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اثرگزاری سنجه های اقلیمی بر روند تغییر پوشش گیاهی با روی‌کرد تخریب سرزمین در بخش‌هایی از آبخیز خلیج فارس و دریای عمان | ||
| پژوهش های آبخیزداری | ||
| مقاله 6، دوره 34، شماره 3 - شماره پیاپی 132، مهر 1400، صفحه 74-94 اصل مقاله (1.91 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmej.2021.352362.1368 | ||
| نویسندگان | ||
| سید علیرضا حسینی1؛ حمید غلامی* 2؛ یحیی اسماعیل پور3؛ آرتمی سردا4 | ||
| 1دانشجوی دکترای بیابان زدایی، دانشکده کشاورزی و منابع طبیعی، دانشگاه هرمزگان | ||
| 2دانشیار گروه مهندسی منابع طبیعی، دانشکده کشاورزی و منابع طبیعی، دانشگاه هرمزگان | ||
| 3استادیار گروه مهندسی منابع طبیعی، دانشکده کشاورزی و منابع طبیعی، دانشگاه هرمزگان | ||
| 4استاد دانشکده جغرافیا، دانشگاه والنسیا، اسپانیا | ||
| چکیده | ||
| تخریب سرزمین پدیده یی چندوجهی تأثیرگیرنده از متغیرهای گوناگون از جمله اقلیم، تغییر کاربری و فعالیتهای اجتماعی- انسانی است. برای بررسی اثر سنجه های اقلیمی بر وضعیت تخریب سرزمین در پنج آبخیز درجه‌ی دو (بلوچستان جنوبی، سدیج بندرعباس، کل- مهران، حله و مند) در آبخیز خلیج فارس و دریای عمان، داده های مشاهده یی 32 ایستگاه هم‌دید در آبخیز برای بازه ی زمانی 31 ساله (1367– 1398) به‌کار برده شد. برای تهیه ی نقشه ی سنجه های اقلیمی الگوریتم IDW، به‌کار برده شد. نتیجه‌های آشکارسازی نشان داد که تغییر طبقه ی دمایی 27/5 – 25 روند افزایشی (9/03 %) دارد و طبقه ی بارش کمتر از 150 میلی متر در منطقه نیز با افزایش 17/3% روبه‌رو است. روند سنجه ی تبخیر به گونه یی بود که طبقه ی 2750-2500 و 3250-300 میلی متر با تغییر (5/4- ،8/3 %) به ترتیب بیشترین اثر کاهشی و افزایشی را نشان داد. طبقه‌های سرعت باد کمتر از 2 و 4-3 متر بر ثانیه با تغییر (5/7، 7/5-%) بیشترین روند افزایش و کاهشی را نشان داد. بر پایه‌ی یافته های تحلیل وایازی، رابطه ی معنی داری در تراز 0/05% بین متغیر اقلیمی (بارش، دما، تبخیر و سرعت باد) و شاخص پوشش گیاهی و شوری بود، و سنجه ی بارش بیشترین اثرگزاری را نشان داد. از آن‌جا که این چهار متغیر اقلیمی به ترتیب (40/5، 47/6%) از تغییر متغیر وابسته‌ی شاخص پوشش گیاهی و شوری را تبیین می کند، می توان نتیجه گرفت که بخشی از تغییر پوشش گیاهی و شوری از شرایط اقلیمی حاکم بر منطقه پی‌روی میکند. از این رو پوشش گیاهی ضعیف منطقه و شوری در بازه ی زمانی بررسی‌شده دائما در نوسان است، و به دنبال آن فرآیند تخریب نیز روند افزایشی و کاهشی دارد. بنابراین با آگاهی از نحوه ی تأثیر سنجه های اقلیمی بر نوسان شاخص های پوشش گیاهی و شوری در دوره ی طولانی 31 ساله می توان پیش بینی لازم را برای مدیریت‌کردن بهینه ی عرصه های طبیعی، به‌خصوص در هنگام خشکسالی اعمال نمود، و مرحله‌های توسعه‌ی تخریب سرزمین را در آبخیز ساحلی خلیج فارس و دریای عمان مهار کرد. | ||
| کلیدواژه‌ها | ||
| آبخیز؛ بارش؛ تخریب سرزمین؛ دما؛ شاخص پوشش گیاهی؛ شاخص شوری | ||
| عنوان مقاله [English] | ||
| Effect of the Climatic Parameters on the Trend of Vegetative Land Cover Changes with Land Degradation Approach in the Persian Gulf and Oman Sea Watershed | ||
| نویسندگان [English] | ||
| Seyed Ali Reza Hosseini1؛ Hamid Gholami2؛ Yahya Esmaeilpoor3؛ Artemi Cerda4 | ||
| 1Ph.D. Candidate of Desert Management, Department of Natural Resources Engineering, Faculty of Agriculture & Natural Resources, University of Hormozgan | ||
| 2Associate Professor, Department of Natural Resources Engineering, Faculty of Agriculture & Natural Resources, University of Hormozgan | ||
| 3Assistant Professor, Department of Natural Resources Engineering, Faculty of Agriculture & Natural Resources, University of Hormozgan | ||
| 4Professor, Department of Geography, University of Valencia, Spain | ||
| چکیده [English] | ||
