Flash flood in Arau watershed, West Sumatera: a mitigation study

Flash flood often occurs in West Sumatera. In spite of heavy rain, flash floods are also caused by the landslide in the riverside that blocks the river as a natural dam. The natural dam can be broken at any time, depending on storage capacity. Flash flood occurs when the dam is broken. The aim of the research is to mitigate flash floods based on parameters influencing flood and landslide. The research was conducted in Arau watershed, West Sumatera. Parameters that have a direct proportion of floods are maximum daily rainfall, watershed shape, river gradient, drainage density, slope, and land cover. Parameters influencing landslides are antecedent soil moisture, slope, geologic type especially fault line, soil depth, and land cover. GIS is used to analyze the factors influencing flood and landslide spatially. The results show that more than 50% of the Arau watershed are slightly high and high vulnerability due to its natural condition. Furthermore, the locations of fault, especially in the riverside, should be noticed because this location could become a natural dam causing flash flood. In order to reduce flash flood impact, the natural dam should be opened as soon as possible.

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Analysis of soil boundary conditions of flash floods in a small basin in SW Hungary

Open Geosciences ◽

10.2478/s13533-012-0119-6 ◽

2013 ◽

Vol 5 (1) ◽

Cited By ~ 5

Author(s):

Péter Hegedüs ◽

Szabolcs Czigány ◽

László Balatonyi ◽

Ervin Pirkhoffer

Keyword(s):

Soil Moisture ◽

Input Data ◽

Flash Flood ◽

Soil Depth ◽

Stream Water ◽

Infiltration Rate ◽

Flash Floods ◽

Water Levels ◽

Antecedent Soil Moisture ◽

Numeric Model

AbstractFlash floods are one of the most significant natural hazards of today. Due to the complexity of flash flood triggering factors, to prevent or mitigate flood triggered losses, numeric model based flood forecasting models are capable tools to predict stream water levels. The main goal of the current research was to reproduce two flow peaks with the HEC-HMS rainfall-runoff model and test the model sensitivity for various input parameters. To obtain sufficient input data, we monitored soil depth, maximum infiltration rate, soil moisture content, rainfall, time of concentration and flow. To obtain input data, parameters were calculated, measured in the Sás Valley experimental watershed (SW Hungary) or optimized with the built in function of the HEC-HMS. Soil moisture was monitored in the 1.7 km2 pilot catchment over the period between September 2008 and September 2009. HEC-HMS had a good performance reproducing the two events, however simulated flow time series are highly influenced by the antecedent soil moisture, infiltration rate and canopy storage. Outflow modeled data were verified for two flood events (June 4, 2008 and July 9, 2009). The HEC-HMS was over-sensitive for input soil moisture and with increasing input rainfall and increasing outflow, larger simulation errors were observed.

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Surface Water Management and Modelling in the Sakia El Hamra Hydraulic Basin (Southern Morocco)

10.5194/egusphere-egu2020-8635 ◽

2020 ◽

Author(s):

Nafia El-alaouy ◽

Aicha Moumni ◽

Badr-eddine Sebbar ◽

Abdeljalil Gouzrou ◽

Aberrahman Lahrouni

Keyword(s):

