Spatio-temporal study of water quality variables in the Rio de Ondas Hydrographic Basin, west of Bahia, Brazil using multivariate analysis.

Water bodies are containers that receive a large load of water quality variables through the release of domestic, industrial, and agricultural effluents. With this focus, this work aimed to conduct a temporal-spatial variability study in the Rio de Ondas Hydrographic Basin through multivariate statistical analysis. For this, seventeen collection sites were established in four stations along the Rio de Ondas and its tributaries between 2017 and 2018. Ionic chromatography with suppressed conductivity was used for ions determination, while ICP-OES determined metals' total concentrations. The land use and occupation assessment between 1985 and 2021 was using data from MapBiomas were used and the descriptive and multivariate analysis of the data using version free of the Statistica software. The results showed that, in 30 years, there was a growth of 569% of agricultural activities in the watershed area, with significant suppression of native vegetation, favoring the transport of contaminants to rivers. Ca2+, PO42-, Al, Cu, and Zn concentrations showed a statistically significant difference between the seasons, with higher medians in the rainy season. Rainy season influenced the formation of three groups in the PCA, consisting of electrical conductivity, salinity, TDS, and PO42- (group 1); temperature, Fe, SO42-, and Cl- (group 2); and Ca2+, Mg2+, Na+, and HCO3- (group 3). The strong correlation between parameters of each group indicates anthropic influence on the watershed's water quality. However, levels are within the potability standard.

Assessment of influencing level of rainfall and physical factors on groundwater level for a semi-arid flat terrain watershed using grid-based geospatial analysis: a case study from Lower Palar Basin, Tamil Nadu, India.

Understanding natural phenomena with the help of modern scientific approaches helps to reach sustainable solutions for current and future water-related problems. In this context, present study aims to assess relative influencing level of physical factors in controlling groundwater level, using a novel grid-based delineation technique, in Lower Palar River Basin, in Kanchipuram and Chengalpattu districts of South India. The influencing factors viz-a-viz: rainfall, soil texture, land use/land cover, terrain slope, geomorphology, lithology, and drainage characteristics were considered for the study. Archived data (2011 to 2020) of monthly rainfall at four rain gauge stations and monthly groundwater level of 22 locations, soil texture, lithology, and geomorphology data were considered for the study. SRTM digital elevation model with 30-m resolution was used for analyzing drainage characteristics and terrain slope. Thematic maps for considered factors were prepared, using common grid delineation method in GIS platform that divided study area into 52 grids, to inter-relate the discrete and continuous parameters with groundwater level. Results indicate that level of influence increases in the order of precipitation followed by lithology, land use/land cover, terrain slope, geomorphology, infiltration number, and soil texture. The study shows groundwater resilience is highly influenced by soil texture and infiltration number compared to other factors considered. It can be concluded that grid-based delineation successfully identifies grids with significant influence of individual factors by comparing with groundwater resilience. Common grid-based delineation method proves to be more effective in assessing groundwater resilience and can be used more efficiently in groundwater studies.

Relationship Between Extreme Rainfall Occurrences and Galactic Cosmic Rays over Natal/RN, Brazil: A Case Study.

The increase in Galactic Cosmic Rays (GCR) flux intensity induces the Condensation Nuclei (CN) production, which intensifies rainfall occurrences. Then, the objective of this study was to analyze the rainfall distribution in the NEB and the impact of GCR flux on extreme rainfall events occurred in July 1998 in Natal/RN, Brazil. We used historical rainfall, Sea Surface Temperature (SST) and GCR flux data for Natal/RN. We used R software for statistical analysis. The results indicate that the GCR flux is important for intensifying extremes rainfall occurrences. This fact is observed when analyzing the relationship between rainfall greater than 10 mm and GCR flux above 6,390 counts/min. Pearson correlation coefficient between rainfall and GCR flux was 0.94 (p-value = 0.0005) and SST was -0.76 (p-value = 0.0263), both statistically significant. The rate between GCR flux and rainfall was +2.87 mm/count/min, while the rate between SST and rainfall was -7.91 mm/°C. The variance proportion explained by regression was 94.41%, with relative importance degree corresponding to 62.0% for GCR flux and 32.4% for SST, respectively. The results show that GCR flux had a greater contribution to extreme rainfall occurrence in the metropolitan region of Natal/RN and it is important in climatological studies.

