ارزیابی مدل‌های مختلف داده‌کاوی برای پیش‌بینی نقشه حساسیت فرسایش آبکندی در حوزه آبخیز رباط ترک استان مرکزی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس تهران، تهران، ایران

2 گروه برنامه‌ریزی، مدیریت و آموزش محیط زیست، دانشکده محیط زیست دانشگاه تهران، تهران، ایران

3 گروه مرتع و آبخیزداری، دانشکده علوم کشاورزی و منابع طبیعی دانشگاه جیرفت، جیرفت، ایران

چکیده

فرسایش آبکندی یکی از اشکال فرسایشی است که موجب هدر رفت مقدار زیادی خاک می­گردد. بنابرین از این فرسایش می­توان به ­عنوان یکی از علل اصلی تخریب زمین و محیط زیست نام برد. این تحقیق با هدف پهنه­بندی حساسیت فرسایش آبکندی با استفاده از مدل­های داده­کاوی، مدل خطی تعمیم یافته (GLM) و شبکه عصبی مصنوعی (ANN) در حوزه آبخیز رباط ترک انجام شد. مناطق دارای فرسایش آبکندی طی بازدیدهای میدانی شناسایی و تعداد 242 نقطه فرسایشی انتخاب گردید. 12 متغیر محیطی موثر در فرسایش آبکندی، نقشه رقومی ارتفاع، درجه شیب، جهت شیب، شکل شیب، شاخص همگرایی، فاصله از رودخانه، تراکم زهکشی، فاصله از جاده، سنگ­شناسی، کاربری اراضی، شاخص اختلاف پوشش گیاهی نرمال شده (NDVI) و نقشه هم باران به منظور مدل­سازی حساسیت فرسایش آبکندی مورد استفاده قرار گرفتند. به منظور ارزیابی و اعتبارسنجی مدل­های مورد استفاده از معیارهای ROC، TSS و Kappa استفاده شد. نتایج حاصل از ارزیابی مدل نشان داد که مدل­ GLM با مقدار ROC، Kappa و TSS به ترتیب 89/0، 7/0 و 7/0 و مدل ANN با ROC، Kappa و TSS به ترتیب 88/0، 7/0 و 7/0 کارایی خیلی خوبی در مدل­سازی مناطق حساس به فرسایش آبکندی دارند. همچنین بررسی کلی مدل­های مورد استفاده براساس شاخص­های ذکر شده نشان داد که مدل GLM دارای کارایی مناسب­تری نسبت به مدل ANN در منطقه مورد مطالعه دارد. نتایج حاصل از پهنه­بندی حساسیت فرسایش آبکندی در منطقه مورد مطالعه نشان داد که مناطق مرکزی حوزه دارای حساسیت خیلی زیاد و زیاد نسبت به فرسایش آبکندی می­باشد.

کلیدواژه‌ها

عنوان مقاله [English]

Evaluating the Capability of Various Types of Geomorphological facies in supplying dust sources in the west of Khozestan province- Iran

نویسندگان [English]

  • ُSaeid Janizadeh 1
  • َAhmad Nohegar 2
  • Mohammadtaghi Avand 1
  • Mojtaba Dolat Kordestani 3
1 Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modares University of Tehran, Tehran, Iran
2 Tehran university
3 Department of Combat desertification, Faculty of Range and Watershed, Jiroft university, Jiroft, Iran.
چکیده [English]

Introduction
Soil erosion is a problem for agriculture in arid and semi-arid regions and is of great importance due to
its long-term effects on soil fertility and sustainable agriculture. Among the types of water erosion,
gully erosion is one of the most important events in soil erosion and land reclamation. Given that the
Markazi province is located in a region with arid and semi-arid climate, the intensity of rainfall is high
in some months of the year. Also because of the abandoned agricultural land in the study area, there is
much vegetation exposed to severe erosion which is conducive to erosion such as gutter erosion, so
serious attention is needed for this area. The data mining method extracts useful information from a
large volume of data and has shown good performance based on the literature review. Therefore, the
aim of the present study was to prioritize environmental factors affecting the occurrence of gully erosion
with data mining and statistical methods.
Materials and Methods
In order to conduct the present study and to map the distribution of gully erosion zones in the Robat
Turk watershed, 242 gully data were identified in the study area and used. A total of 242 points were
identified as non-flooded areas. In order to model the data, it was divided into two categories of training
and validation, with 70% of data used as training and 30% of data used as validation. Based on the
research background, hydrological, geological and physiographic factors including elevation, slope,
aspect, curvature, slope shape, distance from river, distance from road, lithology, land use, annual
precipitation and NDVI, variables were selected for modeling. In order to model the gully erosion,
artificial neural network (ANN) and generalize linear model (GLM) models were used, and the ROC
and Kappa, TSS coefficient were used to determine the accuracy of the gully erosion susceptibility map.
Results and Discussion
The results of gully erosion susceptibility showed that the central areas of the watershed are highly
sensitive to erosion. Considering that most of the lands in the central part of the watershed are bare land
and agricultural, the study of the gully erosion susceptibility map showed that the most sensitive and
highly sensitive erosion susceptibility area was formed in the bare land.
erosion, it should be stated that altitude class of 1800-2000 meters and slope class of 0-12% had the
highest contribution to erosion susceptibility in the study area. This may be due to the higher soil
compactness of these classes than other classes, which increases the likelihood of water infiltration into
the soil and the possibility of material dissolution and piping. Validation results showed that GLM and
ANN with ROC of 0.89 and 0.88 have very good performance regarding gully erosion susceptibility in
the study area.
Conclusion
Gully erosion is one of the erosion processes that widely affects the appearance of the earth. In this
study, GLM and ANN were used to evaluate the impact of environmental variables on gully erosion as
well as to identify potential areas for gully erosion. For this purpose, 12 variables and 242 gully erosion
points were used. ROC, TSS and KAPPA statistics were used to evaluate the models. The results of
evaluation and validation of the models used showed that both models have good performance in zoning
susceptibility to gully erosion. Identification and prediction of gully erosion susceptible areas can
reduce the damaging effects of this type of erosion and prevent its further development and can be of
considerable help to the people of the study area. Given that most of the gutters were created in the
central part of the study area near the village of Robat Turk, protective measures should be increased in
these areas to prevent the spread of agriculture and residential areas to erosive areas.

کلیدواژه‌ها [English]

  • Gully erosion
  • Data mining models
  • ROC curve
  • Rabat Turk watershed

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