Spatial simulation of the ecological processes of stormwater for sponge cities

A comparative study on urban waterlogging susceptibility assessment based on multiple data-driven models

Accurate identification of urban waterlogging areas and assessing waterlogging susceptibility are crucial for preventing and controlling hazards. Data-driven models are utilized to forecast waterlogging areas by establishing intricate relationships between explanatory variables and waterlogging states. This approach tackles the constraints of mechanistic models, which are frequently complex and unable to incorporate socio-economic factors. Previous research predominantly employed single-type data-driven models to predict waterlogging locations and evaluation of their effectiveness. There is a scarcity of comprehensive performance comparisons and uncertainty analyses of different types of models, as well as a lack of interpretability analysis. The chosen study area was the central area of Beijing, which is prone to waterlogging. Given the high manpower, time, and economic costs associated with collecting waterlogging information, the waterlogging point distribution map released by the Beijing Water Affairs Bureau was selected as labeled samples. Twelve factors affecting waterlogging susceptibility were chosen as explanatory variables to construct Random Forest (RF), Support Vector Machine with Radial Basis Function (SVM-RBF), Particle Swarm Optimization-Weakly Labeled Support Vector Machine (PSO-WELLSVM), and Maximum Entropy (MaxEnt). The utilization of diverse single evaluation indicators (such as F-score, Kappa, AUC, etc.) to assess the model performance may yield conflicting results. The Distance between Indices of Simulation and Observation (DISO) was chosen as a comprehensive measure to assess the model's performance in predicting waterlogging points. PSO-WELLSVM exhibited the highest performance with a DISOtest value of 0.63, outperforming MaxEnt (0.78), which excelled in identifying areas highly susceptible to waterlogging, including extremely high susceptibility zones. The SVM-RBF and RF models demonstrated suboptimal performance and exhibited overfitting. The examination of waterlogging susceptibility distribution maps predicted by the four models revealed significant spatial differences due to variations in computational principles and input parameter complexities. The integration of four WSAMs based on logistic regression has been shown to significantly decrease the uncertainty of a single data-driven model and identify the most flood-prone areas. To improve the interpretability of the data model, a geographical detector was incorporated to demonstrate the explanatory capacity of 12 variables and the process of waterlogging. Building Density (BD) exhibits the highest explanatory power in relation to explain waterlogging susceptibility (Q value = 0.202), followed by Distance to Road, Frequency of Heavy Rainstorms (FHR), DEM, etc. The interaction between BD and FHR results in a nonlinear increase in the explanatory power of waterlogging susceptibility. The presence of waterlogging susceptibility risk in the research area can be attributed to the interactions of multiple factors.

Urban rainstorm and waterlogging scenario simulation based on SWMM under changing environment

Urban rainstorm and waterlogging occurred more frequently in recent years, causing huge economic losses and serious social harms. Accurate rainstorm and waterlogging simulation is of significant value for disaster prevention and mitigation. This paper proposed a numerical model for urban rainstorm and waterlogging based on the Storm Water Management Model (SWMM) and Geographic Information System (GIS), and the model was applied in Lianhu district of Xi'an city of China. Furthermore, the effects of rainfall characteristics, pipe network implementation level and urbanization level on waterlogging were explored from the perspectives of spatial distribution of waterlogging points, drainage capacity of pipe network and surface runoff generation and confluence. The results show that: (1) with the increase of rainfall recurrence period, the peak of total water accumulating volume, the average decline rate of water accumulating volume and the number of waterlogging nodes increase; (2) optimizing the pipe diameter can shorten the average overload time of the pipe network from the entire pipe network, but for a single pipe, optimizing the pipe diameter may lead to overloading of unoptimized downstream pipeline; (3) the lower the imperviousness, the less the number of waterlogging nodes and average time of water accumulating, and (4) the west, northwest and southwest areas are relatively affected by the imperviousness, only improving the underlying surface conditions has limited influence on waterlogging in the study area. This study can provide reference for urban waterlogging prevention and reduction and pipe network reconstruction.

