پیش‌بینی و پهنه بندی پتانسیل وقوع سیلاب برحسب الگوریتم‌های تغییر اقلیم (مطالعه موردی حوضه آبخیز گرگانرود) مقالة

مؤلف: پناهی، عبدالحافظ ؛ متولی، صدرالدین ؛ خالدی، شهریار ؛

جغرافیا (انجمن جغرافیایی ایران) پاییز 1402 - شماره 78 التصنيف ب (Ministry of Science (‎26 صفحة - من 109 إلی 134 )

الکلمات المفتاحية: پهنه بندی سیلاب الگوریتم تغییرات اقلیمی گرگانرود Gorganrood GIS Zoning Climate Change Algorithms

خلاصة:

پتانسیل سیل‌خیزی عبارت از تعیین و توصیف مناطق دارای پتانسیل ازنظر رواناب‌های سطحی است درواقع با تعیین محل‌های دارای پتانسیل بالا به‌نوعی می‌توان یک ارزیابی کلی از وضعیت سیل‌خیزی منطقه نیز به دست آورد . روش پژوهش حاضر، با توجه به ماهیت مسئله و موضوع موردبررسی، از نوع توصیفی - تحلیلی است و از نوع مطالعات کاربردی با تأکید بر روش‌های کمی است، در تحقیق حاضر تغییرات منطقه‌ای سیلاب در حوضه آبخیز گرگانرود با کارگیری اطلاعات ایستگاه‌های سازمان هواشناسی (سینوپتیک) با دوره ﺁماری 30 ساله(1368 تا 1397) ، کاربری اراضی ،پوشش گیاهی، شاخص رطوبت توپوگرافیک، شیب، ارتفاع،لیتولوژی زمین، فاصله از رودخانه، تراکم رودخانه،فرسایش، خاکشناسی،رواناب، داده‌های شبیه‌سازی شده میانگین بارندگی حاصل از مدل‌ HadCM3 در LARS-WG تحت سناریو SRA1B بین سال های 2011 تا 2045 برﺁورد شده است. در این تحقیق در دو بخش متفاوت که در روش اول از مدل LARS-WGبرای ریز مقیاس نمائی جهت پیش‌بینی اقلیم آینده (نزدیک و دور) و در بخش دوم از مدل هیدرولوژیکیSWAT برای ارزیابی خطر سیل استفاده استفاده شد و با توجه به درصد خطرات احتمالی در حوزه آبریز گرگانرود در محیط نرم افزار SWAT وGIS پهنه‌بندی گردید. پهنه بندی خطر سیلاب حوضه آبخیز گرگانرود نشان می‌دهد بیشتر سطح حوضه برابر 89 درصد در معرض خطر سیلاب شدید واقع شده است. نتایج نشان داده‌اند که تغییر اقلیم و ساختار محیط طبیعی در منطقه پیامدها و اثراتی ازجمله تغییر الگوی بارش، به وجود آمدن ناهمگنی در سری داده‌های تاریخی، تغییر سطح آب رودخانه‌ها و کاهش تولیدات کشاورزی، تغییر در ترکیب و تولید گیاهی مراتع، تغییر سطح آب‌های زیرزمینی، بروز مشکلات اجتماعی و اقتصادی و ... بوجود آورده است. عوامل فیزیوگرافی همچون شیب، بافت خاک، کاربری اراضی و نفوذپذیری سنگ‌ها موجب پاسخ‌های هیدرولوژیکی متفاوت به رخداد بارش در حوضه‌های مختلف منطقه شده و این امر بر ایجاد و ویژگی‌های سیلاب ناگهانی تأثیرگذار بوده است.

