بررسی نقش عوامل طبیعی و انسانی بر تشدید وقوع سیل و آبگرفتگی در شهر کلات

نوع مقاله : مقالات پژوهشی

نویسندگان

• سارا عطاران ¹
• ابوالفضل مساعدی ²
• حمدالله سجاسی قیداری ³

¹ گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه فردوسی مشهد

² دانشگاه فردوسی مشهد

³ جغرافیا و برنامه ریزی روستایی، دانشگاه فردوسی مشهد، مشهد، ایران

https://doi.org/10.22067/jsw.2022.77163.1173

چکیده

علی‌رغم توسعه علم و فن‌آوری، شواهد نشان می‌دهند که آسیب‌پذیری نسبت به سیل در مقایسه با گذشته افزایش یافته‌است. فعالیت‌های انسانی، تاثیر به‌سزایی در وقوع سیل و خسارات ناشی از آن دارد. به این منظور نیاز است تاثیرات متقابل سیستم انسانی و هیدرولوژیک به دقت بررسی شود. پژوهش حاضر باهدف بررسی تاثیر عوامل طبیعی و انسانی بر تشدید وقوع سیل و آبگرفتگی در شهر کلات (واقع در استان خراسان رضوی) انجام شده‌است. این شهر هرساله شاهد سیل‌هایی است که خسارات زیادی به ساختمان‎های مسکونی، اداری و بناهای تاریخی شهر وارد می‌کند. برای این منظور تاثیر تغییر شدت بارش و تغییر کاربری اراضی بر دبی اوج رواناب بررسی شد، به‌طوری که تغییرات دبی اوج نسبت به افزایش و کاهش 20 درصدی شدت بارندگی و همچنین افزایش و یا کاهش عدد منحنی (CN) براورد شد. همچنین با ارائه چند سناریو، تاثیر تغییر در رویکردهای مدیریتی به منظور کاهش ضریب‌زبری با مدل‌سازی پهنه سیل و با استفاده از نرم‌افزار HEC-RAS مورد آزمون قرار گرفت. از‌ طرفی به منظور تعیین مهم‌ترین عوامل تاثیرگذار در تشدید وقوع سیل و آبگرفتگی، پرسشنامه‌هایی تهیه و نظرات کارشناسی و فنی متخصصین و کارشناسان اجرایی مورد تحلیل قرار گرفت. پرسشنامه‌های مذکور بر اساس طیف لیکرت پنج امتیازی طراحی شد، به‌گونه‌ای که عدد 5 نشان‌دهنده بیش‌ترین تاثیر و عدد 1 بیان‌گر کم‌ترین تاثیر می‌باشد. نتایج نشان داد که تاثیر تغییرات عدد منحنی بر میزان دبی اوج حدود 37 برابر بیشتر از تاثیر تغییرات بارش است. همچنین بررسی سناریوهای مختلف به منظور اصلاح ضریب‌زبری نشان می‌دهد که با انجام برنامه‌های مدیریتی مساحت پهنه سیل در بعضی از زیر حوضه‌ها تا 15درصد می‌تواند کاهش یابد. تحلیل نتایج پرسشنامه‌ها نشان می‌دهد که مهم‌ترین عوامل درون‌شهری در تشدید وقوع سیل در داخل شهر کلات عوامل "فعالیت‌های مردم محلی" با میانگین امتیاز 59/3، و در خارج از شهر عوامل "مدیریتی" با میانگین امتیاز 79/3 هستند.

کلیدواژه‌ها

• ضریب‌زبری
• کلات
• مدیریت سیل
• هیدرولوژی اجتماعی
• هیدرولوژی شهری

20.1001.1.20084757.1401.36.4.1.9

موضوعات

• علوم آب

عنوان مقاله [English]

Investigating the Role of Natural and Human Factors on Intensification of Floods and Flooding in Kalat City

نویسندگان [English]

• S. Attaran ¹
• A. Mosaedi ²
• H. Sojasi Qeydari ³

¹ Water Science and Engineering Department Agriculture Faculty Ferdowsi University of Mashhad Mashhad Iran

² Water Science and Engineering Department Agriculture Faculty, Ferdowsi University of Mashhad Mashhad Iran Postal Code: 91779-48978

³ Ferdowsi University of Mashhad

چکیده [English]

