Changes in the hydrological process caused by urbanization lead to frequent flooding in cities. For fast-growing urban areas, the impact of urbanization on the hydrological process needs to be ...systematically analyzed. This study takes Zhengzhou as an example to analyze the impact of urbanization on the hydrological process based on 1971–2012 hourly rainfall-runoff data, combining Geographic Information Systems with traditional hydrological methods. Our study indicates that the rain island effect in different districts of city became stronger with the increase of its built-up. The uneven land use resulted in the difference of runoff process. The flood peak lag was 25–30% earlier with the change of land use. The change of flood peak increased by 10–30% with the change of built-up. The runoff coefficient increases by 20–35% with the increase of built-up, and its change increased with the change of land use. Affected by the rain island effect, precipitation tends to occur in areas where built-up is dominant, which overall magnifies the impact of urbanization on the hydrological process. This provides new ideas for urban flood control. Refine flood control standards according to regional land use changes to cope with the hydrological process after urbanization.
Sensitivity analysis of urban flood model parameters is important for urban flood simulation. Efficient and accurate acquisition of sensitive parameters is the key to real-time model calibration. In ...order to quickly obtain the sensitive runoff parameters of the urban flood simulation model, this study proposes an artificial neural network-based identification method for sensitive parameters. Artificial neural network (ANN) models were constructed with the binary classification and multi-classification methods, and used environmental indicators that affect the parameter sensitivity of different hydrological response units as the input, with the sensitivity parameters of the Storm water management model (SWMM) being the output. The optimization of the ANN was realized by adjusting the number of nodes in the hidden layer and the maximum number of iterations. An example application was conducted in Zhengzhou, China. The results show that the binary classification ANN quickly identified sensitive parameters, and the prediction accuracy of all parameters exceeded 96%. Convergence can be achieved when the number of nodes in the hidden layer does not exceed twice the number of input nodes, and the maximum number of iterations does not exceed 200. Rapid and accurate identification of the sensitive runoff parameters of the urban flood simulation model was achieved, which reduced the time required for parameter sensitivity analysis.
The detection of small targets within the background of sea clutter is a significant challenge faced in radar signal processing. Small target echoes are weak in energy, and can be submerged by sea ...clutter and sea spikes, which are caused by overturning waves and breaking waves. This severely affects the radar target detection performance. This paper proposes a smoothed pseudo-Wigner–Ville distribution–singular value decomposition (SPWVD-SVD) method for sea clutter suppression. This method determines the instantaneous frequency range of the target by contrasting the time–frequency characteristics of the sea spike and the target. Subsequently, it employs a singular value difference spectrum to reduce the rank of the Hankel matrix, thereby reducing the computational burden of the instantaneous frequency estimation step in the experiment. Based on the instantaneous frequency range of the target in the time–frequency domain, the singular values of the target signal are retained, while the singular values of clutter are set to zero. This process accomplishes the reconstruction of radar echo signals and effectively achieves the suppression of sea clutter. The suppression effect is verified using simulation data alongside ten sets of Intelligent Pixel processing X-band (IPIX) radar data against the background of sea spikes. By contrasting the clutter amplitudes before and after suppression, the SPWVD-SVD algorithm demonstrated an average clutter suppression of 15.06 dB, which proves the effectiveness of the proposed algorithm in suppressing sea clutter.
As a key factor in the flood damage assessment process, the damage ratio is defined as the ratio of the potential damage value to the total risk assets at a certain inundation depth. Spatial ...variability of flood‐bearing elements caused spatial heterogeneity, local correlation and neighborhood non‐stationarity to the damage ratio. Thus, it is challenging to scientifically and rationally measure the damage ratio. In this study, a modeling framework of stochastic flood damage assessment functions was established to measure triple uncertainties. First, based on the maximum likelihood estimation method, migration data of the flood damage ratio were constructed as the beta distribution by heterogeneous multi‐attribute analogy. Then, the Markov chain Monte Carlo method, combined with a variant sliding window method, is used for sampling to generate spatially distributed samples. In addition, three risk factors were integrated grid by grid to assess flood damage. By taking the Jinshui District of Zhengzhou City in China as an example, economic losses during the 1%, 2%, 5% and 10% annual exceedance probability (AEP) floods were assessed, respectively. The results show that the economic losses showed a significant increasing trend with AEP. The optimal domain scales for industrial, commercial, residential and public service land uses were 19, 14, 25 and 32 m, respectively, and also varied with different AEP floods. The model was effectively verified by simulating and comparing historical data of the “7·20” flood event in Zhengzhou, China. This study aims to provide feasible ideas for uncertainty research of damage assessment methods.
Plain Language Summary
The damage ratio serves as the link between flood hydrological elements and damages and has an indispensable role in quantifying flood risks. However, the spatial variability of flood‐bearing elements leads to three kinds of spatial uncertainties in damage ratios: spatial heterogeneity, local correlation and neighborhood non‐stationarity. Thus, in this paper, a stochastic flood damage assessment model considering multiple uncertainties was proposed and it is found that optimal domain scales were inconsistent for different annual exceedance probability flood events and different land uses. The model was effectively verified by simulating and comparing historical data of the “7·20” flood event in Zhengzhou, China.
