Historical Flood Research Articles

Gauged and historical abrupt wave front floods (‘walls of water’) in Pennine rivers, northern England

AbstractExtremely rapid rates of rise in level and discharge in a subset of flash floods (‘abrupt wave front floods’, AWF) are separate hazards from peak level. Such flood events are investigated for Pennine catchments in northern England using both gauged and historical information. Gauged level and flow digital records at 15‐min intervals provide recent data. Historical information for 122 AWF events is extracted from a chronology of flash floods for Britain. Historical AWF events are mapped and found to occur on every major Pennine catchment; catchment descriptors are derived as a basis for assessing catchment vulnerability. We discuss the disputed origin of AWF. Using gauged data, we contrast the rising limb of AWF and ‘normal’ floods. We investigate time series of historical AWF, noting a puzzling peak in the late 19th century. Current rainfall and river monitoring does not provide a reliable basis for understanding AWF processes or for operational response and we suggest improvements. Similarly, current models for design flood estimation and forecasting do not generate the observed rapid increase in level in AWF floods.

Community-based screening for post-traumatic stress disorder among flood victims - A cross-sectional study from Kerala, India.

Natural disasters like floods have various physical and psychological effects on victims. Post-traumatic stress disorder (PTSD) is a condition that arises as a delayed reaction to extraordinarily threatening or catastrophic situations. The objective was to screen for PTSD and associated factors among victims residing in the flood-affected areas of Kerala, India. A community-based screening for PTSD was done among 600 flood victims residing in three selected districts (Pathanamthitta, Alleppey, and Kottayam) of Kerala. A trauma screening questionnaire was used to screen for PTSD. More than 90% of them had to stay in relief camps during floods. More than 80% had damage to houses, followed by loss of domestic animals and vehicle damage. Among participants, 298 (49.7%) screened positive for PTSD 3 months post disaster. No previous history of flooding, odds ratio (OR) = 8.6 [confidence interval (CI) 5.7-13.1]; younger age, OR = 1.41 (CI 1-1.9); higher family income, OR = 4.2 (CI 2.5-6.8); education, OR = 1.4 (CI 1-2.1); flood-related morbidity, OR = 8.8 (CI 5.3-14.8); and death of a family member, OR = 3.4 (CI 1.2-9.3), were the factors that were found to be significantly associated with stress among respondents. Almost 50% of flood victims were screened positive for PTSD. This study's findings reiterate the need to provide psychological support as a priority along with other disaster control measures.

Exploring optimal deep tunnel sewer systems to enhance urban pluvial flood resilience in the gangnam region, South Korea

Urban pluvial flooding is becoming a global concern, exacerbated by urbanization and climate change, especially in rapidly developing areas where existing sewer systems lag behind growth. In order to minimize a system's functional failures during extreme rainfalls, localized engineering solutions are required for urban areas chronically suffering from pluvial floods. This study critically evaluates the Deep Tunnel Sewer System (DTSS) as a robust grey infrastructure solution for enhancing urban flood resilience, with a case study in the Gangnam region of Seoul, South Korea. To do so, we integrated a one-dimensional sewer model with a rapid flood spreading model to identify optimal routes and conduit diameters for the DTSS, focusing on four flood-related metrics: the total flood volume, the flood duration, the peak flooding rate, and the number of flooded nodes. Results indicate that, had the DTSS been in place, it could have reduced historical flood volumes over the last decade by 50.1–99.3%, depending on the DTSS route. Regarding the conduit diameter, an 8 m diameter was found to be optimal for minimizing all flood-related metrics. Our research also developed the Intensity-Duration-Frequency (IDF) surfaces in three dimensions, providing a correlation between simulated flood-related metrics and design rainfall characteristics to distinguish the effect of DTSS on flood risk reduction. Our findings demonstrate how highly engineered solutions can enhance urban flood resilience, but they may still face challenges during extreme heavy rainfalls with a 80-year frequency or above. This study contributes to rational decision-making and emergency management in the face of increasing urban pluvial flood risks.

