Search

Urban flooding can differ significantly from rural flooding due to the influence of rapidly changing land use and rainfall patterns on runoff in urban areas. Consequently, understanding and managing urban flooding necessitate a comprehensive grasp of these influential factors. This study focuses on assessing the impact of land use and rainfall changes on runoff and flood resilience in urban areas of Chennai, India, utilizing the InVEST-UFRM model. The research includes an evaluation of flood risk and potential damage to building infrastructure, examining 14 sub-basins within the study area with diverse land use and rainfall depths for 2015, 2020, and 2025. Observed rainfall and land use data were employed for 2015 and 2020, while future rainfall data relied on Global Circulation Models (GCMs) of the Coupled Model Inter-comparison Project-6 (CMIP6) outputs and QGIS MOLUSCE plugin predicted land use for 2025. The study identified that the change in land use had a more significant impact on runoff than the temporal change in rainfall amount. Notably, the reduction of water bodies in the study area emerged as a major contributing factor to excessive runoff. The estimated maximum potential damage to built infrastructure in the study area reached approximately 10 billion USD. This research provides valuable insights into urban flood resilience and the impact of land use and rainfall changes and proposes effective measures for flood adaptation and mitigation. The study findings can serve as essential tools for urban planners in an effective management of urban floods in similar regions as investigated here. [ABSTRACT FROM AUTHOR]

Rapid urban expansion drives significant land cover changes, which impacts land surface temperature (LST). Understanding the trends in LST is never more relevant in the warming world. In the present study, we obtained the land use and land cover (LULC) change information over the last two decades (2000–2020) and related it with the LST, especially in the vicinity of lakes and vegetation patches. Support Vector Regression (SVR) and Locally Estimated Scatter-plot Smoothing (LOESS) non-parametric regression analyses were fit to explain the LST with the predictor variables consisting of LULC ratios in the vicinity. Results infer that SVR and LOESS models fit the observed LST with the least errors at a correlation of 0.818 and 0.816 for lakes and 0.706 and 0.712 for vegetation patches, respectively. Further, Sobol sensitivity analysis reveals that vegetation cover in the lake buffer zones plays a significant role in LST in the vicinity. Whereas vegetation, barren, and agricultural cover affects LST in vegetation buffer zones as they modify albedo, evapotranspiration, and provide shade that affects LST. The findings provide a new dimension on the role of vegetation in lake buffer areas, which significantly contributes to lowering the LST. This emphasizes re-designing nature-based infrastructure and buffer areas to reap maximum cooling benefits in the warming world. [ABSTRACT FROM AUTHOR]

Urban green spaces (UGS) are known for providing a cooling effect by evapotranspiration, shade, and by altering the albedo. Heat mitigation by UGS reduces the space cooling demand, provides comfort, and enhances productivity. Rapid urbanization in developing countries has resulted in dwindling green spaces and their protective role is often neglected. We have quantified the heat mitigation by UGS using the InVEST model (Integrated Valuation of Ecosystem Services and Trade-offs) for present and future scenarios of Nagpur City which is situated in a heatwave-affected zone. Four future plausible scenarios were generated with a combination of drivers—economic development and commitment to promoting UGS, using the two-axis scenario analysis method. The simulated UGS in each future scenario (by allowing 10% variation in the land use) is utilized for quantification of heat mitigation and energy conserved. In comparison with the present situation, 21–29% less space cooling energy is conserved in scenarios driven by economic development (least commitment to UGS), whereas 17% more energy is conserved when UGS are promoted. In similar lines, the average temperature is increased by 0.5–0.7 °C when UGS are neglected, while the temperature dropped by 0.5 °C when UGS are promoted in Nagpur City. The methodology presents an integration of scenario analysis with heat mitigation modeling which can enable urban planners and researchers to improve their understanding of the ecological structure of urban centers and can aid in appreciating the potential of UGS in heat mitigation for human wellbeing. [ABSTRACT FROM AUTHOR]

According to World Health Organization, 9 out of 10 people breathe polluted air and the ambient air pollution accounts for nearly 4.2 million early deaths worldwide. There is an urgent need for scientific management of urban air systems. Mathematical modeling of air quality helps the researchers and urban authorities in devising scientific management plans for mitigation of the associated impacts. We present an organized review of the broad aspects related to urban air quality modeling such as – urban microclimate, geospatial data, chemical transport models, computational fluid dynamics (CFD) models and integration of CFD and mesoscale models. The paper also discusses about the influence of urban land scape features on air quality, accuracy of emission inventory and model validation methods. The present review provides a vantage point to the researchers in the emerging field of high resolution urban air quality modeling for devising the location specific mitigation plans for the scientific management of the clean air. [ABSTRACT FROM AUTHOR]

In the rapidly urbanizing country like India, the transportation sector is growing rapidly, which lead to overcrowded roads producing air and noise pollution. Noise of a particular region is influenced by the volume of traffic on the highway, in addition to other causative factors like existing infrastructure and industrial setup etc. In the present paper, a geographical information system (GIS)-based noise simulation model has been developed to generate noise levels in Versova region of Mumbai, India. The study area comprises effect of infrastructure, road network, traffic volume, and various mechanical components like sewage pumping station and wastewater treatment facility. Various meteorological parameters and effect of land use and land cover on noise attenuation are also considered in the model. In this way, commutative noise prediction for point as well as mobile sources has been presented in the study. GIS-based noise simulation has been calibrated with observed noise levels during day and night time with correlation of 0.84 and 0.74, respectively. [ABSTRACT FROM AUTHOR]