Introduction
The world population has grown rapidly over the last 150 years and continues to do so, resulting in impacts on hydrologic resources at both a local and global scale (Yang et al., 2012). The competition for water between humans and ecosystems leads to complex interactions between hydrologic and social systems (liu et al., 2015). From the beginning of human history, it is located in floodplains. Floods can have large societal impacts, such as severe damage to urban areas, which are expected to grow around the world (Alfieriet al., 2018). In traditional hydrology, humans are either conceptualized as an external force to the system under study or taken into account as boundary conditions (Peel and Blöschl, 2011). Sivapalan et al. (2012) proposed a new model for investigating the interactions of the hydrological system and the social system. It explores the procedure coupled human-water system evolves and possible trajectories of its co-evolution, including the possibility of generating emergent, even unexpected, behaviors. Socio-hydrology must strive to be a quantitative science. There are several methods to control and mitigate flood risk, one of these methods is flood zoning (Jha et al., 2012). In last two decates, The Kalat city is flooded almost every year and many houses and historical sites in the city are damaged. Therefore, the main purpose of thisWe paper is to show investigated how changing human behavior with nature can affect the behavior of the natural system.
Method and Materials
Kalat city located in 59° 43' 23" to 59° 47' 41" northern latitude and 36° 59' 35" to 37° 00' 05" eastern longitude. The city is divided into 11 sub-basins. The city has experienced fast and inappropriate urbanization over the past few years. To collect our data, the annual reports of the Regional Water Organization and the Environment Organization of Khorasan Province were used.
SCS method was used to estimate the runoff peak discharge. Precipitation has been estimated for seven return periods: 2, 5, 10, 25, 50, 100, and 200 years. In this study, to analyze the sensitivity of runoff, we considered precipitation and curves number from 20% less to 20% more than the actual values in the study basin (at intervals of 5 %). We used the Cowan method to determine the roughness coefficient in this study. HEC-RAS model has been used for flood zoning. To determine the impact of various factors on the intensification of floods in Kalat city, we obtained questionnaires from relevant authorities. Likert scale was used to measure the results of the questionnaires. We prepared two questionnaires; first one is related to the inner city zone and includes the factors that intensify the occurrence of floods inside the city of Kalat, and it was classified into the following parts: 1) Local community 2) Managerial 3) Physical; and the second one includes the factors that intensify the flood in the upper part of Kalat city. We classified these factors into three parts: 1) Non-local community 2) Managerial 3) Environmental .
Results and Discussion
Results of sensitivity analyzes demonstrated that land-use and land cover change had a further effect on peak discharge. In sub-basin 1, by 20% increase in the curve number, the level of peak dumping increased by more than 111%, with a return period of 2 year; while a 20% increase in precipitation, in the same return period, rises the peak discharge only 3%. The peak discharge time in some sub-basins was brief due to the presence of impermeable surfaces, so that in sub-basins 4, 6, 7, and 8, the peak discharge time was less than 30 minutes. These results highlight the dangers of these floods and the need for proper flood planning and management in these sub-basins. The results of the Manning coefficient demonstrated that we can reduce flood damage by applying management measures in the future, as well as paying attention to the feedback between urbanization and the flood zone. Roughness control by applying management programs can reduce the area of flood zones to 0.1 square kilometers. In this case, buildings should be removed from the river, and there should be no structure in the path of the river. According to the questionnaires in the inner city part, the most fundamental factor in intensifying the flood damage was related to “activities of local people” with the average of 3.59. In the upper part of the city, the most influential factors were ascribed to “managerial factors” with the average of 3.79.
Conclusion
In a general conclusion, it can be concluded that the role of human factors in the occurrence and intensification of floods was much greater than rainfall. Therefore, in order to manage and control floods, it is necessary to prevent the change of land use and the reduction of permeability. And management programs should be aimed at increasing surface permeability. We suggest that more research be done on the role of economic and social factors in increasing flood risk in other climate zones.

