Response of water yield to silvicultural treatments in a temperate forest in northern Mexico

Forest management modifies tree cover, directly influencing various ecosystem services, such as water regulation. Evapotranspiration, water interception, surface runoff, stemflow, and throughfall are among those processes that depend on tree cover. The objective of this study was to evaluate the changes in water yield, defined as the difference between precipitation and evapotranspiration, after the application of silvicultural treatments in a temperate forest ecosystem in northern Mexico. Fifteen experimental plots were established in which the following treatments were applied: intensive management (clearcutting), semi-intensive management (selection, tree cutting of 59-61% of basal area), conservative management (selection, tree cutting of 29-31% of basal area), and no treatment (control group). Incident precipitation, throughfall, stemflow, net precipitation, interception, and surface runoff were analyzed. Results show that conservative management treatments increase water yield between 2 to 3.6 mm per m-2 ha-1 of tree basal area removed. Water flow distribution, in relation to the incident precipitation, ranged from 72.3 to 91.8% for throughfall, 0.2 to 0.4% for stemflow, 72.7 to 91.8% for net precipitation, 8.19 to 27.42% for interception or evaporation, and 0.54 to 1.93% for surface runoff. The conservative management treatment was the most viable alternative for increasing water yield without compromising timber harvesting and loss of soil due to hydric erosion.

Biocrusts protect the Great Wall of China from erosion

The Great Wall of China, one of the most emblematic and historical structures built by humankind throughout all of history, is suffering from rain and wind erosion and is largely colonized by biocrusts. However, how biocrusts influence the conservation and longevity of this structure is virtually unknown. Here, we conducted an extensive biocrust survey across the Great Wall and found that biocrusts cover 67% of the studied sections. Biocrusts enhance the mechanical stability and reduce the erodibility of the Great Wall. Compared with bare rammed earth, the biocrust-covered sections exhibited reduced porosity, water-holding capacity, erodibility, and salinity by 2 to 48%, while increasing compressive strength, penetration resistance, shear strength, and aggregate stability by 37 to 321%. We further found that the protective function of biocrusts mainly depended on biocrust features, climatic conditions, and structure types. Our work highlights the fundamental importance of biocrusts as a nature-based intervention to the conservation of the Great Wall, protecting this monumental heritage from erosion.

Next-Generation Intensity-Duration-Frequency Curves for Diverse Land across the Continental United States

The current methods for designing hydrological infrastructure rely on precipitation-based intensity-duration-frequency curves. However, they cannot accurately predict flooding caused by snowmelt or rain-on-snow events, potentially leading to underdesigned infrastructure and property damage. To address these issues, next-generation intensity-duration-frequency (NG-IDF) curves have been developed for the open condition, characterizing water available for runoff from rainfall, snowmelt, and rain-on-snow. However, they lack consideration of land use land cover (LULC) factors, which can significantly affect runoff processes. We address this limitation by expanding open area NG-IDF dataset to include eight vegetated LULCs over the continental United States, including forest (deciduous, evergreen, mixed), shrub, grass, pasture, crop, and wetland. This NG-IDF 2.0 dataset offers a comprehensive analysis of hydrological extreme events and their associated drivers under different LULCs at a continental scale. It will serve as a useful resource for improving standard design practices and aiding in the assessment of infrastructure design risks. Additionally, it provides useful insights into how changes in LULC impact flooding magnitude, mechanisms, timing, and snow water supply.

Exogenously applied 5-aminolevulinic acid modulates growth, yield, and physiological parameters in lentil (Lens culinaris Medik.) under rain-fed and supplemental irrigation conditions

Lentils are a significant source of plant protein and are cultivated across Asia, Europe, and North Africa. Plants are subjected to various environmental stresses, which can hinder growth, yield, and productivity. 5-aminolevulinic acid (ALA) is a compound that acts as a precursor in the biosynthesis of tetrapyrroles and can increase plant tolerance to different abiotic stressors. However, the effects of exogenously applied ALA on lentil growth, yield, and physiological parameters under rain-fed and supplemental irrigation conditions are not well-known. In this study, a split plot experiment was conducted to investigate the impact of ALA foliar application and supplemental irrigation on lentil (Lens culinaris Medik.). The experiment was designed based on a randomized complete block with three replications. The main plot included four levels of supplemental irrigation [(supplementary irrigation in the flowering and early seed-filling stages, supplementary irrigation in the flowering stage, supplementary irrigation in the early seed-filling along with rain-fed conditions (no irrigation)]. The subplot considered foliar application of ALA at varying levels [(0 (control), 50 and 100 ppm)]. The results showed that water regimes and foliar spray with ALA significantly (P ˂ 0.01) affected plant height, number of pods per plant, pod weight, number of seeds per pod and weight of 1000 seeds, biological yield, seed yield, and harvest index. The highest total chlorophyll content was observed in plants that were subjected to supplementary irrigation in flowering and early seed filling stages and foliar sprayed with 100 ppm ALA. The study also found that exogenous ALA improved drought tolerance in lentil plants under rain-fed conditions mainly by regulating antioxidant enzymes, which ultimately protected the cellular membranes against overproduction of H2O2. Furthermore, ALA application increased total carbohydrate contents at all supplemental irrigation levels, but the rate was higher in complementary irrigation conditions during flowering and early seed-filling stages. Malondialdehyde (MDA), H2O2, and proline contents were increased in field-grown plants under rain-fed conditions without exogenous ALA application. In conclusion, this study sheds light on the effects of ALA foliar spray and supplemental irrigation on lentil growth, yield, and physiological parameters. The findings suggest that exogenous ALA can improve plant tolerance to various abiotic stressors and enhance plant growth, yield, and physiological parameters.

Rainwater harvesting for agriculture development using multi-influence factor and fuzzy overlay techniques

Rainwater harvesting (RWH) is an essential technique for enhancing agricultural development, particularly in regions facing water scarcity or unreliable rainfall patterns. Water shortage, however, is one of the key causes of low crop production especially in mountainous regions like the Khyber Pakhtunkhwa province where most rainwater is lost by runoff. Therefore, rainwater harvesting could be a suitable to make better use of runoff and increase crop production. The study focuses on selecting suitable rainwater harvesting sites in District Karak to enhance agriculture by utilizing multi-influence factor (MIF) and fuzzy overlay techniques. We considered seven factors, i.e., land use land cover (LULC), slope, geology, soil, rainfall, lineament, drainage density, to create a ranking system to understand its application in site selection analysis. The results were combined into one overlay process to produce a rainwater harvesting suitability map. The weighted overlay analysis of the MIF model results reveals that 167.96 km2 area has a very high potential for rainwater harvesting, 874.17 km2 has a high potential, 1182.92 km2 has a moderate and 354.50 km2 has a poor potential for rainwater harvesting. The fuzzy overlay analysis revealed that 257.53 km2 has a very high potential for rainwater harvesting, 896.56 km2 area is classified as high, 1018.30 km2 moderate, and 407.7 km2 has poor potential for rainwater harvesting. The findings of this research work will help the policymakers and decision-makers construct various rainwater harvesting structures in the study area to overcome the water shortage problems.

