Probable Maximum Precipitation for 24 Hour Duration over Four Central Provinces in Iran

Moghaddam, Mahyar Naseri; Ghazanfari, Sadegh; Ghahraman, B; Davari, K

doi:10.1061/41036(342)629

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…PMP estimation by the statistical method utilizes a simple process and has been widely used in different countries. PMP studies in India, Malaysia, and Iran (Rakhecha et al, 1992;Rakhecha and Soman, 1994;Desa et al, 2001;Desa and Rakhecha, 2007;Moghaddam et al, 2009) found that the commonly used Hershfield (1961)'s k m value of 15 was too high for some areas. In addition, the k m calculation has been developed in order to get the appropriate value for the rainfall data in a specific area.…”

Section: Estimation Of Pmp Using the Hershfield's Statistical Methodsmentioning

confidence: 99%

Probable maximum precipitation in tropical zone (Thailand) as estimated by generalized method and statistical method

Wangwongwiroj

Khemngoen

2019

Intl Journal of Climatology

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The objective of this research was to estimate probable maximum precipitation (PMP) for the duration of 1 to 3 days in Thailand. Rainfall data were collected from 217 meteorological stations. Two methods for estimating PMP were applied: the generalized method which analysed actual storms data using meteorological process, and the Hershfield's statistical method which applied the frequency analysis of the annual maximum rainfall. Both methods were commonly used and were recommended by the World Meteorological Organization (WMO) for estimating PMP. PMP estimation results were presented as isohyetal maps. For the generalized method, most PMP values were found higher in the east and decreased towards the west. However, there was no clear trend with the statistical method in the PMP's spatial distribution. An analysis of the 3‐day PMP averages showed that PMP estimation using the generalized method is 10% higher than that of the statistical method. The study results were then applied to estimate PMP of six large dams in Thailand and compared with the ones used in the design of the spillways. It was found that PMP estimation based on the generalized method was closer to the value used in the spillway design of those dams than PMP estimation based on the statistical method.

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Section: Estimation Of Pmp Using the Hershfield's Statistical Methodsmentioning

confidence: 99%

Probable maximum precipitation in tropical zone (Thailand) as estimated by generalized method and statistical method

Wangwongwiroj

Khemngoen

2019

Intl Journal of Climatology

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“…There have been several studies about PMP estimation using the hydro-meteorological and statistical approaches in different parts of Iran (Ghahraman, 2008;Naseri Moghaddam et al 2009;Fattahi et al 2010, Shirdeli, 2012. Whereas, there have been few efforts to investigate climate change's impact on Iran's PMP values in recent years.…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Prediction of Climate Change Impact on 24-h Probable Maximum Precipitation in the Southeast of Caspian Sea

Afzali-Gorouh

Faridhosseini

Bakhtiari

et al. 2021

Preprint

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Due to the impacts of climate change on Probable Maximum Precipitation (PMP), and its importance in designing hydraulic structures, PMP estimation is crucial. In this study, the effect of climate change on 24-h probable maximum precipitation (PMP24) was investigated in a part of the Qareh-Su basin located in the Southeast of Caspian Sea. So far, there are no studies emphasizing on climate change impact on hydrological (physical) PMP values have been conducted in the study area. For this purpose, the climatic data were applied during the years 1988–2017. To generate future data, the outputs of the CanESM2 (Second Generation Canadian Earth System Model) model as a general circulation model (GCM) under optimistic (RCP2.6), middle (RCP4.5), and pessimistic (RCP8.5) emission scenarios, and statistical downscaling model (SDSM) were used in the near (2019-2048) and the far (2049-2078) future periods. The PMP24 values were estimated using a physical method in the baseline and future periods under the three scenarios. The PMP24 value was estimated at 143 mm for the baseline-period, using a physical approach. These values were 98, 105, and 109 for the near-future and 129, 122, and 126mm for the far-future period. The results showed that the physical approach's PMP24 values tend to fall at 14-38%. Overall, the PMP24 values decrease in the future, and the rate of decrease in the near-future was more than the rate of the far-future. The spatial distribution maps of PMP24 in the baseline and future-periods showed that the PMP24 values decreased from west to east.

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“…There have been several studies about PMP estimation using the hydro-meteorological and statistical approaches in different parts of Iran (Ghahraman, 2008;Naseri Moghaddam et al, 2009;Fattahi et al, 2010;Shirdeli, 2012). Naseri Moghadam et al, (2009) estimated 1-day PMP for 23 meteorological stations in four central provinces of Iran using the Hershfield method.…”

Section: Introductionmentioning

confidence: 99%

Probable maximum precipitation estimation in a humid climate

Afzali-Gorouh

Bakhtiari

Qaderi

2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Probable maximum precipitation (PMP) estimation is one of the most important components for designing hydraulic structures. The aim of this study was the estimation of 24 h PMP (PMP24) using statistical and hydro-meteorological (physical) approaches in the humid climate of the Qareh-Su basin, which is located in the northern part of Iran. Firstly, for the statistical estimate of PMP, the equations of empirical curves of the Hershfield method were extracted and the Hershfield standard and modified methods were written in Java programming language, as a user-friendly and multi-platform application called the PMP Calculator. Secondly, a hydro-meteorological approach, which is called the convergence model, was used to calculate PMP24. The results of both approaches were evaluated based on statistical criteria, such as the mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), mean absolute percentage error (MAPE), correlation coefficient (r), and coefficient of determination (R2). The maximum values of PMP24 for the Hershfield standard and modified methods were estimated to be 448 and 201 mm, respectively, while the PMP obtained by the physical approach was 143 mm. Comparison of PMP24 values with the maximum 24 h precipitation demonstrated that based on performance criteria including the MAE, MSE, RMSE, MAPE, r, and R2, the physical approach performed better than the statistical approach and it provided the most reliable estimates for PMP. Also, the accuracy of the Hershfield modified method was better than the standard method using modified Km values, and the standard method gives excessively large PMP for construction costs.

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Probable Maximum Precipitation for 24 Hour Duration over Four Central Provinces in Iran

Cited by 5 publications

References 4 publications

Probable maximum precipitation in tropical zone (Thailand) as estimated by generalized method and statistical method

Probable maximum precipitation in tropical zone (Thailand) as estimated by generalized method and statistical method

Monitoring and Prediction of Climate Change Impact on 24-h Probable Maximum Precipitation in the Southeast of Caspian Sea

Probable maximum precipitation estimation in a humid climate

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