Unveiling Torrential Flood Dynamics: A Comprehensive Study of Spatio-Temporal Patterns in the Šumadija Region, Serbia

This paper presents a comprehensive analysis of flood frequency and a spatio-temporal characterization of historical torrential floods in the Šumadija region using water discharge datasets and documented events. A chronology of 344 recorded torrential flood events, spanning from 1929 to 2020, illustrates the region’s vulnerability, with a death toll exceeding 43. The study defines the intra-annual primary and secondary peaks of torrential flood occurrences and explains their spatial distribution. Furthermore, the identification of suitable probability distribution functions underscores the necessity of tailored approaches for effective flood risk management in this diverse geographical environment. The study employed Flood Frequency Analysis (FFA) and goodness-of-fit tests, including the Kolmogorov–Smirnov (K-S) and Cramér–von Mises (CvM) tests, to assess the frequency and magnitude of flood events and evaluate diverse distribution functions. The main results include the identification of suitable probability distribution functions for each river within the region, emphasizing the need for tailored approaches in flood risk management. Additionally, discharge values for various return periods offer crucial insights for informed decision-making in flood risk management and infrastructure planning.

Accelerating flash flood simulations: An efficient GPU implementation for a slim shallow water solver

Flash floods are an increasing hazard to human infrastructure and life. Effective disaster management and mitigation require accurate and fast predictions for decision-making. The Flood Inundation Parallel Computation (FIP) software presented in this paper shows how to fully exploit the tremendous computational capabilities of graphics processing units (GPUs) to accelerate shallow water solvers beyond the current state-of-the-art. The time efficient explicit shallow water scheme for structured grids RMG, is introduced and implemented in FIP. The optimized GPU implementation of FIP achieves balanced memory- and instruction throughputs of up to 80%. Validation and performance tests using laboratory and historical flood cases are presented that demonstrate the accuracy and effectiveness of FIP in predicting flood inundation. Our implementation achieves a fourfold speedup in comparison to state-of-the-art approaches. It enables faster-than real-time simulations of areas of over 600 km2 at 1 m resolution on consumer-grade GPUs.

Landscapes on the edge: River intermittency in a warming world

Sediment transport in rivers is not steady through time. Highly intermittent river systems, which only transport bedload during the most significant flow events, are particularly sensitive to changes in climate and precipitation patterns. People and landscapes can be vulnerable to fluvial processes, and quantifying river intermittency is critical for assessing landscape response to projected changes in precipitation extremes due to climate change. We generated new constraints on recent to modern fluvial intermittency factors—the frequency at which bedload is mobilized in a river—based on field measurements in the Corinth Rift, Greece, and Holocene sediment accumulation rates. Results reveal some of the lowest documented intermittency factors to date, showing Mediterranean rivers can transport an entire annual sediment load in a rare storm event. Coupling intermittency calculations with historical flood and precipitation data indicates these rivers transport bedload during one storm every ∼4 yr, associated with rainfall >50 mm/d, and subsequent floods; this hydroclimate is typical across the Mediterranean region. Furthermore, climate models predict precipitation extremes will increase across Europe, and the frequency of events that surpass thresholds of sediment transport will increase significantly, potentially causing sediment loads to double by 2100 CE. As the area of arid land likely to host intermittent rivers also increases, sensitive landscapes are on the edge of significant geomorphic change, driven by global warming.

Quantitative assessment of the erosion and deposition effects of landslide-dam outburst flood, Eastern Himalaya

Both regular flow and infrequent outburst floods shape the mountain landscape, but their relative contributions have been widely debated, in part due to the paucity of quantitative data on historical outburst floods. In June 2000, an outburst flood was triggered by a landslide-dam failure in a rapidly exhumed region of the Eastern Himalaya. To investigate the role of this kind outburst flood on landscape evolution, we employ topographic differencing, satellite imagery, and 2D hydraulic simulations to quantify the equivalent erosion and deposition within ~ 80 km flood route downstream of the breach. The flood lasted for ~ 10 h, with a peak discharge of 105 m3/s, leading to average erosion of 10 m, and contributed ~ 1–2 × 103 times more sediment than over long-term mean fluvial processes. The flood produced extensive lateral erosion, which triggered a threefold widening of the valley floor and abundant subsequent landslides. The ubiquitous boulder bars deposited in the channel inhibited incision, and facilitated lateral erosion after the flood. The resulting channel configuration and extensive bank erosion continue to affect fluvial dynamics until the next catastrophic flood that remobilizes the boulders. Our quantitative findings highlight the profound importance of recurrent outburst floods for gorge development and landscape evolution in Eastern Himalaya.