Discharge dynamics of agricultural diffuse pollution under different rainfall patterns in the middle Yangtze river

Rainfall plays a crucial role in influencing the loss of agricultural diffuse pollution. The middle Yangtze River region is well-know for its humid climate and numerous agricultural activities. Thus, this study quantitatively analyzed the concentration and distribution of nitrogen (N) and phosphorus (P) load and loss in a major tributary of the middle Yangtze River under different rainfall patterns by using sampling analysis and SWAT model simulation. The total nitrogen (TN) and nitrate-nitrogen (NO3-) concentrations were 1.604-3.574 and 0.830-2.556 mg/L, respectively. The total phosphorous (TP) and Soluble Reactive Phosphorus (SRP) were 2-148 and 2-104 μg/L, respectively. The modeling results demonstrated that higher rainfall intensity led to greater load and loss flux of diffuse pollutant at the outlet. Organic nitrogen (ORGN) is the main nitrogen form transported from the subbasin to the reach, while organic phosphorus (ORGP) and inorganic phosphorus (INORGP) were transported at similar amounts. Under the condition of conventional rainfall, the outlet reaches mainly transported NO3-, and ORGN gradually increased when rainstorm events occurred. The ratio of INORGP to ORGP was relatively stable. During extreme rainfall event, rainfall is the dominant element of agricultural diffuse pollution. A strong positive correlation exists between rainfall intensity and pollution loss during rainstorms. Storm rain events were the main source of TN and TP losses. Few storm rain days generated pollutants that accounted for a large proportion of the total loss, and their impact on TP loss was significantly greater than that of TN. The influence of storm rain on TN is mainly the increase in runoff, while TP is sensitive to the runoff and sediment transport promoted by rainfall. By setting different precipitation scenarios, it was confirmed that under the same rainfall amount, short-term storm rain has the most significant impact on the TN load, whereas TP load may be influenced more by the combined effects of rainfall duration and intensity. Therefore, to reduce the impact of agricultural diffuse pollution, it is important to take targeted measures for the rainstorm days.

Long-term rain exclusion in a Mediterranean forest: response of physiological and physico-chemical traits of Quercus pubescens across seasons

With climate change, an aggravation in summer drought is expected in the Mediterranean region. To assess the impact of such a future scenario, we compared the response of Quercus pubescens, a drought-resistant deciduous oak species, to long-term amplified drought (AD) (partial rain exclusion in natura for 10 years) and natural drought (ND). We studied leaf physiological and physico-chemical trait responses to ND and AD over the seasonal cycle, with a focus on chemical traits including major groups of central (photosynthetic pigments and plastoquinones) and specialized (tocochromanols, phenolic compounds, and cuticular waxes) metabolites. Seasonality was the main driver of all leaf traits, including cuticular triterpenoids, which were highly concentrated in summer, suggesting their importance to cope with drought and thermal stress periods. Under AD, trees not only reduced CO2 assimilation (-42%) in summer and leaf concentrations of some phenolic compounds and photosynthetic pigments (carotenoids from the xanthophyll cycle) but also enhanced the levels of other photosynthetic pigments (chlorophylls, lutein, and neoxanthin) and plastochromanol-8, an antioxidant located in chloroplasts. Overall, the metabolomic adjustments across seasons and drought conditions reinforce the idea that Q. pubescens is highly resistant to drought although significant losses of antioxidant defenses and photoprotection were identified under AD.

Plants alter their aboveground and belowground biomass allocation and affect community-level resistance in response to snow cover change in Central Asia, Northwest China

It is important to elucidate the changing distribution pattern of net primary productivity (NPP) to mechanistically understand the changes in aboveground and belowground ecosystem functions. In water-scarce desert environments, snow provides a crucial supply of water for plant development and the spread of herbaceous species. Yet uncertainty persists regarding how herbaceous plants' NPP allocation responds to variation in snow cover. The goal of this study was to investigate how variation in snow cover in a temperate desert influenced the NPP allocation dynamics of herbaceous species and their resistance to environmental change in terms aboveground and belowground productivity. In the Gurbantunggut Desert, wintertime snow cover depth was adjusted in plots by applying four treatments: snow removal (-S), ambient snow, double snow (+S), and triple snow (+2S). We examined their species richness, aboveground NPP (ANPP), belowground NPP (BNPP), and the resistance of ANPP and BNPP. We found that species diversity of the aboveground community increased significantly with increasing snow cover and decreased significantly Pielou evenness in plots. This resulted in greater ANPP with increasing snow cover; meanwhile, BNPP first increased and then decreased with increasing snow cover. However, this productivity in different soil layers responded differently to changed snow cover. In the 0-10 cm soil layer, productivity first rose and then declined, while it declined linearly in both the 10-20 cm and 20-30 cm soil layers, whereas in the 30-40 cm soil layer it showed an increasing trend. Belowground resistance would increase given that greater snow cover improved the BNPP in deeper soil and maintained the resource provisioning for plant growth, thus improving overall belowground stability. These results can serve as a promising research foundation for future work on how the functioning of desert ecosystems becomes altered due to changes in plant community expansion and, in particular, changes in snow cover driven by global climate change.

Chemical risks in drinking water of inhabitants in the basin of the Tonle Sap Great Lake

The present study aimed to assess chemical risks in the drinking water of inhabitants in the basin of the Tonle Sap Great Lake. Water samples from tube wells (n = 52), dug wells (n = 13), stored rain water (n = 39), ponds/lakes (n = 19), canals/rivers (n = 24), and household pipe water (n = 45) were collected and analyzed for physicochemical properties, as well as microbial and chemical qualities using standard methods. Analytical results revealed that 42.1% of tube wells had As > 10 μg L-1 while 8.3% had Cr > 0.05 mg L-1. Concurrently, 55.2 and 11.8% of tube wells had Cd > 3.00 μg L-1 and Pb > 10 μg L-1, respectively. Moreover, 35.0% of pipe water had Fe > 0.3 mg L-1, whereas 85.7% of tube wells and 69.2% of dug wells had Mn > 0.1 mg L-1. All water sources including pipe water could pose risks of non-carcinogenic effects of chemical mixtures to all exposure groups through their drinking water pathway. Children were at a higher risk of chemical mixtures in their drinking water than adults. This study suggests that advanced treatment technologies should be applied to the current water treatment plants to provide inhabitants with safe drinking water.

Stormwater reuse for water-sensitive city - Integrated analysis of urban hydrology for efficient alternatives of Amaravati city, India

In the present study, Amaravati, a proposed city of Andhra Pradesh, India, is identified for stormwater reuse analysis and for various efficient options for reuse. Peak runoff from the entire catchment is determined for the management of stormwater using different models such as soil and water assessment tool (SWAT), stormwater management model, and intensity-duration-frequency curves by the log Pearson Type III method. Further, the bio-retention cell low-impact development option with 60% impervious area, 60% zero depression impervious area, bio-retention cell for 40% area for each sub-catchment, and the underground stormwater network system, for part of peak runoff reduction, remaining peak runoff is considered for reuse. The remaining peak runoff is proposed to be reused for irrigation purposes (option 1), and storage retention ponds as extended detention ponds (option 2). Also, in situ storage/percolation is recommended for unaccounted stormwater within or around each premise. The findings can help to propose, implement, and maintain various stormwater reuse measures and/or practices for any city.

Flow field and sediment removal in a stormwater sump utilizing internal structures

This study investigated the hydraulic characteristics of stormwater sumps and their design optimization for sediment retention using physical experiments. Particle image velocimetry was utilized to measure the flow field, and the use of internal structures was investigated for improving solids retention. Results indicate that these internal structures can significantly improve the sediment removal efficiency of suspended solids with an average size of 125 μm, resulting in an efficiency improvement of 20-30%. Additionally, a modified Péclet number was proposed to more accurately evaluate the sediment removal efficiency of stormwater sumps, and recommendations were provided for further improving and optimizing sump design. This study provides insights into the hydraulic characteristics of stormwater sumps and has important implications for optimizing and designing particle removal systems for various industrial and environmental applications.

