Introduction and Goal It is essential to examine how watershed systems' behavior changes in response to their inputs. Studying the magnitude of hydrological components like precipitation and runoff with different return periods has received limited attention, or each component has been analyzed separately. Meanwhile, the complex, nonlinear relationships between precipitation and runoff are influenced by factors such as physiographic features, soil, vegetation cover, and land-use. Therefore, compound analysis of these components can offer a more accurate understanding of the watershed's hydrological response, especially during extreme events. This study therefore concentrates on the simultaneous analysis of precipitation and runoff with different return periods in the Neyshabur Watershed in Khorasan Razavi, Iran. Materials and Methods Data on annual precipitation and runoff from 1991 to 2021 were collected from four hydrometric stations and five reliable rain gauge stations representing diverse hydrological conditions within the watershed. Using statistical methods, the accuracy of precipitation and discharge data was verified, and any incomplete or irregular values were corrected or replaced as needed. Then, the annual and maximum annual values of daily precipitation and discharge data were compiled to enable extended analysis and explore the asynchronous behavior of these parameters. Using the Hyfran-Plus model, return period analysis was performed for intervals of 2, 5, 10, 20, 50, 100, and 200 years. In this analysis, the Weibull and Gumbel distributions were identified as the best fits for the precipitation and discharge data, respectively, among the statistical distributions tested. Results and Discussion Additionally, the results show that rainfall and runoff vary across watersheds for different return periods. As the return period increases, maximum instantaneous discharge, mean annual discharge, and runoff volume all rise significantly at all stations, though at different rates. In short-term periods of 5 to 2 years, the amounts of precipitation, maximum instantaneous discharge, mean annual discharge, and runoff volume recorded at Eishabad station are 1.23, 2.06, 2.39, and 4.91 respectively; at Taghoun station, 1.23, 2.00, 2.22, and 4.00 respectively; at Dorud station, 1.23, 1.90, 2.16, and 4.13 respectively; and at Zarandeh station, 1.24, 1.87, 2.09, and 2.78 respectively. For longer periods of 200 to 100 years, the amounts at Eishabad station are 1.04, 1.13, 1.14, and 1.28; at Taghoun station are 1.04, 1.13, 1.13, and 1.28; at Dorud station are 1.03, 1.13, 1.13, and 1.46; and at Zarandeh station are 1.04, 1.13, 131, and 1.28. The variations are mainly due to the watershed's physiographic features, slope, soil type, and land-use. Conclusion and Suggestions The findings highlight that using simultaneous and multivariate approaches in return period analysis is crucial for designing flood and sediment control structures, predicting hydrological events, and managing water and soil resources sustainably in semi-arid plains. The results show that the relationship between precipitation and runoff across different return periods is nonlinear and amplified, emphasizing the importance of considering these components together in flood risk assessment and water infrastructure planning. Additionally, the significant spatial differences in how sub-watersheds respond hydrologically stress the need to develop management strategies tailored to each watershed's specific conditions. Since semi-arid watersheds are highly vulnerable to climate change, combining long-term hydroclimatic data with advanced statistical models can help reduce prediction uncertainties. Finally, expanding such studies to other similar watersheds and including the sediment component in future work can be an effective step toward comprehensive and resilient water and soil resource management. Building on these conclusions, future research should focus on developing integrated hydrological models that dynamically link climate projections with land-use change scenarios. These models would enhance our ability for adaptive water management. Encouraging collaboration among hydrologists, climatologists, and land-use planners is, therefore, essential to turn these scientific insights into appropriate, watershed-specific policies and engineering standards that improve ecosystem services and community resilience in vulnerable semi-arid areas. |