Summer rain and wet soil rather than management affect the distribution of a toxic plant in production grasslands.

In the northern forelands of the Alps, farmers report an increase of Jacobaea aquatica in production grasslands. Due to its toxicity, the species affects grassland productivity and calls for costly control measures. We are investigating the extent to which management practices or climatic factors are responsible for the increase of the species and how the situation will change due to climate change. We tested for effects of management intensity, fertilization, agri-environmental measures, and soil disturbance, and modeled the occurrence of the species under rcp4.5 and rcp8.5 scenarios. The main determinants of the occurrence of the species are soil type and summer rainfall. A high risk is associated with wet soils and > 400 mm of rain between June and August; an influence of the management-related factors could not be detected. Under the climate-change scenarios, the overall distribution decreases and shifts to the wetter alpine regions. Thus, the current increase is rather a shift in the occurrence of the species due to the altered precipitation situation. Under future climatic conditions, the species will decline and retreat to higher regions in the Alps. This will decrease the risk of forage contamination for production grassland in the lowlands.

Water quality performance assessment of two stormwater detention basins located in the recharge zone of a karst aquifer.

Stormwater detention basins are used to minimize peak discharges and improve water quality mainly through sedimentation; however, limited studies have evaluated the water quality performance of detention basins located over karst aquifers. Karst aquifers are vital sources of drinking water for many regions of the world and their recharge areas are susceptible to contamination from surface water resources. In this study, an analysis of two stormwater detention basins (namely, Kyle and TPC) located in the recharge zone of one of the most prolific karst aquifers in the world (Edwards Aquifer, San Antonio, Texas), were conducted over a period of one year to quantify the water quality and hydrologic performance of the basins. Automated samples were collected during the storm events and analyzed for nitrate (NO3--N), nitrite (NO2--N), ammonia (NH3-N), total dissolved nitrogen (TDN), phosphorus (PO43-), total suspended solids (TSS), total dissolved solids (TDS), total carbon (TC), total organic carbon (TOC), and chemical oxygen demand (COD). Both basins reduced NH3-N, TSS and COD concentrations significantly while NO3--N and PO43- concentrations exhibited a net export. Furthermore, TPC showed greater reductions in NO2--N, TOC and TC concentrations compared to Kyle. Higher TSS removal was observed at TPC due to differences in retention time. A volume reduction of 44% and 64% was observed in TPC and Kyle, respectively. The results of this study demonstrate that stormwater detention basins located over the Edwards Aquifer effectively remove particulate pollutants while also being a potential source of dissolved pollutants such as nitrate. Overall, the results presented here have important implications for operation and maintenance of stormwater basins constructed over recharge zones of Edwards Aquifer.

Reversed Holocene temperature-moisture relationship in the Horn of Africa.

Anthropogenic climate change is predicted to severely impact the global hydrological cycle1, particularly in tropical regions where agriculture-based economies depend on monsoon rainfall2. In the Horn of Africa, more frequent drought conditions in recent decades3,4 contrast with climate models projecting precipitation to increase with rising temperature5. Here we use organic geochemical climate-proxy data from the sediment record of Lake Chala (Kenya and Tanzania) to probe the stability of the link between hydroclimate and temperature over approximately the past 75,000 years, hence encompassing a sufficiently wide range of temperatures to test the 'dry gets drier, wet gets wetter' paradigm6 of anthropogenic climate change in the time domain. We show that the positive relationship between effective moisture and temperature in easternmost Africa during the cooler last glacial period shifted to negative around the onset of the Holocene 11,700 years ago, when the atmospheric carbon dioxide concentration exceeded 250 parts per million and mean annual temperature approached modern-day values. Thus, at that time, the budget between monsoonal precipitation and continental evaporation7 crossed a tipping point such that the positive influence of temperature on evaporation became greater than its positive influence on precipitation. Our results imply that under continued anthropogenic warming, the Horn of Africa will probably experience further drying, and they highlight the need for improved simulation of both dynamic and thermodynamic processes in the tropical hydrological cycle.

