بررسی شاخصهای کیفیت خاک در اراضی زراعی و غیر زراعی غرب دشت ارومیه

نوع مقاله : مقاله کامل علمی پژوهشی

نویسندگان

1 دانشجوی دکتری علوم ومهندسی خاک ، دانشگاه لرستان

2 استاد، گروه علوم و مهندسی خاک دانشگاه لرستان

3 استادیار ، گروه علوم خاک، دانشکده کشاورزی، دانشگاه زنجان

4 دانشیار پژوهشی، بخش تحقیقات خاک و آب، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی آذربایجان غربی، سازمان تحقیقات، آموزش و ترویج کشاورزی، ارومیه، ایران.

5 استادیار پژوهش، بخش تحقیقات خاک و آب، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان کرمانشاه، سازمان تحقیقات، آموزش و ترویج

چکیده

چکیده:
سابقه و هدف:شناسایی کاربری های اراضی و تاثیر آنها بر عملکردهای سه گانه خاک شامل،تولیدات زیستی، تصفیه آب و تصفیه هوا چالش امروز محیط زیست است. شاخص کیفیت خاک ابزاری برای بیان توان خاک در ارائه خدمات زیستی و تصفیه آب و هوا و بالاخره مدیریت خاک و سیستم کاربری اراضی است. ویژگی‌های مختلف فیزیکی، شیمیایی و بیولوژیکی خاک به عنوان نمایه های موثر بر کیفیت خاک شناخته می شوند، این نمایه ها برای محاسبه کیفیت خاک استفاده می شوند. این ویژگی‌ها که به مدیریت و عوامل مختلف محیطی و توپوگرافی حساس می‌باشند، با استفاده از روشهای پیشنهادی برای محاسبه شاخص کیفیت خاک استفاده می شوند. هدف از این مطالعه بررسی دو روش مختلف محاسبه شاخص کیفیت خاک شاخص کیفیت وزنی (SQIw) و شاخص کیفیت نمورو (NQI) در اراضی دشت اورمیه می باشد.
مواد وروشها:تعداد 100 نقطه مطالعاتی به روش ابر مکعب لاتین انتخاب و نمونه برداری از عمق صفر تا 25 سانتیمتری انجام شد ، 14 ویژگی موثر بر کیفیت خاک با ورشهای استاندارد اندازه گیری شد. با بررسی تحقیقات گذشته و با استفاده از (PCA) نمایه‌هایی که باید در MDS گنجانده شوند، استفاده شد و از بین 14 ویژگی مورد مطالعه 9ویژگی هدایت الکتریکی، روی، آهن، تنفس، منگنز، آهک فعال، هدایت هیدرولیکی غیر اشباع، نیتروژن و میانگین وزنی قطر خاکدانه‌ها، نمایه‌هایی هستند که بعنوان داده‌های حداقل (MDS) انتخاب گردید.
یافته ها: نتایج نشان داد کار بری های مرتعی، زراعی و باغی دارای مقادیر کیفیت خاک بالاتری نسبت به کاربری های بایر(خاکهای شور) و مسکونی می باشند. به نظر می‌رسد شوری عامل مهمی در تنزل کیفیت خاک است و از طرفی دخالت انسان، تخریب و ساخت و ساز نیز به شدت کیفیت خاک را کاهش می‌دهد. در بین رویکردهای مورد مطالعه، شاخص SQIw در مقایسه با شاخص NQI منجر به ارزیابی مناسب اثرات شیوه‌های مدیریت زمین بر کیفیت خاک شد. بطور کلی این مطالعه نشان می دهد شاخص کیفیت وزنی خاک براورد مناسبی از کیفیت خاک را در مقایسه با روشهای دیگر ارائه می دهد و می تواند برای مناطق خشک و نیمه خشک برای ارزیابی کیفیت خاک ها مورد استفاده قرار گیرد.
نتیجه گیری: در مطالعه کنونی ویژگی های تاثیر گذار بر شاخص نهایی کیفیت خاک شامل شوری خاک، روی، منگنز، نیتروژن، تنفس ، کربن آلی خاک و آهک فعال خاک است. این ویژگی‌ها با اثر بر روی شاخص نهایی خاک سرنوشت درجه کیفیت خاک را تعیین نمودند. خشکی دریاچه ارومیه به دلیل تغییرات اقلیمی از یک سو و افزایش فشار بر منابع آب های زیرزمین در بخش غربی و جنوب غربی دریاچه ارومیه منجر به کاهش کیفیت خاکهای متاثر از نمک در حاشیه دریاچه ارومیه گردیده است. نتایج حاصل از بررسی دو شاخص وزنی خاک و شاخص نمورو کیفیت خاک، نشان می دهد که عموما شاخص نمرو در انتخاب نهایی کلاس کیفیت خاک سخت گیرانه تر بوده و شاخص وزنی کیفیت خاک با وضعیت کنونی بیشتر مطابقت دارد. ساخت و سازهای کنونی و شوری در این بخش از منطقه مورد مطالعه منجر به کاهش شاخص کیفیت خاک شده و شرایط بحرانی برای خاک بوجود آورده است

