Return Period Research Articles

<em>Mimesis</em> und <em>Methexis:</em> Skizze einer Poetik der Teilhabe für die Gegenwart

The paper draws on the history of the concept of participation (methexis) in its conflictual relation to imitation or representation (mimesis) for a deepened understanding of identity-related questions in contemporary literature. Plato subjected mimesis to rigorous critique in favor of participation in 'ideas'. In contrast, the history of poetics since Aristotle develops along the valorization of mimesis, while participation here was not understood as an aesthetic category at all. In a synoptic overview, the first part of the paper argues, that mimesis and methexis can only be understood in their dialectic relationship as modern literature has witnessed a periodic return of the problem of participation in poetics. Against the background of this dialectic, the specific profile of contemporary literature and its treatment of questions related to identity becomes visible. The second part of the paper shows this with regard to Olivia Wenzel's novel 1000 serpentinen angst (2020) and Kim de l'Horizon's Blutbuch (2020), that articulate two very different poetic traditions of methexis.

Cold Region River Flood Mapping and Scour Potential Prediction: Insights from Hydraulic Model Using Advanced Autonomous Surface Vehicles

This study aimed to map the 2022 flood with a 16.5-year return period near a bridge on the Red River, close to Grafton City, North Dakota, and evaluate the scour potential around the bridge. The Red River Basin (RRB) near Grand Forks, ND, and Emerson, ND, is a cold region river vulnerable to floods. Local scouring around bridge piers during floods can lead to hydraulic structure failure. An Autonomous Surface Vehicle (ASV) equipped with LiDAR DEM data from the ND DWR’s LiDAR dataset was used to collect comprehensive bathymetry and discharge data, including the 2022 flood. The HEC-RAS model was used to create flood maps, and the Colorado State University (CSU) methodology was employed to assess local scour around the bridge pier. The study area recorded maximum velocities of 1.71 m/s, 1.87 m/s, and 1.56 m/s for discharge values of 368 m3/s, 784 m3/s, and 1335 m3/s, respectively, with higher velocities recorded upstream of the bridge. The maximum water depth reached 13.14 m during the peak discharge of 1335 m3/s. Higher discharge resulted in increased Froude number and contraction scour depth, with the latter continuing to increase even when the Froude number decreased as water reached the bridge deck. The study highlights the effectiveness of integrating ASVs, bathymetry, and LiDAR data to comprehensively understand flood dynamics and bridge scour in cold region rivers, offering the way for the development of effective flood control measures and strategies to safeguard critical infrastructure.

Floodplain Zoning and Mapping for Lower Kelani River, Sri Lanka

Flood risk mapping and floodplain zoning are emerging as practical tools to reduce flood damage. The study intended to develop floodplain zoning maps in the lower Kelani River basin using Flood frequency analysis and MIKE 11 modeling. Flood quantiles estimated for River gauging station at Hanwella and Lower Kelani basin have been used for the flood map developments. The river gauge at Hanwella to the estuary River strip has been considered for floodplain zoning using MIKE 11 modeling software. The hydrologic modeling was performed using MIKE 11 Nedbor Afstromnings Model (NAM), while the hydraulic modeling was performed using MIKE 11 Hydro-Dynamic (HD) model. MIKE 11 rainfall-runoff (RR) NAM calibration and validation Nash-Sutcliffe efficiency (NSE) results were 0.766 and 0.607, respectively. Similarly, coupled NAM and HD model on Mike-Zero platform calibration and validation NSE results were 0.917 and 0.871, respectively. The return period floods estimated to the Hanwella River gauge and Lower Kelani River basin have been availed to generate flood inundation maps. Finally, the flood plain zoning maps have been developed for the Lower Kelani River for 10-, 25-, and 50-year return periods. These maps can be use to limit cultivations and reduce crop losses during monsoons.

