Flood Inundation Modeling and Damage Assessment in Lahore Using Remote Sensing

Zunaira Abbas; Mehreen Akhtar; Saira Akram; sumaira Hafeez; Sajid Rasheed Ahmad

Authors

Zunaira Abbas College of Earth and Environmental Sciences, University of the Punjab, Lahore, Pakistan.
Mehreen Akhtar College of Earth and Environmental Sciences, University of the Punjab, Lahore, Pakistan.
Saira Akram Center for Remote Sensing and GIS, University of the Punjab, Lahore, Pakistan.
sumaira Hafeez College of Earth and Environmental Sciences, University of the Punjab, Lahore, Pakistan.
Sajid Rasheed Ahmad College of Earth and Environmental Sciences, University of the Punjab, Lahore, Pakistan.

Keywords:

Flood, HEC-RAS, Remote sensing and GIS, Inundation, Damage Assessment, Hydrological Modeling.

Abstract

Introduction:

Ravi River has a great contribution to the glorious history of Lahore City, the second biggest city in Pakistan. But similar to all rivers of Pakistan, River Ravi occasionally experiences extreme floods. During the past 100 years, two extremely high floods created devastation in Lahore City, which caused enormous loss of properties and lives. To save the main metropolitan areas of Lahore in both these floods, the Shahdara Breaching section, on the western bank of the river, was operated. The potential of loss due to floods has increased even more owing to the rise in population, industrialization, and spring of unplanned settlements in the floodplain of the river.

Importance of Study:

This research provides a solution that has the potential for long-term effects in flood management, hygienic improvement of the area, planned urban development around the river, and improvement of sub-surface water quality.

Novelty Statement:

The present study is focused on determining the flood damage assessment using advanced geospatial techniques with HEC-RAS applications.

Materials and Methods:

The reach of the Ravi River is from Shahdara to Balloki. Flood frequency analysis was performed to calculate a flood return period of five and fifty years. Hydraulic modeling of the river on HEC-RAS is used to find river capacity, its Validation, calibration, assessment of hydraulic capacity, flood inundation extent, and depth analysis.

Results:

It is concluded that a flood of 3643.97 cumecs magnitude corresponds to 5 years return period and 7406.699 cumecs magnitude corresponds to 50 years return period. If the same phenomena occur in a repeating manner, then the built-up settlement near Ravi can meet alarming threats. According to the maximum likelihood classification, the damage assessment was mapped wherein the results show that the buildup area was 15657 acres, the water body was 7059.246 acres, the cultivated area was 38395.3 acres, and uncultivated 59464.51 acres were affected.

Conclusion:

The solution can also address the problems arising due to changes in river course and depletion of natural habitat.

Recommendations:

However, along the Lahore City, the required width is not available. In this condition, an engineering solution is mandatory to pass the flood. Channelization can be proposed to create the width of the river. The reclaimed land should be used for high-quality urban development to increase revenues. For the sake of channel stability, a detailed sediment study should be done.

References

J. M. Buttle et al., “Flood processes in Canada: Regional and special aspects,” Can. Water Resour. J., vol. 41, no. 1–2, pp. 7–30, 2016, doi 10.1080/07011784.2015.1131629.

B. M. Popkin, K. E. D’Anci, and I. H. Rosenberg, “Water, hydration, and health,” Nutr. Rev., vol. 68, no. 8, pp. 439–458, 2010, doi: 10.1111/j.1753-4887.2010.00304.x.

M. Mohsin Atiq, A. S. Shakir, and H. N. Hashmi, “Safe Passage of Riverine Flood from Highly Urbanized City: A Case Study of Lahore City in Pakistan,” J. Civ. Environ. Eng., vol. 08, no. 04, 2018, doi: 10.4172/2165-784x.1000320.

H. S. Chang and T. L. Chen, “Spatial heterogeneity of local flood vulnerability indicators within flood-prone areas in Taiwan,” Environ. Earth Sci., vol. 75, no. 23, 2016, doi: 10.1007/s12665-016-6294-x.

Y. Hirabayashi et al., “Global flood risk under climate change,” Nat. Clim. Chang., vol. 3, no. 9, pp. 816–821, 2013, doi: 10.1038/nclimate1911.

A. Ali, Mechanisms , Impacts , and Management. 2013.

K. Ahmad and W. Al, “Variation in the ravi river water quality,” Sanit. Water All Proc. 24th WEDC Conf., pp. 153–156, 1998.

H. A. Shakir and J. I. Qazi, “‘Impact of industrial and municipal discharges on growth coefficient and condition factor of major carps from lahore stretch of river Ravi,’” J. Anim. Plant Sci., vol. 23, no. 1, pp. 167–173, 2013.