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Investigation of soil quality indices in agricultural and non-agricultural lands west of Urmia Plain

نویسندگان [English]

  • Zahra Dibaei 1
  • Hamid Reza Matinfar 2
  • Mohammad sadegh Askari 3
  • Aziz Majidi 4
  • Shahrokh Fatehi 5
1 Dept. of SCI. colleague of Agric. Lorestan University
2 Full prof. of Lorestan University
3 Assistant Professor, Department of Soil Science, Faculty of Agriculture, University of Zanjan
4 Research Associate Professor, Soil and Water Research Department, West Azerbaijan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Urmia, Iran.
5 Research Assistant Prof., Soil and Water Research Department, Kermanshah Agricultural and Natural Resources Research and Education Center, AREEO, Kermanshah, Iran,
چکیده [English]

Background and Purpose:
The challenge of today's environment is to identify the impact of different land uses on soil quality. Soil quality is a measure of the ability of soil to perform three key functions: the production of biological matter, the purification of water and the purification of air. The Soil Quality Index is a tool for expressing soil quality. It is based on the idea that soil quality affects how well it performs these three functions. Different physical, chemical and biological characteristics of soil affect soil quality. These characteristics are used to calculate soil quality. These features are employed in the calculation of the soil quality index using the proposed methods. This study compares two distinct methods of calculating the soil quality index: the Weighted Quality Index (SQIw) and the Numerical Quality Index (NQI) in the Urmia Plain.
Materials and Methods: A total of 100 study points were selected using the Latin hypercube method, and sampling was conducted from a depth of 0 to 25 cm. A total of 14 characteristics affecting soil quality were measured using standard scales. A review of previous research and the use of principal component analysis (PCA) enabled the selection of profiles to be included in the minimum data set (MDS). Among the 14 characteristics studied, nine were selected as the minimum data set (MDS) indexes: electrical conductivity, zinc, iron, respiration, manganese, activated lime, unsaturated hydraulic conductivity, nitrogen and the weighted mean diameter of soil grains.
Findings: The results indicated that pasture, agricultural and garden uses exhibited higher quality values than barren (saline soils) and residential uses. It can be postulated that salinity is an important factor in the degradation of soil quality, and that human intervention, destruction and construction also severely reduce soil quality. Among the studied approaches, the SQIw index, when compared to the NQI index, led to a proper assessment of the effects of land management practices on soil quality. In general, this study demonstrates that the weighted soil quality index provides a reliable estimation of soil quality compared to other methods, and can be employed for arid and semi-arid regions to evaluate the quality of soils.

Conclusion: The characteristics affecting the final index of soil quality in the current study include soil salinity, zinc, manganese, nitrogen, respiration, soil organic carbon and soil active lime. These characteristics determine the fate of soil quality by affecting the final soil index. The drying of Lake Urmia due to climate change, coupled with the increased pressure on underground water resources in the western and southwestern parts of the lake, has resulted in a decline in the quality of soils affected by salt on the lake's edge. The results of the analysis of two soil weight indices and the Nemuro index of soil quality indicate that, in general, the Nemuro index is more rigorous in the final selection of the soil quality class, and the soil quality weight index is more consistent with the current situation. The current constructions and salinity in this part of the studied area have led to a decrease in the soil quality index and created critical conditions for the soil

کلیدواژه‌ها [English]

