Assessment of Probable Maximum Flood (PMF) Using Hydrologic Model for Probable Maximum Precipitation in Maithon Watershed

2021 ◽  
pp. 165-176
Author(s):  
Bhanu Sharma ◽  
Kalyan Kumar Bhar
Keyword(s):  
Hydrologic Model ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Probable Maximum Flood

scholarly journals Estimation of Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) Using GSSHA Model (Case Study Area Upper Citarum Watershed)

2021 ◽  
Vol 893 (1) ◽  
pp. 012023
Author(s):  
Puji R A Sibuea ◽  
Dewi R Agriamah ◽  
Edi Riawan ◽  
Rusmawan Suwarman ◽  
Atika Lubis
Keyword(s):  
Model Simulation ◽  
Hydrologic Model ◽  
Model Case ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Hydrologic Analysis ◽  
Probable Maximum Flood ◽  
The Mean ◽  
The Impact

Abstract Probable Maximum Flood (PMF) used in the design of hydrological structures reliabilities and safety which its value is obtained from the Probable Maximum Precipitation (PMP). The objectives of this study are to estimate PMP and PMF value in Upper Citarum Watershed and understand the impact from different PMP value to PMF value with two scenarios those are Scenario A and B. Scenario A will calculate the PMP value from each Global Satellite Mapping of Precipitation (GSMaP) rainfall data grid and Scenario B calculate the PMP value from the mean area rainfall. PMP value will be obtained by the statistical Hershfield method, and the PMF will be obtained by employed the PMP value as the input data in Gridded Surface Subsurface Hydrologic Analysis (GSSHA) hydrologic model. Model simulation results for PMF hydrographs from both scenarios show that spatial distribution of rainfall in the Upper Citarum watershed will affect the calculated discharge and whether Scenario A or B can be applied in the study area for PMP duration equal or higher than 72 hours. PMF peak discharge for Scenario A is averagely 13,12% larger than Scenario B.

scholarly journals Probable Maximum Precipitation (PMP) Analysis for Bakun Dam Area

2011 ◽  
Vol 2 (2) ◽  
pp. 53-59
Author(s):  
Yiau S.S. ◽  
F.J. Putuhena
Keyword(s):  
Catchment Area ◽  
Flood Control ◽  
Design Criterion ◽  
Control Measures ◽  
Dam Construction ◽  
Research Publication ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Probable Maximum Flood ◽  
The One

Probable Maximum Precipitation is defined as the greatest depth of precipitation which is possible for a given time and duration over a given size storm area under known meteorological conditions. This concept has been used as design criterion of major flood control measures such as spillways of large dams worldwide. It is essential for the generation of Probable Maximum Flood. This paper represents the results of PMP analysis for Bakun Dam Area which has a catchment area of 14,750 km2. Three sets of results were produced, i.e. by statistical method (with frequency factors from World Meteorological Organization manual and National Hydraulic Research Institute of Malaysia in Technical Research Publication No. 1 (TRP 1)) for duration of 1 hour, 8 hours, 24 hours and daily and by experimental method for production of daily PMP. The results were compared with each other and the one made by Sarawak Electricity Supply Corporation on Bakun Dam construction. The set of PMP values results from substitution of Km developed by NAHRIM was concluded to be the most reliable results as daily PMP (276mm) was consistent with the one (280mm) produced by SESCO. However, 6 days PMP value (950mm) done by SESCO was recommended as the Bakun Dam Area cover huge catchment area which higher duration of PMP value should be applied .

Évaluation des méthodes utilisées pour l'estimation de la crue maximale probable en régions nordiques

1999 ◽  
Vol 26 (3) ◽  
pp. 355-367 ◽  
Author(s):  
I Debs ◽  
D Sparks ◽  
J Rousselle ◽  
S Birikundavyi
Keyword(s):  
Return Period ◽  
Extreme Event ◽  
Snow Accumulation ◽  
Model Estimation ◽  
Hydrologic Response ◽  
Return Periods ◽  
Design Flood ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Probable Maximum Flood

