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تحلیل مقایسه‌ای عامل فرسایش‌پذیری خاک در حوضۀ آبخیز شازند | ||
| اکوهیدرولوژی | ||
| مقاله 13، دوره 6، شماره 1، فروردین 1398، صفحه 153-163 اصل مقاله (1.16 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ije.2018.269592.985 | ||
| نویسندگان | ||
| محبوبه کیانی هرچگانی* 1؛ سید حمیدرضا صادقی2؛ سامره فلاحتکار3 | ||
| 1پژوهشگر پسادکتری علوم و مهندسی آبخیزداری، دانشکدۀ منابع طبیعی دانشگاه تربیت مدرس | ||
| 2استاد گروه مهندسی آبخیزداری، دانشکدۀ منابع طبیعی دانشگاه تربیت مدرس | ||
| 3استادیار گروه مهندسی محیط زیست، دانشکدۀ منابع طبیعی، دانشگاه تربیت مدرس | ||
| چکیده | ||
| فرسایش خاک نوعی مشکل جدی محیطی، اجتماعی و اقتصادی است که نه تنها سبب تخریب شدید زمین و هدررفت خاک می‌شود، بلکه تهدید ثبات و سلامت جامعه و بهطور کلی توسعۀ پایدار آن را در پی دارد. فرسایش خاک با متغیرهای مختلف خاک، اندازهگیریها و محاسبات آنها مرتبط است. یکی از عوامل مهم در تعیین فرسایش خاک، فرسایش‌پذیری خاک (K) است. روشهای مختلفی برای تعیین عامل فرسایش‌پذیری خاک با استفاده از مدلهای تجربی یا اندازهگیریهای صحرایی ارائه شده است. در حال حاضر، روابط مبتنی بر ویژگیهای اولیۀ خاک مانند بافت، مادۀ آلی، ساختمان و نفوذپذیری بهصورت گستردهای استفاده شدهاند. بنابراین، در پژوهش حاضر از سه رابطۀ متداول شامل ویشمایر و اسمیت (1978)، رومکنز و همکارانش (1986) و توری و همکارانش (1997 و 2002) به‌ترتیب با علایم K1، K2 و K3 برای برآورد عامل فرسایش‌پذیری خاک در حوضۀ آبخیز شازند استفاده شد. به همین منظور، به نمونهبرداری صحرایی در 140 نقطه از حوضۀ آبخیز شازند با مساحت 1740 کیلومترمربع اقدام شد. حوضۀ آبخیز شازند خاک آهکی با مادۀ آلی کم و بافت متوسط دارد. در ادامه، آزمون تحلیل واریانس یکطرفه برای تحلیل نتایج K1، K2 و K3 تحت تأثیر طبقات مختلف شیب و ارتفاع و کاربریهای مختلف اراضی و روش کریجینگ برای تهیۀ الگوی مکانی آنها بهکار گرفته شد. نتایج به‌دست‌آمده از تحلیل واریانس یکطرفه بیان‌کنندۀ اختلاف معنادار K1، K2 و K3 تحت تأثیر طبقات شیب و ارتفاع (05/0 > P) و نبود اختلاف معنادار آنها تحت تأثیر کاربری اراضی (318/0 ≤ P) بود. همچنین، میانگین عامل فرسایش‌پذیری خاک برای سه رابطۀ یادشده به‌ترتیب برابر با 054/0، 039/0 و 035/0 t ha h ha-1 MJ-1 mm-1 محاسبه شد. | ||
| کلیدواژه‌ها | ||
| تخریب خاک؛ خاکهای آهکی؛ فرسایش‌پذیری؛ مقیاس حوضۀ آبخیز | ||
| عنوان مقاله [English] | ||
| Comparative Analysis of soil Erodibility Factor in Shazand Watershed | ||
| نویسندگان [English] | ||
| Mahboobeh Kiani Harchegani1؛ Seyed Hamidreza Sadeghi2؛ Samereh Falahatkar3 | ||
| 1Postdoctoral Fellow, Department of Watershed Management Engineering, Faculty of Natural Resources Tarbiat Modares University, Noor, Iran | ||
| 2Professor, Department of Watershed Management Engineering, Faculty of Natural Resources Tarbiat Modares University, Noor, Iran | ||
| 3Assistant Professor, Department of Environment Engineering, Faculty of Natural Resources Tarbiat Modares University, Noor, Iran | ||
| چکیده [English] | ||
| Soil erosion is a serious environmental, social and economic problem. It not only causes severe land degradation and soil loss, but also threatens the stability and health of the society and, in general, its sustainable development. Soil erosion is related to different soil characteristics, measurements and its calculations. The soil erodibility factor (K) is one of the important factors in determining soil erosion. Different methods have been developed to determine of K using empirical models or field measurements. Currently, widely used equations that estimate K, on the basis of soil basic properties, include soil texture, organic matter, structure, and permeability. Therefore, in this study, three commonly equations were used to estimate of K in Shazand watershed such as Wischmeier and Smith (1978), Romkens et al. (1986), Torri et al. (1997 and 