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The Impact of Building a Causeway between the Al-Doha and Shuwaikh Areas in Kuwait Bay on Water Quality Using Remote Sensing and GIS

DOI: 10.4236/jgis.2025.174012, PP. 252-275

Keywords: Remote Sensing, Geographic Information System (GIS), Water Quality, Jaber Al-Ahmad Causeway, Google Earth Engine (GEE)

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Abstract:

Since seawater is the main source of water in Kuwait, water quality must be monitored and observed continuously. Remote sensing is considered to be a very practical method for conducting such a study, especially in prohibited and non-accessible areas. The Al-Hishan area is a small bay located between Al-Doha and Shuwaikh in Kuwait Bay. Although it is a coastal area, many industrial activities have been constructed. Also, the construction of the Jaber Al-Ahmad Causeway has increased the accumulation of sediments and biomaterials in this area. Data were taken from 2013 until 2023 using Landsat imagery, which have been corrected and analyzed using the Google Earth Engine (GEE) platform with multiple indices such as “Total Suspended Solids (TSS), Turbidity, Secchi Disk Depth (SDD), Water Surface Temperature (WST), Suspended Particulate Matter (SPM), and Normalized Difference Water Index (NDWI)” to compare the changes in water quality in this area before, during, and after the construction of the Jaber Al-Ahmad Causeway. The results detected some changes in water quality in many factors, such as temperature and chlorophyll. Observing and monitoring water quality is very important and necessary, especially in countries with limited sources of water. The new techniques in remote sensing and Geographic Information Systems (GIS) have proved to be a very practical way to conduct such a study with high accuracy.

