Reduction in precipitation amount, precipitation events, and nitrogen addition change ecosystem carbon fluxes differently in a semi-arid grassland

The increases in extent and frequency of extreme drought events and increased nitrogen (N) deposition due to global change are expected to have profound impacts on carbon cycling in semi-arid grasslands. However, how ecosystem CO2 exchange processes respond to different drought scenarios individually and interactively with N addition remains uncertain. In this study, we experimentally explored the effects of different drought scenarios (early season extreme drought, 50 % reduction in precipitation amount, and 50 % reduction in precipitation events) and N addition on net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP) over three growing seasons (2019-2021) in a semi-arid grassland in northern China. The growing-season ecosystem carbon fluxes in response to drought and N addition were influenced by inter-annual precipitation changes, with 2019 as a normal precipitation year, and 2020 and 2021 as wet years. Early season extreme drought stimulated NEE by reducing ER. 50 % reduction in precipitation amount decreased ER and GEP consistently in three years, but only significantly suppressed NEE in 2019. 50 % reduction in precipitation events stimulated NEE. Nitrogen addition stimulated NEE, ER, and GEP, but only significantly in wet years. The structural equation models showed that changes in carbon fluxes were regulated by soil moisture, soil temperature, microbial biomass nitrogen (MBN), and the key plant functional traits. Decreased community-weighted means of specific leaf area (CWMSLA) was closely related to the reduced ER and GEP under early season extreme drought and 50 % reduction in precipitation amount. While increased community-weighted means of plant height (CWMPH) largely accounted for the stimulated ER and GEP under 50 % reduction in precipitation events. Our study stresses the distinct effects of different drought scenarios and N enrichment on carbon fluxes, and highlights the importance of soil traits and the key plant traits in determining carbon exchange in this water-limited ecosystem.

Toxicity of urban stormwater on Chlorella pyrenoidosa: Implications for reuse safety

Urban stormwater is an alternative water source used to mitigate water resource shortages, and ensuring the safety of stormwater reuse is essential. An in-depth understanding of both individual pollutant concentrations/loads in stormwater and holistic stormwater quality can be used to comprehensively evaluate how safely stormwater can be reused. The toxicity test takes all pollutants present in water samples into account, and the results reflect the integrated effect of these pollutants. In this study, the influence of urban stormwater sourced from different land uses on microalgae (Chlorella pyrenoidosa) and the possible toxicity mechanisms were investigated. The results showed that urban stormwater, particularly residential road stormwater, significantly inhibited microalgal growth. The chlorophyll contents of microalgae exposed to residential road stormwater were relatively lower, while the corresponding values were relatively higher for microalgae exposed to grassland road stormwater. Additionally, the antioxidant-related metabolism of microalgae could be dysregulated due to exposure to urban stormwater. A possible toxicity mechanism is that urban stormwater influences metabolic pathways related to chlorophyll synthesis and further hinders photosynthesis and hence microalgal growth. To resist oxidative stress and maintain regular microalgal cell activities, the ribosome metabolism pathway was upregulated. The research results contribute to elucidating the toxicity effects of urban stormwater and hence provide useful insight for ensuring the safety of stormwater reuse. It is also worth noting that the study outcomes can only represent the influence of land use on stormwater toxicity, while the impacts of other factors (particularly rainfall-runoff characteristics) have not been considered. Therefore, the consideration of all influential factors of stormwater is strongly recommended to generate more robust results in the future and provide more effective guidance for real practices related to stormwater reuse safety.

Performance of wood waste biochar and food waste compost in a pilot-scale sustainable drainage system for stormwater treatment

Sustainable drainage system (SuDS) for stormwater reclamation has the potential to alleviate the water scarcity and environmental pollution issues. Laboratory studies have demonstrated that the capacity of SuDS to treat stormwater can be improved by integrating biochar and compost in the filter media, whereas their performance in scaled-up applications is less reported. This study examines the effectiveness of a pilot-scale SuDS, bioswale followed by bioretention, amended with wood waste biochar (1, 2, and 4 wt.%) and food waste compost (2 and 4 wt.%) to simultaneously remove multiple pollutants including nutrients, heavy metals, and trace organics from the simulated stormwater. Our results confirmed that SuDS modified with both biochar (2 wt.%) and compost (2 wt.%) displayed superior water quality improvement. The system exhibited high removal efficiency (> 70%) for total phosphorus and major metal species including Ni, Pb, Cd, Cr, Cu, and Zn. Total suspended solids concentration was approaching the detection limit in the effluent, thereby confirming its capability to reduce turbidity and particle-associated pollutants from stormwater. Co-application of biochar and compost also moderately immobilized trace organic contaminants such as 2,4-dichlorophenoxyacetic acid, diuron, and atrazine at field-relevant concentrations. Moreover, the soil amendments amplified the activities of enzymes including β-D-cellobiosidase and urease, suggesting that the improved soil conditions and health of microbial communities could possibly increase phyto and bioremediation of contaminants accumulated in the filter media. Overall, our pilot-scale demonstration confirmed that the co-application of biochar and compost in SuDS can provide a variety of benefits for soil/plant health and water quality.

Biochar and vegetation effects on discharge water quality from organic-substrate green roofs

Green roofs have been increasingly used to improve stormwater management, but poor vegetation performance on roof systems, varying with vegetation type, can degrade discharge quality. Biochar has been suggested as an effective substrate additive for green roofs to improve plant performance and discharge quality. However, research on the effects of biochar and vegetation on discharge quality in the long term is lacking and the underlying mechanisms involved are unclear. We examined the effects of biochar amendment and vegetation on discharge quality on organic-substrate green roofs with pre-grown sedum mats and direct-seeded native plants for three years and investigated the key factors influencing discharge quality. Sedum mats reduced the leaching of nutrients and particulate matter by 6-64% relative to native plants, largely due to the higher initial vegetation cover of the former. Biochar addition to sedum mat green roofs resulted in the best integrated water quality due to enhanced plant cover and sorption effects. Structural equation modeling revealed that nutrient leaching was primarily influenced by rainfall depth, time, vegetation cover, and substrate pH. Although biochar-amended sedum mats showed better discharge quality from organic-substrate green roofs, additional ecosystem services may be provided by native plants, suggesting future research to optimize plant composition and cover and biochar properties for sustainable green roofs.

Survival and rapid resuscitation permit limited productivity in desert microbial communities

Microbial activity in drylands tends to be confined to rare and short periods of rain. Rapid growth should be key to the maintenance of ecosystem processes in such narrow activity windows, if desiccation and rehydration cause widespread cell death due to osmotic stress. Here, simulating rain with 2H2O followed by single-cell NanoSIMS, we show that biocrust microbial communities in the Negev Desert are characterized by limited productivity, with median replication times of 6 to 19 days and restricted number of days allowing growth. Genome-resolved metatranscriptomics reveals that nearly all microbial populations resuscitate within minutes after simulated rain, independent of taxonomy, and invest their activity into repair and energy generation. Together, our data reveal a community that makes optimal use of short activity phases by fast and universal resuscitation enabling the maintenance of key ecosystem functions. We conclude that desert biocrust communities are highly adapted to surviving rapid changes in soil moisture and solute concentrations, resulting in high persistence that balances limited productivity.

Removal and release of microplastics and other environmental pollutants during the start-up of bioretention filters treating stormwater

Untreated stormwater is a major source of microplastics, organic pollutants, metals, and nutrients in urban water courses. The aim of this study was to improve the knowledge about the start-up periods of bioretention filters. A rain garden pilot facility with 13 bioretention filters was constructed and stormwater from a highway and adjacent impervious surfaces was used for irrigation for ∼12 weeks. Selected plants (Armeria maritima, Hippophae rhamnoides, Juncus effusus, and Festuca rubra) was planted in ten filters. Stormwater percolated through the filters containing waste-to-energy bottom ash, biochar, or Sphagnum peat, mixed with sandy loam. Influent and effluent samples were taken to evaluate removal of the above-mentioned pollutants. All filters efficiently removed microplastics >10 µm, organic pollutants, and most metals. Copper leached from all filters initially but was significantly reduced in the biochar filters at the end of the period, while the other filters showed a declining trend. All filters leached nutrients initially, but concentrations decreased over time, and the biochar filters had efficiently reduced nitrogen after a few weeks. To conclude, all the filters effectively removed pollutants during the start-up period. Before being recommended for full-scale applications, the functionality of the filters after a longer period of operation should be evaluated.

