基于用户浏览行为相似度的HTTP-Get Flood检测

针对日益泛滥的HTTP-Get Flood攻击,提出了利用用户浏览行为相似性界定HTTP-Get Flood攻击。详细阐述了用户浏览行为相似性的表述方法和检测算法的结构,通过下载公开的Trace对检测算法进行仿真及验证,结果表明,本算法能准确地检测出各种类型的HTTP-Get Flood攻击,很好地揭示攻击行为爆发的时间段,在HTTP-Get Flood攻击检测中有良好的应用。

基于SWMM和LISFLOOD-FP的城市内涝耦合模型研究

以柳州市箭盘山流域为例,构建SWMM一维管道模型与LISFLOOD-FP二维地面模型并将其耦合,基于实测降雨“20180818”24 h暴雨资料,将得到的暴雨内涝淹没水深和淹没面积与该场次降雨情况下记录淹没点的范围相比较,验证耦合模型具有较好的适用性。进而基于耦合模型,对柳州市箭盘山流域2、5、10、20年一遇下设计降雨进行模拟,得到不同重现期下研究区的溢流节点、淹没水深和淹没面积,并于ARCGIS平台将结果可视化。结果表明,重现期由2年上升到20年过程中,溢流节点比例从9.03%增加至25.99%,溢流面积从0.473 km^(2)增加至2.114 km^(2);重点淹没区域分布在屏山大道、炮团路、西江路和东堤路。

Flood Velocity Prediction Using Deep Learning Approach

Floods are one of the most serious natural disasters that can cause huge societal and economic losses.Extensive research has been conducted on topics like flood monitoring,prediction,and loss estimation.In these research fields,flood velocity plays a crucial role and is an important factor that influences the reliability of the outcomes.Traditional methods rely on physical models for flood simulation and prediction and could generate accurate results but often take a long time.Deep learning technology has recently shown significant potential in the same field,especially in terms of efficiency,helping to overcome the time-consuming associated with traditional methods.This study explores the potential of deep learning models in predicting flood velocity.More specifically,we use a Multi-Layer Perceptron(MLP)model,a specific type of Artificial Neural Networks(ANNs),to predict the velocity in the test area of the Lundesokna River in Norway with diverse terrain conditions.Geographic data and flood velocity simulated based on the physical hydraulic model are used in the study for the pre-training,optimization,and testing of the MLP model.Our experiment indicates that the MLP model has the potential to predict flood velocity in diverse terrain conditions of the river with acceptable accuracy against simulated velocity results but with a significant decrease in training time and testing time.Meanwhile,we discuss the limitations for the improvement in future work.

Real-time Rescue Target Detection Based on UAV Imagery for Flood Emergency Response

Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.

Spatial diversion and coordination of flood water for an urban flood control project in Suzhou, China

Suzhou City,located in the Yangtze River Delta in China,is prone to flooding due to a complex combination of natural factors,including its monsoon climate,low elevation,and tidally influenced position,as well as intensive human activities.The Large Encirclement Flood Control Project(LEFCP)was launched to cope with serious floods in the urban area.This project changed the spatiotemporal pattern of flood processes and caused spatial diversion of floods from the urban area to the outskirts of the city.Therefore,this study developed a distributed flood simulation model in order to understand this transition of flood processes.The results revealed that the LEFCP effectively protected the urban areas from floods,but the present scheduling schemes resulted in the spatial diversion of floods to the outskirts of the city.With rainstorm frequencies of 10.0%to 0.5%,the water level differences between two representative water level stations(Miduqiao(MDQ)and Fengqiao(FQ))located inside and outside the LEFCP area,ranged from 0.75 m to 0.24 m and from 1.80 m to 1.58 m,respectively.In addition,the flood safety margin at MDQ and the duration with the water level exceeding the warning water level at FQ ranged from 0.95 m to 0.43 m and from 4 h to 22 h,respectively.Rational scheduling schemes for the hydraulic facilities of the LEFCP in extreme precipitation cases were developed ac-cording to food simulations under seven scheduling scenarios.This helps to regulate the spatial flood diversion caused by the LEFCP during extreme precipitation.

