Heavy Rainfall Conditions Research Articles

Risk assessment of urban infrastructure vulnerability to meteorological disasters: A case study of Dongguan, China

Effective forecasting and response to meteorological hazards are crucial for safeguarding life, property, and supporting sustainable socioeconomic development. With the rising frequency and severity of meteorological hazards worldwide, this study proposes an enhanced risk assessment framework for urban infrastructure exposed to extreme weather events, with a focus on cascading impacts to critical services such as electricity, communication, and transportation networks (roads and subways). A disaster-loss model is developed to quantify infrastructure vulnerability at various spatial and temporal scales under heavy rainfall conditions, accounting for secondary effects. The model's performance is validated through empirical analysis of a 15-year rainfall event in Dongguan City, China, occurring from September 7–8, 2023. Results indicate the model's ability to predict real-event outcomes with approximately 70% accuracy. This model offers valuable insights for disaster prevention and mitigation strategies, aiding decision-makers in optimizing emergency resource allocation, enhancing disaster response efficiency, and issuing timely public risk warnings to minimize losses.

Laboratory Model Tests on the Deformation and Failure of Terraced Loess Slopes Induced by Extreme Rainfall

Heavy rainfall is the main factor inducing the failure of loess slopes. However, the failure mechanism and mode of terraced loess slopes under heavy rainfall have not been well investigated and understood. This paper presents the experimental study on the deformation and failure of terraced loess slopes with different gradients under extreme rainfall conditions. The deformation and failure processes of the slope and the migration of the wetting front within the slope during rainfall were captured by the digital cameras installed on the top and side of the test box. In addition, the mechanical and hydrological responses of the slope, including earth pressure, water content, pore water pressure, and matric suction, were monitored and analyzed under rainfall infiltration and erosion. The experimental study shows that the deformation and failure of terraced loess slopes under heavy rainfall conditions exhibit the characteristic of progressive erosion damage. In general, the steeper the slope, the more severe the deformation and failure, and the shorter the time required for erosion failure. The data obtained from sensors embedded in the slope can reflect the mechanical and hydraulic characteristics of the slope in response to rainfall. The earth pressure and pore water pressure in the slope exhibit a fluctuating pattern with continued rainfall. The failure mode of terraced loess slopes under extreme rainfall can be summarized into five stages: erosion of slope surface and formation of small gullies and cracks, expansion of gullies and cracks along the slope surface, widening and deepening of gullies, local collapse and flow-slip of the slope, and large-scale collapse of the slope. The findings can provide preliminary data references for researchers to better understand the failure characteristics of terraced loess slopes under extreme rainfall and to further validate the results of numerical simulations and analytical solutions.

Impact of Extreme Rainfall on High-Speed Rail (HSR) Delays in Major Lines of China

Abstract Punctuality monitoring and analysis aim to optimize resource allocation for enhancing rail traffic performance and quality. Adverse weather conditions, particularly heavy precipitation events, are recognized as significant drivers of delays and reduced punctuality of the rail system. This study addresses two key research questions using high-speed rail (HSR) as an example—what is the impact of rainfall on HSR’s delay and to what extent are HSR vulnerable to rainstorms. The data for the study were collected from the HSR on the major lines of eastern China in the rainy season of 2015–17 which lasted from May to October. High-resolution precipitation data are integrated with nonspatial HSR operational data using GIS to create composite grids covering buffer zones around HSR lines. These grids match the spatial scale of historical hourly precipitation data and enable regression analyses to assess how precipitation affects HSR operations. The results indicate that extreme rainfall significantly contributes to delays and reduced punctuality, with varying impacts observed across different HSR lines. Specifically, daily areal precipitation significantly delays services on the Hangzhou–Shenzhen and Nanjing–Hangzhou HSR lines. Rainfall intensity has a more pronounced impact on delay services of the Beijing–Shanghai HSR, while extreme precipitation most frequently affects the Shanghai–Nanjing and Jinhua–Wenzhou HSR lines. The case analysis enhances understanding of HSR vulnerability to heavy rainfall conditions and recommends regional adaptation strategies to manage climate-related uncertainties.

