Peak Discharge Values Research Articles

Flash Flood Risk Assessment in the Asir Region, Southwestern Saudi Arabia, Using a Physically-Based Distributed Hydrological Model and GPM IMERG Satellite Rainfall Data

Floods in southwestern Saudi Arabia, especially in the Asir region, are among the major natural disasters caused by natural and human factors. In this region, flash floods that occur in the Wadi Hail Basin greatly affect human life and activities, damaging property, the built environment, infrastructure, landscapes, and facilities. A previous study carried out for the same basin has effectively revealed zones of flood risk using such an approach. However, the utilization of the HEC–HMS (Hydrologic Engineering Center–Hydrologic Modeling System) model and IMERG data for delineating areas prone to flash floods remain unexplored. In response to this advantage, this work primarily focused on flood generation assessment in the Wadi Hail Basin, one of the major basins in the region that is frequently prone to severe flash flood damage, from a single extreme rainfall event. We employed a fully physical-based, distributed hydrological model run with HEC–HMS software version 4.11 and Integrated Multi-satellite Retrievals of Global Precipitation Measurement (IMERG V.06) data, as well as other geo-environmental variables, to simulate the water flow within the Wadi Basin, and predict flash flood hazard. Discharge from the wadi and its sub-basins was predicted using 1 mm rainfall over an 8-h occurrence time. Significant peak discharge (3.6 m3/s) was found in eastern and southern upstream sub-basins and crossing points, rather than those downstream, due to their high-density drainage network (0.12) and CNs (88.4). Generally, four flood hazard levels were identified in the study basin: ‘low risk’, ‘moderate risk’, ‘high risk’, and ‘very high risk’. It was found that 43.8% of the total area of the Wadi Hail Basin is highly prone to flooding. Furthermore, medium- and low-hazard areas make up 4.5–11.2% of the total area, respectively. We found that the peak discharge value of sub-basin 11 (1.8 m3/s) covers 13.2% of the total Wadi Hail area; so, it poses more flood risk than other Wadi Hail sub-basins. The obtained results demonstrated the usefulness of the methods used to develop useful hydrological information in a region lacking ungagged data. This study will play a useful role in identifying the impact of extreme rainfall events on locations that may be susceptible to flash flooding, which will help authorities to develop flood management strategies, particularly in response to extreme events. The study results have potential and valuable policy implications for planners and decision-makers regarding infrastructural development and ensuring environmental stability. The study recommends further research to understand how flash flood hazards correlate with changes at different land use/cover (LULC) classes. This could refine flash flood hazards results and maximize its effectiveness.

Improved general unit hydrograph model for dam-break flood hydrograph

Dam breaks pose significant risks, necessitating simple and effective predictive models for disaster management. This study aims to enhance the understanding of dam-break flood hydrographs, an aspect less emphasized in traditional research focusing mainly on peak discharge and flow depth values. Employing a series of experiments, an improved general unit hydrograph model was used to analyze both discharge and flow depth hydrographs. This model is then critically compared with the standard gamma and log-normal asymmetric distribution models. The results reveal that the improved unit hydrograph model significantly outperforms these traditional models, particularly in predicting the rising stage of discharge hydrographs, evidenced by a 65 % reduction in root mean square error. Comparison of this model with real dam failures in natural river valleys shows its potential to be applied to changes in river slope and different dam-break rates. These advancements present a more precise methodology for predicting dam-break flood hydrographs, offering benefits for disaster management strategies.

Evolution of the Pingluo Section of the Upper Yellow River over the Past 50 Years: Responses to Environmental Change and Human Activity