Climate change drives flooding risk increases in the Yellow River Basin

The Yellow River Basin(YRB)has experienced severe floods and continuous riverbed elevation throughout history.Global climate change has been suggested to be driving a worldwide increase in flooding risk.However,owing to insufficient evidence,the quantitative correlation between flooding and climate change remains illdefined.We present a long time series of maximum flood discharge in the YRB dating back to 1843 compiled from historical documents and instrument measurements.Variations in yearly maximum flood discharge show distinct periods:a dramatic decreasing period from 1843 to 1950,and an oscillating gentle decreasing from 1950 to 2021,with the latter period also showing increasing more extreme floods.A Mann-Kendall test analysis suggests that the latter period can be further split into two distinct sub-periods:an oscillating gentle decreasing period from 1950 to 2000,and a clear recent increasing period from 2000 to 2021.We further predict that climate change will cause an ongoing remarkable increase in future flooding risk and an∼44.4 billion US dollars loss of floods in the YRB in 2100.

Experimental study of the effects of a multistage pore-throat structure on the seepage characteristics of sandstones in the Beibuwan Basin:Insights into the flooding mode

To investigate the relationship between grain sizes, seepage capacity, and oil-displacement efficiency in the Liushagang Formation of the Beibuwan Basin, this study identifies the multistage pore-throat structure as a crucial factor through a comparison of oil displacement in microscopic pore-throat experiments. The two-phase flow evaluation method based on the Li-Horne model is utilized to effectively characterize and quantify the seepage characteristics of different reservoirs, closely relating them to the distribution of microscopic pores and throats. It is observed that conglomerate sandstones at different stages exhibit significant heterogeneity and noticeable differences in seepage capacity, highlighting the crucial role played by certain large pore throats in determining seepage capacity and oil displacement efficiency. Furthermore, it was found that the displacement effects of conglomeratic sandstones with strong heterogeneity were inferior to those of conventional homogeneous sandstone, as evidenced by multiple displacement experiments conducted on core samples with varying granularities and flooding systems. Subsequently, core-based experiments on associated gas flooding after water flooding were conducted to address the challenge of achieving satisfactory results in a single displacement mode for reservoirs with significant heterogeneity. The results indicate that the oil recovery rates for associated gas flooding after water flooding increased by 7.3%-16.4% compared with water flooding alone at a gas-oil ratio of approximately 7000 m^(3)/m^(3). Therefore, considering the advantages of gas flooding in terms of seepage capacity, oil exchange ratio, and the potential for two-phase production, gas flooding is recommended as an energy supplement mode for homogeneous reservoirs in the presence of sufficient gas source and appropriate tectonic angle. On the other hand, associated gas flooding after water flooding is suggested to achieve a more favorable development effect compared to a single mode of energy supplementation for strongly heterogeneous sandstone reservoirs.

Experimental investigation into effects of the natural polymer and nanoclay particles on the EOR performance of chemical flooding in carbonate reservoirs

This paper aims to investigate the tragacanth gum potential as a natural polymer combined with natural clay mineral(montmorillonite,kaolinite,and illite)nanoparticles(NPs)to form NP-polymer suspension for enhanced oil recovery(EOR)in carbonate reservoirs.Thermal gravimetric analysis(TGA)tests were conducted initially in order to evaluate the properties of tragacanth gum.Subsequently,scanning electron microscopy(SEM)and energy-dispersive X-ray(EDX)tests were used to detect the structure of clay particles.In various scenarios,the effects of natural NPs and polymer on the wettability alteration,interfacial tension(IFT)reduction,viscosity improvement,and oil recovery were investigated through contact angle system,ring method,Anton Paar viscometer,and core flooding tests,respectively.The entire experiment was conducted at 25,50,and 75℃,respectively.According to the experimental results,the clay minerals alone did not have a significant effect on viscosity,but the addition of minerals to the polymer solution leads to the viscosity enhancement remarkably,resulting mobility ratio improvement.Among clay NPs,the combination of natural polymer and kaolinite results in increased viscosity at all temperatures.Considerable wettability alteration was also observed in the case of natural polymer and illite NPs.Illite in combination with natural polymer showed an ability in reducing IFT.Finally,the results of displacement experiments revealed that the combination of natural polymer and kaolinite could be the best option for EOR due to its substantial ability to improve the recovery factor.

