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تعیین وضعیت خشکسالی با استفاده از شاخص‌های سنجش از دور و خشکسالی هواشناسی و کشاورزی در مناطق با اقلیم مختلف | ||
| تحقیقات آب و خاک ایران | ||
| دوره 53، شماره 10، دی 1401، صفحه 2383-2398 اصل مقاله (2.11 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2022.348275.669352 | ||
| نویسندگان | ||
| سمیرا رهنما1؛ علی شهیدی* 1؛ مصطفی یعقوب زاده1؛ علی اکبر مهران2 | ||
| 1گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران | ||
| 2گروه مهندسی عمران و محیط زیست، دانشگاه ایالتی سن خوزه، سن خوزه، کالیفرنیا، آمریکا | ||
| چکیده | ||
| پایش مؤثر و به‌موقع خشکسالی می‌تواند به توسعه سامانه‌های خشکسالی و مدیریت بهینه منابع آبی کمک کند و این سامانه‌ها نیز به نوبه خود می‌توانند هزینه‌های ناشی از خشکسالی را به کمینه برسانند. هدف از این پژوهش، بررسی خشکسالی با استفاده از داده‌های ماهواره‌ای سنجنده لندست و شاخص‌های خشکسالی هواشناسی و کشاورزی در سه منطقه با شرایط اقلیمی متفاوت (بیرجند، شیراز و رشت) می‌باشد. بدین منظور شاخص‌های خشکسالی بر مبنای داده‌های ماهواره‌ای شامل شاخص تفاوت پوشش گیاهی نرمال شده (NDVI)، شاخص پوشش گیاهی تعدیل‌کننده اثرات خاک (SAVI) و شاخص پوشش گیاهی نسبت ساده (SR) از روی تصاویر لندست برای دوره زمانی 2002، 2014 تا 2020 استخراج شد. سپس نتایج این شاخص‌ها با مقادیر شاخص بارش استاندارد (SPI) و شاخص شناسایی خشکسالی (RDI) مقایسه گردید. بررسی شاخص‌ها حاکی از بالا بودن مقدار شاخص‌ها در تمامی سال‌های مورد بررسی در منطقه رشت می‌باشد. در منطقه شیراز کاهش قابل توجهی در مقدار میانگین شاخص‌ها در ماه‌های August و September سال‌های 2015 تا 2020 اتفاق افتاد. همچنین این کاهش در مقدار میانگین شاخص‌ها در منطقه بیرجند از September سال 2002 تا 2020 دیده شد. از طرفی از میان ماه‌های مورد بررسی، ماه September سال 2015 در مناطق رشت و شیراز و سال 2014 (September) بیرجند بیشترین خشکسالی را از نظر شاخص‌های سنجش از دور داشته‌اند. نتایج نشان داد که در هر سه منطقه شاخص‌های سنجش از دور از جمله NDVI و SAVI همبستگی بالایی با شاخص‌های SPI و RDI دارند. با این تفاوت که شاخص RDI برای پایش و پیش‌بینی خشکسالی، بر شاخص SPI برتری دارد. در نتیجه، شاخص RDI علاوه بر مقدار بارندگی، تبخیرتعرق را نیز لحاظ می‌کند و از حساسیت بیشتری خصوصاً در مناطق خشک نظیر شیراز و بیرجند که مقدار تبخیرتعرق بیشتر از مقدار بارندگی می‌باشد، برخوردار است. | ||
| کلیدواژه‌ها | ||
| تصاویرلندست؛ شاخص‌های سنجش از دور؛ شاخص SPI؛ شاخص RDI؛ خشکسالی | ||
| عنوان مقاله [English] | ||
| Comparison of remote sensing indices and meteorological and agricultural drought index to determine drought status in regions with different climatic conditions | ||
| نویسندگان [English] | ||
| samira rahnama1؛ Ali Shahidi1؛ Mostafa Yaghoobzadeh1؛ Ali Akbar Mehran2 | ||
| 1P Department of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran | ||
| 2Department of Civil and Environmental Engineering, San Jose State University, San Jose, California, United States | ||
| چکیده [English] | ||
| Effective and timely drought monitoring can contribute to the development of drought systems and the optimal management of water resources using these systems in turn can minimize the costs of drought. The purpose of this study is to investigate the drought using Landsat satellite data and meteorological and agricultural drought indices in three regions with different climatic conditions (Birjand, Shiraz and Rasht). For this purpose, drought indices based on satellite data including Normalized Difference Vegetation Index (NDVI), Soil Adjustment Vegetation Index (SAVI) and Simple Ratio (SR) were extracted from Landsat images for the period 2002, 2014 to 2020. Then the results of these indices were compared with the values of standard precipitation index (SPI) and Reconnaissance Drought Index (RDI). The study of indicators shows that the amount of indicators is high in all studied years in Rasht region. In Shiraz region, a significant decrease in the average value of indicators occurred in August and September from 2015 to 2020. Also, this decrease was seen in the average value of indicators in Birjand region from September 2002 to 2020. On the other hand, among the studied months, September 2015 in Rasht and Shiraz regions and 2014 (September) Birjand had the most drought in terms of remote sensing indicators. The results showed that in all three regions, remote sensing indices including NDVI and SAVI have a high correlation with SPI and RDI indices. The RDI index is superior to the SPI index for drought monitoring and prediction. As a result, the RDI index takes into account evapotranspiration in addition to rainfall and is more sensitive especially in dry areas such as Shiraz and Birjand where evapotranspiration is higher than rainfall. | ||
| کلیدواژه‌ها [English] | ||
| Drought, Landsat images, Remote Sensing Indices, SPI Index, RDI Index | ||
| مراجع | ||
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