Search Results (199)

To date, few studies have been published for cities in Germany that take into account climate change and changing hydrologic patterns due to increases in building density. This study investigates the efficiency of LID for past and future climate in the polycentric agglomeration area Frankfurt, Main (Central Germany) using observed and projected climate (model) data for a standard reference period (1961–1990) and a high emission scenario (RCP 8.5) as well as a climate protection scenario (RCP 2.6), under 40 to 75 percent building density. LID elements included green roofs, permeable pavement and bioretention cells. SWMM₅ was used as model for simulation purposes. A holistic evaluation of simulation results showed that effectiveness increases incrementally with LID implementation percentage and inverse to building density if implemented onto at least 50 percent of available impervious area. Building density had a higher adverse effect on LID efficiency than climate change. The results contribute to the understanding of localized effects of climate change and the implementation of adaption strategies to that end. The results of this study can be helpful for the scientific community regarding future investigations of LID implementation efficiency in dense residential areas and used by local governments to provide suggestions for urban water balance revaluation. Full article

A systems-oriented review of machine learning (ML) over the entire flood management spectrum, encompassing fluvial flood control, pluvial flood management, and resiliency-risk characterization was undertaken. Deep learners like long short-term memory (LSTM) networks perform well in predicting reservoir inflows and outflows. Convolution neural networks (CNNs) and other object identification algorithms are being explored in assessing levee and flood wall failures. The use of ML methods in pump station operations is limited due to lack of public-domain datasets. Reinforcement learning (RL) has shown promise in controlling low-impact development (LID) systems for pluvial flood management. Resiliency is defined in terms of the vulnerability of a community to floods. Multi-criteria decision making (MCDM) and unsupervised ML methods are used to capture vulnerability. Supervised learning is used to model flooding hazards. Conventional approaches perform better than deep learners and ensemble methods for modeling flood hazards due to paucity of data and large inter-model predictive variability. Advances in satellite-based, drone-facilitated data collection and Internet of Things (IoT)-based low-cost sensors offer new research avenues to explore. Transfer learning at ungauged basins holds promise but is largely unexplored. Explainable artificial intelligence (XAI) is seeing increased use and helps the transition of ML models from black-box forecasters to knowledge-enhancing predictors. Full article

Low-impact development (LID) offers environmental, economic, and social benefits, yet research on optimizing facility combinations remains limited. This study evaluates four representative LID types—green roofs, sunken green spaces, permeable pavement, and rain gardens—using an integrated framework combining the Storm Water Management Model (SWMM), NSGA-II genetic algorithm, and Analytic Hierarchy Process (AHP) at Taiyuan University of Technology in Shanxi Province, China. Based on site constraints, each LID type was pre-assigned to suitable subareas, and optimization focused on determining proportional allocations within these areas. SWMM simulations revealed that permeable paving achieved the highest runoff reduction (up to 19.4% at 65% coverage) and strong cost-effectiveness (0.013 USD per % reduction). NSGA-II was used to generate a set of optimal solutions by minimizing construction costs and maximizing runoff and pollutant reductions. AHP then ranked these solutions according to their environmental, economic, and social benefits. In this case, the ideal mix—subject to site-specific constraints and model assumptions—includes 28.58% green roofs, 19.37% sunken green spaces, 48.68% permeable paving, and 3.37% rain gardens. The study proposes a sponge campus renewal strategy, offering theoretical and practical insights for sustainable urban development and precise environmental management. Full article

