تحلیل منطقه‎یی برآورد بار معلق سالانه با به کارگرفتن ویژگی‌های آبخیز در استان هرمزگان

نوع مقاله: مقاله پژوهشی

نویسندگان

1 گروه مهندسی آب، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران

2 دکتری مهندسی عمران- آب

چکیده

این پژوهش با هدف دست‌یابی به مدل‎های منطقه‎یی برآورد بار معلق سالانه در استان هرمزگان انجام شد. متغیر وابسته میانگین بار معلق سالانه‌ی زیرحوزه‎ها، و متغیرهای مستقل 21 سنجه‌ی ریخت‌شناختی و اقلیمی زیرحوزه‎ها با دوره‌ی مشترک داده‌برداری 21 سال (1390-1370) انتخاب شد، و در دو مرحله‌ی تعیین عرصه‎های همگن و استنتاج مدل‎ منطقه‎یی برای منطقه‌های همگن تحلیل شد. پس از شناختن تاثیرگذار‎ترین سنجه‌ها به‌روش تحلیل عاملی، بهترین روش خوشه‎بندی منطقه‎یی بر اساس سه حالت سنجه‌های موثر، میزان بار معلق سالانه، و مشترک (اجتماع دو حالت) با تعداد خوشه‎های متفاوت دانسته شد. معادله‌های وایازی (رگرسیونی) بین اندازه‌های بار معلق سالانه با متغیرها به روش گام‌به‌گام به‌دست آمد. داده‎های وایازی برای ارزیابی‌کردن مدل وایازی به‌دست‌آمده به‌کاررفت و مقدار معیار نش-ساتکلیف این معادله‌ها محاسبه شد. با توجه به نتیجه‌های خوشه‎بندی می‎توان گفت که داده‎های بار معلق از دو مدل منطقه‎یی تبعیت می‎کند. برای برآوردکردن بار معلق این دو منطقه معادله‎هایی با ضریب تبیین 0/78 و 0/84 داده شد. پیشنهاد می‎شود این تحقیق در حوزه‌های بیش‌تر و در شرایط مختلف جغرافیایی انجام شود تا بتوان این رابطه‌ها را برای حوزه‎های بی‌آمار بیش‌تری بهکاربرد.

کلیدواژه‌ها


عنوان مقاله [English]

Regional Suspended Load Analysis Using the Watershed Characteristics in the Province of Hormozgan

نویسندگان [English]

  • Mostafa Jafari Ashourabadi 1
  • Abdolrahim Jamal 2
1 M.Sc. Student, of Water Engineering, Sari Agricultural Sciences and Natural Resources University, Iran
2 Ph.D., of Water Engineering
چکیده [English]

The present study is aimed at estimating the suspended load discharged from watersheds in the Province of Hormozgan. The mean annual suspended loads were considered as the dependent variable and 21 parameters of morphological and climatic factors were selected as the independent parameters. The data were collected from 19 hydrometry stations for a 21-years period (1991–2011). This analysis is presented in two steps; a principal component analysis (PCA) was further applied to extract the underlying factors (principal component) and use the hierarchical clustering analysis in order to identify homogeneous groups. Multi regression was performed to identify the contribution of each variable. Different clustering scenarios were considered for selecting the optimal number of homogeneity groups, and their overall impacts on cluster validation indices were assessed. These three scenarios include dependent variable, independent parameters and the combined variables. The performance of the models was evaluated using the coefficient of determination (R2) and the Nash-Sutcliffe model efficiency. The watersheds were divided into two clusters and multiple regression models were derived for each homogenous region. Eventually, the models with coefficients of determination of 0.78 and 0.84 were used to estimate the mean annual suspended load. It is recommended to study more watersheds with different condition to reach the plurality and improve the quality of these models for estimation of the suspended load in the ungauged watersheds.

کلیدواژه‌ها [English]

  • Estimation of suspended load
  • time series
  • Drainage basin
  • Clustering
  • multiple regression
Adhami M, Najafinejad A, Sadoddin A, Abghari H. 2012. Regional suspended load analysis using watershed characteristics in the Gorgan-Rud and Ghare-Su river basins, Iran. M.Sc. Thesis. College of Range and Watershed Management. Gorgan University of Agricultural Sciences and Natural Resources. 152 p. (In Persian).

Arabkhedri M, Zargar A. 1996. Regression model to estimate sediment of Northern Alborz Basin. 1th Erosion and Sediment National Conference. Tarbiat Modares University, Faculty of Natural Resources and Marine Sciences. 403– 418. (In Persian).