Threshold-based flood early warning in an urbanizing catchment through multi-source data integration: Satellite and citizen science contribution

An effective flood early warning system is vital to take action to save lives and protect properties in urban areas which are increasingly prone to flooding. Despite substantial progress in flood early warning systems, limited available and accessible data often impede their advancement and reliability. Engaging communities affected by flooding can help address data and information gaps in flood early warning systems, facilitated by appropriate methods. This study developed and evaluated a flood threshold combination method to support a community-based flood early warning system in the Akaki catchment, home to Addis Ababa, the capital city of Ethiopia. Various flood threshold combinations were formulated, calibrated and validated by integrating multiple sources of data: rainfall, antecedent precipitation index estimates, Sentinel-1 Synthetic Aperture Radar satellite time series of flood extent, long-term simulated streamflow, citizen science data, river water level and three days lead-time numerical weather prediction rainfall forecast. During validation, the rainfall and river water level threshold combination outperformed other threshold combinations with probability of detection, false alarm ratio, and critical success index estimates of 0.74, 0.18 and 0.63, respectively. The flood threshold combination showed high detection performance for most flooding conditions. Flood forecasts with a 1-day lead-time exhibited a high likelihood in detecting historical severe flood events. The study provides a tested methodology for selecting suitable flood threshold-combinations, enhance the engagement of citizen scientists in a community–based flood early warning system in urban communities.

Unveiling and modelling the flood risk and multidimensional poverty determinants using geospatial multi-criteria approach: Evidence from Jigawa, Nigeria

Floods are recurring natural disasters that pose major challenges to communities worldwide, especially in regions where poverty is widespread. This research focuses on analysing the relationship between flood risk and poverty factors in Jigawa. It uses geospatial data, historical flood records and remote sensing to locate flood-prone areas. The integration of these data sets creates a comprehensive model for measuring flood-prone zones and their impact on multidimensional poverty. The flood risk zone included 3% and 13% as extremely high and high. In addition, 40% of the population is particularly vulnerable to flood disasters, leading to multidimensional poverty in the region. At the same time, poverty determinants such as agricultural activities, income level, education, access to health care, housing conditions, and road networks were analysed using statistical methods of principal component analysis (PCA). Findings from this research will go a long way toward understanding the complex interactions between natural disasters (flood) and poverty and will shed light on the mechanisms that perpetuate vulnerability in impoverished regions. By identifying the specific determinants of poverty that exacerbate the impact of flooding, this study provides evidence-based insights into possible avenues for targeted interventions and risk-reduction strategies. In addition, this study underscores the importance of using geospatial technology for disaster risk management and poverty alleviation. These findings will help policymakers and local authorities implement more efficient and adaptive disaster preparedness and response policies, thereby building the resilience of communities facing the intersecting challenges of poverty and flood risk.

Thresholds for estuarine compound flooding using a combined hydrodynamic–statistical modelling approach

Abstract. Estuarine compound flooding can happen when extreme sea level and river discharges occur concurrently, or in close succession, inundating low-lying coastal regions. Such events are hard to predict and amplify the hazard. Recent UK storms, including Storm Desmond (2015) and Ciara (2020), have highlighted the vulnerability of mountainous Atlantic-facing catchments to the impacts of compound flooding including risk to life and short- and long-term socio-economic damages. To improve prediction and early warning of compound flooding, combined sea and river thresholds need to be established. In this study, observational data and numerical modelling were used to reconstruct the historic flood record of an estuary particularly vulnerable to compound flooding (Conwy, North Wales). The record was used to develop a method for identifying combined sea level and river discharge thresholds for flooding using idealised simulations and joint-probability analyses. The results show how flooding extent responds to increasing total water level and river discharge, with notable amplification in flood extent due to the compounding drivers in some circumstances, and sensitivity (∼ 7 %) due to a 3 h time lag between the drivers. The influence of storm surge magnitude (as a component of total water level) on the flooding extent was only important for scenarios with minor flooding. There was variability as to when and where compound flooding occurred; it was most likely under moderate sea and river conditions (e.g. 60th–70th and 30th–50th percentiles) and only in the middle-estuary zone. For such cases, joint-probability analysis is important for establishing compound flood risk behaviour. Elsewhere in the estuary, either the sea state (lower estuary) or river flow (upper estuary) dominated the hazard, and single-value probability analysis is sufficient. These methods can be applied to estuaries worldwide to identify site-specific thresholds for flooding to support emergency response and long-term coastal management plans.

