پایش تغییرات دینامیک زیر حوضه تالاب میانگران با استفاده از سامانه گوگل ارث انجین (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
تغییرات محیطی، از بحرانی ترین چالش های دستیابی به توسعه پایدار هستند. نظارت، مدیریت و کمک در تصمیم گیری و سیاست گذاری تغییرات آب های سطحی را با توجه به در دسترس بودن داده های ماهواره ای می توان انجام داد. سامانه ی گوگل ارث انجین شرایط مناسب پردازش تصاویر ماهواره ای برای پایش و تحلیل محیطی را ایجاد می کند. هدف از این پژوهش، پایش تغییرات دینامیک زیر حوضه تالاب میانگران در بازه زمانی (2022-2013) است. ساخت یک مدل هارمونیک به دلیل انعطاف پذیری آن در محاسبه چرخه ای با اشکال ساده و قابل تکرار در این پژوهش استفاده شد. سری زمانی هارمونیک پهنه ی آبی و پوشش گیاهی با استفاده از شاخص های NDWI و NDVI در بستر گوگل ارث انجین استخراج شد و آزمون روند من کندال برای آن ها در اکسل با افزونه XLSTAT محاسبه گردید. درنهایت از داده های جهانی آب برای تأیید و تکمیل نتایج تحلیل سری زمانی بهره گرفته شد. نتایج سری زمانی هارمونیک پهنه آبی روند کاهشی و منفی و تغییرات بیشتر در زیر حوضه را نشان داد. برای داده های مشاهده شده پوشش گیاهی بیانگر عدم وجود روند در سری زمانی هارمونیک بود. در مقایسه با نتایج و تجزیه و تحلیل پژوهش های دیگر به نظر می رسد دخالت های انسانی و تغییر کاربری ها می تواند علت عدم روند در زیر حوضه تالاب میانگران باشد. همچنین تغییر اقلیم و خشک سالی سهم عمده ای در تغییرات زیر حوضه تالاب میانگران داشته است. بررسی داده های جهانی آب نیز نشان داد که وقوع آب ازنظر مکانی- زمانی کاهشی و شدت تغییر وقوع آب در زیر حوضه ی تالاب میانگران بحرانی است. همچنین بیشترین تغییرات مربوط به حاشیه ی تالاب میانگران است. درنهایت تخصیص حق آبه، وضع قوانین و تعیین حد بستر محیط زیستی و استفاده از قابلیت های گوگل ارث انجین برای پایش تغییرات محیطی (کاربری، دما، بارش، تبخیر و...) زیر حوضه تالاب میانگران پیشنهاد شد.Monitoring the dynamic changes of Miangaran wetland sub-basin using Google Earth Engine system
IntroductionEnvironmental changes are one of the most critical challenges to achieving sustainable development. Wetlands are part of the earth's structure and as one of the important ecosystems consisting of water, vegetation, soil and microorganisms. Monitoring, management and assistance in decision-making and policy-making of surface water changes can be done according to the availability of satellite data. The availability of Landsat data helps a lot in preparing a high-quality map to show the land surface changes. Although remote sensing is superior to traditional methods in terms of time, speed, and cost, these methods require the use of powerful and practical systems that include complex analysis. The use of data and images on the web is a solution that can be used to solve the mentioned problem, which studies can be done with high accuracy and speed without the need for a strong hardware and software system. The Google Earth Engine system creates suitable conditions for processing satellite images for environmental monitoring and analysis. The purpose of this research is to monitor the dynamic changes in the Miangaran wetland sub-basin in the period (2013-2022).Materials & MethodsMiangaran wetland with an average area of 2500 hectares is located at a distance of one and a half kilometers from Izeh city, in the northeast of Khuzestan province. Time series analysis is one of the most common operations in remote sensing that helps to understand and model seasonal patterns as well as monitor changes. In this research, 421 images from the ee.ImageCollection ("LANDSAT/LC08/C02/T1_L2") data set were used for the period from 2013 to 2022. The construction of a harmonic model was used in this research due to its flexibility in cyclic calculation with simple and repeatable forms. The normalized differential water index is an index for drawing and monitoring content changes in surface waters. Also, the Normalized Difference Vegetation Index (NDVI) is one of the most common remote sensing indices. Harmonic time series of water body and vegetation cover were extracted using NDWI and NDVI indices in Google Earth Engine platform, and Mann-Kendall's non-parametric test was performed using time series data output with XLSTAT extension in Excel software. Finally, global water data was used to confirm and complete the results of time series analysis.Results, discussion and conclusionThe results of the harmonic time series of the water body showed a decreasing and negative trend and more changes in the sub-basin. Kendall's statistical test confirmed the decreasing and negative trend of the water body. Accordingly, since the calculated p-value (<0.0001) is lower than the alpha significance level (0.05), the null hypothesis should be rejected and its alternative hypothesis, the existence of a trend in the time series, should be accepted. The value of Kendall's tau also confirmed a negative value (-0.245) and a decrease. Due to the negative sen's slope statistic for the water area (-0.002), changes are more in the Miangaran Wetland sub-basin. The results of the Mann-Kendall test for the observed vegetation data showed the absence of a trend in the harmonic time series. Since the calculated p-value (0.064) is higher than the significance level of alpha (0.05), the null hypothesis (absence of trend) cannot be rejected. The risk of rejecting the null hypothesis (while true) is 43.6%. Kendall's tau statistic showed a negative value (-0.060) and a non-significant decrease. Therefore, accepting the null hypothesis (absence of trend) indicates that vegetation changes in the harmonic time series were not significantly different from each other. Also, the negative sen's slope statistic for vegetation (-0.026) indicates more changes in the sub-basin of Miangaran Wetland. By comparing with the results and analysis of other researches, it seems that human intervention and change of land use can be the cause of the lack of trend in the Miangaran Wetland sub-basin. Also, according to the negative value of Man-Kendall's vegetation cover which showed a non-significant decreasing trend, it seems that climate change and drought have also played a major role in the changes under the Miangaran wetland basin. The study of the global water data also showed that the water occurrence in terms of space-time is decreasing and the intensity of the change of water occurrence is critical under the basin of Miangaran wetland. The marginal parts of Miangaran Wetland show seasonal water loss, most of these changes occur during the period. This research confirmed the use of harmonic time series in monitoring wetland dynamic changes. Finally, the allocation of water rights, the establishment of laws and the determination of the limit of the ecological bed, and the use of Google Earth Engine capabilities to monitor environmental changes (use, temperature, precipitation, evaporation, etc.) of the Miangaran Wetland sub-basin were suggested.
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