Intelligent beehive monitoring system based on internet of things and colony state analysis

Bees play a crucial role in terrestrial ecosystems. However, beekeepers are unable to monitor the state of beehives (bees and environment) all the time, which often results in bees escaping or even dying. Currently, some researchers provided the scheme of intelligent beehive monitoring system equipped with the Internet of Things (IoT), There remain two challenges: accurately monitor the environmental status around the hive and accurately track and monitor bees in real time. With the development of the IoT and computer vision algorithms, we hope to provide an automated and efficient system to meet the above challenges. In this paper, we proposed a hive monitoring system, and build a visualization module in the cloud to monitor the activity of bee colonies and the environmental dynamic changes. (1) We proposed a multi-bee tracking algorithm to solve the problem of monitoring bees at the door of the hive; (2) we constructed a dataset containing various complex scenes, named BEE22, for training and testing the performance of our algorithm; (3) we designed a bee counting rule, based on results of multi-bee tracking algorithm, to reasonably count the bees entering or leaving the beehive; (4) we have deployed multiple sensors around(center, margin, door, and environment) the hive to accurately reflect the changes in the environment around the hive. Experimental results demonstrate the effectiveness and excellence of our system. In particular, the tracking performance of the multi-bee tracking algorithm reaches 83.5 % ± 0.7 % Multiple Object Tracking Accuracy (MOTA) and 77.3 %±0.2 % Multiple Object Tracking Precision (MOTP), speeds up to 16 frames per second, compared with other algorithms, MOTA and Identity F1 Score (IDF1) are improved by 5.4 % and 8.2 % respectively. Moreover, our counting algorithm also achieved excellent results, with root mean square error (RMSE) of 1.3 ± 0.1, 0.2 ± 0.0, and 1.6 ± 0.1 in counting the number of bees current, entry, and out scene in an episode, respectively. After that, the system will be deployed and monitored for a long time in the actual scenario, it was found that the activity of bees decreased significantly under heavy rainfall conditions. Additionally, the activity of the bee colony will also increase accordingly, when the amplitude is 500 dB to 2000 dB, the temperature of the center of the beehive is 25 °C to 37 °C, and the humidity is 48 % to 67 %. In summary, our system can provide valuable information for bee farmers to make control decisions on hives.

Changes of vertical distribution of Microcystis colonies driven by short-term rainfall: Disappearance and reformation of surface bloom

Global climate warming and human activities have increased the magnitude and frequency of Microcystis surface blooms, posing significant threats to freshwater ecosystems and human health over recent decades. Heavy rainfall events have been reported to cause the disappearance of these blooms. Although some studies have employed turbulence models to analyze the movement characteristics of Microcystis colonies, the impact of rainfall is complex, comprehensive investigations on their vertical migration induced by short-term rainfall are still necessary. Utilizing monitoring data from eutrophic ponds and controlled simulation experiments, this study examines the short-term impacts of rainfall on the vertical distribution of Microcystis in the water column. Our findings indicate that rainfall contributes to the disappearance of Microcystis blooms by reducing the quantity of small to medium-sized colonies (0–100 μm) at the surface, subsequently decreasing the overall Microcystis biomass. As rainfall intensity increases, larger colonies migrate deeper into the water column. At a rainfall threshold of 666 mm, the difference in the median volume diameter (DV50) of Microcystis colonies between the surface and bottom reaches a minimal value of 3.09%. Post-rainfall, these colonies rapidly ascend, aggregate into larger formations, and re-establish surface blooms. The greater the rainfall, the smaller the resultant Microcystis biomass, albeit with larger aggregated colony sizes. When rainfall exceeds 222 mm, the recovery rate of surface Microcystis biomass remains below 100%, decreasing to 19.48% at 666 mm of rainfall, while the median volume diameter (DV50) of the colonies increases to 139.07% of its pre-rainfall level. Furthermore, compared to pre-rainfall conditions, the photosynthetic activity of the surface Microcystis colonies was enhanced and the secretion of EPS was increased under heavy rainfall conditions. Our results identify a critical response time of 30 min for Microcystis colonies to rainfall, after which the response ceases to intensify. These insights are crucial for predicting post-rain Microcystis bloom dynamics and aiding management authorities in timely interventions.