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

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

A closed-loop analysis approach for ensuring stormwater source control design solution to achieve the intended goals

Stormwater source controls have been adopted worldwide to address hydrological and environmental impairments caused by the spread of impervious surfaces in cities. Current design method in China uses 30-year daily rainfall records to generate relationship of rainfall volume capture ratio (αg) and daily design storm, and then uses design storm to propose design solution. However, source control performance differs from rain to rain, and hence the design solution's actual effect may deviate from αg. Borrowing closed-loop feedback concept from business domain, this study proposes closed-loop analysis (CLA) which uses design solution's 30-year simulated result as data feedback to check design solution's effectiveness and then make improvements if necessary. It consists of four methods: 1) hourly design storm statistical method, for addressing the weakness of current daily design storm; 2) design solution model credibility examination method, for guaranteeing credibility of 30-year simulated results for CLA; 3) appropriate design storms determination method for source control without underdrain; 4) additional design parameters optimization method for source control with underdrain. Taking Xiamen city for example, case study results shows that design solution's 30-year simulated results were consistent/comparable with sizing calculation formula that was used to propose design solution, and therefore they were credible for CLA. Appropriate design storms ensured design solutions without underdrain to achieve the intended αg±3 %. Optimal design parameters combinations ensured design solutions with underdrain to achieve αg but also restore natural runoff events with pre- and post-development runoff frequency spectra similarity being 0.670-0.691. Based on stormwater mathematical model, CLA can drive source control design computation to a new methodological stage.

Identification of suitable sites for rainwater and storm water harvesting through spatial analysis and smart sustainable urban water infrastructure in Lahore, Pakistan

Sustainable and water-wise cities maintain an eco-friendly urban hydrological cycle (UHC). Regrettably, the UHC of Pakistani cities is not consistently eco-friendly. Pakistan is situated within the influential area of the world's largest monsoon weather system. Cities like Lahore face simultaneous vulnerabilities to urban flooding and water scarcity due to extreme climate change events. Therefore, Pakistan's urban areas necessitate Urban Water Infrastructural Transformation (UWIT), achievable only after identifying suitable Rainwater and Stormwater Harvesting Potential Sites (RSWHPS) in Lahore. Hence, we conducted spatial analysis to pinpoint these RSWHPS within Lahore city for 2020, utilizing the World View Water Index (WV-WI). The results indicate 85.54 km2 of available areas for rain and stormwater harvesting potential during monsoon rains in Lahore. The area with the highest potential in Lahore is Wagha town, featuring 19.96 km2 of stagnant water. Additionally, RSWHPS is classified into four categories based on potential: high, medium, low, and water bodies in Lahore. Urgent transformation is required for the identified storm and rainwater harvesting sites. Consequently, this study will serve as a snapshot for policymakers to systematically address water shortage and urban flooding, making Lahore's hydrological cycle eco-friendly and sustainable.

Nitrogen removal performance of bioretention cells under polyethylene (PE) microplastic stress

The use of bioretention cells as a stormwater control measure allows stormwater runoff to be collected and filtered, effectively removing microplastics and other pollutants from stormwater. This study investigated the effect of polyethylene microplastics (PE-MPs) retention on the bioretention cell, in terms of denitrification performance and microbial community structure. Four PE-MP exposures were compared at different concentrations of 0, 250, 500 and 1000 mg/L under alternating dry and wet period conditions. Results showed that the removal efficiency reduced by 14.99%, 28.37% and 18.59% with PE-MP concentrations of 250, 500 and 1000 mg/L. The NO3--N removal efficiency increased by 36.19%, 20.19% and 35.39%. After 8 days of dry conditions, the NO3--N removal efficiencies of the bioretention cells were reduced by 36.66%, 46.86% and 31.11% compared to those after 2 days of dry conditions. Microbial sequencing results indicated that the accumulation of PE-MPs changed the microbial community structure within the bioretention cell filler material, promoting the growth of bacteria such as Actinobacteria, Bacteroidetes and Firmicutes. Furthermore, PE-MPs reduced the relative abundance of nitrifying bacteria (e.g. Nitrospira) within the bioretention cell and promoted denitrifying bacteria (e.g. Dechloromonas and Hydrogenophaga), along with numerous other genera such as Azotobacter and Nocardia.

[Water-holding characteristics of litter and soil and the influencing factors after individual rainfall]

To clarify the water-holding characteristics of forest litter and soil, different densities (0, 300, 600, 900 g·m-2) of Pinus tabuliformis litter were covered on the typical soil surface of loess cinnamon and calcareous cinnamon in north China. Based on an artificial simulated rainfall experiment, we observed the variation of litter and soil water content with time, and analyzed the variation process and influencing factors of litter and soil water content after rainfall. The results showed that water content of P. tabuliformis litter decreased significantly with the increases of duration after the rainfall, and that the range of litter water contents under all treatments was 22.9%-71.0%. There was a decreasing exponential function between the decline rate and time. Litter water content was only affected by litter density. The higher the litter density, the greater the decreasing rate of litter water content. Soil water content fluctuated and decreased with the increases of duration after the rainfall, with a variation of 1.5%-8.5%. Soil water-holding capacity was affected by litter density, soil type, and slope position. Litter could effectively reduce the fluctuation of soil water. The higher litter density, the smaller the coefficient of variation of soil water content, the greater the effect of litter on soil water fluctuation, and the better the soil water-holding capacity. The water-holding capacity on loess cinnamon soil was significantly higher than that of calcareous cinnamon soil. Soil water-holding capacity on the downslope was significantly higher than that on the upslope and middle slope, without any difference between upslope and middle slope.

Inflow and infiltration assessment of a prototype sanitary sewer network in a coastal city in China

A 16-month monitoring program was conducted on a prototype sanitary system in a coastal city in China. The groundwater infiltration (GWI) on dry weather days and the rain-derived inflow and infiltration (RDII) on wet weather days were quantified and analyzed. The proportion of monthly averaged GWI to total flow can be as high as 70% during the observation period mainly due to the high groundwater level. The results also show that the ratio of RDII volume to total rainfall volume (defined as R-value) reaches a limited value of approximately 10% for the studied system when the total rainfall depth increases. A reference indicator Rlim for the limited R-value was proposed for assessing the conditions of sewer systems in terms of RDII. The Rlim value depends on local sewer conditions and in general, a lower Rlim value represents a better performance on RDII and vice versa. This study enriches the case studies on the performance of a specific sanitary sewer system on inflow and infiltration in a typical coastal city with exceptionally high groundwater levels, excess rainfall events in the monitoring season and possible typhoon events, which addresses the unique locational and hydrological properties of a representative coastal city.

