Peak Discharge Research Articles

UTILIZATION OF HEC-RAS 2D FOR FLOOD INFLUENCE MODELING DUE TO PEAK DISCHARGE OF WALANAE RIVER IN WAJO DISTRICT

On December 25, 2024, a flood disaster struck Sabbangparu Sub-district, Wajo Regency, South Sulawesi, caused by heavy rains that persisted for several days. This led to the overflow of the Walanae River and additional flooding from neighboring regencies. The disaster affected thousands of residents, submerged agricultural lands, and completely cut off several access roads. This study conducted a simulation aimed at predicting flood-affected areas due to the overflow of the Walanae River in Wajo Regency as part of future disaster mitigation efforts. The simulation utilized HEC-RAS 6.4.1 software, which has the capability to model 1D and 2D fluid flow. Additionally, flood-affected area analysis was performed using ArcGIS 10.8. The flood map simulation results indicated that the affected area covered 10,814.35 hectares, equivalent to 68.22% of the administrative area of Sabbangparu Sub-district. The river cross-section simulation revealed that most of the Walanae River cross-sections were unable to accommodate the peak discharge of 3,658.4 m³/s, causing water to overflow into residential areas and rice fields. This poses the risk of significant economic losses and even fatalities. The results of this study are expected to serve as a reference in planning future flood disaster mitigation efforts.

Molecular-level exploration of spatiotemporal dynamics of fluvial particulate organic carbon sources during storm events: Using a high-temporal resolution multi-biomarker approach.

Identifying the origins of storm fluvial particulate organic carbon (POC) provides information about the hydrological connectivity within the river corridor and the roles of the land-stream interface in the carbon cycle. However, current understanding of storm-induced POC source dynamics is constrained by observations limited in space and time. This study presents a unique approach integrating higher spatial and temporal resolution sampling with a multi-biomarker analysis to better understand POC source dynamics across scales. Storm POC samples were collected at ∼2h intervals at three locations along the flow trajectory of an agricultural stream during six storm events with varied storm characteristics and seasonality, and characterized for their concentrations, C and N contents, stable C isotopes, and biomarker contents. Our results showed a source transition from in-stream algal production during early storm stages to surface soils with vascular plant signatures during peak precipitation and discharge across events and stations. Biomarkers further resolved the terrestrial signature into one likely from bank vegetation and another from row crop soils. This additional separation appeared conditionally, with the magnitude and sequence influenced by environmental factors such as storm trajectory, antecedent conditions, and management/vegetation cover. Source transitions were less distinctive in the lower reaches due to the greater integration of inputs, although one storm with localized precipitation showed the opposite pattern. Both scenarios align with the expected lower hydrological connectivity downstream. With the employed approach, the evolution of the storm pulse POC as it responds to river corridor processes could be visualized both temporally and spatially.

Hydrological Drivers of Flooding in Niamey (Niger): The Role of the Sirba River

Abstract In recent decades, floods have become a major global concern. In Niamey (Niger) in West Africa, flooding is primarily caused by the significant increase in surface runoff resulting from heavy rainfall occuring between July and September in the upstream river basins of the three major tributaries of the Middle Niger River (Sirba, Gorouol and Dargol catchments). While the Sirba is empirically considered as the largest driver to flooding in Niamey, its contribution have not been precisely established. This study analyzes the influence of these tributaries on the Niger River discharges at Niamey during the rainy season, with a particular focus on the Sirba River basin. Daily annual maximum discharge (AMAX) data from 1990 to 2022 timeseries are used as inputs to various statistical analyses, including trend analyses, change point detection, concordance analysis and flood dependency assessment. The results reveal a significant change point in 2009 and increasing trends between the Sirba and Niger River stations. The flood propagation time delay varies from 1 to 4 days between the upstream river basins tributaries and Niamey station, with a strong concordance in peak discharges, particularly dominant with the Sirba River. The Dynamic Time Warping (DTW) and the Gumbel copula analyses highlighted the significant control of the Sirba River basin on flooding in Niamey, while also highlighting the important roles played by other tributaries. These findings are crucial for improving flood prevention and further refine urban flood management strategies in Niamey and other cities globally, affected by fluvial floods.