Pressure transient characteristics of non-uniform conductivity fractured wells in viscoelasticity polymer flooding based on oil-water two-phase flow

Polymer flooding in fractured wells has been extensively applied in oilfields to enhance oil recovery.In contrast to water,polymer solution exhibits non-Newtonian and nonlinear behavior such as effects of shear thinning and shear thickening,polymer convection,diffusion,adsorption retention,inaccessible pore volume and reduced effective permeability.Meanwhile,the flux density and fracture conductivity along the hydraulic fracture are generally non-uniform due to the effects of pressure distribution,formation damage,and proppant breakage.In this paper,we present an oil-water two-phase flow model that captures these complex non-Newtonian and nonlinear behavior,and non-uniform fracture characteristics in fractured polymer flooding.The hydraulic fracture is firstly divided into two parts:high-conductivity fracture near the wellbore and low-conductivity fracture in the far-wellbore section.A hybrid grid system,including perpendicular bisection(PEBI)and Cartesian grid,is applied to discrete the partial differential flow equations,and the local grid refinement method is applied in the near-wellbore region to accurately calculate the pressure distribution and shear rate of polymer solution.The combination of polymer behavior characterizations and numerical flow simulations are applied,resulting in the calculation for the distribution of water saturation,polymer concentration and reservoir pressure.Compared with the polymer flooding well with uniform fracture conductivity,this non-uniform fracture conductivity model exhibits the larger pressure difference,and the shorter bilinear flow period due to the decrease of fracture flow ability in the far-wellbore section.The field case of the fall-off test demonstrates that the proposed method characterizes fracture characteristics more accurately,and yields fracture half-lengths that better match engineering reality,enabling a quantitative segmented characterization of the near-wellbore section with high fracture conductivity and the far-wellbore section with low fracture conductivity.The novelty of this paper is the analysis of pressure performances caused by the fracture dynamics and polymer rheology,as well as an analysis method that derives formation and fracture parameters based on the pressure and its derivative curves.

Response Mechanisms to Flooding Stress in Mulberry Revealed by Multi-Omics Analysis

Abiotic stress,including flooding,seriously affects the normal growth and development of plants.Mulberry(Morus alba),a species known for its flood resistance,is cultivated worldwide for economic purposes.The transcriptomic analysis has identified numerous differentially expressed genes(DEGs)involved in submergence tolerance in mulberry plants.However,a comprehensive analyses of metabolite types and changes under flooding stress in mulberry remain unreported.A non-targeted metabolomic analysis utilizing liquid chromatographytandem mass spectrometry(LC-MS/MS)was conducted to further investigate the effects of flooding stress on mulberry.A total of 1,169 metabolites were identified,with 331 differentially accumulated metabolites(DAMs)exhibiting up-regulation in response to flooding stress and 314 displaying down-regulation.Pathway enrichment analysis identified significant modifications in many metabolic pathways due to flooding stress,including amino acid biosynthesis and metabolism and flavonoid biosynthesis.DAMs and DEGs are significantly enriched in the Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways for amino acid,phenylpropanoid and flavonoid synthesis.Furthermore,metabolites such as methyl jasmonate,sucrose,and D-mannose 6-phosphate accumulated in mulberry leaves post-flooding stress.Therefore,genes and metabolites associated with these KEGG pathways are likely to exert a significant influence on mulberry flood tolerance.This study makes a substantial contribution to the comprehension of the underlying mechanisms implicated in the adaptation of mulberry plants to submergence.

