پلن معامله‌گری :پارامترهای شاخص

بررسی مقایسه ای شاخص مورفولوژی زاویه مرکزی (A) با پارامترهای چند فراکتالی الگوی تکامل پیچان رودها با استفاده از روابط رگرسیونی(مطالعه موردی : رودخانه قره آغاج در استان فارس)

پیچان رودها بعنوان یکی از رایج ترین انواع رودخانه ها در طبیعت هستند که دارای ماهیت خطی بوده و جریان های بسیار پیچیده ای در آنها برقرار است. آشکار سازی این جریان ها که منجر به پیش بینی تغییرات الگوی هندسی رودخانه می‏شوند نیازمند ابزار دقیق مطالعاتی می‏باشد. هدف از این مقاله بررسی و ارزیابی حوضه آبریز قره‏آغاج در استان فارس بر اساس تحلیل چندفراکتال روند تکاملی آبراهه و مقایسه انطباقی حاصل از عملیات رگرسیونی پارامترهای چندفراکتال حوضه آبریز با شاخص زاویه مرکزی(A) می باشد. در مطالعه فراکتال حوضه آبریز رودخانه قره‏آغاج در استان فارس با در نظر گرفتن 3 بازه مطالعاتی از رودخانه در ابتدا شاخص زاویه مرکزی(A) برای تک تک قوس‏های بازه‏های مطالعاتی رودخانه محاسبه گردید. با انجام 180 مدل نموداری در محیط نرم افزار اکسل نتایج بدست آمده حاکی از آن است که الگوی تکاملی رودخانه تحت تاثیر ویژگی‏های چندفراکتال می‏باشد. در تمامی بازه‏های شماره 1 تا 3 رودخانه همواره بیشترین درصد تاثیرگذاری را در افزایش مقدار عددی ‏ضریب رگرسیونی R^2 دارند. در نتایج و بررسی‏های مختلف در نهایت این نتایج حاصل شد که در الگوی تکاملی بازه شماره 1 رودخانه که دارای ریتم منظم تر قوس‏های متوالی نسبت به دو بازه دیگر یعنی بازه‏های 2 و3 بود، تفاوت‏های چشمگیری در نتایج حاصله پدید آمد که همگی این‏ها نشانگر این است که همواره زاوایای مرکزی قوس‏ها در رودخانه از اهمیت بسزایی برخوردار هستند و در چگونگی نحوه شکل گیری آنها بسیار موثر اند.

کلیدواژه‌ها

20.1001.1.22519424.1400.9.4.6.4

عنوان مقاله [English]

Comparative Investigation of Central Angle Morphology Index(A) With Evolutionary Pattern Of Meanders Multi-Fractal Parameters By Using Regression Relations (Case Study : Qhar-e-Aghaj River)

نویسندگان [English]

ali hosseini 1
mohammad hadi fattahi 2

1 MSc Graduate in Civil Engineering Department, Water Resources Management, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.

2 Assistant Professor, پارامترهای شاخص پارامترهای شاخص Civil Engineering Department, Water Resources Management, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.