Study on characteristics of soil and nutrient losses in Sunjiagou small watershed in cold black soil area.

Investigating the impact of different factors on soil and nutrient loss and suggesting viable control measures is currently a significant concern. This study aims to examine the variations in soil erosion, as well as nitrogen and phosphorus loss, in the core area of the typical hilly diffuse Blackland erosion control. To achieve this, runoff plots with slopes of 3° and 5° were set up in the Sunjiagou sub-basin, located in the upper reaches of the Feiketu River. These plots were subjected to various soil and water conservation measures, along with different levels of vegetation cover. This study aims to analyze the soil and nutrient loss patterns and characteristics in each runoff plot during the natural rainfall events occurring between 2020 and 2022. The results show that soil and nutrient losses are highly significantly and positively correlated with rainfall intensity. The RUSLE model demonstrates a better fit for both cross ridge tillage and bare ground. The loss of nitrogen was much more significant than that of phosphorus, and nitrate nitrogen is the main form of nitrogen loss. Nitrogen loss is mainly dominated by nitrate nitrogen (NN), which is easily soluble in water and constantly migrates with runoff due to the negatively charged NN (NN accounted for 45.2% ~ 81.8% of total nitrogen (TN)). In contrast, the positively charged ammonia nitrogen (AN) is more stable in combination with the soil; large losses only occur under severe sediment erosion. Phosphorus is easily attached to sediment, and the high sediment production leads to a more serious loss of total phosphorus (PP) in the particulate state (PP accounts for 72.7% ~ 96.2% of total phosphorus (TP)). Changing longitudinal ridge tillage to cross ridge tillage and planting vegetation with better water retention and sediment fixation as plant hedges can effectively prevent the loss of soil, runoff, nitrogen, and phosphorus.

Assessing children's potential exposures to harmful metals in tire crumb rubber by accelerated photodegradation weathering.

Whether a tire crumb rubber (TCR) playground would expose children to potentially harmful chemicals such as heavy metals is an open question. The released metals available for pickup on the surface of TCR tiles was studied by accelerated 2-year aging of the TCRs in the NIST-SPHERE (National Institute of Standards and Technology Simulated Photodegradation via High Energy Radiant Exposure). The dermal contact was mimicked by a method of composite surface wiping from US Environmental Protection Agency throughout the weathering process. The surface release of ten most concerned harmful metals (Be, Cr, Cu, As, Se, Cd, Sb, Ba, Tl, Pb) was monitored through the course of aging. The cumulative release of Cu, As, Tl, and Sb reached potentially harmful levels at various times within 3 years, although only Cr was found at a harmful level on the surface of the tiles. Taking the cleansing effect of precipitation or periodic cleansing with rain into account, TCR playgrounds may still be safe for use.

Context and detail interaction network for stereo rain streak and raindrop removal.

Recently stereo image deraining has attracted lots of attention due to its superiority of abundant information from cross views. Exploring interaction information across stereo views is the key to improving the performance of stereo image deraining. In this paper, we design a general coarse-to-fine deraining framework for stereo rain streak and raindrop removal, called CDINet, comprising a stereo rain removal subnet and a stereo detail recovery subnet to restore images progressively. Two types of interaction modules are devised to explore interaction information for rain removal and detail recovery, respectively. Specifically, a global context interaction module is proposed to learn long-range dependencies of stereo images and remove rain by utilizing stereo structural information. A local detail interaction module is designed to model local contextual correlation, which aims at restoring the detail information by using neighborhood information from cross views. Extensive experiments are conducted on the two datasets including a synthetic rain streak removal dataset (RainKITTI) and a real raindrop removal dataset (Stereo Waterdrop), which demonstrates that our method sets new state-of-the-art deraining performance in terms of both quantitative and qualitative metrics with faster speed.

Performance evaluation of a low-cost loess-based filler for bioretention cells.