Modeling the Nucleation and Growth of Lead Sulfate Particles on Lead Electrodes

Abstract Lead-acid batteries (LABs) play a pivotal role in the energy storage sector with applications spanning from starting-lighting-ignition batteries to grid energy storage. Passivation of lead negative electrodes by PbSO4 particles is a fundamental mechanism limiting the performance of LAB. In this regard, an electrochemical model is developed that simulates the nucleation and growth (N&G) dynamics of PbSO4 particles on a flat lead electrode, responsible for its passivation. The model considers the electrochemical reactions between lead electrode and sulfuric acid, N&G of PbSO4 particles, passivation of the lead surface, and the ternary transport of PbSO4 (aq), bisulfate, and protons in H2SO4 electrolyte. The model is validated with a dataset of cyclic voltammetry (CV) responses collected at several scan rates and H2SO4 concentrations. The model shows remarkable qualitative and quantitative agreement with the experimental data including CV peak features, discharge capacity, and particle size. The model was employed to explore key N&G quantities, such as supersaturation, nucleation rate, particle count, growth rate, particle size, and surface coverage, and to examine how their interactions influence electrode utilization. Parametric studies were also conducted to evaluate how scan rates and acid concentrations influence the previously mentioned N&G quantities and, subsequently, the utilization of the electrode.

Storm water runoff studies in built-up watershed areas using curve number and remote sensing techniques

Within major city confines, floods are a major cause of worry and are mainly due to excessive urbanization encroaching on natural landscapes which would otherwise have served as areas of infiltration. The study combines the growth of urban landscape to estimate the maximum surface runoff and aimed to quantify this runoff generated and peak discharge for better urban management practices. These past five decades, the area experienced erratic expansion along with various changes in its land classification, resulting in several flood events in various parts. Runoff estimation was made using Curve Number method for the watershed. Annual rainfall deviation from mean saw an increase by 16% on an average in the past decade, with more than a 100% deviation from mean in 2017. Topographical maps generated to study the changes contributing to flood situations show a 90% increase in concretization over the past two decades and more than 50% reduction in the amount of natural vegetative cover in that same time period. Statistical analysis shows a good fit of the selected model for runoff estimation and well correlated variables. The model satisfactorily predicted runoff from the simulated data analysis with evaluation criteria NSE = 0.9945, MAE = 5.4121, r = 0.9975, R2 = 0.9949, RMSE = 6.8117 and PBias = 1.1436. The results revealed a steady increase in yearly runoff, due to topographical changes and increase in precipitation intensity over time. The study suggests intervention efforts be targeted spatially to ensure suitable flood-control structures and systems.

Study on Flood Control of the Sumber Pinang River in Sidogiri, Pasuruan Regency through River Normalization, Levees, and Parapet Walls

The Sumber Pinang River in Pasuruan Regency frequently experiences flooding due to its insufficient capacity. This study aims to analyze flood control measures using hydrological and hydraulic approaches with the HEC-RAS 6.4.1 software. The data used include maximum rainfall, river cross-section profiles, and land use. The planned flood discharge was calculated using the Nakayasu Synthetic Unit Hydrograph (SUH) method, resulting in a peak discharge of 442.823 m³/s. The analysis results indicate that 81% of the river cross-sections are prone to overflow. Proposed control measures include river normalization and the construction of levees and parapet walls. River normalization is planned for the entire river body, while levees and parapet walls are proposed at critical points to enhance the river's capacity. This study provides recommendations for more effective flood control planning in the future.