Extended Abstract
Rivers undergo many changes over time caused by various factors, such as geological, hydrological, and geomorphological features. One of the key topics in river engineering is the identification of river patterns (i.e. morphology). The study of the morphological aspects of rivers has always attracted the attention of specialists. Meandering rivers are among the most common types of rivers in nature with a linear form and very complex currents. The identification of these currents, which leads to the prediction of geometric pattern changes to rivers, requires sophisticated research tools. Fractal and multi-fractal analyses are among the most powerful analysis methods used in nonlinear systems to investigate complex patterns. This paper aims to investigate the Qara Aghaj River drainage basin in Fars province based on the multi-fractal geometry analysis of the waterway evolution process as well as the adaptive comparison derived from the regression operation of the multi-fractal parameters of the drainage basin with the central angle index of (A).
Introduction
The Qara Aghaj River drainage basin is located on the eastern slopes of the Zagros Mountains between longitude of 47-51 and 14-54 N and latitude of 22-28 to 29-54 E. This drainage basin has an area of 13,050 km2. The drainage basin is bounded by the Kor River drainage basin as well as the Bakhtegan and Maharloo Lake drainage basin in the north, by the Kol River drainage basin in the east, by the Mand River drainage basin in the south, and by the Shapur and Dalaki River drainage basin in the west. In the fractal study of the Qara Aghaj River drainage basin in the Fars province, taking into account 3 study periods of the river, very high-quality satellite images were captured in those periods. ArcGIS software was used to perform image correction and process operations. After performing advanced image processing operations to extract the water pattern of the river in ArcGIS software, the river water pattern’s polygon file for all 3 study periods was transferred to AutoCAD software to measure the central angle morphology index (A). To determine the size of the central angle index, arcs were fit to each of the meanders with high precision in AutoCAD software for periods 1 to 3 of the river. Each of the meanders in the river is actually a river arc, with the successive river arcs being the focal point of this research for examining their evolution.
Methodology
After checking the numerical value of each arc in the periods, given the numerical mean of the central angle of 115° for period 1 of the river, 108° for period 2, and 98° for period 3, which were all located within the numerical range of 85° and 158° (158> 115> 108> 98> 85), it was found out all the three selected river periods were of the developed meandering type. However, in the present study, the evolution pattern of the river was evaluated to examine the multi-fractal parameters. Accordingly, period 1 of the river included 22 evolution patterns, period 2 of the river included 23 evolution patterns, and period 3 of the river included 17 evolution patterns. According to the evolution trend of the calculated values, each morphological index of the central angle (A) for periods 1 to 3 of the river was calculated based on the average of its previous values, for each of the evolution patterns. In the present study, Fractalyse software was used to calculate each evolution pattern of periods 1 to 3 of the river. Upon importing the *.tiff image file of each evolution pattern for periods 1 to 3 of the river and using the box-counting method for calculating multi-fractal parameters, all analyzed numbers were exported in the form of *.txt files. Next, they were used for drawing diagrams and correcting some output errors of models in Microsoft Excel.
Results and Discussion
In the present study, given the study of the river evolution patterns for finding logical relationships between the central angle morphology index (A) and multi-fractal parameters, we deal with a lot of numbers in each pattern. Thus, the review of this subject was not possible without drawing a diagram, given the huge amount of data, all of which consisted of numbers and figures. Therefore, to examine more accurately and to convert all these numbers into a comparable criterion, multivariate regression analysis and the R2 regression coefficient were used for each diagram. To this end, for each of periods 1 to 3 of the river, the value of R2 was determined by drawing the diagram of the central angle in the order of the evolutionary pattern of successive arcs. Next, to create a certain weight ratio through multiplying the values of the central angles by each of the 15 corresponding multi-fractal parameters, the new value of R2 was determined.
Conclusions
The results obtained from running 180 regression diagram models in Excel software indicate that the evolution patterns of the river are affected by multi-fractal features. Parameters, such as 〖∆,D〗_f,〖Dq〗_((2) ),〖τq〗_((o) ),〖Dq〗_((max) ),〖Dq〗_((min) ), as well as α_((max) ), most of which being related to generalized and fractal پارامترهای شاخص dimensions, had the highest percentage of effectiveness in increasing the numerical value of the R2 regression coefficient in all periods 1 to 3 of the river. With a more detailed review, it was finally concluded that in the evolution pattern of period 1 of the river which had a more regular rhythm of successive arcs than the other two periods, i.e. periods 2 and 3, significant differences were produced in the results. This indicates that the central angles of the arcs in the river are always of great importance, and that they are very effective in the way the arcs are formed. In the end, we always witness how carefully the nature puts such angles and distances together, thereby creating a special order in the pattern of the complex mathematics of these natural phenomena.

