Deconstructing urban flooding from the perspective of vulnerable communities in Northwestern Pakistan

Urban flooding is a frequent disaster in cities. With the increasing imperviousness caused by rapid urbanization and the rising frequency and severity of extreme events caused by climate change, the hydrological status of the urban area has changed, resulting in urban floods. This study aims to identify trends and gaps and highlight potential research prospects in the field of urban flooding in South Asia. Based on an extensive literature review, this paper reviewed urban flood hazard assessment methods using hydraulic/hydrological models and urban flood management practices in South Asia. With the advancement of technology and high-resolution topographic data, hydrologic/hydraulic models such as HEC-RAS/HMS, MIKE, SWMM, etc., are increasingly used for urban flood hazard assessment. Urban flood management practices vary among countries based on existing technologies and infrastructures. In order to control urban flooding, both conventional physical structures, including drainage and embankments, as well as new innovative techniques, such as low-impact development, are implemented. Non-structural flood mitigation measures, such as improved flood warning systems, have been developed and implemented in a few cities. The major challenge in using process-based hydraulic models was the lack of high-resolution DEM and short-duration rainfall data in the region, significantly affecting the model’s simulation results and the implementation of flood management measures. Risk-informed management must be implemented immediately to reduce the adverse effects of climate change and unplanned urbanization on urban flooding. Therefore, it is crucial to encourage emergency managers and local planning authorities to consider a nature-based solution in an integrated urban planning approach to enhances urban flood resilience.

This study investigates the relationship between Land Use and Land Cover (LULC) changes and urban flooding in the Sri Jayewardenepura Kotte Divisional Secretariat Division (DSD). The research objectives include analysing flooding patterns, mapping LULC changes, and assessing the correlation between these changes and flooding occurrences. Additionally, a temporal rainfall variation analysis was conducted to provide further context. The study employed Geographic Information System (GIS) technology, specifically utilising ArcGIS for LULC classification and Inverse Distance Weighting (IDW) interpolation technique for rainfall data. The analysis reveals a clear association between heightened precipitation and major flood events. In 2010, the flood inundation area was 5.762 km² during the major flood in May, despite a monthly rainfall of over 650mm. However, in 2016, with over 700 mm of rainfall in May, the flood-inundated area was reduced to 4.046 km², highlighting the role of other factors such as wetland recovery. Moreover, it identifies significant LULC changes, emphasising rapid urbanisation and wetland decline. From 2009 to 2018, built-up areas increased from 11.49 km² to 14.18 km², while wetlands decreased from 2.29 km² in 2009 to 1.19 km² in 2015, before recovering slightly to 1.58 km² by 2018. The expansion of built-up areas is found to slightly increase flood risks, while wetland recovery acts as a natural flood buffer. This research underscores the importance of targeted interventions for urban flood resilience, such as flood-resistant infrastructure and wetland management. The findings provide critical insights for evidence-based urban planning and flood management strategies, aiming to create more resilient and sustainable urban environments.

Urban flooding has been an alarming issue in the past around the globe, particularly in South Asia. Pakistan is no exception from this situation where urban floods with associated damages are frequently occurring phenomena. In Pakistan, rapid urbanization is the key factor for urban flooding, which is not taken into account. This study aims to identify flood sensitivity and coping capacity while assessing urban flood resilience and move a step toward the initialization of resilience, specifically for Peshawar city and generally for other cities of Pakistan. To achieve this aim, an attempt has been made to propose an integrated approach named the “urban flood resilience model (UFResi-M),” which is based on geographical information system(GIS), remote sensing (RS), and the theory of analytical hierarchy process (AHP). The UFResi-M incorporates four main factors—urban flood hazard, exposure, susceptibility, and coping capacity into two parts, i.e., sensitivity and coping capacity. The first part consists of three factors—IH, IE, and IS—that represent sensitivity, while the second part represents coping capacity (ICc). All four indicators were weighted through AHP to obtain product value for each indicator. The result showed that in the Westzone of the study area, the northwestern and central parts have very high resilience, whereas the southern and southwestern parts have very low resilience. Similarly, in the East zone of the study area, the northwest and southwest parts have very high resilience, while the northern and western parts have very low resilience. The likelihood of the proposed model was also determined using the receiver operating characteristic (ROC) curve method; the area under the curve acquired for the model was 0.904. The outcomes of these integrated assessments can help in tracking community performance and can provide a tool to decision makers to integrate the resilience aspect into urban flood management, urban development, and urban planning.