Time Series Analysis of River Discharge, Water Stage, and Rainfall at Lokoja Section of Benue River, Kogi State, Nigeria

This study carried out a time analysis of river water level (stage), rainfall, and discharge in the Lokoja section of River Benue and assessed their implications for flooding. The specific objectives that guided the study were focused on monthly and annual variability in water level, rainfall, and discharge are examined, along with their interrelationships. Data on water level and discharge were acquired from the Nigeria Hydrological Services Agency (NHSA), Abuja covering 22 years (2001 -2021), while rainfall data were obtained from the Nigeria Meteorological Agency (NiMet), Lagos Operational Headquarters. Time series analysis was carried out using the Least Square Regression Model. The significance of the trend was tested using the student’s t-test at a 0.05 (95%) confidence level. While descriptive statistics employed are mean, standard deviation, and coefficient of variation. The results indicate a decline in water levels from January to April, followed by a significant rise from May to October. Annual water levels show a significant positive trend over 21 years (R² = 0.2968, r= 0.5448), with notable fluctuations. Peak discharge exhibits a fluctuating monthly pattern, with a significant increasing trend over the years (R² = 0.2451, r = 0.4951), indicating potential flood risks. Monthly rainfall varies significantly, with notable peaks between April and August. Although annual rainfall shows a slight increasing trend, it’s not statistically significant. Strong correlations exist between peak discharge and water levels (r ≈ 0.982), while relationships between discharge and rainfall, and water levels and rainfall are moderate. Multiple regression analysis reveals water level significantly influences discharge (β ≈ 30.27, R² = 0.960). The study recommends implementing seasonal water management plans to address seasonal fluctuations, enhancing flood forecasting systems, adopting adaptive management strategies, investing in long-term monitoring and research, and promoting stakeholder collaboration. These measures aim to improve water resource management resilience, flood preparedness, and response capabilities in the face of climate variability and change.

Reconstructing the 1968 River Chew flash flood: merging a HEC-RAS 2D hydraulic modelling approach with historical evidence

The devastating 1968 flash flood in the River Chew, South-West of England, serves as a stark reminder of the unpredictable nature of such natural disasters and highlights the importance of natural hazard assessments. The uncertain and often incomplete historical data, and the limited field measurements at the time hindered our understanding of this event. By integrating historical evidence, including technical reports, newspapers, literature, and eyewitness accounts, with advanced hydraulic modelling (HEC-RAS 2D), this study reconstructs the 1968 flash flood. A sensitivity analysis of the computational methodologies in HEC-RAS, examining various governing equations and numerical methods, introduces an additional dimension to this research. The results verify a maximum flow rate of 165 m3/s at the Compton Dando hydrometric station, marking a 65% increase from the previous official estimate. This update aligns with over 90% of the historical flood marks observed. Findings suggest recalibrating hydrological models, revising risk assessments, and updating flood frequency analyses in the study area. This novel framework confronts the challenges of uncertain and incomplete historical records through a reverse engineering methodology to reconstruct missing peak discharges. The study also presents a new methodological blueprint that can be replicated for reconstructing historical flash flood events in various regions.

Hydraulic Reconstruction of Paleolandslide-Dammed Lake Outburst Flood Using Water–Sediment Mixture Flow Modeling: A Case Study of Xuelongnang, Upstream Jinsha River

