مدل‌سازی محتوای کربن آلی خاک بر اساس شاخص‌های توپوگرافی و ویژگی‌های خاک کشت‌زارهای دیم گندم

نوع مقاله : مقاله کامل علمی پژوهشی

نویسندگان

1 دانشجوی دکتری / دانشگاه زنجان

2 دانشیار گروه خاکشناسی دانشگاه زنجان

3 عضو هیئت علمی مرکز تحقیقات کشاورزی استان زنجان

چکیده

سابقه و هدف: کربن آلی خاک از عوامل مهمی است که بر کیفیت خاک، آب و اتمسفر مؤثر است. محتوی کربن آلی خاک تابعی از اثرات متقابل اقلیم، پوشش گیاهی، زهکشی، مدیریت زراعی، کاربری اراضی و ویژگی‌های خاک از جمله بافت خاک، نوع کانی و ساختمان خاک است (7). درصد شیب و موقعیت‌های مختلف توپوگرافی بر حفظ رطوبت خاک و ایجاد شرایط مناسب برای استقرار گیاهی و در نتیجه میزان انباشته شدن و تجزیه کربن آلی خاک مؤثر می‌باشند (2). در میان اثر ویژگی‌های خاک بر کربن آلی خاک، بیش‌ترین پژوهش بر بررسی اثر اجزای بافت خاک صورت گرفته و نتایج متفاوتی در این خصوص گزارش شده است (16-18). هدف از این پژوهش ارائه مدل رگرسیونی است که با استفاده از شاخص‌های توپوگرافی و ویژگی‌های خاک، کربن آلی خاک را در کشت‌زارهای دیم واقع در منطقه نیمه خشک برآورد نماید.
مواد و روش‌ها: در این پژوهش 110 نمونه خاک به صورت تصادفی در سه تکرار از مزارع دیم گندم شهرستان خدابنده واقع در جنوب استان زنجان در سال 1392 تهیه شد. شاخص‌های توپوگرافی شامل درصد شیب، شاخص خیسی، همواری بستر دره دارای چند قدرت تفکیک و انحناهای قائم، افقی، عمومی، حداقل و حداکثر با استفاده از مدل ارتفاع رقومی با قدرت تفکیک 90 متر در 90 متر به دست آمدند. ویژگی‌های خاک شامل شن، سیلت و رس، pH گل اشباع و محتوی کربن آلی در آزمایشگاه اندازه‌گیر‌ی شدند. در صورت عدم تبعیت داده‌ها از توزیع نرمال از روش تبدیل جانسون استفاده شد. با به‌کارگیری روش رگرسیون حداقل مربعات جزئی، مدلی برای بیان تغییرات محتوی کربن آلی خاک (80=n) ارائه شد. روش اعتبارسنجی تقاطعی به صورت جداسازی تکی برای انتخاب بهترین مدل براساس تعداد مؤلفه‌های اصلی بکار رفت. سپس، مدل انتخاب شده با استفاده از مجموعه جدیدی از داده‌ها (30= n) مورد ارزیابی قرار گرفت. کل فرآیند ارائه مدل و آزمون آن در سه تکرار به صورت گروه‌بندی داده‌ها در قالب داده‌های مدل و آزمون آن صورت گرفت.
یافته‌ها: در میان شاخص‌های توپوگرافی کربن آلی خاک بیشترین همبستگی را به ترتیب با مقادیر نرمال‌شده شاخص خیسی (5901/0P

کلیدواژه‌ها

عنوان مقاله [English]

Modeling of soil organic carbon content using topographic indices and soil characteristics in rainfed wheat lands

نویسندگان [English]

  • Ali Reza Vaezi 2
  • Mehdi Taheri 3
1 phD student/Univeristy of Zanjan
2 Associate professor/ University of Zanjan
چکیده [English]

Background and objectives: Soil organic carbon is one of the crucial factors which affects soil quality, water and atmosphere. Soil organic carbon content is a function of climate, vegetation cover, drainage, crop management, land use and soil properties such as texture, mineralogy and structure (7). Slope steepness and different topographic positions are influencing on soil moisture retention and a suitable condition creation for plant establishment and eventually soil organic carbon accumulation and decomposition (2). Among soil properties affecting on soil organic carbon, the most researches have been done on soil texture constitutes and the different results has been reported (16-18). The aim of this study is developing a regression model to estimate soil organic carbon using topographic indices and soil characteristics.
Material and methods: In the present study, 110 soil samples were randomly collected from topsoil (0-30 cm) in three replicates from rainfed wheat farms of Khodabandeh County located in South Zanjan, in 2013. Topographic indices including slope steepness, topographic wetness index, multi-resolution valley bottom flatness and profile, plane, general, maximal and minimal curvatures were obtained using digital elevation model in 90m×90m resolution. Soil properties including sand, silt and clay, saturated paste pH and organic carbon content were measured in laboratory. If the data did not follow normal distribution, Johnson Transformation was performed. Applying partial least square regression, a model was developed for describing soil organic carbon variations (n=80). The cross validation by leave one out method was executed to select the optimal model based on principal components number. Then, the selected model were tested using new set of data (n=30). All the modeling, it validation and test processes were performed in three replicates by grouping the data in modeling-validation and test data sets.
Results: Among topographic indices, soil organic carbon demonstrated highest Pearson correlation coefficients with normalized topographic wetness index (r=0.59, P