BioRTC model enables exploration of real time control strategies for stormwater biofilters

Biofilters with real time control (RTC) have great potential to remove microbes from stormwater to protect human health for uses such as swimming and harvesting. However, RTC strategies need to be further explored and optimised for each specific location or end-use. This paper demonstrates that the newly developed BioRTC model can fulfil this requirement and allow effective and efficient exploration of the potential of RTC applications. We describe the development of BioRTC as the first RTC model for stormwater biofilters, including: selection of a 'base' model for microbial removal prediction, its modification to include RTC capabilities, as well as calibration and validation. BioRTC adequately predicted the performance of two previously developed RTC strategies, with Nash Sutcliffe Efficiency (Ec) ranging from 0.65 to 0.80. In addition, high parameter transferability was demonstrated during model validation, where we employed the parameter sets calibrated for another biofilter study without RTC to predict the performance of RTC biofilters. We then employed the BioRTC model to explore RTC applications on a hypothetical biofilter system located at the outlet of an existing catchment. With different scenarios, we tested the impact of input parameters such as RTC set-points and design characteristics, and evaluated the influence of operational conditions on the microbial removal performance of the hypothetical biofilter with RTC. The results showed that strategy rules, set-point values, and biofilter design all govern the performance of RTC biofilters, and that operational conditions could impact the suitability of different RTC strategies. Particularly, the presence of Pareto fronts established that muti-objective optimisation is necessary to balance competing needs. These results underscore the importance of RTC, which allows for local experimentation, climate change adaptation, and adjustment to changing demands for the harvested water. Furthermore, they illustrate the practical use of the newly developed BioRTC model, enabling researchers and practitioners to explore and assess potential RTC strategies and scenarios quickly and cost-effectively.

An alternative for predicting real-time water levels of urban drainage systems

Storm Water Management Model (SWMM) developed by the United States Environmental Protection Agency (EPA) has been widely applied throughout the world for analysis associated with stormwater runoff, combined sewers, and other drainage facilities. To appropriately manage the runoff in urban areas, an integrated system including the simulations of sewer flow, street flow, and regional channel flow, called the 1D/1D SWMM model, was advocated to be performed. Nevertheless, the execution efficiency of this integrated system still needs to be promoted to meet the demand for real-time forecasting of urban floods. The objective of this study is to seek an alternative for predicting water levels both in the sewer system and on the streets within an urban district during rainstorms by utilizing a dynamic neuron network model. To strengthen the physical structure of the artificial intelligence (AI) model and simultaneously make up for the lack of measured data, simulation results of the 1D/1D SWMM model are provided as labels for the training of the proposed model. The novelty of this research is to propose a new methodology to effectively train the AI model for predicting the spatial distributions of depths based on the hydrologic conditions, geomorphologic properties, as well as the network relation of the drainage system. A two-stage training procedure is proposed in this study to consider more possible inundation conditions in both sewer and street (open channel) drainage networks. The research findings show that the proposed methodology is capable of reaching satisfactory accuracy and assisting the numerical-based SWMM model for real-time warning of drainage systems in the urban district.

Component design optimization of green roof substrate layer based on the assessment of multifunctional performance

A high-quality substrate layer is the cornerstone of supporting that green roofs (GRs) can become an efficient and sustainable nature-based solution to urban environmental problems. In the present study, three lightweight substrate materials commonly used in GRs of peat soil, vermiculite and pumice with four appropriate proportions of the nutrient substrate and the mineral substrates were selected to install twelve substrate modules. The lightweight property, water-holding, nutrient retention and rainwater reduction performance of the substrate modules were investigated by the laboratory determination methods and the simulated rainfall experiment. An assessment model based on the multifunctional performance established by analytic hierarchy process (AHP) was used for the component design optimization of GR substrate layer. The results showed that the substrate modules based on peat soil and vermiculite (PV) as the mineral substrate, which the dry volumetric weights and the average water content were 1.40-1.70 kN m-3 and 47.80%-49.06%, always exhibited better lightweight properties and water-holding performance compared to those composed of pumice. PV-40 had the highest value of the multifunction index even while none of its functional performance was optimal among all the substrate modules. The present study emphasizes the necessity of optimizing the GR substrate layer component based on the assessment of multifunctional performance to better promote the sustainable development of GRs in urban areas.

Estimating rainfall interception loss of three dominant shrub species in an oasis-desert ecotone using in situ measurements and the revised Gash analytical model

Canopy interception loss affects the local water budget by removing a non-negligible proportion of rainfall from the terrestrial surface. Thus, quantifying interception loss is essential for thoroughly understanding the role of vegetation in the local hydrological cycle, especially in dryland ecosystems. However, sparse shrubs in dryland ecosystems have not been sufficiently studied, owing to time- and labor-intensive field experiments and challenging model parameterization. In this work, 4-year growing season field experiments on rainfall partitioning were conducted for three dominant shrub species (Haloxylon ammodendron, Nitraria sphaerocarpa, and Calligonum mongolicum) in an oasis-desert ecotone in northwestern China. The revised Gash analytical model was well parameterized, which reliably simulated the cumulative interception loss for sparse shrubs, and the validated model performed better for H. ammodendron, followed by C. mongolicum and N. sphaerocarpa, with relative errors of 8.4%, 15.4%, and 23.9%, respectively. The mean individual interception loss percentage for H. ammodendron (28.4%) was significantly higher than that for C. mongolicum (11.0%) and N. sphaerocarpa (10.9%) (p < 0.05), which could be ascribed to the higher canopy storage capacity and wet-canopy evaporation rate of H. ammodendron. For all shrub species, the majority proportion of interception loss occurred during canopy saturation and drying-out periods, accounting for approximately 79-85% of the cumulative interception loss. Overall, the mean local interception loss of three dominant shrub species in the ecotone removed nearly 17% of the corresponding cumulative rainfall during the growing season. These results not only provide methodological references for estimating the interception loss of sparse vegetation in dryland ecosystems, but also provide scientific insights for water resource management and ecosystem restoration in water-limited regions similar to the experimental site.

Revising the global biogeography of annual and perennial plants

There are two main life cycles in plants-annual and perennial1,2. These life cycles are associated with different traits that determine ecosystem function3,4. Although life cycles are textbook examples of plant adaptation to different environments, we lack comprehensive knowledge regarding their global distributional patterns. Here we assembled an extensive database of plant life cycle assignments of 235,000 plant species coupled with millions of georeferenced datapoints to map the worldwide biogeography of these plant species. We found that annual plants are half as common as initially thought5-8, accounting for only 6% of plant species. Our analyses indicate that annuals are favoured in hot and dry regions. However, a more accurate model shows that the prevalence of annual species is driven by temperature and precipitation in the driest quarter (rather than yearly means), explaining, for example, why some Mediterranean systems have more annuals than desert systems. Furthermore, this pattern remains consistent among different families, indicating convergent evolution. Finally, we demonstrate that increasing climate variability and anthropogenic disturbance increase annual favourability. Considering future climate change, we predict an increase in annual prevalence for 69% of the world's ecoregions by 2060. Overall, our analyses raise concerns for ecosystem services provided by perennial plants, as ongoing changes are leading to a higher proportion of annual plants globally.

Effects of ENSO events on the intensity, seasonality, and diversity of reproductive phenology of Miconia (Melastomataceae) species in tropical rainforest

We evaluated the phenology and reproductive phenological diversity of three sympatric species of Miconia in a gallery forest in the Chapada Diamantina mountains, Bahia, Brazil. The reproductive phenophases (bud, flower, immature fruit, and mature fruit) of M. alborufescens (N=38), M. holosericea (N=46), and M. prasina (N=44) were evaluated monthly, between June/2008 and June/2015. The Fournier index was used to assess the intensities of the reproductive phenophases; synchrony and seasonality were analyzed using circular statistics and the Rayleigh (Z) test. The Frideman and Wilcoxon tests were used to verify interannual variations in phenological patterns. Reproductive phenological diversity was measured by calculating the Shannon-Wiener index; ANOVA tested possible differences in the means of diversity among the different years. The reproductive phenophases of the studied Miconia species occurred sequentially (M. alborufescens, then M. holoserica, followed by M. prasina), in the transition between the dry and rainy seasons, with little overlap between them. In general, the species showed seasonal and synchronic phenological patterns, with some variations that coincided with El Niño and/or La Niña events, e.g., demonstrating changes in the periodicity, synchrony, and intensity of their phenophases. The intensity of fruiting, for example, showed increases during La Niña years. Reproductive phenological diversity appears to respond to climate changes resulting from El Niño events and periods of prolonged drought, with high Shannon-Wiener index values. The results also suggest that the effects of global climatic phenomena (El Niño and La Niña) that alter regional climatic seasonality can also cause variations in the reproductive phenological rhythms of the Miconia species studied.