| Land degradation is a multifaceted phenomenon, which is caused by various variables, including climate, land use changes and socio-human activities. In order to investigate the effects of climatic parameters on land degradation in five second degree watersheds (South Baluchistan, Bandar Abbas - Sedij, Kal - Mehran, Hillah and Mond) located in the entire Persian Gulf and Oman Sea Watershed, observational data E32 of synoptic stations were used in the mentioned catchment areas for of 31- year period (1988-2019). The IDW algorithm was used to map the climatic parameters. The results of the change detection showed that the trend of temperature class changes of 25– 27.5 follows an increasing rate of 19.03%, and the precipitation class is less than 150 mm in the region. The region is also facing an increasing trend of 17.3%. The trend of the evaporation parameter is such that the 2500-2750 and 300-3250 mm classes with the changes of -5.4, 8.3 percent, respectively, have the most decreasing and increasing effects. Moreover, the wind speed classes of less than 2 and 3-4 meters per second with changes of 5.7 and -7.5 percent show the highest increase and decrease respectively, based on the findings of the regression model, there is a significant relationship at the 0.05% level between the climatic variables (precipitation, temperature, evaporation and wind speed) on one hands and the vegetation index and salinity and the precipitation parameter on the others show the greatest effect. Considering that the four mentioned climatic variables explain 47.6% and 40.5% of the changes in the dependent variable of vegetation index and salinity, respectively, it can be concluded that part of the changes in vegetation and salinity are due to the conditions. As the climate prevails in the region, the poor vegetation and salinity were constantly fluctuating during the study period; consequently, the process of degradation followed an increasing and decreasing rate. Therefore, being aware of the effects of climatic parameters on the fluctuation of vegetation and salinity indices in a long period of 31 years, it is possible to make the necessary predictions for the optimal management of natural resources, especially during droughts. This enables the concerned authorities to control the development stages of land degradation in the coastal catchment areas of the Persian Gulf and the Sea of Oman. | ||
| کلیدواژه‌ها [English] | ||
| Land degradation, precipitation, SAVI, SI1, temperature, watershed | ||
| مراجع | ||
|
Ahmadalli Kh, Nikmehr S, Liaghat A. 2009. Evaluation of different spatial estimatingon estimating soil salinity, pH and CaCO3 percentage (Case study of Boukan region). Journal of Water and Soil. 23(2): 46 –54. Ahmadi H, Abbasabadi MR, Onaq M, Ekhtesasi MR. 2001. Quantitative assessment of desertification in Aq Qala and Gomishan plain: Proposing a regional model. Sustainable development of desert communities: A Regional Symposium, Iran Natural Resources, 1(54):207–220. (In Persian). Alimoradi S, KHorani A, Esmaeilpoor Y. 2017. Dynamics of vegetation in Karun Watershed within Khuzestan Province in relation with temperature factors and precipitation. Researches in Geographical Sciences. 17(44): 155 – 177. (In Persian). Azimi F, Farhadvand GhA, Zohourian M. 2015. The examination of evaluating modei of drought and wet year at Mahshahr and Andimeshk Stations. Journal of Natural Geography. 8(29): 107–116. (In Persian). Behzadi karimi H, Mazidi A. 2019. Modeling the relationship between reference evapotranspiration annual and seasonal with climatic factors in catchment central plateau Iran. Journal of Climate Research. 10(37): 69 – 86. (In Persian). Camberlin P, Martiny N, Philippon N, Richard Y. 2007. Determinants of the interannual relationships between remote sensed photosynthetic activity and rainfall in tropical Africa. Remote Sensing of Environment. 106(2):199–216. Eskandari Damaneh H, Gholami H, Mahdavi R, Khoorani A, J Li. 2019. Evaluation of land degradation trend using satellite imagery and climatic data (Case study: Fars province). Desert Ecosystem Engineering Journal. 