کلیدواژه‌ها [English]

Fractal Geometry
Multi-Fractal
Box Counting Method
Central Angle
Morphology Index (A)

مراجع

احسان نیکویی، مهدی حیدری، ناصر طالب بیدختی، علی اکبر حکمت زاده، هندسه فراکتالی در مهندسی رودخانه ایده ها، مفاهیم اساسی و دستاوردها، چهارمین کنگره مهندسی عمران، دانشگاه تهران، اردیبهشت 1387

جلالی، مهدی. شبیه سازی جریان رودخانه با استفاده از شبکه عصبی مصنوعی(مطالعه موردی: حوضه قره‏آغاج در استان فارس)پارامترهای شاخص ، پایان نامه جهت دریافت درجه کارشناسی ارشد در رشته مهندسی منابع طبیعی، گرایش آبخیزداری، دانشگاه مازندران، دانشکده منابع طبیعی، خرداد1388، صص 35-31

فتاحی، محمدهادی. کامیاب، ساره. انطباق سنجی خواص ژئومورفولوژیک حوضه آبریز و ویژگی‏های چندفراکتال شکل آبراهه، تحقیقا منابع آب ایران، سال چهاردهم، شماره 5، زمستان 1397، صص 326-311

کهربائیان، پروین. بهنیافر، ابوالفضل. شاکری زراع، حجت. رضایی عارفی، محسن. تحولات مورفولوژیکی و الگوی پیچان رودی بستر رودخانه مرزی هریرود با استفاده از RS، پژوهش‏های ژئومورفولوژی کمی، سال سوم، شماره 3، زمستان 1939، صص. 64-53

مرتضوی، محمدرضا. بهنیافر، ابوالفضل. قنبرزاده، هادی. بررسی الگوی پیچان‏رودی رودخانه گلمکان با استفاده از شاخص‏های ضریب خمیدگی و زاویه مرکزی، مجله علوم جغرافیا، شماره 29، پاییز و زمستان 1397، صص. 280-290

مهندسین مشاور پارساب، مطالعات شناسایی آبخیزداری حوزه آبخیز سد سلمان فارسی(قیز)، جلد سوم، هیدرولوژی و سیل، وزارت جهاد پارامترهای شاخص و سازندگی، معاونت آبخیزداری، 1375، ص91

Alizadeh Y, Alizadeh H .(2014). The effect of neonate construction on the morphology of drainage network in the watersheds basin using geomorphic-morphometric indices. Geographic Survey Quarterly,29(1): 115-121.

Campos, P., & Paz, I. (2020). Spatial Diagnosis of Rain Gauges’ Distribution and Flood Impacts: Case Study in Itaperuna, Rio de Janeiro—Brazil. Journal of Water, 12(1): 1120-1147

Carpinteri A., Lacidogna G., Niccolini G. (2009). Fractal analysis of damage detected in concrete structural elements under loading. Chaos Soliton Fract, 42(4):2047–2056.

Chhabra A., Meneveau C., Jensen, R. Sreenivasan, K. (1989) Direct determination of the f(α) singularity spectrum and its application to fully developed turbulence. Phys. Rev. A , 40(9):5284529

Fattahi, M. H., Talebbeydokhti, N., Rakhshandehroo, G. R., Shamsai, A. & Nikooee, E. (2010). The robust fractal nalysis of the time series- concerning signal class and data length. Fractals, 9: 1-21.

Fattahi, MH, Taleb Beydokhti N, Nikooee, N. (2012). Multi-fractal approach to the flood flow of the Ghare-aghaj River flow. Journal of Water Resources Engineering, 5: 12-21

Hosseini, M. Fattahi, M.H. and Eslamian, S. (2020). Experimental Analytical Study on Fractal Behaviors of the Density Current. Iranian Journal of Science and Technology, Transactions of Civil Engineering. 44(4): 75-90

Karam A, Saberi M. (2015). Calculating of the fractal dimension in drainage basins and its relation with some geomorphological characteristics of basin (Case study: North Tehran basins). Quantitative geomorphology researches, 4(3): 75-92.

Lee, A., Aubeneau, A & Cardenas, M. (2020). The Sensitivity of Hyporheic Exchange to Fractal Properties of Riverbeds” Journal of Water, 56(5): 20-42.

