Document Type : Research Paper

Authors

• Nezam Tani ¹
• Kamal Omidvar ²
• Ahmd Mazidi ³
• GHolam ali Mozafari ²

¹ PhD student, Department of Meteorology, Natural Hazards, Yazd University, Yazd, Iran

² Professor, Department of Meteorology, Yazd University, Yazd, Iran

³ Associate Professor, Department of Meteorology, Yazd University, Yazd, Iran

Abstract

Introduction
Changes in river discharge fluctuations, whether increases or decreases, can lead to irreversible damage to both human and natural environments. It is now well established that variations in the phases of teleconnection patterns can cause significant increases or decreases in river discharge across different regions of the world, depending on their influence on precipitation cycles, evapotranspiration, and drought occurrence.
 
Materials and methods
For this study, data on 28 major teleconnection indices affecting Iran’s climate were obtained from the NOAA website. In addition, river discharge records from selected hydrometric stations located upstream of the dams on the Karun River (Telezang, Lordegan, Armand, Pataveh, and Kata stations) were collected from the Ministry of Energy for a 30-year period (1993–2022). Following a preliminary assessment of the discharge data, missing values were reconstructed using the multiple regression method to ensure data consistency and reliability. This method was chosen for its ability to preserve the general trend of the dataset while minimizing disturbance to the data. To analyze the trends and magnitude of seasonal and annual discharge variations, the non-parametric Mann–Kendall test and Theil–Sen slope estimator were applied. Furthermore, the relationship between teleconnection indices and river discharge was examined using the Pearson correlation coefficient across three temporal scales: monthly, seasonal, and annual. These correlations were assessed both simultaneously and with time lags of one to three months. Given the large number of indices, only those with statistically significant correlations with discharge were included in the final analyses.
 
Results and discussion
The results indicated that, overall, the mean discharge exhibited a continuous decreasing trend during the study period. Specifically, the mean discharge in all seasons showed a declining pattern, and at the annual scale, a significant decrease of 11.3 m³/s per year was observed, accompanied by a negative Mann-Kendall statistic (Z = –4.1). The correlations between teleconnection patterns and discharge in the study basin were further explored. The findings revealed that, at different temporal scales (monthly, seasonal, and annual), several teleconnection indices—including GLBTS, WHWP, SOI, Solar Flux, TSA, TNA, NINO4, AMO, AMM, MEI v2, PDO, NINO1+2, AAO, Warm Pool, PNA, EPO, WP, TNH, NCP, RMM1, and RMM2-exhibited statistically significant correlations (at the 0.05 and 0.01 confidence levels) with the discharge of the Karun River headwaters, either simultaneously or with lags of one to three months.
 
Conclusions
Overall, the mean discharge recorded at the selected upstream stations of the Karun River dams demonstrated a decreasing trend. Moreover, the study confirmed the existence of significant simultaneous and lagged correlations between the fluctuations of several teleconnection indices and river discharge. Consequently, it can be concluded that the identified teleconnection patterns exert considerable influence on discharge variations in the basin. Given the predictability of these teleconnection indices and their significant correlations with discharge, future fluctuations of the Karun River discharge can potentially be forecasted at monthly, seasonal, and annual scales based on the findings of this research.

Keywords

• Correlation
• Lordegan
• Multiple regression
• Non-parametric Mann–Kendall test
• River discharge