Determining the Flooding Points and comparing it with Aq Qala flood in 1398 and estimating its damage in the agricultural sector using radar images

Document Type : Research Paper

Authors

Golestan university

Abstract

Determining the Flooding Points and comparing it with Aq Qala flood in 1398 and estimating its damage in the agricultural sector using radar images

Abstract:
Floods are one of the most important hazards that depending on the intensity of rainfall and other effective factors cause great damage to urban and rural areas. Predicting flood-prone areas for Planning to prevent floods and estimating flood damage for post-flood management is one of the main issues in flood planning. Today, the use of radar data is one of the newest and most effective methods in flood study.
The exact details of the floods can be studied and the extent of its spread can be determined so that it can be used in future planning. In this research, to estimate flood-prone areas, the FHD model in GIS environment has been determined, which has identified the flood-prone areas, and to validate it from the cumulative flood zone obtained from Sentinel 2 images, the outputs have been fully matched.
Using NDVI index, the images of ssentinel 2 in Google Earth engine were determined and its combination with GFSAD system, the type of cultivation in the study area was determined Using the cumulative flood zone layer, the areas that were flooded were examined according to what type of crops were flooded. The results showed that out of 100% of the existing lands, about 22.5% of its lands were flooded, of which about 15.5% were rainfed cultivated lands and the rest were irrigated cultivated lands.