Debris content plays an important role in controlling erosion capacity and sedimentation characteristics during outburst floods. Numerical models should incorporate sediments in hazard analyses to obtain more accurate assessments of outburst flood magnitudes and downstream behaviors. In this paper, we propose a novel water–sediment mixture flow model to reconstruct the ancient outburst floods at Xuelongnang and demonstrate the performance of this model through comparisons with field evidence. The simulated outburst flood reaches a maximum breach discharge of 10,697.35 m3/s and a peak sediment discharge of 65.29 m3/s, traveling downstream for 87 km within 5.43 h. Based on simulations of riverbed changes, inundation depth, velocity, shear stress, and Froude number, our findings suggest that topographic controls influence hydraulic patterns, which subsequently affect erosional and depositional processes and contribute to landscape evolution. During the downstream propagation of the outburst flood in narrowed valley sections, simulated sediment-simulated deposition occurs downstream while erosion occurs upstream, coinciding with the maximum inundation depths attributed to hydraulic jump phenomena. We also discuss the formation processes of the outburst deposits, identifying areas of greatest channel aggradation. Calculated bed shear stress suggests that sediment transport by the flood deposits on the riverbed decreases as the flood stage wanes, forming the rhythmite-interbedded structures observed in field investigations. This work provides a viable and promising approach to understanding hydro-sediment-morphodynamic processes in flood pathways and the erosional and depositional features left by outburst floods, supporting modern outburst flood hazard prevention and mitigation.

Flash flood dynamics in the foothills of the NW Himalayas: insights into hydrological and morphological controls.

The Himalayas experiences several cloudburst events due to its varied physiographical, geomorphological, and geological conditions and high rainfall. Uttarakhand is one of the Indian states circumscribed by the Himalayan ranges and has experienced a rise in the number of cloudburst catastrophes in the last few decades. These events cause substantial loss of life and property; however, very few studies have characterized these unpredictable cloudburst-induced flash floods in different regions of Uttarakhand. This study examines the geological and hydrological factors associated with the Raipur-Kumalda cloudburst event that occurred from 20 to 21 August 2022 in the Dehradun district of Uttarakhand. The resulting flash flood caused significant damage to roads, bridges, and settlements across the valley. The study aims to understand the geological and geomorphological controls of the event by analyzing the peak discharge and various flood parameters. The basin geomorphometry and rainfall intensity of the region reveal poorly developed drainage networks with low drainage density, steep slopes, rapid peak flows, a sharp peak hydrograph, and intense, concentrated rainfall, all of which worsen the impact of the flood. Various flood indices, including the rising curve gradient (K), flood magnitude ratio (M), and flood response time (TP), indicate a discharge 50 to 100 times higher during the event compared to the average monsoonal discharge. This study also discusses the role of mountain topography, climate, regional geology, and irreversible land use-land cover (LULC) changes associated with urbanization in intensifying the destruction.

Exploring the Impact of Nature-Based Solutions for Hydrological Extremes Mitigation in Small Mixed Urban-Forest Catchment

Many regions in Europe face increasing issues with flooding and droughts due to changing rainfall patterns caused by climate change. For example, higher rainfall intensities increase urban flooding. Nature-based solutions (NbS) are suggested as a key mitigation strategy for floods. This study aims to address and mitigate the challenges faced in Tivoli natural park in Ljubljana regarding high peak discharges and low-flow issues in the creek entering the sewer system. The study involves setting up, calibrating and validating a Hydrologic Engineering Centre–Hydrologic Modelling System (HEC-HMS) model using available data. This study analyses NbS, such as small ponds, green roofs and permeable paving, to reduce peak discharge. Runoff was reduced by an average of 32.4% with all NbS implemented and peak discharge by 20 L/s. Permeable parking performed best, with an average runoff reduction of 6.4%, compared to 4.8% for permeable streets and 5.9% for green roofs. The ponds reduced peak discharge, although their effectiveness varied between rainfall events. Rainfall events with higher volumes and durations tended to overwhelm the proposed solutions, reducing their effectiveness. The ability of HEC-HMS to model NbS is also discussed. The curve number (CN) parameter and impervious % alterations to simulate NbS provided quantitative data on changes in runoff and discharge.