The instability of the river channels has increased in response to the combined effects of global warming and human activity. This instability threatens the lives and property of people who live along river courses. This study takes the Pingluo section of the upper Yellow River, which is ~28 km long and ~400 m wide, as its research focus. We studied 11 periods of Landsat remote sensing images from 1973 to 2023 and analyzed the evolutionary characteristics of the Pingluo section over the past 50 years. The channel morphology indices included the channel braiding index (BIT), the bar braiding index (BIB), the average area of the bar (Ab), and the width of the wet channel area (BW). The results showed that there was an overall shrinking trend in this section of the Yellow River; more particularly, fluctuations in indicators such as the river width and the braiding index highlighted an increasing–decreasing–increasing pattern of change. During the 1973–1986 period, the river showed a widening trend, with narrow anabranches cutting through the floodplain and both the river width and the braiding index increasing dramatically over a short period. Over the 1986–2018 period, the area of the wet channel continued to shrink to its lowest level for the past 50 years, the river’s branches were diverted and abandoned, and the channel tended to straighten out. Between 2018 and 2023, the river showed a slightly expanding trend. The evolution of the river channel appears to be related to regional human activity and climate change. For example, after the joint filling of the Longyangxia and Liujiaxia reservoirs in the upper reaches of the Pingluo section of the Yellow River in 1986, runoff and sediment load along this section decreased, flood events became less frequent, and the channel tended to contract. In addition, the increase in extreme precipitation events over the last five years has led to an increase in the magnitude and frequency of peak discharge values in the region, which is the main reason for the increase in the river braiding index and area.

A complete methodology to assess hydraulic risk in small ungauged catchments based on HEC-RAS 2D Rain-On-Grid simulations

This paper explores the use of the rain-on-grid (or direct rainfall) method for flood risk assessment at a basin scale. The method is particularly useful for rural catchments with small vertical variations and complex interactions with man-made obstacles and structures, which may be oversimplified by traditional hydrologically based estimations. The use of a hydrodynamic model solving mass and momentum conservation equations allows the simulation of runoff over the watershed at a basin scale. As a drawback, more detailed and spatially distributed data are needed, and the computational time is extended. On the other hand, a smaller number of parameters is needed compared to a hydrological model. Roughness and rainfall loss coefficients need to be calibrated only. The direct rainfall methodology was here implemented within the two-dimensional HEC-RAS model for the low-land rural, and ungauged, watershed of the Terdoppio River, Northern Italy. The resulting hydrographs at the closing section of the watershed were compared to synthetic design hydrographs evaluated through pure hydrological modelling, showing agreement on the peak discharge values for the low-probability scenarios, but not on the total volumes. The results in terms of water depth and flow velocity maps were used to create flood hazard maps using the Australian Institute for Disaster Resilience methodology. The Index of Proportional Risk model was then adopted to generate a basin-scale flood risk map, by combining flood hazard maps, damage functions for different building-use classes, and the value of reconstruction and content per unit area.

Selecting the accurate hydrological method for estimating peak discharge in the Lesti River Catchment Area, Malang Regency, East Java Province, Indonesia

Estimating peak discharge in the catchment poses a challenge for hydrologists due to the potential overflow risks. The present study examined various methods, including Synthetic unit hydrograph, Melchior, and Rational, to determine the peak discharge value in the Lesti River Catchment Area. Accurate hydrological input data is essential for effectively estimating peak discharge and mitigating potential damage or failure. Optimized physical parameters using geographic information systems are critical in generating peak discharge values, emphasizing their importance in the estimation process. The mean absolute percentage error (MAPE) and mean average error (MAE) were used to determine the accurate method for estimating peak discharge. Analysis results showed varied peak discharge values across different methods, and it found that the MAPE values ranged from 15.15% to 7.48% and the MAE values ranged from 1.47% to 0.63%, respectively. The Nakayasu synthetic unit hydrograph obtained the minimum error measure value compared to other methods by 7.48% in MAPE and 0.63% in MAE. Therefore, the MAPE and MAE performance considered that the Nakayasu was closely approximating the observed peak discharge and a relatively accurate method for estimating peak discharge in the Lesti River catchment area.

