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Pakistan is a flood-prone country and almost every year, it is hit by floods of varying magnitudes. This study was conducted to generate a flash flood map using analytical hierarchy process (AHP) and frequency ratio (FR) models in the ArcGIS 10.6 environment. Eight flash-flood-causing physical parameters were considered for this study. Five parameters were based on the digital elevation model (DEM), Advanced Land Observation Satellite (ALOS), and Sentinel-2 satellite, including distance from the river and drainage density slope, elevation, and land cover, respectively. Two other parameters were geology and soil, consisting of different rock and soil formations, respectively, where both layers were classified based on their resistance against water percolation. One parameter was rainfall. Rainfall observation data obtained from five meteorological stations exist close to the Chitral District, Pakistan. According to its significant importance in the occurrence of a flash flood, each criterion was allotted an estimated weight with the help of AHP and FR. In the end, all the parameters were integrated using weighted overlay analysis in which the influence value of the drainage density was given the highest value. This gave the output in terms of five flood risk zones: very high risk, high risk, moderate risk, low risk, and very low risk. According to the results, 1168 km2, that is, 8% of the total area, showed a very high risk of flood occurrence. Reshun, Mastuj, Booni, Colony, and some other villages were identified as high-risk zones of the study area, which have been drastically damaged many times by flash floods. This study is pioneering in its field and provides policy guidelines for risk managers, emergency and disaster response services, urban and infrastructure planners, hydrologists, and climate scientists.
Hassan Waqas; Linlin Lu; Aqil Tariq; Qingting Li; Muhammad Baqa; Jici Xing; Asif Sajjad. Flash Flood Susceptibility Assessment and Zonation Using an Integrating Analytic Hierarchy Process and Frequency Ratio Model for the Chitral District, Khyber Pakhtunkhwa, Pakistan. Water 2021, 13, 1650 .
AMA StyleHassan Waqas, Linlin Lu, Aqil Tariq, Qingting Li, Muhammad Baqa, Jici Xing, Asif Sajjad. Flash Flood Susceptibility Assessment and Zonation Using an Integrating Analytic Hierarchy Process and Frequency Ratio Model for the Chitral District, Khyber Pakhtunkhwa, Pakistan. Water. 2021; 13 (12):1650.
Chicago/Turabian StyleHassan Waqas; Linlin Lu; Aqil Tariq; Qingting Li; Muhammad Baqa; Jici Xing; Asif Sajjad. 2021. "Flash Flood Susceptibility Assessment and Zonation Using an Integrating Analytic Hierarchy Process and Frequency Ratio Model for the Chitral District, Khyber Pakhtunkhwa, Pakistan." Water 13, no. 12: 1650.
In this paper, the causes and damages of 2010 flood disaster were analyzed in districts Muzaffar Garh. The study area is one of the severely flood affected districts by floods in the past. A mix research approach is applied to analyse the 2010-flood generating factors and damages in the study area. Primary data were acquired through questionnaires, personal observations and Global Positioning System (GPS). Remote Sensing (RS) Landsat-7 ETM data were obtained from USGS online database for pre- and post-flooding periods to delineate the spatial extent of inundation and estimate different land covers classes with damages. Secondary data regarding Rainfall and river discharge were acquired from concerned Government Departments. Modified Normalized Difference in Water Index (MNDWI) was applied to extract inundation, and supervised image classification algorithm was utilized to classify land cover into different classes. The analysis indicates that the flood was generated by extreme rainfall event in the last week of July, 2010 in the upper catchment areas of River Indus. This generated ever highest discharge in the River Indus. As a consequence, this disastrous flow has breached the left marginal embankment (LME) near Taunsa barrage. Spatially, more than half of the land area was inundated. Moreover, the analysis showed that the inundation incurred total estimated economic loss of about 9.85 million US$. Out of total, the maximum damages of 4.45 million US$ were reported from agriculture sector followed by infrastructures 3.5 million US$. This study will provide an empirical basis for flood disaster management authorities to plan disaster response activity and mitigation strategies to reduce the risk of potential damages. The results can also assist decision makers to evaluate breaching points.
Shakeel Mahmood; Asif Sajjad; Atta-Ur Rahman. Cause and damage analysis of 2010 flood disaster in district Muzaffar Garh, Pakistan. Natural Hazards 2021, 107, 1681 -1692.
AMA StyleShakeel Mahmood, Asif Sajjad, Atta-Ur Rahman. Cause and damage analysis of 2010 flood disaster in district Muzaffar Garh, Pakistan. Natural Hazards. 2021; 107 (2):1681-1692.
Chicago/Turabian StyleShakeel Mahmood; Asif Sajjad; Atta-Ur Rahman. 2021. "Cause and damage analysis of 2010 flood disaster in district Muzaffar Garh, Pakistan." Natural Hazards 107, no. 2: 1681-1692.
