year 13, Issue 4 (Winter 2024 2023)                   E.E.R. 2023, 13(4): 109-129 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Jabalbarezi B, Zehtabian G, Khosravi H, Barkhori S. Evaluation of Temporal-Spatial Changes of Climatic Elements Affecting the Occurrence of Dust Phenomenon in Arid and Semi-arid Regions (Case Study: Jazmurian Wetland). E.E.R. 2023; 13 (4) :109-129
URL: http://magazine.hormozgan.ac.ir/article-1-806-en.html
Department of Reclamation of Arid and Mountains Regions, University of Tehran, Tehran, Karaj , hakhosravi@ut.ac.ir
Abstract:   (755 Views)
1- Introduction
Soil and air are two essential elements in the life of creatures on the earth. Their interaction in certain conditions can cause many risks; among these dangers, dust storms can be mentioned. Under the conditions of dust storms, a large amount of dust is emitted in the air and the horizontal visibility is reduced to less than 1000 meters. Therefore, due to the important role of the dust phenomenon, it is highly necessary to understand the spatial-temporal changes and to analyze their long-term variations. Jazmurian region, located in the southeast of Iran, between the two provinces of Kerman and Sistan and Baluchistan, has become completely dry and turned into a desert due to drought and construction of numerous dams, and has turned this region into one of the key areas of dust production in the country. Therefore, the purpose of this study is to investigate the temporal-spatial changes of dust storms in relation to climatic parameters in Jazmurian wetland, which is of particular importance in order to properly manage this area to face the problems caused by dust storms.
2- Methodology
In order to carry out the present research, the meteorological data related to the synoptic stations located in the Jazmurian wetland area for a period of 20 years (2000-2020) were received from the Iranian Meteorological Organization. Climatic data used in this research include temperature, precipitation, relative humidity, wind speed and direction, horizontal visibility, and remote sensing data including Aerosol Optical Depth (AOD) and Normalized Difference Vegetation Index (NDVI). The research method uses a combination of statistical analysis, observation and remote sensing. In order to check the AOD and NDVI, the monthly data of MODIS sensor was used. In this study, 12 synoptic stations that had the longest and most complete statistical periods were used in order to identify the temporal-spatial changes of dust occurrence in Jazmurian wetlat. The Mann-Kendall test was used to examine the trend of time changes. The slope of the Sen estimator was used to check and confirm the accuracy of the trend changes. In order to better understand the spatial distribution pattern of dust events in the Jazmurian wetland basin, the inverse distance interpolation method (IDW) was used. Also, Pearson's spatial correlation analysis was used to investigate the mutual effects between the indicators.
3- Results
The 20-year average review of the indicators showed that the maximum value of aerosol optical depth in the studied area was 0.3, which is seen in the central part of the wetland. The vegetation index also showed that the maximum value of this index was 0.2, which covers most of the northern, northwestern and western parts. Examining the average rainfall trend showed that the maximum and minimum rainfall in this period are about 219 and 85 mm, respectively. Meanwhile, the 20-year average temperature survey showed that the maximum and minimum temperatures were 28.7 and 17.2 degrees Celsius, respectively. The fact that the maximum rainfall is in the northern and western part is in harmony with the minimum temperatures in these areas. The examination of the average wind speed showed that the maximum speed was 3.6 m/s, which was mostly in the central, west and northwest, south and southwest parts. The results of the wind direction index showed that the lowest wind direction is in the northern parts of the region and the highest wind direction is in other parts of the Jazmurian wetland basin. The maximum humidity in the studied area is 43.73%, which is mostly seen in the north, northwest, west, south, and southwest parts.  Examination of the horizontal visibility index showed that the maximum amount of horizontal visibility was in the northeastern and northwestern parts of the region. Also, the process of changes in the Mann-Kendall test showed that the annual averages of the indicators of wind direction, wind speed and horizontal visibility have been increasing with a positive slope, and the trend of changes in the relative humidity index has a negative slope and indicates a decrease in the period of 20 years. The results of the correlation analysis (at a significance level of 5%) showed that the highest correlation of the optical depth index was with the wind direction parameter and the lowest correlation was with the relative humidity index.
