Introduction

In recent decades, climate change has substantially intensified environmental and hydrological challenges worldwide. Rising temperatures, increased frequency of extreme events, and altered precipitation patterns have a significant impact on the stability and performance of hydraulic structures. One of the most important parameters used in the design of dams, reservoirs, channels, spillways, and other critical hydraulic structures is the Probable Maximum Precipitation (PMP), which plays a key role in estimating the likelihood of extreme floods and in designing structures capable of withstanding such extreme conditions. In arid and semi-arid regions such as Iran, the impacts of climate change on Probable Maximum Precipitation (PMP) are complex. Therefore, evaluating changes in Probable Maximum Precipitation (PMP) during the baseline and future periods under various climate scenarios is crucial for flood risk management, the design of resilient hydraulic structures, and reducing vulnerability across different regions of the country.

Materials and methods

In this study, daily precipitation data from 96 Iranian synoptic stations for the baseline period 1990–2020 and outputs from CMIP6 models for the future period 2030–2060 were used under the SSP2.6, SSP4.5, and SSP8.5 scenarios. First, the performance of the GCMs at each station in simulating precipitation was evaluated using Taylor diagrams, and the optimal model for each station was identified. After selecting the optimal climate model for each station based on the Taylor diagram, daily precipitation data for the future period (2030–2060) were downscaled using the LARS-WG model under three emission scenarios. The modified Desa-Hirschfield method was used to estimate the Probable Maximum Precipitation (PMP). In this method, extreme values are excluded from the data series, after which the revised mean and standard deviation are calculated. This process improves the accuracy of the results and reduces estimation errors. Previous studies in Iran have shown that the classical Hershfield method overestimates PMP, whereas the Desa-Hershfield method produces more reasonable results that are better aligned with the characteristics of extreme precipitation. Therefore, in this study, the baseline and future PMP were estimated for each of the 96 stations using the modified Desa method. Then, the obtained values for both the baseline and future periods were mapped using the Kriging method to reveal the spatial patterns of PMP changes in Iran.

Results and discussion

The results indicated that the spatial distribution of PMP in Iran is highly heterogeneous, and factors such as topography, elevation, distance from moisture sources, proximity to the sea, and humid atmospheric flows play a key role in determining PMP values. The highest PMP values during the baseline period were observed in the humid regions along the Caspian Sea coast, the northwestern highlands, and parts of the western slopes of the Zagros Mountains. In contrast, the central, eastern, and southeastern regions of Iran exhibited the lowest PMP values due to their distance from moisture sources and relatively flat topography. The results of Probable Maximum Precipitation (PMP) for the future period indicated that the spatial distribution pattern of PMP is similar to that of the baseline period, with an increase in PMP values expected in most parts of Iran compared to the baseline. The largest increase occurs under the SSP4.5 scenario. According to this scenario, the greatest rise in PMP relative to the baseline period is expected in the humid temperate regions of northern Iran and the semi-humid areas of western and northwestern Iran. An increase in PMP was also observed in the arid and semi-arid central and southern regions, but it is less intense compared to the humid climates. According to the SSP2.6 scenario, the greatest increase in PMP relative to the baseline period is observed primarily in the southern and southeastern regions. This difference in the spatial pattern of PMP increase is likely due to the differing responses of climate models to changes in temperature, pressure, and synoptic circulations. The results also indicated that the Probable Maximum Precipitation (PMP) under the SSP8.5 scenario is lower than under the other two scenarios. Under the SSP8.5 scenario, a relative decline in PMP compared to the baseline period was detected in certain northern and northwestern regions. This finding contradicts the initial expectation based on the theory that atmospheric moisture-holding capacity increases with temperature, and indicates that under very high emission scenarios, dynamic and thermodynamic atmospheric patterns may alter the trajectories of precipitation systems or the development of convective clouds. Therefore, the distinct response of humid regions under the SSP8.5 scenario highlights the complexity of climate change impacts and underscores the need for rigorous regional-scale analyses. On the other hand, the results showed that in the temperate and humid regions of the north, as well as the western slopes of the Zagros, although the Probable Maximum Precipitation (PMP) is high, the relative risk of flooding is lower than in hot and dry regions due to higher soil permeability, dense vegetation cover, and more efficient drainage networks.



Conclusion

The results of this study demonstrated that climate change exerts a substantial influence on variations in Probable Maximum Precipitation (PMP) across Iran, and that the spatial patterns of these changes differ markedly among various regions of the country. In the near future, the intensity of PMP is expected to increase across most regions of the country, with the greatest rise projected under the SSP4.5 scenario. A decrease in PMP in some northern parts of the country under the SSP8.5 scenario reflects the complexity and nonlinear behavior of precipitation systems under conditions of intense global warming. The results also showed that a high PMP does not necessarily imply a greater hazard, as geomorphological and hydrological conditions play a decisive role. Accordingly, strengthening flood-management strategies—particularly the design of hydrological structures in the arid regions of the country—is of critical importance, while in humid regions, runoff management and soil-erosion reduction are essential. The findings of this study highlight the need to revise water-resources management policies, hydraulic-structure design standards, and urban-planning strategies by incorporating the dynamic behavior of PMP under future climate conditions.