Numerical Analysis of Flood Invasion Path and Mass Flow Rate in Subway Stations under Heavy Rainfall Conditions

The occurrence of extreme weather, such as heavy rainfall and sudden increases in precipitation, has led to a notable rise in the frequency of flooding in subway stations. By conducting numerical simulations of flood disasters in subway stations under heavy rainfall conditions and gaining insights into the patterns of flood invasion inside the stations, it is possible to develop practical and feasible drainage designs for the stations. This paper employs the computational fluid dynamics (CFD) method, utilising the volume of fluid function (VOF) method and the renormalization k-ε group model within the vortex viscosity model. The complete process of flood invasion into subway stations with varying water levels (1500 mm, 2000 mm, and 2450 mm) is modelled, and the distribution of floods at different times under varying operational conditions is analysed to identify the evolutionary patterns of station flood history. The simulation calculations yielded the mass flow rate time history curve at the tunnel entrance and exit, which was then subjected to an analysis of its development trend over time. The total accumulated water in the subway station is calculated by integrating the difference in mass flow rate between the entrance and the tunnel exit, using the mass flow rate curve. In conclusion, the paper proposes drainage measures that provide valuable insights into pumping strategies when floodwaters infiltrate subway stations. The results indicate that the speed of flood spreading in subway stations increases with higher groundwater levels, and that the mass flow rate of floodwater entering the tunnels increases over time, eventually reaching a stable state. It was observed that, at certain times, the mass flow rate of floodwater into the tunnels exhibited a linear relationship with time.

Quantifying the effects of rock fragments embedding vs. Covering on soil erosion in karst sloping cropland

Rock fragments can alter soil structure, thus profoundly affecting soil properties, hydrological and erosion processes. Hence, it is essential to quantify the role of rock fragments in soil-water processes in order to fully grasp their complex impacts on soil erosion. In this study, the effect of vertical embedded (VE) and covered (CV) rock fragments on runoff and soil loss of sloping cropland were investigated in plot scale through field monitoring experiments, with bare land (CK) as a control. Results showed that surface runoff from VE decreased by 24.93% compared to bare land, while subsurface flow and underground flow increased by 12.47% and 10.85%, respectively. Similarly, compared to bare land, CV decreased surface runoff by 14.08% and increased subsurface flow and underground flow by 7.09% and 7.29% respectively. Consequently, both VE and CV effectively decreased surface runoff and enhanced the proportion of rainwater converted into subsurface flow and underground flow (P < 0.05). Simultaneously, the benefits of VE in reducing surface runoff and promoting rainwater infiltration was found to be more significant than that of CV (P < 0.05). In terms of soil erosion, compared with bare land, VE reduced the surface soil loss rate by an average of 41%, while CV instead increased the surface soil loss rate by an average of 3.64%, and these changes were both statistically significant (P < 0.05). Moreover, soil erosion from subsurface flow and underground flow may be a long-term accumulation process, resulting in insignificant differences in soil erosion rates between treatments in this study (P > 0.05). Therefore, in studying the impact of rock fragments on soil erosion in karst sloping cropland, the focus should be on soil erosion caused by surface runoff. Additionally, the impact of rock fragments on the transformation of rainwater and soil erosion was limited by rainfall conditions, with VE showing a more prominent effect in preventing soil erosion under heavy rainfall conditions. Overall, the impact of rock fragments on soil erosion varies depending on their distribution patterns in the topsoil. It is necessary for these differences to be incorporated into process-based runoff and erosion models.

