Assessment of the effect of land use and land cover (LULC) change on depth runoff: case study of Skikda floods event

Lamia Leulmi, Youcef Lazri, Brahim Abdelkebir, Sofiane Bensehla


Land use and land cover changes in coastal cities can influence drainage systems in ways that affect surface overflows and the infiltration potential of a land surface, making flooding one of the drivers. This research aims to demonstrate the spatiotemporal dynamics of LULC and their combined impact on rainfall and flood height in Skikda, Algeria. The research uses remote sensing (RS) and geographic information systems (GIS) to determine the type and location of LULC changes in Skikda. The supervised classification methodology used the maximum likelihood technique (MCL). Changes were identified in five categories: built-up areas, green spaces, bodies of water, agriculture, and vacant land. In Q-GIS 3.28.2, Landsat 4-5 (TM) data from 1984 and 2004 and Landsat 8-9 (OLI)/TIRS data from 2019 were used based on the United States Geological Survey (USGS). The results show that the impervious built-up area has changed significantly (44.01%) due to massive urbanization and rapid industrialization, which would affect heavy rainfall activity and increase flood height due to the intense imperviousness of the affected soil (from 27% to 44%). The precipitation and flood height were examined and compared with observations to investigate the impact of the LULC model modification during the flood. The comparison of three flood events (1984, 2004, and 2019) revealed that the change in the LULC model is the main factor increasing flood risk in the study area. This study demonstrates the importance of considering temporal changes in land use, land cover, rainfall, and flood height when mapping floods in urban cities.

Key words: LULC change, flood risk, extreme rainfall, flood height, Skikda

? 2023?Serbian Geographical Society, Belgrade, Serbia.

This article is an open access article distributed under the terms and conditions of the?Creative Commons Attribution-NonCommercial-NoDerivs?3.0 Serbia.

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Abdelkebir, B., Maoui, A., Mokhtari, E., Engel, B., Chen, J., & Aboelnour, M. (2021). Evaluating Low-Impact Development practice performance to reduce runoff volume in an urban watershed in Algeria. Arabian Journal of Geosciences, 14(9), 814.

Abuhay, W., Gashaw, T., & Tsegaye, L. (2023). Assessing impacts of land use/land cover changes on the hydrology of Upper Gilgel Abbay watershed using the SWAT model. Journal of Agriculture and Food Research, 12, Article 100535.

Apollonio, C., Balacco, G., Novelli, A., Tarantino, E., & Piccinni, A. (2016). Land Use Change Impact on Flooding Areas: The Case Study of Cervaro Basin (Italy). Sustainability, 8(10), 996.

Basukala, A. K., Oldenburg, C., Schellberg, J., Sultanov, M., & Dubovyk, O. (2017). Towards improved land use mapping of irrigated croplands: Performance assessment of different image classification algorithms and approaches. European Journal of Remote Sensing, 50(1), 187?201.

Beroho, M., Briak, H., Cherif, E.K., Boulahfa, I., Ouallali, A., Mrabet, R., Kebede, F., Bernardino, A., & Aboumaria, K. (2023). Future Scenarios of Land Use/Land Cover (LULC) Based on a CA-Markov Simulation Model: Case of a Mediterranean Watershed in Morocco. Remote Sensing, 15, 1162.

Campbell, J. B., & Wynne, R. H. (2011). Introduction to Remote Sensing (5th ed.). The Guilford Press.

Dalponte, M., Bruzzone, L., & Gianelle, D. (2008). Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas. IEEE Transactions on Geoscience and Remote Sensing, 46(5), 1416?1427.

Darabi, H., Choubin, B., Rahmati, O., Torabi Haghighi, A., Pradhan, B., & Kl?ve, B. (2019). Urban flood risk mapping using the GARP and QUEST models: A comparative study of machine learning techniques. Journal of Hydrology, 569, 142?154.

Debnath, J., Sahariah, D., Lahon, D., Nath, N., Chand, K., Meraj, G., Kumar, P., Kumar Singh, S., Kanga, S., & Farooq, M. (2023). Assessing the impacts of current and future changes of the planforms of river Brahmaputra on its land use-land cover. Geoscience Frontiers, 14(4), 101557.

Deshons, P. (2002). Pr?vision et suivi des crues urbaines Exp?rience de la ville de Marseille. La Houille Blanche, 88(2), 56?59.

Do, T. A. T., Do, A. N. T., & Tran, H. D. (2022). Quantifying the spatial pattern of urban expansion trends in the period 1987?2022 and identifying areas at risk of flooding due to the impact of urbanization in Lao Cai city. Ecological Informatics, 72, 101912.

El Bastawesy, M. (2015). The geomorphological and hydrogeological evidences for a Holocene deluge in Arabia. Arabian Journal of Geosciences, 8(5), 2577?2586.

Feizizadeh, B., Omarzadeh, D., Kazemi Garajeh, M., Lakes, T., & Blaschke, T. (2023). Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine. Journal of Environmental Planning and Management, 66(3), 665?697.

Fern?ndez, D. S., & Lutz, M. A. (2010). Urban flood hazard zoning in Tucum?n Province, Argentina, using GIS and multicriteria decision analysis. Engineering Geology, 111(1?4), 90?98.