Serving the purpose of an early warning, this paper provides a multi-disciplinary analysis of how thechanging dynamics of tourist arrivals can lead to rapid and unplanned urbanization. The improvements in infrastructureand communication systems under the aegis of China-Pakistan Economic Corridor (CPEC) in Gilgit-Baltistan have ledto exponential increase in tourists arrival in recent years. Does this increase lead to increase in incomes and spurring anunplanned and rapid urbanization? Hunza district is taken as a case study on the basis of evidence suggesting thataround 70 percent of total tourists Gilgit-Baltistan. To explore the relationship between tourists arrival and rapidurbanization, three types of data were used: survey data collected via questionnaires, secondary data from governmentsources, and Google images, Landsat-7 and Landsat-8 from remotely sensed data. Using cross-tabulations, this studysuggests that tourists arrival led to increase in incomes, which were then spent on building commercial infrastructure.To cross check these results, land use land change study using GIS mapping was conducted for the last ten yearsperiod. It shows that rapid and unplanned urbanization has profound social and environmental implications for Hunza,if not managed properly and timely.

Serving the purpose of an early warning, this paper provides a multi-disciplinary analysis of how thechanging dynamics of tourist arrivals can lead to rapid and unplanned urbanization. The improvements in infrastructureand communication systems under the aegis of China-Pakistan Economic Corridor (CPEC) in Gilgit-Baltistan have ledto exponential increase in tourists arrival in recent years. Does this increase lead to increase in incomes and spurring anunplanned and rapid urbanization? Hunza district is taken as a case study on the basis of evidence suggesting thataround 70 percent of total tourists Gilgit-Baltistan. To explore the relationship between tourists arrival and rapidurbanization, three types of data were used: survey data collected via questionnaires, secondary data from governmentsources, and Google images, Landsat-7 and Landsat-8 from remotely sensed data. Using cross-tabulations, this studysuggests that tourists arrival led to increase in incomes, which were then spent on building commercial infrastructure.To cross check these results, land use land change study using GIS mapping was conducted for the last ten yearsperiod. It shows that rapid and unplanned urbanization has profound social and environmental implications for Hunza,if not managed properly and timely.

Uncertainties of urban flood modeling: Influence of parameters for different underlying surfaces

The Bangkok Metropolitan Region (BMR), located in the Chao Phraya River basin delta, is particularly vulnerable to floods, with susceptibility heightened by geographical aspects and rapid urbanization. This study aimed to assess spatiotemporal flood exposure and allow proper flood‐risk recognition among all stakeholders through a three‐phase flood exposure assessment. First, land use and land cover (LULC) changes were identified based on a 30‐year Landsat time series. Second, built‐up areas that overlapped with past flood inundation maps were designated as flood exposure areas. Third, a rainfall‐runoff inundation (RRI) model simulated the 2011 Thailand Flood, the largest on record, by analyzing inundation depth implications across three decades. The findings revealed a dramatic increase in the use of built‐up areas and the associated flood exposure. In 1992, built‐up areas accounted for approximately 20% of the total area, sharply increasing to nearly 45% by 2022, according to the LULC classification. The flood exposure increased from 648.83 km2 in 1992 to 1681.26 km2 by 2022, demonstrating a linear trend. Notably, the catastrophic 2011 flood did not inhibit urbanization in flood‐prone areas, highlighting the need for robust policies, such as the segmentation of flood‐risk zones, to mitigate future exposure in the region.