Prediction of the Dangerous Range of Dumps Based on a Dynamic Process

A dump is a loose accumulation of solid waste from mining operations that easily leads to disasters such as landslides and debris flows. Taking a dump in the Panzhihua region of China as an example, based on the MPM and SPH meshless methods, the dynamic calculation of the instability process of the spoil slope was carried out according to the realistic three-dimensional calculation model of the generated terrain. Firstly, the strain and displacement of the dump under normal conditions and heavy rainfall conditions were simulated by the MPM material point method. The maximum spatial displacement of the dump under heavy rainfall conditions reached up to 386 m. Then, the motion and morphology of the accumulation of the dump under ordinary working conditions and heavy rainfall conditions were analyzed using the smooth particle hydrodynamics (SPH) method. Under heavy rainfall conditions, the maximum horizontal displacement of the dump was approximately 394 m. The research results are conducive to the risk assessment of the spoil slope and provide theoretical support for the calculation of the range of potential threats from the dump.

Geostationary Satellite-Based Overshooting Top Detections and Their Relationship to Severe Weather over Eastern China

Overshooting tops (OTs), prominent signatures within deep convective storms, are produced by intense updrafts and are closely linked to heavy rainfall, strong winds, and other severe weather conditions. Using an OT dataset derived from multiyear observations of precipitation radar on board the Global Precipitation Measurement core observatory as a reference, the performances of two commonly used OT detection algorithms are evaluated for the Himawari-8 and Fengyun-4A satellites. The results indicate that the infrared contour-based algorithm based on Himawari-8 is the most effective for objective OT detection in eastern China. It exhibits a probability of detection (POD) of 62.1% and a false-alarm ratio (FAR) of 36.6%, outperforming others by achieving a greater POD and a lower FAR. Furthermore, based on the severe weather records from surface meteorological stations and nearby OT detections, a strong relationship is revealed between GEO-detected OTs and the occurrence of short-term heavy rainfall (e.g., ≥20 mm h−1) and extreme wind speed (e.g., ≥17.2 m s−1) events. The OT matched percentages for these events are 61.8% and 54.0%, respectively. This suggests that GEO satellite-based OT data can serve as an important objective product for forecasters to increase their understanding of severe convective storms.

The B-spline mapping function (BMF): representing anisotropic troposphere delays by a single self-consistent functional model

Troposphere’s asymmetry can introduce errors ranging from centimeters to decimeters at low elevation angles, which cannot be ignored in high-precision positioning technology and meteorological research. The traditional two-axis gradient model, which strongly relies on an open-sky environment of the receiver, exhibits misfits at low elevation angles due to their simplistic nature. In response, we propose a directional mapping function based on cyclic B-splines named B-spline mapping function (BMF). This model replaces the conventional approach, which is based on estimating Zenith Wet Delay and gradient parameters, by estimating only four parameters which enable a continuous characterization of the troposphere delay across any directions. A simulation test, based on a numerical weather model, was conducted to validate the superiority of cyclic B-spline functions in representing tropospheric asymmetry. Based on an extensive analysis, the performance of BMF was assessed within precise point positioning using data from 45 International GNSS Service stations across Europe and Africa. It is revealed that BMF improves the coordinate repeatability by approximately 10%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$10\\%$$\\end{document} horizontally and about 5%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$5\\%$$\\end{document} vertically. Such improvements are particularly pronounced under heavy rainfall conditions, where the improvement of 3-dimensional root mean square error reaches up to 13%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$13\\%$$\\end{document}.