Characterization of road-deposited sediment wash-off and accurate splitting of initial runoff pollution in heterogeneous urban spaces

Particulate materials arising from road-deposited sediments (RDS) are an essential target for the control and management of surface runoff pollution. However, the heterogeneity of urban spaces hinders the identification and quantification of particulate pollution, which is challenging when formulating precise control measures. To elucidate the factors that drive particulate pollution in heterogeneous urban spaces, the accumulation of RDS on dry days and the total suspended solids during six natural rainfall events were investigated across three urban-rural spatial units (central urban, central suburban, and remote suburban). The underlying surface type (asphalt or cement roads) and particle size composition jointly determined the spatial heterogeneity in the static accumulation and dynamic output loads of RDS during rainfall. These two factors explained 59.6% and 18.9% of the spatial heterogeneity, respectively, according to principal component analysis. A novel CPSI exponential wash-off equation that incorporates particle size composition and underlying surface type was applied. It precisely described the spatial heterogeneity of RDS wash-off loads, the estimated values exhibiting event mean concentration errors of 10.8-18.2%. When coupled with the M(V) curve, this CPSI exponential wash-off equation more precisely split the initial volume of runoff: a lower total volume (17.6-38.0%) was shown to carry a higher proportion of the load (70.0-93.7%) compared to the traditional coupled exponential wash-off equation (volume: 31.6-49.0%, load: 37-90%). This study provides a new approach to characterizing RDS wash-off processes and splitting initial runoff in heterogeneous spaces.

A typology of subseasonal rainfall evolution during the southern Niger monsoon

Niger is highly vulnerable to rainfall variability, often with adverse socioeconomic consequences. This study examined observed subseasonal rainfall variability during Niger's monsoon season (May to September). Using k-means clustering of dekadal (ten-day) rainfall, a typology was developed for the annual evolution of the monsoon season. Year-to-year rainfall variability for each of the first few dekads of the season is modest, but the middle, or peak of the rainy season demonstrates large interannual variability. Clustering analysis of annual timeseries for each dekad of the season revealed two types of monsoon progression. The distinction between the two types is strongly dependent on differences during the latter half of the season. For the first and third ten-day periods in August, and the first ten days in September, the two groups of years are more distinct. These results imply that while reliable prediction of the timing of anomalous onsets will be challenging, due to the relatively narrow range of uncertainty historically, there are opportunities for further exploration of dynamic and or statistical predictors or precursors using this typology that could potentially provide better information for decision-makers, especially with respect to agriculture.

Exploring the adoption of water quality trading as an alternative stormwater regulatory compliance strategy for land development projects: A case study for Roanoke, Virginia

Urban stormwater runoff is a significant source of nutrient pollution that is very costly to treat. Water quality trading (WQT) is a market-based strategy that can be used to lower the costs associated with meeting stormwater quality regulations. While many WQT programs have experienced low participation, Virginia's program has seen high participation due to the inclusion of land developers and other regulated stormwater dischargers. However, the extent to which WQT is used as a compliance option by regulated stormwater dischargers is not well understood, particularly when compared with the adoption of traditional compliance options. To address this knowledge gap, we collated a novel dataset comprising site characteristics and stormwater compliance methods for all development projects in the City of Roanoke, Virginia from December 2015 to March 2022. We analyzed this dataset to characterize the adoption of nutrient offset credits and other compliance methods being used, including best management practices (BMPs) and improved land covers associated with reduced nutrient export. Results show that credits are the preferred compliance option in Roanoke and were used as the only treatment compliance method for 59% of projects with treatment requirements. Projects using credits corresponded with a lower median disturbed area (1.36 acres) and lower median nutrient load reduction requirement (0.69 pounds of total phosphorus per year) compared with other compliance methods. Furthermore, we found that 58% of the projects that used credits achieved stormwater quantity compliance using methods other than implementing stormwater control devices. By mapping buyers and sellers of credits, we found that all credit sellers are downstream of the development projects. We discuss how this downstream trading could be a cause for concern, as part of a larger discussion of the advantages of tracking stormwater compliance methods, drawing on Roanoke as a case study.

Coupling simulation of pipeline nodes - Storage tank linkage in urban high-density built-up areas using optimization model

Climate change and urbanization contribute to the increased frequency of short-duration intense rainstorms. Traditional solutions often involve multiple scenarios for cost-effectiveness comparison, neglecting the rationality of placement conditions. The effective coupling and coordination of the location, number, size, and cost of storage tanks are crucial to addressing this issue. A three-phase approach is proposed to enhance the dynamic link between drainage pipeline and storage tanks in urban high-density built-up areas, integrating Python language, SWMM, the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-III), and the Analytic Hierarchy Process (AHP) methods. In the first stage, each node within the pipeline network is considered as a potential storage tank location. In the second stage, factors such as the length and diameter of the upstream connecting pipeline, as well as the suitability of the storage tank location, are assessed. In the third stage, the length and diameter of the downstream connecting pipeline node are evaluated. The results show that the 90 overflow nodes (overflow time >0.5h) have been cleared using the three-phase approach with a 50a (duration = 3h) return period as the rainfall scenario, which meets the flooding limitations. After the completion of the three-phase method configuration, the total overflow and SS loads were reduced by 96.45% and 49.30%, respectively, compared to the status quo conditions. These two indicators have decreased by 48.16 and 9.05%, respectively, compared to the first phase (the traditional method of only replacing all overflow nodes with storage tanks). The proposed framework enables decision-makers to evaluate the acceptability and reliability of the optimal management plan, taking into account their preferences and uncertainties.

Microbial communities exhibit distinct diversities and assembly mechanisms in rainwater and tap-water storage systems

Roof-harvested rainwater stored for potable and nonpotable usages represent a clean and sustainable water supply resource. However, the microbial dynamics and mechanisms of community assembly in long-termed operated rainwater storage systems remain elusive. In this study, characteristics of microbial communities in different habitats were systematically compared within rainwater and tap-water simulated storage systems (SWSSs) constructed with different tank materials (PVC, stainless steel and cement). Distinct microbial communities were observed between rainwater and tap-water SWSSs for both water and biofilm samples (ANOSIM, p < 0.05), with lower diversity indexes noted in rainwater samples. Notably, a divergent potential pathogen profile was observed between rainwater and tap-water SWSSs, with higher relative abundances of potential pathogens noted in rainwater SWSSs. Moreover, tank materials had a notable impact on microbial communities in rainwater SWSSs (ANOSIM, p < 0.05), rather than tap-water SWSSs, illustrating the distinct interplay between water chemistry and engineering factors in shaping the SWSS microbiomes. Deterministic processes contributed predominantly to the microbial community assembly in cement rainwater SWSSs and all tap-water SWSSs, which might be ascribed to the high pH levels in cement rainwater SWSSs and low-nutrient levels in all tap-water SWSSs, respectively. However, microbial communities in the PVC and stainless-steel rainwater SWSSs were mainly driven by stochastic processes. Overall, the results provided insights to the distinct microbial assembly mechanisms and potential health risks in stored roof-harvested rainwater, highlighting the importance of developing tailored microbial management strategies for the storage and utilization of rainwater.

Do baseline assumptions alter the efficacy of green stormwater infrastructure to reduce combined sewer overflows?

Green stormwater infrastructure (GSI) is growing in popularity to reduce combined sewer overflows (CSOs) and hydrologic simulation models are a tool to assess their reduction potential. Given the numerous and interacting water flows that contribute to CSOs, such as evapotranspiration (ET) and groundwater (GW), these models should ideally account for them. However, due to the complexity, simplified models are often used, and it is currently unknown how these assumptions affect estimates of CSOs, GSI effectiveness, and ultimately planning guidance. This study evaluates the effect on estimates of CSOs and GSI effectiveness when different flows and hydrologic processes are neglected. We modified an existing EPA SWMM model of a combined sewer system in Switzerland to include ET, GW, and upstream inflows. Historical rainfall data over 30 years are used to assess volume and duration of CSOs with and without three types of GSI (bioretention basins, permeable pavements and green roofs). Results demonstrate that neglect of certain flows in modelling can alter CSO volumes from -15 % to 40 %. GSI effectiveness also varies considerably, resulting in differences in simulated percent of CSO volume reduced from 8 % to 35 %, depending on the GSI type and modeled flow or process. Representation of GW within models is particularly crucial when infiltrating GSI are present, as CSOs could increase in certain subcatchments due to higher GW levels from increased infiltration. When basing GSI planning decisions on modeled estimates of CSOs, all relevant hydrologic processes should be included to the extent possible, and uncertainty and assumptions should always be considered.

Temporal variations in micropollutant inlet concentrations matter when planning the design and compliance assessment of stormwater control measures

Stormwater Control Measures (SCMs) contribute to reducing micropollutant emissions from separate sewer systems. SCM planning and design are often performed by looking at the hydrological performance. Assessment of pollutant removal and the ability to comply with discharge concentration limits is often simplified due to a lack of data and limited monitoring resources. This study analyses the impact of using different time resolutions of input stormwater concentrations when assessing the compliance of SCMs against water quality standards. The behaviour of three indicator micropollutants (MP - Copper, Diuron, Benzo[a]pyrene) was assessed in four SCM archetypes, which were defined to represent typical SCM removal processes. High resolution MP data were extrapolated by using high resolution (2 min) measurements of TSS over a long period (343 events). The compliance assessment showed that high resolution input concentrations can result in a different level of compliance with water quality standards, especially when discharged concentrations are close to the limit values. This study underlines the importance of considering the high temporal variability of stormwater micropollutants when planning and designing SCMs to identify the most effective solutions for stormwater pollution management and to ensure a thorough consideration of all the environmental implications.

