تعیین مؤثرترین ویژگی‌ها به منظور ارزیابی کیفیت خاک در اراضی کشاورزی دشت محمدشهر کرج

نوع مقاله : مقالات پژوهشی

نویسندگان

1 گروه احیاء مناطق خشک و کوهستانی، دانشکده منابع طبیعی، دانشگاه تهران و مربی پژوهشی مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی گیلان، سازمان تحقیقات، آموزش و ترویج کشاورزی

2 گروه احیاء مناطق خشک و کوهستانی، دانشکده منابع طبیعی، دانشگاه تهران

3 پژوهشکده حفاظت خاک و آبخیزداری، سازمان تحقیقات،‌ آموزش و ترویج کشاورزی

4 گروه علوم و مهندسی خاک، دانشکده کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی

چکیده

کیفیت خاک شاخصی‌ ضروری برای مدیریت پایدار اراضی است که به ویژگی‌های فیزیکی، شیمیایی و بیولوژیکی خاک بستگی دارد. بسیاری از محققین ارزیابی کیفیت خاک را بر معدودی از ویژگی‌ها متمرکز کرده‌اند. در این تحقیق به منظور ارزیابی و انتخاب ویژگی‌های موثر در کیفیت خاکِ اراضی کشاورزی دشت محمدشهر کرج با مدیریت‌های مختلف آبیاری، از شاخص کیفیت تجمعی (IQI) و شاخص کیفیت نمرو (NQI) استفاده شد. با حفر و تشریح 12خاکرخ در چهار مزرعه و باغ و نمونه‌برداری از افق‌های سطحی و متوسط عمقی، 16ویژگی‌ مؤثر در کیفیت خاک تعیین و شاخص‌های یاد شده محاسبه گردیدند. بررسی شاخص‌های IQI و NQI نشان داد که خاک‌های این منطقه در نمونه‌های سطحی عمدتاً دارای درجه کیفیت III و در نمونه‌های متوسط عمقی به دلیل عدم تکامل پروفیلی، کربن آلی پایین و سنگریزه بالا دارای درجه کیفیت IV با محدودیت زیاد هستند. بیشترین و کمترین میانگین‌ شاخص کیفیت خاک لایه سطحی به‌ترتیب به مزرعه یونجه (آبیاری بارانی) با 64/0 و مزرعه گندم (آبیاری بارانی) با 58/0 اختصاص یافت. تأثیر مدیریت آبیاری بر شاخص‌های کیفیت خاک نشان داد که نوع سامانه‌ آبیاری نتوانسته است تفاوت معنی‌داری در کیفیت خاک ایجاد نماید. به‌طوری‌که در مزرعه گندم با آبیاری‌های بارانی و غرقابی، تفاوت معنی‌داری در شاخص‌های کیفیت خاک مشاهده نشد. شاخص IQI در مجموعه کل داده‌ها نسبت به شاخص NQI دارای دقت و حساسیت بیشتری برای ارزیابی کیفیت خاک بود؛ لیکن بررسی ضرایب تبیین، قابل اطمینان بودن استفاده از مجموعه حداقل داده‌ها به ‌جای مجموعه کل داده‌ها در هر دو مدل IQI و NQI را نشان داد. در مجموعه حداقل داده‌ها ویژگی‌های میانگین وزنی قطر خاکدانه‌ها و درصد سنگریزه دارای وزن بالاتری به ترتیب در لایه‌های سطحی و متوسط عمقی بودند. استفاده از مؤثرترین ویژگی‌های خاک در مطالعات ارزیابی کیفیت خاک اثر تکرارپذیری حاصل از ویژگی‌های با همبستگی مشابه را کاهش می‌دهد.

کلیدواژه‌ها


عنوان مقاله [English]

Determining the Most Effective Properties to Evaluate Soil Quality of Agriculture Lands in Mohammadshahr Plain of Karaj

نویسندگان [English]

  • K. Kamali 1
  • Gholamreza Zehtabian 2
  • Tayebeh Mesbahzadeh 2
  • Mahmood Arabkhedri 3
  • Hosayin Shahab Arkhazloo 4
  • Alireza Moghadamnia 2
1 Department of Reclamation of Arid and Mountainous Regions, Faculty of Natural Resources, University of Tehran, and Member of Scientific Board, Gilan Agricultural and Natural Resources Research and Education Center, Agricultural Research,
2 Department of Reclamation of Arid and Mountainous Regions, Faculty of Natural Resources, University of Tehran
3 Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization, Tehran, Iran
4 Department of Soil Science, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
چکیده [English]

Introduction: Soil quality is an essential indicator for sustainable land management that generally depends on soil physical, chemical and biological properties. Due to the multiplicity of soil properties, the number of variables is usually reduced to a minimum set by statistical methods, which reduces study time, decreases monitoring cost for sustainable use of agricultural lands. The aim of this study was to introduce the most effective soil characteristics of agricultural lands in Mohammadshahr plain, Karaj, to prevent the descending trend of soil quality.
Materials and Methods: In this study, four farms and orchards which were different in terms of crop type and irrigation system were selected and evaluated with Integrated Quality Index (IQI) and Nemero Quality Index (NQI). In both indicators, the characteristics affecting soil quality are combined in the form of a mathematical model and presented as a numerical quantity. For this purpose, first 12 soil profiles were described, followed by sampling from topsoil (surface layer) and sublayers (weighting average for the depths) and testing 17 soil characteristics affecting its quality. In the next step, both indicators were calculated using two different sets of soil properties. The first category, the Total Data Set (TDS), included all measured soil characteristics, and the second group, the Minimum Data Set (MDS), included the most important properties affecting soil quality. The Principle Component Analysis was implemented to select the MDS. Soil properties were scored to calculate IQI and NQI. For this purpose, a function was defined for each soil feature to standardize all scores between zero and one. Weighting various soil quality properties was also performed by calculating the common variance of the variables, which was obtained by factor analysis method.
Results and Discussion: Calculation of IQI and NQI indices showed that the topsoil samples were in grade III and sublayer samples belonged to grade IV with major limitations due to lack of profile development, organic carbon deficiency, salinity and high gravel. Four and six items out of 16 variables were identified effective for topsoil and sublayers, respectively. The IQI index based on TDS was more accurate and sensitive than the NQI index for soil quality assessment, as more features are considered for TDS. In the IQI index, both the weight of attributes and their scores are effective, while in the NQI index, only the attribute score is considered. On the other hand, the coefficient of determination between the TDS and MDS for topsoil and sublayer samples was 0.55 and 0.56% for IQI model, respectively, and 0.48 and 0.16% for NQI model, respectively. In other words, the determination coefficients showed the reliability of using the MDS instead of TDS in both IQI and NQI models. In the MDS, mean weight diameter (MWD) showed the highest effect on the surface layer and percentage of gravel had the greatest impact on the soil quality of the sublayer.
Conclusion: Although TDS took into account all soil properties and showed a slightly higher coefficient of determinations with both soil quality indicators, the MDS obtained similar results to the TDS with only about half of the properties. In the MDS, the features with an internal correlation is eliminated rendering it more cost effective. The results of this study assist decision-makers to choose better quality management and soil sustainability strategies while decreasing the monitoring cost.

کلیدواژه‌ها [English]

  • Principle component analysis
  • Irrigation systems
  • Integrated Quality Index
  • Nemoro Quality Index
  • Karaj
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