Investigating the relationship between dustiness indices and the aerosols optical depth around the Horulazim wetland

Document Type : Research Paper

Authors

1 M.Sc., Department of Nature Engineering, Faculty of Agriculture and Natural Resources, Ardakan University, Ardakan, Iran

2 Associate Professor, Department of Nature Engineering, Faculty of Agriculture & Natural Resources, Ardakan University, Ardakan, Iran

3 Assistant Professor, Department of Nature Engineering, Faculty of Agriculture & Natural Resources, Ardakan University, Ardakan, Iran

4 Associate professor in Combating desertification, Department of Environmental Science and Engineering, Faculty of Natural Resources, University of Jiroft, Jiroft, Iran

10.29252/aridbiom.2023.19686.1923

Abstract

The phenomenon of dust in recent years has been one of the most important environmental challenges, which has been exacerbated by destructive human activities and has had adverse effects on the environment and human health. Considering that wetlands play an essential role in the balance of water and climate and also prevent the entry of fine dust; The present study was conducted with the aim of analyzing the relationship between the optical depth of aerosol particles (AOD) and the indices of dust-based soil in the area of Horulazim wetland. For this purpose, daily AOD product, MODIS sensor bands and hourly data of dust occurrences related to 3 meteorological stations of Ahvaz, Safi-Abad and Sulaiman masjed were obtained from their supply sources in a period of 18 years (2000-2018). Hourly data recorded in synoptic stations were used to calculate dust storm index (DSI) and MODIS sensor bands were used to extract BTD, BTDI, TIIDI, TDI, Miller and NDDI indices. Linear and non-linear regression methods were used to analyze the relationship between the mentioned indices and AOD. The results of the analysis of the relationship between DSI-AOD showed the very poor performance of this index in the analysis of dust events in all three study stations (R2<0.2). In Ahvaz, Safi Abad and Masjid Sulaiman masjed stations, the maximum value of R2 was observed between AOD-BTDI (0.48), AOD-Miller (0.503) and AOD-BTD (0.50), respectively. These results indicate that, on average, about 50% of the changes in the optical depth of aerosols can be explained using the three indices BTDI, Miller and BTD. Therefore, it is recommended to use these indicators in order to analyze the dust events around Horul Azim lagoon.

