Journal of Rainwater Catchment Systems

fa تحلیل ارتباط الگوی دورپیوندی دریای شمال–خزر با تغییرات بارش در حوضه آبریز دریاچه ارومیه Analysis of the Teleconnective Link between the North Sea–Caspian Pattern (NCP) and Precipitation Variability in the Lake Urmia Basin تخصصي Special پژوهشي Research <table align="right" class="Table" dir="rtl" style="width:100.0%; border-collapse:collapse; border:none" width="100%"> <tbody> <tr> <td style="border-bottom:1px dashed #4bacc6; width:69%; padding:0in 7px 0in 7px; height:19px; border-top:1px dashed #4bacc6; border-right:1px dashed #4bacc6; border-left:1px dashed #4bacc6" valign="top">این پژوهش به واکاوی الگوهای پیوند از دور میان نوسانات بارشی حوضه آبریز دریاچه ارومیه و شاخص دورپیوندی دریای شمال–خزر (NCPI) اختصاص یافته است. بدین منظور، آمار بارش ماهانه پنج ایستگاه همدیدی منتخب طی دوره ۳۰ ساله (۲۰۱۴–۱۹۸۵) از سازمان هواشناسی گردآوری و شاخص NCPI با استفاده از داده‌های ارتفاع ژئوپتانسیل تراز ۵۰۰ هکتوپاسکال بازتحلیل NCEP/NCAR محاسبه شد. سپس ضرایب همبستگی پیرسون میان بارش و شاخص NCPI در نرم‌افزار R محاسبه و الگوهای پهنه‌بندی مکانی آن با روش وزن‌دهی معکوس فاصله (IDW) در محیط GIS ترسیم گردید. نتایج نشان‌دهنده ماهیتی متغیر و وابسته به زمان در این پیوند است. در ماه نوامبر، علامت همبستگی مثبت (مستقیم) سراسر حوضه را دربرمی‌گیرد و در سه ایستگاه سقز (r=0.50)، ارومیه (r= 0.46) و تبریز (r=0.43)  به معناداری اسمی (p<0.05) می‌رسد؛ بررسی معناداری میدانی ماه نوامبر نیز مؤید آن است که این پاسخ هماهنگ، با الگوی فضایی منسجم‌تر در مقیاس حوضه همخوانی دارد. در سایر ماه‌های مرطوب (فوریه، مارس و آوریل)، پیوندهای معنادار اسمی عمدتاً در زیرحوضه‌های غربی و جنوب‌غربی (ایستگاه‌های مهاباد و سقز) متمرکز بوده و در ایستگاه مراغه واکنش آماری پایداری مشاهده نشد. این یافته‌ها بیانگر آن است که هم‌سویی نوسانات بارش با مقادیر شاخص NCPI در دوره سرد سال، با شرایط جوی مساعد برای تقویت و عبور سامانه‌های باران‌زای مدیترانه‌ای به پهنه شمال‌غرب ایران همخوانی دارد. با در نظر گرفتن ملاحظات آماری آزمون‌های چندگانه (BH-FDR, qmin=0.208)، اگرچه ضرایب به معناداری سخت‌گیرانه دست نیافتند، اما این الگوهای اکتشافی می‌توانند بینش‌های اکتشافی نوینی را برای واکاوی نوسانات اقلیمی حوضه در پژوهش‌های آتی فراهم سازند.</td> </tr> </tbody> </table> Introduction: In recent decades, Lake Urmia has experienced a critical decline in its water level, driven by both increasing drought severity and anthropogenic pressures such as uncontrolled agricultural expansion, excessive groundwater abstraction, and inefficient water resources management. At the same time, regional studies have indicated a declining trend in precipitation. Among the large-scale atmospheric factors associated with hydroclimatic variability, teleconnection patterns—particularly the North Sea–Caspian Pattern (NCP)—play an important role. Due to its relative geographical proximity to the study area, variations in this index and its positive and negative values are closely linked to regional precipitation and temperature anomalies across the basin. Methodology: The study area is the Lake Urmia Basin in northwest Iran. To conduct this research, monthly precipitation data from five synoptic stations located across the basin (Tabriz, Urmia, Mahabad, Saqqez, and Maragheh) were obtained from the Iran Meteorological Organization for the 30-year period 1985–2014 (N=30). In addition, the North Sea–Caspian Pattern Index (NCPI) was calculated using NCEP/NCAR reanalysis data based on the difference between standardized 500-hPa geopotential heights anomalies over the North Sea and the northern Caspian Sea. Monthly Pearson correlation coefficients were