Field study on vegetation eco-protection technology for red sandstone fill slope against water damage

The construction of fill slopes becomes a critical aspect when there is a need to change the terrain or create new terrain. However, due to the poor engineering properties of the fill material, especially when red sandstone with notable disintegration properties is used, the risk of slippage or collapse may occur. This material is prone to erosion and disintegration under the action of natural factors such as heavy rainfall, leading to severe soil erosion and slope instability. In addition, the construction of fill slopes inevitably causes the destruction of native vegetation, exacerbating environmental problems. To address these problems, an novel ecological approach for preventing water damage to red sandstone fill slopes was developed using the vegetation–high-performance turf reinforcement mat –anchor–drainage pipe–synergistic slope protection system. Three test red sandstone slopes with different protection methods (unprotected, three-dimensional (3D) protection mesh, and vegetation ecological protection system slopes) were constructed, and the feasibility and reliability of ecological protection against water damage to red sandstone fill slopes were analysed via the field test method. The results showed that the vegetation ecological protection system can effectively inhibit soil erosion and increase the survival rate of vegetation roots. Moreover, the the high-performance turf reinforcement mat provides a strong protective complex through interactions with vegetation roots, anchors, and drains, which significantly enhances slope stability. Under heavy rainfall conditions, the vegetation ecological protection system can effectively limit slope erosion due to water scour, thus maintaining the structural integrity of the slope.

Mechanical responses of shallowly buried pipelines to adjacent deep excavations considering heavy rainfall influence

Climate change has resulted in a high global incidence of heavy rainfall, severely damaging the urban infrastructure. The analytical method used to predict the mechanical response of pipelines under the influence of rainfall influence could serve as a valuable design basis in the preliminary stage. This study developed an analytical solution based on the stratified Green-Ampt model and displacement-controlled two-stage method. The first stage evaluates the greenfield soil displacement at pipeline elevation by employing the Mindlin solution and considering the superposed effects of excavation (unloading) and rainfall infiltration. The second stage predicts the mechanical responses of the pipeline by simplifying the pipeline–soil interaction into a continuous Euler–Bernoulli beam resting on a Winkler foundation model. The analytical solution was calculated using the finite difference method and verified against a published study. Finally, parametric studies were conducted to investigate the rainfall– excavation–pipeline interaction, including the rainfall intensity and duration, maximum lateral wall deflection, and pipeline location. The results showed that a 48-8-mm/h rainfall increased the maximum displacement and maximum bending moment of the pipeline by 6.54% and 7.93%, respectively. The prediction results provide practical guidance for designing deep excavations adjacent to pipelines buried under heavy rainfall conditions.

Performance analysis of 4QAM-OFDM-FSO link under rain weather conditions

Abstract Free space optical communication (FSO) is a technique based on transmission of data by propagating the light in free space. FSO is inexpensive, providing high data rates, high capacity, high security, and low power and uses the license free frequency spectrum. Nevertheless, FSO is still facing many problems such as bad weather conditions, atmospheric turbulence, and multipath fading. In this research work, orthogonal frequency division multiplexing (OFDM) FSO system is analyzed for low to heavy rain fall intensities. Different rain rates have been considered for low, moderate, heavy, very heavy, and torrential rains. For all the rain rates, a direct detection OFDM–FSO system and a coherent detection system have been simulated and results are compared. Analysis has been done on the basis of SNR, received power, and constellation diagrams. According to these parameters, link length of both the systems for different rain rates was found. Coherent detection is applied to improve the system sensitivity compared to conventional direct detection. In tropical regions where heavy rainfall is the main reason for the degradation of the system, the OFDM system with coherent detection can perform better with high data rates. Second, over a 11 km FSO, a 4-QAM wireless signal is successfully transmitted under very heavy rainfall conditions. The distance achieved by moderate and heavy rains is 25 km and 15.5 km with an acceptable SNR of 25 dB and a system sensitivity (received power) of −65.1 dBm.

Toppling stability of partially buried blocks in granite residual soil slope under extremely heavy rainfall condition

The granite blocks are widely distributed on granite residual soil slopes, particularly in the circumstances of humid granitic terrain. These blocks may be partially buried in the soil slope with their long axis upright, which results in complex toppling mechanisms. The objective of this study is to investigate the mechanical stability of the blocks against toppling failure, considering extremely heavy rainfall. Based on the analysis of limit equilibrium, an analytical formulation taking the influence of the block overhang length and the slope inclination into account is proposed to calculate the factor of safety (FOS) of the blocks partially buried in the soil slope. The results of the model experiments verified the performance of this formulation by showing a consistent behavior regarding the stability of the block with the formulation. The FOS obtained from this analytical formulation first shows a trend of increase and then a decrease according to the overhang length of the blocks. Furthermore, the critical overhang length and the critical slope inclination were found related to the toppling failure of potential blocks. The analytical formula obtained in this study can be used to determine the factor of safety against toppling of the single blocks on granite residual soil slopes, which provide a quantitative method for risk evaluation of toppling disaster in granitic regions.