Ashoori M, Yasi M. 2015. Investigation of different evaluation methods of sediment ratting curve using STM software. The 9th National Conference on World Environment, Tehran, Iran.

Bina M, Ranjbaran L, Musavi-Jahromi H. 2010. Modeling of the suspended sediment in the upstream of the Karkheh River in ungauged stations. 8th International River Engineering Conference, Shahid Chamran University. 8 p. (In Persian).

Dalir P, Cash R, Gholami V. 2015. The most important factors related Nvlyd forest roads in the forests of Northern Iran deposition. Journal of Environmental Degradation. 2: 13–23.

Faqfouri Z, Arman N, Faraji M, Khorsandi Z. 2017. Determination of characteristic affecting in sediment using spatial methods (case study: Seyed Abad Basin). Journal of Watershed Engineering and Management. 9(2): 190– 204. (In Persian).

Farahi G, Khodashenas SR, Alizadeh A. 2011. Sediment estimation of northern watersheds of khorasan province using fuzzy regression model. Iran-Watershed Management Science and Engineering. 5: 11–24.

Ghorbani MA, Fakheri Fard A, Nemati S, Tolouei S. 2009. Determining homogeneous regions of spatial distribution of suspended load in Aji-Chai river basin. Water and Soil Science Journal. 2(9): 15– 24. (In Persian).

Grauso S, Pasanisi F, Tebano C, Grillini M, Peloso A. 2018. Investigating the sediment yield predictability in some Italian Rivers by means of hydro-geomorphometric variables. Geosciences. 8: 248– 267

Grubbs F. 1969. Procedures for detecting outlying observations in samples. Technimetrics. 11 (1): 1– 21.

Hakimkhani Sh. 1998. Provide multivariate regression model based on effective characteristic on suspended sediment of lake Urmia watersheds. M.Sc. Thesis. College of Agriculture & Natural Resources, University of Tehran. 212 p (In Persian).

He Q. 1999. A review of clustering algorithms as applied in IR. Graduate School of Library and Information Science University of Illinois at Urbana-Champaign.

Regional Water Company of Hormozgan. 2018. Available from: http://www.hrrw.ir/.

Kheyrfam H, Vafakhah M. 2015. Evaluation of gamma test and Andrew curves to estimate suspended sediment load in southern and southeastern watersheds of the Caspian Sea. Journal of Watershed Management Research. 6 (11): 47– 58. (In Persian).

Kheyrfam H, Mokarram-Kashtiban S. 2019. A regional suspended load yield estimation model for ungauged watersheds. Journal Water Science and Engineering. 11 (4): 328– 337.

Nosrati K, Imeni S, Talari A. 2018. Regional analysis of suspended sediment load using principal components regression method in Sefidrood Drainage Basin. Journal Management System. 71 (3): 809– 827. (In Persian).

Raju KS, Nagesh Kumar D. 2010. Multicriterion analysis in engineering and management. Prentice Hall of India, New Delhi.

Ramezanipour E, Mosaedi A, Mesdaghi M. 2015. Determination of regional relationships of suspended sediment discharge based on watershed characteristic in Mashhad and Nyshabour regions. M.Sc. Thesis. Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad. 139 p. (In Persian).

Roman DC, Vogel RM, Schwarz GE. 2012. Regional regression models of watershed suspended sediment discharge for the eastern United States. Journal of Hydrology. 472: 53– 62.

Rostami M, Ardeshi A, Moradi M, Arabkhedri M. 2002. Predict basin suspended sediments by comparing cluster and fuzzy methods. 6th International River Engineering Conference, Ahwaz. (In Persian).

Tryon RC. 1939. Cluster analysis. New York, McGraw-Hill.

Tucker R, McCollum RC. 1997. Exploratory factor analysis. University of Illinois.

Walling DE, Collins AL, Stroud R. 2008. Tracing suspended sediment and particular phosphorus in catchments. Journal of Hydrology. 350: 274–289.

Waling, DE. 1988. Erosion and sediment yield flood frequency analysis. Hydrological Science Journal, 30: 113–141.

Wang H, Liu Q, Tu Y. 2005. Interpretation of partial least-squares regression models with varimax rotation. Computational Statistics & Data Analysis. 48: 207– 219.

Wang S, Yan Y, Li Y. 2012. Spatial and temporal variations of suspended sediment deposition in the alluvial reach of the upper Yellow River from 1952 to 2007. Catena. 92: 30– 37.