سهم بندی منابع رسوبات تپه‌های ماسه‌ای با استفاده از دو مدل ترکیبی مورد استفاده در روش انگشت-نگاری رسوب (مطالعه موردی: منطقه ی جازموریان، جنوب استان کرمان)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشگاه هرمزگان

2 سازمان انرژی اتمی

3 دانشگاه اکستر

4 دانشگاه گنبد کاووس

چکیده

روش انگشت­نگاری رسوب همراه با مدل­های ترکیبی یک رویکرد رایج در کمی نمودن سهم منابع رسوبات به­ویژه رسوبات آبی می­باشد ولی در زمینه رسوبات بادی تحقیقات اندکی انجام شده است. در این تحقیق، دو مدل ترکیبی کالینز و هوگس مورد استفاده در انگشت­نگاری رسوب به منظور کمی نمودن سهم منابع رسوبات تپه­های ماسه­ای در منطقه جازموریان، جنوب کرمان بکار برده شد. بدین منظور پس از تعیین جهات باد و تهیه نقشه­ زمین­شناسی، اقدام به نمونه­برداری از منابع بالقوه تپه­های ماسه­ای شامل پهنه­های ماسه­ای (Qs)، رسوبات آبرفتی ریزدانه و بستر خشکرودها (Qal)، رسوبات مخروط افکنه­ها و پادگانه­ها (Qt) و ترکیب رس و نمک (Qc)؛ و از مناطق رسوب یا تپه­های ماسه­ای (Qsd) گردید. به طوری که 58 نمونه سطحی از منابع بالقوه تپه­های ماسه­ای شامل 7 نمونه از Qs، 25 نمونه از Qal، 5 نمونه از Qt و 21 نمونه از Qc؛ و 14 نمونه از مناطق رسوب (Qsd) برداشت گردید و پس از آماده­سازی نمونه­ها، غلظت ده عنصر (Ni, Cu, Co, Cr, Ga, Mn, P, Ba, Sr و Li) اندازه­گیری شد. به منظور تفکیک منابع تپه­های ماسه­ای، از یک فرآیند آماری دو مرحله­ای شامل تست­های کروسکال والیس و آنالیز تابع تشخیص گام به گام استفاده گردید که چهار ردیاب شامل Cr, Li, Ni و Co به عنوان ردیاب­های بهینه انتخاب شدند و به عنوان پارامترهای ورودی به مدل­های ترکیبی مورد استفاده قرار گرفتند. سهم­های ارائه شده برای منابع تپه­های ماسه­ای توسط هر دو مدل مشابه هم بدست آمد و منابع Qs و Qal به عنوان منابع غالب برای 14 نمونه تپه ماسه­ای شناخته شدند. همچنین بر طبق نتایج، مقادیر GOF محاسبه شده برای مدل کالینز (با بالاترین مقدار GOF برابر 95/99 درصد) بالاتر از مدل هوگس (با بالاترین GOF برابر 9/99 درصد) محاسبه شد که نشان­دهنده کارآیی بالای این مدل در منشایابی رسوبات تپه ماسه­ای می­باشد. به طور کلی، استفاده از روش انگشت­نگاری رسوب با مدل ترکیبی کالینز برای کمی نمودن سهم منابع تپه­های ماسه­ای فعال در سایر مناطق پیشنهاد می­گردد.

کلیدواژه‌ها


عنوان مقاله [English]

Apportionment sources of sand dune sediment using two mixing models used to sediment fingerprinting (Case study: Jazmurian region, south of Kerman province)

چکیده [English]

