Investigating the Maximum Wind Speed and Wind Direction of Synoptic Stations in the East of Lake Urmia

Document Type : Research Article

Authors

• Pouya Allahverdipour ¹
• Mohammad Taghi Sattari ²

¹ Ph.D Student in Water Resources Engineering, Department of Water Engineering, Faculty of Agriculture, Tabriz University, Tabriz, Iran.

² Associate Professor in Water Resources Engineering, Department of Water Engineering, Faculty of Agriculture, Tabriz University, Tabriz, Iran.

10.22067/geoeh.2024.86654.1464

Abstract

Extended Abstract
Introduction
Using wind and converting it into a source of energy has been practiced in many countries since ancient times. On the other hand, weather is the cause of many natural disasters and accidents, and no part of the planet is immune to atmospheric hazards. Strong and intense winds, known as storms, cause significant damage to human living environments every year. Approximately 90% of the world's natural disasters are related to climatic factors. After floods, which account for approximately 35% of these disasters, storms are responsible for about 30% of the damage caused by natural disasters. The level of risk and damage caused by strong winds and storms depends on their direction, intensity, and the geographical location of the region. Considering the importance of wind in terms of its risks and potential, the study of this phenomenon has drawn the attention of researchers worldwide. Due to its arid and semi-arid climate, Iran experiences the negative effects and consequences of wind more than its benefits. East Azarbaijan Province, located east of Lake Urmia, is one of the windy regions of the country. Due to its proximity to the salt bed formed by the drying up of Lake Urmia, the province faces significant environmental and health hazards. By studying the speed and direction of strong winds in this region, management plans can be developed, vulnerability thresholds for structures determined, and resistant designs implemented to reduce resulting damages. The purpose of this research is to investigate the speed and direction of maximum wind and its changes while identifying vulnerable and windy areas east of Lake Urmia.
Material and Methods
This research investigated the speed, changes, and direction of maximum wind at 16 synoptic stations located east of Lake Urmia during the period of 1394–1401. The non-parametric Mann-Kendall trend test and Sen's slope estimator were used to determine the trend of wind speed changes. Wind Rose diagrams were used to analyze the prevailing wind direction. All calculations related to data preparation and tests for checking the trend of maximum wind speed were performed using XLSTAT software, and WRPLOT software was used to generate wind diagrams.
Results and Discussion
According to the results of the non-parametric Mann-Kendall test and Sen's slope estimator, among the 16 stations investigated in the east of Lake Urmia, significant increasing trends in maximum wind speed changes were observed only at Shabestar and Sahand stations, with Sen's slopes of +0.089 and +0.070, respectively. A significant decreasing trend was observed at Tabriz, Malekan, and Maragheh stations, with Sen's slopes of -0.058, -0.037, and -0.092, respectively. No trend in maximum wind speed changes was observed at Kalibar, Mianeh, Jolfa, Bostanabad, Bonab, and Sarab stations. Based on the Wind Rose diagrams, the prevailing wind direction at most stations is from the west and southwest, which could potentially increase respiratory diseases in the future due to salt storms originating from the dry bed of Lake Urmia affecting the eastern provinces. This pattern is likely related to the pressure gradient influenced by topography, the presence of Sahand mountain heights in the region, surface friction based on geographical characteristics, land use, and urban structures.
At specific stations, the prevailing wind direction was observed as follows: Bonab and Sarab from the west; Ahar, Charoimaq, Mianeh, Tabriz, and Varzeqan from the southwest; Bostanabad, Heris, Malekan, Marand, and Shabestar from the south; Jolfa and Kalibar from the northwest; Maragheh from the east; and Sahand from the west and southwest. The frequency of strong winds was high across all stations, with more than 50% of maximum winds exceeding 11.11 m/s.
 