Bioretention Design Modifications Increase the Simulated Capture of Hydrophobic and Hydrophilic Trace Organic Compounds

Stormwater rapidly moves trace organic contaminants (TrOCs) from the built environment to the aquatic environment. Bioretention cells reduce loadings of some TrOCs, but they struggle with hydrophilic compounds. Herein, we assessed the potential to enhance TrOC removal via changes in bioretention system design by simulating the fate of seven high-priority stormwater TrOCs (e.g., PFOA, 6PPD-quinone, PAHs) with log KOC values between -1.5 and 6.74 in a bioretention cell. We evaluated eight design and management interventions for three illustrative use cases representing a highway, a residential area, and an airport. We suggest two metrics of performance: mass advected to the sewer network, which poses an acute risk to aquatic ecosystems, and total mass advected from the system, which poses a longer-term risk for persistent compounds. The optimized designs for each use case reduced effluent loadings of all but the most polar compound (PFOA) to <5% of influent mass. Our results suggest that having the largest possible system area allowed bioretention systems to provide benefits during larger events, which improved performance for all compounds. To improve performance for the most hydrophilic TrOCs, an amendment like biochar was necessary; field-scale research is needed to confirm this result. Our results showed that changing the design of bioretention systems can allow them to effectively capture TrOCs with a wide range of physicochemical properties, protecting human health and aquatic species from chemical impacts.

Responses of runoff and sediment yield to slope length and gravel content of Lou soil engineering accumulation slope in Guanzhong region, Northwest China

With the economic development, a large number of engineering accumulation bodies with Lou soil as the main soil type were produced in Guanzhong area, Northwest China. We examined the characteristics of runoff and sediment yield of Lou soil accumulation bodies with earth (gravel content 0%) and earth-rock (gravel content 30%) under different rainfall intensities (1.0, 1.5, 2.0, 2.5 mm·min-1) and different slope lengths (3, 5, 6.5, 12 m) by the simulating rainfall method. The results showed that runoff rate was relatively stable when rainfall intensity was 1.0-1.5 mm·min-1, while runoff rate fluctuated obviously when rainfall intensity was 2.0-2.5 mm·min-1. The average runoff rate varied significantly across different rainfall intensities on the same slopes, and the difference of average runoff rate of the two slopes was significantly increased with rainfall intensity. Under the same rainfall intensity, the difference in runoff rate between the slope lengths of the earth-rock slope was more obvious than that of the earth slope. When the slope length was 3-6.5 m, flow velocity increased rapidly at first and then increased slowly or tended to be stable. When the slope length was 12 m, flow velocity increased significantly. In general, with the increases of rainfall intensity, inhibition effect of gravel on the average flow velocity was enhanced. When rainfall intensity was 2.5 mm·min-1, the maximum reduction in the average flow velocity of earth-rock slope was 61.5% lower than that of earth slope. When rainfall intensity was less than 2.0 mm·min-1, sediment yield rate showed a trend of gradual decline or stable change, while that under the other rainfall intensities showed a trend of rapid decline and then fluctuated sharply. The greater the rainfall intensity, the more obvious the fluctuation. There was a significant positive correlation between the average sediment yield rate and runoff parameters, with the runoff rate showing the best fitting effect. Among the factors, slope length had the highest contribution to runoff velocity and rainfall erosion, which was 51.8% and 35.5%, respectively. This study can provide scientific basis for soil and water erosion control of engineering accumulation in Lou soil areas.

Climate change impacts on rainfall intensity-duration-frequency curves in local scale catchments

The increasing intensity and frequency of rainfall events, a critical aspect of climate change, pose significant challenges in the construction of intensity-duration-frequency (IDF) curves for climate projection. These curves are crucial for infrastructure development, but the non-stationarity of extreme rainfall raises concerns about their adequacy under future climate conditions. This research addresses these challenges by investigating the reasons behind the IPCC climate report's evidence about the validity that rainfall follows the Clausius-Clapeyron (CC) relationship, which suggests a 7% increase in precipitation per 1 °C increase in temperature. Our study provides guidelines for adjusting IDF curves in the future, considering both current and future climates. We calculate extreme precipitation changes and scaling factors for small urban catchments in Barranquilla, Colombia, a tropical region, using the bootstrapping method. This reveals the occurrence of a sub-CC relationship, suggesting that the generalized 7% figure may not be universally applicable. In contrast, our comparative analysis with Illinois, USA, an inland city in the north temperate zone, shows adherence to the CC relationship. This emphasizes the need for local parameter calculations rather than relying solely on the generalized 7% figure.

HYADES - A Global Archive of Annual Maxima Daily Precipitation

Time series of annual maxima daily precipitation are crucial for understanding extreme precipitation behavior and its shifts toward nonstationarity with global warming. Extreme precipitation insight assists hydraulic infrastructure design, water resource management, natural hazard prevention, and climate change adaptation. However, not even a third of the records are of sufficient length, and the number of active stations keeps decreasing. Herein, we present HYADES: archive of yearly maxima of daily precipitation records, a global dataset derived from the Global Historical Climatology Network database of daily records (GHCN-Daily). The HYADES dataset contains records from 39 206 stations (heterogeneously distributed worldwide) with record lengths varying from 16 to 200 years between 1805 and 2023. HYADES was extracted through a methodology designed to accurately capture the true maxima even in the presence of missing values within the records. The method's thresholds were determined and evaluated through Monte Carlo simulations. Our approach demonstrates a 96.73% success rate in detecting the true maxima while preserving time series statistical properties of interest (L-moments and temporal monotonic trend).

Effect of vegetation treatment and water stress on evapotranspiration in bioretention systems

Evapotranspiration is a key hydrological process for reducing stormwater runoff in bioretention systems, regardless of their physical configuration. Understanding the volumes of stormwater that can be returned to the atmosphere via evapotranspiration is, therefore, a key consideration in the design of any bioretention system. This study establishes the evapotranspiration dynamics of three common, structurally different, bioretention vegetation treatments (an Amenity Grass mix, and mono-cultures of Deschampsia cespitosa and Iris sibirica) compared with an un-vegetated control using lab-scale column experiments. Via continuous mass and moisture loss data, observed evapotranspiration rates were compared with those predicted by the FAO-56 Penman-Monteith model for five 14-day dry periods during Spring 2021, Summer 2021, and Spring 2022. Soil moisture reductions over the 14-day trials led to reduced rates of evapotranspiration. This necessitated the use of a soil moisture extraction function alongside a crop coefficient to represent actual evapotranspiration from FAO-56 Penman-Monteith reference evapotranspiration estimates. Crop coefficients (Kc) varied between 0.65 and 2.91, with a value of 1.0 identified as a recommended default value in the absence of treatment-specific empirical data. A continuous hydrological model with Kc=1.0 and a loading ratio of 10:1 showed that evapotranspiration could account for between 1 and 12% of the annual water budget for a bioretention system located in the UK and Ireland, increasing to a maximum of 35% when using the highest Kc observed (2.91).

Efficiency of fluralaner pour-on in different strategic control protocols against Rhipicephalus microplus on Brangus cattle in a tropical area

BACKGROUND

The occurrence of higher winter temperatures in Brazilian areas with tropical and highland climates may result in a fifth peak of tick populations during winter in addition to the four generations previously described. Therefore, a strategic control protocol was developed with treatments in two seasons with the objective of controlling the generations of ticks that occur in spring/summer and those that occur in autumn/winter.

METHODS

The study was conducted in Mato Grosso do Sul, Brazil, from the beginning of the rainy season, November 2020, to October 2021. In a randomized block design, 36 calves were distributed into three groups: (i) negative control; (ii) traditional strategic control in one season (SC1S), at the beginning of the rainy season; and (iii) strategic control in two seasons (SC2S), at the beginning and end of the rainy season. The SC1S strategic control group was treated on day 0, November 2020, and twice more with intervals of 42 days. The SC2S group received three more treatments beginning on day 182, May 2021, with intervals of 42 days. All treatments consisted of 5% fluralaner (Exzolt® 5%) delivered via a pour-on dose of 1 mL/20 kg body weight. Counts of semi-engorged female ticks were performed on day 3 and every 14 days thereafter, and the animals were weighed at the same time.

RESULTS

Fluralaner showed a mean efficacy of more than 95% up to day 294. The two treated groups showed a decrease (P < 0.05) in the average number of ticks on day 3. In the SC2S group, the means were close or equal to zero throughout the study, while in the SC1S group, the means did not differ (P > 0.05) from those of the control group from day 231 onward. The final mean weight gain of each group was 76.40 kg, 98.63 kg, and 115.38 kg for the control, SC1S, and SC2S groups, respectively, differing (P < 0.05) from each other.