Marin, G.A., Estevez, J., Morbidelli, R., Saltalippi. C., Murioz, J., & Flammini, A .(2020).Assessing Inhomogeneities in Extreme Annual Rainfall Data Series by Multifractal Approach” Journal of Water, 12(1): 1030-1048

Moon, F. C. (2004). Chaotic and fractal dynamics: an introduction for applied scientists and engineers. WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim, pp. 77-78.

Tanna, H.J and Pathak, K.N. (2013). Multi-fractality due to long-range correlation in the L-band ionospheric scintillation S4 index time series. Astrophysics and Space Science, 350(1): 47-56

Teng, Y., & Shang, P. (2018). Detrended fluctuation analysis based on higher‐order moments of financial time series. Physica A: Statistical Mechanics and its Applications, 490(1): 311-322

Vargas, K., & Salarriaga, J. (2019). Analysis of Fractality in Water Distribution Networks Using Hydraulic Criteria. World Environmental and Water Resources. 15(1): 25-38

Zhang, X., Zhang, G., Qiu, L., Zhang, B., Sun. Y., Gui. Z., & Zhang, Q. (2019).A Modified Multifractal Detrended Fluctuation Analysis (MFDFA) Approach for Multifractal Analysis of Precipitation in Dongting Lake Basin, China. Journal of Water, 11(5): 891-1009

بررسی نقش سازندهای زمین‌شناسی و پارامترهای هیدرولوژیکی بر شاخص جریان پایه، مطالعه موردی: ناحیه خزری

جریان پایه و شاخص مربوطه که متاثر از عوامل مورفومتری، زمین‌شناسی و هیدرواقلیمی است، همواره یکی از موضوعات مهم در هیدرولوژی بوده و اطلاع از میزان آن، نقش به‌سزایی در برنامه‌ریزی و مدیریت بهینه منابع آب دارد. در این پژوهش با استفاده از داده‌های جریان روزانه رودخانه، جریان پایه و شاخص آن، از روش فیلتر رقومی برگشتی یک پارامتره، در 18 ایستگاه آب‌سنجی حوضه خزری، استخراج شد. پارامترهای فیزیوگرافی محاسبه و عوامل هیدرولوژیکی، اقلیمی و زمین‌شناسی در محیط GIS برآورد شد. با استفاده از روش آزمون تحلیل عاملی از بین 18 پارامتر مؤثر در شاخص جریان پایه، پنج عامل به‌عنوان عوامل مستقل انتخاب شدند. سپس روابط تحلیل منطقه‌ای به‌روش‌های رگرسیون خطی، توانی، نمایی و چندمتغیره در سطوح معنی‌داری کمتر از یک و پنج درصد به‌دست آمد. علاوه‌ براین، به‌منظور مقایسه و ارزیابی صحت و کارآیی مدل‌های برآوردی، روش آنالیز باقی‌مانده‌ها نیز مورد استفاده قرار گرفت. از بین عامل‌های زمین‌شناسی مشخصاً سازندهای سخت، از بین عوامل مورفومتری، پارامترهای متوسط ارتفاع و تراکم زهکشی حوضه و از جنبه قابلیت اراضی نیز عامل سطح جنگلی، در روش رگرسیون‌های چند متغیره به‌عنوان بهترین برآورد کننده‌ شاخص جریان پایه رودخانه‌ها، تشخیص داده شدند. همچنین، با توجه به مدل‌های رگرسیون خطی، توانی و نمایی تک‌متغیره، پارامتر Q₉₀/Q₅₀ بهعنوان موثرترین عامل هیدرولوژیکی در تخمین شاخص جریان پایه در منطقه تعیین شد. همراهی سازندهای سخت کربناته با نهشته‌های کواترنری و همچنین، سازندهای سخت غیرکربناته با عامل‌های مورفومتری و درصد پوشش جنگلی در مدل‌های به‌دست آمده، موید نقش کنترل‌کننده عامل زمین‌شناسی بر جریان پایه است.