کلیدواژه‌ها [English]

  • Leave-one-out cross validation
  • Maximal curvature
  • Wetness index
  • Regression

مراجع

1.Adnan, N., Ahmad, M.H., and Adnan, R. 2006. A comparative study on some methods for handling multicollinearity problems. Matematika. 22: 2. 109-119.
2.Andruschkewitsch, R., Geisseler, D., Koch, H.J., and Ludwig, B. 2013. Effects of tillage on contents of organic carbon, nitrogen, water-stable aggregates and light fraction for four different long-term trials. Geoderma. 192: 368-377.
3.Asakereh, H. 2004. Modeling of spatial variation climatic parameters- case study: annual precipitation of Isfahan province. Geographical Research. 74: 3. 213-231. (In Persian)
4.Ayoubi, S., Mokhtari Karchegani, P., Mosaddeghi, M.R., and Honarjoo, N. 2012. Soil aggregation and organic carbon as affected by topography and land use change in western Iran. Soil Tillage Res. 121: 0. 18-26.
5.Bilandi, S.M., Khormali, F., and Karouyeh, A.K. 2014. Map preparing using topographic characteristic and geostatistic in in some part of Toshan area, Golestan Province.
Soil Res. J. (Soil and Water Science.) 28: 2. 459-468. (In Persian)
6.Buol, S.W., Southard, R.J., Graham, R.C., and McDaniel, P.A. 2011. Soil genesis and classification, John Wiley and Sons.
7.Chaudhari, S., Singh, R., and Kundu, D. 2008. Rapid textural analysis for saline and alkaline soils with different physical and chemical properties. Soil Sci. Soc. Am. J. 72: 2. 431-441.
8.Corsi, S., Friedrich, T., Kassam, A., Pisante, M., and Sà, J.M. 2012. Soil organic carbon accumulation and greenhouse gas emission reductions from conservation agriculture: a literature review. Food and Agriculture Organization of the United Nations (FAO).
9.Craine, J.M., and Gelderman, T.M. 2011. Soil moisture controls on temperature sensitivity of soil organic carbon decomposition for a mesic grassland. Soil Biol. Biochem. 43: 2. 455-457.
10.Dan-Dan, W., Xue-Zheng, S., Hong-Jie, W., Weindorf, D.C., Dong-Sheng, Y., Wei-Xia, S., Hong-Yan, R., and Yong-Cun, Z. 2010. Scale effect of climate and soil texture on soil organic carbon in the uplands of Northeast China. Pedosphere. 20: 4. 525-535.
11.Dashtaki, S.G., Homaee, M., and Khodaverdiloo, H. 2010. Derivation and validation of pedotransfer functions for estimating soil water retention curve using a variety of soil data. Soil Use Manage. 26: 1. 68-74.
12.Dormann, C.F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., Marquéz, J.R.G., Gruber, B., Lafourcade, B., Leitão, P.J., Münkemüller, T., McClean, C., Osborne, P.E., Reineking, B., Schröder, B., Skidmore, A.K., Zurell, D., and Lautenbach, S. 2013. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography. 36: 1. 27-46.
13.Fallahzade, J., and Hajabbasi, M.A. 2011. The distribution of organic carbon, nitrogen and carbohydrates in aggeregates of some desert and cropland soils in central Iran. J. Water Soil. 25: 3. 518-529. (In Persian)
14.Florinsky, I.V. 2012. Digital Terrain Analysis in Soil Science and Geology, Elsevier/Academic Press.
15.Franzluebbers, A.J. 2005. Soil organic carbon sequestration and agricultural greenhouse gas emissions in the southeastern USA. Soil Tillage Res. 83: 1. 120-147.
16.Gee, G.W., and Or, D. 2002. Particle-size analysis. P 255-294, In: J. Dane and G.C. Topp (Eds.), Methods of soil analysis, Part 4. Physical Methods. SSSA, Madison, WI. USA.
17.Johnson, N.L. 1949. Systems of Frequency Curves Generated by Methods of Translation. Biometrika Trust. 36: 1-2. 149-176.
18.Knadel, M., Thomsen, A., Schelde, K., and Greve, M.H. 2015. Soil organic carbon and particle sizes mapping using vis–NIR, EC and temperature mobile sensor platform. Comput. Electron. Agric. 114: 0. 134-144.
19.Konen, M., Burras, C., and Sandor, J. 2003. Organic carbon, texture, and quantitative
color measurement relationships for cultivated soils in north central Iowa. Soil Sci. Soc. Am. J. 67: 6. 1823-1830.
20.Kuhn, M., and Johnson, K. 2013. Applied predictive modeling, Springer.
21.Lal, R. 2010. Managing soils and ecosystems for mitigating anthropogenic carbon emissions and advancing global food security. BioScience. 60: 9. 708-721.
