Impact of urbanization on basin hydrology: a case study of the Malir Basin, Karachi, Pakistan

Zafar, Sumaira; Zaidi, Arjumand

doi:10.1007/s10113-019-01512-9

Cited by 24 publications

(10 citation statements)

References 16 publications

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“…Urban areas have increasingly become vulnerable to flooding, and losses of human lives, animals, and property have been recorded. Flood disasters and their related damages have become severe in all four cities (see for details regarding Mumbai [18,19,98,99], Colombo [100][101][102], Karachi [103], and Dhaka [104]). Rapid urban development has damaged the natural drainage systems creating blocks.…”

Section: Urbanization Related Issues and Future Challengesmentioning

confidence: 99%

Spatial Analysis of Urbanization Patterns in Four Rapidly Growing South Asian Cities Using Sentinel-2 Data

et al. 2021

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The rapid and dominant urbanization in Asian cities has fueled concerns regarding the local and global efforts toward urban sustainability. Specifically, South Asian cities have been a topical issue concerning ecological and environmental threats due to their unplanned and haphazard urban development. However, comparative urbanization studies in South Asian cities remain uncommon. Therefore, in this study, we sought to comparatively examine the land use and land cover (LULC) dynamics and to detect the urbanization patterns of four rapidly developing South Asian lowland cities: Mumbai (India), Colombo (Sri Lanka), Karachi (Pakistan), and Dhaka (Bangladesh). Sentinel-2 (10 m) data and various geospatial approaches, including urban–rural gradient and grid-based methods, statistics, and urban landscape metric techniques, were used to facilitate the analysis. The study revealed that Mumbai, Karachi, and Dhaka had larger built-up landscapes compared to Colombo. Mumbai had the highest percentage of green spaces, followed by Colombo. Dhaka and Karachi had relatively small percentages of green spaces. Colombo and Dhaka had more croplands, which consistently increased along the urban–rural gradient compared to Mumbai and Karachi. Karachi showed that the only major land use was built-up, while most of the areas were left as open lands. On the other hand, Colombo’s urban setup was more fragmented than the other three cities. Mumbai and Karachi had larger patches of urban footprints compared to Colombo and Dhaka. Thus, this study provides vital information on the past land utilization priorities in the four cities, and comparatively proffers guidance on certain critical areas of focus for local, regional, and global future sustainable urban planning.

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Section: Urbanization Related Issues and Future Challengesmentioning

confidence: 99%

Spatial Analysis of Urbanization Patterns in Four Rapidly Growing South Asian Cities Using Sentinel-2 Data

et al. 2021

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“…However, a key characteristic of Karachi’s climate is the often unpredictable level of rainfall on a yearly basis [ 40 ]. In addition to causing warmer temperatures in Karachi over the past few years, climate change has likely contributed to the heightened variability in monsoon rains in the city and throughout the Indian subcontinent [ 38 , 39 ]. According to data collected by the Pakistan Meteorological Department from 1985 to 2014, Karachi’s average annual precipitation ranges from 10 to 150 mm [ 41 ].…”

Section: The Emerging Threat Of Climate Change In Karachimentioning

confidence: 99%

“…According to data collected by the Pakistan Meteorological Department from 1985 to 2014, Karachi’s average annual precipitation ranges from 10 to 150 mm [ 41 ]. To illustrate this phenomenon, 2014 went down as one of the driest years on record over the past couple of decades in Karachi, with total annual rainfall falling under 50 mm [ 38 ]. This dry year stands in stark contrast to the 142 mm of precipitation Karachi received in a span of just 24 hours in July 2009 [ 38 ].…”

Section: The Emerging Threat Of Climate Change In Karachimentioning

confidence: 99%

“…To illustrate this phenomenon, 2014 went down as one of the driest years on record over the past couple of decades in Karachi, with total annual rainfall falling under 50 mm [ 38 ]. This dry year stands in stark contrast to the 142 mm of precipitation Karachi received in a span of just 24 hours in July 2009 [ 38 ]. Cycles of drought and intense rainfall in the city continue to present a substantial threat to Karachiites.…”