Flash Flood ◽

Hydrological Regime ◽

Shape Index ◽

Flash Floods ◽

Drainage Density ◽

Agricultural Lands ◽

Surface Water Management ◽

Short Period ◽

Long Time ◽

Log Normal

Due to its arid to semi-arid climate, Morocco often faces significant intense rainfall periods that can generate flash floods and raging torrents causing serious damage in a very short period of time. In this context, these recent years, the watershed corresponding to the SAKIA EL HAMRA wadi has known devastating downpours and excessive heavy rains that caused severe floods in Laayoune city and its regions.The watershed of Sakia El Hamra covers an area of 82000 km2, that drains to Sakia El Hamra wadi, a stream of about 447 km long, crosses the basin in its northern part in the East-to-West direction, to discharge into the Atlantic Ocean at the outlet called Foum El Oued. This zone often experiences dangerous torrents of water and violent flash floods, specifically in the northern part of Laayoune city. For example, a flash flood has occurred at the end of October 2016. The peak flow was far in excess of the average (3000 m3/s against 410m3/s). This river flood, lasted for about 10 h, caused damage to the infrastructure and destruction of agricultural lands near Foum El Oued.The objective of this study is to investigate, through modelling, the hydrological regime of SAKIA EL HAMRA watershed to prevent the floods in the future and improve warning systems. The hydrological parameters of the watershed were determined by WMS software, namely: zone extent, perimeter, slope, basin&#8217;s average elevation, Gravelius compactness index, Horton shape index, average altitude, drainage density and concentration time.Flood flow return was simulated using the Log-normal distribution, using a long time-series of flow and maximum daily and annual precipitation data, recorded between 1985 and 2016, at the Airport station in Laayoune city. The results showed that during flash floods with known flows, water level can reach up to 13 meters, with high flow velocities flooding hundreds of hectares of surrounding plains at the northern part of the city of Laayoune and agricultural lands near Foum El Oued.

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A Statistical Comparison of the Properties of Flash Flooding and Nonflooding Precipitation Events in Portions of New York and Pennsylvania

Weather and Forecasting ◽

10.1175/2007waf2006066.1 ◽

2008 ◽

Vol 23 (1) ◽

pp. 114-130 ◽

Cited By ~ 14

Author(s):

Stephen M. Jessup ◽

Arthur T. DeGaetano

Keyword(s):

New York ◽

Wind Direction ◽

Flash Flood ◽

Convective Available Potential Energy ◽

Potential Temperature ◽

Flash Floods ◽

Antecedent Soil Moisture ◽

Random Events ◽

Rain Events ◽

Precipitation Events

Abstract Flash floods reported for the forecast area of the National Weather Service Forecast Office at Binghamton, New York (BGM), are compared with similar significant precipitation and flash flood watch events not corresponding to flash flood reports. These event types are characterized by measures of surface hydrological conditions, surface and upper-air variables, thermodynamic properties, and proxies for synoptic-scale features. Flash flood and nonflood events are compared quantitatively via discriminant analysis and cross validation, and qualitatively via scatterplots and composite soundings. Results are presented in the context of a flash flood checklist used at BGM prior to this study. Flash floods and nonfloods are found to differ most significantly in antecedent soil moisture. The wind direction at 850 hPa shows differences between flood and nonflood events, with flooding more common for an easterly to southeasterly direction and nonflooding more common for a northwesterly direction. Southwesterly wind direction is characteristic of both types. In general, nonflooding significant precipitation events are more commonly associated with a better-defined ridge axis of relatively high 850-hPa equivalent potential temperature and larger convective available potential energy as compared to the flash flood events. Several parameters included on the BGM flash flood checklist, though effective at distinguishing significant precipitation events and flash floods from random events, were found to be unable to separate flash floods from nonflooding significant rain events.

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Ensemble Flash Flood Predictions Using a High-Resolution Nationwide Distributed Rainfall-Runoff Model: Case Study of the Heavy Rain Event of July 2018 and Typhoon Hagibis in 2019

10.21203/rs.3.rs-40714/v2 ◽

2020 ◽

Author(s):

Takahiro Sayama ◽

Masafumi Yamada ◽

Yoshito Sugawara ◽

Dai Yamazaki

Keyword(s):

Lead Time ◽

Flash Flood ◽

Heavy Rain ◽

Flash Floods ◽

Rain Event ◽

Rainfall Runoff ◽

Heavy Rain Event ◽

Peak Runoff ◽

Rainfall Runoff Model ◽

Runoff Model

Abstract The heavy rain event of July 2018 and Typhoon Hagibis in October 2019 caused severe flash flood disasters in numerous parts of western and eastern Japan. Flash floods need to be predicted over a wide range with long forecasting lead time for effective evacuation. The predictability of flash floods caused by the two extreme events are investigated by using a high-resolution (~150 m) nationwide distributed rainfall-runoff model forced by ensemble precipitation forecasts with 39-h lead time. Results of the deterministic simulation at nowcasting mode with radar and gauge composite rainfall could reasonably simulate the storm runoff hydrographs at many dam reservoirs over western Japan for the case of heavy rainfall in 2018 (F18) with the default parameter setting. For the case of Typhoon Hagibis in 2019 (T19), a similar performance was obtained by incorporating unsaturated flow effect in the model applied to Kanto region. The performance of the ensemble forecast was evaluated based on the bias ratios and the relative operating characteristic curves, which suggested the higher predictability in peak runoff for T19. For the F18, the uncertainty arises due to the difficulty in accurately forecasting the storm positions by the frontal zone; as a result, the actual distribution of the peak runoff could not be well forecasted. Overall, this study showed that the predictability of flash floods was different between the two extreme events. The ensemble spreads contain quantitative information of predictive uncertainty, which can be utilized for the decision making of emergency responses against flash floods.