Integrating Model Predictive Control With Stormwater System Design: A Cost‐Effective Method of Urban Flood Risk Mitigation During Heavy Rainfall

AbstractThe integration of green‐gray infrastructures with advanced control approaches is revolutionizing the stormwater system retrofitting, emerging as an innovative strategy to mitigate urban flood risks. However, a major challenge lies in balancing the substantial investments of these infrastructure projects with their environmental benefits, such as reduced flooding volume and lower peak flow. Model predictive control (MPC), a dynamic and intelligent control approach, optimizes these environmental benefits but is underutilized in the system design phase for cost‐effectiveness analysis. This study introduces a multi‐scenario model framework that incorporates MPC and other control approaches into stormwater system designs, including the implementation of controlled storage tanks and green infrastructures. This framework provides comprehensive modeling tools for practitioners to evaluate the flood control benefits and costs across various infrastructure designs and control scenarios, ultimately identifying solutions that are both environmentally and economically viable. A case study conducted in a small urban catchment area in Shenzhen City, China, demonstrates the effectiveness of this framework. The results indicate that MPC outperforms other control scenarios, particularly under heavy or extreme rainfall conditions. Notably, MPC not only provides superior environmental benefits but also yields considerable cost savings, ranging from 1,787 to 9,371 USD per hectare compared to static control, equating to a 5% reduction in cost relative to rule‐based control. Such findings suggest that integrating MPC is a cost‐effective alternative to extensive infrastructure expansion for flood management, which significantly enhances the benefit contribution of controlled infrastructures without substantial additional expenses.

Advancements in mapping landslide susceptibility in Bafoussam and its surroundings area using multi-criteria decision analysis, statistical methods, and machine learning models

Landslides pose a significant threat to lives and socio-economic stability globally. In this study, we conducted a comprehensive landslide susceptibility mapping (LSM) in the western region of Cameroon, focusing on Bafoussam and its surroundings. The integration of multi-criteria decision analysis models (AHP), statistical methods (Information Value IV, Shannon Entropy SE, Frequency Ratio FR), and machine learning algorithms (Naïve Bayes and Logistic Regression) provided a robust assessment of landslide risk. Our analysis, based on 54 recorded landslides, carefully selected Landslide Conditioning Factors (LCF), and influential parameters such as lithology, slope, altitude, and precipitation, resulted in susceptibility maps categorizing the area into five risk zones. The Spatial distribution shows the centre and northwestern regions as high-risk areas. Model sensitivity differences underscore the need for tailored LSM selection. Validation using the Area Under Curve/Receiver Operating Characteristics (AUC/ROC) method indicates the LR and NB methods have the highest accuracy (82.7% and 84.1%, respectively). Comparative analysis of landslide events in Gouaché, Sichuan, Souk Ahras, and Kekem reveals correlations between heavy rainfall and geological conditions. The study supplies valuable insights for decision-makers in landslide-prone areas, emphasizing the importance of integrating multiple methodologies for comprehensive risk assessment and management.

