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پهنه بندی سیلاب در نواحی شهری با استفاده از مدل هیدرولوژیکی و اطلاعات میدانی (مطالعۀ موردی: سیل بردسیر، استان کرمان) | ||
اکوهیدرولوژی | ||
مقاله 2، دوره 8، شماره 2، تیر 1400، صفحه 331-344 اصل مقاله (1.94 M) | ||
نوع مقاله: پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ije.2021.314075.1423 | ||
نویسندگان | ||
رضا حسن زاده* 1؛ مهدی هنرمند2؛ مهدیه حسینجانی زاده1؛ صدیقه محمدی1 | ||
1استادیار گروه اکولوژی، پژوهشگاه علوم و تکنولوژی پیشرفته و علوم محیطی، دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته، کرمان، ایران | ||
2دانشیار گروه اکولوژی، پژوهشگاه علوم و تکنولوژی پیشرفته و علوم محیطی، دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته، کرمان، ایران | ||
چکیده | ||
در تحقیق حاضر نقش مدلهای هیدرولوژیکی در GIS و اطلاعات میدانی به عنوان اطلاعات مردمی در پهنهبندی سیلاب و آبگرفتگی ناشی از وقوع سیل در شهر بردسیر، در استان کرمان، بررسی شده است. بهمنظور انجام تحقیق پیش رو، اطلاعات لازم شامل اطلاعات مکانی، توپوگرافی، هیدرولوژی و کاربری اراضی و همچنین، اطلاعات میدانی از طریق پرسشنامه و مصاحبۀ رودررو با مردم ساکن در منطقۀ مطالعاتی گردآوری شد. سپس، نقشۀ محدودۀ آبگرفتگی در شهر با استفاده از مدل HEC-RAS و اطلاعات میدانی تهیه شد که بهترتیب مساحت 13/1 و 25/2 کیلومترمربع آبگرفتگی مناطقی از شهر بردسیر را نشان میدهند. مقایسۀ نقشۀ محدودۀ آبگرفتگی تولیدشده توسط مدل و اطلاعات میدانی با اطلاعات واقعی، بهترتیب صحت کلی 16/59 درصد و 07/80 درصد است که صحت بیشتر اطلاعات میدانی در تعیین محدودۀ آبگرفتگی در منطقۀ مطالعاتی را نشان میدهد. اما با ترکیب خروجی مدل با اطلاعات میدانی، صحت نقشۀ ترکیبی در مقایسه با دادههای واقعی به 27/80 درصد افزایش یافت که این مطلب نشاندهندۀ تأثیر اطلاعات میدانی در مدیریت خطر سیل است و اگر محققان هیدرولوژی اطلاعات میدانی وقوع سیلابهای گذشته در محدودۀ مطالعاتی را گردآوری کرده و آنها را در طراحی مقاطع عرضی و محدودۀ پهنۀ آبگیر رودخانه استفاده کنند، بیشک نتایج حاصل از مدلهای هیدرولوژیکی واقعیتر و کاربردیتر خواهند بود. بنابراین، نتایج این تحقیق نشاندهندۀ اهمیت کاربرد اطلاعات میدانی در ترکیب با مدلهای هیدرولوژیکی بهمنظور کمک به برنامهریزان مدیریت شهری و مدیریت سیل در مناطق تحت تأثیر است. | ||
کلیدواژهها | ||
آبگرفتگی؛ اطلاعات میدانی؛ بردسیر؛ سیل؛ کرمان؛ HEC-RAS | ||
عنوان مقاله [English] | ||
Flood zoning in urban areas using hydrological modelling and survey data: Case study of Bardsir city, Kerman Province | ||
نویسندگان [English] | ||
Reza Hassanzadeh1؛ Mehdi Honarmand2؛ Mahdieh Hossinjanizadeh1؛ Sedighe Mohammadi1 | ||
1Department of Ecology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran | ||
2Department of Ecology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran. | ||
چکیده [English] | ||
This research explores the role of hydrological modelling in geographical information system (GIS) and survey data as crowdsourcing (CS) in flood risk management in the study area of Bardsir, Kerman Province, Iran. In order to conduct this research required spatial data including topography, land-use and hydrology were collected from relevant organization, also crowdsourced data were gathered through interview survey in the study area. Modeled and survey inundation maps of the study area were produced using HEC-RAS and crowdsourced data analysis indicating the Inundation area of 1.13 km2 and 2.25 km2, respectively. The results of comparison of these maps with the real data indicated 59.16 and 80.07 percentage accuracy. The combined inundation map of the HEC-RAS and CS showed an increase in accuracy result to 80.27 percentage indicating the effectiveness of crowdsourced data in flood risk management. Based on these results, researcher can collect crowd sourced data regarding previous flood occurrences in the study area to improve the hydrological modeling in regard to the design of flood plain extent and determining cross section of rivers. As, combined results of hydrological modeling and crowdsourcing can assist decision makers and planers in managing flood risks. | ||
کلیدواژهها [English] | ||
Crowdsourcing, HEC-RAS, Hydrological modelling, Bardsir | ||
مراجع | ||