Towards improved knowledge about water-related extremes based on news media information captured using artificial intelligence

Recent advances in machine learning have enabled near real-time retrieval of information from textual documents impacting a wide range of knowledge domains. This advantage makes of the insight extracted from text-based documents (e.g., reports and news) on water-related events an invaluable source of information that complements traditional approaches. By leveraging machine learning, we can not only characterize the event and determine its magnitude or phases of extreme weather event, but also identify its core elements. This is especially crucial in the current era of climate change, where extreme weather events such as floods or thunderstorms are becoming more frequent and unpredictable. By improving our ability to detect and analyse such events, we can enhance our alert systems and take more effective action to mitigate their impact. In this paper we discuss the role of worldwide media observation in extracting and estimating hydrological characteristics of floods, droughts, and heat waves, through the analysis of three case studies, complementing the information provided by traditional monitoring and measurement methods as an earlier but weaker signal. The results presented in this study indicate that the news media signal can be regarded as relatively good proxy of flood dynamics. It can capture the temporal dynamics of the event, and, in some cases, there could be a clear up to 1-day lag between the peak discharge values (i.e., the most extreme flood situation) and the peak in the number of published news. This lag can be attributed to the time needed by journalists to respond to the situation in publishing related news articles covering the event. Our result show that national and regional news can cover well local events. When compared to floods, drought conditions are less explicitly detected from the media. Our result show that European April 2022 drought did not produce much activity in the media while the combination of drought and extreme heat in July 2022 yielded a significant media coverage throughout the Europe. Hence, this can be attributed to the fact that hydrological drought such as low river flows do not attract much attention by the media unless there is a significant impact on the society. Therefore, media signal can be regarded as a relatively good proxy of the hydro-meteorological conditions in case there is a significant impact on the society such as extreme floods causing many casualties and large economic damage.

Flood Simulation Using HEC-HMS 4.8 for Ungauged Catchment During Extreme Events in Lui River, Hulu Langat

Flooding is a sort of natural disaster that can occur anywhere in the world. It is also happening more often now because of global warming and climate change. The Department of Irrigation and Drainage (DID) has designated certain sites along the Lui River in Hulu Langat as flood-prone. Therefore, this study presents a hydrological simulation of the Lui River utilising the flood management software on the Hydrologic Modelling System, HECHMS 4.8, which has been widely used in several studies of water management. The program replicates a river basin system's rainfall-runoff response to a precipitation input by modelling the whole river basin as an integrated system of hydrologic and hydraulic components, displaying the trends in the river's flow for 50 ARI and 100 ARI. The hydrograph of the Lui River may be determined by examining the rainfall-runoff relationship and comparing it to the peak discharge of observed data and the hydrograph for an unmeasured watershed from Hydrological Procedure No. 11. The hydrograph result must undergo model calibration to establish parameters that are validated for the model final value of peak discharge and the shape of the hydrograph. The finding shows that the optimal design hydrograph for the design stage is the model's hydrograph with the greatest peak as in HEC-HMS. Hence, the design storm with the largest output will serve as a guideline for any design matter, be valuable for future river flow research, and function as a future precaution.

Hydrologic Evaluation of the Global Precipitation Measurement Mission over the U.S.: Error Budget Analysis

This study investigates the hydrologic utility of satellite precipitation estimates from the Global Precipitation Measurement mission by comparing flood signals produced across the Continental United States by a ten-year span of in-situ, ground-based radar and satellite-based precipitation data. The flood characteristics generated with radar and satellite precipitation through a distributed hydrologic model are contrasted against reference stream gauge data as a method of integrated validation to assess and quantify error budgets between precipitation products by highlighting precipitation products’ accuracy, hydrologic scaling effects, and the impact of the hydrologic model. It is found that systematic and random errors associated with flood characteristics behave similarly to trends previously seen in precipitation rate errors between precipitation products, establishing a clear link through propagation of errors into the water cycle. Additionally, behaviors associated with both water balance and routing schemes within the hydrologic model were shown to affect outputs. Errors generated by water balance tend to cause overestimation of peak discharge values, while errors associated with routing tend to cause underestimation of flood durations and push flood timings earlier than the stream gauge reference.