CONCLUSIONS

Therefore, three applications of fluralaner, with one application every 42 days from the beginning of the rainy season in the middle spring, resulted in effective tick control for 224 days. When three additional treatments were given in autumn/winter with intervals of 42 days between applications, tick counts were reduced throughout the year. This strategic control approach may be indicated in years with climatic conditions that allow that population peaks are expected to occur in the autumn/winter period.

Resilience of stormwater biofilters following the deposition of wildfire residues: Implication on downstream water quality management in wildfire-prone regions

Stormwater treatment systems such as biofilters could intercept and remove pollutants from contaminated runoff in wildfire-affected areas, ensuring the protection of water quality downstream. However, the deposition of wildfire residues such as ash and black carbon onto biofilters could potentially impair their stormwater treatment functions. Yet, whether and how wildfire residue deposition could affect biofilter functions is unknown. This study examines the impact of wildfire residue deposition on biofilter infiltration and pollutant removal capacities. Exposure to wildfire residues decreased the infiltration capacity based on the amount of wildfire deposited. Wildfire residues accumulated at the top layer of the biofilter, forming a cake layer, but scraping this layer restored the infiltration capacity. While the deposition of wildfire residues slightly changed the pore water geochemistry, it did not significantly alter the removal of metals and E. coli. Although wildfire residues leached some metals into pore water within the simulated root zone, the leached metals were effectively removed by the compost present in the filter media. Collectively, these results indicate that biofilters downstream of wildfire-prone areas could remain resilient or functional and protect downstream water quality if deposited ash is periodically scraped to restore any loss of infiltration capacity following wildfire residue deposition.

Wetness severity increases abrupt shifts in ecosystem functioning in arid savannas

The accelerating pace of climate change has led to unprecedented shifts in surface temperature and precipitation patterns worldwide, with African savannas being among the most vulnerable regions. Understanding the impacts of these extreme changes on ecosystem health, functioning and stability is crucial. This paper focuses on the detection of breakpoints, indicative of shifts in ecosystem functioning, while also determining relevant ecosystem characteristics and climatic drivers that increase susceptibility to these shifts within the semi-arid to arid savanna biome. Utilising a remote sensing change detection approach and rain use efficiency (RaUE) as a proxy for ecosystem functioning, spatial and temporal patterns of breakpoints in the savanna biome were identified. We then employed a novel combination of survival analysis and remote sensing time series analysis to compare ecosystem characteristics and climatic drivers in areas experiencing breakpoints versus areas with stable ecosystem functioning. Key ecosystem factors increasing savanna breakpoint susceptibility were identified, namely higher soil sand content, flatter terrain and a cooler long-term mean temperature during the wet summer season. Moreover, the primary driver of changes in ecosystem functioning in arid savannas, as opposed to wetter tropical savannas, was found to be the increased frequency and severity of rainfall events, rather than drought pressures. This research highlights the importance of incorporating wetness severity metrics alongside drought metrics to comprehensively understand climate-ecosystem interactions leading to abrupt shifts in ecosystem functioning in arid biomes. The findings also emphasise the need to consider the underlying ecosystem characteristics, including soil, topography and vegetation composition, in assessing ecosystem responses to climate change. While this research primarily concentrated on the southern African savanna as a case study, the methodological robustness of this approach enables its application to diverse arid and semi-arid biomes for the assessment of climate-ecosystem interactions that contribute to abrupt shifts.

Possibility of using the STORAGE rainfall generator model in the flood analyses in urban areas

In this investigation, we evaluated the applicability of the Stochastic Rainfall Generator (STORAGE) as a data source for deriving design hydrographs in urban catchments. This assessment involved a comparison with design rainfall calculated using Intensity-Duration-Frequency (IDF) curves derived from observed time-series data. The resulting design rainfall values from both methods were incorporated into a hydrodynamic model of the storm sewer network. To simulate peak discharge and flood areas, the Storm Water Management Model (SWMM) program was employed in conjunction with SCALGO. Our findings indicate that design rainfall values obtained from the STORAGE model exceeded those derived from the observed time-series, with a more pronounced difference for shorter rainfall durations. Simulations further revealed that peak runoff disparities between the two approaches were most evident at a 0.10 probability of exceedance compared to a 0.01 probability. Hydrodynamic simulations demonstrated that the flooding volume induced by design rainfall based on the STORAGE model surpassed that resulting from observed rainfall. Across all events, both the flooding volume and area from STORAGE were consistently greater than those derived from IDF curves. The integration of the SWMM model with the SCALGO application introduced a novel functionality for dynamic visualization of flooding, offering valuable insights for effective flood management in urban areas.

Contribution of rooftop rainwater harvesting to climate adaptation in the city of Hannover: Water quality and health issues of rainwater storage in cisterns and ponds

Rooftop rainwater harvesting systems and blue-green infrastructure are becoming important resilience alternatives for urban climate adaptation. This study sheds light on the largely unreported physicochemical and microbiological quality of private roof-harvested rainwater (RHRW). We aimed to identify the physicochemical and microbiological characteristics of RHRW, explore potential correlations between them and assess probable health risks associated with recreational interactions of children with the water. RHRW was collected from cisterns and ponds located in an inner courtyard in Hanover, Germany. Physicochemical parameters were measured on site and samples were collected once a month in two campaigns in 2020 and 2021. Escherichia coli concentrations ranged from 1 × 10° to 24.1 × 102 MPN/100 mL, Enterococci from 1 × 10° to 19.7 × 102 MPN/100 mL, Salmonella from 1 × 102 to 39 × 103 CFU/100 mL and Pseudomonas aeruginosa from 1 × 10° to 3 × 103 MPN/100 mL. Correlation analysis indicated potential relationships between bacteria, oxygen, and water temperature. The results of the health risk assessment indicated a potential risk of gastrointestinal illnesses due to exposure to Enterococci and Salmonella spp. present in the cisterns and ponds, highlighting the need for appropriate regulations and guidelines for RHRW aimed for non-potable uses. Blue-green infrastructure, when effectively managed and maintained, can offer benefits both by enhancing urban climate resilience and promoting citizens well-being.

A comparative analysis of methods and tools for low impact development (LID) site selection

The site selection for Low Impact Development (LID) practices is a significant process. It affects the effectiveness of LID in controlling stormwater surface runoff, volume, flow rate, and infiltration. This research paper presents a comprehensive review of various methods used for LID site selection. It starts by introducing different methods and tools. Three main methods: index-based methods, GIS-based multi-criteria decision analysis (MCDA), and multi-criteria models and tools, are discussed in detail. A comparative analysis of these methods is then conducted based on ten different criteria. These criteria include the number of variables, data properties, the scale of analysis, benefits maximization approach, multi-attribute decision analysis, user-friendliness, community and stakeholder participation, and the validation methods. This comparison reveals limitations in each method. These include inadequate data availability and quality, lack of evaluation methods, comprehensive assessment criteria and spatial explicitness. These challenges underscore the need for future research to prioritize spatial clarity, broaden criteria, improve data quality through standardization, incorporate field visits and remote sensing for robust results, integrate big data, and develop web-based, open-source tools for enhanced accessibility. These key strategies provide valuable insights for advancing LID site selection methods.

Coupling machine learning and physical modelling for predicting runoff at catchment scale

In this paper, we present an approach that combines data-driven and physical modelling for predicting the runoff occurrence and volume at catchment scale. With that aim, we first estimated the runoff volume from recorded storms aided by the Green-Ampt infiltration model. Then, we used machine learning algorithms, namely LightGBM (LGBM) and Deep Neural Network (DNN), to predict the outputs of the physical model fed on a set of atmospheric variables (relative humidity, temperature, atmospheric pressure, and wind velocity) collected before or immediately after the beginning of the storm. Results for a small urban catchment in Madrid show DNN performed better in predicting the runoff occurrence and volume. Moreover, enriching the input primary atmospheric variables with auxiliary variables (e.g., storm intensity data recorded during the first hour, or rain volume and intensity estimates obtained from auxiliary regression methods) largely increased the model performance. We show in this manuscript data-driven algorithms shaped by physical criteria can be successfully generated by allowing the data-driven algorithm learn from the output of physical models. It represents a novel approach for physics-informed data-driven algorithms shifting from common practices in hydrological modelling through machine learning.