4- Discussion & Conclusions
The growing trend of the emission of dust particles caused by the phenomenon of wind erosion in recent decades has caused major concerns at different regional, national and global levels. Therefore, it is necessary to understand the temporal-spatial changes of the dust caused by these events in order to reduce their adverse consequences in different regions. Accordingly, in this research, with the help of this knowledge, information related to the optical depth of particles in the air (AOD) and the vegetation cover index (NDVI) were investigated using the MODIS sensor satellite data. Using the meteorological data received from the website of the National Meteorological Organization, the climatic data of rainfall, temperature, relative humidity, horizontal visibility, wind direction and wind speed were evaluated in the period of 2000-2020 and finally the correlation between the AOD index and other climate parameters was evaluated. The results of the optical depth investigation showed that the maximum optical depth is located in the central parts of Jazmurian wetland. The trend of changes in rainfall and temperature indicators also showed that the trend of these two parameters was increasing; this increase in temperature is more noticeable. Correlation investigation between optical depth and other parameters showed that the highest correlation of optical depth index was with the wind direction parameter and the lowest correlation was with the relative humidity index. In general, we can conclude that the optical depth of airborne particles is highly dependent on environmental factors, which is more evident in arid and semi-arid areas, especially in Iran and the Jazmurian wetland area. In recent years, the area of the wetland has acted as a source of dust. Therefore, by using the remote sensing data obtained from the MODIS sensor and the climate data, it is possible to examine and analyze the trend of dust changes in the units of time and space.

 
Full-Text [PDF 580 kb]   (134 Downloads)    

Received: 2023/06/22 | Published: 2023/12/31

References
1. Ahmadaali, K.; Eskandari Damaneh, H.; Ababaei, B.; & H. Eskandari Damaneh, 2021. Impacts of droughts on rainfall use efficiency in different climatic zones and land uses in Iran, Journal of Arabian Geosciences, 14, 1-15. [DOI:10.1007/s12517-020-06389-1]
2. Albarakat, R., & V. Lakshmi., (2019). Monitoring Dust Storms in Iraq Using Satellite Data. Sensors. 19(17), 3687. [DOI:10.3390/s19173687]
3. Arjamand, M.; Rashki, A.; & H. Sargazi, 2018. Temporal and spatial monitoring of dust phenomenon using satellite data in southeast Iran, with emphasis on Jazmurian region, Scientific-Research Quarterly of Geographic Information "Sephehr", 27(106), 153-168. (in Persian).
4. Bertrand, T.; Kahre, M.; Urata, R.; Mattaanen, A.; Montmessin, F.; Wilson, J.; & M. Wolff, 2022. Impact of the coagulation of dust particles on Mars during the 2018 global dust storm, Icarus, 115239. [DOI:10.1016/j.icarus.2022.115239]
5. Chubin, B.; Sajidi Hosseini, F.; Rahmati, O.; Mehdizadeh Yushanloui, M.; & M. Jalali, 2022. Examining temporal and spatial changes in the number of days of dust occurrence in West Azarbaijan province, determining the influencing factors and identifying the origin, Journal of Wilderness Management, 10 (2), 71-86. (in Persian).
6. Dargahian, F., & S. Lotfi Nasab Asl., (2020). Identifying the trend of changes in the climatic areas of the watersheds leading to the dust centers of Khuzestan province (Karun Bozor, Karkheh and Zohra-Jarhari). Iran Pasture and Desert Research. 27(2), 320-300. (in Persian).
7. Ebrahimi-Khusfi, Z.; Nafarzadegan, A.; & F. Dargahian, 2021. Predicting the number of dusty days around the desert wetlands in southeastern Iran using feature selection and machine learning techniques, Ecological Indicators, 125, 107499. [DOI:10.1016/j.ecolind.2021.107499]
8. ‎8. Eskandari Damaneh, H.; Eskandari Damaneh, H.; Khosravi, H.; & H. Gholami, 2019. Drought analysis and monitoring using NDVI vegetation cover index (Case study: West Basin of Jazmurian wetland), Marta Research Journal, 13 (3), 475-461. (in Persian).
