Morphology and effective processes on Sefidroud flow changes to predict horizon 2030

Document Type : Research Article

Authors

• Hamidreza Masoumi ¹
• Alireza Habibi ²
• Alireza Ghodrati ³

¹ Department of Geology, Bandar Abbas Branch, Islamic Azad University, Bandar Abbas, Iran

² Soil Conservation and Watershed Management Research Institute, Tehran, Iran

³ Guilan Agricultural and Natural Resources Research Center, Rasht, Iran

10.22067/geoeh.2021.68445.1012

Abstract

The study area is located in the Sefidroud coastal plain in Guilan province. The required theoretical foundations and basic information have been collected based on library studies and reviews of similar researches. Landsat 5, 7, 8 satellite images with similar imaging seasons from 1987, 2002, and 2018 are the basis for remote sensing studies. The trend of land-use change in 2018 was predicted in the Idrisi TerrSet software based on the maps of 1987 and 2002, using the CA-Markov model. To determine the classification and modeling accuracy, 120 ground control random points were determined and validated by field measurement spatial reality in the study area. The river change forecast map has been obtained with fitting the model output of 2030 and the land use map of 2018. This fitting, the Sefidroud canal was divided into 4 sections in the study area, and predicted changes were examined. The integrated CA-Markov model has a good capability in terms of accuracy in predicting land use and morphology of Sefidroud. The probable changes are in the river, coastal lands, and man-made facilities and plains units in the study area. The process of these changes will be such that will undergo erosion, change in the meandering, and flooding of areas around the river. The river canal cross-sections has exhibited a decreasing trend of canal width until 2018. This is due to the reduction of Sefidroud discharge and the Caspian Sea level fall, increasing the channel width trend will occur according to the results of the CA-Markov model, until 2030. This indicates the possibility of increasing the average annual discharge of Sefidroud to about 100 (m3/s) and rising the Caspian Sea level above -27 (m) until 2030.

Keywords

• River channel
• Markov chain
• Automation cell model
• Remote sensing

20.1001.1.23221682.1400.10.1.5.0

---

References

اقتصادی، شهمیر؛ زاهدی، رفیعه؛1390. مطالعه عوامل تأثیرگذار بر نوسانات تراز آب خزر جنوبی. مجله علوم و فنون دریایی. شماره 10(3)، صص 4-13.

جداری عیوضی، جمشید؛ یمانی، مجتبی؛ خوش رفتار، رضا؛ 1384. تکامل ژئومرفولوژی دلتای رود سپیدرود در کواترنر. پژوهش­های جغرافیایی. دوره  37. شماره 53. صص 99-120.

سازمان نقشه برداری کشور؛ 1398. آمار پایش تراز آب دریای خزر، ایستگاه انزلی.

شرکت مدیریت منابع آب ایران؛ 1398. دفتر مطالعات پایه منابع آب. آمار دبی رودخانه سفیدرود، ایستگاه هیدرومتری آستانه.

عبدالهی باغسیاهی، علی؛ حشمتیان، رضا؛ سویزی، مهدی؛ 1397. پهنه بندی سیلاب اصلی ساحل مکران با تلفیق مدل HEC-RAS&GIS (رودخانه باهوکلات). یازدهمین سمینار بین المللی مهندسی رودخانه. اهواز. ایران.

عبدالهی کاکرودی، عطا؛ 1392. نوسانات دریای خزر و تأثیر آن بر سواحل جنوب شرقی دریای خزر. پژوهش­های ژئومورفولوژی کمی، شماره 2(3)، صص 33-44.

عطایی، سهیل؛ عجمی، مهدی؛ لشته نشایی، میراحمد؛ یعصوبی، سیدحسین؛ 1395. تأثیر نوسانات تراز آب دریا بر تغییرات خطوط ساحلی دریای خزر. نشریه مهندسی دریا. شماره 12(4)، صص 103-113.