Flood Risk Assessment in the Lower Valley of Ouémé, Benin

In response to the increased frequency of flood events in recent years, it has become crucial to enhance preparedness and anticipation through precise flood risk assessments. To this end, this study aims to produce updated and precise flood risk maps for the Lower Valley of Ouémé River Basin, located in the South of Benin. The methodology used consisted of a combination of geographical information systems (GIS) and multi-criteria analysis, including Analytical Hierarchy Process (AHP) methods to define and quantify criteria for flood risk assessment. Seven hydro-geomorphological indicators (elevation, rainfall, slope, distance from rivers, flow accumulation, soil type, and drainage density), four socio-economic vulnerability indicators (female population density, literacy rate, poverty index, and road network density), and two exposure indicators (population density and land use) were integrated to generate risk maps. The results indicate that approximately 21.5% of the Lower Valley is under high and very high flood risk, mainly in the south between Dangbo, So-Ava, and Aguégués. The study findings align with the historical flood pattern in the region, which confirms the suitability of the used method. The novelty of this work lies in its comprehensive approach, the incorporation of AHP for weighting factors, and the use of remote sensing data, GIS technology, and spatial analysis techniques which adds precision to the mapping process. This work advances the scientific understanding of flood risk assessment and offers practical insights and solutions for flood-prone regions. The detailed flood risk indicator maps obtained stand out from previous studies and provide valuable information for effective flood risk management and mitigation efforts in the Lower Valley of Ouémé.

Optimization of Gas-Flooding Fracturing Development in Ultra-Low Permeability Reservoirs

Ultra-low permeability reservoirs are characterized by small pore throats and poor physical properties, which areat the root of well-known problems related to injection and production. In this study, a gas injection floodingapproach is analyzed in the framework of numerical simulations. In particular, the sequence and timing of fracturechanneling and the related impact on production are considered for horizontal wells with different fracturemorphologies. Useful data and information are provided about the regulation of gas channeling and possible strategiesto delay gas channeling and optimize the gas injection volume and fracture parameters. It is shown that inorder to mitigate gas channeling and ensure high production, fracture length on the sides can be controlled andlonger fractures can be created in the middle by which full gas flooding is obtained at the fracture location in themiddle of the horizontal well. A Differential Evolution (DE) algorithm is provided by which the gas injectionvolume and the fracture parameters of gas injection flooding can be optimized. It is shown that an improvedoil recovery factor as high as 6% can be obtained.

Development of a Web-Based GIS of Flood Zones in the Municipality of Ouagadougou in Burkina Faso

This document describes the creation of an informative Web GIS aimed at mitigating the impacts of flooding in the municipality of Ouagadougou, in Burkina Faso, a region that is highly sensitive to climate change. Burkina Faso, which is undergoing rapid urbanization, faces major natural threats, particularly flooding, as demonstrated by the severe floods of 2009 that caused loss of life, injury, structural damage and economic losses in Ouagadougou. The aim of this research is to develop a web map highlighting the municipality’s flood-prone areas, with a view to informing and raising awareness of flood risk reduction. Using the Leaflet JavaScript mapping library, the study uses HTML, CSS and JavaScript to implement web mapping technology. Data on Ouagadougou’s flood zones is generated by a multi-criteria analysis combining Saaty’s AHP method and GIS in QGIS, integrating seven (7) parameters including hydrography, altitude, slope, rainfall, soil types, land use and soil moisture index. QGIS processes and maps the themes, PostgreSQL with PostGIS serves as the DBMS and GeoServer functions as the map server. The Web GIS platform allows users to visualize the different flood risks, from very low to very high, or the high-risk areas specific to Ouagadougou. The AHP calculations classify the municipality into five flood vulnerability zones: very low (24.48%), low (27.93%), medium (23.01%), high (17.11%) and very high (7.47%). Effective risk management requires communication and awareness-raising. This online mapping application serves as a tool for communication, management and flood prevention in Ouagadougou, helping to mitigate flood-related natural disasters.