Section: The Emerging Threat Of Climate Change In Karachimentioning

confidence: 99%

“…It is also worth noting that the natural drainage system of Karachi comprises 3 major river systems: the Hub, Lyari, and Malir rivers. Although these river basins were once capable of diverting storm water safely to the Arabian Sea, the riverbeds have been adversely affected by urban settlements and agricultural activities [ 38 , 39 ]. This phenomenon has made Karachi further susceptible to the detrimental effects of monsoon season flooding.…”

Section: The Emerging Threat Of Climate Change In Karachimentioning

confidence: 99%

See 2 more Smart Citations

NTDs in the age of urbanization, climate change, and conflict: Karachi, Pakistan as a case study

Fazal

Hotez

2020

PLoS Negl Trop Dis

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Using big data for evaluating development outcomes: A systematic map

Rathinam

Khatua²,

Siddiqui³

et al. 2021

Campbell Systematic Reviews

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Background Policy makers need access to reliable data to monitor and evaluate the progress of development outcomes and targets such as sustainable development outcomes (SDGs). However, significant data and evidence gaps remain. Lack of resources, limited capacity within governments and logistical difficulties in collecting data are some of the reasons for the data gaps. Big data—that is digitally generated, passively produced and automatically collected—offers a great potential for answering some of the data needs. Satellite and sensors, mobile phone call detail records, online transactions and search data, and social media are some of the examples of big data. Integrating big data with the traditional household surveys and administrative data can complement data availability, quality, granularity, accuracy and frequency, and help measure development outcomes temporally and spatially in a number of new ways.The study maps different sources of big data onto development outcomes (based on SDGs) to identify current evidence base, use and the gaps. The map provides a visual overview of existing and ongoing studies. This study also discusses the risks, biases and ethical challenges in using big data for measuring and evaluating development outcomes. The study is a valuable resource for evaluators, researchers, funders, policymakers and practitioners in their effort to contributing to evidence informed policy making and in achieving the SDGs. Objectives Identify and appraise rigorous impact evaluations (IEs), systematic reviews and the studies that have innovatively used big data to measure any development outcomes with special reference to difficult contexts Search Methods A number of general and specialised data bases and reporsitories of organisations were searched using keywords related to big data by an information specialist. Selection Criteria The studies were selected on basis of whether they used big data sources to measure or evaluate development outcomes. Data Collection and Analysis Data collection was conducted using a data extraction tool and all extracted data was entered into excel and then analysed using Stata. The data analysis involved looking at trends and descriptive statistics only. Main Results The search yielded over 17,000 records, which we then screened down to 437 studies which became the foundation of our systematic map. We found that overall, there is a sizable and rapidly growing number of measurement studies using big data but a much smaller number of IEs. We also see that the bulk of the big data sources are machine‐generated (mostly satellites) represented in the light blue. We find that satellite data was used in over 70% of the measurement studies and in over 80% of the IEs. Authors' Conclusions This map gives us a sense that there is a lot of work being done to develop appropriate measures using big data which could subsequently be used in IEs. Information on costs, ethics, transparency is lacking in the studies and more work is needed in this area to understand the efficaci...

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Impact of urbanization on basin hydrology: a case study of the Malir Basin, Karachi, Pakistan

Cited by 24 publications

References 16 publications

Spatial Analysis of Urbanization Patterns in Four Rapidly Growing South Asian Cities Using Sentinel-2 Data

Spatial Analysis of Urbanization Patterns in Four Rapidly Growing South Asian Cities Using Sentinel-2 Data

NTDs in the age of urbanization, climate change, and conflict: Karachi, Pakistan as a case study

Using big data for evaluating development outcomes: A systematic map

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