Flood susceptibility mapping in the Tongo Bassa watershed through GIS, remote sensing and frequency ratio model

Abstract Flooding constitutes a major problem for the inhabitants of Douala City in general and those of the Tongo Bassa watershed (TBW) in particular. Faced with this situation, public authorities need to put in place measures to mitigate the vulnerability of populations to these disasters. This article aims to map flooding risk areas in the TBW using the geographic information system, field data (historical flood points), remote sensing data (Sentinel II image) and the frequency ratio model. The map produced shows that 1.41, 8.88, 28.51, 33.86 and 27.33% of the basin area are respectively delimited into very low, low, medium, high and very high flood vulnerability classes. High and very high flooding risk areas (those where flooding is most likely to occur) occupy more than half of the basin (61.19%). These areas are characterized by significant imperviousness, low altitudes, weak slopes, significant proximity to watercourses and clayey soils. Most of the houses in the basin (66.92%) are located in areas affected by these two levels of exposure (high and very high). With respective success and prediction accuracy rates of 89 and 96.78%, a certain confidence deserves to be placed on the map of flooding risk areas produced.

Performance analysis of the lisflood hydrological model in a flood event in the madeira river basin

The largest recorded flood of the Madeira River (largest tributary of the Amazon River) occurred in 2014, remaining above the flood level for 90 days, reaching the maximum level on March 30, at 19.69 m. Among the various tools capable of assisting in monitoring and forecasting floods are hydrological models, such as LisFlood, a distributed hydrological model of the rainfall-runoff type. Thus, the objective of this research was to evaluate the performance of the LisFlood model for maximum flows in the Madeira River basin. There were a total of 7 river gauge stations calibrated and subsequently validated, distributed across 5 sub-basins. The calibration process was carried out using a multi-objective method, applying the NSGA II as an optimization algorithm, with the model's performance being evaluated by the NSE and KGE metrics. The calibration and validation results demonstrated, in general, that the LisFlood model performed well between the simulated and observed flow values for the Madeira River basin. The average of the 07 stations analyzed was 0.81 for KGE and 0.69 for NSE, for the calibration process. In validation, the average metrics were 0.78 in KGE and 0.67 in NSE. In relation to the historic flood event that occurred in 2014, it can be seen that the model followed the maximum flow peak observed at the Porto Velho station, with a difference in the simulated flow of 17% lower than the observed flow, for the year 2014, demonstrating good efficiency of LisFlood in simulating maximum flow. Thus, the study demonstrated that the application of the LisFlood model in large basins is effective in simulating maximum flows, satisfactorily simulating extreme flood peaks.

Historical catastrophic floods at the southern edge of the Atacama Desert: A multi-archive reconstruction of the Copiapó river extreme events

The last hydrometeorological extreme event that caused large floods in the southern Atacama Desert in March 2015 raised concern about how little was known about the fluvial dynamic of these arid basins. Understanding the response of intermittent and ephemeral rivers in drylands to the present context of global change is critical to preserve the ecological and human systems they support, to sustainably manage their scarce water resources and to develop flood risk management plans. We have studied the instrumental and historical record and explored the potential of the Copiapó River geological record in the comprehension of how extraordinary the 2015 flood was and how its fluvial dynamic relates with global climate oscillations. We have identified 36 flood events that have occurred in the last 400 years: 22 of them have been classified as ordinary rises of the river flow (discharges <30 m3/s), 11 as extraordinary floods in which the damage is confined to areas adjacent to the river (discharges 30–180 m3/s), and only 3 as catastrophic floods (discharges >180 m3/s), including the 2015 flood event. The incorporation of the historical and palaeohydrological data into the flood frequency analysis results in an increase of the magnitude of the flood quantiles in which large flood events occur with an average recurrence interval of 120 years. Most of the flood events were caused by heavy rains that are largely linked to the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation with a superimposed effect of the ENSO. Discharges >30 m3/s, i.e., extraordinary and catastrophic floods, occur with positive phases of the PDO and the ENSO. Further exploration of the fluvial geological record of the Copiapó River will help lengthening to thousands of years the flood record what will help improving communities' resilience by anticipating flood hazards in the current global change context, in which stronger rainfall events modulated by ENSO and ENSO-like conditions are expected.