Development of decomposition-based model using Copula-GARCH approach to simulate instantaneous peak discharge

Estimation of instantaneous peak discharge is important in the design of hydraulic structures and reservoir management. In this study, a new approach called CEEMD-Copula-GARCH is presented for simulating instantaneous peak discharge in the Qale Shahrokh basin, upstream of Zayanderood Dam, Iran. In the developed method, the Complementary ensemble empirical mode decomposition (CEEMD) algorithm was used to analyze the observed values and generate the intrinsic mode function values and residual series. For this purpose, the intrinsic mode function values were simulated based on vine copula and its tree sequence (C-vine, D-vine, R-vine and their independent and Gaussian modes), and the residual series of the CEEMD algorithm were simulated by the GARCH model. The results of simulating instantaneous peak discharge values (m3/s) using the CEEMD-Copula-GARCH approach in the study area showed that the amount of simulation error based on the RMSE statistic compared to the CEEMD-Copula model and simulation without decomposition has improved by about 20 and 70%, respectively. The model’s efficiency was also estimated based on the Nash–Sutcliffe efficiency in the proposed approach of 0.99, and the certainty of the proposed approach was also confirmed based on the presented violin plot. According to the presented results, the proposed approach has high accuracy and efficiency in the simulation of instantaneous peak discharge (m3/s), which can be used in the flood control system design and flood management. Using the methodology proposed in this study, multivariable models can be used in simulating univariate series with high accuracy.

Estimation of expected peak discharge and flood volume of the Heliopolis basin, East Cairo, Egypt, using RS and WMS program

In recent years, rainfall-induced floods in various Egyptian towns affected several regions, and the area in east Cairo was the worst. The present study aims to detect the rainfall-runoff relationships of the Heliopolis watershed and its sub-basins, to estimate peak discharge and flood volume for the storm event (12 March 2020) and predicting the runoff volume and peak discharge of the flows for various return intervals. This was achieved by applying the Hydrological models (HEC-1and HMS) program using a unit Hydrograph namely SCS-CN. The drainage system and the identification of sub-basinswere established using SRTM DEM, 90 m resolution. The maximum daily rainfall per year was investigated and determined for various return times using the statistical analysis tool Hyfran. Results reveal that the peak discharge (Qp) and flood volume value (Qv) of the Heliopolis watershed are 686.8 m3/s and 48039.8 m3, respectively. The obtained results for the various recurrence times during the regression periods of 5 and 100 years, reveal that the peak flood inflow of the Heliopolis basin ranged between 19.47 and 742.16 m3/s and the flood volume ranged between 1,295,110 and 53,752,968 m3. This shows that these valleys move a significant volume of water to be released into the mainstream. The recognition and forecasting of the degree of dangerous rain events can help planners and decision-makers in finding flooded areas before the future development of the new settlements.

Kajian Pengaruh Pelebaran Sungai terhadap Debit Aliran

Flood is one of the problems that often occurs in Indonesia. In Jambi City, every rainy season often experiences flooding, especially in Jambi City or the Garuda III Jaya Complex area, Bagan Pete Village, Jambi City. Thus, this study aims to determine how much rainfall intensity is on the Kenali Besar River and how much river flood discharge has been carried out at Komplek.Perum Garuda III Jaya, Bagan Bete Village, Jambi City with a time of 10 years and so that later the Kenali Besar River channel can be channeled. can function optimally to reduce flooding that occurs in the Garuda III Jaya Complex area, Bagan Pete Village, Jambi City, so that a good and quality river is created while taking into account the safety and comfort factors for the surrounding community. In this study, the data used were secondary data in the form of daily rainfall for 10 years and cross-sectional dimension data of the Kenali Besar River Komplek.Perum Garuda III Jaya, Bagan Pete Village. The results of the calculation of the planned rain with a return period of 10 years is 246.469 mm⁄hour, while the planned discharge using the Rational method obtained a peak discharge value of 30.833 m3⁄seconds the step is continued using HEC-RAS 5.0.7 software to determine the capacity of the drainage channel by using plan debit. After being analyzed using software.