Displacement characteristics of CO_(2)flooding in extra-high water-cut reservoirs

Carbon dioxide(CO_(2))flooding is a widely applied recovery method during the tertiary recovery of oil and gas.A high water saturation condition in reservoirs could induce a‘water shielding’phenomenon after the injection of CO_(2).This would prevent contact between the injected gas and the residual oil,restricting the development of the miscible zone.A micro-visual experiment of dead-end models,used to observe the effect of a film of water on the miscibility process,indicates that CO_(2)can penetrate the water film and come into contact with the residual oil,although the mixing is significantly delayed.However,the dissolution loss of CO_(2)at high water-cut conditions is not negligible.The oil-water partition coefficient,defined as the ratio of CO_(2)solubility in an oil-brine/two-phase system,keeps constant for specific reservoir conditions and changes little with an injection gas.The NMR device shows that when CO_(2)flooding follows water flooding,the residual oil decreasesdnot only in medium and large pores but also in small and micro pores.At levels of higher water saturation,CO_(2)displacement is characterized initially by a low oil production rate and high water-cut.After the CO_(2)breakthrough,the water-cut decreases sharply and the oil production rate increases gradually.The response time of CO_(2)flooding at high watercut reservoirs is typically delayed and prolonged.These results were confirmed in a pilot test for CO_(2)flooding at the P1-1 well group of the Pucheng Oilfield.Observations from this pilot study also suggest that a larger injection gas pore volume available for CO_(2)injection is required to offset the dissolution loss in high water saturation conditions.

Effects of unilateral superimposed high-frequency jet ventilation on porcine hemodynamics and gas exchange during one-lung flooding

BACKGROUND Superimposed high-frequency jet ventilation(SHFJV)is suitable for respiratory motion reduction and essential for effective lung tumor ablation.Fluid filling of the target lung wing one-lung flooding(OLF)is necessary for therapeutic ultrasound applications.However,whether unilateral SHFJV allows adequate hemodynamics and gas exchange is unclear.AIM To compared SHFJV with pressure-controlled ventilation(PCV)during OLF by assessing hemodynamics and gas exchange in different animal positions.METHODS SHFJV or PCV was used alternatingly to ventilate the non-flooded lungs of the 12 anesthetized pigs during OLF.The animal positions were changed from left lateral position to supine position(SP)to right lateral position(RLP)every 30 min.In each position,ventilation was maintained for 15 min in both modalities.Hemodynamic variables and arterial blood gas levels were repeatedly measured.RESULTS Unilateral SHFJV led to lower carbon dioxide removal than PCV without abnormally elevated carbon dioxide levels.SHFJV slightly decreased oxygenation in SP and RLP compared with PCV;the lowest values of PaO_(2) and PaO_(2)/FiO_(2) ratio were found in SP[13.0;interquartile range(IQR):12.6-5.6 and 32.5(IQR:31.5-38.9)kPa].Conversely,during SHFJV,the shunt fraction was higher in all animal positions(highest in the RLP:0.30).CONCLUSION In porcine model,unilateral SHFJV may provide adequate ventilation in different animal positions during OLF.Lower oxygenation and CO_(2) removal rates compared to PCV did not lead to hypoxia or hypercapnia.SHFJV can be safely used for lung tumor ablation to minimize ventilation-induced lung motion.

Screening and field application of microbial-flooding activator systems

This study aims to further enhance the oil recovery of reservoirs in the Zhong-2 Block of the Gudao Oilfield by identifying the most effective microbial-flooding activator systems and applying them in the field.We began by analyzing the structure of the reservoirs'endogenous microbial communities to understand the potential impact of microbial flooding.This was followed by determining commonly used activator systems based on their abilities to stimulate oil-displacement functional bacteria.Through laboratory experiments on oil displacement efficiency and sweep characteristics,we determined the optimal activator injection method(injection ratio)and the requisite bacterial concentration for maximal microbial-flooding efficacy.Finally,we selected the optimal activator systems and applied them to field tests.Our findings suggest the target block is highly receptive to microbial-flooding.In terms of performance,the activator systems ranked as No.3>No.4>No.1>No.2.Interestingly,a deep activator system,when compared to the top-performing No.3 system,exhibited a higher bacterial concentration peak and longer peaking duration.Optimal oil displacement effects were observed at a 1:4 vol ratio between the No.3 activator and deep activator systems,with bacterial concentrations of up to 106 cells/mL or above.Field tests with the selected activator systems,following a specific injection protocol,demonstrated a notable increase in oil production and a reduction in water cut.