Articulating a Loss and Damage Fund: How the Global South is Rethinking Agency and Justice in an Age of Climate Disasters

ABSTRACT The Global South (or Low-Income Countries, LICs) long has been advocating for the establishment of a Loss and Damage (L&D) Fund to address vulnerability and limited adaptation capacity in response to disasters exacerbated by climate injustices, which finally gained international recognition of late. This essay focuses on two key moments that led to this landmark agreement: at COP19, when Philippines climate delegate Naderev “Yeb” Saño advocated for L&D in the wake of Typhoon Haiyan; and during COP27, when global leaders invoked the historic floods in Pakistan as the agreement was reached. We consider how these two disasters were invoked during the passing of L&D in ways that critically interrupted the prevailing spiral of silence to articulate “disasters” to “climate” and “climate” to “justice” in the global climate policy arena. These discourses reveal, then, part of the expanding imaginary emerging to address human agency and inequities in an age of the climate disasters, including the idea of a “global majority.”

Sensitivity analysis of typhoon-induced floods in coastal cities using improved ANP-GIS

This study developed an analytical network process (ANP) incorporated into a geographic information system (GIS; abbreviated as ANP-GIS) to assess flood sensitivity in coastal cities. A new consulting process is proposed to improve the ANP analysis by determining range scores of assessment factors. Compared with the original analytical hierarchy process (AHP) combined with GIS (AHP-GIS), the improved ANP-GIS with new consulting process can effectively consider the interrelationships of assessment factors between the index and sub-index layers. To verify the efficiency of ANP-GIS with new consulting process, both AHP-GIS and ANP-GIS were adopted to assess the exposure of sensitivity to typhoon-induced floods in the coastal cities of Guangdong Province. The results were validated by historical typhoon-induced flood records, revealing that most of the typhoon-induced floods were in the region with the assessed higher and highest flood sensitivities. The percentage of the highest flood sensitivity from the improved ANP-GIS with typhoons was twice that of the AHP-GIS. When considering typhoons, the higher and highest flood sensitivity levels increased from 29% to 48%, as indicated in this study. The assessment results from the improved ANP-GIS were closer to the historical records and better than the performance of AHP-GIS.

Overflowing waters, diluted investments: The enduring impact of historical Yellow River floods on enterprise fixed assets investments

Unraveling the long shadow of historical natural disasters, this study explores how the Yellow River floods shape enterprise fixed asset investments in an institutional and cultural context. Leveraging the regression discontinuity approach, we uncover a significant negative impact of these floods on investments, primarily due to weakened property rights and increased reliance on religious coping mechanisms. Further analysis suggests that the enduring impact of floods on investment persists even after controlling for confounding short-term natural disasters, financial development level, and the Tangshan Earthquake. In addition, the impact of historical Yellow River flood arises from cumulative consequences, rather than individual flood outcomes. Overall, this study not only sheds light on the dynamics between historical natural disasters and enterprise economic behavior, but also contributes to a deeper understanding regarding the broader, long-term economic impacts of climate change.

Amplified Extreme Floods and Shifting Flood Mechanisms in the Delaware River Basin in Future Climates

AbstractHistorical records in the Delaware River Basin reveal complex and spatially diverse flood generating mechanisms influenced by the region's mountains‐to‐plains gradients. This study focuses on predicting future flood hazards and understanding the underlying drivers of changes across the region. Using a process‐based hydrological model, we analyzed the hydrometeorological condition of each historical and future flood event. For each event, at the subbasin scale, we identified the dominant flood generating mechanism, including snowmelt, rain‐on‐snow, short‐duration rain, and long‐duration rain. The rain‐induced floods are further categorized based on the soil's Antecedent Moisture Condition (AMC) before the event, whether dry, normal, or wet. Our historical analysis suggests that rain‐on‐snow is the primary flood mechanism of the Upper Basin. Although most frequent, the magnitude of rain‐on‐snow floods is often less severe than short rain floods. In contrast, historical floods in the Lower Basin are primarily caused by short rain under normal AMC. Given the uncertainties in climate projections, we used an ensemble of future climate scenarios for flood projections. Despite variations in regional climate projections, coherent perspectives emerge: the region will shift toward a warmer, wetter climate, with a projected intensification of extreme floods. The Upper Basin is projected to experience a marked decrease in rain‐on‐snow floods, but a substantial increase in short rain floods with wet AMC. The largest increase in flood magnitude will be driven by short rains with wet AMC in the Upper Basin and by short rains with normal AMC in the Lower Basin.

