سازمان هواشناسی کشورنیوار1735-056550Special Issue (S2)20260321Decoding the Direction and Magnitude of Wind Speed Trends Using Multiple Statistical ApproachesDecoding the Direction and Magnitude of Wind Speed Trends Using Multiple Statistical Approaches12024526910.30467/nivar.2026.557484.1358FAHediehAhmadpariPhD candidate, Hydrology of land, water resources, hydrochemistry, Department of Engineering Hydrology, Institute of Hydrology and Oceanology, Russian State Hydrometeorological University0000-0002-3639-1651VitalyKhaustovCandidate of Technical Sciences, Associate Professor, Department of Engineering Hydrology, Institute of Hydrology and Oceanology, Russian State Hydrometeorological University0000-0003-0182-5699HamedAbasalinezhadمسئول هواشناسی کشاورزی استان آذربایجان غربی-کارشناس همدیدی اداره تحقیقات هواشناسی کشاورزی- دبیر توسعه هواشناسی کاربردی تهک کشاورزی0000-0002-1887-9557Journal Article20251104Analyzing wind speed trends provides valuable insights into regional climate dynamics, atmospheric circulation changes, and their impacts on environmental and energy systems. This study investigates the temporal trends of monthly and annual wind speed in the Darreh Dozdan River basin, located in Lorestan Province, Iran, using a 25-year dataset (1998–2022) from the Kuhdasht synoptic station. Both parametric (linear regression and Pearson correlation coefficient) and nonparametric (Mann–Kendall test and Sen’s slope estimator) methods were applied to detect and quantify wind speed trends. The Mann–Kendall test showed that all months had positive and statistically significant Z values greater than +1.96, confirming a persistent upward trend in wind speed. The strongest increases occurred in June, August, and September (Z = 4.27–4.86), reflecting intensified wind activity during the warmer months. The Sen’s slope and linear regression analyses revealed the largest increases in wind speed during February (0.12 m/s per year) and March (0.14 m/s per year), indicating that wind speeds rose most rapidly in late winter and early spring, while the annual results from both methods confirmed a steady increase in average wind speed of 0.08 m/s per year. Pearson correlation coefficients showed significant positive relationships (r > 0.6 for all months), with the strongest correlations in June, August, and September (r > 0.8), confirming a highly consistent and stable upward trend during these months. All four analytical methods converged on the conclusion that wind speed had increased in a statistically significant and persistent manner, differing only in which months exhibited the steepest or most stable growth, thereby providing a comprehensive and robust confirmation of wind intensification in the Darreh Dozdan River basin. These findings highlight the importance of accounting for increasing wind intensity in future regional climate assessments, water resource management, and land-use planning within the basin.Analyzing wind speed trends provides valuable insights into regional climate dynamics, atmospheric circulation changes, and their impacts on environmental and energy systems. This study investigates the temporal trends of monthly and annual wind speed in the Darreh Dozdan River basin, located in Lorestan Province, Iran, using a 25-year dataset (1998–2022) from the Kuhdasht synoptic station. Both parametric (linear regression and Pearson correlation coefficient) and nonparametric (Mann–Kendall test and Sen’s slope estimator) methods were applied to detect and quantify wind speed trends. The Mann–Kendall test showed that all months had positive and statistically significant Z values greater than +1.96, confirming a persistent upward trend in wind speed. The strongest increases occurred in June, August, and September (Z = 4.27–4.86), reflecting intensified wind activity during the warmer months. The Sen’s slope and linear regression analyses revealed the largest increases in wind speed during February (0.12 m/s per year) and March (0.14 m/s per year), indicating that wind speeds rose most rapidly in late winter and early spring, while the annual results from both methods confirmed a steady increase in average wind speed of 0.08 m/s per year. Pearson correlation coefficients showed significant positive relationships (r > 0.6 for all months), with the strongest correlations in June, August, and September (r > 0.8), confirming a highly consistent and stable upward trend during these months. All four analytical methods converged on the conclusion that wind speed had increased in a statistically significant and persistent manner, differing only in which months exhibited the steepest or most stable growth, thereby providing a comprehensive and robust confirmation of wind intensification in the Darreh Dozdan River basin. These findings highlight the importance of accounting for increasing wind intensity in future regional climate assessments, water resource management, and land-use