Flood analysis using the HEC-RAS software for Antakya Altınçay Creek

Flood is one of the most important disasters in the world. Floods, common in our country, are the second disaster after the earthquake in terms of loss of life and property caused by natural disasters and the first among climatic disasters. The district of Antakya is located where streamflow has a high flow coefficient. Because of flooding in Altınçay Creek which flows through the center of Antakya into the Orontes River, flood studies need to be carried out and the necessary precautions taken to prevent flooding. In this study, peak discharges for 2, 5, 10, 25, 50, and 100-year return periods of Altınçay Creek passing through residential areas in Antakya were determined by SCS and DSI synthetic methods. Using these estimated peak discharges the water profile along the Altınçay Creek route has been simulated using HEC-RAS software, and the flood risk areas were determined on cross-sections basis. As a result, flood risk was not observed in peak discharge for return periods of 2, 5 and 10 years. However, flood events were observed at 16, 51, and 73 different cross sections in peak discharges for return periods of 25, 50, and 100 years respectively. To reduce flood damage, it was suggested that the cross-sectional areas having flood risk must be increased.

Post-Disaster Engineering Strategy for Anai River Debris Flow Management on Anai Valley National Road West Sumatra Indonesia

One of the causes of flash floods is eruption material from Mount Marapi that is carried downstream, disrupting transportation access and the local economy. This study aimed to design and implement an effective post-disaster engineering strategy for debris flow management in the Anai River and evaluate its long-term success. Data were collected through field observations to measure river profiles, photogrammetry, and sediment sampling. Secondary data were used to calculate rainfall intensity and flood discharge in the Anai River to plan debris flow control. The study results showed that the large catchment area and high rainfall contributed significantly to the high peak discharge. Disturbed soil samples taken from the river surface were saturated, indicating the influence of sediment from the debris flow from the eruption of Mount Marapi. The removal of material from the riverbed needs to be controlled to avoid overexploitation that could exacerbate erosion of the riverbanks, ultimately threatening bridge structures and other infrastructure along the Anai River. To overcome this problem, it is necessary to build sediment control structures such as check dams and groundsills, as well as secure riverbanks in the management of debris flows in the Anai River.

Active Sites Regulation and Mass Production of a Hierarchically Porous Fe-N-C Catalyst for Zinc-Air Batteries.

Although the iron-nitrogen-carbon (Fe-N-C) catalyst has great potential in zinc-air batteries (ZABs), the insufficient performance and low production of the Fe-N-C catalyst are still the key factors that greatly limit the commercial application. In this study, first, a simple dual melt-salt template method is developed to prepare the hierarchically porous HPFe-N-C catalyst with abundant highly stable Fe-pyridinic-N sites. Then, HPFe-N-C and Fe-phenanthroline are mixed and heated for the mass production of THPFe-N-C with rich highly active Fe-pyrrolic-N sites. Under the synergistic effect of the different active sites, THPFe-N-C exhibits better activity and stability of oxygen reduction reaction (ORR) than Pt/C. Density functional theory is utilized to reveal the changing of the free energy for the ORR process of active sites. COMSOL multiphysics simulations are used to prove that the hierarchically porous THPFe-N-C is beneficial to the O2 mass-transfer process. Therefore, THPFe-N-C shows a better discharge performance and peak power density than Pt/C in the ZABs.

Storylines of extreme precipitation events and flood impacts in alpine and pre-alpine environments under various global warming levels

Exploring the impacts of extreme weather events has gained increased attention in recent years after repeated record-breaking events, such as unprecedented river flood events in central Europe in summer 2021. After the flood event, risk management institutions, such as for example, fire brigades, civil protection units, or natural hazard experts asked if it was possible to predict the impacts of such an unprecedented event ex-ante and if similar events could occur elsewhere or if climatic changes can even worsen extreme flood events. Here, we present an approach to explore storylines of physically plausible extreme river flood events in a warming climate. The simulated flood events are based on extreme precipitation events selected from re-forecast archives. River discharge, flood processes, and their impacts on people and infrastructure are simulated for nine storylines under five global warming levels for the alpine and pre-alpine headwater catchments of the main rivers in northern Switzerland. The precipitation intensity was increased linearly with global warming according to the Clausius-Clapeyron relation. The coupled hydrological-hydraulic simulations show that the increase in peak discharge is higher than the increase in precipitation. The flood impacts increase non-linearly with higher global warming levels. The results show that record-breaking, high-impact river floods are possible under the current atmospheric conditions, and climate change substantially aggravates flood impacts. The simulations show a broad range of potential outcomes of flood impact storylines depending on the simulated scenario and local conditions. This leads to the conclusion that storylines of extreme flood events are a valuable tool to explore, describe, and communicate extreme events. Still, the inherent challenge is the communication of the representativeness of a particular storyline and, hence, the practical consequences that should or should not be derived. We, therefore, suggest considering storylines of events with a range of magnitudes and different spatiotemporal precipitation patterns to comprehend the possible range of outcomes and select appropriate storylines out of the set for risk communication.

