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تعیین رابطه بین متغیرهای حدی دما با فراوانی گردو غبارزیستمحیطی و ارزیابی بهترین مدل پیشبینی شاخص FDSD در غرب کشور | ||
تحقیقات آب و خاک ایران | ||
دوره 53، شماره 5، مرداد 1401، صفحه 1093-1109 اصل مقاله (2.03 M) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijswr.2022.342666.669261 | ||
نویسندگان | ||
هانیه محمدی1؛ جواد بذرافشان* 2 | ||
1گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج. | ||
2دانشیار گروه مهندسی آبیاری و آبادانی، پردیس کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران. | ||
چکیده | ||
گرد و غبار همواره به عنوان یکی از مهمترین مخاطرات محیطی مطرح بوده و پیامدهای زیستمحیطی نامطلوبی را برجای میگذارد. هدف از این پژوهش، بررسی رابطهی متغیرهای حدی دمایی با طوفانهای گرد و غبار و ارزیابی بهترین مدل جهت پیشبینی شاخص FDSD در غرب کشور میباشد. با استفاده از دادههای ساعتی قدرت دید افقی، کدهای سازمان جهانی هواشناسی، نمایههای حدی دمایی شامل دمای بیشینه (T) و دمای کمینه () در مقیاس ماهانه برای 14 ایستگاه هواشناسی واقع در غرب کشور با طول دورۀ آماری 25 ساله (2014-1990) و ضرایب همبستگی تاو-کندال و پیرسون به ارتباط سنجی پرداخته شد. نقشه ضرایب همبستگی برای نمایش بهتر نتایج به روش اسپلاین (روش شعاع پایه) در نرمافزار ArcGIS تهیه گردید. همچنین سه مدل هوش مصنوعی شامل الگوریتم بهترین همسایگی (KNN)، برنامهریزی بیان ژن (GEP) و شبکه بیزین (BN) جهت پیشبینی گرد و غبار مورد ارزیابی قرار گرفتند. نتایج نشان داد که طوفانهای گرد و غباری همبستگی مثبت و معنیداری با نمایههای حدی دمایی در 14 ایستگاه مورد مطالعه دارند به نحوی که بالاترین ضریب همبستگی تاو-کندال با شاخص FDSD مربوط به متغیر بیشینه دما در ایستگاه دو گنبدان با مقدار 202/0 و دمای کمینه در ایستگاه سر پل ذهاب با مقدار 242/0 بود. همچنین بالاترین ضریب همبستگی پیرسون با شاخص FDSD نیز برای متغیر بیشینه دما در ایستگاه دوگنبدان با مقدار 415/0 و دمای کمینه در ایستگاه اسلام آباد با مقدار 211/0 بود. همچنین نتایج پیشبینی حاکی از عملکرد مناسب روش KNNمیباشد که در 13 ایستگاه رتبه نخست را به خود اختصاص داده است و در ایستگاه اسلامآباد روش BN بهترین عملکرد را داشته است. نتایج نشان داد که این مطالعه میتواند به درک صحیح وقوع طوفانهای گرد و غبار و بررسی روابط اقلیمی و همچنین کاهش خسارات ناشی از این پدیده در منطقه مورد مطالعه کمک شایانی کند. | ||
کلیدواژهها | ||
متغیرهای حدی دما؛ همبستگی تاو-کندال؛ پیش بینی؛ الگوریتم بهترین همسایگی؛ شبکه بیزین | ||
عنوان مقاله [English] | ||
Determining the relationship between temperature extreme variables and the frequency of environmental dust and evaluating the best model for predicting the FDSD index in the west of the country | ||
نویسندگان [English] | ||
Haniyeh Mohammadi1؛ Javad Bazrafshan2 | ||
1Irrigation and Development Engineering Department, College of Agriculture and Natural Resources, University of Tehran, Karaj. | ||
2Associate Professor, Department of Irrigation and Development Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. | ||
چکیده [English] | ||
Dust has always been one of the most important environmental hazards and has adverse environmental consequences. The purpose of this study is to investigate the relationship between temperature extreme variables and dust storms and evaluate the best model for predicting the FDSD index in the west of the country. We used hourly visibility data, World Meteorological Organization codes and temperature extreme indices including maximum temperature (TXx) and minimum temperature (TNn) on a monthly basis for 14 meteorological stations located in the west of the country with a statistical period of 25 years (1990-2014) and correlation between them were considered using Tau-Kendall and Pearson correlation coefficients. Map of correlation coefficients to better display the results was prepared by spline method (base radius method) in ArcGIS software. Also, three artificial intelligence models including best neighbor algorithm (KNN), gene expression programming (GEP) and Bayesian network (BN) were evaluated to predict dust. The results showed that dust storms have a positive and significant correlation with temperature extreme indices in 14 studied stations, so that the highest Tau-Kendall correlation coefficient with FDSD index is related to the maximum temperature variable in Dogonbadan station with a value of 0.202 and with the minimum temperature at Sare-Pole-Zahab station with the correlation coefficient 0.242. Also, the highest Pearson correlation coefficient with FDSD index for the maximum temperature variable in Dogonbadan station was 0.415 and that of the minimum temperature in Islamabad station 0.211. Also, the results of the forecast indicated the proper performance of the KNN method, which is ranked first in 13 stations and the BN method had the best performance in Islamabad station. The results of this study can help to better understand the occurrence of dust storms and to studying their climatic relations, as well as to reducing the damage caused by this phenomenon in the study area. | ||
کلیدواژهها [English] | ||
Temperature limit variables, Tau Kendall correlation, Forecast, Best Neighborhood Algorithm, Bayesn Network | ||
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