M. Akhtar, S. Mahboob, S. Sultana, T. Sultana, K. A. Alghanim, and Z. Ahmed, “Assessment of pesticide residues in flesh of Catla catla from Ravi River, Pakistan,” Sci. World J., vol. 2014, 2014, doi: 10.1155/2014/708532.

R. G. Death, I. C. Fuller, and M. G. Macklin, “Resetting the river template: The potential for climate-related extreme floods to transform river geomorphology and ecology,” Freshw. Biol., vol. 60, no. 12, pp. 2477–2496, 2015, doi: 10.1111/fwb.12639.

K. Chapi et al., “Spatial-Temporal Dynamics of Runoff Generation Areas in a Small Agricultural Watershed in Southern Ontario,” J. Water Resour. Prot., vol. 07, no. 01, pp. 14–40, 2015, doi: 10.4236/jwarp.2015.71002.

K. Komi, J. Neal, M. A. Trigg, and B. Diekkrüger, “Modelling of flood hazard extent in data sparse areas: a case study of the Oti River basin, West Africa,” J. Hydrol. Reg. Stud., vol. 10, pp. 122–132, 2017, doi: 10.1016/j.ejrh.2017.03.001.

K. Khosravi et al., “A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods,” J. Hydrol., vol. 573, pp. 311–323, Jun. 2019, doi: 10.1016/J.JHYDROL.2019.03.073.

Z. Zhu et al., “Benefits of the free and open Landsat data policy,” Remote Sens. Environ., vol. 224, no. February, pp. 382–385, 2019, doi: 10.1016/j.rse.2019.02.016.

M. K. Shah, M. E. Student, A. T. Motiani, and I. Prakash, “Assessment of Coastal and Adjacent Area Flooding of Jamnagar District Using Remote,” vol. 1, no. 11, pp. 68–75, 2015.

G. Ettritch, A. Hardy, L. Bojang, D. Cross, P. Bunting, and P. Brewer, “Enhancing digital elevation models for hydraulic modelling using flood frequency detection,” Remote Sens. Environ., vol. 217, no. August, pp. 506–522, 2018, doi: 10.1016/j.rse.2018.08.029.

A. R. da Paz, W. Collischonn, C. E. M. Tucci, and C. R. Padovani, “Large-scale modelling of channel flow and floodplain inundation dynamics and its application to the Pantanal (Brazil),” Hydrol. Process., vol. 25, no. 9, pp. 1498–1516, 2011, doi: 10.1002/hyp.7926.

J. Neal, G. Schumann, and P. Bates, “A subgrid channel model for simulating river hydraulics and floodplain inundation over large and data sparse areas,” Water Resour. Res., vol. 48, no. 11, pp. 1–16, 2012, doi: 10.1029/2012WR012514.

M. A. Butt et al., “Flood Frequency Analysis of Chenab River for Predicting Peak Flows during Late Monsoon Period,” Adv. Remote Sens., vol. 08, no. 01, pp. 1–29, 2019, doi: 10.4236/ars.2019.81001.

H. Aksoy, V. S. Ozgur Kirca, H. I. Burgan, and D. Kellecioglu, “Hydrological and hydraulic models for determination of flood-prone and flood inundation areas,” IAHS-AISH Proc. Reports, vol. 373, pp. 137–141, 2016, doi: 10.5194/piahs-373-137-2016.

P. Dimitriadis et al., “Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping,” J. Hydrol., vol. 534, pp. 478–492, 2016, doi: 10.1016/j.jhydrol.2016.01.020.

F. Zhang, S. Ahmad, H. Zhang, X. Zhao, X. Feng, and L. Li, “Simulating low and high streamflow driven by snowmelt in an insufficiently gauged alpine basin,” Stoch. Environ. Res. Risk Assess., vol. 30, no. 1, pp. 59–75, 2016, doi: 10.1007/s00477-015-1028-2.

F. Onen and T. Bagatur, “Prediction of Flood Frequency Factor for Gumbel Distribution Using Regression and GEP Model,” Arab. J. Sci. Eng., vol. 42, no. 9, pp. 3895–3906, 2017, doi: 10.1007/s13369-017-2507-1.

M. G. and M. G. Jaya Gupta, “The Lomax-Gumbel Distribution,” Palest. J. Math., vol. 5, no. 1, pp. 35–42, 2016.

Y. M. Gómez, H. Bolfarine, and H. W. Gómez, “Gumbel distribution with heavy tails and applications to environmental data,” Math. Comput. Simul., vol. 157, pp. 115–129, 2019, doi: 10.1016/j.matcom.2018.10.003.

S. Ahmed and I. Tsanis, “Climate Change Impact on Design Storm and Performance of Urban Storm-Water Management System - A Case Study on West Central Mountain Drainage Area in Canada,” J. Waste Water Treat. Anal., vol. 07, no. 01, pp. 1–11, 2015, doi: 10.4172/2157-7587.1000229.