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Modernizing Probable Maximum Precipitation Estimation

Modernizing Probable Maximum Precipitation Estimation
Author: National Academies of Sciences Engineering and Medicine
Publisher:
Total Pages: 0
Release: 2025-03-18
Genre: Science
ISBN: 9780309715119

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For more than 75 years, high-hazard structures in the U.S., including dams and nuclear power plants, have been engineered to withstand floods resulting from the most unlikely but possible precipitation, termed Probable Maximum Precipitation (PMP). Failure of any one of the more than 16,000 high-hazard dams and 50 nuclear power plants in the United States could result in the loss of life and impose significant economic losses and widespread environmental damage, especially under the pressures of climate change. While PMP estimates have provided useful guidance for designing critical infrastructure, weaknesses in the scientific foundations of PMP, combined with advances in understanding, observing, and modeling extreme storms, call for fundamental changes to the definition of PMP and the methods used to estimate it. Modernizing Probable Maximum Precipitation Estimation recommends a new definition of PMP and presents a vision for a methodology relevant for design, operation, and regulation of critical infrastructure. The new definition targets precipitation depths with an extremely low exceedance probability instead of assuming rainfall is bounded, and considers specified climate periods so that PMP estimates can change as the climate changes. Near-term enhancements to PMP include improved data collection, model-based storm reconstructions, and strengthened scientific grounding for PMP methods. Long-term model-based PMP estimation will employ kilometer-scale climate models capable of resolving PMP storms and producing PMP-magnitude precipitation. A Model Evaluation Project will provide scientific grounding for model-based PMP estimation and determine when transition to a model-based PMP estimation should occur. Scientific and modeling advances along this front will contribute to addressing the societal challenges linked to the changes in extreme storms and precipitation in a warming climate, which are critical steps to ensuring the safety of our infrastructure and society.


Manual on Estimation of Probable Maximum Precipitation (PMP)

Manual on Estimation of Probable Maximum Precipitation (PMP)
Author: World Meteorological Organization
Publisher:
Total Pages: 294
Release: 2009
Genre: Flood forecasting
ISBN:

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The manual describes procedure for estimating the maximum probable precipitation and the maximum probable flood. This is the third revised version. The first and second editions of this manual were published in 1973 and 1986, respectively. The current edition keeps a majority of the content from the second edition. Newly added content in this third edition primarily results from experiences, since 1986, in directly estimating PMP for the requirements of a given project in a design watershed on probable maximum flood (PMF) in China, the United States of America, Australia and India.--Publisher's description.


Development of a Methodology for Probable Maximum Precipitation Estimation Over the American River Watershed Using the WRF Model

Development of a Methodology for Probable Maximum Precipitation Estimation Over the American River Watershed Using the WRF Model
Author: Elcin Tan
Publisher:
Total Pages:
Release: 2010
Genre:
ISBN: 9781124025803

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A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the physically possible upper limits of precipitation due to climate change. The simulation results indicate that the meridional shift in atmospheric conditions is the optimum method to determine maximum precipitation in consideration of cost and efficiency. Finally, exceedance probability analyses of the model results of 42 historical extreme precipitation events demonstrate that the 72-hr basin averaged probable maximum precipitation is 21.72 inches for the exceedance probability of 0.5 percent. On the other hand, the current operational PMP estimation for the American River Watershed is 28.57 inches as published in the hydrometeorological report no. 59 and a previous PMP value was 31.48 inches as published in the hydrometeorological report no. 36. According to the exceedance probability analyses of this proposed method, the exceedance probabilities of these two estimations correspond to 0.036 percent and 0.011 percent, respectively.