Among all existing methods for estimating extreme floods, the probable maximum flood method is the safest, since it is a flood with a probability of excedance that is theoretically zero. In the early 1970s, this flood was calculated as the combination of the probable maximum precipitation (PMP) and the probable maximum snow accumulation (PMSA). In the 1990s, this combination has been considered to be highly improbable. Experts advise against combining two maximized events and, instead, recommend combining one maximized event with a relatively typical extreme event. This article presents a sensitivity analysis on the return period to be used for the typical extreme event to be combined with the maximized event to obtain a "more realistic" PMF. To achieve this, all the steps of a PMF study were reviewed and applied to the Sainte-Marguerite watershed, i.e., calibration and (or) validation of SSARR model, estimation of the PMP, the PMSA, and the temperature sequence. Different flood scenarios have been simulated including accumulated snowfall corresponding to return periods of 50, 100, and 500 years, followed by PMP and PMSA, followed by precipitation corresponding to return periods of 50, 100, and 500 years. It has been noticed that the use of a return period of 50, 100, or 500 years, to represent the unmaximized extreme event, has little effect on the hydrologic response of the basin. Based on the results of this work the use of a return period of 100 years is recommended.Key words: probable maximum flood, probable maximum precipitation, probable maximum snow accumulation, design flood, SSARR model.

scholarly journals Estimation of Extreme Precipitation in Norway

1989 ◽  
Vol 20 (4-5) ◽  
pp. 257-276 ◽  
Author(s):  
E.J. Førland ◽  
D. Kristoffersen
Keyword(s):  
Extreme Precipitation ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Probable Maximum Flood

Probable Maximum Precipitation (PMP) is an important parameter for estimation of Probable Maximum Flood. This paper describes results of PMP estimation by different methods, both meteorological and statistical. A survey of the highest recorded rainfall values in Norway is also presented.

scholarly journals Effects of variability in probable maximum precipitation patterns on flood losses

2018 ◽  
Author(s):  
Andreas Paul Zischg ◽  
Guido Felder ◽  
Rolf Weingartner ◽  
Niall Quinn ◽  
Gemma Coxon ◽  
...  
Keyword(s):  
River Basin ◽  
Critical Infrastructure ◽  
Flood Hazard ◽  
Infrastructure Management ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Precipitation Patterns ◽  
Probable Maximum Flood ◽  
Flood Losses ◽  
Model Chain

Abstract. The assessment of the impacts of extreme floods is important for dealing with residual risk, particularly for critical infrastructure management and for insurance purposes. Thus, modelling of the probable maximum flood (PMF) from probable maximum precipitation (PMP) by coupling hydrologic and hydraulic models has gained interest in recent years. Herein, we examine whether variability in precipitation patterns exceeds or is below other uncertainties in flood loss estimation and if the flood losses within a river basin are related to the probable maximum discharge at the basin outlet. We developed a model experiment with an ensemble of probable maximum precipitation scenarios created by Monte-Carlo simulations. For each rainfall pattern, we computed the flood losses with a model chain and benchmarked the effects of variability in rainfall distribution with other model uncertainties. The results show that flood losses vary considerably within the river basin and depend on the timing and superimposition of the flood peaks from the basin's sub-catchments. In addition to the flood hazard component, the other components of flood risk, exposure and vulnerability, contribute remarkably to the overall variability. This leads to the conclusion that the estimation of the probable maximum expectable flood losses in a river basin should not be based exclusively on the PMF. Consequently, the basin-specific sensitivities to different precipitation patterns and the spatial organisation of the settlements within the river basin need to be considered in the analyses of probable maximum flood losses.

scholarly journals Probable Maximum Precipitation Comparison using Hershfield’s Statistical Method and Hydro-Meteorological Method for Sungai Perak Hydroelectric Scheme

2018 ◽  
Vol 7 (4.35) ◽  
pp. 603 ◽  
Author(s):  
Razali J ◽  
Sidek L.M ◽  
Rashid M.A ◽  
Hussein A ◽  
M. Marufuzzaman
Keyword(s):  
Extreme Precipitation ◽  
Physical Method ◽  
Loss Of Life ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Extreme Flood ◽  
Probable Maximum Flood ◽  
Potential Risks ◽  
Dam Overtopping ◽  
Downstream Area