Tool for fast assessment of stormwater flood volumes for urban catchment: A machine learning approach

Specific flood volume is an important criterion for evaluating the performance of sewer networks. Currently, mechanistic models - MCMs (e.g., SWMM) are usually used for its prediction, but they require the collection of detailed information about the characteristics of the catchment and sewer network, which can be difficult to obtain, and the process of model calibration is a complex task. This paper presents a methodology for developing simulators to predict specific flood volume using machine learning methods (DNN - Deep Neural Network, GAM - Generalized Additive Model). The results of Sobol index calculations using the GSA method were used to select the ML model as an alternative to the MCM model. It was shown that the DNN model can be used for flood prediction, for which high agreement was obtained between the results of GSA calculations for rainfall data, catchment and sewer network characteristics, and calibrated SWMM parameters describing land use and sewer retention. Regression relationships (polynomials and exponential functions) were determined between Sobol indices (retention depth of impervious area, correction factor of impervious area, Manning's roughness coefficient of sewers) and sewer network characteristics (unit density of sewers, retention factor - the downstream and upstream of retention ratio) obtaining R2 = 0. 55-0.78. The feasibility of predicting sewer network flooding and modernization with the DNN model using a limited range of input data compared to the SWMM was shown. The developed model can be applied to the management of urban catchments with limited access to data and at the stage of urban planning.

Profiling emerging micropollutants in urban stormwater runoff using suspect and non-target screening via high-resolution mass spectrometry

Urban surface runoff contains chemicals that can negatively affect water quality. Urban runoff studies have determined the transport dynamics of many legacy pollutants. However, less attention has been paid to determining the first-flush effects (FFE) of emerging micropollutants using suspect and non-target screening (SNTS). Therefore, this study employed suspect and non-target analyses using liquid chromatography-high resolution mass spectrometry to detect emerging pollutants in urban receiving waters during stormwater events. Time-interval sampling was used to determine occurrence trends during stormwater events. Suspect screening tentatively identified 65 substances, then, their occurrence trend was grouped using correlation analysis. Non-target peaks were prioritized through hierarchical cluster analysis, focusing on the first flush-concentrated peaks. This approach revealed 38 substances using in silico identification. Simultaneously, substances identified through homologous series observation were evaluated for their observed trends in individual events using network analysis. The results of SNTS were normalized through internal standards to assess the FFE, and the most of tentatively identified substances showed observed FFE. Our findings suggested that diverse pollutants that could not be covered by target screening alone entered urban water through stormwater runoff during the first flush. This study showcases the applicability of the SNTS in evaluating the FFE of urban pollutants, offering insights for first-flush stormwater monitoring and management.

Effects of urban catchment characteristics on combined sewer overflows

Pollution from Combined Sewer Overflows (CSOs) cause diffuse environmental problems, which are still not satisfactorily addressed by current management practices. In this study, a sensitivity analysis was conducted on several CSO environmental impact indicators, with respect to parameters that characterise climate, urban catchment and the CSO structure activation threshold. The sensitivity analysis was conducted by running 10000 simulations with the Storm Water Management Model, using a simplified modelling approach. The indicators were calculated at yearly scale to evaluate overall potential effects on water bodies. The results could be used to estimate pollution load ranges, known the values of the input parameters, and to investigate suitable strategies to reduce pollution of the receiving water bodies. The percentage of impervious surface of the catchment was found the most influent parameter on all the indicators, and its reduction can contain the discharged pollutant mass. The activation threshold, instead, resulted the second least influent parameter on all the indicators, suggesting that its regulation alone would not be a suitable strategy to reduce CSO pollution. However, along with the reduction of the imperviousness, its increase could effectively decrease the concentration of pollutant in the overflow. The results also indicate that neither adopting sustainable urban drainage practices, nor interventions on the CSO device, significantly affect the frequency of the overflows. Therefore, restricting this latter was found to be ineffective for the reduction of both the discharged pollutant mass and the concentration of pollutant in the overflow.

The investigation of sorption-desorption performance and mechanism of copper by surfactant-modified zeolite in aqueous solutions

As the most common filler in stormwater treatment, zeolite (NZ-Y) has good cation exchange capability and stabilization potential for the removal of heavy metal from aqueous solutions. In this study, sodium dodecyl sulfate (SDS) and NZ-Y were selected to preparing new adsorbent (SDS-NZ) by using a simple hydrothermal method. The sorption-desorption performance and mechanism of Cu(II) onto SDS-NZ were investigated. The results showed that the sorption of Cu(II) on SDS-NZ was in accordance with the pseudo-second-order kinetic model with an equilibrium time of 4 h. The sorption behavior fitted Langmuir isotherm with a saturation sorption capability of 9.03 mg/g, which was three times higher than that of NZ-Y. The modification of SDS increases the average pore size of NZ-Y by 3.96 nm, which results in a richer internal pore structure and more useful sorption sites for Cu(II) sorption. There was a positive correlation between solution pH values and sorption capability of Cu(II) in the range of 3.0-6.0. With the ionic strength increased, the sorption capability of Cu(II) onto SDS-NZ first decreased and then increased, which may be attributed to competitive sorption and compression of the electronic layer. The desorption of Cu(II) on SDS-NZ was favored by the increase in SDS concentration and ionic strength and decrease in solution pH values. The application of SDS-NZ in runoff improved the leaching risk of Cu(II). After several cycles, the ability of reused SDS-NZ to efficiently adsorb most heavy metals was verified with removal rates above 99%.

Physiological and biochemical assortment in different wheat genotypes (Triticum aestivum L.) under rain fed conditions

Wheat (Triticum aestivum L.) is the most extensively cultivated cereal crop in the world; however, its growth and development are affected by different types of biotic and abiotic stress conditions. The aim of this study was to assess the physico-chemical diversity in different wheat genotypes under rain-fed conditions. Principle component analysis (PCA) showed that significant variation for different components contributed 77.87% of total variability among all genotypes. In the scree plot, the first two PCs (PC1=44.75%, PC2=14.28%) had significant differences for numerous agronomic traits. The scatter biplot depicted eight genotypes (Zardana, NR-462, D-97, BARS-2009 (a check), NR-481, Tarnab-73, NR-489 and Pirsabak-91) with high diversity (variation ~90%) for different morphological traits, identifiable as they were located further away from the origin than other genotypes. Factor analysis of loading factors among wheat genotypes across different morpho-physiological traits also showed significant diversity for positive and negative loads. In cluster analysis, genotypes such as BWP-97, BARS-2009, NR-489, NR-448 and Pak. 13 were outliers, indicating significant diversity among all genotypes for different agronomic traits. Biochemical analysis showed maximum values for antioxidant activity, total phenolic content, and total flavonoid content in lines NR-485 (93.76%), NR-489 (3.55mg gallic acid equivalent (GAE)/g), and the variety Suleman-96 (3.45mg quercetin equivalent (QE)/g), respectively. This study provides new insights for understanding the diversity of different wheat genotypes under rain-fed conditions, and the selected genotypes can be evaluated for further breeding programs.

Analysis of pollutant dispersion patterns in rivers under different rainfall based on an integrated water-land model

In the context of rapid urban expansion, the interaction between humanity and nature has become more prominent. Urban land and rivers often exist as distinct entities with limited material exchange. However, during rainfall, these two systems interconnect, resulting in the transfer of land-derived pollutants into rivers. Such transfer significantly increases river pollutant levels, adversely affecting water quality. Therefore, developing a water quality simulation and prediction model is crucial. This model should effectively illustrate pollutant movement and dispersion during rain events. This study proposes a comprehensive model that merges the Storm Water Management Model (SWMM) with the Environmental Fluid Dynamics Code (EFDC). This integrated model assesses the spread and dispersion of pollutants, including Ammonia Nitrogen (NH3-N), Total Phosphorus (TP), Total Nitrogen (TN), and Chemical Oxygen Demand (COD), within urban water cycles for various rainfall conditions, thus offering critical theoretical support for managing the water environment. The application of this model under different rainfall intensities (light, moderate and heavy) provides vital insights. During light rainfall, the river's natural purification process can sustain surface water quality at Class IV. Moderate rainfall causes accumulation of pollutants, reducing water quality to Class V. Conversely, heavy rainfall rapidly increases pollutant concentrations due to higher inflow, pushing the river to a degraded Class V status, which is beyond its natural purification capacity, necessitating engineering solutions to reattain Class IV quality. Furthermore, pollutant accumulation in downstream river sections is more influenced by flow rate than by rainfall intensity. In summary, the SWMM-EFDC integrated model proves highly effective in predicting river water quality, thereby significantly aiding urban water pollution control.

Profiling wastewater characteristics in intra-urban catchments using online monitoring stations

This study aims to investigate the differences in intra-urban catchments with different characteristics through real-time wastewater monitoring. Monitoring stations were installed in three neighbourhoods of Barcelona to measure flow, total chemical oxygen demand (COD), pH, conductivity, temperature, and bisulfide (HS-) for 1 year. Typical wastewater profiles were obtained for weekdays, weekends, and holidays in the summer and winter seasons. The results reveal differences in waking up times and evening routines, commuting behaviour during weekends and holidays, and water consumption. The pollutant profiles contribute to a better understanding of pollution generation in households and catchment activities. Flows and COD correlate well at all stations, but there are differences in conductivity and HS- at the station level. The article concludes by discussing the operational experience of the monitoring stations.