Probabilistic Cascade Modeling for Enhanced Flood and Landslide Hazard Assessment: Integrating Multi-Model Approaches in the La Liboriana River Basin

Extreme rainfall events in Andean basins frequently trigger landslides, obstructing river channels and causing flash flows, loss of lives, and economic damage. This study focused on improving the modeling of these events to enhance risk management, specifically in the La Liboriana basin in Salgar (Colombia). A cascading modeling methodology was developed, integrating the spatially distributed rainfall intensities, hazard zoning with the SLIDE model, propagation modeling with RAMMS using calibrated soil rheological parameters, the distributed hydrological model TETIS, and flood mapping with IBER. Return periods of 2.33, 5, 10, 25, 50, and 100 years were defined and applied throughout the methodology. A specific extreme event (18 May 2015) was modeled for calibration and comparison. The spatial rainfall intensities indicated maximum concentrations in the northwestern upper basin and southeastern lower basin. Six landslide hazard maps were generated, predicting landslide-prone areas with a slightly above random prediction rate for the 2015 event. The RAMMS debris flow modeling involved 30 simulations, indicating significant deposition within the river channel and modifying the terrain. Hydraulic modeling with the IBER model revealed water heights ranging from 0.23 to 7 m and velocities from 0.34 m/s to 6.98 m/s, with urban areas showing higher values, indicating increased erosion and infrastructure damage potential.

Introducing a climate, demographics, and infrastructure multi-module workflow for projected flood risk mapping in the greater Pamba River Basin, Kerala, India

Enhanced understanding of extreme events is essential for comprehensive risk assessment promoting informed decision-making and early warning to ensure the resilience against challenges imposed by changing climate. This study proposes a novel multi-module integration framework for the comprehensive evaluation of future flood risk in the Greater Pamba River basin, Kerala, India. The integrative modelling framework is developed by assembling a Cellular Automata-Markov Chain (CAMC) based and Use/Land Cover (LULC) projections, Reliability Ensemble Averaging (REA) of Global Climate Model (GCM) rainfall projections, Bayesian approach-based population projection, and spatial analysis of projected infrastructure and Digital Elevation Models (DEMs). By seamlessly interweaving the associated datasets, we illustrate the intricacies of flood vulnerability, exposure, and frequency across multiple return periods (2, 5, 10, and 100, 200 and 500 year) leading to the creation of diagnostic and prognostic high-resolution flood risk maps. The resultant flood analytics and analyses shown that around 36 % of the villages/municipalities and between 70 and 80 % of the critical facilities like schools, hospitals, and flood relief camps are falling under high-risk zones, for the 100-year return period flood. This finding is in line with Kerala's devastating flood episode in 2018, which exhibited characteristics of a nearly 100-year return period flood. In light of a changing climate, population growth, and shifting landscapes, these approaches provide a roadmap for more informed decision-making and adaptive flood risk management measures.

Impacts of River Network Connectivity on Flood Signatures and Severity Regulated by Flood Control Projects

The operation of hydraulic projects within plain river networks to mitigate floods can alter river network connectivity patterns, subsequently affecting flood processes. This study employed the MIKE 11 model to simulate flood processes under three different river network connectivity scenarios. Based on the simulations, we propose a method to evaluate flood intensity severity by integrating three flood characteristic indices: Slope of the Flow Duration Curve (SFDC), Rising Climb Index (RCI), and Flashiness Index (FI). These indices assess the overall magnitude of change, the rate of rise, and process fluctuations, respectively. Results indicate that changes in river network connectivity significantly impact RCI and SFDC, more than FI. Compared to the natural river network connectivity mode, changes in urban or watershed river network connectivity resulted in a significant decrease in RCI values by 3–37% or 18–38% across various return periods, with the rate of change in RCI values increasing as the return period lengthened. The impact of urban river network connectivity changes on SFDC within the Changzhou urban area was more pronounced under high-magnitude storm conditions, causing a 61% reduction. Furthermore, changes in watershed river network connectivity had a larger effect on SFDC under low-magnitude storm conditions than under high-intensity storms. Over 80% of the rivers under natural connectivity conditions exhibited flood intensity severity of Level III or higher, particularly in the Chenshu–Qingyang area. The alterations in connectivity significantly decreased flood intensity severity, with 85% to 91% of rivers showing the lowest flood intensity severity of Level I. Under a 100-year rainstorm scenario, flood risk shifted from within the flood protection envelope to outside it in the Changzhou urban area. The results will provide an important scientific basis for regional flood management in plains with dense rivers.