The sand and gravel fillers used in traditional bioretention cells are expensive and becoming increasingly scarce, and their performance is unstable. It is important to find a stable, reliable, and low-cost alternative filler for bioretention facilities. Using cement as a modified loess filler for bioretention cells is a low-cost and easily obtainable alternative. The loss rate and anti-scouring index of the cement-modified loess (CM) were analyzed under different curing times, cement addition amount, and compactness control conditions. This study found that the stability and strength of the cement-modified loess in water with a density of not less than 1.3 g/cm3, a curing time, of not less than 28 d and a cement addition amount not less than 10% meets the use requirements of the bioretention cell filler. X-ray diffraction and Fourier transform infrared spectroscopy of cement-modified materials with a 10% cement addition and a curing time of 28 days (CM28) and 56 days (CM56). Cement-modified materials with 2% straw and a curing time of 56 days (CS56) showed that the three kinds of modified loess all contain calcium carbonate and that the surface contains hydroxyl and amino functional groups that can effectively remove phosphorus. The specific surface areas of the CM56, CM28, and CS56 samples were 12.53 m2/g, 24.731 m2/g, and 26.252 m2/g, respectively, which are significantly higher than that of sand (0.791 m2/g). At the same time, the adsorption capacity of the ammonia nitrogen and the phosphate that was present in the three modified materials is better than that of sand. CM56, like sand, has rich microbial communities, which can entirely remove nitrate nitrogen in water under anaerobic conditions, indicating that CM56 can be used as an alternative filler for bioretention cells. The production of cement-modified loess is simple and cost-effective, and using modified loess as a filler can reduce the use of stone resources or other on-site materials. Current methods for improving the filler of bioretention cells are mainly based on sand. This experiment used loess to improve the filler. The performance of loess is better than sand, and can completely replace sand as the filler in bioretention cells.

BK-SWMM flood simulation framework is being proposed for urban storm flood modeling based on uncertainty parameter crowdsourcing data from a single functional region.

In recent years, urban flood disasters caused by sudden heavy rains have become increasingly severe, posing a serious threat to urban public infrastructure and the life and property safety of residents. Rapid simulation and prediction of urban rain-flood events can provide timely decision-making reference for urban flood control and disaster reduction. The complex and arduous calibration process of urban rain-flood models has been identified as a major obstacle affecting the efficiency and accuracy of simulation and prediction. This study proposes a multi-scale urban rain-flood model rapid construction method framework, BK-SWMM, focusing on urban rain-flood model parameters and based on the basic architecture of Storm Water Management Model (SWMM). The framework comprises two main components: 1) constructing a SWMM uncertainty parameter sample crowdsourcing dataset and coupling Bayesian Information Criterion (BIC) and K-means clustering machine learning algorithm to discover clustering patterns of SWMM model uncertainty parameters in urban functional areas; 2) coupling BIC and K-means with SWMM model to form BK-SWMM flood simulation framework. The applicability of the proposed framework is validated by modeling three different spatial scales in the study regions based on observed rainfall-runoff data. The research findings indicate that the distribution pattern of uncertainty parameters, such as depression storage, surface Manning coefficient, infiltration rate, and attenuation coefficient. The distribution patterns of these seven parameters in urban functional zones indicate that the values are highest in the Industrial and Commercial Areas (ICA), followed by Residential Areas (RA), and lowest in Public Areas (PA). All three spatial scales' REQ, NSEQ, and RD2 indices were superior to the SWMM and less than 10%, greater than 0.80, and greater than 0.85, respectively. However, when the study area's geographical scale expands, the simulation's accuracy will decline. Further research is required on the scale dependency of urban storm flood models.

Rapid quantification of the surface overflow and underground infiltration in sewer pipes based on computer vision and continuous optimization.

The overloading of the sewer network caused by unwarranted infiltration of stormwater may lead to waterlogging and environmental pollution. The accurate identification of infiltration and surface overflow is essential to predict and reduce these risks. To retrieve the limitations of infiltration estimation and the failure of surface overflow perception using the common stormwater management model (SWMM), a surface overflow and underground infiltration (SOUI) model is proposed to estimate the infiltration and overflow. First, the precipitation, water level of the manhole, surface water depth and images of the overflowing point, and volume at the outfall are collected. Then, the surface waterlogging area is identified based on computer vision to reconstruct the local digital elevation model (DEM) by spatial interpolation, and the relationship between the waterlogging depth, area and volume is established to identify the real-time overflow. Next, a continuous genetic algorithm optimization (CT-GA) model is proposed for the underground sewer system to determine the inflow rapidly. Finally, surface and underground flow estimations are combined to perceive the state of the urban sewer network accurately. The results show that, compared with the common SWMM simulation, the accuracy of the water level simulation is improved by 43.5% during the rainfall period, and the time cost of the computational optimization is reduced by 67.5%. The proposed method can effectively diagnose the operation state and overflow risk of the sewer networks in real time during rainfall seasons.