New phosphorus losses via tile drainage depend on fertilizer form, placement, and timing

Agricultural phosphorus (P) losses are harmful to water quality, but knowledge gaps about the importance of fertilizer management practices on new (recently applied) sources of P may limit P loss mitigation efforts. Weighted regression models applied to subsurface tile drainage water quality data enabled estimating the new P losses associated with 155 P applications in Ohio and Indiana, USA. Daily discharge and dissolved reactive P (DRP) and total P (TP) loads were used to detect increases in P loss following each application which was considered new P. The magnitude of new P losses was small relative to fertilizer application rates, averaging 79.3 g DRP ha-1 and 96.1 g TP ha-1 , or <3% of P applied. The eight largest new P losses surpassed 330 g DRP ha-1 or 575 g TP ha-1 . New P loss mitigation strategies should focus on broadcast liquid manure applications; on average, manure applications caused greater new P losses than inorganic fertilizers, and surface broadcast applications were associated with greater new P losses than injected or incorporated applications. Late fall applications risked having large new P losses applications. On an annual basis, new P contributed an average of 14% of DRP and 5% of TP losses from tile drains, which is much less than previous studies that included surface runoff, suggesting that tile drainage is relatively buffered with regard to new P losses. Therefore old (preexisting soil P) P sources dominated tile drain P losses, and P loss reduction efforts will need to address this source.

A critical review of the mechanisms, factors, and performance of pervious concrete to remove contaminants from stormwater runoff

Stormwater can carry pollutants accumulated on impervious surfaces in urban areas into natural water bodies in absence of stormwater quality improvement devices. Pervious concrete (PC) pavement is one of the low-impact development practices introduced for urban flooding prevention and stormwater pollution reduction. PC removes various types of water contaminants. Mechanisms contributing to the water pollution removal capacity of PC can be categorized into three groups: physical, chemical, and biological. Properties of PC such as permeability, porosity, thickness, and adsorption capacity influence removal of all contaminants, although their impact might differ depending on the pollutant properties. Chemical mechanisms include precipitation, co-precipitation, ion and ligand exchange, complexation, diffusion, and sorption. Bulk organics and nutrients are removed primarily by biodegradation. Physical filtration is the primary mechanism to retain suspended solids, although biological activities may have a minor contribution. Release of calcium (Ca2+) and hydroxide (OH-) from hardened cement elevates the effluent pH, which is an environmental concern. However, the pH elevation is also the prime contributor to heavy metals and nutrients removal through precipitation. Specific cementitious materials (e.g., Pozzolans and nanoparticles) and carbonation curing approach are recommended to control effluent pH elevation. Complexation, diffusion, ion solubility, and stability constants are other mechanisms and parameters that influence heavy metal removal. Organic matter availability, electrostatic attraction, temperature, pH, contact time, specific surface area, and roughness of PC pores contribute to the pathogen removal process. Although PC has been found promising in removing various water pollutants, limited salinity removal can be achieved due to the inherent release of Ca2+and OH- from PC.

The effect of green infrastructure on resilience performance in combined sewer systems under climate change

Climate change is currently reshaping precipitation patterns, intensifying extremes, and altering runoff dynamics. Particularly susceptible to these impacts are combined sewer systems (CSS), which convey both stormwater and wastewater and can lead to combined sewer overflow (CSO) discharges during heavy rainfall. Green infrastructure (GI) can help mitigate these discharges and enhance system resilience under historical conditions; however, the quantification of its effect on resilience in a future climate remains unknown in the literature. This study employs a modified Global Resilience Analysis (GRA) framework for continuous simulation to quantify the impact of climate change on CSS resilience, particularly CSOs. The study assesses the efficacy of GI interventions (green roofs, permeable pavements, and bioretention cells) under diverse future rainfall scenarios based on EURO-CORDEX regional climate models (2085-2099) and three Representative Concentration Pathways (2.6, 4.5, 8.5 W/m2). The findings underscore a general decline in resilience indices across the future rainfall scenarios considered. Notably, the total yearly CSO discharge volume increases by a range of 145 % to 256 % in response to different rainfall scenarios. While GI proves effective in increasing resilience, it falls short of offsetting the impacts of climate change. Among the GI options assessed, green roofs routed to pervious areas exhibit the highest adaptive capacity, ranging from 9 % to 22 % at a system level, followed by permeable pavements with an adaptation capacity between 7 and 13 %. By linking the effects of future rainfall scenarios on CSO performance, this study contributes to understanding GI's potential as a strategic tool for enhancing urban resilience.

Microbial composition of Saharan dust plumes deposited as red rain in Granada (Southern Spain)

During durst storms, also biological material is transported from arid areas such as the Sahara Desert. In the present work, rain samples containing significant amounts of mineral dust have been collected in Granada during different red rain episodes. Biological features (bacteria, biofilm, pollen grain and fungal spore) as well as size-particle distribution and mineralogical composition were studied by SEM. Nanobacteria were observed for the first time in red rain samples. A preliminary metabarcoding analysis was performed on three red rain samples. Here, Bacillota made up 18 % and Pseudomonadota 23 % of the whole prokaryotic community. The fungal community was characterized by a high abundance of Ascomycota and, dependent on the origin, the presence of Chytridiomycota. By means of 16S rRNA sequencing, 18 cultivable microorganisms were identified. In general, members of the phyla Pseudomonadota and Bacillota made up the majority of taxa. Some species, such as Peribacillus frigoritolerans and Bacillus halotolerans were isolated during three different red rain episodes. Generally, red rain carries a wide variety of microorganisms, being their ecosystem and health effects largely unknown.

The effects of heavy rain on the fate of urban and agricultural pollutants in the riverside area around weirs using multi-isotope, microbial data and numerical simulation

The increase in extreme heavy rain due to climate change is a critical factor in the fate of urban and agricultural pollutants in aquatic system. Nutrients, including NO3- and PO43-, are transported with surface and seepage waters into rivers, lakes and aquifers and can eventually lead to algal blooms. δ15N-NO3-, δ18O-NO3-, and δ11B combined with hydrogeochemical and microbial data for groundwater and surface water samples were interpreted to evaluate the fate of nutrients in a riverside area around weirs in Daegu, South Korea. Most of the ions showed similar concentrations in the groundwater samples before and after heavy rain while concentrations of major ions in surface water samples were diluted after heavy rain. However, Si, PO43-, Zn, Ce, La, Pb, Cu and a number of waterborne pathogens increased in surface water after heavy rain. The interpretation of δ11B, δ15N-NO3-, and δ18O-NO3- values using a Bayesian mixing model revealed that sewage and synthetic fertilizers were the main sources of contaminants in the groundwater and surface water samples. δ18O and SiO2 interpreted using the Bayesian mixing model indicated that the groundwater component in the surface water increased from 4.4 % to 17.9 % during the wet season. This is consistent with numerical simulation results indicating that the direct surface runoff and the groundwater baseflow contributions to the river system had also increased 6.4 times during the wet season. The increase in proteobacteria and decrease of actinobacteria in the surface water samples after heavy rain were also consistent with an increase of surface runoff and an increased groundwater component in the surface water. This study suggests that source apportionment based on chemical and multi-isotope data combined with numerical modeling approaches can be useful for identifying main hydrological and geochemical processes in riverside areas around weirs and can inform suggestions of effective methods for water quality management.

Changes in vegetation in China's drylands are closely related to afforestation compared with climate change

The response of vegetation to climate change and human activities has attracted considerable attention. However, quantitative studies on the effects of climate change and human activities on dryland vegetation in different seasons remain unclear. This study investigated the impacts of precipitation, temperature, soil water storage (SWS) (top [0-7 cm], shallow [7-28 cm], and middle [28-100 cm] layers), vapor pressure deficit (VPD), and afforestation on vegetation as well as their relative contribution rates during the rainy season ([RS], June to September), dry season ([DS], November to April), transition season ([TS], May and October), and all year period (AY) in China's drylands from 2001 to 2020 using the first-difference method. Areas with precipitation and SWS showing significant positive correlation with dryland vegetation (p < 0.05) were found to be larger in RS than in DS and TS, and the positive effect of SWS increased with soil depth in the 0-28 cm interval. Increasing VPD induced a significant negative effect on vgetation during RS but it was not predominant in DS and TS. Afforestation showed an extremely significant positive correlated with dryland vegetation across >60 % of China's dryland areas (p < 0.01), but this improvement was found to be limited to regions with the highest afforestation area. Moreover, dryland vegetation dynamics were driven by afforestation in all seasons, with contribution rates of 64.23 %-71.46 %. The effects of SWS and VPD on vegetation driven by precipitation and temperature exceeded the direct effects of precipitation and temperature. Among climatic factors, VPD showed a major regulating effect on dryland vegetation at the top and shallow soil layers in almost all seasons, whereas the relative contribution rate of SWS increased with soil layer. The findings can provide a scientific reference for the sustainable development and protection of drylands under global warming.