22.Liu, S., Zhang, W., Wang, K., Pan, F., Yang, S., and Shu, S. 2015. Factors controlling accumulation of soil organic carbon along vegetation succession in a typical karst region in Southwest China. Sci. Total. Environ. 521-522: 0. 52-58.
23.McLean, E.O. 1982. Soil pH and lime requirement, pp. (199-224). In: Page, A.L., ed., Methods of soil analysis, (Volume) Part 2. Chemical and microbiological properties:  American Society of Agronomy, Madison, Wisconsin.
24.Moore, I.D., Gessler, P., Nielsen, G., and Peterson, G. 1993. Soil attributes prediction using terrain analysis. Soil Sci. Soc. Am. J. 57: 2. 443-452.
25.Nelson, D.W., and Sommer, L.E. 1982. Total carbon, organic carbon, and organic matter,
pp. (539-579). In: Page, A.L., ed., Methods of Soil Analysis:, (Volume) Chemical and Microbiological Properties ASA Monograph, 9 American Society of Agronomy, Madison.
26.O'Brien, S.L., Jastrow, J.D., Grimley, D.A., and Gonzalez-Meler, M.A. 2015. Edaphic controls on soil organic carbon stocks in restored grasslands. Geoderma. 251-252: 0. 117-123.
27.Office of budget and planning. 2011. Planning assistant of Zanjan province general governor. 5. 1st edition.
28.Parton, W.J., Schimel, D.S., Cole, C.V., and Ojima, D.S. 1987. Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil Sci. Soc. Am. J.
51: 5. 1173-1179.
29.Parvizi, Y., Gorji, M., Mahdian, M.H., and Omid, M. 2010. Soil organic carbon variability prediction and determination of physical and management variables impacts in a semi-arid rainfed watershed using multivariate canonical discriminate analysis (CDA) techniques.
J. Water Soil. 24: 4. 745-756. (In Persian)
30.Pei, T., Qin, C.Z., Zhu, A.X., Yang, L., Luo, M., Li, B., and Zhou, C. 2010. Mapping soil organic matter using the topographic wetness index: A comparative study based on different flow-direction algorithms and kriging methods. Ecol. Indic. 10: 3. 610-619.
31.Reeves, D. 1997. The role of soil organic matter in maintaining soil quality in continuous cropping systems. Soil Tillage Res. 43: 1. 131-167.
32.Reinsch, S., Ambusa, P., Thornton, B., and Paterson, E. 2013. Impact of future climatic conditions on the potential for soil organic matter priming. Soil Biol. Biochem. 65: 133-140.
33.Renwick, W., Smith, S., Sleezer, R., and Buddemeier, R.W. 2004. Comment on" managing soil carbon"(ii). Science. 305: 5690. 1567-1567.
34.Rhoades, J.D. 1982. Soluble salts. P 167-179, In: A.L. Page, R.H. Miller and D.R. Keeney (Eds.), Methods of soil analysis: Part 2: Chemical and microbiological properties, (Volume) Monograph Number 9 (Second Edition): ASA, Madison, WI. USA.
35.Ritchie, J.C., McCarty, G.W., Venteris, E.R., and Kaspar, T.C. 2007. Soil and soil organic carbon redistribution on the landscape. Geomorphology. 89: 1-2. 163-171.
36.Ryan, B., Joiner, B., and Cryer, J. 2012. MINITAB Handbook: Update for Release.
37.Schwanghart, W., and Jarmer, T. 2011. Linking spatial patterns of soil organic carbon to topography-a case study from south-eastern Spain. Geomorphology. 126: 1. 252-263.
38.Soil Survey Staff. 2014. Keys to Soil Taxonomy, 12th ed. USDA-Natural Resources Conservation Service, Washington, DC.
39.Volk, C., Wood, L., Johnson, B., Robinson, J., Zhu, H.W., and Kaplan, L. 2002. Monitoring dissolved organic carbon in surface and drinking waters. J. Environ. Monit. 4: 1. 43-7.
40.Wiesmeier, M., Hübner, R., Barthold, F., Spörlein, P., Geuß, U., Hangen, E., Reischl, A., Schilling, B., von Lützow, M., and Kögel-Knabner, I. 2013. Amount, distribution and driving factors of soil organic carbon and nitrogen in cropland and grassland soils of southeast Germany (Bavaria). Agric. Ecosyst. Environ. 176: 0. 39-52.
41.Zarinfar, S., Ghahraman, B., and Davary, K. 2011. Development of Some Pedotransfer Functions to Predict the Saturated Hydraulic Conductivity of Gravel Soils Using Partial Least Square Regression Method. J. Water Soil. 25: 3. 617-624. (In Persian)
42.Zinn, Y.L., Lal, R., and Resck, D.V.S. 2005. Texture and organic carbon relations described by a profile pedotransfer function for Brazilian Cerrado soils. Geoderma. 127: 1-2. 168-173.
مجله پژوهش‌های حفاظت آب و خاک
دوره 23، شماره 3
مرداد 1395
صفحه 111-129

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