کلیدواژه‌ها [English]

• Flood management
• Kalat city
• Roughness coefficient
• Social hydrology
• Urban hydrology

مراجع

1. Aerts, J.C., Botzen, W.W., Emanuel, K., Lin, N., De Moel, H., & Michel-Kerjan, E.O. (2014). Evaluating flood resilience strategies for coastal megacities. Science 344: 473-475. https://doi.org/10.1126/science.1248222.
2. Alizadeh, A. (2007). Principles of applied hydrology. The seventh edition. (In Persian)
3. Alfieri, L., Dottori, F., Betts, R., Salamon, P., & Feyen, L. (2018). Multi-model projections of river flood risk in Europe under global warming. Climate 6: https://doi.org/10.3390/cli6010006.
4. Asadi, R., Karami, M., & Jafari, Gh. (2015). Investigating the main factors of aggravating flood damage in Iran and its control methods. 10^th International Seminar on River Engineering, Ahvaz.
5. Badri, A., Sadeghloo, T., & Kazemi, N. (2018). Crisis management (with emphasis on rural areas). Noor e Elm Publications, Tehran. (In Persian)
6. Baioni, D. (2011). Human activity and damaging landslides and floods on Madeira Island. Natural Hazards and Earth System Sciences 11: 3035-3046. https://doi.org/10.5194/nhess-11-3035-2011.
7. Bala, J. (2016). Contribution of SPSS in Social Sciences Research. International Journal of Advanced Research in Computer Science
8. Beshir, AA., & Song, J. (2021). Urbanization and its impact on flood hazard: the case of Addis Ababa, Ethiopia. Natural Hazards 109(1): 1167-1190. https://doi.org/10.1007/s11069-021-04873-9.
9. Blair, P., & Buytaert, W. (2016). Socio-hydrological modelling: a review asking" why, what and how?". Hydrology and Earth System Sciences 20: 443-478. https://doi.org/10.5194/hess-20-443-2016.
10. Chan, SW., Abid, SK., Sulaiman, N., Nazir, U., & Azam, K.A. (2022). systematic review of the flood vulnerability using geographic information system. Heliyon https://doi.org/10.1016/j.heliyon.2022.e09075.
11. Cowan, W.L. (1956). Estimating hydraulic roughness coefficients. Agricultural Engineering 37: 473-475.
12. CRED, U. (2015). The human cost of weather related disasters. The United Nations Office for Disaster Risk Reduction (UNISDR). org/10.1017/CBO9781107415324, 4.
13. Daliran firooz, H., Mokhtari, F., Soltani, S., & Moosavi, A. (2015). Evaluation of flood damage in Ghamsar and Qahroud watersheds using HEC-FIA software. Journal of Soil and Water Sciences 19: 63-75. (In Persian)
14. Dankers, R., Arnell, N.W., Clark, D.B., Falloon, P.D., Fekete, B.M., Gosling, S.N., & Satoh, Y. (2014). First look at changes in flood hazard in the Inter-Sectoral Impact Model Intercomparison Project ensemble. Proceedings of the National Academy of Sciences 111: 3257-3261. https://doi.org/10.1073/pnas.1302078110.
15. Diaconu, DC., Costache, R., & Popa, MC. (2021). An overview of flood risk analysis methods. Water 13(4): 474. https://doi.org/10.3390/w13040474.
16. Di Baldassarre, G., Montanari, A., Lins, H., Koutsoyiannis, D., Brandimarte, L., & Blöschl, G. (2010). Flood fatalities in Africa: from diagnosis to mitigation. Geophysical Research Letters 37(22). https://doi.org/10.1029/2010GL045467.
17. Di Baldassarre, G., Viglione, A., Carr, G., Kuil, L., Salinas, J., & Blöschl, G. (2013). Socio-hydrology: conceptualising human-flood interactions. Hydrology and Earth System Sciences 17: 3295-3303. https://doi.org/10.1002/2014WR016416.
18. Dougherty, M., Dymond, R.L., Grizzard Jr, T.J., Godrej, A.N., Zipper, C.E., & Randolph, J. (2007). Quantifying long-term hydrologic response in an urbanizing basin. Journal of Hydrologic Engineering 12: 33-41. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:1(33).
19. Du, J., Qian, L., Rui, H., Zuo, T., Zheng, D., Xu, Y., & Xu, C.-Y. (2012). Assessing the effects of urbanization on annual runoff and flood events using an integrated hydrological modeling system for Qinhuai River basin, China. Journal of Hydrology 464: 127-139. https://doi.org/10.1016/j.jhydrol.2012.06.057.
