| تعداد نشریات | 287 |
| تعداد نشریات سازمان | 85 |
| تعداد شمارهها | 3,159 |
| تعداد مقالات | 35,108 |
| تعداد مشاهده مقاله | 50,529,961 |
| تعداد دریافت فایل اصل مقاله | 90,478,428 |
تحلیل عاملهای مؤثر بر شدت سیل خیزی در ایران | ||
| پژوهش های آبخیزداری | ||
| مقاله 6، دوره 34، شماره 1 - شماره پیاپی 130، فروردین 1400، صفحه 59-73 اصل مقاله (872.44 K) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmej.2020.342597.1330 | ||
| نویسندگان | ||
| رحیم کاظمی* 1؛ جهانگیر پرهمت2 | ||
| 1استادیار پژوهشکدهی حفاظت خاک و آبخیزداری، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران | ||
| 2استاد پژوهشکدهی حفاظت خاک و آبخیزداری، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران | ||
| چکیده | ||
| شناخت پدیدهی سیل و عاملهای مؤثر بر آن پیشنیاز مهار و مدیریتکردن آن است. این پدیده که متأثر از عاملهای آبشناسی، اقلیمی و گیتاشناسی آبخیز است همواره یکی از موضوعهای مهم در آبشناسی بوده است. در این پژوهش ابتدا با روی همگذاشتن نقشهی اقلیم کشور بر اساس نظام طبقهبندی دومارتن با مرز حوزهها، آبخیزهای هر منطقهی اقلیمی تفکیک کرده و 314 ایستگاه آبسنجی با دادههای مناسب از دورهی مشترک دادهبرداری 1355-1390 در شش منطقهی اقلیمی انتخاب شد. آبدهی بیشینهی لحظهیی با دورهی بازگشت50 ساله محاسبه شد. پانزده سنجهی آبشناسی، اقلیمی، و گیتاشناسی مؤثر بر شدت سیلخیزی شامل ارتفاع متوسط، مساحت حوزه، ضریب گراویلیوس، شیب حوزه و طول رودخانهی اصلی، بارش متوسط سالانه، متوسط تعداد روزهای بارانی، شاخص جریان پایه، ضریب افت آبنگار جریان، درصد بیتجاوز Q2,Q5,Q10,Q20، شمارهی منحنی، و نفوذپذیری برای هر حوزه محاسبه شد. پس از بهمعیار کردن دادهها، برای انتخابکردن مهمترین عاملهای مستقل مؤثر بر شدت سیلخیزی در هر منطقهی اقلیمی، تحلیل عاملی جداگانه انجام و رابطههای وایازی ﺑﯿﻦ شاخص سیلخیزی و ﻋاﻣﻞهای اﻧﺘﺨﺎبشده در منطقههای ﻣﺨﺘﻠﻒ اﻗﻠﯿﻤﯽ اﺳﺘﺨﺮاج و ﺗﺤﻠﯿﻞ کرده ﺷﺪ. نتیجهها نشان داد که سنجههای بهکاررفته در همهی منطقههای اقلیمی بیش از 74% از پراکنش دادهها را توجیه میکند. سنجههای مشترک در عامل اول همهی منطقههای اقلیمی، مولفههای مختلف جریان شامل شاخص جریان پایه، ضریب افت آبنگار، شاخصهای منحنی تداوم جریان، بههمراه سنجههای مرتبط با مشخصهی ذاتی حوزه مانند شمارهی منحنی و نفوذپذیری بود. شاخصهای بخش پرآبی منحنی تداوم جریان در همهی منطقههای اقلیمی در مرتبهی اول تاثیرگزاری و در قالب عامل اول بود، که برای برآورد و پیشبینی کردن سیلخیزی توصیه میشود. بهنجارﺑﻮدن ﺗﻮزﯾﻊ ﺧﻄﺎﻫﺎ در رابطههای وایازی همهی منطقههای اﻗﻠﯿﻤﯽ و ضریب دوربین-واتسن بین 1/5 ﺗﺎ 2/5 بیانگر ممکنبودن اعتماد به رابطهها برای برآوردکردن شدت سیلخیزی در حوزههای بی آمار است. | ||
| کلیدواژهها | ||
| برآورد؛ تحلیل عاملی؛ مشخصه های جریان؛ منطقههای اقلیمی؛ منحنی تداوم جریان | ||
| عنوان مقاله [English] | ||
| An Analysis of the factors Affecting Flooding Severity in Iran | ||
| نویسندگان [English] | ||
| Rahim Kazemi1؛ Jahangir Porhemmat2 | ||
| 1Assistant Prof., Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization, Tehran, Iran | ||
| 2Prof., Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization, Tehran, Iran | ||
| چکیده [English] | ||
| Understanding the flooding phenomenon and its effective factors is an essential prerequisite of its control and management. This phenomenon is influenced by hydrological, climatic and physiographic factors, as it has always been one of the most important issues in hydrology. Using the overlapping of the climate and the border maps of the country, catchments of each climatic region were demarcated. Furthermore, 314 hydrometry stations with a common period (1976-2011) in six climatic zones were selected. The instantaneous peak discharge value was calculated for a 50-year return period. 