Time‐varying copula‐based compound flood risk assessment of extreme rainfall and high water level under a non‐stationary environment

AbstractQuantifying flood risk depends on accurate probability estimation, which is challenging due to non‐stationarity and the combined effects of multiple factors in a changing environment. The threat of compound flood risks may spread from coastal areas to inland basins, which have received less attention. In this study, a framework based on time‐varying copulas was introduced for the treatment of compound flood risk and bivariate design in non‐stationary environments. Archimedean copulas were developed to diagnose the non‐stationary trends of flood risk. Return periods, average annual reliabilities, and bivariate designs were estimated. Model uncertainty was analyzed by comparing the results for stationary and non‐stationary conditions. The case study investigated the extreme rainfall and water level series from the Qinhuai River Basin and the Yangtze River in China. The results showed that marginal distributions and correlations are non‐stationary in all bivariate combinations. Ignoring composite effects may lead to inappropriate quantification of flood risk. Excluding non‐stationarity may lead to risk over or underestimation. It showed the limitations of the 1‐day scale and quantified the uncertainty of non‐stationary models. This study provided a flood risk assessment framework in a changing environment and a risk‐based design technique, which is essential for climate change adaptation and water management.

Post-glacial stratigraphy and late Holocene record of great Cascadia earthquakes in Ozette Lake, Washington, USA

Ozette Lake is an ~100-m-deep coastal lake located along the outer coast of the Olympic Peninsula (Washington, USA); it is situated above the locked portion of the northern Cascadia megathrust but also relatively isolated from active crustal faults and intraslab earthquakes. Here we present a suite of geophysical and geological evidence for earthquake-triggered mass transport deposits (MTDs) and related turbidite deposition in Ozette Lake since ca. 14 ka. Comprehensive high-resolution bathymetry data, seismic reflection profiles, and sediment cores are used to characterize the post-glacial stratigraphic framework and examine paleoseismic evidence in the lacustrine sediments. Stacked sequences of MTDs along the steep eastern flanks of the lake appear to grade basin-ward from thick, chaotic, blocky masses to thin, parallel-bedded turbidite beds. The discrete turbidite event layers are separated by fine-grained (silt and clay) lake sedimentation. The event layers are observed throughout the lake, but the physical characteristics of the deposits vary considerably depending on proximity to primary depocenters, steep slopes, and subaqueous deltas. A total of 30–34 event deposits are observed in the post-glacial record. Radiometric dating was used to reconstruct a detailed sedimentation history over the last ~5.5 k.y., develop an age model, and estimate the recurrence (365–405 yr) for the most recent 12 event layers. Based on sedimentological characteristics, temporal overlap with other regional paleoseismic chronologies, and recurrence estimates, at least 10 of the dated event layers appear to be sourced from slope failures triggered by intense shaking during megathrust ruptures; the recurrence interval for these 10 events is 440–560 yr. Thus, Ozette Lake contains one of the longest and most robust geological records of repeated shaking along the northern Cascadia subduction zone.