Global resilience analysis of combined sewer systems under continuous hydrologic simulation.

Managing and reducing combined sewer overflow (CSO) discharges is crucial for enhancing the resilience of combined sewer systems (CSS). However, the absence of a standardised resilience analysis approach poses challenges in developing effective discharge reduction strategies. To address this, our study presents a top-down method that expands the existing Global Resilience Analysis to quantify resilience performance in CSS. This approach establishes a link between threats (e.g., rainfall) and impacts (e.g., CSOs) through continuous and long-term simulation, accommodating various rainfall patterns, including extreme events. We assess CSO discharge impacts from a resilience perspective by introducing eight new metrics. We conducted a case study in Fehraltorf, Switzerland, analysing the performance of three green infrastructure (GI) types (bioretention cells, green roofs, and permeable pavements) over 38 years. The results demonstrated that GI enhanced all resilience indices, with variations observed in individual CSO performance metrics and their system locations. Notably, in Fehraltorf, green roofs emerged as the most effective GI type for improving resilience, while the downstream outfall displayed the highest resilience enhancement. Overall, our proposed method enables a shift from event-based to continuous simulation analysis, providing a standardised approach for resilience assessment. This approach informs the development of strategies for CSO discharge reduction and the enhancement of CSS resilience.

Tipping Bucket Rain Gauges in Hydrological Research: Summary on Measurement Uncertainties, Calibration, and Error Reduction Strategies.

Tipping bucket rain gauges (TBRs) continue to be one of the most widely used pieces of equipment for rainfall monitoring; they are frequently used for the calibration, validation, and downscaling of radar and remote sensing data, due to their major advantages-low cost, simplicity and low-energy consumption. Thus, many works have focused and continue to focus on their main disadvantage-measurement biases (mainly in wind and mechanical underestimations). However, despite arduous scientific effort, calibration methodologies are not frequently implemented by monitoring networks' operators or data users, propagating bias in databases and in the different applications of such data, causing uncertainty in the modeling, management, and forecasting in hydrological research, mainly due to a lack of knowledge. Within this context, this work presents a review of the scientific advances in TBR measurement uncertainties, calibration, and error reduction strategies from a hydrological point of view, by describing different rainfall monitoring techniques, summarizing TBR measurement uncertainties, focusing on calibration and error reduction strategies, discussing the state of the art and providing future perspectives of the technology.

High-resolution precipitation monitoring with a dense seismic nodal array.

Accurate precipitation monitoring is crucial for understanding climate change and rainfall-driven hazards at a local scale. However, the current suite of monitoring approaches, including weather radar and rain gauges, have different insufficiencies such as low spatial and temporal resolution and difficulty in accurately detecting potentially destructive precipitation events such as hailstorms. In this study, we develop an array-based method to monitor rainfall with seismic nodal stations, offering both high spatial and temporal resolution. We analyze seismic records from 1825 densely spaced, high-frequency seismometers in Oklahoma, and identify signals from nine precipitation events that occurred during the one-month station deployment in 2016. After removing anthropogenic noise and Earth structure response, the obtained precipitation spatial pattern mimics the one from a nearby operational weather radar, while offering higher spatial (~ 300 m) and temporal (< 10 s) resolution. We further show the potential of this approach to monitor hail with joint analysis of seismic intensity and independent precipitation rate measurements, and advocate for coordinated seismological-meteorological field campaign design.

Spatio-temporal dengue risk modelling in the south of Thailand: a Bayesian approach to dengue vulnerability.