References

[1]  Al-Ghadban, A.N. (2004) Assessment of Suspended Sediment in Kuwait Bay Using Landsat and SPOT Images. Kuwait Journal of Science and Engineering, 31, 155-172.
[2]  Alazmi, H.J., Mitchell, G. and Trigg, M.A. (2023) Kuwait Household Water Demand in 2050: Spatial Microsimulation and Impact Appraisal. Water and Environment Journal, 38, 139-152.
https://doi.org/10.1111/wej.12906
[3]  Dekker, A.G. and Peters, S.W.M. (1993) The Use of the Thematic Mapper for the Analysis of Eutrophic Lakes: A Case Study in the Netherlands. International Journal of Remote Sensing, 14, 799-821.
https://doi.org/10.1080/01431169308904379
[4]  Pandey, C., Srivastava, P., Balzter, H., Bhattacharya, B. and Petrolous, G. (2020) Hyperspectral Remote Sensing: Theory and Applications. Elsevier.
[5]  Ritchie, J.C., Zimba, P.V. and Everitt, J.H. (2003) Remote Sensing Techniques to Assess Water Quality. Photogrammetric Engineering & Remote Sensing, 69, 695-704.
https://doi.org/10.14358/pers.69.6.695
[6]  Chen, Q., Zhang, Y., Ekroos, A. and Hallikainen, M. (2004) The Role of Remote Sensing Technology in the EU Water Framework Directive (WFD). Environmental Science & Policy, 7, 267-276.
https://doi.org/10.1016/j.envsci.2004.05.002
[7]  Tyler, A.N., Hunter, P.D., Spyrakos, E., Groom, S., Constantinescu, A.M. and Kitchen, J. (2016) Developments in Earth Observation for the Assessment and Monitoring of Inland, Transitional, Coastal and Shelf-Sea Waters. Science of the Total Environment, 572, 1307-1321.
https://doi.org/10.1016/j.scitotenv.2016.01.020
[8]  Pahlevan, N., Lee, Z., Wei, J., Schaaf, C.B., Schott, J.R. and Berk, A. (2020) Advances in Aquatic Remote Sensing with Landsat 9: From Science Requirements to Product Advancements. Remote Sensing of Environment, 248, Article ID: 111968.
[9]  Gulf Engineering & Industrial Consultancy (GEIC) (2019) Sheikh Jaber Al-Ahmad Al-Sabah Causeway Project Overview. GEIC Website.
[10]  Erftemeijer, P.L.A. and Robin Lewis, R.R. (2006) Environmental Impacts of Dredging on Seagrasses: A Review. Marine Pollution Bulletin, 52, 1553-1572.
https://doi.org/10.1016/j.marpolbul.2006.09.006
[11]  Glasgow, H.B., Burkholder, J.M., Reed, R.E., Lewitus, A.J. and Kleinman, J.E. (2004) Real-Time Remote Monitoring of Water Quality: A Review of Current Applications, and Advancements in Sensor, Telemetry, and Computing Technologies. Journal of Experimental Marine Biology and Ecology, 300, 409-448.
https://doi.org/10.1016/j.jembe.2004.02.022
[12]  Xu, G., Shen, W. and Wang, X. (2014) Applications of Wireless Sensor Networks in Marine Environment Monitoring: A Survey. Sensors, 14, 16932-16954.
https://doi.org/10.3390/s140916932
[13]  Gholizadeh, M., Melesse, A. and Reddi, L. (2016) A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques. Sensors, 16, Article No. 1298.
https://doi.org/10.3390/s16081298
[14]  Van der Woerd, H.J. and Pasterkamp, R. (2008) Mapping of the North Sea Turbid Coastal Waters Using SeaWiFS Data. Canadian Journal of Remote Sensing, 34, 423-434.
[15]  O’Reilly, J.E., Maritorena, S., Mitchell, B.G., Siegel, D.A., Carder, K.L., Garver, S.A., et al. (1998) Ocean Color Chlorophyll Algorithms for SeaWiFS. Journal of Geophysical Research: Oceans, 103, 24937-24953.
https://doi.org/10.1029/98jc02160
[16]  Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D. and Moore, R. (2017) Google Earth Engine: Planetary-Scale Geospatial Analysis for Everyone. Remote Sensing of Environment, 202, 18-27.
https://doi.org/10.1016/j.rse.2017.06.031
[17]  Kutser, T. (2009) Passive Optical Remote Sensing of Cyanobacteria and Other Intense Phytoplankton Blooms in Coastal and Inland Waters. International Journal of Remote Sensing, 30, 4401-4425.
https://doi.org/10.1080/01431160802562305
[18]  Matthews, M.W. (2011) A Current Review of Empirical Procedures of Remote Sensing in Inland and Near-Coastal Transitional Waters. International Journal of Remote Sensing, 32, 6855-6899.
https://doi.org/10.1080/01431161.2010.512947
[19]  Huang, S., Liu, J., Cai, L., Zhou, M., Bu, J. and Xu, J. (2020) Satellites HY-1C and Landsat 8 Combined to Observe the Influence of Bridge on Sea Surface Temperature and Suspended Sediment Concentration in Hangzhou Bay, China. Water, 12, Article No. 2595.
https://doi.org/10.3390/w12092595
[20]  Guo, J., Ma, C., Ai, B., Xu, X., Huang, W. and Zhao, J. (2020) Assessing the Effects of the Hong Kong-Zhuhai-Macau Bridge on the Total Suspended Solids in the Pearl River Estuary Based on Landsat Time Series. Journal of Geophysical Research: Oceans, 125, e2020JC016202.
https://doi.org/10.1029/2020jc016202
[21]  Yuan, Y., Jalón-Rojas, I. and Wang, X.H. (2019) Impact of Coastal Infrastructure on Ocean Colour Remote Sensing: A Case Study in Jiaozhou Bay, China. Remote Sensing, 11, Article No. 946.
https://doi.org/10.3390/rs11080946