The return period and probabilities of earthquakes occurrence in North-East, India (Eastern-Himalayas) and its vicinity inferred from Gutenberg–Richter relation

The return period and probabilities of earthquakes occurrence in North-East, India (Eastern-Himalayas) and its vicinity inferred from Gutenberg–Richter relation

ANALYZING THE RESPONSES OF DEFENSE SECTOR STOCKS TO INTERIM UNION BUDGET ANNOUNCEMENT 2024: AN EVENT STUDY

The interim union budget, the government's primary economic policy document, outlines the intended use of public funds to achieve policy objectives. Industries look forward to it as it can lead to significant changes, and stock markets also react to budget releases to some extent. The paper examines how the NSE's Defense Stocks are affected by the Interim Union Budget. The data was accumulated between 2023 and 2024 from the authorized NSE website. The impact is measured in terms of daily average returns in the pre-and post-budget periods of the top five contributors to the Nifty India Defense index. The statistical tools used include regression analysis and a one-sample t-test. The study found that the impact on defense sector stocks was attributed to factors other than budget announcements. This paper suggests that investors should not consider budget announcements as significant events and should focus on other market factors as well for trading and investing.

Observed flash drought to persist in future over southern Africa

Southern Africa has experienced multiple occurrences of drought episodes, which is projected to persist in the future, considering all climate scenarios. Despite the documented change in a meteorological, agricultural, and hydrological drought situation in the region, few studies are yet to explore the changes in flash drought (hereafter; FD), which is characterized by a rapid reduction in root-zone soil moisture and more substantial intensification in few days to weeks. Here, we analyze the observed FD and related underlying drivers during the past 34 years. Also, we estimate the future changes in FD using the severity-duration magnitude matrix under the middle of the road (SSP2-4.5) and business as usual (SSP5-8.5), scenario. Lastly, the study investigates the role of anthropogenic warming using the fraction of attributable risk (FAR) approach and possible bivariate return periods of FD events. Our results demonstrate that the region has experienced multiple occurrences up to 72 pentads from 1980 to 2014. Underlying mechanisms revealed the compounding influence of Vapor Pressure Deficit (VPD), Potential Evapotranspiration (PET), and precipitation deficit that have a significant impact on the abrupt onset and rapid intensification of FD events and other hot extremes over the SAF region. Under a high emission scenario, the region will experience FD duration lasting for 30 days with >40 % severity projected to impact the region. Anthropogenic climate change and land use and land cover changes remain the most dominant drivers altering the FD events over the SAF region. The return period of FD events under the SSP5-8.5 scenario shows that the SAF region will witness multiple FD events of up to 80 pentads in the far future. These findings reinforce the need to limit the emission of greenhouse gases. Sustained warming of the climate will exacerbate the extreme events and other compounding factors, thus affecting the livelihoods of humans and life-supporting strata.

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.

Probability and recurrence interval of large earthquakes (Mw ≥ 6) in the Himalayan seismicity zone

The Himalayan Mountains are one of the world’s most seismically active regions. Due to the active seismic status of the Himalayan belt and ongoing development activities in the region, it is important to keep the seismic hazard estimates updated by incorporating historical and new data. This study uses the Gutenberg-Richter relations for four seismogenic source zones (SSZ) to estimate the probability of earthquakes of a specified magnitude in a given time interval. We used exponential, Weibull, Rayleigh, and log-normal statistical models to assess the probability of earthquakes (Mw ≥ 6). The probable recurrence time of the large earthquake (Mw ≥ 6) can be estimated by maximizing the conditional probability estimates. This recurrence interval is calculated after the elapsed time since the most recent large earthquake in the region. We also apply an autoregressive (AR) forecasting technique to predict earthquake recurrence intervals. The results indicate that the approximate recurrence interval of the large earthquakes (Mw ≥ 6) may be 22.052 ± 5.65 years within the seismicity zones, as per our statistical estimates based on limited and available datasets. The results of this study may be useful for the agencies involved in assessing seismic hazards and developing mitigation and preparedness strategies in the region.