کلیدواژه‌ها

جریان روزانه
سازند کربناته
فیلترهای رقومی
مدل‌های منطقه‌ای
واحدهای سنگ‌شناسی

عنوان مقاله [English]

Study role of geological formations and hydrological parameters on the based index, case study: Caspian area

نویسندگان [English]

Rahim Kazemi 1
Ali Reza Eslami 2

1 Scientific Board, Soil Conservation and Watershed Management Research Institute, Iran,

2 Assistant Professor, Soil Conservation and Watershed Management Research Institute, Iran

چکیده [English]

Base flow and related index is influenced by morphometric, geologic and hydroclimatological factors. As a result, it is precondition data for planning and water resources management. In this research, base flow and related index were extracted from daily stream flow data using one parameter recursive digital filter in eighteen hydrometric stations of the Caspian Basin. Physiographic, climatic, hydrological, and geological factors were calculated in GIS environment. Using factor analysis of the eighteen parameters, five factors were selected as independent factors. Statistical models were formulated to calculate several regressions between hydroclimatological and physiographic parameters. Further, residual analysis method was used to compare and evaluate the accuracy and efficiency of the models. Results showed that Hard Formations, the average height of basin, drainage density, and coverage of forest were the best predictors of the base flow index. Statistical models highlights importance of Q90/Q50 ratio as the suitable hydrologic index to estimate the base flow index. Besides, this model confirmed controlling role of Hard formations and the forest coverage on the base flow index.

بررسی مقایسه ای شاخص مورفولوژی زاویه مرکزی (A) با پارامترهای چند فراکتالی الگوی تکامل پیچان رودها با استفاده از روابط رگرسیونی(مطالعه موردی : رودخانه قره آغاج در استان فارس)

کلیدواژه‌ها

20.1001.1.22519424.1400.9.4.6.4

عنوان مقاله [English]

Comparative Investigation of Central Angle Morphology Index(A) With Evolutionary Pattern Of Meanders Multi-Fractal Parameters By Using Regression Relations (Case Study : Qhar-e-Aghaj River)

نویسندگان [English]

ali hosseini 1
mohammad hadi fattahi 2

1 MSc Graduate in Civil Engineering Department, Water Resources Management, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.

2 Assistant Professor, Civil Engineering Department, Water Resources Management, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.