Urbanization and climate change have disrupted natural water circulation by increasing impervious surfaces and altering rainfall patterns, leading to reduced groundwater infiltration, deteriorating water quality, and heightened flood risks. This study investigates the application of Low Impact Development (LID) and flood control facilities as structural measures to address these challenges in the upper watershed of the Fucha River in Bogotá, Colombia. The methodology involved analyzing watershed characteristics, defining circulation problems, setting hydrological targets, selecting facility types and locations, evaluating performance, and conducting an economic analysis. To manage the target rainfall of $26.5$$\mathrm{m}$$\mathrm{m}$ under normal conditions, LID facilities such as vegetated swales, rain gardens, infiltration channels, and porous pavements were applied, managing approximately 2362 ${\mathrm{m}}^3$ of runoff. For flood control, five detention tanks were proposed, resulting in a 31.8% reduction in peak flow and a 7.3% decrease in total runoff volume. The flooded area downstream was reduced by $46.8$$\mathrm{h}\mathrm{a}$, and the benefit–cost ratio was calculated at 1.02. These findings confirm that strategic application of LID and detention facilities can contribute to effective urban water cycle management and disaster risk reduction. While the current disaster management approach in Bogotá primarily focuses on post-event response, this study highlights the necessity of transitioning toward proactive disaster preparedness. In particular, the introduction and expansion of flood forecasting and warning systems are recommended as non-structural measures, especially in urban areas with complex infrastructure and climate-sensitive hydrology. Full article

Mountainous cities are especially vulnerable to flooding and water quality degradation due to surrounding steep terrain, variable precipitation, and fragile ecosystems. Existing studies often rely on small-scale scenario simulations or computationally intensive optimization algorithms, limiting their practical application. This study proposes a spatial layout strategy for stormwater management tailored to mountainous environments, using the Xining sponge city pilot area as a case study. Based on the “source–sink” theory, flood risk was assessed at the district scale, and the Storm Water Management Model (SWMM) was applied to evaluate four Low-Impact Development (LID) deployment schemes. A novel indicator—the source–sink coupling optimization degree (SSCOD)—was introduced to quantify LID spatial coordination between source and sink zones and identify optimal configuration thresholds. Results show that the four LID allocations significantly reduce runoff and improve water quality compared to the no-LID baseline. Analyses also reveal diminishing returns: optimal LID performance occurs when SSCOD ranges from 0.345 to 0.423, with 24.24–24.41% of LID facilities placed in high-risk zones. Beyond this range, effectiveness plateaus or declines, leading to potential resource waste. The proposed framework provides a technical basis and practical strategy for guiding stormwater infrastructure planning in mountainous cities, balancing effectiveness with resource efficiency. Full article

Low-impact development (LID) facilities serve as a fundamental approach in urban stormwater management. However, significant variations in land use among different plots lead to discrepancies in runoff reduction demands, frequently leading to either the over- or under-implementation of LID infrastructure. To address this issue, we propose a cost-effective optimization framework grounded in the concept of “Capacity Trading (CT)”. The study area was partitioned into multi-scale grids (CT-100, CT-200, CT-500, and CT-1000) to systematically investigate runoff redistribution across heterogeneous land parcels. Integrated with the Sequential Least Squares Programming (SLSQP) optimization algorithm, LID facilities are allocated according to demand under two independent constraint conditions: runoff coefficient ($\phi$ ≤ 0.49) and runoff control rate ($\eta$ ≥ 70%). A quantitative analysis was conducted to evaluate the construction cost and reduction effectiveness across different trading scales. The key findings include the following: (1) At a constant return period, increasing the trading scale significantly reduces the demand for LID facility construction. Expanding trading scales from CT-100 to CT-1000 reduces LID area requirements by 28.33–142.86 ha under the $\phi$-constraint and 25.5–197.19 ha under the $\eta$-constraint. (2) Systematic evaluations revealed that CT-500 optimized cost-effectiveness by balancing infrastructure investments and hydrological performance. This scale allows for coordinated construction, avoiding the high costs associated with small-scale trading (CT-100 and CT-200) while mitigating the diminishing returns observed in large-scale trading (CT-1000). This study provides a refined and efficient solution for urban stormwater management, overcoming the limitations of traditional approaches and demonstrating significant practical value. Full article