A New Method for Analyzing Storm Event Discharge‐Concentration Hysteresis: The Upper Yangtze River as an Example

AbstractThe analysis of hydrological and sediment dynamics during flood events offers a new perspective on material transport within basins and the management of rivers. The literature has highlighted the hysteretic nature of material transport at the event scale, which arises from temporal differences in the transport of materials (flow and sediment). Current hysteresis research methods fall short in effectively assessing the complex events. This study leverages suspended‐sediment and discharge data from the upper Yangtze River to show proof‐of‐concept for hysteresis studies using Dynamic Time Warping (DTW) algorithm, a time series analysis tool. To evaluate the efficacy of the method, extensive assessments were undertaken using a combination of synthetic data and basin data with over 700 flood events. The proposed index effectively captures and quantifies hysteresis relationships associated with flood events, making it a versatile tool for hysteresis studies. We also similarly tested the robustness of the method and the application to complex events, and the results were satisfactory. Furthermore, we explored the hysteretic features of flood events in the studied basin. The results revealed that a proportion ranging from 50% to 60% flood events exhibit sediment peak leading pattern, indicating that in the upper Yangtze River, sediment peaks tend to occur in a leading pattern. The operation of reservoirs profoundly impacts the dynamics of sediment transport, resulting in an increased proportion (from 27% to 54%) of sediment peaks lagging behind discharge peaks. These study findings can be used to improve hysteresis study methods and contribute to the understanding of hydrological and sediment transport characteristics.

Mapping a Novel Metric for Flash Flood Recovery Using Interpretable Machine Learning

Abstract Flash floods are one of the most devastating natural disasters, yet many aspects of their severity and impact are poorly understood. The recession limb is related to postflood recovery and its impact on communities, yet it remains less documented than the rising limb of the hydrograph to predict the peak discharge and timing of floods. This work introduces a new metric called flash flood recovery or recoveriness, which is the potential for recovery of a watershed to preflood conditions. Using a comprehensive database of 78 years and supervised machine learning algorithms, flash flood recovery is mapped in the conterminous United States. A suite of geomorphological and climatological variables is used as predictors to provide probabilistic estimates of recoveriness. Slope index, river basin area, and river length are found to be the most significant predictors to predict recoveriness. Several new localized hotspots were identified, such as the western slopes of the Appalachians consisting of Kentucky, Tennessee, and West Virginia and the interlinked areas of western Montana and northern Idaho. This new metric can be useful for prioritizing relief and rehabilitation efforts as well as precautionary measures for disaster risk reduction.

Effects of Environmental Changes on Flood Patterns in the Jing River Basin: A Case Study from the Loess Plateau, China