Introduction
The entrainment, transport, and deposition of sediments by wind, or aeolian processes, affect  all  major  components  of the  Earth  system  and  provide  important  biogeochemical  linkages between the atmosphere, hydrosphere, biosphere, and pedosphere (Field et al, 2010). Large part of Iran located in arid and semi-arid regions which wind erosion act as an important geomorphological process over an area of about 24 million ha and also, Iran’s dune fields as depositional Aeolian environments cover an area about 5.5 million ha (Gholami et al, 2017a). Aeolian deposits are widely distributed in the arid areas of Iran, forming ergs such as Yazd, Ashkzar, Kashan and Jazmurian. Jazmurian erg and its surrounding areas at the border of south of Kerman and Sistan-Baloochestan provinces, Iran experiences severe wind erosion, which causes both on-site and off-site effects.
Although there have been studies of Aeolian sand in both arid and semiarid zones, much of the focus has been on genesis of dune forms, sedimentary structures, and chronology of dune deposition. It is interesting that there has been much less work done on understanding dune sediment provenance (Muhs, 2017).
Therefore, Identifying and quantifying source contribution of Aeolian sediments is necessary to decreasing on-site and off-site effects of wind erosion in the arid and semi-arid regions of worldwide. Sediment fingerprinting was applied by many researchers to quantifying source contributions of fluvial sediments (e.g., Collins et al, 1997; Walling et al, 1999; Pulley et al, 2015; Haddadchi et al, 2013; Nosrati et al, 2014) and several studies applied this technique to quantify source contributions of Aeolian sediments (e.g., Gholami et al, 2017a,b; Liu et al, 2016). A remarkable range of properties has been employed in sediment fingerprinting studies including geochemical elements (Collins et al, 2012; Lamba et al, 2015; Liu et al, 2016a; Gholami et al, 2017b), geochemical indicators (Vale et al, 2016), isotopic reatios (Douglas et al, 1995), radionuclides (Walling et al, 1999; Olley et al, 2012), organic elements (Walling et al, 1999; Gellis et al, 2009), magnetic properties (Russell et al, 2001) and physical signatures (Kouhpeima et al, 2010).
 
Methodology
Sediment fingerprinting applied to quantifying source contributions of sand dune sediments in the Jazmurian region, south of Kerman. In order to, we collected 58 surficial samples from potential sources including  7 samples from Qs, 25 samples from Qal, 5 samples from Qt and 21 samples from Qc; and also, 14 samples collected from Qsd as sediment region. Then, 10 tracers including Ni, Cu, Co, Cr, Ga, Mn, P, Ba, Sr and Li measured at each samples. For discriminating sources of sand dune sediments applied a two-stage statistical procedure including Kruskal-Wallis and stepwise Discriminant Function Analysis. Finally, source contribution of sand dune sediments quantified using two mixing models including Collins et al, (1997) and Hughes et al, (2009). In all mixing models, the objective is to determine the source contribution for Aeolian sediment samples by minimizing the errors. Solutions to this models are obtained by finding values for proportional source contributions that minimize the calculated difference between the mean tracer concentrations in potential source and sediment samples (Smith et al., 2013). For calculating of optimum contributions, we used SOLVER tools in the Excel.
Results and Discussions
Results of two-stage statistical procedure showed that all 10 tracers are capable to discriminating sources of sand dune and results from second step showed that four tracers Cr, Ni, Co and Li were selected as optimum composite fingerprints as entrance parameters to mixing models. According to two mixing models results, Qs recognized as dominant source for seven sediment samples and also, Qal provided the most contributions for six sediment samples. GOF values ranged between 80 to 98% for both Collins and Hughes mixing models. Several researchers used a GOF for assessing results of Collins mixing model to sediment fingerprinting (e.g., Collins et al, 2010; Haddadchi et al, 2013; Collins et al, 2013; Stone et al, 2014; Lamba et al, 2015; Liu et al, 2016b).
 
Conclusion
Mixing models used in the sediment fingerprinting are effective tools for quantifying of source contribution of Aeolian sediments. Here, we applied a sediment fingerprinting technique to quantifying source contributions of sand dune sediments. Four optimum composite fingerprints generated highly acceptable GOF values for all four mixing models using the local optimization approach in the Solver. Qs and Qal recognized as major sources supplying sediments for sand dunes in the Jazmurian region. Based on GOF results, Collins mixing model was more efficient to Hughes mixing model to quantify source contributions. Finally, we suggests applying Collins mixing model to quantifying source contributions of sand dune sediments at other regions with active sand dunes.