9. Eskandari Damaneh, H.; Jafari, M.; Eskandari Damaneh, H.; Behnia, M.; Khoorani, A.; & JP. Tiefenbacher, 2021. Testing possible scenariobased responses of vegetation under expected climatic changes in Khuzestan Province, Journal of Air, Soil and Water Research, 14, 13117862212110332. [DOI:10.1177/11786221211013332]
10. Eskandari Dameneh, H.; Gholami, H.; & M. Telfer, 2021. Desertification of Iran in the early twenty-first century: assessment using climate and vegetation indices, Journal of Scienfific Report, 11, 20548. [DOI:10.1038/s41598-021-99636-8]
11. Gherboudj, I.; Beegum, S.; & H. Ghedira, 2017. Identifying natural dust source regions over the Middle-East and North-Africa: Estimation of dust emission potential, Earth-science reviews, 165, 342-355. [DOI:10.1016/j.earscirev.2016.12.010]
12. Khusfi, Z.; Khosroshahi, M.; Roustaei, F.; & M. Mirakbari, 2020. Spatial and seasonal variations of sand-dust events and their relation to atmospheric conditions and vegetation cover in semi-arid regions of central Iran, Geoderma, 365, 114225. [DOI:10.1016/j.geoderma.2020.114225]
13. Mallick, J.; Talukdar, S.; Alsubih, M.; Salam, R.; Ahmed, M.; Kahla, N.; & M. Shamimuzzaman, 2021. Analysing the trend of rainfall in Asir region of Saudi Arabia using the family of Mann-Kendall tests, innovative trend analysis, and detrended fluctuation analysis, Theoretical and Applied Climatology, 143(1), 823-841. [DOI:10.1007/s00704-020-03448-1]
14. Mann, H., 1994. Nonparametric tests against trend, Econometrica: Journal of the econometric society, 245-259. [DOI:10.2307/1907187]
15. Marchese, F.; Sannazzaro, F.; Falconieri, A.; Filizzola, C.; Pergola, N.; & V. Tramutoli, 2017. An Enhanced Satellite-Based Algorithm for Detecting and Tracking Dust Outbreaks by Means of SEVIRI Data, Remote Sensing, 9(6), 537. [DOI:10.3390/rs9060537]
16. Mehri Cherodeh, M., & S. Mohammadi Nematabad., (2020). Investigating the factors affecting the dust phenomenon in Iran and providing solutions and suggestions. The fifth international conference on modern accounting, management and human sciences research in the third millennium. (in Persian).
17. Middleton, N., 2019. Variability and trends in dust storm frequency on decadal timescales: climatic drivers and human impacts, Geosciences, 9 (6), 261. [DOI:10.3390/geosciences9060261]
18. Mir, A.; Maleki, S.; & N. Middleton, 2021. An investigation into climatic and terrestrial drivers of dust storms in the Sistan region of Iran in the early twenty-first century, Science of The Total Environment, 757, 143952. [DOI:10.1016/j.scitotenv.2020.143952]
19. Mirakbari, M., & Z. Ebrahimi Khousfi., (2020). Investigating the trend of temporal and spatial changes of atmospheric suspended particles using the optical depth index of aerosols in southeast Iran. Journal of Remote Sensing and Geographical Information System in Natural Resources. 11(3), 105-87. (in Persian).