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Peak Discharge in Jemelak Subwatershed, Sintang District

Jurnal Sylva Lestari ◽

10.23960/jsl38273-282 ◽

2020 ◽

Vol 8 (3) ◽

pp. 273

Author(s):

Diah Auliyani ◽

Esa Bagus Nugrahanto

Keyword(s):

Land Cover ◽

Agricultural Land ◽

Daily Rainfall ◽

Peak Discharge ◽

Swamp Forest ◽

Maximum Rainfall ◽

Bare Land ◽

Big Rivers ◽

Second Period ◽

Maximum Daily Rainfall

Jemelak Sub Watershed is close to the junction of two big rivers, i.e., Kapuas and Melawi. Therefore, this location faces environmental issues such as a flood. To avoid its possible damages, information on peak discharge becomes critical, particularly in calculating the drainage structure. This study was aimed to predict the peak discharge in this area using a rational method. The maximum daily rainfall data from 1998 to 2017 were divided into two periods of 10 years and analyzed. In the first period, maximum rainfall rangesfrom98.6 to 176.3 mm, while the second period fluctuates from67.6 to 190 mm. Analysis of land cover described that 43.97% of secondary swamp forests turned into shrubs and swamp shrubs in the first period. Furthermore, about 800.71 ha of secondary swamp forest tuned into 582.80 ha of bare land, 181.04 ha of a plantation, and 36.88 ha of swamp shrubs in the second period. About 95.15% of shrubs were also turned into agricultural land mixed with shrubs in the second period. The result showed that the changes in the maximum daily rainfall and land cover simultaneously affected the improvement of the peak discharge by about 2.53% in the first period and 28.30% in the second period. If the peak discharge exceeds the river capacity, then the local flooding will occur along the river border. Keywords: land cover, peak discharge, rainfall, Jemelak

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Utilization of estimated rainfall as an early warning system before flash flood event

Journal of Physics Theories and Applications ◽

10.20961/jphystheor-appl.v2i2.30670 ◽

2018 ◽

Vol 2 (2) ◽

pp. 73

Author(s):

Fara Diva Claudia ◽

Cecylia Putri Mawarni ◽

Kadek Krisna Yulianti ◽

Paulus Agus Winarso

Keyword(s):

Flash Flood ◽

Remote Sensing Data ◽

Heavy Rain ◽

Flash Floods ◽

Extreme Weather ◽

Atmospheric Dynamics ◽

Observation Data ◽

Rainfall Estimation ◽

Wrf Modeling ◽

The Impact

On October 10, 2018 there has been extreme weather in the form of heavy rain accompanied by lightning in Tanah Datar District, West Sumatra. This extreme weather caused flash floods and landslides that killed many people. Therefore, by using remote sensing data in the form of radar and satellite as well as WRF modeling (Weather Research and Forecasting) the authors conducted analysis of heavy rainfall events to determine the estimated rainfall and atmospheric dynamics during the occurrence of flash floods and landslides. WRF modeling is used to determine the condition of atmospheric lability. For the calculation of rainfall estimation, the method used is the Convective Stratiform Technique (CST) method that utilizes satellite data and the Z-R relation selection method that utilizes radar data. Then the calculation results from each method are verified using observation data. Relative bias shows the CST method and the selection of Z-R relations tend to be overestimate, but has a very high correlation value with observation data. Information on rainfall estimation and atmospheric dynamics is expected to be used to provide early warnings aimed at minimizing losses from the impact of disasters.