One of the potential risks attributed to the occurrence of dam overtopping and dam wall failure due to the inadequacy of the spillway capacities is the loss of life and property damages in the downstream area. The current practices in most countries in minimizing these risks are by analyzing the extreme precipitation that leads to extreme flood. Extreme precipitation is best known as Probable Maximum Precipitation (PMP) and this estimation is useful in determining Probable Maximum Flood (PMF) in reviewing the spillway adequacy of dam structures. This paper presented PMP estimations using two approaches; physical method (Hydro-meteorological Method) and statistical approach (Hershfield’s Method) at the Sungai Perak Hydroelectric Scheme that consists of four cascading dams namely Temengor dam, Bersia dam, Kenering dam and Chenderoh dam. The highest PMP estimates from these two methods will be chosen as the rainfall input to establish PMF hydrographs. Estimations using Hydro-meteorological generalized map produces 40-50% higher estimates compared to Hersfield’s method with the PMP values of 550mm (1hours), 600mm (3hours), 800mm (6hours), 820mm (12hours), 1300mm (24hour) and 1600mm (72 hours). Accepting the Hydro-meteorological Method to determine PMF values for this hydroelectric scheme may be the best course since the estimations of the extreme precipitations using this method are the highest.

scholarly journals Effects of variability in probable maximum precipitation patterns on flood losses

2018 ◽  
Vol 22 (5) ◽  
pp. 2759-2773 ◽  
Author(s):  
Andreas Paul Zischg ◽  
Guido Felder ◽  
Rolf Weingartner ◽  
Niall Quinn ◽  
Gemma Coxon ◽  
...  
Keyword(s):  
River Basin ◽  
Spatial Organization ◽  
Critical Infrastructure ◽  
Flood Hazard ◽  
Infrastructure Management ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Precipitation Patterns ◽  
Probable Maximum Flood ◽  
Flood Losses

Abstract. The assessment of the impacts of extreme floods is important for dealing with residual risk, particularly for critical infrastructure management and for insurance purposes. Thus, modelling of the probable maximum flood (PMF) from probable maximum precipitation (PMP) by coupling hydrological and hydraulic models has gained interest in recent years. Herein, we examine whether variability in precipitation patterns exceeds or is below selected uncertainty factors in flood loss estimation and if the flood losses within a river basin are related to the probable maximum discharge at the basin outlet. We developed a model experiment with an ensemble of probable maximum precipitation scenarios created by Monte Carlo simulations. For each rainfall pattern, we computed the flood losses with a model chain and benchmarked the effects of variability in rainfall distribution with other model uncertainties. The results show that flood losses vary considerably within the river basin and depend on the timing and superimposition of the flood peaks from the basin's sub-catchments. In addition to the flood hazard component, the other components of flood risk, exposure, and vulnerability contribute remarkably to the overall variability. This leads to the conclusion that the estimation of the probable maximum expectable flood losses in a river basin should not be based exclusively on the PMF. Consequently, the basin-specific sensitivities to different precipitation patterns and the spatial organization of the settlements within the river basin need to be considered in the analyses of probable maximum flood losses.

scholarly journals Estimation of probable maximum precipitation for tropical catchment

2018 ◽  
Vol 162 ◽  
pp. 03012 ◽  
Author(s):  
Saad Sammen ◽  
Thamer Mohamed ◽  
Abd Alhalim Ghazali ◽  
Lariyah Sideq ◽  
Azlan Abdul Aziz
Keyword(s):  
Return Period ◽  
Statistical Approach ◽  
Extreme Rainfall ◽  
Physical Method ◽  
Hydraulic Structures ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
Storm Duration ◽  
Probable Maximum Flood

Probable Maximum Precipitation (PMP) is the maximum precipitation depth for specific region or station within a certain time. The main purpose of PMP estimation is calculate the Probable Maximum Flood (PMF). The PMF is considered necessary for design and manage the hydraulic structures. PMP can be estimate using two methods, either using a physical method or by using statistical method. In this study, statistical approach was used to estimate the PMP for Temengor catchment in Perak state, Malaysia. Extreme value type-1 distribution (EV1) is adopted to estimate the extreme rainfall and Hershfeid method was used to estimate PMP value. Also, intensity duration curve (IDC) was derived for 1, 2 and 3 days storm duration with return period 5, 10, 50, 100, 500 years. The results showed that the values of PMP for 1000 return period are 222.361mm, 311.847mm and 348.307mm for 1, 2 and 3 days respectively.

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