Conclusion
The results of this research revealed that the maximum wind speed in the east of Lake Urmia was recorded at Varzeqan and Marand stations, while the lowest values were recorded at Kalibar and Jolfa stations. According to the Mann-Kendall trend test and Sen's slope estimator, changes in maximum wind speed at most synoptic stations showed either no trend or a decreasing trend, with significant increasing trends observed only at Shabestar and Sahand stations. Significant decreasing trends were observed at Tabriz, Malekan, and Maragheh stations. The prevailing wind direction at most stations was found to be from the west and southwest. These findings should be considered in structural design, including the orientation of buildings, power plants, and wind turbines. Additionally, they are critical for agricultural planning, such as rain irrigation system design.
The high frequency of strong winds across all synoptic stations underscores the vulnerability of this area to strong winds and storms, highlighting the importance of structural resilience. However, from an energy perspective, the region holds significant potential for wind power generation. Given the necessity of reducing dependence on fossil fuels due to their negative environmental impacts, including climate change, decreased precipitation, rising temperatures, and reduced water resources, utilizing wind power as a clean energy source becomes essential.
One limitation of this research was its focus on the eastern part of Lake Urmia. A broader study encompassing the entire Lake Urmia basin in all directions would provide a more comprehensive understanding of wind speed and direction changes under conditions of Lake Urmia's drying and the expansion of the salt bed. This would enable more precise land-use planning and management strategies for the coming years.

Keywords

• Wind Speed and Direction Analysis
• Mann-Kendall and Sen’s Slope Index
• Atmospheric Hazards
• Environmental Impacts
• Urmia Lake
• Wind Power Potential

Main Subjects

• Climatic and atmospheric hazards

---

References

Ahmadi, F., Khalili, K., Behmanesh, J., & Verdinazhad, V. (2013). Determination of Climate Changes on Air Temperature and Shahar-Chai River in the West of Urmia Lake Using Trend and Stationarity Analysis. Irrigation Sciences and Engineering, 35(4), 97-108. [In Persian] https://dorl.net/dor/20.1001.1.25885952.1391.35.4.10.0

Allahverdipour, P., & Sattari, M. T. (2023). Comparing the performance of the multiple linear regression classic method and modern data mining methods in annual rainfall modeling (Case study: Ahvaz city). Water and Soil Management and Modelling, 3(2), 125-142. [In Persian] https://doi.org/10.22098/mmws.2022.11337.1120

Allahverdipour, P., Ghorbani, M. A., & Asadi, E. (2024). Evaluating the effects of climate change on the climatic classification in Iran. Water and Soil Management and Modelling, 4(3), 95-112. [In Persian]. https://doi.org/10.22098/mmws.2023.12755.1271

Asakereh, H., Beyranvand, A., & Doustkamian, M. (2019). Assessment of wind power in the synoptic station of Ardebil. Spatial Planning, 8(3), 65-82. [In Persian] https://doi.org/10.22108/sppl.2018.110113.1179

Azorin‐Molina, C., Rehman, S., Guijarro, J. A., McVicar, T. R., Minola, L., Chen, D., & Vicente‐Serrano, S. M. (2018). Recent Trends in Wind Speed Across Saudi Arabia, 1978–2013: a Break in The Stilling. International Journal of Climatology, 38(1), e966-e984. https://doi.org/10.1002/joc.5423

Biabani, L., Nazari Samani, A., Khosravi, H., & Kazemzadeh, M. (2019). An investigation of the trends of monthly wind speed fluctuation on the edge of Lake Urmia over the last 30 years. Journal of Arid Biome, 9(1), 139-151. [In Persian] https://dorl.net/dor/20.1001.1.2008790.1398.9.1.11.5

Bilir, L., Imir, M., Devrim, Y., & Albostan, A. (2015). Seasonal and Yearly Wind Speed Distribution and Wind Power Density Analysis Based on Weibull Distribution Function. International Journal of Hydrogen Energy, 40(44), 15301-15310. http://doi.org/10.1016/j.ijhydene.2015.04.140

Dabbaghiyan, A., Fazelpour, F., Abnavi, M. D., & Rosen, M. A. (2016). Evaluation of Wind Energy Potential in Province of Bushehr, Iran. Renewable and Sustainable Energy Reviews, 55, 455-466. http://doi.org/10.1016/j.rser.2015.10.148

Deng, K., Azorin-Molina, C., Minola, L., Zhang, G., &Chen, D. (2021). Global Near-Surface Wind Speed Changes over the Last Decades Revealed by Reanalyses and CMIP6 Model Simulations. Journal of Climate, 34(6), 2219-2234. https://doi.org/10.1175/JCLI-D-20-0310.1