Background: More than half of the global population is predicted to be living in areas susceptible to dengue transmission with the vast majority in Asia. Dengue fever is of public health concern, particularly in the southern region of Thailand due to favourable environmental factors for its spread. The risk of dengue infection at the population level varies in time and space among sub-populations thus, it is important to study the risk of infection considering spatio-temporal variation. Methods: This study presents a joint spatio-temporal epidemiological model in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation with the CARBayesST package of R software. For this purpose, monthly dengue records by district from 2002 to 2018 from the southern region of Thailand provided by the Ministry of Public Health of Thailand and eight environmental variables were used. Results: Results show that an increasing level of temperature, number of rainy days and sea level pressure are associated with a higher occurrence of dengue fever and consequently higher incidence risk, while an increasing level of wind speed seems to suggest a protective factor. Likewise, we found that the elevated risks of dengue in the immediate future are in the districts of Phipun, Phrom Kili, Lan Saka, Phra Phrom and Chaloem Phakiat. The resulting estimates provide insights into the effects of covariate risk factors, spatio-temporal trends and dengue-related health inequalities at the district level in southern Thailand. Conclusion: Possible implications are discussed considering some anthropogenic factors that could inhibit or enhance dengue occurrence. Risk maps indicated which districts are above and below baseline risk, allowing for the identification of local anomalies and high-risk boundaries. In the event of near future, the threat of elevated disease risk needs to be prevented and controlled considering the factors underlying the spread of mosquitoes in the Southeast Asian region.

Sensors for Biomass Monitoring in Vegetated Green Infrastructure: A Review.

Bioretention cells, or rain gardens, can effectively reduce many contaminants in polluted stormwater through phytoremediation and bioremediation. The vegetated soil structure develops bacterial communities both within the soil and around the vegetation roots that play a significant role in the bioremediative process. Prediction of a bioretention cell's performance and efficacy is essential to the design process, operation, and maintenance throughout the design life of the cell. One of the key hurdles to these important issues and, therefore, to appropriate designs, is the lack of effective and inexpensive devices for monitoring and quantitatively assessing this bioremediative process in the field. This research reviews the available technologies for biomass monitoring and assesses their potential for quantifying bioremediative processes in rain gardens. The methods are discussed based on accuracy and calibration requirements, potential for use in situ, in real-time, and for characterizing biofilm formation in media that undergoes large fluctuations in nutrient supply. The methods discussed are microscopical, piezoelectric, fiber-optic, thermometric, and electrochemical. Microscopical methods are precluded from field use but would be essential to the calibration and verification of any field-based sensor. Piezoelectric, fiber-optic, thermometric, and some of the electrochemical-based methods reviewed come with limitations by way of support mechanisms or insufficient detection limits. The impedance-based electrochemical method shows the most promise for applications in rain gardens, and it is supported by microscopical methods for calibration and validation.

Removal effect of typical pollutants from stormwater runoff in ecological ditches.

Ecological ditches are a typical ecological facility for controlling road stormwater runoff pollution; they mainly remove harmful pollutants from runoff through plant absorption, retention and sedimentation, ecological adsorption, and microbial action. In this paper, according to the transport form of rainwater in the ditches, the removal effects of two different types of ditches on nitrogen, phosphorus, heavy metals, and other pollutants were simulated under three conditions of rainfall, slow flow, and still water, respectively, and their operating characteristics were analyzed. The results showed that the removal rate of TN in the two ecological ditches under slow flow conditions showed a downward trend as a whole with the increase of hydraulic load, and the suitable hydraulic load for TN removal should be selected as 0.3 m3/(m2 day). Under the simulated rainfall conditions, the TN removal rates of no. 1 and no. 2 ditches were 26.1-37.2% and 24.9 ~ 52.5%, respectively, and the TP removal rates were 44.6 ~ 63.3% and 36.1 ~ 62.1%. After 19.4 h and 22.1 h in the static state, the TP concentration in no. 1 ditch and no. 2 ditch reached the surface V water standard, and the average removal rate of TP was 74.7% and 53.7%, respectively. This paper provides a reference for selecting suitable parameters and optimizing the operational performance of ecological ditches to reduce runoff pollutants more effectively.

Effects of rainfall characteristics and sugarcane growth stage on soil and nitrogen losses.