2002) with K1, K2 and K3, respectively. In this regard, field sampling was done at 140 points of Shazand watershed with an area of 1740 km2. The Shazand watershed has limestone with low organic matter and medium texture. In the following, one-way ANOVA was used to analyze of K1, K2 and K3 results under the impact of different slope and elevation classes and different land uses, as well as Kriging's method for generation their spatial pattern. The results of one-way ANOVA showed that K1, K2 and K3 influenced by different slope and elevation classes with a significant difference (P< 0.05). But they had no significant difference (P ≤ 0.318) in different land use. Also, the average of K1, K2 and K3 was calculated to be 0.054, 0.039 and 0.035 t ha h ha-1 MJ-1 mm-1 respectively. | ||
| کلیدواژه‌ها [English] | ||
| Erodibility, Land degradation, Limestone soil, Watershed scale | ||
| مراجع | ||
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[1]. MEA (Millennium Ecosystem Assessment). Ecosystems and human well-being: desertification synthesis. Washington: World Resource Institute. 2005. [2]. Kiani Harchegani M, Sadeghi SHR, Asadi H. Changeability of concentration and particle size distribution of effective sediment in initial and mature flow generation conditions under different slops and rainfall intensities, J. Watershed Eng. Manag. 2017, 9(2): 205-2016. [3]. Kiani-Harchegani M, Sadeghi SHR, Asadi H. Comparing grain size distribution of sediment and original soil under raindrop detachment and raindrop-induced and flow transport mechanism, Hydrol. Sci. J. 2018, 63 (2), 312-323. [4]. Seager R, Ting M, Held MI, Kushnir Y, Lu J, Vecchi G, et al. Model projections of an imminent transition to a more arid climate in southwestern North America. Sci. 2007, 316: 1181–1184. [5]. Ravi S, Breshears DD, Huxman TE, D’Odoric P. Land degradation in drylands: Interactions among hydrologic-aeolian erosion and vegetation dynamics. Geomorph. 2009, 116(3-4): 236-245. [6]. Sommer S, Zucca C, Grainger A, Cherlet M, Zougmore R, Sokona Y, Hill J, Della R, Peruta Roehrig J, Wang G. Application of indicator systems for monitoring and assessment of desertification from national to global scales. Land Deg. Dev. 2011, 22(2): 184-197. [7]. Wang G, Fang Q, Wu B, Yang H, Xu Z. Relationship between soil erodibility and modeled infiltration rate in different soils. J. Hydrol. 2015, 528: 408-418.
[8]. Efthimiou N, Lykoudi E, Karavitis C. 2017, Comparative analysis of sediment yield estimations using different empirical soil erosion models. Hydrol. Sci. J. 2017, 62(16): 2674-2694.
[9]. Wischmeier WH, Smith DD. Predicting rainfall erosion losses (No. 537). USDA Agricultural Service Handbook. 1978, Washington, D.C.
[10]. Renard KG, Foster GR, Weesies GA, McCool DK, Yoder DC. Predicting soil erosion by water: A guide to conservation planning with the revised universal soil loss equation RUSLE (p. 404). U. S. Department of Agriculture, Agriculture Handbook 703, Government Printing Office, SSOP, Washington, D.C., 1997, ISBN 0-16-048938-5.
[11]. Wang G, Gertner G, Fang S, Anderson A.B. Mapping multiple variables for predicting soil loss by geostatistical methods with TM images and a slope map. Photogram. Eng. Remote Sens. 2003, 69: 889–898.
[12]. Lu DLG, Valladares GS, Batistella M. Mapping soil erosion risk in Rondonia, Brazilian Amazonia: Using RUSLE, remote sensing and GIS. Land Deg. Dev. 2004, 15: 499–512.
[13]. Ozcan AU, Erpul G, Basaran M, Erdogan HE. Use of USLE/GIS technology integrated with geostatistics to assess soil erosion risk in different land uses of Indagi Mountain Pass—Cankırı, Turkey. Environmental Geology. 2008, 53(8): 1731–1741.