کلیدواژه‌ها [English]

  • Mixing Models
  • Sediment Fingerprinting
  • Optimum Composite Fingerprints
  • Jazmurian regions
  • احمدی، حسن، (1387). ژئومرفولوژی کاربری. چاپ دوم و انتشارات دانشگاه تهران، تهران.
  • غلامی. حمید.، فیض­نیا. سادات.، احمدی. جواد.، احمدی, حسن.، نظری سامانی. علی اکبر.، نوحه­گر. احمد.، 1393. تعیین سهم رخساره­های ژئومورفولوژی در تولید رسوبات بادی با بهره­گیری از روش ردیابی رسوبات (بررسی موردی: تپه­های ماسه­ای اشکذر). مدیریت بیابان, شماره 4، پاییز و زمستان 1393، صفحات 42-31.
  • غلامی. حمید.، طاهری مقدم. الهام.، نجفی قیری. مهدی.، مهدوی نجف­آبادی. رسول.، 1394. تعیین سهم کاربری­های اراضی در تولید رسوب تپه­های ماسه­ای با استفاده از روش انگشت­نگاری (منطقه مورد مطالعه: ارگ نگار بردسیر، استان کرمان). پژوهش­های فرسایش محیطی، شماره 5 (2)، صفحات 54-46.
    • Brosinsky, A. Foerster, S. Segl, K. Lopez-Tarazan, J.A. Pique, G. and Bronstert, A., 2014. Spectral fingerprinting: characterizing suspended sediment sources by the use of VNIR-SWIR spectral information. Journal of Soils and Sediments. doi:10.1007/s11368-014-092-z.
    • Chen, F. Fang, N. and Shi, Z., 2016. Using biomarkers as fingerprint properties to identify sediment sources in a small catchment. Science of the Total Environment, 557-558, 123–133. doi:10.1016/j.scitotenv.2016.03.028.
    • Collins, A. L. and Walling, D. E., 2007. Sources of fine sediment recovered from the channel bed of lowland groundwater-fed catchments in the UK. Geomorphology, 88, 120-138. doi: 10.1016/j.geomorph.2006.10.018
    • Collins, A.L. Walling, D.E. and Leeks, G.J.L., 1997. Fingerprinting the origin of fluvial suspended sediment in larger river basins: combining assessment of spatial provenance and source type. Geografiska  Annaler, 79, 239–254
    • Collins, A. L. Walling, D. E. and Leeks, G. J. L., 1998. Use of composite fingerprints to determine the provenance of the contemporary suspended sediment load transported by rivers. Earth Surface Processes and Landforms, 23, 31-52. doi. 10.1002/(SICI)1096-9837(199801)23:1<31::AID-ESP816>3.0.CO;2-Z
    • Collins, A. L. Walling, D. E. Stroud, R. W. Robson, M. and Peet, L. M., 2010. Assessing damaged road verges as a suspended sediment source in the Hampshire Avon catchment, southern United Kingdom. Hydrological Processes, 24, 1106-1122. doi: 10.1002/hyp.7573
    • Collins, A.L. Zhang, Y. Walling, D.E. Grenfell, S.E. Smith, P. Grischeff, J. … Brogden, D., (2012). Quantifying fine-grained sediment sources in the River Axe Catchment, southwest England: Application of a Monte-Carlo numerical modelling framework incorporating local and genetic algorithm optimisation. Hydrological Processes, 26 (13), 1962–1983. doi:10.1002/hyp.8283.
    • Collins, A.L. Zhang, Y.S. Duethmann, D. Walling, D.E. and Black, K.S., 2013. Using a novel tracing-tracking framework to source fine-grained sediment loss to watercourses at sub-catchment scale. Hydrological Processes, 27 (6), 959–974. doi:10.1002/hyp.9652.
    • Devereux, O. H. Prestegaard, K. L. Needelman, B. A. and Gellis, A. C., 2010. Suspended-sediment sources in an urban watershed, Northeast Branch Anacostia River, Maryland. Hydrological Processes, 24, 1391–1403. doi. 10.1002/hyp.7604