MotivationRecurring urban flooding in Bengaluru, India, has brought multiple intersecting development challenges to the forefront. While climate change is a catalyst for flooding, rapid urbanisation has aggravated the problem by neglecting its ecological history. Repeated floods have particularly affected migrants living in the slums, further worsening their already vulnerable conditions. Currently, only about 40% of slums are formally recognized by city authorities, leaving most slum dwellers with limited access to public benefits and basic infrastructure. Although the city offers piecemeal solutions, it currently lacks foresight for long‐term planning that includes marginalized voices.PurposeWe explore the multiple and intertwined development challenges faced by Bengaluru city, attempting to frame them from the perspective of migrant slum dwellers experiencing flooding. We try to bring to the forefront the everyday risks and vulnerabilities of the marginalized populations in Indian cities, which have received limited attention both in research and policy.The results of this exercise are intended to create sustainable collaborative processes to inform future decisions, particularly addressing the problem of urban flooding.Methods and approachOur proposed methodology integrates climate risk assessment—urban flood modelling and exposure mapping of slums across the city—with vulnerability assessments at the household level including analysis of life histories to capture the relative vulnerabilities of slum dwellers and the slums in which they live.FindingsWe deconstruct urban flooding, particularly from the perspective of migrant slum dwellers to identify some critical challenges, especially that of recognition, to foresight thinking. By incorporating marginalized voices, our methods aim to be inclusive and contextually relevant, while considering intersectional variations among those marginalized.A mixed‐methods approach allows climate risk assessment to be augmented by life histories of vulnerable slum populations to collaboratively reimagine a more inclusive future.Policy implicationsTo make policy more inclusive, more participatory processes are needed. The proposed methods will contextualize everyday vulnerabilities and risks of migrant slum dwellers to bring these perspectives into conventional climate risk assessment. Thus, a more inclusive future with lower impacts from urban floods can be envisaged.

Based on Remote Sensing image processing and Geographic Information Systems analysis, population-dependent urban structures can be accurately monitored, analysed, and potential spatial or environmental problems restrained by professional land use management. In this study, the city of Nizip, located within the province of Gaziantep, was evaluated in this perspective and its development in the last thirty years was determined. The satellite images of 1990 and 2019 were evaluated within the framework of CORINE land classification system. The controlled classification method was implemented in the analysis and the city's growth rate and direction were determined while land cover changes were investigated both statistically and spatially. According to the analysis, residential areas in the study area, which were 555 ha in 1990, exceeded 1000 ha in 2019, due to industrialization and population growth. Urban sprawl was observed in NE and E directions. In addition, the bare lands of the city have been converted to dry agricultural lands in the last three decades which is supposedly due to long term climate effects. Along with the increasing industrialization movement in this period, the population increased by 30% on average in the central neighbourhoods. Migration from evacuated villages to the city centre following dam construction and water impoundment phases has increased the population. Rapid urbanization is also observed alongside newly built highways and motorways. Regarding increasing population movements in recent years, it is predicted that there could be spatial and environmental problems due to rapid and unplanned urbanization in Nizip city. It is stated that the elimination of these problems can be carried out through accurate and planned land use decision support systems.

Rapid unplanned urbanization is a common phenomenon in developing countries and the necessity for making an urban area sustainable and livable is one of the major challenges of today’s world. While the timely identification of the factors contributing to rapid unplanned urbanization is essential, uncovering the core reasons behind this phenomenon remains one of the most challenging tasks. The Night Light Development Index (NLDI) can track and monitor urbanization over time and can be used for understanding and optimizing the use of urban space at night due to its timely availability and accessibility. Previous research has only been conducted using VIIRS or DMP OLS satellite imagery to calculate the NLDI. However, the temporal and spatial resolution of these types of imagery are quite poor and require a lot of preprocessing. In this research, these complexities are addressed by introducing a modified NLDI, leveraging high-resolution nighttime imagery from NASA’s Black Marble product suite and population data from NASA’s Socioeconomic Data and Applications Center (SEDAC). This study examines the core drivers of unplanned urbanization in Dhaka by analyzing changes in regional inequality, electrification patterns, and GDP in relation to nighttime light, amidst the significant challenges posed by rapid urbanization in developing countries. The results indicate significant transformations in Dhaka’s urban land cover change (ULCC), with substantial increases in built-up areas correlating with heightened electrification and economic activity/GDP, as evidenced by NTL radiance patterns. Furthermore, the modified NLDI effectively captures the nuances of urban development and inequality, offering insights into regional disparities and urban planning challenges. We find that the income inequality or the NLDI value is the highest in the Biman Bandar area (0.910), followed by Pallabi (0.665), Turag (0.640), and Khilkhet (0.587). These values indicate significant income disparity between affluent and impoverished populations within these regions.