Dancing in the purple rain: color affinity and oviposition choices in Aedes sierrensis (Diptera: Culicidae)

The western tree hole mosquito, Aedes sierrensis (Ludlow) (Diptera: Clucidae), is a pestiferous mosquito with a range extending over the entire pacific seaboard and into portions of the intermountain west. As a peridomestic heartworm vector, it demands at least some level of surveillance to understand its abundance. However, the species is refractory to a majority of conventional vector surveillance approaches for tracking mosquitoes. To find more options for Aedes sierrensis surveillance, a variety of oviposition attractants were evaluated in arena-style choice assays using colony reared adults. A range of infusion treatments (e.g., alfalfa, oak, and beetroot) were examined and then combined with investigations of liquid color as well as ovicup color and entryway position. These studies revealed that Ae. sierrensis have an affinity for purple coloration, plain water, and larger entryway sizes for oviposition cups. A prototype ovicup was 3D-printed using purple filament and multiple types of entryways, and used to re-test infusion waters. No particular attraction differences were detected after normalizing for purple color. Comparisons to black 3D-printed cups yielded surprising observations that male mosquitoes also aggregated on purple cups while females sheltered, but not necessarily oviposited, in black cups. Although this was only a laboratory-based assessment, these studies provide useful information for future field trials of potential oviposition traps for surveillance of Ae. sierrensis.

Inter-event and intra-event dynamics of microplastic emissions in an urban river during rainfall episodes

Urban rivers represent the major conduits for land-sourced microplastics in the global oceans, yet the real-time dynamics of their emissions in rivers during rainfall (and runoff) events are poorly understood. Herein, we report the results of high-frequency sampling of microplastic particles (MPs) and fibers (MPFs) in the surface water of an urban river in Japan over the course of three rainfall events (i.e., light, moderate, and heavy rainfalls). The event mean concentrations (EMCs) of MPs amounted to 35,000 items/m3, 929,000 items/m3, and 331,000 items/m3; and the corresponding total loads were 0.5 kg, 19.8 kg, and 35.0 kg for light, moderate and heavy rainfalls, respectively. The inter-event total loads of MPs correlate well with the total rainfall, while the concentrations were linked with the number of antecedent dry days. The dynamic trends show that <2000 μm MPs displayed first flush effects during light to moderate rainfall events (>50% mass discharged with the initial 20-40% of flow). Small-sized MPs (10-40 μm) mobilized rapidly at lower rainfall intensities, whereas MPs over 2000 μm discharged immediately after the peak rainfall intensity. Moreover, <70 μm MPs depicted a surge following heavy rainfall events due to turbulent flow conditions reverting the deposited MPs into suspension. Overall, the three events increased the loads by 4-110 folds, and EMCs by 10-350 folds compared to the concentrations during dry weather while portraying a significant impact on 300-1000 μm MPs. The dynamics of MPs were correlated with those of suspended solids in river water, and the characteristics were comparable to the same of road dust sampled in Japan. Although the dynamic trends between MPs and MPFs in river water were comparable, MPFs were relatively less impacted by rain, likely due to the intervention of separate sewer systems in the study area.

Multi-media interaction improves the efficiency and stability of the bioretention system for stormwater runoff treatment

Bioretention systems are one of the most widely used stormwater control measures for urban runoff treatment. However, stable and effective dissolved nutrient treatment by bioretention systems is often challenged by complicated stormwater conditions. In this study, pyrite-only (PO), pyrite-biochar (PB), pyrite-woodchip (PW), and pyrite-woodchip-biochar mixed (M) bioretention systems were established to study the feasibility of improving both stability and efficiency in bioretention system via multi-media interaction. PB, PW, and M all showed enhanced dissolved nitrogen and/or phosphorus removal compared to PO, with M demonstrating the highest efficiency and stability under different antecedent drying durations (ADD), pollutant levels, and prolonged precipitation depth. The total dissolved nitrogen and dissolved phosphorus removal in M ranged between 64%-86% and 80%-95%, respectively, with limited organic matter and iron leaching. Pore water, microbial community, and material analysis collectively indicate that pyrite, woodchip, and biochar synergistically facilitated multiple nutrient treatment processes and protected each other against by-product leaching. Pyrite-woodchip interaction greatly increased nitrate removal by facilitating mixotrophic denitrification, while biochar further enhanced ammonium adsorption and expanded the denitrification area. The Fe3+ generated by pyrite aerobic oxidation was adsorbed on the biochar surface and potentially formed a Fe-biochar composite layer, which not only reduced Fe3+-induced pyrite excessive oxidation but also potentially increased organic matter adsorption. Fe (oxyhydr)oxides intermediate product formed by pyrite oxidation, in return, controlled the phosphorus and organic matter leaching from biochar and woodchip. Overall, this study demonstrates that multi-media interaction may enable bioretention systems to achieve stable and effective urban runoff treatment.

Interactions of particulate- and dissolved-phase heavy metals in a mature stormwater bioretention cell

Bioretention is an increasingly common stormwater control measure (SCM) for mitigation of stormwater quantity and quality. Studies from lab to field scale have shown successful removal of total metals from stormwater, especially Cu and Zn which are ubiquitous in the urban environment yet detrimental to aquatic ecosystems. While bioretention effectively removes particulate matter and particulate bound (PB) contaminants, removal performance of dissolved metals has been neglected in field studies. After approximately two decades of these systems being implemented, with a typical design-life of 20 years, performance of mature systems is unknown. This study examined the performance of a 16- to 18-year-old bioretention cell by characterizing Cu and Zn partitioning and removal. Flow-weighted composite samples of stormwater and bioretention effluent were collected and analyzed for total and dissolved metals. Size-fractioned road-deposited sediments (RDS) were collected and analyzed for metals and particle size distribution. The comparison of RDS and PB metals showed that PB-Zn was enriched in stormwater, indicating higher mobility of PB-Zn compared to PB-Cu. The mature bioretention system effectively removed particulates and PB-metals with average load reductions of 82% and 83%, respectively. While concentrations for dissolved metals were low (<40 μg/L), no significant difference between influent and effluent was observed. Effluent concentrations of total and dissolved Cu, total organic carbon, and particulates were not significantly different from those measured over 10 years ago at the site, while total Zn effluent concentration slightly increased. MINTEQ speciation modeling showed that Cu was approximately 100% bound with dissolved organic matter (DOM) in all bioretention effluent. While Zn was also mostly bound with DOM in effluent, some events showed free ionic Zn reaching concentrations in the same order of magnitude. Media amendments, maintenance, and monitoring of SCMs should be considered where further removal of dissolved metals is necessary for the protection of aquatic environments.

Empirical dynamic modelling and enhanced causal analysis of short-length Culex abundance timeseries with vector correlation metrics

Employing Empirical Dynamic Modelling we investigate whether model free methods could be applied in the study of Culex mosquitoes in Northern Greece. Applying Simplex Projection and S-Map algorithms on yearly timeseries of maximum abundances from 2011 to 2020 we successfully predict the decreasing trend in the maximum number of mosquitoes which was observed in the rural area of Thessaloniki during 2021. Leveraging the use of vector correlation metrics we were able to deduce the main environmental factors driving mosquito abundance such as temperature, rain and wind during 2012 and study the causal interaction between neighbouring populations in the industrial area of Thessaloniki between 2019 and 2020. In all three cases a chaotic and non-linear behaviour of the underlying system was observed. Given the health risk associated with the presence of mosquitoes as vectors of viral diseases these results hint to the usefulness of EDM methods in entomological studies as guides for the construction of more accurate and realistic mechanistic models which are indispensable to public health authorities for the design of targeted control strategies and health prevention measures.

Rain may improve survival from direct lightning strikes to the human head

There is evidence that humans can survive a direct lightning strike to the head. Our question is: could water (rain) on the skin contribute to an increase in the survival rate? We measure the influence of rain during high-energy direct lightning strikes on a realistic three-compartment human head phantom. We find a lower number of perforations and eroded areas near the lightning strike impact points on the head phantom when rain was applied compared to no rain. Current amplitudes in the brain were lower with rain compared to no rain before a fully formed flashover. We conclude that rain on the scalp potentially contributes to the survival rate of 70-90% due to: (1) lower current exposition in the brain before a fully formed flashover, and (2) reduced mechanical and thermal damage.