Extreme freshwater discharge events exacerbated by climate change influence the structure and functional response of the chironomid community in a biodiversity hotspot

Global climate change is expected to exacerbate extreme discharge events in freshwater ecosystems as a consequence of changes in precipitation volume and snow cover duration. Chironomid midges were used as a model organism in this study because of their small size and short life cycles, which enable fast colonization of new habitats and great resilience. This resilience is often expressed in easy recolonization after an extreme event. Chironomid samples together with physico-chemical water measurements were collected for 14 years, between 2007 and 2020, in a karst tufa barrier that is part of the Plitvice Lakes National Park in Croatia. More than 13,000 individuals belonging to >90 taxa were collected. Mean annual water temperature increased by 0.1 °C during this period. Multiple change-point analysis revealed three main periods by discharge patterns: the first one from January 2007 to June 2010, the second from July 2010 to March 2013, characterised by extreme low discharge, and the third from April 2013 to December 2020, characterised by an increase in extreme peak discharge values. Based on multilevel pattern analysis, indicator species of the first and the third discharge period were detected. The ecological preferences of these species indicate an environmental change related to the changes in discharge. Along with species composition, functional composition has changed with the abundance of passive filtrators, shredders and predators increasing over time. Species richness and abundance did not change over the period of observation, thus emphasizing the importance of species-level identification in detecting the earliest community response to change that would otherwise be overlooked.

Study of Dam-Break Flow Over a Vegetated Channel With and Without a Drop

The effects of a drop in a vegetated channel on the flow characteristics during a dam failure were investigated using a numerical approach. A CFD package was used for all dam failure simulations. After performing validation tests, the model was used to predict the flow characteristics during a dam failure over a vegetated channel with positive, negative, or no drop. A positive drop resulted in a backflow into the reservoir with a negative discharge of Qbackflow = − 0.01 m3/s. Even in the channel with no drop, backflow into the reservoir occurred in the last stage due to the drag effect of the vegetation. The maximum discharge occurred at the peak time tpeak = 2.5 s above the drop for all models. The peak discharge decreased from Qpeak = 0.037 m3/s to Qpeak = 0.032 m3/s with increasing positive drop height. However, a negative drop had no significant effect on peak discharge values. In most cases, the maximum flow velocity was around um = 2 m/s. The maximum eddy values decreased by Δωmax = 500 1/s for the positive drops and increased by Δωmax = 700 1/s for negative drops at the middle stage.

Analisa Kapasitas Drainase Untuk Menanggulangi Banjir Pada Perumahan Kembar Lestari 1 Jambi

In the city of Jambi, there are still various places that experience puddles or floods during high rainfall which results in drainage channels being unable to accommodate excess water. Drainage is very important to cope with flooding, one of which is in residential areas, especially in the Kembar Lestari 1 Jambi Housing area, Kenali Besar Village, Jambi City. Thus, this study aims to re-analyze the condition of the drainage channel at the Jambi City Kembar Lestari 1 Housing and find out the existing condition of the drainage channel at the 1 Jambi Sustainable Twin Housing and redesign the optimal drainage channel capacity so that later the Kenali Besar River channel can function optimally to reduce flooding that causes flooding. occurred in the Kembar Lestari 1 Housing area, Kenali Besar Village, Jambi City, so that a good and quality river was created while still taking into account the safety and comfort factors for the surrounding community. In this study, the data used is secondary data in the form of daily rainfall for 10 years and cross-sectional dimension data of the drainage channel of the Kembar Lestari 1 Housing Village, Kenali Besar. The results of the calculation of the planned rainfall with a return period of 10 years is 75.795 mm⁄hour, while the planned discharge using the Rational method is obtained a peak discharge value of 9.399 m^3⁄seconds, the steps are followed by using HEC-RAS 5.0.7 software to determine the capacity of the drainage channel by using plan debit.

Flood Hazard Assessment of Water-Front Geosynthetic Reinforced Soil Wall for Dam Regulation Rule Level

The flood hazard parameter of peak discharge and prolonged inundation due to change in dam regulation is estimated for a water front Geosynthetic Reinforced Soil (GRS) wall on the downstream of large dam. Dam regulation rule level is pre-emptying the reservoir with lower peak discharge to protect the expanding downstream city intruding the flood plain. Present study is to test the hypothesis that rule level has significantly changed peak discharge and inundation duration and also to estimate these two important parameters of flood hazard for different flood return periods. The methodology consists of three parts: first is the categorization of flood data according to major event of flood regulation, second is the distribution test and third is the estimation of design maximum peak discharge and duration of flood. The estimated value of peak discharge and flood duration clearly indicate the implication of dam regulation rule level; the estimated value of peak discharge for 200 years return period is 13.9 lakh Cusecs, which is lower than the flood discharge for year 1968, which was 15 lakh Cusecs, and the estimated flood duration for 10 years return period is 41 days. The most important finding of this study is the substantial increase in duration of flood due to implementation of rule level which will add one more flood hazard parameter for water front geotechnical structure that is prolonged inundation.