Key word: Aq Qala Flood, Damage Estimation, GEE, Sentinel 1 and 2

Keywords

References

  • References

    • Afshin, Y. (1994). Rivers of Iran, first volume. first edition, Tehran: Ministry of Energy. [In Persian]
    • Ardavan, B., Moghimi, I., & Asadin, F. (2016). Estimating Flood potential of Germi basin with emphasize on risk management by using SCS method (Rudbar, Gilan Provence). Journal of Environmental Risk Management, 3(4), 315-330. [In Persian]
    • Y., Jacob. A., & Gamba, P. (2015). Spaceborne SAR data for global urban mapping at 30 m resolution using a robust urban extractor. ISPRS Journal of Photogrammetry and Remote Sensing, 103, 28-37.
    • Boccardo, P., & Tonolo, F.G. (2015). Remote sensing role in emergency mapping for disaster response. Engineering Geology for Society and Territory, 5, 17-24.
    • M.L., Townshend. J.R., DiMiceli. C.M., Noojipady. P., & Sohlberg, R.A. (2009). A new global raster water mask at 250 m resolution. International Journal of Digital Earth, 2 (4),pp. 291–308.
    • R., & Anderson, E. (2006). MODIS-based flood detection, mapping and measurement: the potential for operational hydrological applications. Transboundary floods: reducing risks through flood management, pp. 1–12.
    • Centre for Research on the Epidemiology of Disasters, Emergency Events Database (CRED EMDAT), 2015, http://www.emdat.be/.
    • Chen, S.A., Evans, B., Djordjevic. S., & Savic, D.A. (2012). Multi-layered coarse grid modeling in 2D urban flood simulations. Journal of Hydrology, 470/471, 1-11.
    • Choudhari, K., Panigrahi. P., & Chandra Paul, j. (2014). Simulation of rainfall-runoff process using HEC-HMS model for Balijore Nala watershed, Odisha, India. International Journal of Geomatics and Geosciences, 5(2), pp.253-265
    • De Risi, R., Jalayer, F., & De Paola, F. (2015). Meso-scale hazard zoning of potentially flood prone areas. Journal of Hydrology, 527, 315-325.
    • Dovonce, E. (2000). A physically based distributed hydrologic model. Master of Science Thesis, the Pennsylvania State University.
    • Emadodin, S., & Mohammad Ghasemi, M. (2021). Monitoring of flood expansion maps using radar images (SAR) (Case study: Flood in March 2019, Aq Qala city). Journal of Climate Change Research, 2(6), pp. 79-96. [In Persian]
    • Ganji, K., Qara Chelo, S., & Ahmadi, A. (2020). Investigation of the effect of morphological indicators of Gorganrood river on flood zones using remote sensing data and spatial analysis (Study area: Aq Qala city). Journal of Geography and Environmental Hazards, 9(35), pp. 205-255. [In Persian]
    • Giordan, D., Notti, D., Villa, A., Zucca, F., Calò, F., Pepe, A., Dutto, F., Pari, P., Baldo, M., & Allasia, P. (2018). Low cost, multiscale and multi-sensor application for flooded area mapping. Natural Hazards and Earth System Sciences Discussions, 18, 1493–1516.
    • Hervé Kouassi, K., Alexis N’go, Y., Anoh, K., Jean-Jacque Koua, T., & Constantin Stoleriu, C. (2020). Contribution of Sentinel 1 radar data to flood mapping in the San-Pédro River Basin (South-west Côte d’Ivoire). Asian Journal of Geographical Research, 3, 1-8.
    • Iran Space Research Institute, (2018). Report on the activities of the Remote Sensing Group of the Space Research Center of the Iran Space Research Institute to help flood management in Golestan, Lorestan and Khuzestan provinces. [In Persian]
    • jalaliyan, S.I. (2022). Evaluating and zoning flooding on a temporal and spatial scale (Study Area: Gorgan River Watershed in Golestan Province). Geographical Planning of Space Quarterly Journal, 11(42), 107-125. [In Persian]
    • Kumar, R., Singh, R., Gautam, H., & Pandey, M.K. (2018). Flood hazard assessment of August 20, 2016 floods in Satna District, Madhya Pradesh, India. Remote Sensing Application: Society and Environment, 11, 104–118.
    • Matgen, P., Schumann. G., Henry. J.B., Hoffmann. L., & Pfister, L. (2007). Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management. International Journal of Applied Earth Observation and Geo information, 9(3), pp.247-263.
    • Mohamad Nejhad, V. (2021). Flood extent area mapping using sentinel 1 SAR image (a case study: the flood of Poledokhtar, march 2021). Geographical planning of Space Quarterly Journal, 11(41),69-80. [In Persian]
    • Nascimento, N., Lea Machado, M., Baptista, M., De Paula, E., & Silva, A. (2007) The assessment of damage caused by floods in the Brazilian context. Journal of Urban Water, 4(3), pp. 195-210.
    • Nezammahalleh, M., Yamani, M., Gorabi, A., Masghsodi, M., & mohammadkhan, S. (2017) Evaluation of a GIS-Based Floodplain Height Difference Model for Flood Inundation Mapping, Case Study: Rudbar, Iran, Journal of Environmental Treatment Techniques, 3, 100-106.
    • Panjekoobi, P., Reyhani Parvari, M., Javerdi, M., & Rahman Nia, M. (2020). Investigation of Intensity- Duration- Area of Rainfall and its Impact on Floods Using Radar Images (Case Study of the Flood on May 2014). Remote Sensing and GIS, 1(45), 73-86. [In Persian]
    • Rahman, R., & Thakur, P. (2017). Detecting, mapping and analysing of flood water propagation using synthetic aperture radar (SAR) satellite data and GIS: A case study from the Kendrapara District of Orissa State of India. The Egyptian Journal of Remote Sensing and Space Sciences,21, 537-541
    • Revellino, P., Guerriero, L., Mascellaro, N., Fiorillo, F., Grelle, G., Ruzza, G., & Guadagno, F.M. (2019) Multiple Effects of Intense Meteorological Events in the Benevento Province, Southern Italy. Water, 11(8), 1560.
    • Ruzza, G., Guerriero, L., Grelle, G., Guadagno, F.M., & Revellino, P. (2019). Multi-Method Tracking of Monsoon Floods Using Sentinel-1 Imagery. Water, 11(8), pp.1-23.
    • Smith, K., & Ward, R. (1998) Floods: Physical processes and human impacts, New York: Wiley.
    • X., Wang. D., Mao. K., Anagnostou. E., & Hong, Y. (2019). Inundation extent mapping by synthetic aperture radar: a review. Remote Sensing, 11(7), 879.
    • Solaimani, K., Sharifipour, M., & Abdoli Boozhani, S. (2020). Flood Damage Detection Algorithm Using Sentinel-2 Images (Case Study: Golestan Flood of March 2019). Journal of Echo Hydrology, 7(2), pp. 303-312. [In Persian]
    • Tiwari, V., Kumar, V., Mir Abdul, M., thapa, A., Lee Ellenburg, W., Gupta, N.& Thapa, S. (2020). Flood inundation mapping- Kerala 2018; Harnessing the power of SAR, automatic threshold detection method and Google Earth Engine, Plos one, pp. 1-17.
Geographical Planning of Space
Volume 12, Issue 2
August 2022
Pages 83-98

Files

Share

How to cite

Statistics