Human activities and climate change have significantly influenced the water cycle, impacting flood risks and water security. This study centers on the Jing River Basin in the Chinese Loess Plateau, analyzing hydrological patterns and flood progression using the HEC-HMS model under changing conditions. The findings indicate that climate change substantially affects flood predictions, increasing peak flows and volumes by up to 10.9% and 11.1%, respectively. It is essential to recognize that traditional flood models may underestimate the risks posed by these changes, emphasizing the necessity for updated methods incorporating climatic and human factors. Changes in land use, such as the expansion of grasslands and forests, have reduced peak discharges and flood volumes. Consequently, the combined impacts of climate and land use changes have intensified flood frequencies, necessitating updated strategies to manage risks effectively. The dynamics of flooding are significantly impacted by changes in climate and land use, particularly in minor floods that occur frequently, highlighting the influence of climate change on flooding trends. Within the Jing River Basin, hydrological patterns have been shaped by both climatic variations and human activities, leading to an increase in extreme hydrological events and concerns regarding water security. Using the HEC-HMS model, this study examines the hydrology of the Jing River Basin, focusing on the design of storm events and analyzing various flood characteristics under different scenarios. Climate change has resulted in higher peak discharges and volume surges ranging from 6.3% to 10.9%, while shifts in land use, such as decreases in farmland and the expansion of grasslands, have caused declines ranging from 7.2% to 4.7% in peak flows and volumes. The combined effects of climate variation and land utilization have complex implications for flood patterns, with milder to moderate floods showing a more significant impact and shorter return periods facing increased consequences. These findings underscore the interconnected nature of climate change, land use, and flooding dynamics in the Jing River Basin, highlighting the need for comprehensive strategies to address these challenges and ensure sustainable water management in the region.

The vulnerability of buildings to a large-scale debris flow and outburst flood hazard cascade that occurred on 30 August 2020 in Ganluo, southwest China

Abstract. In mountainous areas, damage caused by debris flows is often aggravated by subsequent dam-burst floods within the main river confluence zone. On 30 August 2020, a catastrophic disaster chain occurred at the confluence of the Heixiluo Gully and Niri River in Ganluo County, southwest China, consisting of a debris flow, the formation of a barrier lake, and subsequent dam break that flooded the community. This study presents a comprehensive analysis of the characteristics of the two hazards and the resulting damage to buildings from the cascading hazards. The peak discharge of the debris flow in the gully mouth reached 1871 m3 s−1. Following the dam break, the flood with a peak discharge of 2737 m3 s−1 significantly altered the main river channel, causing a 4-fold increase in flood inundation compared to an ordinary flood. Three hazard zones were established based on the building damage patterns: (I) primary debris flow burial, (II) secondary dam-burst flood inundation, and (III) sequential debris flow burial and dam-burst inundation. Vulnerability curves were developed for Zone (II) and Zone (III) using impact pressures and inundation depths, and a vulnerability assessment chart is presented that contains the three damage categories. This research addresses a gap in the vulnerability assessments of debris flow hazard cascades and can support future disaster mitigation within confluence areas.

Probabilistic assessment of peak discharge and debris flow concentration in the Surma River using Monte Carlo simulation

ABSTRACT Rivers, vital for household and industrial needs, vary in size due to erosion and sedimentation and are significantly impacted by climate variations. Accurate estimation of river characteristics like discharge and debris flow concentration is essential for designing hydraulic systems in flood-prone areas. This study assesses these factors in the Surma River, located in Sylhet, Bangladesh, by using Monte Carlo simulation to reduce uncertainty. The simulation optimized the time of concentration against water level height. Peak discharge results for 5, 10, 25, 50, and 100-year return periods were 1,904.66, 2,174.77, 2,543.63, 2,846.72, and 3,124.25 m3/s, with corresponding debris flow concentrations (Cv) of 0.5499989, 0.5499976, 0.5499967, 0.5499940, and 0.5499147. During the monsoon season, the maximum peak discharge reached 5,095.58 m3/s with a Cv of 0.7886368. Model validation using the F test and R2 test demonstrated high accuracy, indicated by low mean squared error (MSE), mean absolute error (MAE), and root mean square error (RMSE), along with a coefficient of determination (R2) of 0.7097. The p-value from the F test (0.197852) indicated strong alignment between predicted and observed discharges. This study enhances understanding of flow dynamics, improves prediction precision, and underscores the importance of historical data in flood risk assessment.