Keywords

References

[1]. Afrasyabi, S., Tazeh, M., Taghizadeh Mehrjardi, R., Ghanei bafghi, M. J., & Kalantari, S. (2022). Performance of two measurement methods of pin meter and laser disto meter in the measurement of microtopography Created by desert pavement. Desert Ecosystem Engineering, 8(22), 1-14. doi: 10.22052/deej.2018.7.22.45. [in Farsi]
[2]. Almasi, A., Mousavi, A. R., Bakhshi, S., & Namdari, F. (2014). Dust storms and environmental health impacts. Journal of Middle East Applied Science and Technology, 8(1), 353-6.
[3]. Aloysius, M., Mohan, M., Suresh Babu, S., Parameswaran, K., & Moorthy, K. K. (2009). Validation of MODIS derived aerosol optical depth and an investigation on aerosol transport over the South East Arabian Sea during ARMEX-II. Annales Geophysicae, 27, 2285-2296.
[4]. Azad, M., Kalantari, S., Shirmardi, M., & Tazeh, M. (2022). Investigating the Effect of Land Use and Soil’s Physio-chemical properties on Wind Erosion Threshold Velocities via Data Mining. Desert Ecosystem Engineering, 9(29), 1-14. doi: 10.22052/deej.2020.9.29.1. [in Farsi]
[5]. Demizadeh, M., Mahdavi, R., Nowrozi, A.A., HaliSaz, A., & Gholami, H. (2020). Detection and analysis of dust in Hormozgan province. Watershed Engineering and Management, 13(1), 111-124. [in Farsi]
[6]. Ebrahimi Khosfi, Z., vali, A. A., Khosrow Shahi, M., & Qazdavi, R.  (2016). Investigating the role of the dried up surfaces of the Govkhoni wetland on the generation of dusts using Landsat and landsat images (case study: Isfahan city). Iran's Pasture and Desert Research, 24(1), 152-164. [in Farsi]
[7]. Fathizad, H., Tazeh, M., Kalantari, S., & Shojaei, S. (2017). The investigation of spatiotemporal variations of land surface temperature based on land use changes using NDVI in southwest of Iran. Journal of African Earth Sciences, 134, 249-256.
[8]. Filonchyk, M., Yan, H., & Zhang, Z. (2018). Analysis of spatial and temporal variability of aerosol optical depth over China using MODIS combined Dark Target and Deep Blue product. Theoretical and Applied Climatology, 137(1), 2271-2288.
[9]. Givehchi, R., Arhami, M., & Tajrishy, M. (2013). Contribution of the Middle Eastern dust source areas to PM10 levels in urban receptors: Case study of Tehran, Iran. Atmospheric environment, 75, 287-295.
[10]. Hao, X., & Qu, J. J. (2007). Saharan dust storm detection using moderate resolution imaging Spector radiometer thermal infrared bands. Journal of Applied Remote Sensing, 1, 013510.
[11]. Liu, Y., & R. Liu. (2011). A thermal index from MODIS data for dust detection. International Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada.
[12]. Jebali, A., Zare, M., Ekhtesasi, M. R., & Jafari, R. (2018). Performance evaluation of dust storm detection algorithms in arid areas (case study of Yazd province). Journal of Desert Ecosystem Engineering, 8(23), 105-85. [in Farsi]
[13]. Kargaran, F., Kalantari, S., Ghaneei, M.J., & Tazeh, M. (2017). The Compare of grading criteria in Coarse ripple Mark on the windward and leeward slopes (Case Study: Hassan Abad erg in Bafg). Quantitative geomorphological research, 4(1), 134-144. [in Farsi]
[14]. Khairandish, Z., Jamali, J. B., & Raigani, B. (2017). Identifying the best dust detection algorithm using MODIS data. Journal of Natural Environment Hazards, 7(15), 205-218. [in Farsi]
[15]. Mobasheri, M., Ghorbani-Salkhurd, R., & Rahim-Zadegan, M. (2019). Ability of MODIS sensor data in qualitative and quantitative analysis of air quality in urban areas. Climatology Research Journal, 1(34), 59-72. [in Farsi]
[16]. Taghizadeh, R., Ghazali, A., Kalantari, S., & Rahimian, M. (2016). Spatial distribution of soil salinity using auxiliary variables and hypercube sampling method in Meybod. Journal of Arid Biome, 6(1), 69-79. [in Farsi]
[17]. Zarei, M., Tazeh, M., Moosavi, V., & Kalantari, S. (2021). Evaluating the changes in Gavkhuni Wetland using MODIS satellite images in 2000-2016.  Nature and Spatial Sciences, 1, 27-41. [in Farsi]
[18]. Samadi, M. (2011). Detection and origin of dust storms using satellite images.  Department of Cartography, Master's thesis, University of Tehran.  [in Farsi]
[19]. Small, I., Van der Meer, J., & Upshur, R.E.G. (2001). Acting on an environmental health disaster: the case of the Aral Sea. Environmental Health Perspectives, 109, 547-549.
[20]. Soleimani, A., Askari, H. M., Dadalhi Sohrab, A., Elmizadeh, H., & Khazaei, S.H. (2014). Evaluation of optical depth obtained from MODIS satellite images in the Persian Gulf. Journal of Marine Science and Technology, 14(4), 75-83. [in Farsi]
[21]. Zehtabian, G.R., Ahmadi, H., Samani Nazari, A. A., Ehsani, A. H., & Tazeh, M. (2017). Determinig the most important geomorphometric parameters in classification of desert plans using artificial networks and sensitivity analysis. Range and Watershed Management, 70(1), 197-206. [in Farsi]
[22]. Zeinali, B., & Asghari, S. (2017). Evaluation of some dust identification indicators and its monitoring (case study: August 10, 2008 storm in eastern Iran). Geography and Planning Scientific-Research Journal, 22(65), 1-18. [in Farsi]
[23]. Zoljoodi, M., Didevarsal, A., & Ranjbar Saadatabadi, A. (2013). Dust events in the western parts of Iran and the relationship with drought expansion over the dust-source areas in Iraq and Syria. Atmospheric and Climate Sciences, 3, 321–336.
Journal of Arid Biome
Volume 12, Issue 1
April 2022
Pages 141-158

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