Review of Sponge City implementation in China: performance and policy

Urban flooding is a major problem for large cities around the world. Rapid urbanization in China has tremendously increased, resulting in more frequent incidences of urban flooding. In 2013, China launched a program of 30 pilot sponge cities (SPCs) to establish integrated urban stormwater management. However, today, after several years of implementation, some sponge cities still experience flooding. This study provides answers and solutions to these problems, by evaluating the overall performance of SPC in China from a systematic perspective considering the variable climatic conditions. This paper also highlights the limitations associated with implementing the current SPC. The adoption of overseas models, before adhering them to Chinese catchment properties, has generated significant uncertainty for simulation outputs and material provision challenges at various stages of the implementation process. Furthermore, hydrological connectivity between neighboring catchments has been neglected in most SPC projects. Developing local models based on local conditions and needs would address these issues and open new research windows for exploring more effective stormwater management initiatives. That includes the advancement of cost-effective evaluation studies, modern optimum efficiency design studies, and the analysis of groundwater contamination due to high infiltration rates and so on.

Identifying the influence of natural and human factors on seasonal water quality in China: current situation of China's water environment and policy impact

Agricultural production, urbanization, and other anthropogenic activities, the major causes of surface water pollution in China, have dramatically altered hydrological processes and nutrient cycles. Identifying and quantifying the key factors affecting water quality are essential for the better prevention and management of water pollution. However, due to the limitations of traditional statistical analysis methods, it is difficult to evaluate the spatial changes and interactions of influencing factors on water quality. In addition, research on a national scale is difficult, as it involves large-scale and long-term water quality monitoring work. In this study, we collected and collated the monthly average concentrations of four water quality parameters, dissolved oxygen, ammonia nitrogen, chemical oxygen demand, and total phosphorous, based on data from 1547 water quality monitoring stations in China. The combined pollution level of the water quality was assessed using the water quality index. Based on the water quality characteristics, water quality monitoring sites in the dry and wet seasons were grouped using k-means clustering. Eleven environmental factors were evaluated using geodetector software, including six human factors and five natural factors. The results showed that there are high-risk areas for water quality pollution in the eastern and southeastern coastal regions of China in both the dry and wet seasons and that surface water pollution in China is highly spatial heterogenous in both the dry and wet seasons. Among the anthropogenic factors, urban land area is the main factor of water quality pollution in the dry season, and the explanation rate of spatial heterogeneity of integrated water quality pollution index is 20.3%. The number of poultry farms and the area of farmland explained 12.4% and 12.1% of the integrated water quality pollution index in the wet season. The nonlinear relationship between these three anthropogenic and natural factors and their interaction exacerbated water quality pollution. Based on this analysis, we identified the key factors affecting surface water quality in China during the dry and wet seasons, evaluated the achievements of the water environmental protection policies in China in recent years, and proposed future management measures for the effective prevention and control of water quality pollution in high-risk areas.

Optimal designs of LID based on LID experiments and SWMM for a small-scale community in Tianjin, north China

Urban flooding and waterlogging are becoming increasingly serious due to rapid urbanization and climate change. The stormwater management philosophy of low-impact development (LID) has been applied in urban construction to alleviate these problems. The selection and placement of LID designs are the most important tasks. In this study, LID experiments were performed to calibrate the Storm Water Management Model (SWMM). Then, a multi-objective optimization model, which adopted the minimum surface runoff coefficient, surcharge time, and investment cost as objectives, was established by coupling the SWMM and non-dominated sorting genetic algorithm-II (NSGA-II). Hydrological simulations were performed with the SWMM, and optimal calculations were conducted with NSGA-II. Real-coded optimal variables containing detailed size and location information of multiple LID measures were generated, and a decision space for LID design selection was obtained. The optimization designs reduced the surface runoff coefficient from 0.7 to approximately 0.5, the conduit surcharge duration was reduced from 1.62 h to 0.04-0.47 h, and the total investment cost only ranged from 395,000-872,000 ¥. Thus, the optimization model could achieve synchronous optimization of all objectives. This study could provide valuable information for LID design with the aim of urban flooding and waterlogging control.

Effect of Different Ameliorants on the Infiltration and Decontamination Capacities of Soil

The expansion of urban construction areas can reduce the infiltration rate of rainwater in permeable land, and a large amount of runoff rainwater cannot penetrate the soil. In extreme rainstorm weather, it is easy to cause serious urban waterlogging problems. To improve the infiltration and decontamination ability of green space soil, two types of inorganic ameliorants (i.e., sand and grain shell) and structural ameliorants (i.e., desulfurization gypsum and polyacrylamide) were utilized as amendments in the soil. The influence of the selected ameliorants on the infiltration and decontamination ability was analyzed through a soil infiltration test, soil pore distribution determination and a soil decontamination test. Three parameters including the soil infiltration rate, pore distribution characteristics and pollutant removal rate were proposed. The results showed that sand, grain shells and desulfurization gypsum (FGD gypsum) all enhanced the infiltration capacity of soil, while PAM decreased the infiltration capacity. Meanwhile, mixed sand and grain shell with the FGD gypsum and polyacrylamide can effectively improve the decontamination capacity of the soil. Comprehensive analysis showed that the better improvement combination is 10% sand + 20% grain hull + 0.5 g/kg FGD gypsum + 0.1 g/kg PAM.

