Estimating the Probable Maximum Flood under Climate Change

Abstract:

Probable Maximum Flood (PMF) is a conservative method to estimate flood design and is generally chosen over flood frequency distribution method when the consequences of structural failure are not tolerable. The PMF is largely determined by the Probable Maximum Precipitation (PMP) which is a theoretical estimate of the maximum physically possible rainfall intensity for a given duration. There are different ways to estimate PMP ranging from empirical equations to elaborate methods that takes into account meteorological parameters. Under climate change the meteorological parameters (e.g., air temperature, wind speed, and saturation vapor pressure) changes, which could change the PMP and PMF estimates. Although a few studies have explored the possible increase in PMP and PMF under climate change, there is no agreement upon what methodology to use.

Here we propose a framework for PMP and PMF estimation under climate change and an example demonstration with a case study of a Himalayan hydropower project. The framework provides clear guidelines on how to incorporate future climate information in the different methods for selection of PMP. For the example case study, the PMP estimates are likely to increase in the future due to the intensification of the Indian summer monsoon, and the observed increase in the cloud cover during the peak rainfall months. In addition to the PMP, increased glacial melt in the summers, and increased risk of Glacial Lake Outburst Flood with warming further aggravates the flood risks to the project in the future. This exemplary study shows how to select a design flood to ensure safety of hydropower projects despite limitations on data quality and availability, and large future climate uncertainty.