Assessment of factors causing landslides using the Analytical Hierarchy Process (AHP) method

Landslides are Indonesia's second most common disaster in the last ten years. Landslides cause losses, reaching hundreds of billions and threatening human safety. For this reason, it is necessary to take action to reduce the negative impact of landslides. Physical and non-physical mitigation can occur before, during, and after a disaster. The most essential thing in disaster mitigation is knowing the major factors that cause landslides. This research aims to analyze the major and minor factors that cause landslides using the Analytical Hierarchy Process (AHP) and the Likert scale. Respondents in this research are experts in disasters, especially landslides—respondents from universities in Indonesia, practitioners, and people involved in disaster mitigation. Validity and reliability tests were carried out on each question used in the questionnaire. The research results show that the landslide disaster was caused by a disruption in balance that occurred due to internal and external disturbance factors. The major external factors that cause slope failures are the cutting of hills and changes in land use to built-up areas. In contrast, the major internal factors that trigger landslides are heavy rainfall and steep topographic conditions. The results of this research in the form of weight and scoring values for each factor causing landslides can be used as a reference for mapping landslide areas to identify areas with the potential for landslides.

Slope Stability Analysis under Heavy Rainfall Conditions Based on a Modified Green-Ampt Model

Slope Stability Analysis under Heavy Rainfall Conditions Based on a Modified Green-Ampt Model

Characterization and Application of Rice Straw-Based Polyurethane Foam Blocks for Soil Erosion Control

Soil erosion, a global problem, degrades land quality and increases pollution and sedimentation in bodies of water. This study propounds a new material to mitigate soil erosion using rice straw-based polyurethane foam (RSPF) blocks as a potential replacement for commercially available expanded polystyrene (EPS) foam in slope stabilization. RSPF was synthesized via a conventional one-shot foaming method with 15% rice straw-based polyol content. The RSPF blocks have an average density of 43.29 kg/m3, average compressive strength of 184.55 kPa, closed cell content of 88.4%, and water absorption capacity of 262% that can effectively reduce water runoff. These properties are comparable to EPS foams according to ASTM D6817, except for the high absorption capacity of RSPF. This added feature allows the foam to act as topsoil protection by reducing runoff. In slope stabilization and topsoil protection applications, the effectiveness of the RSPF blocks in reducing soil loss was tested in both simulated and natural rainfall events with different land slope degrees, rain intensities, and soil covers. Results show that the use of RSPF in the simulated setup with a heavy rain intensity of 80 mm/h reduced the soil loss by 61.5%, 22.7%, and 4.3% in 5°, 10°, and 20° of land slope, respectively. There was also a higher degree of soil loss reduction when the RSPF block was coupled with a natural vegetation soil cover by 79.6%, 70%, and 19.3% in 5°, 10°, and 20° land slopes, respectively. Moreover, in the natural rainfall events in an open field with a land slope of 20°, the recorded soil loss reduction reached 93.6–98.8% at an average rainfall intensity of 16.26 mm/h. Additionally, the relationship between soil loss and land slope was investigated to produce a best fit model that predicts the soil loss up to a 20° land slope. An interesting observation was made wherein the erosion rate increased using linear regression modeling in the simulated setup for bare soil (BS), soil with vegetation (SV), soil with RSPF (SF), and soil with RSPF and vegetation (FV), with high coefficient of determination (R2) values between 0.92 and 0.99. These findings suggest that the RSPF block is a promising alternative and sustainable material for EPS foams in mitigating soil erosion, especially under heavy rainfall conditions.

Range augmentation of 16 × 60 GHz WDM RoFSO system in foggy &amp; rainy weather

Abstract The wavelength division multiplexed radio over free space optics (WDM RoFSO) system is a paramount candidate to provide extended range thus enabling efficient last mile connectivity. But the conventional design is unable to transmit the information up to larger distances under harsh climate conditions. An improved 16 channel WDM-RoFSO system is proposed and simulated which yields quality transmission for extended range under the attenuation of 5.8 dB/km, 7.7 dB/km, 9.2 dB/km and 26 dB/km for foggy and rainy conditions respectively. A radio frequency (RF) signal of 60 GHz is modulated over an optical signal carrier and successfully transported with cumulative 16 × 10 Gbps bit rate up to 3.75 km in foggy environment. The link range is augmented by 1.65 km, 0.9 km, 1.8 km &amp; 1 km for light fog, moderate fog, moderate rainfall and heavy rainfall conditions respectively.