Climate change and rapid urbanization have increased pressure on drainage systems, posing new challenges to preventing and controlling urban waterlogging. In 2013, China proposed the Sponge City, a strategic measure for urban waterlogging control. This study quantifies the effects of stormwater management measures in runoff reduction for different levels of rainfall and conducts a one-dimensional visual analysis of urban waterlogging risks. At the same time, the best cost-effective scheme is determined based on life-cycle cost, analytic hierarchy process, and regret decision theory. The results showed stormwater management measures could realize the function of runoff control and waterlogging prevention, especially under low precipitation. However, these measures were still not enough to eliminate waterlogging risk. Combined measures have stronger runoff control capabilities than single measures. Considering economic, environmental, and operational impacts comprehensively, the combined measures of bio-retention (BR), permeable pavement (PP), and green roof (GR) were determined as the best cost-effective scheme because of the lowest regret value. The proposed method is helpful to provide reference and decision-making basis for the construction of sponge cities in the future.
Northwest China has experienced dramatic changes in vegetation cover over the past few decades with the Yellow River Basin (YRB) being the most representative area. As the major climate-sensitive area in China, vegetation cover change is one reason for its impact on surface air temperature (SAT). This study uses the observation minus reanalysis (OMR) method to reveal the spatio-temporal variations of vegetation cover and its impact on SAT change over non-urban areas of the YRB from 1982 to 2015. The Global Inventory Modeling and Mapping Studies dataset, SAT derived from meteorological stations, and ERA-interim reanalysis temperature data were used to analyze the relationship between normalized difference vegetation index (NDVI) and temperature variation caused by vegetation change. The NDVI trend (SlopeNDVI) of the entire YRB reached 1.11×10−2 decade−1, which indicated the recovery of vegetation in general. The impact of variation in vegetation conditions on SAT change during 1982–2015 was estimated to be 0.037 °C decade−1, which contributed 7.62% to the temperature change. The mean annual NDVI (MNDVI) and SlopeNDVI in the YRB were significantly negatively correlated (P<0.001) with OMR temperature variation. A negative correlation was exhibited in semi-arid and semi-humid regions, whereas a positive correlation was found in the arid region. The observed changes in vegetation and SAT in the YRB support the theory of the impact of vegetation variation on SAT in China.
Pakistan is water stressed, and its water resources are vulnerable due to uncertain climatic changes. Uncertainties are inherent when it comes to the modeling of water resources. The predicted flow variation in the Kunhar River Basin was modeled using the statistically decreased high-resolution general circulation model (GCM) as an input for the Hydrologiska Byråns Vattenbalansavdelning (HBV) model to assess the hydrological response of the Kunhar River Basin under prevailing climate changes. The model’s best performance during the calibration and validation stages was obtained with a regular 0.87 and 0.79 Nash–Sutcliffe efficiency in the basin, respectively. Under the high-end emission scenario, a 122% increase was expected in evapotranspiration in the rising season of months during the winter period 2059–2079, and such developments were attributed to an immense increase in liquid precipitation and temperature. The model’s output reflects a potential for basin stream flow in terms of increasing liquid precipitation up to 182% at the beginning of the monsoon season in the period 2059–2079 in the scenario of high-end emissions. Moreover, the study produced possible uncertainties in high-elevation zones, where the modeling of a catchment can lead to typical snow ablation and accumulation in future projections. This study revealed that the precipitation rate will increase annually, resulting in an increase in the summer stream flow over the basin, though snow is hardly expected to accumulate in the basin’s future climate.
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