Span>In riverine flood-prone areas, the delineation of the spatial pattern of flood extents and durations allow flood planners to anticipate likely threats from floods and to formulate actions to mitigate these events. Rapid flood mapping is crucial for flood disaster estimation and evaluation in the early stage. Accurate and timely updates of flood inundation have been made possible by remote sensing techniques. The present study applies the Water indexes and Classification method to analyzes and estimates the riverine Spatio-temporal flood-2014 extent changes using Landsat-8 imagery in Lower Chenab Plain, Pakistan. The lower Chenab plain is particularly prone to frequent riverine flooding but is understudied. It has experienced history worst flooding in September 2014. Optical Landsat-8 data can be used for flood inundation mapping when the flooded areas are clouds free. Cloud free Landsat-8 data was acquired for pre-flood, during-flood, and post-flood periods for detailed analysis. We used different water indexes including Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Water Ratio Index (WRI), Normalized Difference Vegetation Index (NDVI), and Automated Water Extraction Index (AWEI) for the delineation of inundated areas based on increase water index value from pre-flood and post-flood Landsat-8 images. Satellite-derived Water Indexes which are mostly utilized for flood extent estimation that separates the flooded water area from non-flooded areas based on a threshold value. Further, we also used supervised classification to detect flooded areas and compare them with water indexes. The resulted analysis allowed us to compute flood extent area, duration, and flood recession. The inundated area values of used water indexes are higher in the post-flood instance as compared to the pre-flood instance. The proposed RS technique provides an empirical basis for the rapid identification of inundated areas, which would enable emergency response and relief efforts on newly flooded areas in future events. Thus, our study provides another perspective and substantial contributions to flood monitoring using free satellite data in Pakistan.
Asif Sajjad. Rapid Riverine Flood Mapping with Different Water Indices Using Flood Instances Landsat-8 Images. Proceedings of 5th International Electronic Conference on Water Sciences 2020, 1 .
AMA StyleAsif Sajjad. Rapid Riverine Flood Mapping with Different Water Indices Using Flood Instances Landsat-8 Images. Proceedings of 5th International Electronic Conference on Water Sciences. 2020; ():1.
Chicago/Turabian StyleAsif Sajjad. 2020. "Rapid Riverine Flood Mapping with Different Water Indices Using Flood Instances Landsat-8 Images." Proceedings of 5th International Electronic Conference on Water Sciences , no. : 1.
In flood-prone areas, the delineation of the spatial pattern of historical flood extents, damage assessment, and flood durations allow planners to anticipate potential threats from floods and to formulate strategies to mitigate or abate these events. The Chenab plain in the Punjab region of Pakistan is particularly prone to flooding but is understudied. It experienced its worst riverine flood in recorded history in September 2014. The present study applies Remote Sensing (RS) and Geographical Information System (GIS) techniques to estimate the riverine flood extent and duration and assess the resulting damage using Landsat-8 data. The Landsat-8 images were acquired for the pre-flooding, co-flooding, and post-flooding periods for the comprehensive analysis and delineation of flood extent, damage assessment, and duration. We used supervised classification to determine land use/cover changes, and the satellite-derived modified normalized difference water index (MNDWI) to detect flooded areas and duration. The analysis permitted us to calculate flood inundation, damages to built-up areas, and agriculture, as well as the flood duration and recession. The results also reveal that the floodwaters remained in the study area for almost two months, which further affected cultivation and increased the financial cost. Our study provides an empirical basis for flood response assessment and rehabilitation efforts in future events. Thus, the integrated RS and GIS techniques with supporting datasets make substantial contributions to flood monitoring and damage assessment in Pakistan.
Asif Sajjad; Jianzhong Lu; Xiaoling Chen; Chikondi Chisenga; Nayyer Saleem; Hammad Hassan. Operational Monitoring and Damage Assessment of Riverine Flood-2014 in the Lower Chenab Plain, Punjab, Pakistan, Using Remote Sensing and GIS Techniques. Remote Sensing 2020, 12, 714 .
AMA StyleAsif Sajjad, Jianzhong Lu, Xiaoling Chen, Chikondi Chisenga, Nayyer Saleem, Hammad Hassan. Operational Monitoring and Damage Assessment of Riverine Flood-2014 in the Lower Chenab Plain, Punjab, Pakistan, Using Remote Sensing and GIS Techniques. Remote Sensing. 2020; 12 (4):714.
Chicago/Turabian StyleAsif Sajjad; Jianzhong Lu; Xiaoling Chen; Chikondi Chisenga; Nayyer Saleem; Hammad Hassan. 2020. "Operational Monitoring and Damage Assessment of Riverine Flood-2014 in the Lower Chenab Plain, Punjab, Pakistan, Using Remote Sensing and GIS Techniques." Remote Sensing 12, no. 4: 714.