    • Field, J.P. Belnap, J. Breshears, D.D. Neff, J.C. Okin, G.S. Whicker, J.J. Painter, T.H. Ravi, S.  Reheis,  M.C. and Reynolds,  R.L. 2010.  The  ecology  of  dust.  Ecol.  Soc.  Am.  8,  423-430. doi:10.1890/090050
    • Garzanti, E. Ando, S. Vezzoli, G. Lustrino, M. Boni, M. and Vermeesch, P. 2012. Petrology of the Namib sand sea: Long-distance transport and compositional variability in the wind-displaced Orange Delta. Earth Sci. Rev. 112, 173e18 9 .
    • Gellis, A. C. Hupp, C. R. Pavich, M. J. Landwehr, J. M. Banks, W. S. L. Hubbard, B. E. Langland, M. J. Ritchie, J. C. and Reuter J. M., 2009. Sources, transport, and storage of sediment in the Chesapeake Bay Watershed. U.S. Geological Survey Scientific Investigations Report 2008-5186: 95.
    • Gholami, H., Middleton, N., Nazari Samani, A. A., Wasson, R. 2017a. Determining contribution of sand dune potential sources using radionuclides, trace and major elements in central Iran. Arab J Geosci, 10:163. doi. 10.1007/s12517-017-2917-0.
    • Gholami, H., Telfer, M. W., Blake, W. H., and Fathabadi, A. 2017b. Aeolian sediment fingerprinting using a Bayesian mixing model. Earth Surf. Process. Landforms, 42: 2365–2376. doi: 10.1002/esp.4189.
    • ·         Haddadchi, A. Olley, J. and Laceby, P., 2014. Accuracy of mixing models in predicting sediment source contributions. Science of the Total Environment, 497-498, 139-152. dx.doi.org/10.1016/j.scitotenv.2014.07.105
    • Haddadchi, A. Ryder, D. Evrard, O. and Olley, J., 2013. Sediment fingerprinting in fluvial systems: review of tracers, sediment sources and mixing models. International Journal of Sediment Research, 28, 560-578. doi.org/10.1016/S1001-6279(14)60013-5
    • Hughes, A. O. Olley, J. M. Croke, J. C. and Mc Kergow, L. A., 2009. Sediment source changes over the last 250 years in a dry-tropical catchment, central Queensland, Australia. Geomorphology, 104, 262-275. doi.org/10.1016/j.geomorph.2008.09.003
    • ·         . Huisman, N. L. H. Karthikeyan, K. G. Lamba, J. Thompson, A. M. and Peaslee, G., 2013. Quantification of seasonal sediment and phosphorus transport dynamics in an agricultural watershed using radiometric fingerprinting techniques. J Soils Sediments, 13; 1724-1734. DOI 10.1007/s11368-013-0769-0
    • Laceby, J.P. and Olley, J., 2015. An examination of geochemical modelling approaches to tracing sediment sources incorporating distribution mixing and elemental correlations. Hydrological Processes, 29, 1669–1685.
    • Lal, R., 2001. Soil degradation by erosion. La. Degrad. Dev. 12, 519–539. doi:10.1002/ldr.472
    • Liu, B. Niu, Q. Qu, J. and Zu, R., 2016. Quantifying the provenance of aeolian sediments using multiple composite fingerprints. Aeolian Research, 22, 117-122. dx.doi.org/10.1016/j.aeolia.2016.08.002
    • Motha, J.A. Wallbrink, P.J. Hairsine, P.B. and Grayson, R.B., 2003. Determining the sources of suspended sediment in a forested catchment in southeastern Australia. Water Resources, 39 (3), 1056. doi:10.1029/2001wr000794.
    • Muhs, D. R., 2017. Evaluation of simple geochemical indicators of Aeolian sand provenance: Late Quaternary dune fields of North America revisited. Quaternary Science Reviews, 171, 260-296. doi.org/10.1016/j.quascirev.2017.07.007