[14]. Saygın SD, Basaran M, Ozcan AU, Dolarslan M, Timur OB, Yilman FE, Erpul G. Land degradation assessment by geo-spatially modeling different soil erodibility equations in a semi-arid catchment. Environ. Monitor. Asses. 2011, 180(1-4): 201-215.
[15]. Panagos P, Meusburger K, Ballabio C, Borrelli P, Alewell C. Soil erodibility in Europe: a high-resolution dataset based on LUCAS. Sci. Total Environ. 2014, 479: 189-200.
[16]. Wang G, Gertner G, Liu X, Anderson A. Uncertainty assessment of soil erodibility factor for revised universal soil loss equation. Catena, 2001, 46: 1–14.
[17]. Parysow P, Wang G, Gerther G, Anderson A. Spatial uncertainty analysis for mapping soil erodibility based on joint sequential simulation. Catena. 2003, 53: 65–78.
[18]. Bonilla CA, Johnson OI. Soil erodibility mapping and its correlation with soil properties in Central Chile. Geoderma, 2012, 189: 116-123.
[19]. Fu BJ, Zhao WW, Chen LD, Zhang QJ, Lü YH, Gulinck H, Poesen J. Assessment of soil erosion at large watershed scale using RUSLE and GIS: a case study in the Loess Plateau of China. Land Deg. Dev. 2005, 16(1): 73-85.
[20]. Pérez-Rodríguez R, Marques MJ, Bienes R. Spatial variability of the soil erodibility parameters and their relation with the soil map at subgroup level. Sci. Total Environ. 2007, 378(1-2): 166-173.
[21]. Baskan O, Dengiz O. Comparison of traditional and geostatistical methods to estimate soil erodibility factor. Arid land Res. Manag. 2008, 22(1): 29-45.
[22]. Wang B, Zheng F, Guan Y. Improved USLE-K factor prediction: A case study on water erosion areas in China. Inter. Soil. Water Conserv. Res. 2016, 4(3): 168-176.
[23]. Pereira ECB, Lopes FB, Gomes FEF, de Almeida AMM, de Magalhães ACM, de Andrade, EM. Determining the soil erodibility for an experimental basin in the semi-arid region using geoprocessing. Am. J. Plant Sci. 2017, 8(12), 3174.
[24]. Okorafor OO, Adeyemo AJ. Determination of soils erodibility factor (K) for selected sites in Imo State, Nigeria. Resour. Environ. 2018, 8(1): 6-13.
[25]. Mulengera MK, Payton RW.Estimating the use-soil erodibility factor in developing tropical countries: a case study in Tanzania. J. Engin. Tec. 2008, 22(2).
[26]. Vaezi A, Bahrami H, Sadeghi SHR, Mahdian M. A new nomograph for estimating erodibility factor (K) in some soils of the semi-arid regions in northwest of Iran, Water. Soil Sci. 2009, 13(49): 69-80. (In Persian)
[27]. Vaezi AR, Sadeghi SHR, Bahrami HA, Mahdian MH. Modeling the USLE K-factor for calcareous soils in northwestern Iran. Geomorph. 2008, 97(3-4): 414-423.
[28]. Vaezi AR, Hasanzadeh H, Cerdà A. Developing an erodibility triangle for soil textures in semi-arid regions, NW Iran. Catena. 2016, 142: (221-32-27).
[29]. Zandi J, Habibnejad Roshan M, Solimani K. Soil erosion risk assessment and its relationship with some environmental parameters (Case study: Vazroud watershed, Mazandaran), Rang. Watershed Manag. 2013, 66(3): 401-415. (In Persian)
[30]. Shabani F, Kumar L, Esmaeili A. Improvement to the prediction of the USLE K factor. Geomorph. 2014, 204: 229-234.
[31]. Ostovari Y, Ghorbani-Dashtaki S, Bahrami HA, Abbasi M, Dematte AM, Arthur E, Panagos P. Towards prediction of soil erodibility, SOM and CaCO3 using laboratory Vis-NIR spectra: A case study in a semi-arid region of Iran. Geoderma. 2018, 314: 102-112.
[32]. Kiani-Harchegani M, Sadeghi SHR, Boor S. Comparative analysis of soil variables in different land uses of the Shazand watershed, Iran, The 9th international scientific agriculture symposium "AGROSYM 2018", 2018, 4-7 October, Jahorina, Bosnia and Herzegovina.