15 hydrological, climatic and physiographic parameters affecting the flood severity, namely average altitude, catchment area, the Gravelius coefficient, the slope, the main river length, the annual average precipitation, the average number of rainy days, the base flow index (BFI), the hydrograph recession coefficient (K), the curve number (CN), the permeability and the flow duration curve indices (FDC indices) of, Q2, Q5, Q10, Q20, were calculated for each catchment. The factor analysis after data standardization was performed in order to select the most important independent factors affecting flooding severity for each climatic region and the regression between the Flooding severity index and the selected factors in different climate zones were extracted and analyzed. Results indicated that the parameters used in all of the climatic regions explained more than 74% of the variance of the data. Common parameters in the first class of effective factors in all of the climatic zones were different flow parameters of (BFI, K, FDC indices), along with some parameters that were related to the intrinsic characteristic of the catchment, such as the CN and permeability. The flow exceedance value of, Q2, Q5, Q10, Q20 in all of the climatic zones were ranked first and may be recommended for estimation and prediction in the ungauged catchment. The normal distribution of errors and the coefficient of Durbin Watson (between 1.5 and 2.5) reflect the confidence of the regression equations to estimate the Flooding severity in the ungauged catchments in the different climatic zones. | ||
| کلیدواژهها [English] | ||
| Climate zone, estimation, factor analysis, flood intensity, flow characteristics | ||
| مراجع | ||
|
Abedini M, Khoshkhoy- Delshad A. 2016. Investigation of factors affecting on flood in Hovigh catchment using ANP model, First International Conference on Natural Hazards and Environmental Crisis of Iran, Solution and Challenges, Water Resource Center, Shahre-Kord University, pp. 1–20. (In Persian). Arabkhedri M. 1995. Estimation of flood using catchment characteristics, proceeding of water resource management, Regional Conference, Isfahan. Industrial University of Isfahan, pp. 213–227. (In Persian). Bar‐Kochba Y, Simon AL. 1972. Factors affecting floods from watersheds in humid region of northeastern OHAIO. Journal of the American Water Resources Association, 8(6):1235–1245. Benson MA. 1963. Factors influencing the occurrence of floods in a humid region of diverse terrain, US Department of the Interior, Geological Survey, 1580-B: 1–64. Berghuijs WR, Woods RA, Hutton CJ, Sivapalan M. 2016. Dominant flood generating mechanisms across the United States. Geophysical Research Letters, 43(9): 4382–4390. Blöschl G, Gaál L, Hall J, Kiss A, Komma J, Nester T, Salinas JL. 2015. Increasing river floods: Fiction or reality? Wiley Interdisciplinary Reviews. Water. 2(4): 329–344. Bouchard JRTJ, Loehlin JC. 2001. Genes, evolution, and personality. Behavior Genetics, 31(3):243–273. Dastorani MT, Hayatzade M. 2010. Evaluation of the most important factors effecting maximum flood discharge using sensivity analysisis of empirical formulae. Arid Biom Scientific and Research Journal, 1(1):1–12. (In Persian). Dastoorani M, Hayatzadeh M, Fathzadeh A, Hakimzadeh M, 2014. Review the efficiency of empirical relations on estimating the peak flow rate of flood in arid areas of central Iran, 12(36):145–160. (In Persian). Gao H, Cai H, Duan Z. 2018. Understanding the impacts of catchment characteristics on the shape of the storage capacity curve and its influence on flood flows. Hydrology Research, 49(1): 90–106. Gerbing DW, Hamilton JG. 1996. Viability of exploratory factor analysis as a precursor to confirmatory factor analysis. Structural Equation Modeling: A Multidisciplinary Journal, 3(1):62–72. Guhathakurta P, Sreejith OP, Menon PA. 2011. Impact of climate change on extreme rainfall events and flood risk in India. Journal of Earth System Science, 120(3): 359–373. Hashemi M, Hashemi A, Rezaei P, Hashemi A, 2012. Investigation of the most important flooding factors of Zar-Abad catchment, 3Th National Conference on Desertification and Sustainable Development of Iran, Arak, Azad University, pp.1180–1185. (In Persian). Jalali H. 1986. Investigation of Iran floods, First Conference on Hydrology of Iran. Ministry of Energy Press, pp. 37–102, (In Persian). Kazemi R, Porhemmat J, Sharifi F. 2018. Investigation and determination of factors affecting the shape of the flow duration curve in different climates of Iran, Journal of Water and Soil Conservation. 