Evaluation of quantitative changes in surface water resources, affected by the earthquake of Sarpol-e-Zahab, using satellite data
Subject Areas : Applications in natural hazard and disasterAmjad Maleki 1 , Ali Khazai 2 , Ali Abdolmaleki 3
1 - Associate Professor, Department of Geography, Faculty of Literature and Human Sciences, University of Kermanshah, Iran
2 - MSc. Department of Geography, Faculty of Literature and Human Sciences, University of Kermanshah, Iran
3 - MSc. Student of Geomorphology and Environmental Planning, Faculty of Literature and Human Sciences, University of Kermanshah, Iran
Keywords: Normalized difference vegetation index (NDVI), Modified normalized difference water index (MNDWI), remote sensing, Sarpol-e-Zahab, Water resources, Earthquake,
Abstract :
Background and Objective Earthquake In addition to the destructive effects of man-made structures, earthquakes also have different effects on surface water resources. Earthquakes always increase or decrease the water flow depending on its intensity, time, direction, and profundity. It may even cause the springtime fountain to flow that has dried up over the years. The use of remote evaluation technology in various earth sciences is very common compared to geocentric methods due to the wide coverage of satellite images, the timeliness of images, and its little cost. Also, one of the important and unique capabilities of digital satellite data is its temporal, spatial, spectral, and radiometric resolution. These important features of satellite imagery allow for important studies such as the evaluation and monitoring of dynamic phenomena such as quantitative changes in water resources in temporal and spatial dimensions. Because in some cases the information obtained from a sensor alone does not meet the desired needs. Although optical multispectral data provide rich spectral information of various effects, it is significantly affected by environmental factors such as smoke, fog, clouds, and the amount of sunlight. Unlike optical sensors, radar data with virtual aperture (SAR) is independent of different weather and radiation conditions, as well as the sensitivity of its signal, scatter to target parameters such as structure (shape, orientation, size), roughness, and moisture content of the features can provide more information about the study area, but on the other hand, radar images cannot clearly identify the details and edges of objects. Therefore, combining different properties of optics images and radar data using image integration techniques can provide a more complete view of the target and provide higher accuracy and reliability for the results obtained from this method. In the present perusal, in order to achieve the above purpose, using satellite data and the image combination method, the data have been standardized in such a way that they can be used together in the form of a dataset for processing. Materials and Methods Using the method of combining satellite images of quantitative changes of surface water resources, affected by the SARPOL-E-ZAHAB earthquake in the course of 7 days, 11/11/2017 to 17/11/2017, using radar data (S_1A-IW-SLC), With 100 m spatial baseline and Landsat 8 (OLI) optical data, and obtained by applying remote evaluation techniques and indicators to detect changes in water resources, including Normalized difference vegetation index (NDVI), Modified normalized difference water index (MNDWI) in ENVI software environment and then analysis in ArcGIS software environment.Results and Discussion : Examination of the results of quantitative changes in surface water resources shows that in the time period of 7 days after the earthquake in the study area, the highest amount of small changes (in a decreasing manner) occurred in dams (HAMMAM Strait and GILANGH-GHARB Dam). As the Strait of HAMMAM dam decreased by 0.13 square meters and the Gilan GHARB dam decreased by 0.07 square meters. Also, small changes occurred in the surface (SARPOL-E-ZAHAB SARAB-GARM) (drinking water source of the region), SIRVAN river and canals), and there were a total of 7523421 square meters of changes in the surface water resources of the study area after the earthquake.Conclusion The earthquake caused the outflow of groundwater and decreased the volume of dams in the region and fed the surface rivers of the region, including (the Sirvan river) and finally caused water loss and in some places caused the drying of springs and Damage to normal living conditions.
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McFeeters SK. 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7): 1425-1432. doi:https://doi.org/10.1080/01431169608948714.
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Nespoli M, Todesco M, Serpelloni E, Belardinelli ME, Bonafede M, Marcaccio M, Rinaldi AP, Anderlini L, Gualandi A. 2016. Modeling earthquake effects on groundwater levels: evidences from the 2012 Emilia earthquake (Italy). Geofluids, 16(3): 452-463. doi:https://doi.org/10.1111/gfl.12165.
Turker M, San B. 2004. Detection of collapsed buildings caused by the 1999 Izmit, Turkey earthquake through digital analysis of post-event aerial photographs. International Journal of Remote Sensing, 25(21): 4701-4714. doi:https://doi.org/10.1080/01431160410001709976.
Wang R, Luo Y, Yang Y, Tian F, Zhou Y, Tian M-Z. 2015. Characterization of land subsidence induced by groundwater withdrawals in Wenyu River alluvial fan, Beijing, China. Proceedings of the International Association of Hydrological Sciences, 372: 481-484.
Wen-Chi L, Koizumi N, Matsumoto N, Kitagawa Y, Lin C-W, Shieh C-L, Lee Y-P. 2004. Effects of seismic ground motion and geological setting on the coseismic groundwater level changes caused by the 1999 Chi-Chi earthquake, Taiwan. Earth, Planets and Space, 56(9): 873-880. doi:https://doi.org/10.1186/BF03352534.
_||_Abdol Maleki A. 2017. Monitoring the quantitative and qualitative changes of surface water resources affected by earthquakes using remote sensing (Case study of Sarpol-e Zahab. November 13, 2017 earthquake). Thesis for receiving a master's degree in geography majoring in geomorphology in environmental planning. Faculty of Literature and Humanities, Department of Geography. Razi University of Kermanshah. (In Persian).
Ambraseys NN, Melville CP. 2005. A history of Persian earthquakes. Cambridge University Press, 240 p.