Ghaedi, S. (2019). Wind Speed Trends in Iran. Desert Management, 7(13), 15-28. [In Persian] https://doi.org/10.22034/jdmal.2019.36529

Hafner, M., Tagliapietra, S., & de Strasser, L. (2018). The challenge of energy access in Africa. Energy in Africa: Challenges and Opportunities, 1-21. https://doi.org/10.1007/978-3-319-92219-5_1

Hanafi, A., & Iranpour, F. (2017). Evaluation and zoning of wind speed potential in the country in order to plan for wind power generation. Journal of Climate Research, 8(31), 73-88. [In Persian] https://clima.irimo.ir/article_68879.html

Kendall, M. G. (1948). Rank Correlation Methods(3rd ed.). London: Griffin.

Klink, K. (2015). Seasonal patterns and trends of fastest 2‐min winds at coastal stations in the conterminous USA. International Journal of Climatology, 35(14), 4167-4175. https://doi.org/10.1002/joc.4275

Libanda, B., & Paeth, H. (2023). Modelling wind speed across Zambia: Implications for wind energy. International Journal of Climatology, 43(2), 772-786. https://doi.org/10.1002/joc.7826

Mahmood, F. H., Resen, A. K., & Khamees, A. B. (2020). Wind characteristic analysis based on Weibull distribution of Al-Salman site, Iraq. Energy Reports, 6, 79-87. https://doi.org/10.1016/j.egyr.2019.10.021

Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13(3), 245-259. https://doi.org/10.2307/1907187

Mazidi, A., & Bahaaddinbeygi, H. (2021). Study of temperature, precipitation and wind speed trends in the northern and western regions of Kerman province using parametric and non-parametric tests. Geography and Human Relationships, 4(2), 246-254. [In Persian] https://doi.org/10.22034/gahr.2021.296784.1587

Mofidi, A., & Kamali, S. (2012). Investigating the Structure of Dust-storms in the Sistan Region by using Regional Climate Model RegCM4; Case Study July 30, 2001. 1st National Desert Conference, University of Tehran, Tehran, Iran. [In Persian]

Molaei, A., & Lashkari, H. (2020). Investigation of wind speed trend changes in central Iran using ECMWF Reanalysis data. Physical Geography Research, 52(3), 481-498. [In Persian] https://doi.org/10.22059/jphgr.2020.295406.1007476

Raeispoor, K., Beykrezaei, E., & Tavoosi, T. (2013). Statistical Analyze and Predicting Incident Probability of Stormy and Strong Winds in Kermanshah Province. Geography and Environmental Planning, 24(3), 93-106. [In Persian] https://dorl.net/dor/20.1001.1.20085362.1392.24.3.9.8

Raheja, L., Wadalkar, R., Chaudhuri, R. R., & Pandit, A. (2024). Surface wind speed trends for the period of 1981–2020 and their implication for a highly urbanised semi-arid Delhi–NCR and surrounding areas. Journal of Earth System Science, 133(2), 112. https://doi.org/10.1007/s12040-024-02322-2

Sattari, M. T., & Allahverdipour, P. (2024). Application of tree-based intelligence methods for wind speed estimation at the east of Lake Urmia. In: Kahraman, C., Cevik Onar, S., Cebi, S., Oztaysi, B., Tolga, A.C., Ucal Sari, I. (eds) Intelligent and Fuzzy Systems. INFUS 2024. Lecture Notes in Networks and Systems, 1090. Springer, Cham. https://doi.org/10.1007/978-3-031-67192-0_20

Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall's tau. Journal of the American Statistical Association, 63(324), 1379-1389. https://doi.org/10.1080/01621459.1968.10480934

Shi, H., Dong, Z., Xiao, N., & Huang, Q. (2021). Wind speed distributions used in wind energy assessment: a review. Frontiers in Energy Research, 9, 769920. https://doi.org/10.3389/fenrg.2021.769920

Ying, J., Yong, L., & Zongci, Z. (2013). Maximum wind speed changes over China. Acta Meteorology Sinica, 27(1), 63-74. https://doi.org/10.1007/s13351-013-0107-x