  • soil quality index
  • minimum data
  • PCA
  • Urmia
1.Dominati, E., Patterson, M., & Mackay, A. (2010). A framework for classifying and quantifying the natural capital and ecosystem services of soils. Ecological economics, 69(9), 1858-1868.
2.Doran, J. W., & Parkin, T. B. (1994). Defining and assessing soil quality. Defining soil quality for a sustainable environment, 35 (1-21) https://doi.org/ 10.2136/sssaspecpub35.c1.
3.Karlen, D. L., Mausbach, M. J., Doran, J. W., Cline, R. G., Harris, R. F., & Schuman, G. E. (1997). Soil quality: a concept, definition, and framework for evaluation (a guest editorial). Soil Science Society of America Journal, 61(1), 4-10. https://doi.org/10.2136/sssaj1997.03615995006100010001x.
4.Matinfar, H. R., Jalali, M., & Mohamadi, S. (2019). Soil Quality, Jihad Daneshgahi publication, Tehran. [In Persian]
5.Karlen, D. L., Ditzler, C. A., & Andrews, S. S. (2003). Soil quality: why and how? Geoderma, 114(3-4), 145-156.
6.Arshad, M. A., & Coen, G. M. (1992). Characterization of soil quality: physical and chemical criteria. American Journal of Alternative Agriculture, 7(1-2), 25-31.
7.Abdel Rahman, M. A., & Tahoun, S. (2019). GIS model-builder based on comprehensive geostatistical approach to assess soil quality. Remote sensing Applications: society and Environment, 13, 204-214.
8.Ball, B. C., Batey, T., & Munkholm, L. J. (2007). Field assessment of soil structural quality–a development of the Peerlkamp test. Soil use and Management, 23(4), 329-337. https://doi.org/10.1111/ j.1475-2743.2007.00102.x.
9.Andrews, S. S., Karlen, D. L., & Cambardella, C. A. (2004). The soil management assessment framework: A quantitative soil quality evaluation method. Soil Science Society of America Journal, 68(6), 1945-1962. https://doi. org/10.2136/sssaj2004.1945.
10.Qi, Y., Darilek, J. L., Huang, B., Zhao, Y., Sun, W., & Gu, Z. (2009). Evaluating soil quality indices in an agricultural region of Jiangsu Province, China. Geoderma, 149(3-4), 325-334.
11.Askari, M. S., O'Rourke, S. M., & Holden, N. M. (2015). Evaluation of soil quality for agricultural production using visible–near-infrared spectroscopy. Geoderma, 243, 80-91. https://doi.org/ 10.1016/j.geoderma.2014.12.012.
12.Bastida, F., Moreno, J. L., Hernández, T., & García, C. (2006). Microbiological degradation index of soils in a semiarid climate. Soil Biology and Biochemistry, 38(12), 3463-3473.
13.Li, P., Zhang, T., Wang, X., & Yu, D. (2013a). Development of biological soil quality indicatorsystem for subtropical China. Soil Tillage Res. 126, 112-118. https://doi.org/10.1016/j.still.2012.07. 011.
14.Nabiollahi, K., Golmohamadi, F., Taghizadeh-Mehrjardi, R., Kerry, R., & Davari, M. (2018). Assessing the effects of slope gradient and land use change on soil quality degradation through digital mapping of soil quality indices and soil loss rate. Geoderma, 318, 16-28. https://doi.org/ 10.1016/ j.geoderma. 2017.12.024.

15.Yred, M., Kibebew, K., Bobe, B., & Muktar, M. (2021). Soil quality evaluation under different land use
types in Kersa sub-watershed, eastern Ethiopia, Environmental Systems Research, 10, 1-11.

