پديد آورندگان :
كرمي، علي داد سازمان تحقيقات آموزش و ترويج كشاورزي، شيراز - مركز تحقيقات و آموزش كشاورزي و منابع طبيعي استان فارس , زارع، روح اله دانشگاه آزاد اسلامي واحد علوم و تحقيقات فارس، شيراز , جهانديده مهجن آبادي، وحيد اله دانشگاه شيراز - دانشكده كشاورزي
كليدواژه :
بعد فركتالي , پايداري خاكدانه ها , توزيع اندازه خاكدانه ها , راسته خاك , ساختمان خاك
چكيده فارسي :
ساختمان خاك و پايداري آن با بسياري از فرآيندهاي كشاورزي و زيست محيطي در ارتباط است. از اين رو توصيف و كمي سازي ساختمان خاك از اهميت ويژه اي برخوردار است. ولي ساختمان خاك بصورت كيفي (مكعبي، دانه اي و...) بيان مي شود. هدف از اين تحقيق تعيين پايداري خاكدانه ها و استفاده از هندسه فركتالي و تعيين بعد فركتالي ساختمان خاك در برخيازراسته هايخاكبود كه نتيجه در مدل هاي كاربردي براي بيان فرآيندهاي خاك و مدل سازي قابل استفاده خواهد بود. بنابراين از افق هاي مشخصه هفت راسته خاك شامل انتي سول، ورتي سول، اريدي سول، مالي سول، الفي سول، هيستو سول و اينسپتي سول در استان فارس نمونه برداري خاك (27 نمونه) انجام گرديد. ويژگي هاي خاك شامل توزيع اندازه خاكدانه ها، بافت، درصد رطوبت اشباع، كربن آلي، EC، pH، گچ و آهك اندازه گيري و ميانگين وزني قطر خاكدانه ها (MWD) و ميانگين هندسي قطر خاكدانه ها (GMD) و بعد فركتالي خاكدانه ها محاسبه شد. نتايج نشان داد كه همبستگي معني داري بين بعد فركتالي مدل هاي ريو و اسپوزيتو (DnR) و تيلر و ويت كرافت (DmT) با MWD و GMD با ويژگي هاي خاك وجود داشت. اين همبستگي بين پارامترهاي فركتالي با ماده آلي، جرم مخصوص ظاهري، درصد رس و درصد شن، قوي تر از ديگر ويژگي هاي خاك بود. همبستگي منفي و معني داري (در سطح يك درصد) بين DnR و DmT با MWD و GMD وجود داشت. به طوري كه راسته هاي خاكي كه عدد بعد فركتالي كمتري داشتند، MWD و GMD بزرگتري داشتند. ضريب تبيين، ميانگين خطاها، ريشه ميانگين مربعات خطاها، مجذور مربعات باقي مانده ها، مجذور مربعات عدم برازش و آماره آكايك مطلوبيت بيشتر مدل تيلر و ويت كرافت را نشان داد. مدل ريو و اسپوزيتو نيز مدل مناسبي بود گرچه در مواردي بعد فركتالي را زياد محاسبه كرد كه دليل آن احتمالا حساسيت زياد اين مدل مي باشد. به طور كلي بعد فركتالي از اهميت ويژه اي براي مطالعه و كمي سازي ساختمان خاك برخوردار است و مقدار آن به استثناء راسته هيستوسول در ديگر راسته ها در محدوده مناسب (3) بود.
چكيده لاتين :
Introduction: Fractal geometry concepts have been widely applied as a useful tool to describe complex
natural phenomena, in particular,for a better understanding of soil physical systems. However, limited
information is available on the fractal characteristics of soil properties or soil aggregation. A soil aggregate is
made of closely packed sand, silt, clayand organic particles building upsoil structure. Soil aggregation is a soil
quality index integrating the chemical, physical, andbiological processes involved in the genesis of soil structure.
Soil structure and its stability are important issuesfor many agronomic and environmental processes. Thus,
quantitative description of soil structure is very important. Soil forming factors in different soils (various orders)
and forms affect the soil structureformation. Characterizing aggregate size distribution for different soil orders
using fractal theory is necessary for evaluating the impact of soil forming factors on soil structure and
quantifying the relationship between fractal dimension and other important soil properties. Therefore, the aims of
this research were quantifying the structure of different soil orders using fractal geometry, mean weight diameter
of aggregates (MWD)and geometric mean diameter of aggregates (GMD). In addition, MWD and GMD indices
and fractal parameters of soil aggregate size distribution were compared toevaluate soil structure and
determinethe relationship between fractal parameters with MWD, GMDand other soil properties.
Materials and Methods: Fractal models which simulate soil structure are also used to better understand soil
behaviors. Aggregate size distribution is determined by sieving a fixed amount of soil mass under mechanical
stress and is commonly synthesized by the MWD, GMDand fractal dimensions such as the fragmentation fractal
dimensions. Therefore, aggregate size distribution and its stability variation were evaluated using some fractal
models and MWD and GMD (empirically indices).In the current study, the original data were obtained from
analysis of diagnostic horizons of seven important soil orderslocated in Fars Province in the Southern Iran. Soil
samples were collected from diagnostic horizons of seven soil orders includingEntisols, Vertisols, Aridisols,
Mollisols, Alfisols, Histosols and Inceptisols. The measured physico-chemical properties of soil were aggregate
size distribution, soil particle size percentage (sand, silt, and clay), saturation percentage (SP), organic carbon
(OC), pH, calcium carbonate equivalent (TNV), gypsum content, soil electrical conductivity (EC) and soil bulk
density (BD). The MWD and GMD indices, the fractal dimensions and fractal parameters of aggregates were
then calculated. Relationships between soil properties with MWD, GMD and the fractal dimension were also
determined.
Results and Discussion: The results showed that there was a significant correlation between fractal
dimension of Riue and Sposito and Taylor and Wheatcraft models and soil aggregate stability indices (MWD
and GMD indices of aggregates) with the other soil characteristics. This correlation between fractal parameters
with organic matter, bulk density, clay and sand percentage was stronger than other soil properties. There was a
significant and negative correlation (p< 0.01) between fractal dimension of Riue and Sposito and Taylor and
Wheatcraft models with mean weight diameter of aggregates and geometric mean diameter of aggregates.
Inverse correlation between fractal dimension and aggregate stability indices illustrateed thatlower fractal
dimensionswere calculated for the soils with more stable aggregates which have the highest mean weight
diameter of aggregates and geometric mean diameter of aggregates. Subsequently, the fractal dimension of
aggregates could reflect the aggregate stability factors. The values of coefficient of determination (R2) and mean
error (ME), root mean square error (RMSE), residual some of squares (RSS), mean square of non-fitted (Sr2) and
Akaike (AIC) statistical criteria indicated that Taylor and Wheatcraft model had the better performance.
Although largerfractal dimensions were estimated by Riue and Sposito modelwhich can be explained by the
great model sensitivity, this model overall performed well.
Conclusion: The results indicated that fractal theory can be used to characterize soil structure at different soil
orders and fractal dimensions of soil aggregate seems to be more effective in this regard, except forHistosols.
Fractal dimension can be estimated using some easily available soil properties. Fractal theory can be applied to
characterize and quantify soil structure in different soil orders of Fars Province.