Performance and microbial community of MBBRs under three maintenance strategies for intermittent stormwater treatment

Maintaining microbial activities is a critical problem for biological treatment processes of stormwater runoff because of its intermittent nature. In this study, the suitability of the moving bed biofilm reactor (MBBR) was assessed for stormwater treatment by long-term dry - rainy alternation operation. Three strategies to maintain microbial activities during the dry period, including keeping idle (MBBR_I), introducing river water throughout the period (MBBR_C), and ahead of a rainy day (MBBR_M), were investigated. COD and NH₄⁺-N removal efficiencies declined linearly from 94.2 % and 94.7 % to 51.7 % and 64.6 %, respectively, after the 61-day operation with microbial activity and biomass decreased. Introducing river water adversely affected the process performance as MBBR_C presented the highest declining rates of COD and NH₄⁺-N removal efficiencies. Most genera in MBBRs decayed and their microbial communities developed towards individualization, especially in MBBR_M because of its highest environmental variability. Keeping idle slightly alleviated the performance decline and formed a more stable microbial community structure. However, significantly deteriorating performance in all MBBRs after the long-term operation indicated that MBBRs were unsuitable for treating stormwater independently of intermittent nature.

Suitable coverage and slope guided by soil and water conservation can prevent non-point source pollution diffusion: A case study of grassland

Non-point source pollution caused by surface runoff has been a popular hydrological and environmental safety issue and has attracted extensive attention from global scholars. To identify the optimal vegetation coverage of Festuca arundinacea grassland for controlling soil erosion and purifying surface runoff, bare land was chosen as the control in this experiment. Simulated rainfall experiments were carried out with three levels of coverage (low coverage, moderate coverage and full coverage) under four slope conditions (flat slope, gentle slope, medium slope, and steep slope) and at four rainfall intensities (moderate rainfall, heavy rainfall, rainstorm and heavy rainstorm). The comprehensive evaluation results suggested that the capacity of Festuca arundinacea grassland for reducing the surface runoff, sediment yield, suspended solids (SS), total nitrogen (TN), total phosphorus (TP) and chemical oxygen demand (COD) decreased with increasing rainfall intensity and slope but increased with increasing vegetation coverage. Structural equation model (SEM) results suggested that there were positive relationships between the vegetation coverage and purification capacity index and negative correlations between the rainfall intensity and slope and the purification capacity index. The response surface analysis results suggested that the optimal vegetation coverage should be higher than 84% and that the slope should be smaller than 10° for controlling soil erosion and avoiding pollution via diffusion with surface runoff in Festuca arundinacea grassland. This study proposes recommendations for the vegetation configuration pattern in the development and management of runoff purification systems.

A Water Resilience Evaluation Model for Urban Cities

Cities around the world are having to become more resilient to the effects of climate change and ongoing development pressures and consequently are seeking to improve urban water resource management. In order to analyze the key factors affecting a city’s water resilience, this research establishes an urban water resilience evaluation model. The DEMATEL method is used to calculate the intensity of the interaction among the water resilience indicators and to establish their causal relationships. Then, an ANP structured diagram is established and the weighting of the water resilience evaluation index for the city of Wuhan is obtained using the Super Decisions software. The key water resilience factors for Wuhan are shown to have significant mutual influences, with the main factors found to be the utilization of rainwater resources, the utilization of reclaimed water, and the total annual runoff control of the city. This method provides a sound basis for the evaluation of urban water resilience with scope to extend this to other cities. The results provide useful guidance for policy makers and other key stakeholders in supporting more sustainable urban development.

