Overflow Nodes Research Articles

Clarifying urban flood response characteristics and improving interpretable flood prediction with sparse data considering the coupling effect of rainfall and drainage pipeline siltation

With climate warming and accelerated urbanisation, severe urban flooding has become a common problem worldwide. Frequent extreme rainfall events and the siltation of drainage pipes further increase the burden on urban drainage networks. However, existing studies have not fully considered the effects of rainfall and pipeline siltation on the response characteristics of flooding when constructing numerical models of urban flooding simulations. To solve this problem, a surface-subsurface coupling model was constructed by combining the Saint-Venant equation, Manning equation, a one-dimensional pipeline model (SWMM), and a two-dimensional surface overflow model (LISFLOOD-FP). Then, the SWMM model considering pipeline siltation and the two-dimensional surface overflow model (LISFLOOD-FP) were coupled with the flow exchange governing equation, and the urban flooding response characteristics considering the coupling effect of “rainfall and drainage pipeline siltation” were analysed. To enhance the solvability of waterlogging prediction, an intelligent prediction model of urban flooding based on Bayes-CNN-BLSTM was established by combining a convolutional neural network (CNN), bidirectional long short-term memory neural network (BLSTM), Bayesian optimisation (Bayes), and an interpretable loss function error correction method. The actual rainfall events and flooding processes recorded by the monitoring equipment at Huizhou University were used to calibrate and verify the model. The results show that in the Rainfall 1 and Rainfall 2 scenarios, the overload rates of the pipelines in the current siltation scenario were 60.06 % and 68.37 %, respectively, and the proportions of overflow nodes were 24.87 % and 25.89 %, respectively. When the drainage network was initially put into operation, the overload rates of the pipeline were 36.67 % and 41.16 %, and the overflow nodes accounted for 3.05 % and 4.06 %, respectively. The inundated area and volume of urban flooding increased when the combined siltation coefficient (CSC) was 0.2; therefore, two desilting schemes were determined. Under Rainfall 1, Rainfall 2, and the four rainfall recurrence periods, the Bayes-CNN-BLSTM model had clear advantages in terms of accuracy, reliability, and robustness.

Simulation and Comprehensive Evaluation of the Multidimensional Environmental Benefits of Sponge Cities

The implementation of grey and green infrastructure is an effective means to address urban flooding and nonpoint source pollution, but due to the complexity of the process and the diversity of benefits, there is a lack of measurement of the comprehensive benefits. Adopting a typical university in Beijing as an example, this paper simulated the multidimensional benefits of the water quantity, water quality, and ecology of grey and green facility renovation by coupling the storm water management model (SWMM) and InfoWorks Integrated Catchment Management (ICM). Monetization methods and economical means were employed to characterize the comprehensive benefits. The results showed that grey and green infrastructure retrofitting reduced the number of severe overflow nodes in the study area by 54.35%, the total overflow volume by 22.17%, and the nonpoint source pollution level by approximately 80% under the heavy rain scenario and 60% under the rainstorm scenario. The annual benefits of grey and green infrastructure renovation reached CNY764,691/year: of this amount, CNY275,726/year was from hydrological regulation, CNY270,895/year was from nonpoint source pollution reduction, and CNY218,070/year was from ecological improvement. The benefits of green facilities were higher than those of grey facilities, and the combined benefits were negatively correlated with the rainfall level, with a total benefit–cost ratio of 1.19. The results provide methodological and data support for grey and green infrastructure retrofitting within the context of sponge cities.

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.

Urban Flood Modeling and Risk Assessment with Limited Observation Data: The Beijing Future Science City of China.

The frequency of urban storms has increased, influenced by the climate changing and urbanization, and the process of urban rainfall runoff has also changed, leading to severe urban waterlogging problems. Against this background, the risk of urban waterlogging was analyzed and assessed accurately, using an urban stormwater model as necessary. Most studies have used urban hydrological models to assess flood risk; however, due to limited flow pipeline data, the calibration and the validation of the models are difficult. This study applied the MIKE URBAN model to build a drainage system model in the Beijing Future Science City of China, where the discharge of pipelines was absent. Three methods, of empirical calibration, formula validation, and validation based on field investigation, were used to calibrate and validate the parameters of the model. After the empirical calibration, the relative error range between the simulated value and the measured value was verified by the formula as within 25%. The simulated runoff depth was consistent with a field survey verified by the method of validation based on field investigation, showing the model has good applicability in the study area. Then, the rainfall scenarios of different return periods were designed and simulated. Simulation results showed that, for the 10-year return period, there are overflow pipe sections in northern and southern regions, and the number of overflow pipe sections in the northern region is more than that in the southern region. For the 20-year return period and 50-year return period, the number of overflow pipe sections and nodes in the northern region increased, while for the 100-year return period, the number of overflow nodes both increased. With the increase in the rainfall return period, the pipe network load increased, the points and sections prone to accumulation and waterlogging increased, and the regional waterlogging risk increased. The southern region is prone to waterlogging because the pipeline network density is higher than that in the northern region and the terrain is low-lying. This study provides a reference for the establishment of rainwater drainage models in regions with similar database limitations and provides a technical reference for the calibration and validation of stormwater models that lack rainfall runoff data.