20. Mohammadpour, K.; Saligheh, M.; Darvishi Balorani, A.; & T. Rezaei, 2020. Analysis and comparison of satelli te and simulated AOD productions in the analysis of dust in western Iran (2000-2018), Journal of Spatial Analysis of Environmental Hazards, 7(1), 15-32. (in Persian). [DOI:10.29252/jsaeh.7.1.3]
21. O'Loingsigh, T.; McTainsh, E.; Tews, C.; Strong, J.; Leys, Shinkfield, P.; & N. Tapper, 2014. The Dust Storm Index (DSI): a method for monitoring broadscale wind erosion using meteorological records, Aeolian Research, 12, 29-40. [DOI:10.1016/j.aeolia.2013.10.004]
22. Qavidel Rahimi, Y.; Farajzadeh, M.; & I. Leshanizand, 2018. Analysis of temporal changes of Khorram Abad dust storms, Applied Research in Geographical Sciences, 18(21), 102-87. (in Persian). [DOI:10.29252/jgs.18.51.87]
23. Qin, W.; Liu, Y.; Wang, L.; Lin, A.; Xia, X.; & H. Che, 2018. Characteristic and driving factors of aerosol optical depth over mainland china during 1980-2017, Journal of Remote Sensing, 10, 1064. [DOI:10.3390/rs10071064]
24. Rashki, A.; Middleton, N.; & A. Goudie, 2021. Dust storms in Iran-Distribution, causes, frequencies and impacts, Aeolian Research, 48, 100655. [DOI:10.1016/j.aeolia.2020.100655]
25. Saidifar, Z.; Khosrowshahi, M.; Gohardoost, A.; Ebrahimi Khousfi, Z.; Lotfi Nasab Asl, S.; & F. Dargahian, 2020. Investigating the origin and spatial spread of high dust concentrations and its synoptic analysis in the Gakhkhoni area, Journal of Remote Sensing and Geographical Information System in Natural Resources, 11 (4), 47-64. (in Persian).
26. Savari, M.; Eskandari Damaneh, H.; & H. Eskandari Damaneh, 2021. Factors influencing farmers' management behaviors toward coping with drought: evidence from Iran, Journal of Environmental Planning and Management, 64(11), 2021-2046. [DOI:10.1080/09640568.2020.1855128]
27. Sen, P. K., 1986. Estimates of the regression coefficient based on Kendall's tau, Journal of the American Statistical Association, 63(324), 1379-89. [DOI:10.1080/01621459.1968.10480934]
28. Sharafi, S., & N. Mir Karim., (2020). Investigating trend changes of annual mean temperature and precipitation in Iran. Journal of Arabian Geosciences. 13, 759-765. [DOI:10.1007/s12517-020-05695-y]
29. Soleimani Sardo, F.; Mutkan, A. A.; & S. Karami, 2022. Forecasting the movement path of dust particles using HYSPLIT and WRF-Chem models in Jazmurian basin, Climatology Research Journal, 13(51), 1-13. (in Persian). [DOI:10.1038/s41598-023-34318-1]
30. Song, H.; Zhang, K.; Piao, Sh.; & Sh. Wan, 2016. Spatial and temporal variations of spring dust emissions in northern China over the last 30 years, Atmospheric Environment, 126, 117-127. [DOI:10.1016/j.atmosenv.2015.11.052]
31. Temski, E.; Khurani, A.; Darvishi Belorani, A.; & A, Nohagar, 2016. Monitoring and forecasting the occurrence of dust storms using remote sensing data, spatial information system and ground data based on the investigation of changes in vegetation cover and climatic elements (case study: south and southeast of Iran), Iranian Remote Sensing and GIS Journal, 7(4), 27-44. ‎(in Persian).
32. Wang, D.; Zhang, F.; Yang, S.; Xia, N.; & M. Ariken, 2020. Exploring the spatial-temporal characteristics of the aerosol optical depth (AOD) in Central Asia based on the moderate resolution imaging spectroradiometer (MODIS), Journal of Environmental Monitoring and Assessment, 192, 383. [DOI:10.1007/s10661-020-08299-x]
33. Yarmoradi, Z.; Nasiri, B.; Mohammadi, G.; & M. Karampour, 2020. Long-term characteristics of the observed dusty days and its relationship with climatic parameters in East Iran, Arabian Journal of Geosciences, 13(6), 1-11. [DOI:10.1007/s12517-020-5198-y]
34. Yousefi, R.; Wang, F.; Ge, Q.; Lelieveld, J.; & A. Shaheen, 2021. Aerosol Trends during the Dusty Season over Iran, Journal of Remote Sensing, 13, 1045-1065. [DOI:10.3390/rs13061045]
35. Zheng, Y.; Davis, S. J.; Persad, G. G.; & K. Caldeira, 2020. Climate effects of aerosols reduce economic inequality, Journal of Nature Climate Change, 10, 220-224. [DOI:10.1038/s41558-020-0699-y]

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Environmental Erosion Research Journal

Designed & Developed by : Yektaweb