Application of Machine Learning and Process-Based Models for Rainfall-Runoff Simulation in DuPage River Basin, Illinois

Rainfall-runoff simulation is vital for planning and controlling flood control events. Hydrology modeling using Hydrological Engineering Center—Hydrologic Modeling System (HEC-HMS) is accepted globally for event-based or continuous simulation of the rainfall-runoff operation. Similarly, machine learning is a fast-growing discipline that offers numerous alternatives suitable for hydrology research’s high demands and limitations. Conventional and process-based models such as HEC-HMS are typically created at specific spatiotemporal scales and do not easily fit the diversified and complex input parameters. Therefore, in this research, the effectiveness of Random Forest, a machine learning model, was compared with HEC-HMS for the rainfall-runoff process. Furthermore, we also performed a hydraulic simulation in Hydrological Engineering Center—Geospatial River Analysis System (HEC-RAS) using the input discharge obtained from the Random Forest model. The reliability of the Random Forest model and the HEC-HMS model was evaluated using different statistical indexes. The coefficient of determination (R2), standard deviation ratio (RSR), and normalized root mean square error (NRMSE) were 0.94, 0.23, and 0.17 for the training data and 0.72, 0.56, and 0.26 for the testing data, respectively, for the Random Forest model. Similarly, the R2, RSR, and NRMSE were 0.99, 0.16, and 0.06 for the calibration period and 0.96, 0.35, and 0.10 for the validation period, respectively, for the HEC-HMS model. The Random Forest model slightly underestimated peak discharge values, whereas the HEC-HMS model slightly overestimated the peak discharge value. Statistical index values illustrated the good performance of the Random Forest and HEC-HMS models, which revealed the suitability of both models for hydrology analysis. In addition, the flood depth generated by HEC-RAS using the Random Forest predicted discharge underestimated the flood depth during the peak flooding event. This result proves that HEC-HMS could compensate Random Forest for the peak discharge and flood depth during extreme events. In conclusion, the integrated machine learning and physical-based model can provide more confidence in rainfall-runoff and flood depth prediction.

A hybrid artificial intelligence and semi-distributed model for runoff prediction

Abstract Hydrological simulations perform a vital role in river discharge forecasts, which is very essential in water resources engineering. The present study has been carried out using a semi-distributed model developed using HEC-HMS, an artificial neural network (ANN), and a hybrid model (HEC-HMS-ANN) for simulation of daily discharge in the Kallada River basin, Kerala, India. The HEC-HMS model did not perform well with the available dataset. So for simulating daily runoff, a hybrid model is developed by coupling HEC–HMS output with ANN. The model prediction accuracy is assessed using statistical metrics. Precipitation, lagged precipitation, and lagged discharge were used as input variables for the ANN model. The optimal number of lags was determined using partial autocorrelation. The hybrid model integrating the output from HEC-HMS into ANN shows better performance than the other models in simulating daily discharge and estimating the accuracy of yearly peak discharge. The accuracy evaluation of yearly peak discharge values demonstrates that simulation error is reduced by 66% and 26.5% in the hybrid model compared to the HEC-HMS and ANN models, respectively.

