modeling usually involves simulating drainage network runoff and overland flow. We describe a method for urban pluvial flood modeling by coupling the stormwater management model (SWMM) with a raster-based 2D hydrodynamic model, which is based on a simplified form of the shallow water equations. Then, the method is applied to a highly urbanized area in Nanjing City, China. The elevation of the raster-based 2D hydrodynamic model shows that the raster-based model has comparable capabilities to LISFLOOD-FP for surface flood modeling. The calibration and validation results of the coupled model show that the method is reliable. Moreover, simulation results under the six rainfall return periods, which include 1-, 5-, 10-, 20-, 50-, and 100-year return periods show that node overflow, water depth, and flooding area increase proportionately as the intensity of rainfall increases. Therefore, the coupling model provides a simplified and intuitive method for urban pluvial flood modeling, which can be used to detect flood-sensitive areas and elevate the capacity of urban drainage networks for urban pluvial flooding.

Linking a Storm Water Management Model to a Novel Two-Dimensional Model for Urban Pluvial Flood Modeling

This article describes a new method of urban pluvial flood modeling by coupling the 1D storm water management model (SWMM) and the 2D flood inundation model (ECNU Flood-Urban). The SWMM modeling results (the overflow of the manholes) are used as the input boundary condition of the ECNU Flood-Urban model to simulate the rainfall–runoff processes in an urban environment. The analysis is applied to the central business district of East Nanjing Road in downtown Shanghai, considering 5-, 10-, 20-, 50-, and 100-year return period rainfall scenarios. The results show that node overflow, water depth, and inundation area increase proportionately with the growing return periods. Water depths are mostly predicted to be shallow and surface flows generally occur in the urban road network due to its low-lying nature. The simulation result of the coupled model proves to be reliable and suggests that urban surface water flooding could be accurately simulated by using this methodology. Adaptation measures (upgrading of the urban drainage system) can then be targeted at specific locations with significant overflow and flooding.

A 3D dynamic visualization method coupled with an urban drainage model

The urban drainage model is an important tool for the management and decision-making around an urban drainage network. Owing to urban drainage networks’ complex distribution, existing model analysis methods have gradually exposed problems of insufficient utilization of spatial information, weak coupling and analytical capacity of multi-source heterogeneous data, and poor human-computer interaction. By coupling an urban drainage model with 3D GIS technology and 3D visualization technology, this study presents a 3D dynamic visualization method of an urban drainage model (3DDVM-UDM). A case study from Chaohu, China, is used to demonstrate the method. The environmental information and distributions of pipe network objects in 3D space were presented. The urban drainage model can be edited and simulated in the 3D environment, and a 2D flooding simulation method was also established. Multiple model results were dynamically and simultaneously visualized in the pipe network entity models. By coupling and comparing the model results under different rainfall return periods, various information was intuitively analyzed, such as the water level and water quality differences of each pipe and node, and the spatial distribution differences of fully filled pipes, overflowed nodes and buildings influenced by node overflow. The operation state of a drainage pipe network can be systematically analyzed by intuitively combining with the attribute information of a pipe network, 3D spatial information and other relevant data. This study provides a feasible theory and method to assist in environmental management and decision-making, to facilitate communication between different fields, and to promote a shift in analysis from 2D to the combination of 2D and 3D.

Multi-Dimensional Indexes in DBMSs

Multi-dimensional data is present across multimedia, data mining and other data-driven applications. The R-Tree is a popular index structure that DBMSs are implementing as core for efficient retrieval of such data. The gap between the best and worst-case performance is very wide in an R-tree. Thus, building quality R-trees quickly is desirable. Variations differ in how node overflow are approached during the building process. This article studies the R-Tree technique that the open-source PostgreSQL DBMS uses. Focus is on a specific parameter controlling node overflows as an optimisation target, and improved configurations are proposed. This parameter is hard-wired into the DBMS, and therefore, an implementation is presented to allow this parameter to become accessible through an SQL construct. The access method designer can resort to configuring this parameter when trying to meet specific storage or time-related performance targets. With this study, the reader can gain an insight into the effects of changing the parameter by considering the spatial indexes on well-known workloads.