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Classification of Karst Springs For Flash Flood-Prone Areas in Western Turkey

10.5194/nhess-2016-6 ◽

2016 ◽

Author(s):

M. Demiroglu

Keyword(s):

Groundwater Flow ◽

Flash Flood ◽

Heavy Rain ◽

Flash Floods ◽

Fracture Permeability ◽

Western Turkey ◽

Discharge Rates ◽

Dry Seasons ◽

High Storage ◽

Wet And Dry Seasons

Abstract. Flash floods are the result of very intensive rainfall events and karst plays an important role in flash floods. A study, using a hydrogeochemical approach, assessing data from several springs of different carbonate rocks in Western Turkey was made to classify karst aquifers' response to heavy rain events. Physicochemical measurements in wet and dry seasons and discharge rates were compared in order to explain aquifer characteristics. The groundwaters have pH values ranging from 6.3 to 8.9, temperatures (T) vary from 7 to 35 °C, and electrical conductivity (EC) values go from 140 to 998 μS cm/S. The groups that have high EC, high T, and low dissolved oxygen (DO) values represent the deep circulating waters. Low EC, low T and high DO values represent the shallow circulating waters. Low variations of the measurements in both the wet and dry seasons reveal that fracture permeability is predominantly controlled by diffused groundwater flow with low or high storage and conduit permeability with high storage. High variations of the measurements show conduit permeability with low storage but high transfer capability is predominantly controlled by turbulent groundwater flow which effective in flash floods.

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Estimation of extreme flash flood evolution in Barcelona County from 1351 to 2005

Natural Hazards and Earth System Science ◽

10.5194/nhess-6-505-2006 ◽

2006 ◽

Vol 6 (4) ◽

pp. 505-518 ◽

Cited By ~ 54

Author(s):

A. Barrera ◽

M. C. Llasat ◽

M. Barriendos

Keyword(s):

Roman Empire ◽

Flash Flood ◽

Flood Hazard ◽

Climatic Variability ◽

Daily Rainfall ◽

Weather Conditions ◽

Flash Floods ◽

Economic Losses ◽

Data Series ◽

Perception Threshold

Abstract. Every year, flash floods cause economic losses and major problems for undertaking daily activity in the Catalonia region (NE Spain). Sometimes catastrophic damage and casualties occur. When a long term analysis of floods is undertaken, a question arises regarding the changing role of the vulnerability and the hazard in risk evolution. This paper sets out to give some information to deal with this question, on the basis of analysis of all the floods that have occurred in Barcelona county (Catalonia) since the 14th century, as well as the flooded area, urban evolution, impacts and the weather conditions for any of most severe events. With this objective, the identification and classification of historical floods, and characterisation of flash-floods among these, have been undertaken. Besides this, the main meteorological factors associated with recent flash floods in this city and neighbouring regions are well-known. On the other hand, the identification of rainfall trends that could explain the historical evolution of flood hazard occurrence in this city has been analysed. Finally, identification of the influence of urban development on the vulnerability to floods has been carried out. Barcelona city has been selected thanks to its long continuous data series (daily rainfall data series, since 1854; one of the longest rainfall rate series of Europe, since 1921) and for the accurate historical archive information that is available (since the Roman Empire for the urban evolution). The evolution of flood occurrence shows the existence of oscillations in the earlier and later modern-age periods that can be attributed to climatic variability, evolution of the perception threshold and changes in vulnerability. A great increase of vulnerability can be assumed for the period 1850–1900. The analysis of the time evolution for the Barcelona rainfall series (1854–2000) shows that no trend exists, although, due to changes in urban planning, flash-floods impact has altered over this time. The number of catastrophic flash floods has diminished, although the extraordinary ones have increased.

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Evaluation of sub daily satellite rainfall estimates through flash flood modelling in the Lower Middle Zambezi Basin

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-378-59-2018 ◽

2018 ◽

Vol 378 ◽

pp. 59-65 ◽

Cited By ~ 2

Author(s):

Thomas Matingo ◽

Webster Gumindoga ◽

Hodson Makurira

Keyword(s):