Association between environmental factors and dengue incidence in Lao People's Democratic Republic: a nationwide time-series study

BACKGROUND

Dengue fever is a vector-borne disease of global public health concern, with an increasing number of cases and a widening area of endemicity in recent years. Meteorological factors influence dengue transmission. This study aimed to estimate the association between meteorological factors (i.e., temperature and rainfall) and dengue incidence and the effect of altitude on this association in the Lao People's Democratic Republic (Lao PDR).

METHODS

We used weekly dengue incidence and meteorological data, including temperature and rainfall, from 18 jurisdictions in Lao PDR from 2015 to 2019. A two-stage distributed lag nonlinear model with a quasi-Poisson distribution was used to account for the nonlinear and delayed associations between dengue incidence and meteorological variables, adjusting for long-term time trends and autocorrelation.

RESULTS

A total of 55,561 cases were reported in Lao PDR from 2015 to 2019. The cumulative relative risk for the 90th percentile of weekly mean temperature (29 °C) over 22 weeks was estimated at 4.21 (95% confidence interval: 2.00-8.84), relative to the 25th percentile (24 °C). The cumulative relative risk for the weekly total rainfall over 12 weeks peaked at 82 mm (relative risk = 1.76, 95% confidence interval: 0.91-3.40) relative to no rain. However, the risk decreased significantly when heavy rain exceeded 200 mm. We found no evidence that altitude modified these associations.

CONCLUSIONS

We found a lagged nonlinear relationship between meteorological factors and dengue incidence in Lao PDR. These findings can be used to develop climate-based early warning systems and provide insights for improving vector control in the country.

The effects of precipitation change on urban meadows in different design models and substrates

Climate change, such as temperature and precipitation changes, is becoming increasingly obvious, and in this context, planting designs need to urgently consider future climate change in advance. A field experiment was conducted in Beijing, China, where the future precipitation is predicted to increase, and extra irrigation was used to simulate the future precipitation increase. The species richness of sown meadows, including spontaneous plants and sown plants, and the adaptive strategies of the communities were recorded under different types of design models and substrates. The results showed that precipitation increased the diversity of sown plants and resource-demanding spontaneous plants but had no significant effect on the dry matter content of the entire community of species. Moreover, the interactions among precipitation and substrate, especially the design models, were significant. Of the models, the three-layer model had the highest species richness and least invasive plants. In addition, increased precipitation significantly changed the functional strategy of the plant community away from ruderals and towards competitor-stress tolerant species. This study provides guidance for the design and management of naturalistic plant communities under climate change.

Impact-based seasonal rainfall forecasting to trigger early action for droughts

The Horn of Africa faces an ongoing multi-year drought due to five consecutive failed rainy seasons, a novel climatic event with unpreceded impacts. Beyond the starvation of millions of livestock, close to 23 million individuals in the region are currently facing high food insecurity in Kenya, Somalia and Ethiopia alone. The severity of these impacts calls for the urgent upscaling and optimisation of early action for droughts. However, drought research focuses mainly on meteorological and hydrological forecasting, while early action triggered by forecasts is seldom addressed. This study investigates the potential for early action for droughts by using seasonal forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) SEAS5 system for the March-April-May (MAM) and October-November-December (OND) rainy seasons. We show that these seasonal rainfall forecasts reflect major on-the-ground impacts, which we identify from drought surveillance data from 21 counties in Kenya. Subsequently, we show that the SEAS5 drought forecasts with short lead times have substantial potential economic value (PEV) when used to trigger action before the OND season across the region (PEVmax = 0.43). Increasing lead time to one or two months ahead of the season decreases PEV, but the benefits persist (PEVmax = 0.2). Outside of Kenya, MAM forecasts have limited value. The existence of opportunities for early action during the OND season in Kenya and Somalia is demonstrated by high PEV values, with some regions recording PEVmax values close to 0.8. To illustrate the practical value of this research, we point to a dilemma that a pastoralist in the Kenyan drylands faces when deciding whether to adopt early livestock destocking. This study underscores the importance to determine the value of early actions for forecast users with different action characteristics, and to disseminate this value alongside the standard forecasts themselves. This allows users to trigger effective actions before drought impacts develop.

Evaluating the effectiveness of spontaneous vegetation for stormwater mitigation on green roofs

Green roofs can reduce stormwater runoff in urban areas by capturing rainfall. The extent of this capture is partially influenced by vegetation type and cover, which can be manipulated to optimise run-off reduction. However, in the absence of routine maintenance, planted green roof vegetation is often replaced by 'weedy' spontaneous species with unknown rainfall retention qualities. To better understand the role of spontaneous vegetation in green roof stormwater mitigation, we undertook a 100-day rainfall simulation involving 14 plant species that occur spontaneously on green roofs in Mediterranean-type climates. Green roof modules were filled with either 7 cm (shallow) or 14 cm (deep) substrate. The substrate was either left bare or sown with the spontaneous species community, which established approximately 100 % cover prior to the beginning of the rainfall simulation. During the simulation, modules were subjected to a "dry" and then a "wet" rainfall phase, each based on historical climate records from Melbourne, Australia. The "dry" treatment replicated the timing and depth of the driest rainfall period on record, while the "wet" treatment applied rainfall depths randomly selected from the 90th, 95th, and 99th percentiles of recorded rainfall. Rainfall retention, evapotranspiration, time to initiation of runoff and soil water content was measured for 17 rainfall events. Spontaneous vegetation cover and both species and functional diversity were measured at the end of each rainfall phase, and biomass was measured at the end of the wet phase. During the dry phase, modules with spontaneous vegetation cover retained 88 % of applied rainfall regardless of substrate depth and had 6 % greater retention than bare substrate. During the wet phase, deep substrate modules with spontaneous vegetation cover had 30 % greater retention than other treatment combinations. At the end of the wet phase, spontaneous vegetation in deep substrate had 42 % greater biomass, 19 % greater coverage and more than twofold greater functional richness than in shallow substrate. These findings demonstrate that spontaneous vegetation can increase stormwater retention on green roofs relative to bare substrate and have similar retention performance to commonly utilised species. However, the extent to which stormwater mitigation on green roofs is enhanced by spontaneous vegetation is dependent on factors that are more important for rainfall retention, such as substrate depth and rainfall patterns.

Design and spatial pattern optimization for a sponge city using factor analysis and geographical statistics to restore urban resilience: A case study in a coastal area of China

The sponge city is a new concept of stormwater management for ecological city construction, which aims to restore water-cycle processes and reduce runoff. Cities in coastal districts are suffering from serious instability due to high population density, urbanization, and land-use changes. However, previous research contains few evaluations of balancing urban ecological indicators of sponge city performance, including geographical, environmental, economic, and social factors, and their effect on resilience at a macro level to develop low-impact development schemes. In this study, we developed an integrated framework using factor analysis, geographical statistics, multi-objective analysis, and remote sensing methods to extract the factors influencing sponge city resilience and to establish spatial pattern schemes. The results indicated that the urbanization degree and plant adaptability had the greatest impact on sponge city performance, with weights of 45 and 27%, respectively. Sponge city spatial pattern schemes performed the best in the combination scenario of 14.8-46.8% green roofs (by area ratio) supported by grooves and rain barrels +10% herbaceous basins divided into units by ecological tree pools +10% permeable pavements and sidewalks. This scenario balanced facilities and cost to optimize the spatial pattern, which improved sponge city adaptability and urban ecological conditions.

