pesd2023172001

	PRESENT ENVIRONMENT AND SUSTAINABLE DEVELOPMENT Volume 18, Issue no.1/ 2024

	Title: Assessment of LULC change and its impact on Surface Runoff using SCS-CN method for Noakhali Region, Bangladesh
	Authors : Md. Riyadul HAQUE, Md. Kamruzzaman TUSAR, Momotaj Ara MOU, Md. Shiblur RAHAMAN Department of Environmental Science and Disaster Management, Noakhali Science and Technology University, Bangladesh E-mail : * Corresponding author: kamruzzaman.dsm@gmail.com; shiblu@nstu.edu.bd;
	hhttps://doi.org/10.47743/pesd2024181020
	VIEW FULL TEXT
	Abstract Land use and land cover (LULC) change detection and its subsequent impact on hydrology are of significant importance in the field of urban planning and the sustainable management of water and land resources. The primary objective of this research work is to illustrate LULC map in a specific study area, which encompasses approximately 316.7 km² in the Noakhali region. Additionally, this study tries to examine the enduring impacts of LULC changes on surface runoff within the specified area. In order to achieve this goal, the analysis of LULC change trends in the region was conducted using Landsat OLI/TM data from 2000 to 2020. The analysis focused on five distinct classes: built-up land, vacant land, farmland, vegetation, and waterbodies. The research employs the Soil Conservation Service Curve Number (SCS-CN) model to evaluate the influence of LULC changes on surface runoff. Notably, the findings indicate a substantial increase in built-up areas from 1.05% in 2000 to 11.21% in 2020. This urban expansion is strongly correlated with a notable rise in surface runoff, as evidenced by a high correlation coefficient (R2 = 0.98) between urban expansion and modelled runoff depth. The observed increase in impervious urban areas contributes to a 2.65% rise in average runoff from 2000 to 2020, equivalent to an 8.96 mm increment in average runoff. The study underscores the profound implications for managing urban storm floods and designing urban areas, especially in rapidly expanding cities globally, with a focus on developing nations. The insights gained offer valuable information for informed decision-making in sustainable urban development and water resource management, not only in the Noakhali region but also beyond.

