ارزیابی تفکیک مکانی مدل‌های رقومی ارتفاعی بر دقت برآورد بارش در مقیاس سالانه

نوع مقاله : پژوهشی

نویسندگان

1 دانش آموخته‌ی دکتری علوم و مهندسی آبخیزداری، دانشکده‌ی منابع‌طبیعی، دانشگاه تهران، ایران

2 دانشیار دانشکده ی منابع‌طبیعی، دانشگاه تهران، ایران

3 استاد دانشکده ی منابع‌طبیعی، دانشگاه تهران، ایران

4 استادیار مرکز تحقیقات و آموزش کشاورزی و منابع‌طبیعی استان آذربایجان‌ غربی، سازمان تحقیقات، آموزش و ترویج کشاورزی، ارومیه، ایران

چکیده

مقدمه و هدف
کاربران با بهره‌گیری از ایستگاه‌های باران‌سنجی داده‌های دقیقی از اندازه‌ی بارندگی را تهیه می‌کنند. با این ‌حال، درون‌یابی داده‌های بارندگی به‌دلیل تغییرپذیری زمانی و مکانی دشوار است. ازاین‌رو ایستگاه‌های باران‌سنجی در بسیاری از مناطق پراکندگی مناسبی ندارند و این مشکل نیز در مناطق کوهستانی بیش‌تر است. در یک آبخیز کوهستانی، درک تعامل میان تفکیک‌پذیری مدل رقومی ارتفاعی (DEM) و متغیرهای آب و هوایی برای درون‌یابی دقیق مکانی میانگین بارندگی در بسیاری از مناطق ضروری است و از سوی دیگر نیاز به اطلاعات دقیقی در مدل‌سازی آب‌شناختی و بسیاری از بررسی‌های محیط‌زیستی و اقلیمی است. بر این اساس یکی از مشکلاتی که در بسیاری از مطالعات آب‌شناسی وجود دارد و همیشه بدون توجه به آن نقشه‌های بارشی تهیه می‌شود، تهیه‌ی نقشه‌ی بارش با استفاده از درون‌یابی و یا استفاده از مدل‌های رقومی ارتفاعی در دسترس است، که دارای خطای بارش برآوردی است.
مواد و روش‌ها
در این پژوهش به‌منظور معرفی بهترین مدل رقوم ارتفاعی برای کاربران در تهیه‌ی نقشه‌ی شیب بارش از داده‌های 11 ایستگاه هواشناسی در استان کرمانشاه و چهار مدل رقومی ارتفاعی (DEM) با تفکیک مکانی 30، 90، 1000 و 10000 متر که متداول‌ترین مدل‌های رقومی ارتفاعی در پژوهش‌ها هستند، استفاده شد. با استفاده از مدل وایازی خطی برازش داده‌شده میان بلندی هر ایستگاه و میانگین بارش 20 ساله، نقشه‌ی بارش سالانه برای استان کرمانشاه تهیه شد و سپس بر اساس معیارهای ارزیابی خطا بهترین مدل رقومی ارتفاعی در برآورد بارش مشخص شد.
نتایج
نتایج این پژوهش نشان داد که در برآرود بارش مدل‌های رقومی ارتفاعی با اندازه‌ی سلولی 1000 و 10000 متر (R2 = 0.76, 0.81) در مقایسه با DEMهای با دقت مکانی 30 و 90 متری (R2= 0.75) دقت بیشتری داشتند. در بررسی ضریب نش - ساتکلیف (NS) مشخص شد که DEM با تفکیک مکانی 1000 متر (یک کیلومتر) با ضریب نشساتکلیف 0/76، سطح معنی‌داری 0/01 و ضریب همبستگی 0/81 در مقایسه با دیگر مدل‌های رقومی ارتفاعی دقت بیشتری داشت.
نتیجه‌گیری و پیشنهادها
نتایج این پژوهش می‌تواند در برآرود و تعمیم بارش در مناطق فاقد ایستگاه و هم‌چنین در تهیه‌ی نقشه‌های بارشی در مناطقی که تعداد ایستگاه محدود است، استفاده شود. افزون بر این در روش‌های درون‌یابی تک‌متغیره که دقت مناسبی به‌دلیل در نظر نگرفتن فاصله‌های مکانی ندارند، استفاده شود. هم‌چنین با توجه به پستی‌بلندی پیچیده‌ی زمین و نبودن یکنواختی ایستگاه‌های هواشناسی در سطح کره‌ی زمین، برای برآورد بارش به کارگیری مدل‌های رقوی ارتفاعی با قدرت تفکیک مکانی زیادتر نیاز است که با حذف سطوح پستی‌بلندی‌های خطاساز دقت برآورد مدل‌های رقومی در ارزیابی پژوهش‌های بارش افزایش خواهد یافت.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Evaluating the Spatial Resolution of Digital Elevation Models (DEMs) on the Accuracy of Rainfall Estimation at the Annual Scale