The efficacy of hydrogen sulfide (H2S) tests for detecting microbial contamination in rooftop-harvested rainwater

As climate change strains the world's freshwater resources, access to safe and clean water becomes limited. The use of alternative water sources, such as rooftop-harvested rainwater, has become one mechanism to address freshwater scarcity in the American Southwest, particularly when it comes to home gardening. The University of Arizona's Project Harvest, in partnership with the Sonora Environmental Research Institute, Inc., is a multi-year, co-created citizen science project aimed at increasing current understanding of harvested rainwater quality. Citizens in four Arizona, USA, communities (Hayden/Winkelman, Globe/Miami, Dewey-Humboldt, and Tucson) submitted harvested rainwater samples over 3 years. The harvested rainwater samples were then analyzed using IDEXX Colilert® for total coliforms and E. coli and using Hach PathoScreen™ test for sulfate-reducing bacteria (SRB). This study design allows for the validation of a low-cost, at-home alternative methodology for testing rainwater for bacteria that may indicate fecal contamination. In total, 226 samples were tested using both methodologies, revealing a positive correlation (r=0.245; p<0.002) between total coliform MPN and SRB MPN, but no discernable correlation between E. coli MPN and SRB MPN. This work indicates a potential value of SRB testing for harvested rainwater if cost, laboratory access, and fecal contamination are of concern.

Monitoring spore washoff during a biological contamination incident response using automated stormwater samplers and sensors to predict contamination movement

This study examined the washoff of Bacillus globigii (Bg) spores from concrete, asphalt, and grass surfaces by stormwater. Bg is a nonpathogenic surrogate for Bacillus anthracis, which is a biological select agent. Areas (2.74 m × 7.62 m) of concrete, grass, and asphalt were inoculated twice at the field site during the study. Spore concentrations were measured in runoff water after seven rainfall events (1.2-65.4 mm) and complimentary watershed data were collected for soil moisture, depth of water in collection troughs, and rainfall using custom-built telemetry units. An average surface loading of 107.79 Bg spores/m2 resulted in peak spore concentrations in runoff water of 102, 260, and 4.1 CFU/mL from asphalt, concrete, and grass surfaces, respectively. Spore concentrations in the stormwater runoff were greatly reduced by the third rain event after both inoculations, but still detectable in some samples. When initial rainfall events occurred longer after the initial inoculation, the spore concentrations (both peak and average) in the runoff were diminished. The study also compared rainfall data from 4 tipping bucket rain gauges and a laser disdrometer and found they performed similarly for values of total rainfall accumulation while the laser disdrometer provided additional information (total storm kinetic energy) useful in comparing the seven different rain events. The soil moisture probes are recommended for assistance in predicting when to sample sites with intermittent runoff. Sampling trough level readings were critical to understanding the dilution factor of the storm event and the age of the sample collected. Collectively the spore and watershed data are useful for emergency responders faced with remediation decisions after a biological agent incident as the results provide insight into what equipment to deploy and that spores may persist in runoff water at quantifiable levels for months. The spore measurements are also a novel dataset for stormwater model parameterization for biological contamination of urban watersheds.

Laboratory study of the effect of vegetation and gravel on runoff parameters under variable rainfall intensities

The present study aims to evaluate the performance of the impervious surface as a control (O), sandy loam substrate (SL), gravel (G), gravel with geocell layer (GGE), rosemary (R), rosemary with geocell layer (RRE), turf (T), and turf with geocell layer (TGE) in the reduction of runoff volume, time-to-start runoff (TR), runoff coefficient (C), time-to end runoff (TER), peak flow rate (PF), time to peak (TP), and time base (TB) in the laboratory dimension under three different scenarios of rainfall intensity and two different slopes using a rainfall simulator. The results revealed a significant difference between the data at the level of 5% in all cases. Generally, three rainfall scenarios for all hydrological parameters TR, TER, TP, TB, C, and PF were classified into different groups. In all cases, GGE treatment performed better than that of the rest of the test groups in reducing runoff and cumulative volume. Further, treatments O and GGE experienced the highest and lowest flow rates, respectively. For a specific scenario of rainfall intensity and slope, the value of C is the lowest for GGE treatment. Finally, the implementation of geocell in the pavements was able to delay the time to start runoff.

Precipitation regime changes in High Mountain Asia driven by cleaner air

High Mountain Asia (HMA) has experienced a spatial imbalance in water resources in recent decades, partly because of a dipolar pattern of precipitation changes known as South Drying-North Wetting1. These changes can be influenced by both human activities and internal climate variability2,3. Although climate projections indicate a future widespread wetting trend over HMA1,4, the timing and mechanism of the transition from a dipolar to a monopolar pattern remain unknown. Here we demonstrate that the observed dipolar precipitation change in HMA during summer is primarily driven by westerly- and monsoon-associated precipitation patterns. The weakening of the Asian westerly jet, caused by the uneven emission of anthropogenic aerosols, favoured a dipolar precipitation trend from 1951 to 2020. Moreover, the phase transition of the Interdecadal Pacific Oscillation induces an out-of-phase precipitation change between the core region of the South Asian monsoon and southeastern HMA. Under medium- or high-emission scenarios, corresponding to a global warming of 0.6-1.1 °C compared with the present, the dipolar pattern is projected to shift to a monopolar wetting trend in the 2040s. This shift in precipitation patterns is mainly attributed to the intensified jet stream resulting from reduced emissions of anthropogenic aerosols. These findings underscore the importance of considering the impact of aerosol emission reduction in future social planning by policymakers.

A new approach for sensitivity analysis of the StormWater Management Model applied in an airport

Sensitivity analysis of urban flood model parameters is important for efficient and accurate flood simulation. In order to explore the problems of large sampling parameters and nonlinear correlation between input and output variables, this paper proposed a new correlation analysis approach. The type, strength, and the order of sensitive parameters to the four outputs are analyzed using the proposed approach. The results show that the R values of Manning-N are biggest, its distribution is linear in heat maps, and the Manning-N has a strong linear correlation with Average Depth, Hour of Maximum Flooding, and Time to Peak. For Average Depth, the second sensitive parameter is Conductivity. For Hour of Maximum Flooding, the second and third more sensitive parameters are Conductivity and N-perv; however, there are certain nonlinear correlations from heat maps. For Total Inflow, the R values of each parameter are between 0.021 and 0.534. Most sensitive parameters are none; however, the more sensitive parameters are Conductivity, N-perv, and initial deficit. For Time to Peak, the second and third more sensitive parameters are N-perv and N-Imperv; however, there are certain non-linear correlations from heat maps. The results can provide theoretical guidance for application and parameter calibration of SWMM in airport.