computed within the R statistical environment. To address the multiplicity effect arising from simultaneous station-month hypothesis testing, the False Discovery Rate (FDR) procedure via the Benjamini–Hochberg method was applied. Furthermore, field significance was evaluated to ensure that spatially coherent basin responses exceeded random point-wise noise. The spatial patterns of correlation coefficients were mapped using Inverse Distance Weighting (IDW) interpolation in a GIS environment to explore spatial-temporal associations between the NCPI and basin precipitation. Results and Discussion: Evaluation of the monthly relationships between precipitation and the NCPI revealed that, among the five stations, four stations (Tabriz, Mahabad, Urmia, and Saqqez) exhibited nominally significant responses (p < 0.05) in certain wet months, whereas no nominally significant correlation was detected at Maragheh station. Spatially and temporally, the highest coherence appeared in November, during which positive correlations covered the entire basin and reached nominal significance at Saqqez (r = 0.50, p = 0.005), Urmia (r = 0.46, p = 0.010), and Tabriz (r = 0.43, p = 0.018); field significance testing confirmed that this November signal was not an artifact of random local variability. Nominally significant positive correlations were also observed in other cold/wet months: February and April at Mahabad (r = 0.44, p = 0.015 and r = 0.42, p = 0.021, respectively), and March at Saqqez (r = 0.44, p = 0.015). In all responsive station-months, higher NCPI values corresponded directly to increased precipitation. Spatially, stronger signals were concentrated in the western and southern sectors of the basin (Urmia, Mahabad, and Saqqez). However, after applying the multiplicity correction via the Benjamini–Hochberg FDR test across the 60 station-month tests, none of the individual correlation coefficients survived strict statistical significance (qmin = 0.208). Therefore, these spatial configurations should be interpreted as exploratory empirical patterns rather than deterministic statistical linkages. Conclusion: The findings indicate that the association between precipitation and the NCPI in the Lake Urmia Basin is predominantly confined to the cold and wet seasons, reaching its peak spatial coherence in November. Nominally significant direct correlations were concentrated across the western and southern sub-basins (Urmia, Mahabad, and Saqqez), while the eastern sector (notably Maragheh) exhibited no persistent statistical response. In line with rigorous statistical standards, the lack of strict FDR significance requires interpreting these teleconnection signals as exploratory patterns rather than definitive causal relationships. Nevertheless, these empirical patterns provide valuable baseline insights into large-scale atmospheric patterns affecting northwest Iran, offering exploratory utility for regional hydroclimatic monitoring and future climate variability studies.   آبریز دریاچه ارومیه، بارش، پیوند از دور، تحلیل همبستگی، دریای شمال–خزر Correlation Analysis, Lake Urmia Basin, North Sea–Caspian Pattern (NCP), Precipitation, Teleconnection 0 0 http://jircsa.ir/browse.php?a_code=A-10-2437-2&slc_lang=fa&sid=1 Bromand Salahi برومند صلاحی Salahi@uma.ac.ir 10031947532846006581 10031947532846006581 Yes University of Mohaghegh Ardabili دانشگاه محقق اردبیلی Ali Shahi علی شاهی ali.shahi@uma.ac.ir 10031947532846006582 10031947532846006582 No University of Mohaghegh Ardabili دانشگاه محقق اردبیلی