ارزیابی میزان بهره‌وری آب کشاورزی با استفاده از تصاویر ماهواره‎ای و مدلWATPRO مطالعه موردی: اراضی تحت کشت گندم حوضه آبخیز دشت جیرفت

نوع مقاله: مقاله پژوهشی

نویسندگان

1 عضو هیات علمی گروه سنجش از دور و GIS ، دانشکده جغرافیا، دانشگاه تهران

2 گروه سنجش از دور و جی آی اس، دانشکده جغرافیا، دانشگاه تهران، ایران

3 گروه سنجش از دور و جی آی ای، دانشکده جغرافیا، دانشگاه تهران

4 مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی جنوب استان کرمان، سازمان تحقیقات، آموزش و ترویج کشاورزی، جیرفت، ایران

چکیده

در سال‌های اخیر تغییرات اقلیمی و افزایش تقاضای جهانی آب بدلیل رشد جمعیت، منابع آبی را با کمبود و مشکلات جدی مواجه ساخته است. در این میان محاسبه میزان بهره‌وری آب کشاورزی در راستای مدیریت بهینه منابع آب و کاهش مصرف بسیار ضروری می‌باشد،که در این راستا یکی از روش‌های پرکاربرد استفاده از داده‌های سنجش از دور می‌باشد. بنابراین در پژوهش حاضر اقدام به استفاده از مدل کاربردی و کاملا مبتنی بر داده های ماهواره‌ای تحت عنوان WATPRO جهت محاسبه مستقیم میزان بهره‌وری آب کشاورزی و ارزیابی آن در حوضه آبخیز دشت جیرفت استان کرمان گردید. بدین منظور تصایر ماهواره‌ای لندست 8 در دوره کشت تا برداشت گندم در سال زراعی (1395-1396) دریافت و پس از انجام پیش پردازش‌های لازم اقدام به اجرای مدل WATPRO گردید. زمان استقرار، اوج توسعه و برداشت محصول از طریق سری زمانی NDVI در 6 منطقه تقسیم‌بندی شده، مشخص شد، و بهره‌وری آب گندم محاسبه و نتایج با نقاط کنترل زمینی ارزیابی گردید. نتایج این پژوهش نشان داد که بیشترین، کمترین و میزان میانگین بهره‌وری به‌ترتیب kg m-3 8/0 و 4/0 و 5/0 بوده است. همچنین ضریب همبستگی 5/76 درصد در بررسی رابطه بین میانگین NDVI و بهره‌وری آب بدست آمد. در ارزیابی دقت مدل، مقادیر RMSE و ضریب همبستگی بین بهره‌وری محاسبه شده و مشاهدات زمینی، به‌ترتیب برابر با kg m-3 16/0 و 85 درصد شد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Assessing the water productivity using remote sensing data and WATPRO model, Case study of wheat lands of the Jiroft plain

نویسندگان [English]

  • Saeid Hamzeh 1
  • Seyed Karim Afshary Pour 2
  • Seyed Kazem alavipanah 3
  • Esmaeil moghbeliDameneh 4
1 Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran
2 Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran
3 Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran
4 Agricultural Engineering Research Department, South Kerman Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Jiroft, Iran
چکیده [English]

In recent years, climate change and rising global water demand as a result of population growth has caused water scarcity. In this regard, calculation of agricultural water productivity in order to optimize the management of water resources and reduce the water consumption is essential. One of the promising methods for this purpose is remote sensing. In this research, a functional and fully satellite-based model that called WATPRO was used for direct calculation of agricultural water productivity and its evaluation in the Jiroft plain located in Kerman province. For this aim, Landsat8 satellite imagery were acquired during the growing season of wheat on 2016-2017 years and after necessary image preprocessing, the WATPRO model was implemented. The deployment peak, cultivation and harvesting time for six divided field were determined by using the time series of Normalized Deference Vegetation Index (NDVI) extracted from satellite imagery, then wheat water productivity was calculated and the results were evaluated with ground control points. The results shows that the highest and lowest water productivity for wheat in this area is 0.4 and 0.8 kg m-3, respectively and the average of water productivity in the study area was estimated around 0.5 kg m-3. Also the correlation coefficient of 76.5% was found between average NDVI and water productivity in this area. Assessing the accuracy of the WATPRO model with the measured water productivity at field show that this model perform well for estimation and mapping water productivity with an RMSE and correlation coefficient of 0.16 kgm-3 and 85% respectively.

کلیدواژه‌ها [English]

  • Remote Sensing
  • Water productivity
  • WATPRO Model
  • Wheat
  • Jiroft plain
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