نویسندگان [English]

  • Morteza Gheysouri 1
  • Shahram Khalighi Sigaroodi 2
  • Ali Salajegheh 3
  • Bahram Choubin 4
1 Ph.D. of Watershed Management, Faculty of Natural Resources, University of Tehran, Iran
2 Associate Professor, Faculty of Natural Resources, University of Tehran, Iran
3 Professor, Faculty of Natural Resources, University of Tehran, Iran
4 Assistant Professor, Soil Conservation and Watershed Management Research Department, West Azarbaijan Agricultural and Natural Resources Research and Education Center (AREEO), Urmia, Iran
چکیده [English]

Introduction and Goal
Users prepare accurate data of the amount of rainfall by using rain gauge stations. However, an interpolation of rainfall data is difficult due to temporal and spatial variability. Therefore, rain gauge stations are not well distributed in many areas, especially in mountainous areas. In a mountainous area, understanding the interaction between the resolution of the Digital Elevation Model (DEM) and climate variables is necessary for accurate spatial interpolation of average rainfall in many areas, and on the other hand, the need for accurate information in hydrological modeling and many environmental studies and it is climatic. One of the problems that exists in many hydrological studies is that rainfall maps are always prepared using interpolation or available DEM, regardless of rainfall, which have an estimated rainfall error.
Materials and Methods
In this study, four DEMs with spatial resolutions of 30, 90, 1000, and 10000 m, which are the most common DEMs in studies, were used to introduce the best elevation digital model for extracting the rainfall gradient map from the data of 11 meteorological stations in Kermanshah province. A rainfall map for Kermanshah province was prepared using a linear regression model fitted between the height of each station and the 20-year average rainfall. The best DEM for rainfall estimation was then determined on the basis of error evaluation criteria.
Results
The results of this research showed that in estimating rainfall, DEMs with cell sizes of 1000 and 10000 m (R2 = 0.76, 0.81) were more accurate than DEMs with spatial accuracy of 30 and 90 m (R2 = 0.75). In the examination of the Nash–Sutcliffe coefficient (NS), compared to other digital height models of accuracy, DEM with a spatial resolution of 1000 m (one km) with a Nash–Sutcliffe coefficient of 0.76, a significance level of 0.01, and a correlation coefficient of 0.81 was found to have greater accuracy.
Conclusion and Suggestions
The results of the present study can be used to estimate and generalize rainfall in areas that do not have stations and to prepare rainfall maps in areas where the number of stations is limited. In addition, it should be used in univariate interpolation methods that do not have proper accuracy because spatial distances are not considered. In addition, due to the complex topography of the earth and the non-uniformity of meteorological stations on the earth’s surface, high-resolution models with higher spatial resolution are required for the estimation of rainfall, which increases the accuracy of digital models in the evaluation of rainfall studies by removing topographical levels that cause errors.

کلیدواژه‌ها [English]

  • DEM resolution
  • Kermanshah province
  • linear regression
  • mountainous watershed
  • rainfall estimation
  • rainfall gradient

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  • تاریخ دریافت: 08 اسفند 1401
  • تاریخ بازنگری: 21 اردیبهشت 1402
  • تاریخ پذیرش: 31 خرداد 1402

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