Investigating the Impact of Spatial Distribution of Sustainable Drainage System (SuDS) Components on Their Flood Mitigation Performance in Communities with High Groundwater Levels

This paper investigated the impact of the spatial distribution of SuDS components on their flood reduction performance and the underlying mechanisms in a community with high groundwater levels. The effects of SuDS components’ connectivity, decentralized level, and installation position along the flow direction on the reduction of total discharge volume (TDV), average discharge flow rate (ADFR), maximum discharge flow rate (MDFR), inundated area (IA), average inundated depth (AID), and maximum inundated depth (MID) were studied by coupling of the storm water management model (SWMM) and high-performance integrated hydrodynamic modelling system (HiPIMS). The results demonstrate that the connectivity has a positive linear correlation with the reduction of TDV (R2 > 0.991), ADFR (R2 > 0.992), and MDFR (R2 > 0.958), while the decentralized level of rain gardens and green roofs present positive one-phase exponential correlation with the reduction of TDV (R2 > 0.935), ADFR (R2 > 0.934) and MDFR (R2 > 0.967). A better-integrated mitigation of TDV and ADFR could be achieved by installing SuDS upstream along the flow direction. The connectivity from green roofs to rain gardens has a positive effect on the reduction of AID and MID but leads to the increase of IA. The findings of this study may contribute to the development of general spatial distribution guidelines and strategies to optimize the overall performance of SuDS components, especially at a community scale.

Integrating Sponge City Requirements into the Management of Urban Development Land: An Improved Methodology for Sponge City Implementation

Sponge city planning aims to manage urban development land to prevent flooding and to support the achievement of water resource protection objectives. In this study, from the perspective of rainfall management demand and ability, we present an improved planning method, including two calculation models, aimed at determining the VCRAR (volume capture ratio of annual rainfall) and then integrating VCRAR requirements into the management of urban development land more accurately and objectively, while simultaneously considering the rainfall condition and urban planning attributes to support the implementation of sponge city planning. Compared to the current method, the VCRAR calculation model greatly improves the accuracy of the VCRAR for various space scales, and the conversion model solves the fundamental problem that urban land indicators corresponding to the VCRAR are difficult to calculate objectively and accurately. Moreover, this methodology can achieve a reasonable tradeoff between the development of individual districts and the environmental protection of the whole urban watershed, which allows a poetic vision to be turned into executable planning and design. The results of the application of this methodology in a case study in Jizhou, China, show that the improved method can make land utilization, development period and natural conditions more integrated and scientifically involved in the indicator calculation. The results also quantitatively show that the capacity of volume capture inside the site for one district increases as its green space ratio increases, and it decreases with an increase in the transformation difficulty for stormwater management facilities, when restricted by the investment and available space.

Dynamic testing in columns for soil heavy metal removal for a car park SUDS

The increase in urban runoff brought about by a rise in impermeable surfaces has triggered the alteration and pollution of many aquatic systems. The overall goal of this research was to design a 'Sustainable Urban Drainage System' (SUDS) for the retention of heavy metals from a car park consisting of mixing autochthonous soil (70%) with sand (30%) to improve the hydrological conductivity and adsorption capacity. To quantify the retention of metals we characterize the adsorption kinetics and isotherms of the soil mixture and perform dynamic experiments. The proposed methodology allowed us to work out the amount of heavy metal retention by the adsorbent and the retention mechanisms. The retention capacity of the adsorbent mixture was as follows: Cr³⁺ ≈ Cu²⁺ ≫ Zn²⁺ > Ni²⁺ > Cd²⁺. Chromium and copper ions were mainly retained by precipitation, whereas zinc, nickel and cadmium were retained by ionic exchange with calcium ions that saturate the soil colloids. The soil mixture buffered pH was found to change when fed with an acid solution of metallic ions.

Addressing Challenges of Urban Water Management in Chinese Sponge Cities via Nature-Based Solutions

Urban flooding has become a serious issue in most Chinese cities due to rapid urbanization and extreme weather, as evidenced by severe events in Beijing (2012), Ningbo (2013), Guangzhou (2015), Wuhan (2016), Shenzhen (2019), and Chongqing (2020). The Chinese “Sponge City Program” (SCP), initiated in 2013 and adopted by 30 pilot cities, is developing solutions to manage urban flood risk, purify stormwater, and provide water storage opportunities for future usage. Emerging challenges to the continued implementation of Sponge Cities include (1) uncertainty regarding future hydrological conditions related to climate change projections, which complicates urban planning and designing infrastructure that will be fit for purpose over its intended operating life, and (2) the competing priorities of stakeholders and their reluctance to make trade-offs, which obstruct future investment in the SCP. Nature-Based Solutions (NBS) is an umbrella concept that emerged from Europe, which encourages the holistic idea of considering wider options that combine “Blue–Green” practices with traditional engineering to deliver “integrated systems of Blue–Green–Grey infrastructure”. NBS includes interventions making use of natural processes and ecosystem services for functional purposes, and this could help to improve current pilot SCP practices. This manuscript reviews the development of the SCP, focusing on its construction and design aspects, and discusses how approaches using NBS could be included in the SCP to tackle not only urban water challenges but also a wide range of social and environmental challenges, including human health, pollution (via nutrients, metals, sediments, plastics, etc.), flood risk, and biodiversity.