Opportunities and challenges in green stormwater infrastructure (GSI): A comprehensive and bibliometric review of ecosystem services from 2000 to 2021

The great challenges induced by global climate change coupled with rapid urbanization underline the growing urgency for a change in stormwater management with a novel integrated approach. This study conducted a comprehensive review on state-of-the-art knowledge in the research field of green storm infrastructure (GSI) using bibliometric analysis. A corpus of 3988 GSI-related publications (2000-2021) extracted from the Web of Science database was used to evaluate the scientific output in GSI research through the "Bibliometrix" R package and "CiteSpace". Ever since 2010, the number of publications per year exhibited an exponential increase, with the annual publication growth rate of 28.61%. Notably, the United States (23.55%) and China (19.58%) contributed most in GSI publications. "Water" (306) was identified as the most relevant journal in GIS research field, followed by "Sustainability" (252) and "Science of the Total Environment" (200). Cluster analysis unveiled the predominant research themes, i.e., "Conceptual development of GSI" (69.25%), "Adaptation of GSI" (46.89%), and "Performance evaluation of GSI practices" (18.28%). Research foci have generally shifted from conventional engineering-based frameworks (e.g., reduce stormwater runoff and enhance water quality) to ecological-based multi-elements (e.g., preserve natural resources, augment urban biodiversity and optimize land-use patterns). This systematic review concludes trends, challenges and future research prospects of GSI, and aims to provide reference and guidance for decision-makers on the development of a more dynamic, resilient, and robust integrated GSI approach for sustainable urban stormwater management.

Seasonal advance of intense tropical cyclones in a warming climate

Intense tropical cyclones (TCs), which often peak in autumn1,2, have destructive impacts on life and property3-5, making it crucial to determine whether any changes in intense TCs are likely to occur. Here, we identify a significant seasonal advance of intense TCs since the 1980s in most tropical oceans, with earlier-shifting rates of 3.7 and 3.2 days per decade for the Northern and Southern Hemispheres, respectively. This seasonal advance of intense TCs is closely related to the seasonal advance of rapid intensification events, favoured by the observed earlier onset of favourable oceanic conditions. Using simulations from multiple global climate models, large ensembles and individual forcing experiments, the earlier onset of favourable oceanic conditions is detectable and primarily driven by greenhouse gas forcing. The seasonal advance of intense TCs will increase the likelihood of intersecting with other extreme rainfall events, which usually peak in summer6,7, thereby leading to disproportionate impacts.

Quantifying the influence of urban road surface roughness on heavy metals pollution in road-deposited sediment's accumulation and wash-off

Surface roughness is an important factor to consider when evaluating the loads of surface runoff caused by road-deposited sediment (RDS) wash-off and creating management solutions for this occurrence in metropolitan areas. Nevertheless, the implications of surface roughness on RDS development and escape remain unclear due to a paucity of experimental evidence distinguishing the significance of surface roughness. This research aimed to differentiate the impact of surface roughness on RDS accumulation and wash-off by employing paired asphalt, rainfall simulation designs, and concrete road surfaces. Our findings indicated that normal asphalt surfaces are typically rougher than typical concrete surfaces because they frequently contain deeper depressions. Compared to concrete surfaces, asphalt surfaces typically retain more RDS, a higher proportion of coarse aggregates, more RDS wash-off loads, and a lower proportion of wash-off. Surface roughness has varying impacts on the RDS motilities of particulates of varying sizes during rainy runoff; nevertheless, the settleable particles (40-150 μm) were more noticeably impacted by it. The first flush effect also seemed to be more pronounced on surfaces with lower roughness. Hence, surface roughness has a significant impact on how RDS builds on and is washed off of various road aspects.

Review of Sponge City implementation in China: performance and policy

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

Electrocoagulation flotation as a municipal wastewater (pre-)treatment technology: Effect of weather conditions and current density

Electrocoagulation (EC) is a promising compact alternative technology, despite its viability in municipal wastewater treatment (MWWT) is currently challenged by its energy-intensive and batch-mode operation. This study introduces an innovative continuous electrocoagulation flotation (ECF) design for MWWT. ECF shows promising pollutant removal efficiencies, with identical results using both iron (Fe) and aluminum (Al) anodes. At a current density (CD) of 120 A/m2, it achieved significant removals: 90% tCOD, 98% TP, 94% TSS, 60% BOD5, and 40% TN. Designed ECF is proposed as a pre-treatment step due to limited TN removal. The study investigated optimal ECF performance under varying weather conditions using CD ranges of 40, 80, and 120 A/m2. Both Fe and Al ECF outperformed in treating rainy weather (RW) and dry weather (DW) municipal wastewater (MWW). However, Al anode's super-faradaic behavior resulted in higher residual concentrations in effluent, (i.e., an average of 6.53-33.7 mg/L), and operational costs compared to Fe ECF. Optimized Fe ECF setting needs to be changed depending in the weather variation. Fe ECF achieved high removal rates for tCOD (94%) and TP (95%) in RW MWW at a low CD of 40 A/m2. Comparative to this, the optimum CD for treated DW MWW was between 40 and 80 A/m2, removing tCOD (71-73%) and TP (85-95%). Specifically, at these conditions, the operational expenses were respectively 0.47 ± 0.03 €/m3 (RW MWW), and 0.37 ± 0.02 €/m3 to 0.81 ± 0.04 €/m3 (DW MWW). Moreover, ECF enables resource recovery and a circular economy through anaerobic sludge digestion, with Fe ECF generating more biogas than Al.

Assessing runoff control of low impact development in Hong Kong's dense community with reliable SWMM setup and calibration

Low impact development (LID) is a sustainable practice to managing urban runoff. However, its effectiveness in densely populated areas with intense rainfall, such as Hong Kong, remains unclear due to limited studies with similar climate conditions and urban patterns. The highly mixed land use and complicated drainage network present challenges for preparing a Storm Water Management Model (SWMM). This study proposed a reliable framework for setting up and calibrating SWMM by integrating multiple automated tools to address these issues. With a validated SWMM, we examined LID's effects on runoff control in a densely built catchment of Hong Kong. A designed full-scale LID implementation can reduce total and peak runoffs by around 35-45% for 2, 10 and 50-year return rainfalls. However, LID alone may not be adequate to handle the runoff in densely built areas of Hong Kong. As the rainfall return period increases, total runoff reduction increases, but peak runoff reduction remains close. Percentages of reduction in total and peak runoffs decline. The marginal control diminishes for total runoff while remaining constant for peak runoff when increasing the extent of LID implementation. In addition, the study identifies the crucial design parameters of LID facilities using global sensitivity analysis. Overall, our study contributes to accelerating the reliable application of SWMM and deepening the understanding of the effectiveness of LID in ensuring water security in densely built urban communities located near the humid-tropical climate zone, such as Hong Kong.

Nitrogen removal performance in roadside stormwater bioretention cells amended with drinking water treatment residuals

Bioretention cells, a type of green stormwater infrastructure, have been shown to reduce runoff volumes and remove a variety of pollutants. The ability of bioretention cells to remove nitrogen and phosphorus, however, is variable, and bioretention soil media can act as a net exporter of nutrients. This is concerning as excess loading of nitrogen and phosphorus can lead to eutrophication of surface waters, which green stormwater infrastructure is intended to ameliorate. Drinking water treatment residuals (DWTR), metal (hydr)oxide-rich by-products of the drinking water treatment process, have been studied as an amendment to bioretention soil media due to their high phosphorus sorption capacity. However, very few studies have specifically addressed the effects that DWTRs may have on nitrogen removal performance within bioretention cells. Here, we investigated the effects of DWTR amendment on nitrogen removal in bioretention cells treating stormwater in a roadside setting. We tested the capacity of three different DWTRs to either retain or leach dissolved inorganic nitrogen in the laboratory and also conducted a full-scale field experiment where DWTR-amended bioretention cells and experimental controls were monitored for influent and effluent nitrogen concentrations over two field seasons. We found that DWTRs alone exhibit some capacity to leach nitrate and ammonium, but when integrated into sand- and compost-based bioretention soil media, DWTRs have little to no effect on the removal of nitrogen in bioretention cells. These results suggest that DWTRs can be used in bioretention media for enhanced phosphorus retention without the risk of contributing to nitrogen export in bioretention effluent.