[1]. Alfieri L, Salamon P, Bianchi A, Neal J, Bates P, Feyen L. Advances in pan-European flood hazard mapping. Hydrological Processes. 2014;28(13):4067-77. [2]. de Moel H, van Alphen J, Aerts JCJH. Flood maps in Europe – methods, availability and use. Nat Hazards Earth Syst Sci. 2009;9(2):289-301. [3]. Baker VR. Geomorphological understanding of floods. Geomorphology and Natural Hazards: Elsevier; 1994. p. 139-56. [4]. Tanoue M, Hirabayashi Y, Ikeuchi H. Global-scale river flood vulnerability in the last 50 years. Scientific reports. 2016;6:36021. [5]. Schanze J, Zeman E, Marsalek J. Flood risk management: hazards, vulnerability and mitigation measures: Springer Science & Business Media; 2007. [6]. Longley PA, Goodchild MF, Maguire DJ, Rhind DW. Geographic Informaiton Systems and Science. ed. n, editor. Hoboken: Jhon Wiley; 2005. [7]. Burnham MW, Dunn CN, Carl RD. HEC's Flood Damage Analysis (HEC-FDA) Program. Building Partnerships2000. [8]. Hydrologic Engineering Center (US). The Hydrologic Modeling System (HEC-HMS). US Army Corps of Engineers, Hydrologic Engineering Center,: 2001. [9]. Scharffenberg WA, Fleming MJ. Hydrologic modeling system HEC-HMS: user's manual. US Army Corps of Engineers, Hydrologic Engineering Center,, 2006. [10]. Shen J, Parker A, Riverson J. A new approach for a Windows-based watershed modeling system based on a database-supporting architecture. Environmental Modelling & Software. 2005;20(9):1127-38. [11]. Danish Hydraulic Institute (DHI). A modeling system for Rivers and channels (MIKE 11), Reference manual and User Guide. Denmark: DHI Water and Environment,, 2007. [12]. Hill M. Flood plain delineation using the HEC-GeoRAS extension for Arcview. Brigham Young University, 514p. 2001. [13]. Demir V, Kisi O. Flood hazard mapping by using geographic information system and hydraulic model: Mert River, Samsun, Turkey. Advances in Meteorology. 2016;2016. [14]. Solaimani K. Flood forecasting based on geographical information system. African Journal of Agricultural Research. 2009;4(10):950-6. [15]. Gichamo TZ, Popescu I, Jonoski A, Solomatine D. River cross-section extraction from the ASTER global DEM for flood modeling. Environmental Modelling & Software. 2012;31:37-46. [16]. Eum H-I, Simonovic SP. City of London: Vulnerability of Infrastructure to Climate Change. 2009. [17]. Kumar N, Kumar M, Sherring A, Suryavanshi S, Ahmad A, Lal D. Applicability of HEC-RAS 2D and GFMS for flood extent mapping: a case study of Sangam area, Prayagraj, India. Modeling Earth Systems and Environment. 2020;6(1):397-405. [18]. Eftekhari ar, pourtaheri m, sadeghlou t, sojasi qidari h. Analyzing the Effective Factor in Participatory Flood Management in Rural Area (Case Study: flooded villages of Gorganrud Basin in Golestan Province). Journal of Rural Research. 2010;1(2):-. [19]. Ghafari G, Amini A. Managing flood plain using GIS: case study of Ghezeloozan river. Geographical Space. 2010;10(32):117-34. [20]. Eftekhari A, Salajegheh A, Hossini. S. Evaluation of flood zoning based on Manning's roughness coefficient: case study of Atrak river Natural Geography Journal. 2011;20:91-106. [21]. Sheikh Alishahi N, Jamali, AA., Hassanzadeh., M. Flood zoning by hydrological river model: case study of Menshad watershed, Yazd province. Geographical Space. 2016;16(53):77-96. [22]. Karimil firoozjaei M, Abdolaho kakroodi A, Jolodar niyaraki M. Preparing a flood risk map based on the flow energy by using geographical information system Case study: Nekaroud River. Quantitative Geomorphological Research. 2018;5(4):159-75. [23]. Shafiei Motlagh K, Ebadati N. Flood Zoning and Hydraulic Behavior Simulation Using HEC RAS in (GIS) Case Study: Maroon River - Southwestern Iran. Iranian journal of Ecohydrology. 2020;7(2):397-409. [24]. Brabham DC. Crowdsourcing as a Model for Problem Solving: An Introduction and Cases. Convergence: The International Journal of Research into New Media Technologies. 