Extended Abstract
Rivers undergo many changes over time caused by various factors, such as geological, hydrological, and geomorphological features. One of the key topics in river engineering is the identification of river patterns (i.e. morphology). The study of the morphological aspects of rivers has always attracted the attention of specialists. Meandering rivers are among the most common types of rivers in nature with a linear form and very complex currents. The identification of these currents, which leads to the prediction of geometric pattern changes to rivers, requires sophisticated research tools. Fractal and multi-fractal analyses are among the most powerful analysis methods used in nonlinear systems to investigate complex patterns. This paper aims to investigate the Qara Aghaj River drainage basin in Fars province based on the multi-fractal پارامترهای شاخص geometry analysis of the waterway evolution process as well as the adaptive comparison derived from the regression operation of the multi-fractal parameters of the drainage basin with the central angle index of (A).
Introduction
The Qara Aghaj River drainage basin is located on the eastern slopes of the Zagros Mountains between longitude of 47-51 and 14-54 N and latitude of 22-28 to 29-54 E. This drainage basin has an area of 13,050 km2. The drainage basin is bounded by the Kor River drainage basin as well as the Bakhtegan and Maharloo Lake drainage basin in the north, by the Kol River drainage basin in the east, by the Mand River drainage basin in the south, and by the Shapur and Dalaki River drainage basin in the west. In the fractal study of the Qara Aghaj River drainage basin in the Fars province, taking into account 3 study periods of the river, very high-quality satellite images were captured in those periods. ArcGIS software was used to perform image correction and process operations. After performing advanced image processing operations to extract the water pattern of the river in ArcGIS software, the river water pattern’s polygon file for all 3 study periods was transferred to AutoCAD software to measure the central angle morphology index (A). To determine the size of the central angle index, arcs were fit to each of the meanders with high precision in AutoCAD software for periods 1 to 3 of the river. Each of the meanders in the river is actually a river arc, with the successive river arcs being the focal point of this research for examining their evolution.
Methodology
After checking the numerical value of each arc in the periods, given the numerical mean of the central angle of 115° for period 1 of the river, 108° for period 2, and 98° for period 3, which were all located within the numerical range of 85° and 158° (158> 115> 108> 98> 85), it was found out all the three selected river periods were of the developed meandering type. However, in the present study, the evolution pattern of the river was evaluated to examine the multi-fractal parameters. Accordingly, period 1 of the river included 22 evolution patterns, period 2 of the river included 23 evolution patterns, and period 3 of the river included 17 evolution patterns. According to the evolution trend of the calculated values, each morphological index of the central angle (A) for periods 1 to 3 of the river was calculated based on the average of its previous values, for each of the evolution patterns. In the present study, Fractalyse software was used to calculate each evolution pattern of periods 1 to 3 of the river. Upon importing the *.tiff image file of each evolution pattern for periods 1 to 3 of the river and using the box-counting method for calculating multi-fractal parameters, all analyzed numbers were exported in the form of *.txt files. Next, they were used for drawing diagrams and correcting some output errors of models in Microsoft Excel.
Results and Discussion
In the present study, given the study of the river evolution patterns for finding logical relationships between the central angle morphology index (A) and multi-fractal parameters, we deal with a lot of numbers in each pattern. Thus, the review of this subject was not possible without drawing a diagram, given the huge amount of data, all of which consisted of numbers and figures. Therefore, to examine more accurately and to convert all these numbers into a comparable criterion, multivariate regression analysis and the R2 regression coefficient were used for each diagram. To this end, for each of periods 1 to 3 of the river, the value of R2 was determined by drawing the diagram of the central angle in the order of the evolutionary pattern of successive arcs. Next, to create a certain weight ratio through multiplying the values of the central angles by each of the 15 corresponding multi-fractal parameters, the پارامترهای شاخص new value of R2 was determined.
Conclusions
The results obtained from running 180 regression diagram models in Excel software indicate that the evolution patterns of the river are affected by multi-fractal features. Parameters, such as 〖∆,D〗_f,〖Dq〗_((2) ),〖τq〗_((o) ),〖Dq〗_((max) ),〖Dq〗_((min) ), as well as α_((max) ), most of which being related to generalized and fractal dimensions, had the highest percentage of effectiveness in increasing the numerical value of the R2 regression coefficient in all periods 1 to 3 of the river. With a more detailed review, it was finally concluded that in the evolution pattern of period 1 of the river which had a more regular rhythm of successive arcs than the other two periods, i.e. periods 2 and 3, significant differences were produced in the results. This indicates that the central angles of the arcs in the river are always of great importance, and that they are very effective in the way the arcs are formed. In the end, we always witness how carefully the nature puts such angles and distances together, thereby creating a special order in the pattern of the complex mathematics of these natural phenomena.

کلیدواژه‌ها [English]

Fractal Geometry
Multi-Fractal
Box Counting Method
Central Angle
Morphology Index (A)

مراجع

جلالی، مهدی. شبیه سازی جریان رودخانه با استفاده از شبکه عصبی مصنوعی(مطالعه موردی: حوضه قره‏آغاج در استان فارس)، پایان نامه جهت دریافت درجه کارشناسی ارشد در رشته مهندسی منابع طبیعی، گرایش آبخیزداری، دانشگاه مازندران، دانشکده منابع طبیعی، خرداد1388، صص 35-31

مهندسین مشاور پارساب، مطالعات شناسایی آبخیزداری حوزه آبخیز سد سلمان فارسی(قیز)، جلد سوم، هیدرولوژی و سیل، وزارت جهاد و سازندگی، معاونت آبخیزداری، 1375، ص91