	References . Al-Juaidi, A.E.M. (2018) A simplified GIS-based SCS-CN method for the assessment of land-use change on runoff. Arab J Geosci, 11(11), 269. https://doi.org/10.1007/s12517-018-3621-4 Basheer, S.; Wang, X.; Farooque, A. A.; Nawaz, R. A.; Liu, K.; Adekanmbi, T.; Liu, S. (2022) Comparison of Land Use Land Cover Classifiers Using Different Satellite Imagery and Machine Learning Techniques. Remote Sensing, 14(19), 1–18. https://doi.org/10.3390/rs14194978 Chelkeba Tumsa, B. (2023) The Response of Sensitive LULC Changes to Runoff and Sediment Yield in a Semihumid Urban Watershed of the Upper Awash Subbasin Using the SWAT+ Model, Oromia, Ethiopia. Appl Environ Soil Sci, 2023. https://doi.org/10.1155/2023/6856144 Chilagane, N.A.; Kashaigili, J.J.; Mutayoba, E.; Lyimo, P.; Munishi, P.; Tam, C.; Burgess, N. (2021) Impact of Land Use and Land Cover Changes on Surface Runoff and Sediment Yield in the Little Ruaha River Catchment. Open J Modern Hydrol, 11(03), 54–74. https://doi.org/10.4236/ojmh.2021.113004 Das, P.C.; Esraz-Ul-Zannat, M. (2022) Assessing the impacts of land use-land cover changes on direct surface runoff: a remote sensing approach in Khulna City. Water Sci Technol, 85(10), 3122–3144. https://doi.org/10.2166/wst.2022.097 Erena, S.H.; Worku, H. (2019) Dynamics of land use land cover and resulting surface runoff management for environmental flood hazard mitigation: The case of Dire Daw city, Ethiopia. J Hydrol: Regional Stud, 22(February), 100598. https://doi.org/10.1016/j.ejrh.2019.100598 Githui, F.; Gitau, W.; Mutua, F.; Bauwens, W. (2009) Climate change impact on SWAT simulated streamflow in western Kenya. Int J Climatol, 29(12), 1823–1834. https://doi.org/10.1002/joc.1828 Gorelick, N.; Hancher, M.; Dixon, M.; Ilyushchenko, S.; Thau, D.; Moore, R. (2017) Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens Environ, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031 Hu, S.; Fan, Y.; Zhang, T. (2020) Assessing the Effect of Land Use Change on Surface Runoff in a Rapidly Urbanized City: A Case Study of the Central Area of Beijing. Land, 9(1), 17. https://doi.org/10.3390/land9010017 Li, Y.; Wang, C. (2009) Impacts of urbanization on surface runoff of the dardenne creek watershed, St. Charles County, Missouri. Phys Geogr, 30(6), 556–573. https://doi.org/10.2747/0272-3646.30.6.556 McCuen, R.H. A Guide to Hydrologic Analysis Using SCS Methods; Prentice-Hall, Inc.: Hoboken, NJ, USA, 1982. Moniruzzaman, M.; Thakur, P.K.; Kumar, P.; Ashraful Alam, M.; Garg, V.; Rousta, I.; Olafsson, H. (2020) Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing. Remote Sensing, 13(1), 83. https://doi.org/10.3390/rs13010083 RCS (1986) Urban Hydrology for Small Watersheds-Technical Release 55; US Department of Agriculture Natural Resources Conservation: Washington, DC, USA, 1986. Ozdemir, H.; Elbasi, E. (2015) Benchmarking land use change impacts on direct runoff in ungauged urban watersheds. Phys Chem Earth, Parts A/B/C, 79–82, 100–107. https://doi.org/10.1016/j.pce.2014.08.001 Pal, M. (2005) Random forest classifier for remote sensing classification. Int J Remote Sens, 26(1), 217–222. https://doi.org/10.1080/01431160412331269698 Pandey, A.C. (2017) Geospatial Technique for Runoff Estimation Based on SCS-CN Method in Upper South Koel River Basin of Jharkhand (India). Int J Hydrol, 1(7). https://doi.org/10.15406/ijh.2017.01.00037 Population Census 2011: Noakhali. Bangladesh Bureau of Statistics. Available at: http://203.112.218.66/WebTestApplication/userfiles/Image/Census2011/Chittagong/Noakhali/Noakhali_C01.pdf Psomiadis, E.; Soulis, K.X.; Efthimiou, N. (2020) Using SCS-CN and Earth Observation for the Comparative Assessment of the Hydrological Effect of Gradual and Abrupt Spatiotemporal Land Cover Changes. Water, 12(5), 1386. https://doi.org/10.3390/w12051386 Rahaman, M.S.; Hossain, N.; Nurain, A.; Sarker, P.; Ichihara, S. (2020) Investigation on Causes and Effects of Waterlogging in the Southern Part of Bangladesh. Manag Sustain Develop, 12(2), 4–11. https://doi.org/10.54989/msd-2020-0006 Reis, S. (2008) Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey. Sensors, 8(10), 6188–6202. https://doi.org/10.3390/s8106188 Ruddiman, W.F. (2003) The Anthropogenic Greenhouse Era Began Thousands of Years Ago. Climatic Change, 61(3), 261–293. https://doi.org/10.1023/B:CLIM.0000004577.17928.fa Sajikumar, N.; Remya, R.S. (2015) Impact of land cover and land use change on runoff characteristics. J Environ Manag, 161, 460–468. https://doi.org/10.1016/j.jenvman.2014.12.041 Satheeshkumar, S.; Venkateswaran, S.; Kannan, R. (2017) Rainfall–runoff estimation using SCS–CN and GIS approach in the Pappiredipatti watershed of the Vaniyar sub basin, South India. Modeling Earth Systems and Environment, 3(1), 1–8. https://doi.org/10.1007/s40808-017-0301-4 Sharma, K.D.; Singh, S. (1992) Runoff estimation using Landsat Thematic Mapper data and the SCS model. Hydrol Sci J, 37(1), 39–52. https://doi.org/10.1080/02626669209492560 Song, K.; Kim, M.; Kang, H.M.; Ham, E.K.; Noh, J.; Khim, J.S.; Chon, J. (2022) Stormwater runoff reduction simulation model for urban flood restoration in coastal area. Natural Hazards, 114(3), 2509–2526. https://doi.org/10.1007/s11069-022-05477-7 Soulis, K.X.; Valiantzas, J.D. (2012) SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach. Hydrol Earth Syst Sc, 16(3), 1001–1015. https://doi.org/10.5194/hess-16-1001-2012 Sun, Z.; Li, X.; Fu, W.; Li, Y.; Tang, D. (2013) Long-term effects of land use/land cover change on surface runoff in urban areas of Beijing, China. J Appl Remote Sens, 8(1), 084596. https://doi.org/10.1117/1.JRS.8.084596 Suriya, S.; Mudgal, B.V. (2012) Impact of urbanization on flooding: The Thirusoolam sub watershed – A case study. J Hydrol, 412–413, 210–219. https://doi.org/10.1016/j.jhydrol.2011.05.008 Talukdar, S.; Singha, P.; Mahato, S.; Shahfahad; Pal, S.; Liou, Y.A.; Rahman, A. (2020) Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review. Remote Sensing, 12(7), 1135. https://doi.org/10.3390/rs12071135 United States Department of Agriculture Soil Conservation Service, “Urban hydrology for small watersheds,” Technical Release 55, USDA Natural Resources Conservation Service, Washington, DC (1986). Vojtek, M.; Vojteková, J. (2019) Land use change and its impact on surface runoff from small basins: A case of Radiša basin. Folia Geographica, 61(2), 104–125. Wahap, N.A.; Shafri, H.Z.M. (2020) Utilization of Google Earth Engine (GEE) for land cover monitoring over Klang Valley, Malaysia. IOP C Ser Earth Env Sci, 540(1). https://doi.org/10.1088/1755-1315/540/1/012003 Wang, J.; Yin, X.; Liu, S.; Wang, D. (2023) Spatiotemporal change and prediction of land use in Manasi region based on deep learning. Environ Sci Pollut R, 30(34), 82780–82794. https://doi.org/10.1007/s11356-023-27826-0

© 2007 Present Environment and Sustainable Development
ISSN 1843-5971 (Printed version) ISSN 2284 – 7820 (online version)

Home Editorial Board

Webdesign Adrian Ursu ©2008 UAIC