planning within the basin.https://nivar.irimo.ir/article_245269_33761c6bd739cedfe1e86cf29489ace1.pdfسازمان هواشناسی کشورنیوار1735-056550Special Issue (S2)20260321Analysis of Climate Scenarios and Wheat Water Productivity in Khorasan Razavi Province with a Sustainability ApproachAnalysis of Climate Scenarios and Wheat Water Productivity in Khorasan Razavi Province with a Sustainability Approach214324579810.30467/nivar.2026.570227.1365FATahmineDehghaniPhD Candidate in Irrigation and Drainage, Department of Irrigation and Reclamation, Faculty of Agriculture and Natural Resource, University of Tehran, Karaj, Iran.0000-0002-1064-7356AbdolmajidLiaghatProfessor, Department of Irrigation and Reclamation, Faculty of Agriculture and Natural Resource, University of Tehran, Karaj, Iran0000-0002-3224-6529BijanNazariAssociate Professor, Department of Irrigation and Reclamation, Faculty of Agriculture and Natural Resource, University of Tehran, Karaj, Iran; Faculty Member at Imam Khomeini International University, Qazvin, Iran0000-0002-9356-5961Journal Article20260102Climate change, as one of the major challenges of the 21st century, has widespread impacts on agricultural production and food security. In this study, LARS-WG 8 models were used to generate climate data and AquaCrop 7.1 to simulate wheat yield in Khorasan Razavi Province. the effects of different greenhouse gas emission scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) were assessed towards 2040. The results showed that the LARS WG model performs reasonably well in generating average precipitation and temperature, but shows limitations in representing temperature variability and fluctuations. According to the results the average temperature at Sabzevar, Quchan, and Torbat-e Jam stations will increase the most in the SSP5-8.5 scenario; for example, the average temperature in Quchan will increase from 12.7 degrees in the period 2010-2024 to 14.1°C in SSP5-8.5. Future precipitation is expected to increase by 11–38 %, while reference evapotranspiration (ET0) may decline by 8–32%. The average grain yield of wheat in Khorasan Razavi Province is projected to increase by about 7 to 13% across scenarios. Water productivity (WP) has also projected to rise from 1.7 in 2023 to 1.9 and 2.0 under different scenarios.<br>The findings of this study indicate that climate change in the 2040 horizon could, under some conditions, lead to increased yield and water productivity of wheat in Khorasan Razavi Province. However, these increases will only be sustainable if they are accompanied by smart water resource management, selection of resistant varieties, and adaptive policies to address the risks of warming, changing rainfall patterns, and the spread of pests and diseases. Therefore, although the short-term results are promising, from a sustainability perspective, a comprehensive and forward-looking approach is required to ensure food security and agricultural resilience in the region.Climate change, as one of the major challenges of the 21st century, has widespread impacts on agricultural production and food security. In this study, LARS-WG 8 models were used to generate climate data and AquaCrop 7.1 to simulate wheat yield in Khorasan Razavi Province. the effects of different greenhouse gas emission scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) were assessed towards 2040. The results showed that the LARS WG model performs reasonably well in generating average precipitation and temperature, but shows limitations in representing temperature variability and fluctuations. According to the results the average temperature at Sabzevar, Quchan, and Torbat-e Jam stations will increase the most in the SSP5-8.5 scenario; for example, the average temperature in Quchan will increase from 12.7 degrees in the period 2010-2024 to 14.1°C in SSP5-8.5. Future precipitation is expected to increase by 11–38 %, while reference evapotranspiration (ET0) may decline by 8–32%. The average grain yield of wheat in Khorasan Razavi Province is projected to increase by about 7 to 13% across scenarios. Water productivity (WP) has also projected to rise from 1.7 in 2023 to 1.9 and 2.0 under different scenarios.<br>The findings of this study indicate that climate change in the 2040 horizon could, under some conditions, lead to increased yield and water productivity of wheat in Khorasan Razavi Province. However, these increases will only be sustainable if they are accompanied by smart water resource management, selection of resistant varieties, and adaptive policies to address the risks of warming, changing rainfall patterns, and the spread of pests and diseases. Therefore, although the short-term results are promising, from a sustainability perspective, a comprehensive and forward-looking approach is required to ensure food security and agricultural resilience in the region.https://nivar.irimo.ir/article_245798_fbaa8955494033c158299276396ea464.pdf