برآورد پارامترهای منحنی مشخصه آب خاک در مدل‌های مختلف در خاک های سبک

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه صنعتی اصفهان

2 گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه صنعتی اصفهان، اصفهان، ایران

چکیده
برای رشد گیاهان علاوه بر مقدار آب، پتانسیل ماتریک آب خاک نیز دارای اهمیت است. رابطه بین این دو با عنوان منحنی مشخصه آب خاک بیان می‌شود. مدل‌های بسیاری برای توصیف منحنی مشخصه آب خاک براساس داده‌های تجربی ارائه شده است اما به ندرت توانایی ‌آن‌ها در تخمین منحنی مذکور برای بافت خاک‌های مختلف بررسی شده است. در پژوهش حاضر از اطلاعات مکش- رطوبت، 16 نمونه خاک در اطراف ایستگاه جنگلی در مرکز فنلاند استفاده شده است. تعداد 9 مدل معروف و پرکاربرد منحنی مشخصه آب خاک بر داده‌های تجربی برازش داده شدند. دقیق‌ترین مدل یک مرتبه برای کل داده‌ها و یک مرتبه برای هر گروه بافتی بر اساس معیارهای ریشه میانگین مربعات خطا، ضریب تبیین و میانگین خطا انتخاب شد. نتایج نشان داد مدل‌های ون گنوختن -معلم، ون گنوختن، گاردنر و براتسارت به ترتیب بیشترین و مدل‌ بروکس- کوری کمترین دقت را در تخمین منحنی مشخصه رطوبتی خاک داشتند.

کلیدواژه‌ها


عنوان مقاله English

Estimation of soil water characteristic curve parameters in different models in light soils

نویسندگان English

jahangeer abedi koupaee 1
Nahid Pourabdollah 2
Shahab Ansari 2
1 sfahan university
2 Department of Water Science and Engineering, College of Agriculture Isfahan University of Technology, Isfahan, Iran
چکیده English

In addition to soil water content, soil matric potential is also important for plant growth. Soil water characteristic curve (SWCC) or soil moisture characteristic curve describes soil water content and soil matric potential relationship. Many models have been developed to describe the SWCCs and their fitting to the experimental data. However, their fitting accuracies in different soil textures, have been rarely investigated. In this study, matric potential-moisture data of 16 soil sample of forest station in Finland use to fit SWCC models. Nine well known and frequently applied SWCC models were fitted to the measured data. The most accurate models of total soil samples, each textural group and each textural class were estimated using root mean square error (RMSE), coefficient of determination (R2) and mean error (ME). Result showed that van Genuchten-Mualem, van Genuchten, Gardner and Brutsaert models had most accurate and Brooks and Corey model had least accurate to predict SWCC.

کلیدواژه‌ها English

Soil texture
SWCC
van Genuchten-Mualem
van Genuchten
Gardner and Brutsaert models
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