[22]  Al-Ghadban, A.N. and El-Sammak, A. (2005) Sources, Distribution and Composition of the Suspended Sediments, Kuwait Bay, Northern Arabian Gulf. Journal of Arid Environments, 60, 647-661.
https://doi.org/10.1016/j.jaridenv.2004.07.017
[23]  Al-Yamani, F. and Naqvi, S.W.A. (2019) Chemical Oceanography of the Arabian Gulf. In: Sheppard, P.F.S., Ed., The Persian Gulf Ecosystem: Structure and Function, Springer, 161-178.
[24]  Roy, D.P., Wulder, M.A., Loveland, T.R., C.E., W., Allen, R.G., Anderson, M.C., et al. (2014) Landsat-8: Science and Product Vision for Terrestrial Global Change Research. Remote Sensing of Environment, 145, 154-172.
https://doi.org/10.1016/j.rse.2014.02.001
[25]  Al-Sudairawi, M., Misak, R. and Al-Sudairawi, S. (2017) Impact of Climate Change on Kuwait Coastal Zone. World Journal of Engineering and Technology, 5, 255-271.
[26]  Franz, B.A., Kwiatkowska, E.J., Meister, G. and McClain, C.R. (2007) Moderate Resolution Imaging Spectroradiometer on Terra: Limitations for Ocean Color Applications. Journal of Applied Remote Sensing, 1, Article No. 01150.
[27]  Zhu, Z., Wang, S. and Woodcock, C.E. (2015) Improvement and Expansion of the Fmask Algorithm: Cloud, Cloud Shadow, and Snow Detection for Landsats 4-7, 8, and Sentinel 2 Images. Remote Sensing of Environment, 159, 269-277.
https://doi.org/10.1016/j.rse.2014.12.014
[28]  McFeeters, S.K. (1996) The Use of the Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features. International Journal of Remote Sensing, 17, 1425-1432.
https://doi.org/10.1080/01431169608948714
[29]  Xu, H. (2006) Modification of Normalised Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery. International Journal of Remote Sensing, 27, 3025-3033.
https://doi.org/10.1080/01431160600589179
[30]  Chander, G., Markham, B.L. and Helder, D.L. (2009) Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors. Remote Sensing of Environment, 113, 893-903.
https://doi.org/10.1016/j.rse.2009.01.007
[31]  Vermote, E., Justice, C., Claverie, M. and Franch, B. (2016) Preliminary Analysis of the Performance of the Landsat 8/OLI Land Surface Reflectance Product. Remote Sensing of Environment, 185, 46-56.
https://doi.org/10.1016/j.rse.2016.04.008
[32]  Gao, B. (1996) NDWI—A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space. Remote Sensing of Environment, 58, 257-266.
https://doi.org/10.1016/s0034-4257(96)00067-3
[33]  Mobley, C.D. (1999) Estimation of the Remote-Sensing Reflectance from Above-Surface Measurements. Applied Optics, 38, 7442-7455.
https://doi.org/10.1364/ao.38.007442
[34]  Lee, Z., Carder, K.L., Chen, R.F. and Peacock, T.G. (1998) Properties of the Water Column and Bottom Derived from Airborne Visible Infrared Imaging Spectrometer (AVIRIS) Data. Journal of Geophysical Research: Oceans, 103, 21629-21648.
[35]  Hu, C., Lee, Z. and Franz, B. (2012) Chlorophyll a Algorithms for Oligotrophic Oceans: A Novel Approach Based on Three-Band Reflectance Difference. Journal of Geophysical Research: Oceans, 117, C01011.
https://doi.org/10.1029/2011jc007395
[36]  Vanhellemont, Q. and Ruddick, K. (2015) Advantages of High-Quality SWIR Bands for Ocean Colour Processing: Examples from Landsat-8. Remote Sensing of Environment, 161, 89-106.
https://doi.org/10.1016/j.rse.2015.02.007
[37]  Dogliotti, A.I., Ruddick, K.G., Nechad, B., Guerrero, R. and Lasta, C. (2015) Potential of MODIS and MERIS for Monitoring Turbidity and SPM in La Plata River Estuary. Hydrobiologia, 764, 111-125.
[38]  Zhang, Y., Pulliainen, J., Koponen, S., Hallikainen, M. and Wang, X. (2003) Water Clarity Estimation Using Optical Data from Airborne and Satellite Remote Sensing Systems in the Gulf of Finland. The Science of the Total Environment, 268, 155-161.
[39]  Kratzer, S., Håkansson, B. and Sahlin, C. (2003) Assessing Secchi and Photic Zone Depth in the Baltic Sea from Satellite Data. AMBIO: A Journal of the Human Environment, 32, 577-585.
https://doi.org/10.1579/0044-7447-32.8.577
[40]  Du, C., Ren, H., Qin, Q., Meng, J. and Zhao, S. (2015) A Practical Split-Window Algorithm for Estimating Land Surface Temperature from Landsat 8 Data. Remote Sensing, 7, 647-665.
https://doi.org/10.3390/rs70100647
[41]  Barsi, J.A., Schott, J.R., Palluconi, F.D. and Hook, S.J. (2014) Validation of a Web-based Atmospheric Correction Tool for Single Thermal Band Instruments. Proceedings of SPIE—The International Society for Optical Engineering, Vol. 9218, 92181E.
[42]  Google (2024) Kuwait City, Aerial View [Google Earth].
https://earth.google.com/
[43]  Li, D., Xie, P., Zhang, B. and Liu, Y. (2017) Effects of Hydrodynamics on the Spatial and Temporal Variations of Chromophoric Dissolved Organic Matter in a Large Eu-trophic Shallow Lake (Lake Taihu, China). Hydrological Processes, 31, 1323-1332.

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