High intensity rainfall in southern China has led to soil erosion on sloping farmland, causing serious ecological and environmental problems. But how the interaction of rainfall factors and growth stages influence soil erosion and nitrogen loss on sugarcane-cultivated slope under natural rainfall have not been studied considerably. This study concentrated on the in situ runoff plot observation test. Surface runoff, soil erosion, and nitrogen loss under individual natural rainfall events during the different sugarcane growth stages (seedling stage (SS), tillering stage (TS), elongation stage (ES)) from May to September in 2019 and 2020 were recorded and measured. The effects of rainfall factors (intensity and amount) on soil erosion and nitrogen loss were quantified by path analysis. The influence of rainfall factors and sugarcane planting on soil erosion and nitrogen loss was analyzed. Surface runoff, soil erosion, and nitrogen loss on sugarcane-cultivated slope were 4354.1 m3/ha, 155.4 t/ha, and 25.87 kg/ha during 2019 to 2020, and were mainly concentrated in SS, accounting for 67.2%, 86.9%, and 81.9% of total surface runoff, soil erosion, and nitrogen loss, respectively. Nitrogen losses were mainly concentrated in surface runoff, accounting for 76.1% of total nitrogen loss, and the main form in surface runoff was nitrate nitrogen (NO3--N, 92.9%). Under individual rainfall events, surface runoff, soil erosion, and nitrogen loss changed with the changing of rainfall characteristics and sugarcane growth. Surface runoff and nitrogen loss were obviously affected by rainfall characteristics, while the soil erosion and nitrogen loss were affected by both rainfall characteristics and sugarcane growth stages. Path analysis indicated that maximum rainfall intensities at 15 min (I15) and 60 min (I60) were most significant to the production of surface runoff and soil erosion with direct path coefficients of 1.19 and 1.23, respectively. NO3--N and ammonium nitrogen (NH4+-N) losses in surface runoff were mostly influenced by maximum rainfall intensity at 30 min (I30) and I15 with direct path coefficients of 0.89 and 3.08, respectively. NO3--N and NH4+-N losses in sediment yield were mostly influenced by I15 and rainfall amount, and the direct path coefficients were 1.61 and 3.39, respectively. The main stage of soil and nitrogen loss was seedling stage, while the significant factors of rainfall characteristics affecting surface runoff, soil erosion, and nitrogen loss were quite different. The results provide theoretical support for soil erosion and quantitative rainfall erosion factors of sugarcane-cultivated slope in southern China.

Using SWMM for emergency response planning: A case study evaluating biological agent transport under various rainfall scenarios and urban surfaces.

To assist in emergency preparedness for a biological agent terrorist attack or accidental pathogen release, potential contaminant levels and migration pathways of spores spread by urban stormwater were evaluated using a Storm Water Management Model (SWMM) of U.S. Coast Guard Base Elizabeth City, North Carolina. The high temporal-spatial resolution SWMM model was built using spore concentrations in stormwater runoff from asphalt, grass, and concrete collected from a point-scale field study. The subsequent modeled contamination scenarios included a notional plume release and point releases mimicking the field study under three rainfall conditions. The rainfall scenarios included a 6-hour natural rainfall event on Dec. 8, 2021 and two design storms (2-year and 100-year events). The observed spore concentrations from asphalt and concrete from the actual field experiment were applied to calibrate the washoff parameters in the SWMM model, using an exponential washoff function. The calibrated washoff coefficient (c1) and exponent (c2) were 0.01 and 1.00 for asphalt, 0.05 and 1.45 for grass, and 2.45 and 1.00 for concrete, respectively. The calibrated SWMM model simulated spore concentrations in runoff at times and magnitudes similar to the field study data. In the point release modeled scenario, the concrete surface generated 55.6% higher average spore concentrations than asphalt. Similarly, in the field experiment, a 175% (p < 0.05) higher average spore concentration in surface runoff was observed from concrete than from asphalt. This study demonstrates how SWMM may be used to evaluate spore washoff from urban surfaces under different precipitation amounts, intensities, and durations, and how visualized spatial migration pathways in stormwater runoff may be used for emergency planning and remediation.