Stormwater reuse plays a critical role under changing climates and increasing water demands. This study investigates the removal efficacy of lead (Pb²⁺) and ammonia (NH₃) using sand and rice husk (RH) biochar for potential stormwater quality improvements and treatments. Column experiments combined with HYDRUS inverse modeling were conducted to optimize adsorption isotherms from breakthrough curves. Among linear and non-linear models, the Langmuir and Freundlich models performed better for sand and biochar, respectively. RH biochar showed much higher adsorption capacity of both Pb²⁺ (4.813 mg/g) and NH₃ (6.188 mg/g). In contrast, sand showed a relatively limited adsorption capacity for Pb²⁺ (0.118 mg/g) and NH₃ (0.104 mg/g). This can be contributed to higher pore size distribution, surface area, and the presence of different functional groups of biochar. The optimized adsorption coefficients and adsorption capacity parameters of sand and RH biochar by inverse modeling provided useful input for improving field designs. These findings will enhance the development of the best management practices (BMPs) for managing heavy metal and solute pollution in groundwater or stormwater low-impact development (LID) infrastructure systems. Full article

The parameters of Low-Impact Development (LID) facilities significantly influence their operational performance and runoff control effectiveness at the site. Despite extensive research on LID effectiveness, limited studies have focused on optimizing design parameters at a community-wide scale, integrating both hydrological and statistical methodologies. A novel approach to optimizing LID design parameters was presented in this study. This study established a community-scale SWMM model, identified the key parameters by the Morris screening method, and determined the reasonable parameter ranges based on runoff control effects. The Response Surface Methodology (RSM) was applied to optimize the key parameters under different return periods and impervious area ratios. The results showed that key LID parameters for runoff volume control were the berm height of the surface layer of sunken greenbelt (SG_Surface_H), the conductivity of the soil layer of sunken greenbelt (SG_Soil_I), the permeability of the pavement layer of permeable pavement (PP_Pavement_I), and the thickness of the storage layer of permeable pavement (PP_Storage_T). The reasonable ranges were 50–265 mm, 5–80 mm/h, 50–140 mm/h, and 100–165 mm, respectively. The key LID parameters for peak flow reduction were SG_Surface_H, SG_Soil_I, PP_Pavement_I, and the berm height of the surface layer of vegetated swale (VS_Surface_H). The reasonable ranges were 50–260 mm, 5–50 mm/h, 50–195 mm/h, and 50–145 mm, respectively. The optimization results of LID parameters showed that for the runoff volume control rate, the optimization strategy involved increasing SG_Surface_H as the return period increased and when the impervious area ratio was large, especially in the rehabilitation of old communities. Meanwhile, the optimal value of SG_Soil_I for runoff volume control was greater than that for peak flow reduction. In contrast, the optimal value of PP_Pavement_I was larger for peak flow reduction. This study provides a significant reference for LID planning and design by emphasizing the optimization of LID design parameters. Full article

With urbanization accelerating, low-impact development (LID) facilities, particularly bioretention facilities, play a crucial role in urban water management. However, rising groundwater tables present challenges for their application in high-water-table areas. This study experimentally evaluated the impact of shallow groundwater tables on the hydrological performance of bioretention facilities. The experiment was designed to evaluate the effects of different groundwater table levels, soil media types, runoff ratios, and rainfall characteristics on hydrological responses. It also examined their impact on drainage pipe design and groundwater recharge. Results showed that as the groundwater table rose from 0.2 m to 0.5 m, the drainage pipe discharge increased (Facility #1: 52%→76%, Facility #3: 31%→58%) while the groundwater recharge decreased (Facility #1: 44%→17%, Facility #3: 63%→39%). This indicates that a higher groundwater table intensifies the diversion effect of the drainage pipe, increasing the proportion of stormwater discharged while reducing the proportion infiltrating to recharge the groundwater. Under moderate to heavy rainfall, sandy loam reduced the drainage time by 41–43% and increased the groundwater recharge by up to 80%. Without drainage pipes, sandy loam enhanced the recharge rates (α = 0.87), and #3 exhibited superior infiltration. Rainfall intensity and interval significantly influenced the hydrological performance. Full article

