چکیده:
حوضة آبریز سیرجان واقع در استان کرمان، یکی از مناطق درگیر با بحران کمآبی است. هدف از این پژوهش، پتانسیلیابی منابع آب زیرزمینی در این حوضه با استفاده از تکنیکهای سنجش از دور و GIS است. در این پژوهش بهمنظور شناسایی خطوارههای تکتونیکی، یکی از عوامل مهم در تشکیل منابع آب زیرزمینی، از تصاویر راداری سنتینل 1 استفاده شد. در این زمینه با انجام آنالیز بافت و تهیة پارامترهای مربوط به ماتریس همرویداد گامهای خاکستری، شامل میانگین، واریانس، یکنواختی، تباین، اختلاف، آنتروپی، موقعیت ثانویه و همبستگی، مؤلفههای اصلی مربوط تهیه شد؛ سپس با اعمال فیلترهای جهتدار روی تصویر مؤلفة اصلی 1، تعداد 389 خطوارة تکتونیکی بارزسازی شد. بهمنظور پتانسیلیابی منابع آبی جدید، عوامل مختلف هیدرولوژی و هیدروژئولوژیکی مؤثر بر تشکیل منابع آب زیرزمینی شامل لایة تراکم خطوارههای تکتونیکی، بارندگی، تراکم آبراههای، سنگشناسی، شیب و پوشش گیاهی در محیط GIS تهیه شد. پس از تشکیل ماتریس مقایسات زوجی براساس روش Fuzzy-AHP، لایههای مدنظر وزندهی و تلفیق شد؛ درنتیجه نقشة پتانسیل آب زیرزمینی حوضة سیرجان تهیه شد. براساس نتایج، محدودة پژوهش بهلحاظ پتانسیل آب زیرزمینی به پنج منطقة خیلی خوب (228 کیلومترمربع)، خوب (836 کیلومترمربع)، متوسط (4016 کیلومترمربع)، ضعیف (2252 کیلومترمربع) و خیلی ضعیف (396 کیلومترمربع) تقسیم میشود. بهمنظور صحتسنجی نتایج از دادههای 30 چاه مشاهدهای استفاده شد. براساس ماتریکس خطای تهیهشده، صحت نتایج بهدستآمده برمبنای دبی و شوری به ترتیب 33/83 درصد و 33/73 درصد برآورد شد.
Groundwater resources are an important natural resource for domestic, agricultural, and industrial use. Today, due to the population growth as well as agricultural, and industrial development, the demand for groundwater use has increased dramatically. Climate changes, repeated droughts, and the risk of surface water pollution as a result of human and industrial activities are other important factors in the human interest in using groundwater resources. However, the unplanned use of groundwater disrupts the natural nutrient balance of aquifers. The accumulation and movement of groundwater in an area depend on various factors such as geology, tectonics, soil type, geomorphological characteristics of the region, drainage pattern, land use, and the relationship between such factors. The tectonic factor is one of the most important factors in the concentration of groundwater resources. Earth faults and fractures, known as tectonic faults, cause more and more surface water to penetrate into the earth's crust and feed the groundwater aquifers. Therefore, the identification of tectonic faults is one of the important cases in the study of groundwater resources. Kerman province, and especially its northern and northwestern cities, due to the increasing expansion of pistachio orchards, has faced an increase in the extraction of groundwater resources and water scarcity is one of the most important problems in the region. Sirjan city is also one of the areas that needs the identification of new groundwater resources. Therefore, in this study, an attempt has been made to process Sentinel 2 multispectral images and Fuzzy-AHP methods, which are among the multi-criteria decision analysis techniques. The maps of the various factors influencing the creation of groundwater aquifers have been prepared in the GIS environment. The maps were weighed and combined to identify suitable areas with good potential. The main difference between this method and the AHP method is the difference in the method of weighting criteria and options so that in this method, the weighting is done as fuzzy. Methodology The textural analysis consists of quantifying the different gray levels of the image in terms of roughness and their distribution. The contextual analysis technique makes it possible to highlight image dissimilarities or homogeneous zones. There are several methods for textural analysis including structural, statistical, study-based methods, and fractal methods. In this study, a statistical approach known as Grey Level Co-occurrence Matrix (GLCM) proposed by Haralick (1979) was adopted. It allows the identification and selection of the parameters that best define the elements from the measurement of the gray tone distributions. The factors are the mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation. These factors have many applications in geological and topographic studies. In this study, these factors were used in the analysis of the main components and then in the filtering operation to extract tectonic faults. Lineaments are related to fractures and lithological boundaries and in some cases to geomorphic relief. Thus, lineaments appear on the image with a tonal difference. The Fuzzy-AHP method was first proposed by Chang (1996, p. 649). Discussion The textural analysis was