25(1): 85–105. (In Persian). Khairizade AAM, Maleki J, Amoonia H. 2013. Zooning of flood risk potential occurrence in Mardaghchay Basin using ANP model. Quantative Geomorphologic Research, 1(3):39–56. (In Persian). Langhammer J, Vilímek V. 2008. Landscape changes as a factor affecting the course and consequences of extreme floods in the Otava river basin, Czech Republic. Environmental Monitoring and Assessment, 144(1–3): 53–66. Mahdavi M, Hashemi A. 1997. Determination of medium discharge from physical factors in Semnan Province, Pajohesh and Sazandegi, 10(36):18–21. (In Persian). Mahdavi M, Jamali A, Ayoubzadeh SA, Vafakhah M. 2004. A sensitivity study of some hydrologic empirical methods for estimating flood peak as related to drainage area in watersheds in Iran, Iranian Journal of Natural Resources, 57(3): 403 –414. (In Persian). Mahdavi M. 1999. Flood management, first stage studies, the United Nations Development Program (UNDP), the national plan for the prevention and control of natural disasters, ministry of the interior, Iran. 110 p. (In Persian). Malekinezhad H, Kowsari MR. 2009. Sensitivity analysis and relative importance assessment of the main factors on peak discharge in curve number-scs method, Iranian Journal of Watershed Management Science, 2(5): 31–40. (In Persian). Milly PC, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP, Stouffer RJ. 2008. Stationarity is dead: Whither water management? Science, 319(5863):573–574. Montanari A, Young G, Savenije HHG, Hughes D, Wagener T, Ren LL, ... & Blöschl G. 2013. Panta Rhei—everything flows: change in hydrology and society—the IAHS scientific decade 2013–2022. Hydrological Sciences Journal, 58(6):1256–1275. Mosaffaie J, Malekinezhad H. 2017. Peak flow estimation in ungagged catchments using flow index. Iran Watershed Management Science and Engineerting, 11(37):85–89. (In Persian). Najafi A, Nasri M. 2010. Effective factors in flood of Esfahan-Sirjan watershed employing factor analysis method, Geography and Environmental Planning (University of Isfahan), 20(4-36): 101–118. (In Persian). Nie C, Li H, Yang L. 2012. Spatial and temporal changes in flooding and the affecting factors in China. Nat Hazards 61(2): 425–439. Pohl B, Macron C, Monerie PA. 2017. Fewer rainy days and more extreme rainfall by the end of the century in Southern Africa. Scientific Reports, 7(1): 1–7. Porhemmat J. 2016. A model on investigation on flood hazard over watersheds of Iran. Iran Watershed Management Science and Engineerting, 10(34):1–14. (In Persian). Porhemmat J .2017. Preparing and integrating digital data and maps of 7Th order watersheds and developing spatial, temporal and thematic database related to water capacity. (SCWMRI) Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization, Tehran, Iran. Code No. 014-29-29-9451-94003. 120 p. (In Persian). Porhemmat J, Kazemi R. 2017. Regional modeling and evaluation or runoff coefficient in Karkhe basin, Journal of Watershed Mmanagement Research, 8(15): 82–91. (In Persian). Stonestrom DA, Scanlon BR, Zhang L. 2009. Introduction to special section on impacts of land use change on water resources. Water Resources Research, 45(7):1–3. | ||
|
آمار تعداد مشاهده مقاله: 1,305 تعداد دریافت فایل اصل مقاله: 1,052 |
||