This study addresses the growing inadequacies of traditional architectural concepts and techniques in stormwater management amid the increasing frequency of extreme weather events, particularly in densely built urban micro-spaces. To tackle these challenges, we propose an integrated theoretical and practical framework applied to a case study of a small-scale urban public space in Chang’an District, Shijiazhuang City, Hebei Province, covering an area of about 2.15 hectares in North China. The framework combines Best Management Practices Planning (BMP-P) with Low Impact Development Design (LID-D). The framework optimizes sub-catchment delineation, strategically locates drainage outlets, and configures network layouts to reduce runoff path lengths, thereby reducing total runoff volume, enhancing drainage capacity, and alleviating surface water accumulation, which, in turn, informs the parametric design of LID facilities. In the BMP-P phase, four source-control measures were developed based on runoff control and stormwater retention: adjusting terrain slopes, adding or removing curbs and facilities, redistributing infiltration areas, and adjusting drainage outlet and piping layouts. By shortening runoff paths and reducing potential waterlogging areas, these measures effectively reduced total runoff volume (Trv) by 31.5% to 35.7% and peak runoff volume (Prv) by 19.4% to 32.4%. Moreover, by remodeling the stormwater network with a different layout, larger pipe diameters, and substantially increased network capacity, the total discharge (Tdv) increased by 1.8% to 50.2%, and the peak discharge rate (Pdr) increased by 100% to 550%, thus minimizing surface flooding. In the LID-D phase, we developed a Grasshopper-based parametric design program for the layout and design of LID facilities. This approach significantly reduces interdisciplinary communication costs and enhances urban planning efficiency. By integrating BMP and LID strategies, the proposed framework offers a flexible, rapid, and efficient solution for achieving resilient stormwater management in the context of urban micro-renewal. Full article

This study utilizes ArcGIS, the InVEST model, and the SCS model to analyze remote sensing data from the central urban areas of Chengdu. The analysis simulates water yield and runoff within the study area while calculating the water conservation capacity for each land use type using the water balance method. This study aims to address the challenges faced by Chengdu in implementing its sponge city initiatives. The results reveal that the spatial distribution of direct runoff generally follows a pattern of “low in the periphery and high in the center”. Transportation, commercial, industrial, and residential land types account for 74.7% of the total surface runoff within the study area, emphasizing their importance in urban rainwater management and sponge city development. Water yield varies across different land use types, with water bodies exhibiting the lowest capacity and artificial land exhibiting the highest capacity. This pattern initially exhibited a downward trend before increasing, with land use type, climatic factors, and vegetation coverage identified as the primary drivers of water yield. The water conservation capacity of the study area gradually decreased, with higher values observed in the east and south and lower values in the north and west. These trends and spatial differences can be attributed to urban expansion and alterations in land cover. Based on these findings, this study assessed the risk of urban waterlogging and provided recommendations for optimizing low-impact development (LID) strategies. This study provides a scientific foundation for the development of sponge city initiatives, urban waterlogging mitigation, and rainwater management strategies in Chengdu. Full article

In recent years, the urgent need to mitigate stormwater runoff and address urban waterlogging has garnered significant attention. Low Impact Development (LID) has emerged as a promising strategy for managing urban runoff sustainably. However, the vast array of potential LID layout combinations presents challenges in quantifying their effectiveness and often results in high construction costs. To address these issues, this study proposes a simulation-optimization framework that integrates the Storm Water Management Model (SWMM) with advanced optimization techniques to minimize both runoff volume and costs. The framework incorporates random variations in rainfall intensity within the basin, ensuring robustness under diverse climatic conditions. By leveraging a multi-objective scatter search algorithm, this research optimizes LID layouts to achieve effective stormwater management. The algorithm is further enhanced by two local search techniques—namely, the ‘cost–benefit’ local search and path-relinking local search—which significantly improve computational efficiency. Comparative analysis reveals that the proposed algorithm outperforms the widely used NSGA-II (Non-dominated Sorting Genetic Algorithm II), reducing computation time by an average of 8.89%, 16.98%, 1.72%, 3.85%, and 1.23% across various scenarios. The results demonstrate the method’s effectiveness in achieving optimal LID configurations under variable rainfall intensities, highlighting its practical applicability for urban flood management. This research contributes to advancing urban sponge city initiatives by providing a scalable, efficient, and scientifically grounded solution for sustainable urban water management. The proposed framework is expected to support decision-makers in designing cost-effective and resilient stormwater management systems, paving the way for more sustainable urban development. Full article