Urban stormwater characterization, control, and treatment

This review summarizes over 280 studies published in 2019 related to the characterization, control, and management of urban stormwater runoff. A summary of quantity and quality concerns is provided in the first section of the review, serving as the foundation for the following sections which focus on the control and treatment of stormwater runoff. Finally, the impact of stormwater control devices at the watershed scale is discussed. Each section provides a self-contained overview of the 2019 literature, common themes, and future work. Several themes emerged from the 2019 literature including exploration of substrate amendments for improved water quality effluent from stormwater controls, the continued study of the role of vegetation in green infrastructure practices, and a call to action for the development of new models which generate reliable, computationally efficient results under the physical, chemical, biological, and social complexity of stormwater management. PRACTITIONER POINTS: Over 280 studies were published in 2019 related to the characterization, control, and treatment of urban stormwater. Studies on bioretention and general stormwater characteristics represented the two most common subtopics in 2019. Trends in 2019 included novel substrate amendments, studies on the role of vegetation, and advancements in computational models.

A new model framework for sponge city implementation: Emerging challenges and future developments

Sponge City concept is emerging as a new kind of integrated urban water systems, which aims to address urban water problems. However, its implementation has encountered a variety of challenges. The lack of an integrated comprehensive model to assist Sponge City planning, implementation and life cycle assessment is one of the most challenging factors. This review briefly analyses the opportunity of existing urban water management models and discusses the limitation of recent studies in the application of current integrated models for Sponge City implementation. Furthermore, it proposes a new Sponge City model framework by integrating four main sub-models including MIKE-URBAN, LCA, W045-BEST, and MCA in which environmental, social, and economic aspects of Sponge City infrastructure options are simulated. The new structure of Sponge City model that includes the sub-model layer, input layer, module layer, output layer, and programing language layer is also illustrated. Therefore, the proposed model could be applied to optimize different Sponge City practices by not only assessing the drainage capacity of stormwater infrastructure but also pays attention to multi-criteria analysis of urban water system (including the possibility of assessing Sponge City ecosystem services for urban areas and watershed areas) as well. Balancing between simplification and innovation of integrated models, increasing the efficiency of spatial data sharing systems, defining the acceptability of model complexity level and improving the corporation of multiple stakeholders emphasizing on possible future directions of a proper Sponge City design and construction model.

First flush analysis using a rainfall simulator on a micro catchment in an arid climate

Urban runoff water from simulated rainfall for three different land uses (residential, industrial, commercial) at six different locations of Doha, Qatar was analysed for physico-chemical parameters such as, trace metals, pH, total suspended solids (TSS), total organic carbon (TOC), total phosphorus (TP), total kjeldahl nitrogen (TKN) and polyaromatic hydrocarbons (PAHs). Rainfall events with two different intensities (40 mm/h and 20 mm/h) were simulated in a micro catchment area (4.55 × 4.55 m²) using a specially designed portable rainfall simulator. Out of six sites, runoff samples were collected from five sites with paved surfaces. The study results demonstrated significant concentration of TSS, Cu, Fe, Mn and Zn in the urban runoff exceeding the Qatar Ministry of Municipality and Environment (MME) and Tropical Australian Standards. The first flush effect was also investigated during the experiment which exhibited first flush effect of selected pollutants (TSS, TKN, TP, TOC and heavy metals) at five study sites with impervious surfaces. The magnitude of the first flush varies across the study sites and was found to be affected by the surface texture of the sites. Analysis of variance revealed that, rainfall intensity has limited effect on the first flush in the studied scenarios, however, first flush effects showed relation with the event mean runoff concentration. Furthermore, strong positive correlations were observed between analysed water quality parameters, particularly between TSS, TOC and metals. This study is the first study investigating first flush in Qatar's capital, Doha which will provide a ground for future researcher to design appropriate stormwater treatment devices that will capture and treat the first flush for significant reduction of urban stormwater pollution.