Effectiveness of regional risk mitigation policies in equitably improving connectivity to essential service during hurricane-induced floods

This study aimed to evaluate the effectiveness of regional disaster mitigation policies in providing equitable access to essential services during hurricane-induced floods in Southeast Louisiana. Studies have been conducted on access to essential service facilities during and after disasters. However, there is limited research on whether current regional disaster mitigation plans ensure equitable access to emergency facilities. To this end, a methodology was developed to assess the effect of the 2017 Louisiana Coastal Master Plan developed by the Coastal Protection and Restoration Agency (CPRA) on equity in connectivity to essential service facilities (hospitals and fire stations) in a case study region in southeastern Louisiana. First, a graph-based model was used to represent the road network and determine the connectivity of five demographic groups during hurricane-induced flood scenarios. Herein, a hurricane-induced flood scenario with a low return period (50 years) was chosen for future years up to 2065, considering sea level rise and subsidence. Roads with flood depths exceeding 30 cm were considered impassable and were removed from the network. Connectivity was then determined using breadth-first search. Monte Carlo simulations were performed to propagate uncertainties in flood depths. It was found that minority groups were at a higher risk of losing access to emergency services during the selected hazard scenario. Native American and Asian populations were found to be at the highest risk of disconnection, followed by the Hispanic and African-American populations. Overall, the coastal master plan did not affect the equity (or lack thereof) in connectivity to essential service facilities.

Motion responses optimal design of semi-submersible platform equipped with a hollow moonpool based on CFD

Moonpools protect objects from the influence of environmental loads to some extent, however, the influence of the moonpool on floater motion is complicated. Based on the validation of CFD (computational fluid dynamics) simulations against model tests, the motion responses of a conceptually designed semi-submersible platform with a hollow annular cylindrical moonpool are analyzed under waves in a 100-year return period, which is the design condition. The results show that a larger opening size and a smaller moonpool chamber can decline the hydrodynamic responses of heave and pitch of the platform. Apart from wave frequency in the heave frequency, obvious low frequency is found, which is related to the difference frequency between the incident wave frequency and natural heave frequency. This complex heave motion is attributed to the moonpool shape. The vorticity analyses show that the large damping due to flow separation in the proximity of the bottom edge of the moonpool is beneficial for inhibiting the piston-like motion in the moonpool, resulting in reduced pitch motion but increased heave motion. Finally, an optimal design in terms of the heave motion is suggested with care owing to the vigorous piston-like motion in the moonpool for design cases.

Cascading consequences of structural interventions in a tropical wandering gravel‐bed river

AbstractRiverscapes are often modified and managed through ‘command and control’ structural engineering approaches. These structures not only alter flow and sediment transport patterns but also negatively affect riverscape biodiversity. These impacts are particularly acute for rivers that are characterised by high mobility and wide flow distribution during extreme events. We used hydrodynamic and geomorphological change assessment to appraise the impacts of existing flood structures and their potential for removal in a tropical wandering gravel‐bed river in the Philippines. Our approach informs a systematic decision‐making process to screen opportunities for channel reconnection. Two‐dimensional hydraulic modelling showed flood structures confine flood water within the active channel for more frequent flood events, but banks are overtopped during larger magnitude events (>50‐year recurrence interval). Incorporating modelling results, a multi‐criteria analysis was developed to appraise opportunities for river reconnection based on structure purpose, functionality, and local land‐use. We differentiate among four actions for each structure: removal, redesign, set back, or retention. One structure is recommended for removal because it cuts off an anabranch, reduces channel capacity, and increases main anabranch bed shear stress. Increased potential for bed and bank erosion due to the structure's presence had a cascading effect, resulting in further interventions downstream and on the opposite bank. We show how the use of system‐scale two‐dimensional hydraulic modelling alongside high‐resolution topographic mapping can support management of interventions to reconnect a river to its wider anabranch‐bar morphology. Such actions form part of proactive, adaptive, and nature‐based flood management plans with local and non‐local benefits.