16.Biswas, S., Hazra, G. C., Purakayastha, T. J., Saha, N., Mitran, T., Roy, S. S., Basak, N., & Mandal, B. (2017). Establishment of critical limits of indicators and indices of soil quality in rice-rice cropping systems under different soil orders. Geoderma, 292, 34-48. https:// doi.org/ 10.1016/ j.geoderma. 2017.01.003.
17.Gomez, C., Le Bissonnais, Y., Annabi, M., Bahri, H., & Raclot, D. (2013). Laboratory Vis–NIR spectroscopy as
an alternative method for estimating the soil aggregate stability indexes of Mediterranean soils. Geoderma,
209, 86-97. https://doi.org/10.1016/ j.geoderma.2013.06.002.
18.Rezaee, L., Moosavi, A. A., Davatgar, N., & Sepaskhah, A. R. (2020). Soil quality indices of paddy soils in
Guilan province of northern Iran: Spatial variability and their influential parameters. Ecological Indicators, 117, 106566.
19.Rahmanipour, F., Marzaioli, R., Bahrami, H. A., Fereidouni, Z., & Bandarabadi, S. R. (2014). Assessment of soil quality indices in agricultural lands of Qazvin Province, Iran. Ecological indicators, 40, 19-26. https://doi.org/10.1016/j.ecolind.2013.12.003.
20.Moges, A., Dagnachew, M., & Yimer, F. (2013). Land Use Effects on Soil Quality Indicators: A Case Study of Abo‐Wonsho Southern Ethiopia. Applied and Environmental Soil Science, 2013(1), 784989.
21.Ahmadi, K., Ebadzadeh, H. M., Hatami, F., Mohammad Niya Afrozi. S. H., Talgani, R. A., Yari, S. H., & Kalantari, M. (2022). Agricultural statistics, the third volume of horticultural and horticultural products, Ministry of Agricultural Jihad, Planning and Economic Deputy, Information and Communication Technology Center,44, 1-17. (In Persian)
22.Reynolds, W. D., Drury, C. F., Tan, C. S., Fox, C. A., & Yang, X. M. (2009). Use of indicators and pore volume-function characteristics to quantify soil physical quality. Geoderma, 152 (3-4), 252-263.
23.Roudier, P. (2011). Clhs: A R Package for Conditioned Latin Hypercube Sampling. Roudier, P., Beaudette, D., Hewitt, A., 2012. A Conditioned Latin Hypercube Sampling Algorithm Incorporating Operational Constraints. pp. 227-231.
24.Brus, D. J. (2019). Sampling for digital soil mapping: A tutorial supported by R scripts. Geoderma, 338, 464-480.
25.Mulder, V., de Bruin, S., & Schaepman, M. (2013). Representing major soil variability at regional scale by constrained latin hypercube sampling of remote sensing data. Int. J. Appl. Earth Obs. Geoinf. 21, 301-310. https:// doi.org/10.1016/j.jag.2012.07.004.
26.Ramirez-Lopez, L., Schmidt, K., Behrens, T., van Wesemael, B., Dematte, J., & Scholten, T. (2014). Sampling optimal calibration sets in
soil infrared spectroscopy. Geoderma. 226, 140-150. https://doi.org/10.1016/ j.Geoderma.2014.02.002.
27.Gee, G. W., & Bauder, J. W. (1986) Particle-Size Analysis. In: Klute, A., Ed., Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods, Agronomy Monograph No. 9, 2nd Edition, American Society of Agronomy/ Soil Science Society of America, Madison, WI, 383-411.
28.Brasher, B. R., Franzmeier, D. P., Valassis, V., & Davidson, S. E. (1966). Use of saran resin to coat natural
soil clods for bulk-density and water-retention measurements. Soil Science, 101(2), 108.
29.Nath, A. J., & Rattan, L. A. L. (2017). Effects of tillage practices and land use management on soil aggregates and soil organic carbon in the north Appalachian region, USA. Pedosphere, 27 (1), 172-176. https://doi.org/10.1016/S1002-0160 (17) 60301-1.
30.Saxton, K. E., & Rawls, W. J. (2006). Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil science society of America Journal, 70 (5), 1569-1578. https://doi.org/10.2136/sssaj2005.0117.
31.Walkley, A., & Black, I. A. (1934). An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil science, 37(1), 29-38.
32.Lindsay, W. L., & Norvell, W. (1978). Development of a DTPA soil test for zinc, iron, manganese, and copper. Soil science society of America journal, 42(3), 421-428.
33.Thomas, G. W. (1996). Soil pH and Soil Acidity. P: 475-490. In: D. L. Sparks et al. (ed.) Methods of Soil Analysis. Part 3. SSSA, ASA, Madison WI.
34.Olsen, S. R., & Sommers, L. E. (1982). Phosphorus. Agronomy, Monograph.
9: Methods of Soil Analisis. Part, 2,
401-430.
35.Knudsen, D., Peterson, G. A., & Pratt,
P. F. (1983). Lithium, sodium, and potassium. Methods of Soil Analysis: Part 2 Chemical and Microbiological Properties, 9, 225-246.
36.Carter and Gary, D., Peterson, G. A., & Pratt, P. F. (1983). Lithium, sodium, and potassium. Methods of Soil Analysis: Part 2 Chemical and Microbiological Properties, 9, 225-246.
37.Nannipieri, P., Greco, S., & Ceccanti, B. (1990). Ecological significance of the biological activityin soil. In: Bollag,
J. M., Stozky, G. (Eds.), Soil Biochemistry. 6, Marcel Dekker, NewYork, 293-355.
38.Nakajima, T., Lal, R., & Jiang, S. (2015). Soil quality index of a crosby silt loam in central Ohio. Soil and Tillage Research, 146, 323-328. https://doi.org/10.1016/j.still.2014.10. 001.
39.Lal, R. (1994). Methods and guidelines for assessing sustainable use of soil
and water resources in the tropics. Department of Agronomy The Ohio State UniversityColumbus, Ohio. Soil Management Support Services USDA Soil Conservation Service, and U.S. Agency for International Development, 1, 2-70.
40.Raiesi, F., & Kabiri, V. (2016). Identification of soil quality indicators for assessing the effect of different tillage practices through a soil quality index in a semi-arid environment. Ecological Indicators, 71, 198-207.
41.Andrews, S. S., Karlen, D. L., & Mitchell, J. P. (2002). A comparison of soil quality indexing methods for vegetable production systems in Northern California. Agriculture, ecosystems & environment, 90 (1), 25-45.
42.Liebig, M. A., Varvel, G., & Doran, J., (2001). A simple performance‐based index for assessing multiple agroecosystem functions. Agronomy Journal, 93 (2), 313-318. https:// doi.org/10.2134/agronj2001.932313x.
43.Askari, M. S., O'Rourke, S. M., & Holden, N. M. (2015). Evaluation of soil quality for agricultural production using visible–near-infrared spectroscopy. Geoderma, 243, 80-91.
44.Brejda, J., Moorman, T. B., Karlen, D. L., & Dao, T. H. (2000). Identification of regional soil quality factors and indicators: I. Central and Southern High Plains. Soil Sci. Soc. Am. J. 64, 2115-2124.
45.Nocita, M., Kooistra, L., Bachmann, M., Müller, A., Powell, M., & Weel, S. (2011). Predictions of soil surface and topsoil organic carbon content through the use of laboratory and field spectroscopy in the Albany Thicket Biome of Eastern Cape Province of South Africa. Geoderma, 167, 295-302.
 
