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ارزیابی روشهای یادگیری نظارتی هوشمند و سطح پاسخ برای بهینهسازی عوامل مؤثر بر فرسایش خاک (مطالعهی موردی حوزه آبخیز امامزاده عبدالله باغملک) | ||
تحقیقات آب و خاک ایران | ||
مقاله 4، دوره 51، شماره 7، مهر 1399، صفحه 1653-1666 اصل مقاله (964.44 K) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijswr.2020.296715.668485 | ||
نویسندگان | ||
مجتبی شیرازی1؛ عطااله خادم الرسول* 2؛ سید محمد صفی الدین اردبیلی3 | ||
1دانشگاه شهید چمران اهواز | ||
2استادیار گروه خاکشناسی، دانشکده کشاورزی، دانشگاه شهید چمران اهواز، ایران | ||
3مهندسی بیوسیستم، دانشکده کشاورزی، دانشگاه شهید چمران اهواز | ||
چکیده | ||
ارزیابی عوامل مؤثر بر کنترل فرسایش خاک در قالب شیوههای مدیریتی از اهمیت شایانی برخوردار است. در این پژوهش تأثیرات شیوههای مدیریتی غیر سازهای شامل قرق و اصلاح پوشش گیاهی توسط مدل WEPP در حوزه آبخیز امامزاده عبدالله باغملک واقع در شمال شرقی استان خوزستان، شبیهسازی شد. بهینهسازی متغیرهای فیزیکی و هیدرولیکی مؤثر بر فرسایش شامل بافت خاک و اجزاء معادله ونگنوختن توسط روشهای سطح پاسخ (RSM)، جنگل تصادفی (RF)، ماشین بردار پشتیبان (SVM) و شبکهی عصبی مصنوعی (ANN) صورت پذیرفت. همچنین مقدار فرسایش خاک قبل از اعمال شیوههای مدیریتی بهعنوان پاسخ اول (R1) و مقدار فرسایش خاک پس از اعمال شیوههای مدیریتی تحت عنوان پاسخ دوم (R2) تعریف شد. نتایج بهینهسازی توسط نرمافزار Orange شامل روشهای جنگل تصادفی، ماشین بردار پشتیبان و شبکه عصبی مصنوعی نشان داد که روش جنگل تصادفی با MSE، RMSE و R2 به ترتیب برابر 991/0، 995/0 و 963/0 برای پاسخ اول و برای پاسخ دوم به ترتیب برابر 095/0، 307/0 و 974/0، بهعنوان مناسبترین روش است. همچنین بهینهسازی به روش سطح پاسخ با نتایج آماری MSE، RMSE و R2 برای پاسخ اول به ترتیب 7/28، 37/5 و 999/0 و برای پاسخ دوم به ترتیب برابر 16/4، 03/2 و 998/0، مناسبترین روش محسوب میشود. در مجموع استفاده از روشهای بهینهسازی، ابزاری مناسب برای ارزیابی شیوههای مدیریتی و در نهایت انتخاب بهترین آنها در مناطق بحرانی میباشد. متناسب بودن شیوههای مدیریتی بر پایهی شرایط بهینه، منجر به کاهش هدررفت منابع آب و خاک میشود. | ||
کلیدواژهها | ||
فرسایش خاک؛ روش سطح پاسخ؛ ماشین بردار؛ جنگل تصادفی؛ سناریوهای مدیریتی | ||
عنوان مقاله [English] | ||
Evaluation of Different Supervised Learning Smart Methods and Response Surface Method to Optimize Factors Affecting Erosion (Case Study: Emamzadeh Watershed of Baghmalek) | ||
نویسندگان [English] | ||
mojtaba shirazi1؛ Ataallah Khademalrasoul2؛ Seyyed Mohammad Safieddin Ardebili3 | ||
1shahid chamran university of ahvaz | ||
3Department of Biosystem Faculty of Agriculture Shahid Chamran University of Ahvaz | ||
چکیده [English] | ||
Evaluation of soil erosion control factors is important regarding the application of management practices. In this study, the effects of non-structural management practices including revision of crop cover (RC) and exclosure (EX) were simulated using WEPP model in Emamzadeh Abdullah watershed of Baghmalek, located in the northeast of Khuzestan Province. Optimization of physical and hydraulic parameters affecting erosion including soil texture and components of the Van Genuchten equation was performed using response surface methodology (RSM), random forest (RF), support vector machine (SVM) and artificial neural network (ANN). Also, the soil erosion rate before and after management practices was defined as the first response (R1) and the second response (R2), respectively. Optimization results by Orange software including random forest methods, support vector machine and artificial neural network showed that the random forest method with MSE, RMSE and R2 equal to 0.991, 0.995 and 0.963 respectively, for the first response and equal to 0.095, 0.307 and 0.974 respectively, for the second response is the most proper method. Also, optimization by response surface method is the most appropriate method with MSE, RMSE and R2 equal to 28.7, 5.37 and 0.999 respectively, for the first response and equal to 4.16, 2.03 and 0.998 respectively, for the second response. Generally, using optimization techniques is a convenient method for evaluating management practices and finally selecting the best one for critical areas. Appropriate management practices based on optimal conditions leading to water and soil loss reduction. | ||
کلیدواژهها [English] | ||
Soil erosion, Response surface methodology, Support vector machines, Random forest, Management scenarios | ||
مراجع | ||
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