20. Eftekhari, A., Salajeghe, A., & Hoseini, A. (2011). Evaluation of flood zoning with changes in roughness coefficient Case study: Atrak river. Journal of Natural Geography 22: 91-106. (In Persian)
21. Feng, B., Zhang, Y., & Bourke, R. (2021). Urbanization impacts on flood risks based on urban growth data and coupled flood models. Natural Hazards 106(1): 613-627. http://creativecommons.org/licenses/by/4.0/.
22. Ghahraman, B., & Abkhezr, H. (2004). Correction and relations of intensity-duration-frequency of rainfall in Iran. Soil and Water Sciences 8(2): 1-14. (In Persian). http://20.1001.1.24763594.1383.8.2.1.4.
23. Ghaljaee, F., Naderifar, M., & Goli, H. (2017). Snowball, a purposive sampling method in qualitative research. Strides in Development of Medical Education.
24. Handayani, W., Chigbu, UE., Rudiarto, I., & Putri, IHS. (2020). Urbanization and Increasing Flood Risk in the Northern Coast of Central Java—Indonesia: An Assessment towards Better Land Use Policy and Flood Management. Land 9(10): 343. https://doi.org/10.3390/land9100343.
25. Harrower, M.J. (2010). Geographic Information Systems (GIS) hydrological modeling in archaeology: an example from the origins of irrigation in Southwest Arabia (Yemen). Journal of Archaeological Science 37: 1447-1452. https://doi.org/10.1016/j.jas.2010.01.004.
26. Hodgkins, G., Dudley, R., Archfield, S.A., & Renard, B. (2019). Effects of climate, regulation, and urbanization on historical flood trends in the United States. Journal of Hydrology 573: 697-709. https://doi.org/10.1016/j.jhydrol.2019.03.102.
27. Jha, A.K., Bloch, R., & Lamond, J. (2012). Cities and flooding: a guide to integrated urban flood risk management for the 21st century. World Bank Publications.
28. Junk, W.J., Bayley, P.B., & Sparks, R.E. (1989). The flood pulse concept in river-floodplain systems. Canadian Special Publication ofF and Aquatic Sciences 106: 110-127.
29. Khorasan Razavi water technical report. (2014). Report of Khorasan Razavi floods (2014-2015).
30. Ma, M., Liu, C., Zhao, G., Xie, H., Jia, P., Wang, D., & Hong, Y. (2019). Flash flood risk analysis based on machine learning techniques in the Yunnan Province, China. Remote Sensing 11: https://doi.org/10.3390/rs11020170.
31. Marcus, W.A., Roberts, K., Harvey, L., & Tackman, G. (1992). An evaluation of methods for estimating Manning's n in small mountain streams. Mountain Research and Development 227-239. https://doi.org/10.2307/3673667.
32. Mohamadi, J., Khoda Rahmi, Y., & Golabi, M. (2017). Estimation of flood hydrograph with HEC-HMS model and simulation of flood zoning using HEC-RAS model Case study: Bakhtiar catchment, Karun river. The second national hydrological conference of Iran, Shahrekord. (In Persian)
33. Munawar, HS., Hammad, AW., & Waller, ST. (2022). Remote Sensing Methods for Flood Prediction: A Review. Sensors 22(3): 960. https://doi.org/10.3390/s22030960.
34. Nardi, F., Annis, A., & Biscarini, C. (2018). On the impact of urbanization on flood hydrology of small ungauged basins: The case study of the Tiber river tributary network within the city of Rome. Journal of Flood Risk Management 11: S594-S603. https://doi.org/10.1111/jfr3.12186.
35. (2010). National Engineering Handbook Hydrology. USDA Soil Conservation Service
36. Ogden, F.L., Raj Pradhan, N., Downer, C.W., & Zahner, J.A. (2011). Relative importance of impervious area, drainage density, width function, and subsurface storm drainage on flood runoff from an urbanized catchment. Water Resources Research 47(12). https://doi.org/10.1029/2011WR010550.
37. Opperman, J.J., Galloway, G.E., Fargione, J., Mount, J.F., Richter, B.D., & Secchi, S. (2009). Sustainable floodplains through large-scale reconnection to rivers. Science 326: 1487-1488. https://doi.org/10.1126/science.1178256.
38. Peel, M.C., & Blöschl, G. (2011). Hydrological modelling in a changing world. Progress in Physical Geography 35: 249-261. https://doi.org/10.1177/0309133311402550.