Study on Waterlogging Reduction Effect of LID Facilities in Collapsible Loess Area Based on Coupled 1D and 2D Hydrodynamic Model

The accurate evaluation method of LID toward the attenuation of urban flood is still a hot issue. This paper focuses on a coupled 1D and 2D hydrodynamic model, investigating the model parameters set in a collapsible loess area, and the changes in the surface runoff, waterlogged area, and drainage network indicators under different rainfall patterns. The results show that the coupled model can effectively simulate the effect of LID facilities under unaltered and retrofitted conditions. It is found that the infiltration parameters in a collapsible loess area are higher than in other eastern cities by calibration and validation. After implementing the LID facilities, the total runoff, peak flood flow, waterlogged area, runoff coefficient, and drainage pressure under different rainfall patterns have all been reduced. With the increases in the rainfall return period, the waterlogging reduction effect of LID facilities would gradually weaken. The rainfall return period has a great impact on the indicators of surface runoff, waterlogged area, and drainage capacity. The coefficient of rainfall peak has a relatively big impact on indicators of pipelines, such as the proportion of overflow nodes, the proportion of fully loaded pipelines, and the average full-load duration. The rainfall duration has a major impact on the total runoff quantity, runoff coefficient, and average full-load duration.

Combined Optimization of LID Patches and the Gray Drainage System to Control Wet Weather Discharge Pollution

Low impact development (LID) has emerged as an effective management to control urban runoff. However, for storm drainage systems located in high-density old urban areas with scarce land resources and fragmented landscapes, there are difficulties in the application of LID layouts. To solve the waterlogging and wet weather discharge pollution (WWDP), based on the spatial distribution of available land resources, runoff path, ponding area, overflow nodes, and sediments in drainages, a spatial optimized layout method of LID patches combined with gray drainages was proposed and applied to a typical storm drainage system in Shanghai, China. Only 22.9% of the ground surface and 14.0% of the roof, which accounted for the study area were reconstructed to LIDs, and the optimal LID patches combined with 0.4 m storage capacity depth (SCD) could prevent discharge below 6.5 mm rainfall. The optimal LID-gray drainages increased the reduction ratios of suspended substances (SSs) in WWDP by 37–74% compared with only LID patches in 9.1–21.8 mm rainfall. The “LID patches-gray system” could effectively control WWDP in old urban areas with high frequencies of moderate and light rain. The proposed methodology can be instructive for the sustainable reconstruction of storm drainages inappropriately connected with sewage.

Comprehensive analysis of waterlogging control and carbon emission reduction for optimal LID layout: a case study in campus.

Nowadays, sponge city reconstruction has become the focus of research because of the increasingly serious urban waterlogging. Carbon emission reduction, waterlogging area reduction, cost, and other indicators were considered to explore the optimal sponge allocation scheme in the study area. The two-dimensional coupled model MIKE FLOOD was established to analyze the causes of waterlogging through numerical simulation. Low-impact development (LID) combination scenarios were set to analyze the control effects of waterlogging water and total runoff. The carbon emission reduction capacity and economic benefit of each scenario were calculated and evaluated. The analytic hierarchy process (AHP) was used to comprehensively evaluate the LID combination scenario and explore the optimal cost-benefit LID configuration scheme. The results show that the campus rainwater pipe network is under overload operation, and the number of overflow nodes accounts for up to 58.1% under the 3a rainfall return periods. After setting up LID measures, the runoff control rate can be increased by 26.15-42.84%, and the waterlogging area where the depth exceeds 15cm can be reduced by 72.87-100%. If the energy conservation and emission reduction benefits and costs are considered at the same time, the layout scenario of 9% bioretention facility + 3% green roof + 3% permeable pavement can achieve the best benefits. The research can provide a reference for planning and reconstruction of sponge campus and residential areas.