LAZY R-tree: The R-tree with lazy splitting algorithm

The spatial index is a data structure formed according to the position and shape of the spatial object or the relationship between the spatial objects according to certain rules, and the spatial data is managed by an effective spatial data structure. The quality of a spatial index directly affects the performance of spatial queries. The R-tree index structure is a highly efficient spatial index. According to the R-tree query rule, when performing spatial query, most data that is not related to the query condition can be filtered out, and finally, a few leaf nodes can be accessed to query the data satisfying the condition. Its query performance is affected by factors such as non-leaf node overlap and node space utilisation. This article proposes a lazy splitting method to improve the R-tree construction process. The scheme works as follows: (1) When a node overflows, it creates an overflow node for that node and all overflow nodes are saved in a hash table. (2) If the node continues to insert data, the data are added to its overflow node. (3) When an overflow node is saturated, the node and its overflow node are split into two saturated nodes. We use both simulated and actual data to perform experiments. The experimental results show that an R-tree constructed by the lazy algorithm is superior to an R-tree constructed using the original R-tree PM algorithm or the corner-based splitting (CBS) algorithm based on the number of splits created, the node space used and the efficiency of region queries and k-nearest neighbour (kNN) queries.

Linked Block-based Multiversion B-Tree index for PCM-based embedded databases

In this paper, by exploring the application characteristics of cyber-physical systems (CPS) and the performance characteristics of PCM, we propose a new B-tree index structure, called Linked Block-based Multi-Version B-Tree (LBMVBT), for indexing multi-version data in an embedded multi-version database for CPS. In LBMVBT, to reduce the number of writes to PCM in maintaining the index and improve the efficiency in serving version-range queries, we introduce the block-based scheme for indexing in which multiple versions of a data item are grouped into a version block to be indexed by a single entry in the multi-version index. To reduce the index re-organization cost (i.e., number of writes to PCM) due to node overflow and underflow, we add external entries in each index leaf node so that a node re-organization can be done by only updating pointers without copying the index entries of the re-organized leaf nodes to the new node. Analytic studies have been performed on LBMVBT and a series of experiments has been conducted to evaluate the efficacy of LBMVBT. The experimental results show that LBMVBT can effectively reduce the number of writes to the index and achieve a good overall performance on serving update transactions while version-range queries can be served with smaller number of reads to the index compared with MVBT.

Array-based Cache Conscious Trees

Making effective use of cache can give good performance. In this paper, Array-Based Cache conscious trees (ABC trees for short) are proposed for realizing good performance of not only search operation but also update operation. The logical structure and manipulation of an ABC tree are similar to those of a B+-tree. The initial space of an array for an ABC tree as it is supposed to be a complete tree is allocated. This allows the tree to have contiguous memory space for its core and to reduce the number of pointers in it. As a result, the key capacity of a node increases and we can make effective use of cache. We also present an enhancement of ABC trees, which can increase the capacity of an ABC tree with overflow nodes. We describe how we can decide whether to create an overflow node when a node overflows for performance. Some experimental studies show that ABC trees can give good performance of operations under certain conditions.

Fast indexing and visualization of metric data sets using slim-trees

Many recent database applications need to deal with similarity queries. For such applications, it is important to measure the similarity between two objects using the distance between them. Focusing on this problem, this paper proposes the slim-tree, a new dynamic tree for organizing metric data sets in pages of fixed size. The slim-tree uses the triangle inequality to prune the distance calculations that are needed to answer similarity queries over objects in metric spaces. The proposed insertion algorithm uses new policies to select the nodes where incoming objects are stored. When a node overflows, the slim-tree uses a minimal spanning tree to help with the splitting. The new insertion algorithm leads to a tree with high storage utilization and improved query performance. The slim-tree is a metric access method that tackles the problem of overlaps between nodes in metric spaces and that allows one to minimize the overlap. The proposed is a way to quantify whether a given tree can be improved and also to compare two trees. We show how to use the fat-factor to achieve accurate estimates of the search performance and also how to improve the performance of a metric tree through the proposed algorithm. This paper also presents a new tool in the slim-tree's arsenal of resources, aimed at visualizing it. Visualization is a powerful tool for interactive data mining and for the visual tracking of the behavior of a tree under updates. Finally, we present a formula to estimate the number of disk accesses in range queries. Results from experiments with real and synthetic data sets show that the new slim-tree algorithms lead to performance improvements. These results show that the slim-tree outperforms the M-tree by up to 200% for range queries. For insertion and splitting, the minimal-spanning-tree-based algorithm achieves up to 40 times faster insertions. We observed improvements of up to 40% in range queries after applying the slim-down algorithm.

On Numerical Solution of the Markov Renewal Equation: Tight Upper and Lower Kernel Bounds

We develop tight bounds and a fast parallel algorithm to compute the Markov renewal kernel. Knowledge of the kernel allows us to solve Markov renewal equations numerically to study non-steady state behavior in a finite state Markov renewal process. Computational error and numerical stability for computing the bounds in parallel are discussed using well-known results from numerical analysis. We use our algorithm and computed bounds to study the expected number of departures as a function of time for a two node overflow queueing network.