8(24): 49 – 64. (In Persian). Eskandari Damaneh H, Gholami H, Khosravi H, Mahdavi Najafabadi R, Khoorani A. 2020. Modeling spatial and temporal changes in Land-Uses and land cover of the Urmia Lake Basin applying cellular automata and markov chain. Journal of Geography and Sustainability of Environment. 35(220): 57–72. (In Persian). Ding JL, Wu MC, Tiyip T. 2011. Study on soil salinization information in arid region using remote sensing technique. Agricultural Sciences in China. 10(3): 404–411. Guan D, Li H, Inohae T, Su W, Nagaie T, Hokao K. 2011. Modeling urban land use change by the integration of cellular automaton and markov model. Ecological Modelling. 222(20–22) :3761–3772. Hadian F, Jafari R, Bashari H, Ramezani, N. 2013. Investigating the effects of Hanna dam construction on long-term land use/cover changes. Iranian Journal of Applied Ecology. 2(4):101–114. (In Persian). Hou G, Zhang H, Wang Y. 2011. Vegetation dynamics and its relationship with climatic factors in the Changbai Mountain Natural Reserve. Journal of Mountain Science, 8(6): 865–875. Islamic Republic of Iran Meteorology Office (IRIMO). 2018. Available at www. IRIMO.ir. Ji L, Peters AJ. 2004. A spatial regression procedure for evaluating the relationship between AVHRR-NDVI and climate in the northern Great Plains. International Journal of Remote Sensing. 25(2): 297–311. Karampoor M, Yousefi A, Koohpaye N. 2015. Relationship between climatic elements with vegetation cover of meadows in the Hormozgan province (A case study: Gymnocarpus decander. Journal of Natural Ecosystem of Iran. 6 (3):41– 48. (In Persian). Kharazmi R, Abdollahi A, Rahdari MR, Karkon varnosfaderani M. 2016. Monitoring land use change and its impacts on land degradation and desertification trend using landsat satellite images (Case study: East of Iran, Hamoon Wetland). Arid Regions Geographic Studies. 7 (25): 64 -75. (In Persian). Khosh akhlagh F, Ranjbar F, Toolaei S, Moghbel M, Masoompoor Samakoosh J.2009. Investigation of drought in the water year 2007-2008 and its effects on water and agricultural resources. Journal of Iranian Geographical Society. 8(24) :119–136. (In Persian). Khoshbayan A, Araghinejad S, Aghashariatmadari Z. 2019. The effect of climatic parameters of temperature and precipitation on water resources status of persian Gulf and Oman Sea Catchment Areas Using CORDEX Project. Iranian Journal of Soil and Water Research. 3(50): 615 – 624. (In Persian). Li J, Lewis J, Rowland J, Tappan G, Tieszen LL. 2004. Evaluation of land performance in Senegal using multi-temporal NDVI and rainfall series. Journal of Arid Environments. 59(3): 463–480. Li W, Du J, Li S, Zhou X, Duan Z, Li R, Wu S, Wang S, Li M. 2019. The variation of vegetation productivity and its relationship to temperature and precipitation based on the GLASS-LAI of different African ecosystems from 1982 to 2013. International Journal of Biometeorology. 63(7):847–860. Liu Y, Li L, Chen X, Zhang R, Yang J. 2018. Temporal-spatial variations and influencing factors of vegetation cover in Xinjiang from 1982 to 2013 based on GIMMS-NDVI3g. Global and Planetary Change. 169: 145–155. Marzaioli R, Ascoli RD, De Pascale RA, Rutigliano FA. 2010. Soil quality in a Mediterranean area of Southern Italy as related to different land use types. Applied Soil Ecology. 44(3): 205–212. Masoudi M, Patwardhan AM, Gore SD. 2006. A new methodology for producing of risk maps of soil salinity, (Case study: Payab Basin, Iran). Journal of Applied Sciences and Environmental Management. 10(3): 9–13. (In Persian). Masoudi R, Zehtabian GR, Ahmadi H, Malkian A. 2015. Evaluation of the quantitative and qualitative changes of groundwater in Kashan Plain. Desert Management. 3(5): 67–80. (In Persian). Masoudi M, Jokar P, Pradhan B. 2018. A new approach for land degradation and desertification assessment using geospatial techniques. Natural Hazards and Earth System Sciences. 18:1133–1140. (In Persian).