performed on the Sentinel 1 radar image of the study area. The result were 8 images of different co-occurrence indices. Figure 3 in the text shows the images mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation. In order to extract tectonic faults, the analysis of the principle components on eight co-occurrence factors was performed. Since the first principle component contains about 90% of the image information, it shows the major structural features of the image. In order to reduce the noise and increase structural information as much as possible, the first main component was multiplied. In order to extract tectonic lines, the oriented filter was applied to the conjugate image of the first main component at zero, 45, 90, and 135 degree angles. In this way, the north-south, northeast-southwest, east-west, and southeast-northwest directions were highlighted, respectively. Figure 6 in the text shows the effective factors in the potential assessment. In order to achieve the final map of the potential of groundwater resources in the fuzzy hierarchical method, each criterion must first be weighed and merged accordingly. Table 2 in the text shows the binary comparison matrix of criteria. Accordingly, the lithological criterion with a weight of 0.378 has the most effective factor and the vegetation criterion with a weight of 0.043 has the least effect on the concentration of groundwater resources. About 3 percent of the study area is in the very good category (228 square kilometers), 11 percent in the good category (836 square kilometers), 52 percent in the average category (4016 square kilometers), 29 percent in the low category (2252 square kilometers), and 5 percent in the very low category (396 square kilometers). Very good and good areas are mostly in the foothills to the highlands of the study area. Conclusion The results of the grey level co-occurrence matrix method show the capability of this method in extracting tectonic lines. In addition, the higher spatial resolution of the Sentinel 1 radar images than the available optical images makes the separation and detection of tectonic lines better. By combining the effective layers in the concentration of groundwater, the study area was potentialized in terms of the existence of groundwater reserves. The results show that about 14% of the study area has good potential (mostly located in foothills and within calcareous and alluvial rocks) in this area. Due to the declining quality of water resources in existing wells, the identified areas with a good and very good potential can be explored specifically for new water resources. Keywords: Potential Assessment, Groundwater Resources, Remote Sensing, Fuzzy-AHP, Sirjan Basin. References - Agarwal, E., Rajat, A., Garg, R. D., & Garg, P. K. (2013). Delineation of Groundwater Potential Zone: An AHP/ANP Approach. Journal of Earth System Science, 122(3), 887-898. - Andualem, T. G., & Demeke, G. G. (2019). Groundwater Potential Assessment Using GIS and Remote Sensing: A Case Study of Guna Tana Landscape, Upper Blue Nile Basin, Ethiopia. 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خلاصه ماشینی:
ارزيابي پتانسيل منابع آب زيرزميني با استفاده از پردازش داده هاي راداري سنتينل ١ و تکنيک آناليز تصميم گيري چندمعياره (MCDA) نمونۀ پژوهش : حوضۀ آبريز سيرجان علي مهرابي ، استاديار گروه جغرافيا و برنامه ريزي شهري، دانشکده ادبيات و علوم انساني، دانشگاه شهيد باهنر کرمان ، کرمان ، ايران mehrabi@uk.
شهرستان سيرجان نيز، يکي از اين مناطق اسـت کـه بـه شناسـايي منـابع آب زيرزميني جديد نياز دارد؛ از اين رو در اين پـژوهش سـعي شـده بـا اسـتفاده از پـردازش تصـاوير راداري سـنتينل ١، چندطيفي سنتينل ٢ و روش Fuzzy-AHP که يکي از تکنيک هاي آناليز تصميم گيـري چنـدمعياره اسـت ، در محـيط GIS نقشۀ عوامل مختلف مؤثر بر ايجاد سفره هاي آب زيرزميني تهيه ، وزن دهي و تلفيق شود تا مناطق مناسب و داراي پتانسيل خوب (به لحاظ ذخيرٔە آب زيرزميني ) شناسايي شوند.
پردازش تصاوير راداري و چندطيفي از آنجا که يکي از مهم ترين عوامل تمرکز و ايجاد منـابع آب زيرزمينـي، تکتونيـک و بـه طـور کلـي خطـواره هـاي تکتونيکي است ، به منظور تهيۀ نقشۀ مدنظر از پردازش تصاوير راداري سنتينل ١ استفاده شـد؛ بـه طـوري کـه بـا انجـام اعمال فيلترهاي جهت دار روي تصوير، خطواره هاي تکتونيکي منطقه بارزسازي و ترسيم شد؛ علاوه بر ايـن بـه منظـور تهيۀ نقشۀ پوشش گياهي از اعمال شاخص NDVI روي تصوير چندطيفي سنتينل ٢ استفاده شد که در ادامه روش هاي يادشده شرح داده مي شوند.
نقشۀ خطواره هاي تکتونيکي منطقۀ پژوهش ؛ تهيه شده درنتيجۀ آناليز بافت و فيلترگذاري داده هاي راداري سنتينل ١ (نگارندگان ، ١٣٩٩) با توجه به اينکه يکي از اهداف اصلي اين پژوهش پتانسيل يابي منابع آب زيرزميني است ، عوامـل و معيارهـاي مـؤثر بـر تمرکز منابع آب زيرزميني بررسي و درنهايت به صورت نقشه در محيط GIS ترسيم شد.