Key Points
Accurately quantifying flood damage ratios is a challenge due to the link between flood hydrological elements and losses
Spatial variability of flood‐bearing components caused triple spatial uncertainties to damage ratios
Different land uses and flood events with different annual exceedance probabilities exhibited inconsistent optimal domain scales
Extreme rainfall is the main influencing factor of urban waterlogging. Different types of rainfall often have different characteristics of waterlogging. In order to establish a more accurate urban ...flood control system, it is necessary to classify waterlogging rainstorms and divide their thresholds. This study proposes a method for applying web crawlers to identify waterlogging rainfall in cities lacking waterlogging observation data and classifying them using the rainfall intensity–duration curves. By selecting appropriate duration thresholds and return period, waterlogging rainstorms are divided into rainfall intensity waterlogging (IW), rainfall amount of waterlogging (AW), combined waterlogging (CW) and no waterlogging (NW). In the application of Zhengzhou City, China, the urban flood control standard and the rainfall time distribution characteristics are used as the basis for the selection of the return period and duration thresholds, and the storm water management model (SWMM) is constructed to simulate the 4 kinds of rainfall characteristics of waterlogging, which is similar to actual situations. It proves that the method is suitable for the classification and thresholds division of different waterlogging rainfall in cities. The results show that the best duration thresholds in Zhengzhou are 20 min (M20) and 60 min (M60), and the best return period standard is 2 a. The thresholds for the 4 types of waterlogging rainstorm are: M20 ≥ 26.47 mm, M60 ≥ 43.80 mm, CW; M20 ≥ 26.47 mm, M60 < 43.80 mm, IW; M20 < 26.47 mm, M60 ≥ 43.80 mm, AW; M20 < 26.47 mm and M60 < 43.80 mm, No waterlogging.
Over the past several decades, urban flooding and other water-related disasters have become increasingly prominent and serious. Although the urban rain flood model’s benefits for urban flood ...simulation have been extensively documented, the impact of rainfall input to model simulation accuracy remains unclear. This systematic review aims to provide structured research on how rain inputs impact urban rain flood model’s simulation accuracy. The selected 48 peer-reviewed journal articles published between 2015 and 2019 on the Web of Science™ database were analyzed by key factors, including rainfall input type, calibration times and verification times. The results from meta-analysis reveal that when a traditional rain measurement was used as the rainfall input, model simulation accuracy was higher, i.e., the Nash–Sutcliffe efficiency coefficient (NSE) of traditional technology for rain measurement was higher than the 0.18 for the new technology rain measurement with respect to flow simulation. In addition, the single-field sub-flood calibration model was better than the multi-field sub-flood calibration model. NSE was higher than 0.14. The precision was better for the verification period; NSE of the calibration value showed a 0.07 higher verification value on average in flow simulation. These findings have certain significance for the development of future urban rain flood models and propose the development direction of the future urban rain flood model. Finally, in view of the rainfall input problem of the urban storm flood model, we propose the future development direction of the urban storm flood model.
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.
The storm water management model (SWMM) is widely used in urban rainfall runoff simulations, but there are no clear rules for the division of its sub catchment areas. At present, the popular sub ...catchment area division method takes the average slope as the slope parameter of the sub catchment area, which brings errors to the model in mechanism. Based on the current method, this paper proposes a new method to further subdivide the sub catchment area of the SWMM model, according to the Digital Elevation Model (DEM) data of underlying surface, slope and aspect information. By comparing with the previous methods, it was found that the division method based on slope and aspect can make the setting of model parameters and hydraulic exchange conditions clearer, and improve the accuracy of the model on a certain level.
Abstract Atopic dermatitis (AD) is a common skin disease involving important immune mechanisms. There is an unmet need for a treatment for this condition. Herein, we focused on elucidating the role ...of Bi 2-x Mn x O 3 nanospheres (BM) in alleviating skin inflammation in AD-like C57BL/6 mice. The BM was fabricated via sacrificial templates and its biosafety was systematically evaluated. The BM was applied topically to skin lesions of AD-like C57BL/6 mice. The phenotypic and histological changes in the skin were examined carefully. The responses of barrier proteins, inflammatory cytokines and cells to BM were evaluated in HaCaT cells and AD mouse models. The data demonstrated that BM treatment alleviated the AD phenotypes and decreased the level of inflammatory factors, while increasing the expression of the barrier proteins filaggrin/involucrin in the skin. BM effectively reduced the expression of phosphorylated STAT6, which in turn reduced the expression of GATA3, and further decreased the differentiation ratio of Th2 cells, thereby reducing the expression of IL-4. In conclusion, topical drug therapy with BM provides a safe and effective treatment modality for AD by reducing IL-4 and increasing barrier proteins. Graphical Abstract
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