Application of Machine Learning for Flood Prediction and Evaluation in Southern Nigeria

This study explored the application of machine learning techniques for flood prediction and analysis in southern Nigeria. Machine learning is an artificial intelligence technique that uses computer-based instructions to analyze and transform data into useful information to enable systems to make predictions. Traditional methods of flood prediction and analysis often fall short of providing accurate and timely information for effective disaster management. More so, numerical forecasting of flood disasters in the 19th century is not very accurate due to its inability to simplify complex atmospheric dynamics into simple equations. Here, we used Machine learning (ML) techniques including Random Forest (RF), Logistic Regression (LR), Naïve Bayes (NB), Support Vector Machine (SVM), and Neural Networks (NN) to model the complex physical processes that cause floods. The dataset contains 59 cases with the goal feature “Event-Type”, including 39 cases of floods and 20 cases of flood/rainstorms. Based on comparison of assessment metrics from models created using historical records, the result shows that NB performed better than all other techniques, followed by RF. The developed model can be used to predict the frequency of flood incidents. The majority of flood scenarios demonstrate that the event poses a significant risk to people’s lives. Therefore, each of the emergency response elements requires adequate knowledge of the flood incidences, continuous early warning service and accurate prediction model. This study can expand knowledge and research on flood predictive modeling in vulnerable areas to inform effective and sustainable contingency planning, policy, and management actions on flood disaster incidents, especially in other technologically underdeveloped settings.

Effect of CO_(2)flooding in an oil reservoir with strong bottom-water drive in the Tahe Oilfield,Tarim Basin,Northwest China

The dissolution and diffusion of CO_(2)in oil and water and its displacement mechanism were investigated by laboratory experiment and numerical simulation for Block 9 in the Tahe oilfield,a sandstone oil reservoir with strong bottom-water drive in Tarim Basin,Northwest China.Such parameters were analyzed as solubility ratio of CO_(2)in oil,gas and water,interfacial tension,in-situ oil viscosity distribution,remaining oil saturation distribution,and oil compositions.The results show that CO_(2)flooding could control water coning and increase oil production.In the early stage of the injection process,CO_(2)expanded vertically due to gravity differentiation,and extended laterally under the action of strong bottom water in the intermediate and late stages.The CO_(2)got enriched and extended at the oil-water interface,forming a high interfacial tension zone,which inhibited the coning of bottom water to some extent.A miscible region with low interfacial tension formed at the gas injection front,which reduced the in-situ oil viscosity by about 50%.The numerical simulation results show that enhanced oil recovery(EOR)is estimated at 5.72%and the oil exchange ratio of CO_(2)is 0.17 t/t.

基于LisFlood-SWMM耦合模型的城市停车场所积水风险评估

全球变暖气候变化导致特大暴雨频发,城市化水平提高下建成区面积不断增加,由此引发的洪涝灾害风险居高不下,城市内涝发生时市内车辆泡水现象频发。本文以深圳市福田区城市停车场为研究对象,利用POI(兴趣点)数据爬取方法构建了深圳市福田区的停车场数据库,根据LisFlood-SWMM模型模拟了不同降雨情景下的淹没情况。以此为基础,划分了内涝造成的积水风险等级,得到了不同降雨情景下城市停车场所积水风险评估,并提出了风险防范措施建议,对我国城市停车场积水风险评估具有一定参考意义。

基于MIKE FLOOD耦合模型的深圳黄沙河片区内涝风险评估和改造分析

为解决城市内涝问题,以深圳市黄沙河片区排水分区为例,基于MIKE FLOOD平台,耦合城市雨水管网、水系及地形地物,建立城市内涝模型,模拟分析研究区2年一遇、10年一遇、50年一遇等不同重现期的排涝情景。结果表明:耦合模型能直观反映受涝区积水深度与积水时间,并随着重现期的增大,溢流点和充满的管道会增多;建立MIKE FLOOD耦合模型,发现黄沙河片区高风险区域面积1.6 km^(2),主要集中在坑塘立交桥、龙岗大道;中风险区域面积3.2 km^(2),主要集中在同富裕工业区、新联北路;低风险区域面积2.8 km^(2),主要集中在坑塘立交桥、坪梓路,并分析易涝点的成因,提出改造建议。