Detrimental land cover conversion has emerged as a pressing issue in the Quinali A Watershed, Albay, the Philippines. However, there has been a lack of monitoring regarding the change and its repercussions. Establishing baseline information is imperative to enable informed decisions and policies toward sustainable development. Landsat images were used to analyze the land cover changes in Quinali A Watershed from 1990–2020. Two-dimensional flood models and landscape metrics derived from FRAGSTATS were employed to assess the impacts of land cover change on flood exposure and landscape fragmentation. Results revealed that cropland, artificial surfaces, submerged vegetation, and inland water increased since 1990, but at the expense of forest, brushland, and barrenland. Generally, flooding occurs in areas of topographic lows of the watershed. The expansion of artificial surfaces took place in flood-prone areas, nearly doubling the flood exposure rates recorded in 1990. Despite cropland expansion, it decreased in the low-lying areas of the watershed, resulting in reduced exposure to flooding. The annual rate of change indicates substantial increases of 2.77 and 0.79% in NP for artificial surfaces and barren land, respectively, with ED increasing by 2.73 and 0.74%. AWM increased by 1.62% in non-forest areas, whereas forest areas showed an increase of 0.65%. Although the PAFRAC decreased by 0.02%, it maintained a high value of 1.53 in 1990 and 1.52 in 2020, indicating low stability of the land cover structure within the watershed landscape. Continuous monitoring of these changes is imperative to recommend science- based policies that can regulate resource utilization in Quinali A Watershed.

Urban flood hazard is a typical natural disaster that occurs due to the reduction of permeable surfaces as a result of land use conversion and changes in rainfall intensity. It ensures the need of different mitigation strategies such as sufficient drainage system, and it is a simple mitigation measure that can be applied in the ground. This paper is timely due to the lack of research studies undertaken that are related to the study area. Natural disasters, flood hazard, influence of urbanization for urban flood, and negative influence of urban flood in the context of the world and Asian region have been discussed in the available literature. Limited research has been undertaken on urban flood mitigation based on hydrological analysis and run off volume calculation in Kaduwela Municipal Council (KMC) area. With this limitation, this paper focuses on analysing the runoff rainwater volume to mitigate urban flood in 2030 (predicted land use) by calculating the rainwater volume in natural and artificial possible outfalls of each watersheds in KMC. The analysis consists of three phases such as: land use prediction, hydrological analysis, and calculation. A GIS-based land use prediction is simulated to analyse the land use changes in relation to green, blue, and brown fills. The revealed land use conversion is also processing day by day as a result of land use conversion and rapid urbanization which will increase the runoff volume in 2030. A GISbased Hydrological analysis was carried out to identify the outfalls and watersheds of the study area. The possible outfalls function as outlets of runoff water which were collected in each watershed. Runoff volume was calculated by using rational formula (Q = 0.0028CIA) and the parameters of the equation used were the coefficient of land use in 2030, rainfall intensity, and 90 acres portion of the watersheds. A sufficient drainage system was also designed to make KMC a disaster resilient municipality. This research will be important in the process of decision-making and policy implementation in the fields of urban planning and flood mitigation.

Urban flood damage is increasing globally, particularly in major cities. Factors contributing to flood risk include urban environmental changes, such as watershed development and precipitation variations caused by climate change. Rapid urbanization and weather anomalies further complicate flood management and damage mitigation. Additionally, detailed analyses at small spatial units (e.g., roads, buildings) remain insufficient. Hence, urban flood analysis considering such spatial variations is required. This study analyzed flood risk in Ulsan, Korea, under a severe flood scenario. Land cover changes from the 1980s to 2010s were examined in 10-year intervals, along with the frequency of heavy rainfall and high river water levels that trigger severe floods. Flood risk was structured as a matrix of likelihood and impact. The results revealed that land cover changes, influenced by development policies or regulations, had a minimal impact on urban flood risk, which is likely because effective drainage systems and stringent urban planning regulations mitigated their effects. However, the frequency and intensity of extreme precipitation events had a substantial effect. These findings were validated using a comparative analysis of an inundation damage trace map and flood range simulated by a physical model. The 10 m grid resolution and time-series likelihood-and-impact framework used in this study can inform budget allocation, resource mobilization, disaster prevention planning, and decision-making during disaster response efforts in major cities.

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

Urban flood risk warning under rapid urbanization