مقایسه عملکرد مدل‌های رگرسیون فازی با روش پنمن-مانتیث در برآورد تبخیر و تعرق ماهانه گیاه مرجع در دشت نیشابور

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش‌آموخته کارشناسی ارشد، گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران

2 دانشیار، گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران

3 استاد، گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران

چکیده

در پژوهش حاضر از رهیافت­های رگرسیون فازی به‌منظور برآورد مقادیر تبخیر-تعرق گیاه مرجع در دشت نیشابور بهره گرفته شد. داده­ها شامل دمای حداکثر (Tmax)، دمای حداقل (Tmin)، دمای متوسط هوا (Tmean)، رطوبت نسبی (RH)، ساعات آفتابی (Rs) و سرعت باد در m 2 از سطح زمین (U2) بود. داده­های مورداستفاده از ایستگاه هواشناسی سینوپتیک نیشابور اخذ شده و برای هریک از مدل­های رگرسیون امکانی و کم­ترین مربعات فازی، 3 سناریو مختلف جهت برآورد تبخیر و تعرق گیاه مرجع طراحی شد. برای ارزیابی عملکرد مدل­های رگرسیون فازی در مقایسه با روش استاندارد پنمن-مانتیث از ضریب تبیین، میانگین مربعات خطا و خطای مطلق میانگین استفاده شد. نتایج نشان داد مدل رگرسیون امکانی فازی در ماه دی و مدل رگرسیون کم­ترین مربعات فازی در ماه مهر با ضریب تبیین به­ترتیب 903/0 و 502/0 بیش­ترین و کم‌ترین دقت را داشت. در بین مدل­های پیشنهادی جدید، اگرچه مدل رگرسیون امکانی فازی تحت سناریو شماره 1 بالاترین دقت را داشته، اما در هر دو مدل رگرسیون فازی، سناریو 2 علی­رغم دارا بودن پارامترهای ورودی کمتر (Tmin، RH و Rs)، دقت قابل‌مقایسه‌ای با سایر سناریوها دارد و لذا می­توان استفاده از آن را در شرایط کمبود داده به‌عنوان رویکرد بهینه در تعیین ETo برای برنامه‌ریزی آبیاری و مدیریت منابع آب پیشنهاد نمود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Efficiency Comparison of Fuzzy Regression Models with the Penman-Monteith Method in Estimating of Monthly Reference Evapotranspiration of Neyshabour Plain

نویسندگان [English]

  • Sepide Zeraati Neyshabouri 1
  • Mohsen Pourreza Bilondi 2
  • Abbas Khashei-Siuki 3
  • Ali Shahidi 2
1 M.Sc. Alumni, Department of Water Resource Management, Faculty of Agriculture, University of Birjand, Birjand, Iran
2 Assoc. Professor, Department of Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran
3 Professor, Department of Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran
چکیده [English]

In this study, fuzzy linear and fuzzy least-squres regression approach was employed to estimate the monthly reference evapotranspiration of Neyshabour plain. The data used, including maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tmean), relative humidity (RH), solar radiation (Rs) and wind speed (U2), were obtained from synaptic meteorological station of Neyshabour. Three different scenarios were designed to estimate the evapotranspiration for either fuzzy linear or fuzzy least-squres regression models. Mean absolute error (MAE), root mean square error (RMSE), and the coefficient of determination (R2) were used to evaluate the performance fuzzy regression models and its comparison with FAO-56 Penman-Monteith. Results indicated that the fuzzy linear regression model in January and the fuzzy least squares regression model in October had the highest and lowest accuracy with R2 of 0.903 and 0.502, respectively. Among the new proposed models, the fuzzy linear regression under scenario FLR1 (Inputs included Tmax, Tmin, RH and U2) had the highest accuracy, however, in both regression models, despite having lower input parameters (Tmean, RH and Rs), the second scenario, was comparable with other and therefore it can be used in data deficit conditions as an optimal approach in determining ETo for irrigation planning and water resource management.

کلیدواژه‌ها [English]

  • Efficiency
  • evapotranspiration
  • neyshabour plain
  • modelling
  • Regression
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دوره 8، شماره 1
فروردین 1401
صفحه 205-217
  • تاریخ دریافت: 05 اردیبهشت 1400
  • تاریخ بازنگری: 10 مرداد 1400
  • تاریخ پذیرش: 11 مرداد 1400
  • تاریخ اولین انتشار: 11 مرداد 1400