    • Muhs, D.R. Reynolds, R. Been, J. and Skipp, G., 2003. Eolian sand transport pathways in the southwestern United States: importance of the Colorado River and local sources. Quat. Int. 104, 3e18
    • Nosrati, K. Govers, G. Ahmadi, H. Sharifi, F. Amoozegar, M. A. Merckx, R. and Vanmaercke, M., 2011. An exploratory study on the use of enzyme activities as sediment tracers: biochemical fingerprints?. International Journal of Sediment Research, 28, 136-151. doi.org/10.1016/S1001-6279(11)60082-6
    • Palazón, L. Latorre, B. Gaspar, L. Blake, W.H. Smith, H.G. and Navas, A., 2015. Combining catchment modelling and sediment fingerprinting to assess sediment dynamics in a Spanish Pyrenean river system. Science of the Total Environment, in press. doi:10.1016/j.scitotenv.2016.06.189.
    • Rashki, A. Arjmand, M. and Kaskaoutis, D.G., 2017. Assessment of dust activity and dust-plume pathways over Jazmurian Basin, southeast Iran. Aeolian Research, 24, 145-160.
    • Russell, M. A. Walling, D. E. and Hodgkinson, R. A., 2001. Suspended sediment sources in two small lowland agricultural catchments in the UK. Journal of Hydrology, 252, 1–24. doi.org/10.1016/S0022-1694(01)00388-2
    • Scheidt, S. Lancaster, N. and Ramsey, M., 2011. Eolian dynamics and sediment mixing in the Gran Desierto, Mexico, determined from thermal infrared spectroscopy and remote-sensing data. Geol. Soc. Am. Bull. 123, 1628 e 16 4 4
    • Slattery, M. Walden, J. and Burt, T. P., 2000. Fingerprinting suspended sediment sources using mineral magnetic measurements- A quantitative approach. Tracers in geomorphology, John Wiley and Sons: pp. 309–322.
    • Stone, M. Collins, A.L. Silins, U. Emelko, M.B. and Zhang, Y.S., 2014. The use of composite fingerprints to quantify sediment sources in a wildfire impacted landscape, Alberta, Canada. Science of the Total Environment, 473-474, 642–650. doi:10.1016/j.scitotenv.2013.12.052.
    • Voli, M.T. Wegmann, K.W. Bohnenstiehl, D.R. Leithold, E. Osburn, C.L. and Polyakov, V., 2013. Fingerprinting the sources of suspended sediment delivery to a large municipal drinking water reservoir: Falls Lake, Neuse River, North Carolina, USA. Journal of Soils and Sediments, 13 (10), 1692–1707. doi:10.1007/s11368-013-0758-3.
    • Walling, D.E., 2005. Tracing suspended sediment sources in catchments and river systems. Science of the Total Environment, 344 (1-3), 159–184. doi:10.1016/j.scitotenv.2005.02.011.
    • ·         Walling, D. E. Owens, P. N. and Leeks, G. J. L., 1999. Fingerprinting suspended sediment sources in the catchment of the River Ouse, Yorkshire, UK. Hydrological Processes, 13, 955-975. doi. 10.1002/(SICI)1099-1085(199905)13:7<955::AID-HYP784>3.0.CO;2-G
    • Zhang, X. C. and Liu, B. L., 2016. Using multiple composite fingerprints to quantify fine sediment source contributions: A new direction. Geoderma, 268, 108-118. dx.doi.org/10.1016/j.geoderma.2016.01.031
    • Zhou, H. Chang, W. and Zhang, L., 2016. Sediment sources in a small agricultural catchment: A composite fingerprinting approach based on the selection of potential sources. Geomorphology, 266, 11-19. dx.doi.org/10.1016/j.geomorph.2016.05.007