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Article

Characterization of the 2014 Indus River Flood Using Hydraulic Simulations and Satellite Images

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State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China
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CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal
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Department of Geography, University of the Punjab, Lahore 54590, Pakistan
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School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK
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Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
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Faculty of Water Resource Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 100000, Vietnam
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Environmental Quality, Atmospheric Science and Climate Change Research Group, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
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Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
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Author to whom correspondence should be addressed.
Academic Editors: Apoorva Shastry and Adnan Rajib
Remote Sens. 2021, 13(11), 2053; https://doi.org/10.3390/rs13112053
Received: 6 March 2021 / Revised: 8 May 2021 / Accepted: 18 May 2021 / Published: 23 May 2021
Rivers play an essential role to humans and ecosystems, but they also burst their banks during floods, often causing extensive damage to crop, property, and loss of lives. This paper characterizes the 2014 flood of the Indus River in Pakistan using the US Army Corps of Engineers Hydrologic Engineering Centre River Analysis System (HEC-RAS) model, integrated into a geographic information system (GIS) and satellite images from Landsat-8. The model is used to estimate the spatial extent of the flood and assess the damage that it caused by examining changes to the different land-use/land-cover (LULC) types of the river basin. Extreme flows for different return periods were estimated using a flood frequency analysis using a log-Pearson III distribution, which the Kolmogorov–Smirnov (KS) test identified as the best distribution to characterize the flow regime of the Indus River at Taunsa Barrage. The output of the flood frequency analysis was then incorporated into the HEC-RAS model to determine the spatial extent of the 2014 flood, with the accuracy of this modelling approach assessed using images from the Moderate Resolution Imaging Spectroradiometer (MODIS). The results show that a supervised classification of the Landsat images was able to identify the LULC types of the study region with a high degree of accuracy, and that the most affected LULC was crop/agricultural land, of which 50% was affected by the 2014 flood. Finally, the hydraulic simulation of extent of the 2014 flood was found to visually compare very well with the MODIS image, and the surface area of floods of different return periods was calculated. This paper provides further evidence of the benefit of using a hydrological model and satellite images for flood mapping and for flood damage assessment to inform the development of risk mitigation strategies. View Full-Text
Keywords: flood characterization; HEC-RAS; hydraulic simulation; Indus River; Landsat; MODIS flood characterization; HEC-RAS; hydraulic simulation; Indus River; Landsat; MODIS
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MDPI and ACS Style

Tariq, A.; Shu, H.; Kuriqi, A.; Siddiqui, S.; Gagnon, A.S.; Lu, L.; Linh, N.T.T.; Pham, Q.B. Characterization of the 2014 Indus River Flood Using Hydraulic Simulations and Satellite Images. Remote Sens. 2021, 13, 2053. https://doi.org/10.3390/rs13112053

AMA Style

Tariq A, Shu H, Kuriqi A, Siddiqui S, Gagnon AS, Lu L, Linh NTT, Pham QB. Characterization of the 2014 Indus River Flood Using Hydraulic Simulations and Satellite Images. Remote Sensing. 2021; 13(11):2053. https://doi.org/10.3390/rs13112053

Chicago/Turabian Style

Tariq, Aqil, Hong Shu, Alban Kuriqi, Saima Siddiqui, Alexandre S. Gagnon, Linlin Lu, Nguyen T.T. Linh, and Quoc B. Pham. 2021. "Characterization of the 2014 Indus River Flood Using Hydraulic Simulations and Satellite Images" Remote Sensing 13, no. 11: 2053. https://doi.org/10.3390/rs13112053

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