2008;14(1):75-90. [25]. Richter K-F, Winter S. Citizens as Database: Conscious Ubiquity in Data Collection Advances in Spatial and Temporal Databases. In: Pfoser D, Tao Y, Mouratidis K, Nascimento M, Mokbel M, Shekhar S, et al., editors. Lecture Notes in Computer Science. 6849: Springer Berlin / Heidelberg; 2011. p. 445-8. [26]. Milo T. Crowd-Based Data Sourcing Databases in Networked Information Systems. In: Kikuchi S, Madaan A, Sachdeva S, Bhalla S, editors. Lecture Notes in Computer Science. 7108: Springer Berlin / Heidelberg; 2011. p. 64-7. [27]. Eisnor D. What is neogeography anyway? : Platial News and Neogeography; 2006 [September 14, 2014]. Available from: http://platial.typepad.com/news/2006/05/what_is_neogeog.html. [28]. Goodchild M. Citizens as sensors: the world of volunteered geography. GeoJournal. 2007;69(4):211-21. [29]. Hong M. Utilization of Crowdsourced Maps in Catastrophic Disasters: San José State University; 2014. [30]. Morrow N, Mock N, Apapendieck A, Kocmich N. Independent Evaluation of the Ushahidi Haiti Project. Development Information systems International, 2011 2011. Report No. [31]. Gebremedhin ET, Basco-Carrera L, Jonoski A, Iliffe M, Winsemius H. Crowdsourcing and interactive modelling for urban flood management. Journal of Flood Risk Management. 2020;13(2):e12602. [32]. Ghosh S, Huyck CK, Greene M, Gill SP, Bevington J, Svekla W, et al. Crowdsourcing for Rapid Damage Assessment: The Global Earth Observation Catastrophe Assessment Network (GEO-CAN). Earthquake Spectra. 2011;27(S1):S179-S98. [33]. Barrington L, Ghosh S, Greene M, Har-Noy S, Berger J, Gill S, et al. Crowdsourcing earthquake damage assessment using remote sensing imagery. Annals of geophisycs. 2012;54(6):680 - 7. [34]. Meier P, Munro R. The Unprecedented Role of SMS in Disaster Response: Learning from Haiti. SAIS Review, Johns Hopkins University Press. 2010;30(2):91-103. [35]. Poser K, Dransch D. Volunteered geographic information for disaster management with application to rapid flood damage estimation. Geomatica. 2010;64(1):89-98. [36]. Middleton S, Zielinski A, Necmioğlu Ö, Hammitzsch M. Spatio-Temporal Decision Support System for Natural Crisis Management with TweetComP1. In: Dargam F, Hernández JE, Zaraté P, Liu S, Ribeiro R, Delibašić B, et al., editors. Decision Support Systems III - Impact of Decision Support Systems for Global Environments. Lecture Notes in Business Information Processing. 184: Springer International Publishing; 2014a. p. 11-21. [37]. Shelton T, Poorthuis A, Graham M, Zook M. Mapping the data shadows of Hurricane Sandy: Uncovering the sociospatial dimensions of ‘big data’. Geoforum. 2014;52(0):167-79. [38]. Barbier G, Zafarani R, Gao H, Fung G, Liu H. Maximizing benefits from crowdsourced data. Comput Math Organ Theory. 2012:1-23. [39]. Hassanzadeh R, Nedovic-Budic Z. Identification of Earthquake Disaster Hot Spots with Crowd Sourced Data. In: Zlatanova S, Peters R, Dilo A, Scholten H, editors. Intelligent Systems for Crisis Management. Lecture Notes in Geoinformation and Cartography: Springer Berlin Heidelberg; 2013. p. 97-119. [40]. Mehr News. Breakdown of earth dam of Hanafieh 2017. Available from: mehrnews.com/news/3910333 [41]. Isna News. Bardsir: a flooded urban area 2017 [20 Feb 2017]. Available from: https://www.isna.ir/photo/95120201385/. [42]. Public Relation of Kerman Medical University. Total damage to emergency management office due to flood in Bardisir city. 2017. [43]. Bonner V, Brunner G, Jensen M. HEC river analysis system (HEC-RAS). Hydraulic Engineering, ASCE. 1994:376-80. [44]. Hydrologic Engineering Center (U.S.). HEC river analysis system (HEC-RAS) US Army Corps of Engineers, : Hydrologic Engineering Center,, 1994. [45]. Congalton RG, Green K. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton, FL, USA: CRC Press; 2009. [46]. Petersson L, ten Veldhuis M-C, Verhoeven G, Kapelan Z, Maholi I, Winsemius HC. Community Mapping Supports Comprehensive Urban Flood Modeling for Flood Risk Management in a Data-Scarce Environment. Frontiers in Earth Science. 2020;8(304). | ||
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