Kantakumar, L. N., & Neelamsetti, P. (2015). Multi-temporal land use classification using hybrid approach. The Egyptian Journal of Remote Sensing and Space Science, 18(2), 289?295.

Kordelas, G., Manakos, I., Aragon?s, D., D?az-Delgado, R., & Bustamante, J. (2018). Fast and Automatic Data-Driven Thresholding for Inundation Mapping with Sentinel-2 Data. Remote Sensing, 10(6), 910.

Li, Y., Osei, F. B., Hu, T., & Stein, A. (2023a). Urban flood susceptibility mapping based on social media data in Chengdu city, China. Sustainable Cities and Society, 88, 104307.

Liping, C., Yujun, S., & Saeed, S. (2018). Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques?A case study of a hilly area, Jiangle, China. PLOS ONE, 13(7), e0200493.

Lo, C. P., & Choi, J. (2004). A hybrid approach to urban land use/cover mapping using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images. International Journal of Remote Sensing, 25(14), 2687?2700.

Lucchetta, B. C., Watanabe, F. S. Y., & do Carmo, N. M. R. B. (2023). A spatiotemporal classification approach to evaluate the impacts of land use and land cover changes before and after the Tr?s Irm?os reservoir formation in the Tiet? River, Brazil. Modeling Earth Systems and Environment.

Miguez, M. G., Ver?l, A. P., Battemarco, B. P., Yamamoto, L. M. T., de Brito, F. A., Fernandez, F. F., Merlo, M. L., & Queiroz Rego, A. (2019). A framework to support the urbanization process on lowland coastal areas: Exploring the case of Vargem Grande ? Rio de Janeiro, Brazil. Journal of Cleaner Production, 231, 1281?1293.

Mokhtari, E., Mezali, F., Abdelkebir, B., & Engel, B. (2023). Flood risk assessment using analytical hierarchy process: A case study from the Cheliff-Ghrib watershed, Algeria. Journal of Water and Climate Change, 14(3), 694?711.

Nouri, M., Ozer, A., & Ozer, P. (2016). Etude pr?liminaire sur le risque d?inondation en milieu urbain (Alg?rie) Preliminary study on the flood risk in urban areas (Algeria). Geo-Eco-Trop, 40(3), 201-208.

Notti, D., Giordan, D., Cal?, F., Pepe, A., Zucca, F., & Galve, J. (2018). Potential and Limitations of Open Satellite Data for Flood Mapping. Remote Sensing, 10(11), 1673.

Olang, L. O., & F?rst, J. (2011). Effects of land cover change on flood peak discharges and runoff volumes: Model estimates for the Nyando River Basin, Kenya. Hydrological Processes, 25(1), 80?89.

Romero-Lankao, P., Gnatz, D., Wilhelmi, O., & Hayden, M. (2016). Urban Sustainability and Resilience: From Theory to Practice. Sustainability, 8(12), 1224.

Saghafian, B., Farazjoo, H., Bozorgy, B., & Yazdandoost, F. (2008). Flood Intensification due to Changes in Land Use. Water Resources Management, 22(8), 1051?1067.

Salazar-Briones, C., Ruiz-Gibert, J. M., Lomel?-Banda, M. A., & Mungaray-Moctezuma, A. (2020). An Integrated Urban Flood Vulnerability Index for Sustainable Planning in Arid Zones of Developing Countries. Water, 12(2), 608.

Samarasinghe, J. T., Gunathilake, M. B., Makubura, R. K., Arachchi, S. M. A., & Rathnayake, U. (2022). Impact of Climate Change and Variability on Spatiotemporal Variation of Forest Cover; World Heritage Sinharaja Rainforest, Sri Lanka. Forest and Society, 6(1).

Seyam, M. M. H., Haque, M. R., & Rahman, M. M. (2023). Identifying the land use land cover (LULC) changes using remote sensing and GIS approach: A case study at Bhaluka in Mymensingh, Bangladesh. Case Studies in Chemical and Environmental Engineering, 7, 100293.

Sugianto, S., Deli, A., Miswar, E., Rusdi, M., & Irham, M. (2022). The Effect of Land Use and Land Cover Changes on Flood Occurrence in Teunom Watershed, Aceh Jaya. Land, 11(8), 1271.

Toubin, M. (2015). III. Am?liorer la r?silience urbaine par un diagnostic collaboratif?L?exemple des services urbains parisiens face ? l?inondation.

Vivekananda, G., Swathi, R., & Sujith, A. (2021). Multi-temporal image analysis for LULC classification and change detection. European Journal of Remote Sensing, 54(sup2), 189?199.

Waghwala, R. K., & Agnihotri, P. G. (2019). Flood risk assessment and resilience strategies for flood risk management: A case study of Surat City. International Journal of Disaster Risk Reduction, 40, 101155.

Wang, X., Xia, J., Zhou, M., Deng, S., & Li, Q. (2022). Assessment of the joint impact of rainfall and river water level on urban flooding in Wuhan City, China. Journal of Hydrology, 613, 128419.

Yousuf, A., & Romshoo, S. A. (2022). Impact of Land System Changes and Extreme Precipitation on Peak Flood Discharge and Sediment Yield in the Upper Jhelum Basin, Kashmir Himalaya. Sustainability, 14(20), 13602.


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