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آریایی, آرزو, شرافتی, احمد. (1403). پایش خشکسالی مبتنی بر داده‌های سنجش از دور شهر تهران بر اساس SPI ناپارامتریک. , 14(4), 969-988. doi: 10.22059/jwim.2024.378794.1171
آرزو آریایی; احمد شرافتی. "پایش خشکسالی مبتنی بر داده‌های سنجش از دور شهر تهران بر اساس SPI ناپارامتریک". , 14, 4, 1403, 969-988. doi: 10.22059/jwim.2024.378794.1171
آریایی, آرزو, شرافتی, احمد. (1403). 'پایش خشکسالی مبتنی بر داده‌های سنجش از دور شهر تهران بر اساس SPI ناپارامتریک', , 14(4), pp. 969-988. doi: 10.22059/jwim.2024.378794.1171
آریایی, آرزو, شرافتی, احمد. پایش خشکسالی مبتنی بر داده‌های سنجش از دور شهر تهران بر اساس SPI ناپارامتریک. , 1403; 14(4): 969-988. doi: 10.22059/jwim.2024.378794.1171

پایش خشکسالی مبتنی بر داده‌های سنجش از دور شهر تهران بر اساس SPI ناپارامتریک

مدیریت آب و آبیاری
دوره 14، شماره 4، اسفند 1403، صفحه 969-988    اصل مقاله (1.69 M)
نوع مقاله: مقاله پژوهشی
شناسه دیجیتال (DOI): 10.22059/jwim.2024.378794.1171
نویسندگان
آرزو آریایی1؛ احمد شرافتی* 2
1دانشکده مهندسی عمران، واحد غرب تهران، دانشگاه آزاد اسلامی، تهران، ایران.
2دانشکده مهندسی عمران، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.
چکیده
امروزه پدیده خشک‌سالی یک رخداد مخاطره­آمیز در مناطق مختلف جهان از جمله ایران به‌شمار می­رود. مدیریت این پدیده، لزوم پایش خشک‌سالی و استفاده از ابزارهای سنجش از دور را به‌منظور تعیین شدت و زمان خشک‌سالی ایجاب می­کند. در مطالعه حاضر، خشک‌سالی محدوده مطالعاتی شهر تهران براساس داده‌های بارش مشاهداتی و سنجش از دور تعیین گردیده است. در این راستا، تولیدات بارش ماهواره TRMM در بازه سال­های ۱۹۹۸ تا 2019 با استفاده از ابزار کدنویسی در Google Earth Engine استخراج شد. سپس خشک‌سالی منطقه براساس شاخص استاندارد شده بارش (SPI) ناپارامتریک و داده‌های بارش مشاهداتی و سنجش­ از ­دور برای مقیاس­های زمانی سه، شش و 12 ماهه پایش گردید. در این زمینه، ارتباط میان بارش ماهواره­ای و مشاهداتی با استفاده از روش بوت‌استرپ محاسبه و تحلیل شد. سپس، با استفاده از دو معیار RMSE و NS خطای برآورد بارش و خشک‌سالی محاسبه‌شده براساس تولیدات ماهواره TRMM تعیین گردید. نتایج اعتبارسنجی نشان دادند SPI محاسباتی براساس داده‌های بارش TRMM در مقیاس شش­ماهه دارای خطای کم‌تری می­باشد. با توجه به یافته‌ها، مقادیر RMSE و NS در برآورد خشک‌سالی شش­ماهه به‌ترتیب برابر 873/0 و 028/0 است. به­علاوه، به­منظور بررسی دقیق­تر محصولات بارش ماهواره TRMM و داده‌های بارش اندازه­گیری‌شده، با استفاده از روش­های آماری اسپیرمن، کندال، دو رشته‌ای نقطه‌ای و پیرسن، همبستگی میان خشک‌سالی زمینی و ماهواره­ای در مقیاس­های مختلف برآورد شد. نتایج نشان دادند با افزایش مقیاس زمانی تخمین خشک‌سالی هواشناسی، همبستگی بین داده‌های ماهواره­ای و زمینی افزایش می­یابد.
کلیدواژه‌ها
خشک‌سالی؛ سنجش از دور؛ ماهواره TRMM؛ همبستگی
عنوان مقاله [English]
Remote sensing-Based drought monitoring in Tehran city using nonparametric SPI
نویسندگان [English]
Arezoo Ariyaei1؛ ahmad sharafati2
1Department of Civil Engineering, West Tehran Branch, Islamic Azad University, Tehran, Iran.
2Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
چکیده [English]
Today, drought is considered a dangerous phenomenon in various regions of the world, including Iran. This fact necessitates drought monitoring and the use of remote sensing tools to determine the intensity and duration of drought. In the current study, drought in the study area of Tehran city was determined based on observational and remote sensing rainfall data. For this purpose, TRMM satellite precipitation products were extracted between 1998 and 2019 using the coding tool in Google Earth Engine. Then, the drought of the region was monitored based on the non-parametric standardized precipitation index (SPI) and observational and remote sensing precipitation data for 3, 6, and 12 months' time scales. In this context, the relationship between satellite precipitation and observations was determined using the bootstrap method. Also, to deeply examine the TRMM satellite precipitation and the measured precipitation data, the correlation between observed and satellite drought in the different time scales was estimated using Spearman, Kendall, Point-biserial and Pearson statistical methods. Finally, using RMSE and NS, the error in estimating rainfall and drought based on TRMM satellite products was calculated. Validation results showed that the calculated SPI based on TRMM rainfall data on a 6-month scale had less error. According to the findings, the RMSE and NS values for the 6-month drought estimation were 0.873 and 0.028, respectively. Additionally, the results showed that the drought in the study area between 1998 and 2019 exhibited an increasing trend.
کلیدواژه‌ها [English]
Correlation, Drought, Remote Sensing, TRMM
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آمار
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