39. Qi, W., Ma, C., Xu, H., Chen, Z., Zhao, K., & Han, H. (2021). A review on applications of urban flood models in flood mitigation strategies. Natural Hazards 108(1): 31-62. https://doi.org/10.1007/s11069-021-04715-8.
40. Regional Water Company of Khorasan Razavi. (2015). Comprehensive Studies of Floods in Kalat. (In Persian)
41. Romali, NS., Yusop, Z., & Ismail, AZ. (2018). Application of HEC-RAS and Arc GIS for floodplain mapping in Segamat town, Malaysia. GEOMATE Journal 15(47): 7-13. https://doi.org/10.21660/2018.47.3656.
42. Roodaki, S., & Azizian, A. (2020). Uncertainty analysis due to the application of different infiltration estimation methods on the performance of the HEC-HMS rainfall-runoff model using the GLUE algorithm. Iran Water Resources Research 16(2): 50-66. (In Persian). https://www.sid.ir/fa/journal/ViewPaper.aspx?id=562645.
43. Saberi tansavan, M., Ganji, Z., Delghand, M., & Dorostkar, V. (2020). Investigation of sensitivity analysis of flood parameters to roughness changes (Case study: Shirvan region). Irrigation and Water Engineering of Iran 10: 167-180. (In Persian)
44. Salami, A.W., Bilewu, S.O., Ibitoye, B.A., & Ayanshola, M.A. (2017). Runoff hydrographs using Snyder and SCS synthetic unit hydrograph methods: A case study of selected rivers in south west Nigeria. Journal of Ecological Engineering 18(1). http://10.12911/22998993/66258.
45. Schwartz, S.S., & Smith, B. (2014). Slowflow fingerprints of urban hydrology. Journal of Hydrology 515: 116-128. https://doi.org/10.1016/j.jhydrol.2014.04.019.
46. Sivapalan, M., Savenije, H.H., & Blöschl, G. (2012). Socio-hydrology: A new science of people and water. Hydrol. Process 26: 1270-1276. http://doi.org/10.1002/hyp.8426.
47. Thompson, S., Sivapalan, M., Harman, C., Srinivasan, V., Hipsey, M., Reed, P., & Blöschl, G. (2013). Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene. Hydrology and Earth System Sciences 17: 5013-5039. https://doi.org/10.5194/hess-17-5013-2013.
48. Tripathi, G., Pandey, AC., & Parida, BR. (2022). Flood Hazard and Risk Zonation in North Bihar Using Satellite-Derived Historical Flood Events and Socio-Economic Data. Sustainability 14(3): 1472. https://doi.org/10.3390/su14031472.
49. Troy, T., Konar, M., Srinivasan, V., & Thompson, S. (2015). Moving sociohydrology forward: a synthesis across studies. Hydrology and Earth System Sciences 19: 3667-3679. https://doi.org/10.5194/hess-19-3667-2015.
50. Valeo, C., He, J., & Kasiviswanathan, K.S. (2021). Urbanization under a Changing Climate–Impacts on Hydrology. Multidisciplinary Digital Publishing Institute 13(4): 393. https://doi.org/10.3390/w13040393.
51. Viglione, A., Di Baldassarre, G., Brandimarte, L., Kuil, L., Carr, G., Salinas, J.L., & Blöschl, G. (2014). Insights from socio-hydrology modelling on dealing with flood risk–roles of collective memory, risk-taking attitude and trust. Journal of Hydrology 518: 71-82. https://doi.org/10.1016/j.jhydrol.2014.01.018.
52. Winsemius, H.C., Aerts, J.C., Van Beek, L.P., Bierkens, M.F., Bouwman, A., Jongman, B., & Van Vuuren, D.P. (2016). Global drivers of future river flood risk. Nature Climate Change 6: 381-385. https://doi.org/10.1038/nclimate2893.
53. Van den Brink, H., Können, G., Opsteegh, J., Van Oldenborgh, G., & Burgers, G. (2005). Estimating return periods of extreme events from ECMWF seasonal forecast ensembles. International Journal of Climatology: A Journal of the Royal Meteorological Society 25(10): 1345-1354.
54. White, G.F. (1945). Human adjustment to floods. A Geographical Approach to the Flood Problem in the United States. In: Chicago, T.U.O., Ed., Research Paper No. 29, The University of Chicago, Chicago.
55. Yang, X., Ren, L., Singh, V., Liu, X., Yuan, F., Jiang, S., & Yong, B. (2012). Impacts of land use and land cover changes on evapotranspiration and runoff at Shalamulun River watershed, China. Hydrology Research 43: 23-37. https://doi.org/10.2166/nh.2011.120.