Understanding the Impact of Precipitation Bias‐Correction and Statistical Downscaling Methods on Projected Changes in Flood Extremes

AbstractThis study evaluates five bias correction and statistical downscaling (BCSD) techniques for daily precipitation and examines their impacts on the projected changes in flood extremes (i.e., 1%, 0.5%, and 0.2% floods). We use climate model outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to conduct hydrologic simulations across watersheds in Iowa and determine historical and future flood extreme estimates based on generalized extreme value distribution fitting. Projected changes in these extremes are examined with respect to four Shared Socioeconomic Pathways (SSPs) alongside five BCSD techniques. We find the magnitude of the estimates of future annual exceedance probabilities (AEPs) are expected to increase under all SSPs, especially for the emission scenarios with higher greenhouse gases concentrations (i.e., SSP370 and SSP585). Our results also suggest the choice of BCSD impacts the magnitude of the projected changes, with the SSPs that play a more limited role compared to the choice of downscaling method. The variability in projected flood changes across Iowa is similar across the downscaling technique but increases as the AEP increases. Our findings provide insights into the impact of downscaling techniques on flood extremes' projections and useful information for climate planning across the state.

Climate Change Impact Assessment and Disaster Risk Financing Strategies in Mali: A Comprehensive Analysis of Drought and Flood Events

Climate change impact increasingly led to humanitarian assistance increase and needed. To better address climate change impacts mitigation, a suitable financing instrument is essential to facilitate government, humanitarian, and other stakeholders' finance mobilization. However, few studies have been done on disaster risk profiling to guide decision-makers in their choices. Disaster risk profile analysis has been conducted in Mali to facilitate financial resources mobilization and climate finance instrument choice by identifying Historical drought and flood events. To do so, published papers; and some international institution websites dealing with climate hazard events such as Reliefweb, Hazard/risk, climate information services, Relief Web; CRED- EM-DAT; World Bank Climate Knowledge Portal, World Bank- UNDRR -ThinkHazard, WFP ARC/GeoNode/VAM/DataViz addressing Mali country have been assimilated for evidence accumulation and synthesis and presented in a database. Furthermore, national statistics and national reports on hazards have been also reviewed. Before starting the reading exercise, a reading/analytical framework has been elaborated. In Mali the year 1984 to 2019, 21 flood events occurred in Mali and the most exposed regions to floods are Koulikoro, Bamako and Gao. From 1969 to 2020, 21 drought events were registered in in Mali and the most affected regions are Koulikoro, Mopti, Gao, Kayes. The time return period of drought has been estimated to 3 years while the time return of flood has been estimated to be about 2 years. Drought events are less frequent than flood events, however, drought events affect more population than floods. Also, Also, the yearly response cost for drought events is USD million 277.46 with an average US USD 204.37 cost per affected population. For the flood, even the yearly response cost is USD 11.107 million With USD 261.82 per affected population. Macro-insurance and CAT bonds are more suitable disaster risk financing instruments and are recommended to better address drought events while Anticipatory action and government contingency funds are more suitable climate disaster risk financing instruments to better address flood events in Mali.

The assessment of flood hazard in Pondok Keumuning village of Langsa City, Aceh due to heavy rain in 2020

Langsa faces the recurring threat of floods every year, primarily caused by high rainfall resulting in surface runoff in the Langsa Watershed. However, there is uncertainty regarding the specific causes of flooding in the city. This research discusses the flood hazards generated by Langsa River due to high rainfall in Keumuning Village, Langsa City, in 2020. The data utilized in this study includes daily rainfall data obtained from PTPN I Langsa, specifically from the Kebun Lama (KLM), Kebun Baru (KBR), and Tualang Sawit (TWS) stations. Additionally, observed water level data is collected from the Keumuning water gauge station operated by the Aceh Irrigation Agency. Since there is no river discharge record at the Keumuning water gauge station, the Nreca method is used to analyze the direct runoff from the Langsa Watershed due to rainfall, linking it to the water level at Keumuning. Historical flood event data is compiled from the Regional Disaster Management Agency of Langsa City, online media sources, and interviews with flood-affected communities. The research findings indicate that floods in Keumuning Village, Langsa, are triggered by high rainfall, leading to increased river discharge as a result of heavy rainfall at the TWS station (located upstream in the Langsa Watershed) with a 2-year return period. This can result in flooding for the villages around the Langsa River. Similarly, suppose rainfall reaches a 2-year return period at the KLM and KBR stations situated within the middle and downstream of the Langsa Watershed. In that case, it poses a flood threat to the upstream villages along the estuary branches. However, further studies are necessary to assess compound floods triggered by tidal water levels, rainfall, and river discharge in the vicinity of these estuary branches.