معصومی، حمیدرضا؛ غریب رضا، محمدرضا؛ معتمد، احمد؛ 1390. بررسی مورفولوژی و الگوی پیچانرودی رودخانه زهره در جلگه ساحلی هندیجان. مجله مهندسی و مدیریت آبخیز. دوره 3. شماره 2. صص 102-112.

هلالات ناصریان، حسین؛ صادقی، محمد عامل؛ واعظی پور، حسینعلی؛ سیف، سامان؛ 1392. مدلسازی جامع سیلاب منطقه دشتیاری شهرستان چابهار توسط مدل MIKE FLOOD و ارائه طرح علاج بخشی سیل در منطقه. دوازدهمین کنفرانس هیدرولیک ایران. تهران. ایران.

 

Bravard, JP. Petit, F., 2009. Geomorphology of streams and rivers. In Tochner K, Likens GE, editors. Encyclopedia of inland waters. Elsevier, 387-95. DOI: 10.1016/B978-012370626-3. 00043 -0.

Chen, J. L., Pekker, T., Wilson, C. R., Tapley, B. D., Kostianoy A. G., Cretaux, J. F., Safarov, E. S., 2017. Long-term Caspian Sea level change. Geophysical Research Letters, 6993- 7001. DOL: 10.1002/2017GL073958.

Janes, V. J. J., Nicholas, A. P., Collins, A. L., Quine, T. A., 2017. Analysis of fundamental physical factors influencing channel bank erosion: results for contrasting catchments in England and Wales. Environmental Earth Science, 76-307. DOI: 10.1007/s12665-017-6593-x.

Khoshravan, H., Naqinezhad, A., Alinejad-Tabrizi, T., Yanina, T., 2020. Effects of the Caspian Sea water level change on Boujagh National Park, southwest the Caspian Sea. Caspian Journal of Environmental Science, 19(2), 99-110. 

Kondolf, G. M., Piégay, H., David, R. M., Schmitt, L., David, R. M., 2016. Geomorphic classification of rivers and streams, Chapter 7. Tools in fluvial geomorphology. 169-202. DOI: 10.1002/9781118648551.ch7.

Medel, I. D., Stubblefield, A. P., Sheam C., 2020. Sedimentation and erosion patterns within anabranching channels in a lowland river restoration project. International Journal of River Basin Management, DOI: 10.1080/15715124.2020.1809435.

Mirzaeizadeh, V., Niknwzhad, M., Ouladi, J., 2015. Evaluating non-parametric supervised classification algorithms in land cover map using LandSat-8 Images. Journal of RS and GIS for natural resources, Vol. 6, No. 3, 29-44.

Mondal, S., Sharma, N., Kappas, M., Garg, P. K., 2020. Cellular automata (CA) contiguity filters impacts on CA Markov modelling of land use land cover change predictions results. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLIII, B3, 1585–1591.

Muller, M. R., Middleton, J., 1994. A Markov model of land-use change dynamics in the Niagara Region, Ontario, and Canada. Landscape Ecology, 9, 151-157.

Pal, M., Mather, P. M., 2005. Support vector machines for classification in remote sensing. International Journal of Remote Sensing, 26 (5), 1007-1011.

Sang, L., Zhang, C., Yang, J., Zhu, D., Yun, W., 2011. Simulation of land use spatial pattern of towns and villages based on CA–Markov model. Mathematical and Computer Modelling, 10, 883-848. DOI: 2002022/j.mcm.10200220028.

Subedi, P., Subedi, K., Thapa, B., 2013. Application of a Hybrid Cellular Automation Markov (CA-Markov) Model in Land-Use Change Prediction: A Case Study of Saddle Creek Drainage Basin, Florida. Applied Ecology and Environmental Sciences, 16, 126-132.

Zhang, F., Tiyip, T., Feng, ZD. Kung, H-T., Johnson, V. C., Ding, JL., Tashpolat, N., Sawut, M. Gui, DW., 2015. Spatio-temporal patterns of land use/cover changes over the past 20 years in the middle reaches of the Tarim River, Xinjiang, China. Land Degradation and Development, 26,284- 29.