46.Navar, J., Moorman, T. B., Karlen, D. L., & Dao, T. H. (2000). Identification of regional soil quality factors and indicators: I. Central and Southern High Plains. Soil Sci. Soc. Am. J. 64, 2115-2124.
47.Govaerts, B., Sayre, K. D., & Deckers, J. (2006). A minimum data set for Soil quality assessment of wheat and maize cropping in the highlands of Mexico. Soil and tillage research, 87 (2), 163-174.
48.Hendrickson, A. E., & White, P. O. (1964). Promax: A quick method for rotation to oblique simple structure. British journal of statistical psychology, 17 (1), 65-70.
49.Kaštovská, E., Picek, T., Bárta, J., Mach, J., Cajthaml, T., & Edwards, K. (2012). Nutrient addition retards decomposition and C immobilization in two wet grasslands. Hydrobiologia, 692, 67-81.
50.Rezaee, L., Moosavi, A. A., Davatgar, N., & Sepaskhah, A. R. (2020). Soil quality indices of paddy soils in Guilan province of northern Iran: Spatial variability and their influential parameters. Ecological Indicators, 117, 106566.
51.Da Silva, M. G., de Aguiar Netto, A. D. O., de Jesus Neves, R. J., do Vasco, A. N., Almeida, C., & Faccioli, G. G. (2015). Sensitivity analysis and calibration of hydrological modeling of the watershed Northeast Brazil. Journal of Environmental Protection, 6 (08), 837.