Effects of Urban Development on Regional Climate Change and Flood Inundation in Jakarta, Indonesia

Flood risks associated with changes in land use and climate are a common concern, especially in relation to their potential effects on many cities around the world. Jakarta is a typical urbanized Asian city in Indonesia where flooding presents a consistent challenge. This study aimed to quantify the effects of land use and climate change using a flood inundation model to analyze future urban growth and climate change scenarios. The projected rainfall data of RCP2.6-SSP1 and RCP8.5-SSP3, based on the WRF simulation, were used as inputs for rainfall-runoff and flood inundation simulations in Jakarta. In addition, RCP2.6 and RCP8.5, without urban development scenarios, were investigated to determine the effects of urbanization in Jakarta. The results showed that rainfall intensity, peak discharge, and flood inundation generally increased in the high RCP and SSP future scenarios. Significantly, the RCP2.6-SSP1 scenario showed a higher peak discharge value than RCP8.5, owing to the combination of land-use change and increased rainfall. We conclude that the effects of urban development on atmospheric and runoff processes should be considered in climate change studies in urban areas.

Coupled hydrodynamic modelling approach to assess land use change induced flood characteristics.

MIKE 11 rainfall-runoff model and MIKE 21 overland flow model were successfully coupled in the MIKE FLOOD platform for flood simulation in Gin catchment (932 km2) of Sri Lanka to assess land use change induced changes in flood discharge. MIKE 11 Nedbør-Afstrømings-Model (NAM) rainfall-runoff simulation depicted a good agreement with the observed discharge at Thawalama and Baddegama gauging stations. MIKE FLOOD, validated against the two major flood events that occurred in May 2003 and in May 2017, showed a reasonable agreement with the observed water depths and peak discharge values displaying more than 70% goodness of fit between the observed and simulated inundated extents. Dominant land use change processes in the catchment between 1999 and 2016 were identified as the forest area and built-up land expansion at the expense of agricultural land and bare land which possessed contradictory impacts on flood generation. The impact of a single factor, 17-year land use change, on flood formation was differentiated. In the upstream sub-catchment having 490 km2, despite a 0.74% increase in the built-up land, 2.85% increase in the forest area had significantly contributed to mitigate the overall flood formation with 34% and 40% reduction in the peak discharge and the flood volume, respectively. Overall reduction of the flood discharge attributed to the forest expansion emphasised the importance of preserving forest cover and pervious area. The modelling framework presented in this typical tropical monsoon catchment study could be effectively used to quantify the land use change induced flow regime variations in similar catchments.

Physical Characteristics Of The Krueng Seunagan Watershed And River Storage Capacity Against Peak Discharge

Peak discharge information is indispensable for flood control planning by taking into account the physiographic factors of the watershed. Flood occurs because the capacity of the watershed and river channels is smaller than the flood discharge. One of the causes of rivers' reduced flood flow capacity is vegetation cover and land use that cannot store rainfall. Thus, this paper aims to determine the peak discharge from the watershed's physical characteristics and land-use changes by comparing the river storage capacity in the Krueng Seunagan watershed. The rational method is used to calculate the peak discharge. Some of the data used in this study are the shapefile map provided by Geospatial Information Agency, land use, rainfall, soil types, and Landsat 8 OLI/TIRS digital imagery. Analysis of the physical characteristics of the watershed consists of morphology and morphometry. Land use in the area of the Krueng Seunagan watershed increased the peak discharge during the observation year (2003-2017). Besides the land-use factor, discharge is also influenced by high rainfall intensity and runoff coefficient obtained from land use analysis. In the Krueng Seunagan watershed area, the C value obtained was 0.0505 – 0.0720, indicating that the Krueng Seunagan watershed area was classified as good or harmless. The river flow density of 0.53 belongs to the medium category. The river flow increases and decreases in the flood water level, which is neither too fast nor too slow. The roundness index of the Seunagan watershed of 1.0004 indicates that the basins are widened or circular and, consequently, the rate and volume of surface runoff are fast. Krueng Seunagan watershed runoff coefficient increased by 42.51% and rainfall intensity by 37.05%, while discharge increased by 95.31%. The discharge capacity that the Krueng Seunagan River Basin can accommodate from the measurement results in the downstream watershed is 158.47 m3/sec. While the peak discharge using the rational method gets a value that varies in each year of observation from (2003-2017). The peak discharge value in 2003 amounted to 183.52 m3/sec, and the highest in 2017 amounted to 358.44 m3/sec. This shows that the river holding capacity in the Krueng Seunagan watershed will not accept the amount of peak discharge, and consequently, the flood will always occur.