Mohammadi A. 2009. Basics of geographical sciences and information systems, Samt Publications. 290 p. (In Persian). Momeni A. 2010. Geographical distribution and levels of soil salinity, Journal of Soil Research (Water and Soil), 24(3): 203–215. (In Persian). Munkhtsetseg ER, Kimura J, Wang M, Shinoda. 2007. Pasture yield response to precipitation and high temperature in Mongolia. Journal of Arid Environment. 70(2007):94–110. Nakhaee NFS, Akbari D, Telfer MW, Rezaei M. 2018. Comparing different methods of land use classification using the thermal band (Case study: Southern Khorasan Province), Journal of Desert Management. 6(11): 65–81. (In Persian). Nasrian A, Akbari M, Faridhosseini A, Neamatollahi E, Davari S. 2019. Quantitative assessment of desertification intensity indices in the agricultural lands of Dargaz plain, Khorasan Razavi Province. Journal of Desert Management. 7(13): 149 – 170. (In Persian). Nemani RR, Keeling CD, Hashimoto H, Jolly WM, Piper SC, Tucker CJ, Myneni RB, Running SW. 2003. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science. 300(5625):1560–1563. Negaresh H, Rakhshani Z, Firoozi F, Alinia H. 2016. Desertification assessment using the analytic hierarchy process and GIS in southeast Iran. Geografiska Annaler: Series A, Physical Geography 98(1):1–14. (In Persian). Nell JP. 2013. Quantification of the salt content of soils under different climatic conditions on a national scale in south Africa. In Developments in Soil Salinity Assessment and Reclamation. Springer, Dordrecht. 2013(955936): 61–73. Park HS, Sohn BJ. 2010. Recent trends in changes of vegetation over East Asia coupled with temperature and rainfall variations. Journal of Geophysical Research: Atmospheres .115(14): Salimi S, Balyani S, Hosseini SA, Momenpour SE. 2018. The prediction ofspatial and temporal distribution of precipitation regime in Iran: The case of Fars Province. Modeling Earth Systems and Environment. 4 (2): 565–77. (In Persian). Sefianian AR, KHodakarami L. 2011. Land use mapping using fuzzy classification: Case study in three catchment areas in Hamedan Province, journal of Town and Country Planning. 4(3): 95 –114. (In Persian). Shen X, Liu B, Zhou D. 2016. Using GIMMS NDVI time series to estimate the impacts of grassland vegetation cover on surface air temperatures in the temperate grassland region of China. Remote Sensing Letters, 7(3):229–238. Shirazi M, Zehtabian GH, Matinfar HR. 2010. Survey of capability of remote sensing indices for enhancement of land cover in arid areas (Case study: Najmabad). Iranian Journal of Range and Desert Research. 17(2): 256–275. (In Persian). Symeonakis E, Karathanasis N, Koukoulas S, Panagopoulos. G. 2016. Monitoring sensitivity to land degradation and desertification with the environmentally sensitive area index: The case of Lesvos Island, Land Degradation and Development. 27(6): 1562–1573. Taheri sarteshnizi F, Feghi J, Danekar A, Moeinoddini M. 2019. Modeling the pattern of green space and effect on land surface temperature (Case study of Tehran). Journal of Environmental Science and Technology. 21(9):179–191. (In Persian). United States Geological Survey (USGS). 2019. Landsat satellites, “Landsat 8,” [Online]. Available at https://www.usgs.gov.https://earthexplorer.usgs.gov/ (accessed on 1 May, 2019). Vesali A, Zehtabian GR, Azarnivand H. 2015. Determining the most effective indicators of water and irrigation on severity of desertification (Case study: Kashan Plains and AranoBidgol). Desert Management. 3(6): 38–25. (In Persian). Wijesundara CJ, Dayawansa NDK. 2011. Construction of large dams and their impact on cultural landscape: A study in Victoria Reservoir and the Surrounding Area. Tropical Agricultural Research. 22(1):211–219. Xia JY, Chen JQ, Piao SL, Ciais P, Luo YQ, Wan SQ. 2014. Terrestrial carbon cycle affected by non-uniform climate warming. Nature Geoscience. 7(3): 173–180. Xu Y, Yang J, Chen Y. 2016. NDVI-based vegetation responses to climate change in an arid area of China. Theoretical and Applied Climatology, 126(1–2):213–22. | ||
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