Urbanization leads to increased stormwater runoff, placing enormous pressure on the drainage system, including that of port cities in Hunan Province. This increases the risk of urban flooding and threatens the sustainability of the urban ecosystem. In this study, we employed the Storm Water Management Model (SWMM) to assess surface runoff and pollutant accumulation (TSS, COD, TN, and TP) under varying storm conditions and evaluate the efficacy of low-impact development (LID) measures in mitigating these impacts. The results included a peak ratio of 0.45, indicating complex concentration dynamics and good agreement with the observed rainfall patterns. The installation of permeable paving, rainwater infiltration ditches, and rainwater storage tanks reduced the peak flows by 33.3%, 30%, and 50%, respectively, with the rainwater storage tanks also reducing the total phosphorus (TP) load by 29.17%. In addition, it was found that rainwater collected in cisterns could be used not only for resource recycling but also to replenish groundwater resources. This demonstrates that low-impact development (LID) measures significantly reduce peak flows and pollutant loads and effectively promote the sustainable use of urban stormwater resources. The cost–benefit analyses show that the long-term benefits of LID systems are superior to those of traditional stormwater management systems. Therefore, LID measures can not only effectively reduce the pressure on urban drainage systems and improve flood prevention and mitigation capabilities but also promote sustainable development and the green transformation of cities. Full article

Urbanization necessitates Low Impact Development (LID) practices for sustainable development, but existing studies lack analysis about the comprehensive effect and optimal allocation of LID combination practices. To address this gap, this study conducted an in-depth analysis of the runoff control effects of individual and combined LID practices and pollutants under varying retrofit proportions, utilizing the Storm Water Management Model (SWMM). Four evaluation metrics were employed for parameter calibration and validation assessment to ensure the accuracy of the SWMM. The Response Surface Methodology (RSM) was then employed to optimize the retrofit proportions of LID practices due to its high efficiency and statistical rigor. The results showed that, under the same retrofit ratio, bio-retention (BC) has a better runoff reduction rate and pollutant removal rate. For example, when the retrofit proportion is 100%, the runoff pollutant removal rates of BC in Parcel 1 and Parcel 2 are 29.6% and 32.9%, respectively. To achieve a 70% runoff control rate, the optimal retrofit proportions for Parcel 1 were 67.5% for green roofs (GR), 92.2% for permeable pavements (PP), 88.9% for bio-retention cells (BC), and 50% for low-elevation greenbelts (LEG); these correspond to the proportions for Parcel 2 that were 65.1%, 68.1%, 82.0%, and 50%, respectively. In conclusion, this study provides scientific and technical support for urban planners and policymakers in urban rainwater management, especially in similar regions. Full article

Sea fennel, a halophyte with growing economic importance in the Mediterranean region, offers a rich source of bioactive compounds for diverse applications in various industries, including food, pharmaceuticals, and cosmetics. Recognizing the crucial role of eco-design in promoting sustainable food production, this study aimed to assess the environmental impacts of two novel sea fennel products: dried spice and fermented pickles. The Life Cycle Assessment (LCA) method was used to evaluate the environmental burdens of these new products, from raw material acquisition to packaging end-of-life, to fine-tune the innovation process. Primary data were collected from a company in the Marche region, Italy. The Environmental Footprint 3.1 method was applied to analyze the impacts. From the results obtained, the climate change score for the spice was 6.24 kg CO₂ eq./kg spice, while the fermented pickle was 0.89 kg CO₂ eq./kg product—net weight. The results also revealed that primary packaging emerged as the primary environmental hotspot for both products, accounting for more than 40% of the total impacts in most of the impact categories. Glass packaging significantly contributed to the environmental impact of the spice, while both glass jars and tin-plated steel lids contributed substantially to the impact of the pickled products. Despite the generally low impact of sea fennel cultivation, the processing and packaging stages significantly increased the overall environmental impacts of both products. This study provides valuable insights for manufacturers seeking to develop and commercialize highly sustainable sea fennel-based products. By identifying key environmental hotspots and implementing eco-design principles during the product development phase, manufacturers can significantly reduce the environmental impact of these novel food products. Full article