A hybrid surrogate model for real-time coastal urban flood prediction: An application to Macao

Tropical cyclones could cause co-occurrences of storm tides and rainfall and, therefore, induce flooding hazards, posing high risks to coastal cities. Accurate and timely prediction of flood hazards in time–space domain is essential for flood risk management. In this study, a hybrid surrogate model is proposed for real-time flooding prediction by considering the compound effects of storm tides, rainfall, and drainage outflows. The hybrid surrogate model combines a long short-term memory (LSTM) neural network for predicting drainage outflows with a one-dimensional convolutional neural network (1D CNN) for predicting water depths. The model is tested using performance metrics, and the simulation results agree well with the historical measurements. Moreover, a sensitivity analysis of the drainage outflows using the modified Morris screening method reveals the importance of considering drainage systems in flood modelling, particularly when rainfall return periods are relatively small. The sensitivity indices vary over the computation domain in terms of different driving factors, with positive values corresponding to rainfall-dominated area while negative values corresponding to storm tide-dominated area. The computation cost of the model is quite low, and the fast prediction speed could provide a sound basis for early warning and real-time flood management. The proposed hybrid surrogate model offers a promising function for rapid and accurate flood inundation prediction in coastal cities, enabling more effective flood risk management and emergency response planning.

Performance Analysis and Techno-Economic Evaluation of Solar Energy Retrofitting for Coal-Fired Power Plant in Central Kalimantan Province

The power generation sector significantly contributes to climate change. Mitigation efforts are crucial to adhering to the global commitment to limit temperature increases below 2°C. One potential solution is retrofitting existing power plants with technologies that integrate renewable energy. This study explores the integration of solar energy into the operational processes of a coal-fired power plant in Central Kalimantan, replacing the extraction steam turbine in the high-pressure feed water heater No. 7. Using STEAG EBSILON for simulation, this research evaluates the power plant's performance before and after retrofitting in both power-boost (PB) and fuel-save (FS) modes under varying load conditions. The results demonstrate that thermal efficiency in both PB and FS modes increased by up to 2% compared to the base scenario. Specific fuel consumption decreased by 15.05 g/kWh in PB mode and 15.75 g/kWh in FS mode, leading to a reduction in coal consumption and CO2 emissions by 4.69% and 4.94% respectively. Additionally, the study observed that the solar percentage and solar-to-electricity efficiency increased as the load decreased. In FS mode, the solar electricity proportions at VWO, 100%, 75%, and 50% load rates were 5.23%, 5.53%, 7.76%, and 11.92%, respectively. The levelized cost of energy (LCOE) for solar electricity was calculated to be 431.82 IDR/kWh, with an expected investment return period of 5.87 years.

Fitting the return period of dengue fever epidemic in Guangdong province of China

ObjectivesThe prevention and control of dengue fever (DF) has been a major public health issue in Guangdong (GD) province, China. This study aims to analyze the return period (RP) and the return level (RL) of DF epidemic in GD, to help the formulation of prevention and control plan. MethodsThree models, namely Lognormal distribution (Lognor D.), normal distribution (Norm D.), and generalized logistic distribution (GLD) were selected to fit the annual number of indigenous DF cases in GD from 1978 to 2021. The coefficient of determination (R2), the root mean squared error (RMSE), and the Akaike information criterion (AIC) were used to evaluate the goodness of fit. We predicted the RP of 45130 historical maximum cases that occurred in 2014 and the RP of 4884 peak cases that occurred in 2019 over the 5 years up to 2021. ResultsFitting through the three models, the R2 was 0.98, 0.98, and 0.96, respectively. The predicted RLs of the annual DF case number were between 297 and 43234, 297 and 43233, 362 and 41868 for the RPs of 2–45 years. The predicted RPs of DF outbreaks exceeding the historical maximum were 43, 43, and 44 years, and the RPs of DF epidemic exceeding the peak in 2019 were 7, 7, and 8 years, respectively. Therefore, we predicted that GD would experience a DF outbreak beyond the historical maximum in the next 35 or 36 years from 2022. And in the next 4 or 5 years from 2022, there would be a DF epidemic exceeding the peak in 2019. ConclusionsThe study discloses a temporal periodicity inherent to the DF epidemic in GD. The three models are applicable for forecasting and evaluating the RP and RL of DF epidemic in GD, separately.

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.