Analysis of effects of climate change on runoff in an urban drainage system: a case study from Seoul, Korea

Climate uncertainty and vulnerability of urban flooding associated with regional risk using multi-criteria analysis in Mumbai, India

The study made a comprehensive effort to examine climatic uncertainties at both yearly and monthly scales, along with mapping flood risks based on different land use categories. Recent studies have progressively been engrossed in demonstrating regional climate variations and associated flood probability to maintain the geo-ecological balance at micro to macro-regions. To carry out this investigation, various historical remote sensing record, reanalyzed and in-situ data sets were acquired with a high level of spatial precision using the Google Earth Engine (GEE) web-based remote sensing platform. Non-parametric techniques and multi-layer integration methods were then employed to illustrate the fluctuations in climate factors alongside creating maps indicating the susceptibility to floods. The study reveals an increased pattern in LST (Land Surface Temperature) (0.03 °C/year), albeit marginal declined in southern coastal regions (-0.15 °C/year) along with uneven rainfall patterns (1.42 mm/year). Moreover, long-term LULC change estimation divulges increased trends of urbanization (16.4 km2/year) together with vegetation growth (8.7 km2/year) from 2002 to 2022. Furthermore, this inquiry involves numerous environmental factors that influence the situation (elevation data, topographic wetness index, drainage density, proximity to water bodies, slope, and soil properties) as well as socio-economic attributes (population) to assess flood risk areas through the utilization of Analytical Hierarchy Process and overlay methods with assigned weights. The outcomes reveal nearly 55 percent of urban land is susceptible to flood in 2022, which were 45 and 37 percent in 2012 and 2002 separately. Additionally, 106 km2 of urban area is highly susceptible to inundation, whereas vegetation also occupies a significant proportion (52 km2). This thorough exploration offers a significant chance to formulate flood management and mitigation strategies tailored to specific regions during the era of climate change.

Long-Term 10 m Resolution Water Dynamics of Qinghai Lake and the Driving Factors

As the largest inland saltwater lake in China, Qinghai Lake plays an important role in regional sustainable development and ecological environment protection. In this study, we adopted a spatial downscaling model for mapping lake water at 10 m resolution through integrating Sentinel-2 and Landsat data, which was applied to map the water extent of Qinghai Lake from 1991 to 2020. This was further combined with the Hydroweb water level dataset to establish an area-level relationship to acquire the 30-year water level and water volume. Then, the driving factors of its water dynamics were analyzed based on the grey system theory. It was found that the lake area, water level, and water volume decreased from 1991 to 2004, but then showed an increasing trend afterwards. The lake area ranges from 4199.23 to 4494.99 km2. The water level decreased with a speed of ~0.05 m/a before 2004 and then increased with a speed of 0.22 m/a thereafter. Correspondingly, the water volume declined by 5.29 km3 in the first 13 years, and rapidly increased by 15.57 km3 thereafter. The correlation between climatic factors and the water volume of Qinghai Lake is significant. Precipitation has the greatest positive impact on the water volume variation with the relational grade of 0.912, while evaporation has a negative impact.

Comparison of urbanization and climate change impacts on urban flood volumes: Importance of urban planning and drainage adaptation

Understanding the drivers behind urban floods is critical for reducing its devastating impacts to human and society. This study investigates the impacts of recent urban development on hydrological runoff and urban flood volumes in a major city located in northern China, and compares the urbanization impacts with the effects induced by climate change under two representative concentration pathways (RCPs 2.6 and 8.5). We then quantify the role of urban drainage system in mitigating flood volumes to inform future adaptation strategies. A geo-spatial database on landuse types, surface imperviousness and drainage systems is developed and used as inputs into the SWMM urban drainage model to estimate the flood volumes and related risks under various urbanization and climate change scenarios. It is found that urbanization has led to an increase in annual surface runoff by 208 to 413%, but the changes in urban flood volumes can vary greatly depending on performance of drainage system along the development. Specifically, changes caused by urbanization in expected annual flood volumes are within a range of 194 to 942%, which are much higher than the effects induced by climate change under the RCP 2.6 scenario (64 to 200%). Through comparing the impacts of urbanization and climate change on urban runoff and flood volumes, this study highlights the importance for re-assessment of current and future urban drainage in coping with the changing urban floods induced by local and large-scale changes.

Source-Based Modeling Of Urban Stormwater Quality Response to the Selected Scenarios Combining Future Changes in Climate and Socio-Economic Factors

The assessment of future trends in urban stormwater quality should be most helpful for ensuring the effectiveness of the existing stormwater quality infrastructure in the future and mitigating the associated impacts on receiving waters. Combined effects of expected changes in climate and socio-economic factors on stormwater quality were examined in two urban test catchments by applying a source-based computer model (WinSLAMM) for TSS and three heavy metals (copper, lead, and zinc) for various future scenarios. Generally, both catchments showed similar responses to the future scenarios and pollutant loads were generally more sensitive to changes in socio-economic factors (i.e., increasing traffic intensities, growth and intensification of the individual land-uses) than in the climate. Specifically, for the selected Intermediate socio-economic scenario and two climate change scenarios (RSP = 2.6 and 8.5), the TSS loads from both catchments increased by about 10 % on average, but when applying the Intermediate climate change scenario (RCP = 4.5) for two SSPs, the Sustainability and Security scenarios (SSP1 and SSP3), the TSS loads increased on average by 70 %. Furthermore, it was observed that well-designed and maintained stormwater treatment facilities targeting local pollution hotspots exhibited the potential to significantly improve stormwater quality, however, at potentially high costs. In fact, it was possible to reduce pollutant loads from both catchments under the future Sustainability scenario (on average, e.g., TSS were reduced by 20 %), compared to the current conditions. The methodology developed in this study was found useful for planning climate change adaptation strategies in the context of local conditions.

Modelling runoff on ceramic tile roofs using the kinematic wave equations

Generally, roofs are the best candidates for rainwater harvesting. In this context, the correct evaluation of the quantity and quality of runoff from roofs is essential to effectively design rainwater harvesting systems. This study aims to evaluate the performance of a kinematic wave based numerical model in simulating runoff on sloping roofs, by comparing the numerical results with the ones obtained from laboratory rainfall simulations on a real-scale Lusa ceramic tile roof. For all studied slopes, simulated discharge hydrographs had a good adjust to observed ones. Coefficient of determination and Nash-Sutcliffe efficiency values were close to 1.0. Particularly, peak discharges, times to peak, peak durations and runoff volumes were very well simulated.