Runoff control simulation and comprehensive benefit evaluation of low-impact development strategies in a typical cold climate area

With the acceleration of urbanization, the proportion of surface imperviousness is increasing continuously in cities, resulting in frequent waterlogging disasters. In this context, storm water management, based on the low-impact development (LID) concept, offers an effective measure for the management of urban storm waters. First, the storm water management model (SWMM) was built for a typical cold climate city (Changchun) in China. Next, the two-stage calibrated model was employed to explore the surface runoff and storm sewer control effects of four LID combination plans. Finally, these plans were put through a “cost-benefit” evaluation through an analytic hierarchy process. According to the results, after using four LID plans, the reduction rates of peak runoff exceeded 40% and the problem of overflow load of the storm sewage was significantly mitigated. The infiltration-oriented Plan I proved to be the optimal plan, with the lowest proportions of the overflow nodes and full-load pipe sections in each return period, as well as with maximum overall performance. This study offers technical and conformed methodological support to cold cities for the prevention and control of waterlogging disasters and recycling of rainwater resources.

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.

토사적체를 고려한 우수관망의 신뢰도 분석

In this study, analysis of reliability of sewer network was progressed with the number of overflow nodes and overflow volume simultaneously for urban areas considering sedimentation. Reliability analysis shows that it is possible to quantify the difference in the phenomenon of the destruction of sedimentation in urban sewer system under the same design frequency. It is proposed as one of the indicators evaluated as full reliability for sewer system. To analyze detailed changes in conduit designs in urban sewer networks, tried to reduction of sedimentation in sewer networks using modified pipe slope in Bujeon-dong catchment, Busan. The various sewer designs were applied and then, the most effective improvement of reliability over 10%. Suggested reliability process can produce the quantitative evaluations about sewer systems using the results of the system simulations and use of possible the objective function for the sewer network designed with a relative evaluation.

Read/write-optimized tree indexing for solid-state drives

Flash-memory-based solid-state drives (SSDs) are used widely for secondary storage. To be effective for SSDs, traditional indices have to be redesigned to cope with the special properties of flash memory, such as asymmetric read/write latencies (fast reads and slow writes) and out-of-place updates. Previous flash-optimized indices focus mainly on reducing random writes to SSDs, which is typically accomplished at the expense of a substantial number of extra reads. However, modern SSDs show a narrowing gap between read and write speeds, and read operations on SSDs increasingly affect the overall performance of indices on SSDs. As a consequence, how to optimize SSD-aware indices by reducing both write and read costs is a pertinent and open challenge. We propose a new tree index for SSDs that is able to reduce both writes and extra reads. In particular, we use an update buffer and overflow pages to reduce random writes, and we further exploit Bloom filters to reduce the extra reads to the overflow nodes in the tree. With this mechanism, we construct a read/write-optimized index that is capable of offering better overall performance than previous flash-aware indices. In addition, we present an analysis of the proposed index and show that the read and write costs of the operations on the index can be balanced by only tuning the false-positive rate of the Bloom filters. Our experimental results suggest that our proposal is efficient and represents an improvement over existing methods.

Optimizing R-tree for flash memory

R-tree has been widely used in spatial data management and data analysis to improve the performance of spatial data retrieval. However, the original R-tree is designed for magnetic disks, and has poor performance on flash memory, due to the special features of flash memory such as asymmetric read/write speeds (fast read, slow write) and the erase-before-write feature. Particularly, the original updating mechanism of R-tree usually has to update a few interior nodes when inserting an indexing item into or deleting an item from a leaf node, yielding many slow writes to flash memory. With the wide use of flash memory in many location-based fields, e.g., to store moving trajectories in intelligent transportation systems, how to optimize R-tree for flash memory has become a critical issue. In this paper, we propose a novel spatial index named Flash-Optimized R-tree that is optimized for flash memory. In particular, we propose to defer the node-splitting operations on R-tree by introducing overflow nodes, which results in an unbalanced tree structure. With this mechanism, we can reduce random writes to flash memory and improve the overall performance of R-tree. In addition, we present a new buffering scheme to efficiently cache the updates to the tree, which can further reduce random writes to flash memory. We conduct extensive experiments on real flash-memory storage devices as well as a flash memory simulation platform to evaluate the performance of our proposal, and the results suggest the efficiency of our proposal with respect to different metrics.

Splitting Approach for Overflow Nodes in R-tree via Incremental k-means Clustering Optimization

R-tree is suitable for maintaining dynamic data and spatial query in many areas such as reverse engineering,CAD/CAM and machine vision,while CR-tree is an excellent variant of R-tree. Aiming at the deficiency in clustering result and compute cost for overflow nodes splitting algorithm of CR-tree,an incremental k-means algorithm via principal components analysis(PCA) is proposed,which can search the new cluster center along the first principal component directions in present clusters. Combining with Silhouette indicator,the algorithm is applied to solving the problem of point set clustering,which is converted from the problem of overflow nodes Splittin. Consequently the clustering results nearly global optimal can be obtained quickly. The experimental results show that the R-tree built with the algorithm based on incremental clustering is better than CR-tree and RR*-tree in synthetic performance in aspects such as the efficiency of building R-tree,storage utilization and spatial query.