A. – Lu Sajjad. THE RIVERINE FLOOD CATASTROPHE IN AUGUST 2010 IN SOUTH PUNJAB, PAKISTAN: POTENTIAL CAUSES, EXTENT AND DAMAGE ASSESSMEN. Applied Ecology and Environmental Research 2019, 17, 14121 -14142.
AMA StyleA. – Lu Sajjad. THE RIVERINE FLOOD CATASTROPHE IN AUGUST 2010 IN SOUTH PUNJAB, PAKISTAN: POTENTIAL CAUSES, EXTENT AND DAMAGE ASSESSMEN. Applied Ecology and Environmental Research. 2019; 17 (6):14121-14142.
Chicago/Turabian StyleA. – Lu Sajjad. 2019. "THE RIVERINE FLOOD CATASTROPHE IN AUGUST 2010 IN SOUTH PUNJAB, PAKISTAN: POTENTIAL CAUSES, EXTENT AND DAMAGE ASSESSMEN." Applied Ecology and Environmental Research 17, no. 6: 14121-14142.
Digital elevation models (DEMs) are considered an imperative tool for many 3D visualization applications; however, for applications related to topography, they are exploited mostly as a basic source of information. In the study of landslide susceptibility mapping, parameters or landslide conditioning factors are deduced from the information related to DEMs, especially elevation. In this paper conditioning factors related with topography are analyzed and the impact of resolution and accuracy of DEMs on these factors is discussed. Previously conducted research on landslide susceptibility mapping using these factors or parameters through exploiting different methods or models in the last two decades is reviewed, and modern trends in this field are presented in a tabulated form. Two factors or parameters are proposed for inclusion in landslide inventory list as a conditioning factor and a risk assessment parameter for future studies.
Nayyer Saleem; Enamul Huq; Nana Yaw Danquah Twumasi; Akib Javed; Asif Sajjad. Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review. ISPRS International Journal of Geo-Information 2019, 8, 545 .
AMA StyleNayyer Saleem, Enamul Huq, Nana Yaw Danquah Twumasi, Akib Javed, Asif Sajjad. Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review. ISPRS International Journal of Geo-Information. 2019; 8 (12):545.
Chicago/Turabian StyleNayyer Saleem; Enamul Huq; Nana Yaw Danquah Twumasi; Akib Javed; Asif Sajjad. 2019. "Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review." ISPRS International Journal of Geo-Information 8, no. 12: 545.
In this paper, we assessed 2010 flood-generating factors and extent of damages in one of the severely affected areas in the Central Indus Basin, Pakistan. This study is based on mixed research approach. Primary data were collected through a standard questionnaire using random sampling techniques, unstructured interviews, and field observations. Secondary data were acquired from concerned government departments. Descriptive statistical analysis and spatial analysis techniques were applied to explore 2010 flood disaster causes and damages. Analysis revealed that the flood was generated by the 4-day wet spell (27–30 July 2010) in headwaters zone of the Himalaya–Hindu Kush region, Pakistan. This rainstorm generated heavy discharge in the Indus River system. In several cases, river discharge exceeded the carrying capacity of dams and barrages, and as a consequence, many structures were damaged. In the study area, this heavy flow has left no choice for the flood dealing authorities, but to breach the left bank marginal embankment at RD 32–38 near Kot Addu. Overtopping of the flood on breached section has disrupted the entire area and incurred heavy losses to standing crops, livestock, and physical infrastructure. As a consequence, it has put heavy burden on local community and the country’s economy. The analysis further indicated that the total estimated economic loss caused by this imposed inundation was about 2.54 million US$. Infrastructure was the leading sector with maximum estimated economic loss of l.65 million US$ followed by the agricultural sector. This study will bring the attention of disaster management authorities to devise flood-risk reduction plan and identify suitable locations to be breach in emergency situation. This will reduce risk of flood in downstream areas, physical damages, and economic losses.
Shakeel Mahmood; Atta-Ur Rahman; Asif Sajjad. Assessment of 2010 flood disaster causes and damages in district Muzaffargarh, Central Indus Basin, Pakistan. Environmental Earth Sciences 2019, 78, 63 .
AMA StyleShakeel Mahmood, Atta-Ur Rahman, Asif Sajjad. Assessment of 2010 flood disaster causes and damages in district Muzaffargarh, Central Indus Basin, Pakistan. Environmental Earth Sciences. 2019; 78 (3):63.
Chicago/Turabian StyleShakeel Mahmood; Atta-Ur Rahman; Asif Sajjad. 2019. "Assessment of 2010 flood disaster causes and damages in district Muzaffargarh, Central Indus Basin, Pakistan." Environmental Earth Sciences 78, no. 3: 63.