Hydrological Behavior Simulation of the Neyshabur Watershed in Iran during Different Rainfall and Runoff Return Periods

Introduction and Goal
Investigating the response behavior of hydrological systems to inputs such as precipitation, particularly runoff analysis under different return periods is one of the primary objectives of hydrological research. The analysis of the return periods of hydrological components, including precipitation and runoff, has a long history. However, less attention has been paid to the comparative and simultaneous assessment of these components and to the analysis of their asynchronous behavior under different return periods. On the other hand, the complex and nonlinear relationships between precipitation and runoff, as well as the observed differences among stations, are attributed to the local conditions governing each sub-watershed. In this regard, the simultaneous assessment of these components can offer a more accurate understanding of the watershed's hydrological response, especially during extreme events conditions. Therefore, in this study, precipitation and runoff magnitudes were simultaneously investigated under different return periods in the Neyshabur Watershed in Khorasan Razavi, Iran.
Materials and Methods
Data on annual precipitation and runoff for the period from 1991 to 2021 were collected from four hydrometric stations, which represented different hydrological conditions within the watershed. Using statistical methods, precipitation and discharge data were verified in terms of quality, and missing values or data inconsistent with hydrological trends were corrected or replaced using linear regression and correlation analysis with neighboring stations. After data correction, daily precipitation and discharge values were converted into annual precipitation and discharge values. This process enabled long-term analysis and the assessment of the asynchronous behavior of the components. The corresponding precipitation and runoff magnitudes for return periods of 2, 5, 10, 20, 50, 100, and 200 years were estimated using the Hyfran-Plus software. In this analysis, among various statistical distributions, the Weibull distributions for precipitation data and the Gumbel distributions for discharge data were selected as the best-fit distributions for the studied datasets, based on the recommendation of the decision support system and using Akaike and Bayes information criteria.
Results and Discussion
The results show that the rainfall magnitudes for return periods of 2, 5, 10, 20, 50, 100, and 200 years were 290.26, 357.25, 391.87, 418.47, 447.40, 465.67, and 482.54 mm, respectively. Across different sub-watersheds, the return periods of precipitation and runoff were not consistent, and with increasing precipitation return periods, the instantaneous peak discharge, mean annual discharge, and runoff volume increased significantly at all stations, but with different rates of change. 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. While the aforementioned ratio in long-term periods of 200 to 100 years, the precipitation amounts, maximum instantaneous discharge, average annual discharge, and runoff volume were obtained at Eishabad station 1.04, 1.13, 1.14, and 1.28; at Taghoun station 1.04, 1.13, 1.13, and 1.28; at Dorud station 1.03, 1.13, 1.13, and 1.46; and at Zarandeh station 1.04, 1.13, 131, and 1.28 respectively. These differences are likely due to local watershed characteristics.
Conclusion and Suggestions
The findings of this study confirmed that the use of simultaneous and multivariate approaches in precipitation and runoff 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 the hydrological response of sub-watersheds indicate the importance of developing management strategies based on the specific conditions of each watershed. Given the high susceptibility of semi-arid watersheds to climate change, the uncertainty in predictions can be reduced by combining long-term hydroclimatic data with advanced statistical models. Finally, expanding such studies to other similar watersheds, as well as incorporating the sediment component in future analyses, is an effective step towards comprehensive and resilient management of water and soil resources. Based on the results of this study, it is suggested that future research focus on developing integrated hydrological models that dynamically link climate projections with land-use change scenarios. With such models and analyses, the ability of experts to comprehensively manage water and soil resources, reduce flood risks, and plan land-use in a manner that is consistent and based on the conditions of each watershed will increase. Furthermore, it is recommended to promote collaboration among hydrologists, climatologists, and land-use planners to translate these scientific insights into appropriate and region-specific engineering policies and standards, in order to improve ecosystem services and community resilience in vulnerable semi-arid regions.