An Enhanced Safety Algorithm for Network QoS Multicast Routing Optimization

In the traditional QoS multicast network routing algorithm, when the node encounters abnormal traffic network data, the node data overflows. The current protocol is lack of directional guidance for overflow, which causes abnormal data jitter and disorder, the data path planning of traditional Qos protocol blocked and network delay. In order to solve this problem, this paper presents an enhanced safety algorithm for QoS multicast network routing optimization. The constraint relationship between security level of input parameters of network service request and trust level of network service is set, in order to judge and screen the traffic overflow nodes generated by abnormal operation. Then filtered set of network services is used to construct a multi-path network services digraph and converts it into web services selection tree in use of pointing relationship between sub-services. Finally, it sorts the paths and according to the size of Qos path selects the optimal one to carry out through tracing method. Simulation results show the new algorithm has optimum network quality of service and lower complexity. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4245

초과강우에 대한 우수관망 신뢰도 평가 기법

우수관망의 신뢰도에 관한 기존의 연구들 중 우수관망에서의 파괴 현상을 초과 강우 사상들에 대한 월류 발생 현상으로 정의하고 이에 따른 신뢰도 산정 방법인 RSDMM(Reliability of Sewer system using DMM)을 제안한 바가 있다. 이때 RSDMM 산정을 위한 매개변수로는 초과 강우 사상들에 대한 관망 내 월류 발생량 및 발생 지점 개수가 되며, 이때 이 두 가지 요소는 단위와 차원이 다르므로 거리척도방법(Distance Measure Method, DMM)을 이용하여 하나의 정량화된 신뢰도를 산정하였다. 그러나 이러한 연구에서 제안된 우수관망 신뢰도 산정식 및 산정 절차는 적용 대상이 되는 초과강우 사상들의 범위를 명확히 규정짓지 못하고 있다. 즉, 적용되는 초과강우사상에 따라서 월류의 발생 현상이 명확히 차이남에도 불구하고 단순 평균하여 신뢰도를 산정하였다. 따라서 본 연구에서는 우수관망 신뢰도 산정을 위한 적용 대상 초과강우사상의 범위를 명확히 규정지었으며, 또한 빈도별 초과강우사상에 따른 월류 발생량 및 발생 지점 개수에 대한 스케일 조정을 통하여 하나의 정량화된 신뢰도를 산정할 수 있도록 기존의 RSDMM 산정식을 개선하고 산정 절차를 새롭게 수립하였다. One of the researches about the reliability of storm sewer network defined the sewer system failure as the overflow occurrence for the rainfall events and suggested the reliability evaluation method of storm sewer network, RSDMM(Reliability of Sewer system using DMM). In this study, the parameters to estimate the reliability are the overflow volume and the number of the overflow manholes in the storm sewer network. In order to estimate the reliability, this method used the Distance Measure Method (DMM) to estimate the distance between the parameters while the units and dimensions of each parameter are different. But, the frequency boundary of applied rainfall events was not clear although the reliability results can be different when the boundary of rainfall event's frequency is different. That is, the RSDMM is estimated as the average of overflows for each excessive rainfall event although the overflow occurrences are different according to applied rainfall frequencies. Therefore, to solve these problems and improve the RSDMM, in this study, the frequency boundary of applied rainfall events was defined clearly and the scale control between the number of overflow nodes and overflow volume was organized. Then, the reliability of sewer network is estimated as the quantitative evaluation and this new suggested method improved the RSDMM of Lee's study.

PROMETHEE를 이용한 도시 하수관거시스템 침수위험순위 평가

In this study, Entropy method and PROMETHEE(Preference Ranking organization METHod for Enrichment Evaluations) which is one of the multi criteria decision making methods are applied to estimate the relative inundation risk ranking of the urban sewer systems. Then, the evaluation factors were selected considering two main items to estimate the inundation risk using Entropy and PROMETHEE. In the first item considering topographical and environmental factor, average elevation, average slope, width of area, population, density of conduit were selected as the detailed factors of first item which have influence of the overflow occurrence and damage scale in urban sewer system. And, the relative reliability of sewer network was considered as the second item which can quantify the inundation appearance. Then, the reliability is estimated considering the number of overflow nodes and overflow volume simultaneously. Therefore, the suggested inundation risk evaluation method can be used as the evaluation index for sewer networks and contribute to decision making for the sewer rehabilitation policy.

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.