[33]. Sadeghi SHR, Hazbavi Z, Gholamalifard M. Interactive impacts of climatic, hydrologic and anthropogenic activities on watershed health. Sci. Total Environ. 2019, 648: 880-893.
[34]. Nelson DW, Sommers LE. Total carbon, organic carbon and organic matter, in: Sparks, D.L. (Ed.), Methods of Soil Analysis. Part 3. Chemical Methods, SSSA Book Ser. 5. 3., Madison, USA, Soil Sci. Soc. Am. 1996, pp. 961-1010.
[35]. Rhoades J.D. Salinity: electrical conductivity and total dissolved solids, in: Sparks, D.L. (Ed.), Methods of Soil Analysis. Part 3. Chemical Methods, SSSA Book Ser. 5. 3., Soil Sci. Soc. Am. Madison, USA. 1996, pp. 417-436.
[36]. Blake GR, Hartge KH. Bulk Density, in A. Klute, ed., Methods of soil analysis, part I. physical and mineralogical methods: Agronomy Monograph. 1986, no. 9 (2nd ed.), pp. 363-375.
[37]. Bremner JM. Total Nitrogen, in: Sparks, D.L. (Ed.), Methods of soil analysis. part 3 chemical methods, SSSA Book Ser. 5. 3., Soil Sci. Soc. A. Madison, 1996, USA, pp. 1085-1122.
[38]. Richard HL, Donald LS. Carbonate and gypsum, in: Sparks, D.L. (Ed.), Methods of soil analysis. part 3 chemical methods, SSSA Book Ser. 5. 3., Soil Science Society of America, Madison, USA, 1996, pp. 437-474.
[39]. Agharazi H, Davudi Rad AA, Mardian M, Soofi M. Investigation of area slope threshold of gullies in the Zahirabad Watershed, Shazand, Markazi Province, J. Watershed Eng. Manag. 2014, 6(1): 1-9. (In Persian)
[40]. Refahi, HGh. Water erosion and conservation, Tehran University Publication, 2009, 6: 671 p. (In Persian)
[41]. Wang B, Zheng F, Römkens MJ, Darboux F. Soil erodibility for water erosion: A perspective and Chinese experiences. Geomorph. 2013, 187: 1-10.
[42]. Wischmeier WH, Johnson CB, Cross BV. A soil erodibility nomograph for farmland and construction sites. J. Soil. Water Conserv. 1971, 26: 189–193.
[43]. Romkens MJM, Prasad SN, Poesen, JWA. Soil erodibility and properties. In Proc. 13th congree. International soil science society. 1986, (Vol. 5, pp. 492–504). Germany: Hamburg.
[44]. Torri D, Poesen J, Borselli L. Predictability and uncertainty of the soil erodibility factor using a global dataset. Catena. 1997, 31: 1–22.
[45]. Torri D, Poesen J, Borselli L. Corrigendum to “Predictability and uncertainty of the soil erodibility factor using a global dataset” [Catena 31 (1997) 1–22] and to “Erratum to Predictability and uncertainty of the soil erodibility factor using a global dataset. [Catena 32 (1998) 307–308]”. Catena, 2002, 46: 309–310.
[46]. Bayazidi A, Oladi B, Abbasi N. Data analysis by SPSS (PASW) 18 software. Abed Publication. 2009; 1: 250 p. (In Persian)
[47]. Davudi Rad AA, Sadeghi SHR, Sadoddin A. Monitoring temporal and spatial changes in land use in the Shazand Watershed, Ecohydrol. 2016, 2(4): 405-415. (In Persian)
[48]. Tsui CC, Chen ZS, Hsieh CF. Relationships between soil properties and slope positioning a low land rain forest of southern Taiwan. Geoderm., 2004, 123: 131–142.
[49]. Dessalegn D, Beyene S, Ram N, Walley F, Gala TS. Effects of topography and land use on soil characteristics along the toposequence of Ele watershed in southern Ethiopia. Catena, 2014, 115: 47-54.
[50]. Rosemary F, Indraratne SP, Weerasooriya R, Mishra U. Exploring the spatial variability of soil properties in an Alfisol soil catena. Catena. 2017, 150, 53-61.
[51]. Sadeghi S.H.R, Pourghasemi H.R, Mohamadi M, Agharazi H. Evaluation of Accuracy and Efficiency of USLE and Some of Its Versions in Estimation of Storm-Wise Soil Erosion and Sediment Yield, J. Water. Soil Sci. 2009, 12(46), 323-334. | ||
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