Flash Flood ◽

Daily Rainfall ◽

Flash Floods ◽

Rain Gauge ◽

Hydrological Modelling ◽

Probability Of Detection ◽

Time Step ◽

Flood Modelling ◽

Satellite Rainfall ◽

Rainfall Estimates

Abstract. Flash floods are experienced almost annually in the ungauged Mbire District of the Middle Zambezi Basin. Studies related to hydrological modelling (rainfall-runoff) and flood forecasting require major inputs such as precipitation which, due to shortage of observed data, are increasingly using indirect methods for estimating precipitation. This study therefore evaluated performance of CMORPH and TRMM satellite rainfall estimates (SREs) for 30 min, 1 h, 3 h and daily intensities through hydrologic and flash flood modelling in the Lower Middle Zambezi Basin for the period 2013–2016. On a daily timestep, uncorrected CMORPH and TRMM show Probability of Detection (POD) of 61 and 59 %, respectively, when compared to rain gauge observations. The best performance using Correlation Coefficient (CC) was 70 and 60 % on daily timesteps for CMORPH and TRMM, respectively. The best RMSE for CMORPH was 0.81 % for 30 min timestep and for TRMM was 2, 11 % on 3 h timestep. For the year 2014 to 2015, the HEC-HMS (Hydrological Engineering Centre-Hydrological Modelling System) daily model calibration Nash Sutcliffe efficiency (NSE) for Musengezi sub catchment was 59 % whilst for Angwa it was 55 %. Angwa sub-catchment daily NSE results for the period 2015–2016 was 61 %. HEC-RAS flash flood modeling at 100, 50 and 25 year return periods for Angwa sub catchment, inundated 811 and 867 ha for TRMM rainfall simulated discharge at 3 h and daily timesteps, respectively. For CMORPH generated rainfall, the inundation was 818, 876, 890 and 891 ha at daily, 3 h, 1 h and 30 min timesteps. The 30 min time step for CMORPH effectively captures flash floods with the measure of agreement between simulated flood extent and ground control points of 69 %. For TRMM, the 3 h timestep effectively captures flash floods with coefficient of 67 %. The study therefore concludes that satellite products are most effective in capturing localized hydrological processes such as flash floods for sub-daily rainfall, because of improved spatial and temporal resolution.

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Characterization of physically based hydrologic model behaviour with temporal sensitivity analysis for flash floods in Mediterranean catchments

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-10-1375-2013 ◽

2013 ◽

Vol 10 (1) ◽

pp. 1375-1422

Author(s):

P. A. Garambois ◽

H. Roux ◽

K. Larnier ◽

W. Castaings ◽

D. Dartus

Keyword(s):

Sensitivity Analysis ◽

Flash Flood ◽

Soil Depth ◽

Flash Floods ◽

Hydrologic Model ◽

Valuable Insight ◽

Model Output ◽

Flood Events ◽

Extreme Flood ◽

Physically Based

Abstract. This paper presents a detailed analysis of 10 flash flood events in the Mediterranean region using the distributed hydrological model MARINE. Characterizing catchment's response during flash flood events may provide a new and valuable insight into the processes involved for extreme flood response and their dependency on catchment properties and flood severity. The main objective of this study is to analyze hydrologic model sensitivity in the case of flash floods with a new approach in hydrology, allowing model outputs variance decomposition for temporal patterns of parameter sensitivity analysis. Such approaches enable ranking of uncertainty sources for non-linear and non-monotonic mappings with a low computational cost. This study uses hydrologic model and sensitivity analysis as learning tools to derive temporal sensitivity analysis with a variance based method in the case of 10 flash floods that occurred in the French Pyrenees and Cévennes foothills. This constitutes a huge dataset given the scarcity of data about flash flood events. With Nash performances above 0.73 on average for this extended set of validation events, the five sensitive parameters of MARINE distributed physically based model are analyzed. This contribution shows that soil depth explains more than 80% of model output variance when most hydrographs are peaking. Moreover the lateral subsurface transfer is responsible for 80% of model variance for some catchment-flood events' hydrographs during slow declining limbs. The unexplained variance of model output representing interactions between parameters reveals to be very low during modeled flood peaks and informs that model parsimonious parameterization is appropriate to tackle the problem of flash floods. Interactions observed after model initialization or rainfall intensity peaks incite to improve water partition representation between flow components and initialization itself. This paper gives a practical framework for application of this method to other models, landscapes and climatic conditions, potentially helping to improve processes understanding and representation.

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