Extended AbstractIntroductionFlood is one of the natural phenomena and one of the most important and destructive hazards in the world, which is associated with loss of life and property every year in different parts of the world and Iran. Climate change has consequences and effects on global warming, reduction of Agricultural production, changes in the diversity and vegetation of pastures, changes in groundwater levels, the occurrence of social and economic problems, and so on. The overall goal of this research is to zoning and model areas at risk and flood risk for changing climates. The prevailing approach of the research is the approach of climate change and its effects on the hydrology of Gorganrood watershed. The key goal of the current research is to model and forecast regional flood risk under climate change conditions using fuzzy analysis algorithm, hierarchical analysis and SWAT model in the watersheds of Golestan province. In fact, it is possible to plan the water resources of the region more precisely and help to calculate the more precise management of the transfer of the region along with other environmental variables, including this research. There have been many research studies on the phenomenon of precipitation in Golestan province and Iran, but none of them have examined this climatic variable with the perspective of climate change together with environmental variables. MethodologyGorganrood Basin with an area of 10197 square kilometers is one of the northeastern basins of the country, a large part of which is located in Golestan province. It is bounded by the Atrak catchment area and the Caspian Sea and Qarahsu catchment area from the west. In the present study, flood zone changes in Gorganrood watershed based on the use of meteorological organization (synoptic) station information with a 30-year statistical period (1989 to 2018), land use, vegetation, topographic moisture index, slope, altitude, land lithology, Distance from river, river density, erosion, soil science, runoff, simulated data The average rainfall of HadCM3 model in LARS-WG under SRA1B scenario is estimated between 2011 and 2045. The evaluation criteria used in this study are defined based on parameters such as ME, RMSE, ASE, MSE. The most important criterion for estimating estimates is the square root of the mean error (RMSE). (ME) is the mean of the errors or the mean difference between the estimated value and the value observed at point I. The SWAT model is an extension under ArcGIS software that simulates the main hydrological processes including evapotranspiration, surface runoff, deep infiltration, groundwater flow and subsurface flows by the simulator model. The type of land use in the region, the type of vegetation in the region, the slope values and the length of the slope in different areas, which is used through the Geographic Information System (GIS). The input spatial variables of the SWAT model in this study include the digital elevation model (DEM) information layers, the soil layer with soil texture information, and the land use layer with its descriptive information. Hydroclimatology and numerical variables of SWAT model include daily precipitation, minimum and maximum temperature related to stations inside and outside the basin and the average daily runoff of the basin outlet along with their geographical locations. Simulating large and complex areas with different management strategies can be done without spending a lot of time and money. Results and discussionThe results for SRA1B scenario therefore it can be concluded that in general for the next period, the area under study will face a decrease in average flow rate. By analyzing the obtained results, it can be inferred that the phenomenon of climate change will have tangible effects on the studied area over time and will change the values of temperature and precipitation parameters and will reduce winter precipitation and increase the temperature of the studied area. results of the future discharge simulation show a decrease in runoff for October under the SRA1B scenario. Therefore, according to the results, it can be stated that in general, the SRA1B scenario predicts a decrease in discharge for the next period compared to the observed discharge. The simulation results of the basin output flow and observational flow measured by architect R2 and NS as well as the uncertainty parameters r-factor, pfactor were evaluated and analyzed. The optimal values of R2 and NS coefficients are one and one. One of the goals of the SWAT model is to To reduce impotence. So that most of the observational data are at the level of 95%. In research, NS coefficient greater than 0.5 and p-factor greater than 0.5 have been introduced as satisfactory values. Examining the changes, it is expected that the runoff will decrease with increasing scenarios. This trend has decreased in RCP4.5, although its limit rainfall has also increased, and in RCP8.5 (with more rainfall) the runoff has increased. The reason for this change is that the incidence of precipitation in RCP4.5 was in summer and early autumn, which despite the high evaporation and lack of snowmelt (according to RCP8.5 which in spring coincides with snowmelt) runoff is less than the next scenario. ConclusionFlood risk zoning in the Gorganrood watershed, 345 villages with a population of 275,312 people are at high risk of flooding. square, it has a relatively low potential equal to 1425.46 square kilometers, a very high degree of flood risk equal to 884.68 square kilometers, and finally, an area with a low flood potential equal to 623.12 square kilometers from the entire surface of the Gorganrood watershed. It can also be concluded that most of the basin level equal to 89% is at risk of severe flooding. In all the stations, according to the predictions made by the LARS-WG model, the rainfall for the future scenario has increased in some months and decreased in some months compared to the base period . So that in the summer month, the rainfall will decrease and compared to the winter season, the rainfall will increase compared to the base period. The comparison of the monthly rainfall of the base period (2011-2007) with the rainfall simulated by the HadCM3 model for the SRA1B scenario (2011-2045) also shows a significant increase in rainfall in this series of scenarios in the months of September, October and November. It can be seen with a few changes. which can be investigated in terms of the effects of this phenomenon by studying the average percentage of precipitation changes for the SRA1B scenario in 2 periods; 2011-2045, 2045-2065 also shows the changes in rainfall from August in the period, 2011-2045 to 37.5% in November of the same period compared to the base period. The very high increase of precipitation changes in November can also be investigated and pondered for the cause of autumn floods.

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