Association of rainfall pattern with the disappearance of mineral mixtures fed cattle managed on tropical pastures

The objective of the present study was to evaluate the association between rainfall and the disappearance of mineral mixtures in the supplementation of cattle on pasture. Supplement consumption and rainfall data were obtained from five experiments carried out between 2016 and 2022. The experiments lasted from 84 to 126 days and had 12 to 18 paddocks formed by Brachiaria spp. under grazing by beef cattle (n = 544), receiving mineral supplementation. Supplement disappearance (SD), difference between the amount offered and leftovers (considering intake and losses) and precipitation (PR), was measured over periods of 14 to 21 days. The periods (n = 565) were classified as very dry, dry, normal, rainy, and very rainy, using the Quantis method. The number of rainy days (RD) and the average precipitation per RD (APRD) per period and the average body weight (BW) of the animals in the periods were also determined. Linear regression analyses assessed the association between BW, PR, RD, and APRD. The average PR in the periods studied was 68.5 mm, ranging from 0.00 to 160.3 mm. Each period had up to six RD, with up to 129.5 mm precipitated. The average BW was 270 kg, ranging from 208 to 335 kg and the average SD was 82.2 g/animal/day, ranging from 0.52 to 176.7 g/animal/day. Differences in RD and APRD are consistent across precipitation classes. In the regression analysis, the model with the highest coefficient of determination was the one that contained the linear and quadratic terms for the RD variable. Including linear and quadratic terms of all variables in a multiple regression represented more than half of the variation in the disappearance of the supplement (R2 = 0.5823). There is no clear relationship between the intensity of precipitation, reflected in the form of classes, and the disappearance of supplements offered to cattle on pasture since dry and very rainy periods can be equivalent. However, variables that characterize the precipitation pattern are more relevant than animal live weight to explain existing variations in supplement disappearance. Among them, the frequency with which precipitation occurs (number of rainy days in the period) seems to be more important than the precipitation rate itself, probably because it is related to the volume of precipitation accumulated in the period.

The storm runoff management strategy based on agricultural ditch nutrient loss characteristics in Erhai Lake, China

Initial flush management is an effective measure to control non-point source pollution (NPSP) in storm runoff. However, determining the parameter of the initial flush in different areas may pose challenges in storm runoff management strategies. To address this issue, Erhai Lake in China, Yunnan-Guizhou Plateau, was selected as an example for the study. Erhai Lake is a typical mesotrophic lake with the profound influence of NPSP. The NPSP control strategy in this area will provide a valuable reference for other lakes. In 2021, 289 storm events and 190 ditchwater samples were detected around Erhai Lake. The average flow in the ditches ranged from 0.004 to 0.147 m3/s, the instant total nitrogen (TN) concentration ranged from 0.28 to 91.43 mg/L, and the instant total phosphorus (TP) concentration ranged from 0.26 to 7.35 mg/L in the storm events. It was found that the concentration of pollutants was lower than expected in the initial flush period. Instead, the event mean concentrations of TN and TP were 9.3 and 2.1 times higher than in the wet seasons, showing high nutrient concentration levels throughout the entire rainfall period. To manage storm runoff effectively, a flow-processes-division method was proposed to analyze the inflow condition and pollutant removal rate in different runoff periods. The peak flow interception strategy was recommended as the optimal stormwater management plan, as it showed the highest inflow conditions and 50% pollutant removal rate. Considering the need to reduce the constant flush of stormwater runoff, it is essential to establish a healthy water cycle system to alleviate NPSP and raise the Erhai water level. The storm runoff management method can serve as a practical tool for lake areas that do not exhibit initial flush characteristics.

Dominant flood types in mountains catchments: Identification and change analysis for the landscape planning

The classification of floods may be a supporting tool for decision-makers in regard to water management, including flood protection. The main objective of this work is the classification of flood generation mechanisms in 28 catchments of the upper Vistula basin. A significant innovation in this study lies in the utilization of decision trees for flood classification. The methodology has so far been applied in the Alpine region. The analysis reveals that peak daily precipitation in the catchments mainly occurs in summer, particularly from June to August. Maximal daily snowmelt typically happens at the end of winter (March to April) and occasionally in November. Winter peaks are observed in March to April and, in some areas, in November to December, while summer peaks occur in May and, in specific catchments, in October. Higher peak flows for annual floods are noted in March to April and June to August. Most annual floods in the Upper Vistula basin are classified as Rain-on-Snow Floods (RoSFs) or Lowland River Floods (LRFs). LRFs contribute from 19% to almost 72%, while RoSFs range from 18% to 75%. In Season 1 (summer), most seasonal floods are identified as LRFs (51%-100%), with very few as RoSFs (0%-46.9%). In Season 2 (winter), the opposite pattern is observed, with most RoSFs (48.4%-97.9%) and fewer LRFs (0%-20.6%). While there are changes in flood patterns, they are not statistically significant. Conducted studies and obtained results can be useful for the preparation of flood prevention documentation and for flood management in general.

Influence of short- and long-term persistence on identification of rainfall temporal trends using different versions of the Mann-Kendall test in Mizoram, Northeast India

Investigating the temporal dynamics of rainfall in a changing climate, especially in rainfed agriculture regions, is crucial for analyzing climate-induced changes and offering adaptation options. Since Mizoram experiences unfavorable impacts of rain nearly every year, the region rainfall has been altering over the years, and vital climatic activity is becoming uncontrollable. The current study is primarily concerned with the changing trend of rainfall over Mizoram, which includes both short-term persistence (STP) and long-term persistence (LTP) of rainfall in seasonal and annual time series of rainfall overseeing for the period of 25 years of daily average rainfall from 1996 to 2020 collected collectively from the seven stations over the study area of Mizoram. Four different Mann-Kendall method iterations were used to analyze rainfall trends: the original or conventional method (without autocorrelation) (MnKn1), removing lag-1 autocorrelation (trend-free pre-whitening), considering multiple lag autocorrelation (more than lag-1 autocorrelation) (MnKn3), and Hurst coefficient or LTP (MnKn4). In the analysis, the study found that during monsoon, station Lawngtlai (LT) observed the highest rainfall having a Z value of 1.986, increased by 0.466 cm/year, while station Serchhip (SC) observed the lowest rainfall having Z value of -2.282, decreased by -0.163 cm/year. After applying modified MnKn4, we observed LTP of rainfall in winter at station Lawngtlai (LT) with an increasing trend and other stations observing STP in almost all seasons either increasing or decreasing trend. Therefore, possible climate change adaptation measures should be made to optimize rainfall use for various applications for the states of Mizoram.

Runoff nitrogen losses under confluence and diverging drainage systems in the sloped plot scale: A comparative study

The drainage system is a key measure for regulating runoff nutrient losses on sloping farmlands. Confluence and diverging drainage systems are two drainage layouts representing natural water network systems and are widely distributed in sloping farmlands; however, the effects of these drainage systems on runoff nutrient losses in the sloped plots remain unclear. This study investigated the effects of different drainage systems on the characteristics of runoff nitrogen (N) losses in sloped plots using laboratory rainfall simulations. Three treatments, including bare slope (without drainage system, CK), confluence drainage system (T1), and diverging drainage system (T2), were used to compare the changes in concentrations and losses of total nitrogen (TN), dissolved nitrogen (DN), and particulate nitrogen (PN), and the DN:TN ratio in runoff under a combination of 1.8 mm min-1 rainfall intensity and three slope gradients (5°, 10°, and 15°). The results showed that the time to runoff was significantly delayed in T2 compared with that in CK and T1 across all slopes (p < 0.05). Accumulated runoff depth was considerably lower in T1 and T2 than in CK across all slopes (p < 0.05). The TN and PN concentrations in T1 were markedly lower than those in T2 on the 10° and 15° slopes (p < 0.05). The DN concentration in T1 was lowest at the 5° slope (p < 0.05). TN loss in T1 was 14.7-33.9% and 17.9-30.3% lower than those in CK and T2 across all slopes, respectively (p < 0.05). The PN loss in T1 was 56.7% and 53.3% lower than that in T2 on the 10° and 15° slopes, respectively (p < 0.05). DN loss in T1 was 39.3-72.5% lower than that in CK for all slopes (p < 0.05). DN:TN in T2 was lower than that in CK and T1 at the 10° and 15° slopes (p < 0.05). Our results confirm the effectiveness of drainage systems in reducing runoff nutrient losses in a sloped plot and demonstrate that the confluence drainage system is better at reducing N losses in runoff than diverging drainage systems.

Study of experimental and numerical simulation on the influence of gravel on the interflow of slope land

The formation of interflow is of great significance for the stability of mountain slopes and soil erosion. Hillsides are often covered with a certain amount of gravel, and research on interflow of slope land with different gravel ratios needs to be carried out. This article is based on indoor experiments and numerical models to study the formation law of interflow in hillside soil under different gravel coverage ratios. It was found that the interflow in the soil rapidly increased in the early stage and began to decrease after briefly reaching equilibrium. The formation of interflow is a complex process that is related to slope, soil characteristics, and rainfall intensity, but the correlation is not high when viewed separately. The lattice Boltzmann model can effectively simulate such problems and achieve high simulation accuracy. The [Formula: see text] of the simulated data and measured data ranged from 0.5217 to 0.7403, and [Formula: see text] of the simulated data and measured data ranged from 0.4051 to 0.5711.