Arun K. 2011. Water Quality Retrieval from Landsat TM Imagery. Procedia Computer Science, 6: 475-480. doi:https://doi.org/10.1016/j.procs.2011.08.088.
Baban SMJ. 1995. The use of Landsat imagery to map fluvial sediment discharge into coastal waters. Marine Geology, 123(3): 263-270. doi:https://doi.org/10.1016/0025-3227(95)00003-H.
Bhargava D, Mariam D. 1992. Cumulative effects of salinity and sediment concentration on reflectance measurements. International Journal of Remote Sensing, 13(11): 2151-2159. doi:https://doi.org/10.1080/01431169208904258.
Bhoj PR, Thapa K, Koju R. 2016. Post-earthquake drinking water quality in the Kathmandu valley: A pilot study. Al Ameen Journal of Medical Science, 9(2): 130-133.
Chi‐Yuen W, Dreger DS, Wang CH, Mayeri D, Berryman JG. 2003. Field relations among coseismic ground motion, water level change and liquefaction for the 1999 Chi‐Chi (Mw= 7.5) earthquake, Taiwan. Geophysical Research Letters, 30(17). doi:https://doi.org/10.1029/2003GL017601.
Cle P, Van Genderen JL. 1998. Review article multisensor image fusion in remote sensing: concepts, methods and applications. International Journal of Remote Sensing, 19(5): 823-854. doi:https://doi.org/10.1080/014311698215748.
Delacourt C, Raucoules D, Le Mouélic S, Carnec C, Feurer D, Allemand P, Cruchet M. 2009. Observation of a large landslide on La Reunion Island using differential SAR interferometry (JERS and Radarsat) and correlation of optical (Spot5 and Aerial) images. Sensors, 9(1): 616-630. doi:https://doi.org/10.3390/s90100616.
Goudarzi S, Ashkpoor Motlagh S, Mansouri R, Shokri Kaveh M (eds) (2018) Investigating the effect of earthquake on aquifers groundwater level, 18 th Iranian Geophysical conference, 8- 10 May, Tehran, Iran, 1-4 p. (In Persian).
Hartmann J, Levy JK. 2006. The influence of seismotectonics on precursory changes in groundwater composition for the 1995 Kobe earthquake, Japan. Hydrogeology Journal, 14(7): 1307-1318. doi:10.1007/s10040-006-0030-7.
Hellweger FL, Schlosser P, Lall U, Weissel JK. 2004. Use of satellite imagery for water quality studies in New York Harbor. Estuarine, Coastal and Shelf Science, 61(3): 437-448. doi:https://doi.org/10.1016/j.ecss.2004.06.019.
Ingebritsen S, Manga M. 2019. Earthquake hydrogeology. Water Resources Research, 55(7): 5212-5216. doi:https://doi.org/10.1029/2019WR025341.
Jerry RC, Zimba PV, Everitt JH. 2003. Remote sensing techniques to assess water quality. Photogrammetric Engineering & Remote Sensing, 69(6): 695-704. doi:https://doi.org/10.14358/PERS.69.6.695.
Khorram S. 1985. Remote sensing of water quality in the Mense river estuary, North Carolina. Photogrammetric Engineering and Remote Sensing, 51: 329-341.
Lee TH, Moon WM. 2001. Lineament Extraction from Landsat TM, JERS-1 SAR, and DEM for Geological Applications. In: International Symposium on Remote Sensing. pp 401-406. https://doi.org/410.1109/IGARSS.2002.1027154.
Matsuoka Y, Kawamura H, Sakaida F, Hosoda K. 2011. Retrieval of high-resolution sea surface temperature data for Sendai Bay, Japan, using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Remote Sensing of Environment, 115(1): 205-213. doi:https://doi.org/10.1016/j.rse.2010.08.018.
McFeeters SK. 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7): 1425-1432. doi:https://doi.org/10.1080/01431169608948714.
Mumipour M. 2016. Study of coastal Water Quality using HYPERION Hyperspectral satellite images-case study of Arvandkenar Coasts. Journal of Marine Sciences and Technology, 15(1): 113-122. (In Persian).
Nepal P, Khanal NR, Zhang Y, Paudel B, Liu L. 2020. Land use policies in Nepal: An overview. Land Degradation & Development, 31(16): 2203-2212. doi:https://doi.org/10.1002/ldr.3621.
Nespoli M, Todesco M, Serpelloni E, Belardinelli ME, Bonafede M, Marcaccio M, Rinaldi AP, Anderlini L, Gualandi A. 2016. Modeling earthquake effects on groundwater levels: evidences from the 2012 Emilia earthquake (Italy). Geofluids, 16(3): 452-463. doi:https://doi.org/10.1111/gfl.12165.
Turker M, San B. 2004. Detection of collapsed buildings caused by the 1999 Izmit, Turkey earthquake through digital analysis of post-event aerial photographs. International Journal of Remote Sensing, 25(21): 4701-4714. doi:https://doi.org/10.1080/01431160410001709976.
Wang R, Luo Y, Yang Y, Tian F, Zhou Y, Tian M-Z. 2015. Characterization of land subsidence induced by groundwater withdrawals in Wenyu River alluvial fan, Beijing, China. Proceedings of the International Association of Hydrological Sciences, 372: 481-484.
Wen-Chi L, Koizumi N, Matsumoto N, Kitagawa Y, Lin C-W, Shieh C-L, Lee Y-P. 2004. Effects of seismic ground motion and geological setting on the coseismic groundwater level changes caused by the 1999 Chi-Chi earthquake, Taiwan. Earth, Planets and Space, 56(9): 873-880. doi:https://doi.org/10.1186/BF03352534.