Comparison of different variants of storm maximization method for Probable Maximum Precipitation estimation in changing climate

Design and risk assessment of large hydraulic structures, whose failure can cause catastrophic damage to the environment, ecology, life and property, are based on Probable Maximum Precipitation (PMP). It is deemed as the theoretical upper bound of the maximum precipitation that is physically possible over a given area for a specified duration. The conventional approaches for estimating PMP are based on stationarity assumption, i.e., the current climatic conditions will remain unchanged even in the future. But the recent increase in extreme precipitation events across the globe and projected increase in the same for future climatic scenarios raises questions on the validity of the stationarity assumption. This issue has gained attention in recent years, and efforts have been directed towards improving existing approaches and devising novel methodologies that would yield reliable PMP estimates in changing climatic conditions. Several researchers have proposed different variations of the widely used storm maximization method to account for non-stationarities arising due to changing climate. The variations imbibe the potential change in PMP resulting either from the trend in precipitable water or from the complex interaction of drivers of PMP. There is a need to compare their relative performance to quantify if the improvement offered by complex variants is significant compared to simple variants in different parts of the globe. In this study, it is investigated through a case study on the frequent flood-prone Mahanadi River Basin in India. For this analysis, future projections of various atmospheric variables (e.g., precipitation, dew point temperature, precipitable water) were obtained from 5 GCMs (General Circulation Models) corresponding to two CMIP6 SSP (Coupled Model Intercomparison Project-6 Shared Socioeconomic Pathways) forcing scenarios namely, SSP1-2.6 and SSP5-8.5. The PMP estimates obtained from improved variants were also compared with their conventional stationary counterpart to assess the effect of dispensing the stationarity assumption.