Changes in paleo-groundwater levels revealed by water wells and their relationship with climate variations in imperial Southern China

Based on records of the bottom elevations of 511 ancient water wells from published archaeological reports, we reconstructed the paleo-groundwater levels (PGWL) in urban areas of Chengdu, Changsha, Nanjing, Suzhou, Suqian, Yancheng, Fuzhou, and Guangzhou cities in southern China. Our PGWL reconstruction shows that PGWL varied in two patterns. In the inland monsoon region (Chengdu and Changsha), there was a low PGWL in Jin (AD 266-420) and South Song (AD 1127-1279), and a high PGWL in Tang (AD 618-907) and Ming (AD 1368-1644). In the coastal region (Yancheng, Fuzhou, and Guangzhou), there was a low PGWL in Jin (AD 266-420) and Ming (AD 1368-1644) but a high PGWL in Tang (AD 618-907) and Song (AD 960-1279). Via cross-wavelet transform and wavelet transform coherence analyses, we found that monsoon and temperature significantly drove the PGWL fluctuations at the inter-centennial scale. East Asian Summer Monsoon-induced precipitation has continuously affected cities in the inland monsoon area represented by Chengdu and Changsha over the past 2,500 years. It has also intermittently affected Nanjing and Suzhou when EASM intensified. In parallel, temperature influenced the PGWL in coastal cities such as Yancheng, Fuzhou, and Guangzhou via the changes in the sea level. Also, the temperature affected the PGWL in relatively inland cities during climatic anomalies such as the Medieval Warm Period and Little Ice Age. This study demonstrates the value of archaeological records in learning how climatic factors influence the PGWL variation and its mechanism.

Influence of geographical location and outdoor meteorological parameters on indoor humidity environment in rural residential buildings during the Plum Rains Season in the hot summer and cold winter region

Plum Rains Season (PRS) has the typical characteristics of outdoor air temperature dramatic changes and high air humidity in the hot summer and cold winter region in China. When the outdoor temperature rises rapidly during PRS, the building envelope surface temperature is probably lower than the indoor air dew point temperature, resulting in moisture condensation. This paper evaluates the influence of geographical location and outdoor meteorological parameters on the indoor humidity environment. The effects of critical parameters such as altitude, average temperature, relative humidity, total precipitation, total precipitation days, atmospheric pressure, and wind speed on the building envelope moisture condensation in nine typical cities in the hot summer and cold winter region were simulated and analyzed. The results show that the Condensation Frequency (CFn) in the western, central, and eastern regions reached the highest in April, May, and June, respectively. Among the nine typical cities, Changsha has the highest Condensation Risk (CR). In addition, the altitude, total precipitation, and atmospheric pressure have little effect on the indoor humidity environment, and it is not directly related to CR; The average temperature and total precipitation days were not related to CR in the western and eastern regions and positively correlated with CR in the central region; The wind speed was positively correlated with CR in the western and central regions and negatively correlated in the eastern region; The relative humidity can affect the indoor humidity environment and moisture condensation on the inner surface of walls, when the relative humidity increases, the CR increases.

Inter-comparison of measurements of inorganic chemical components in precipitation from NADP and CAPMoN at collocated sites in the USA and Canada during 1986-2019

Wet deposition monitoring is a critical part of the long-term monitoring of acid deposition, which aims to assess the ecological impact of anthropogenic emissions of SO2 and NOx. In North America, long-term wet deposition has been monitored through two national networks: the Canadian Air and Precipitation Monitoring Network (CAPMoN) and the US National Atmospheric Deposition Program (NADP), for Canada and the USA, respectively. In order to assess the comparability of measurements from the two networks, collocated measurements have been made at two sites, one in each country, since 1986 (Sirois et al., in Environmental Monitoring and Assessment, 62, 273-303, 2000; Wetherbee et al., in Environmental Monitoring and Assessment, 1995-2004, 2010). In this study, we compared the measurements from NADP and CAPMoN instrumentation at the collocated sites at the Pennsylvania State University (Penn State), USA, from 1989 to 2016, and Frelighsburg, Quebec, Canada, from 2002 to 2019. We also included in the study the collocated daily-vs-weekly measurements by the CAPMoN network during 1999-2001 and 2016-2017 in order to evaluate the differences in wet concentration of ions due to sampling frequency alone. The study serves as an extension to two previous CAPMoN-NADP inter-comparisons by Sirois et al. (Environmental Monitoring and Assessment, 62, 273-303, 2000) and Wetherbee et al., in (Environmental Monitoring and Assessment, 1995-2004, 2010). At the Penn State University site, for 1986-2019, CAPMoN was higher than NADP for all ions, in terms of weekly concentration, precipitation-weighted annual mean concentration, and annual wet deposition. The precipitation-weighted annual mean concentrations were higher for SO42- (2%), NO3- (12%), NH4+ (16%), H+ (6%), and base cations and Cl- (11-15%). For annual wet deposition, CAPMoN was higher for SO4-2, NO3-, NH4+ and H+ (5-17%), and base cations and Cl- (12-17%) during 1986-2019. At the Frelighsburg site, NADP changed the sample collector in October 2011. For 2002-2011, the relative differences at the Frelighsburg site were positive and similar in magnitude to those at the Penn State site. For 2012-2019, the precipitation-weighted annual mean concentrations were 5-27% lower than NADP, except for H+, which was 23% higher. The change in sample collector by NADP had the largest effect on between-network biases. The comparisons of daily-vs-weekly measurements conducted by the CAPMoN network during 1999-2001 and 2016-2017 show that the weekly measurements were higher than the daily measurements by 1-3% for SO42-, NO3-, and NH4+; 3-9% for Ca2+, Mg2+, Na+, and Cl-; 10-24% for K+; and lower for H+ by 8-30% in terms of precipitation-weighted mean concentration. Thus, differences in sampling frequencies did not contribute to the systematically higher CAPMoN measurements. Understanding the biases in the data for these networks is important for interpretation of continental scale deposition models and transboundary comparison of wet deposition trends.

Ancient Maya reservoirs, constructed wetlands, and future water needs

The Classic Maya (c. 250 to 900 CE) in the tropical southern lowlands of Central America dealt with water scarcity during annual dry seasons and periods of climate instability via sophisticated urban reservoir systems they relied on for over a thousand years. Surface water is limited because typically rain percolates through the karstic terrain. I posit that Maya reservoirs functioned as do constructed wetlands (CWs) at present. Still-water systems like CWs and Maya reservoirs can become stagnant and nonpotable due to the build-up of nutrients that promote algal growth. Stagnant waters also serve as breeding grounds for mosquitoes that spread endemic diseases. CWs keep water clean via certain aquatic plants since all plants uptake nutrients (e.g., nitrogen, phosphorus) and decomposing plant matter supports microbial biofilms that break down nutrients. CWs also support diverse zooplankton that prey on pathogens and bacteria that assist to denitrify water. CWs do not require the use of chemicals or fossil fuels and after the initial labor-intensive output become self-cleaning and self-sufficient with some maintenance. I posit that the Maya used a diverse array of aquatic plants and other biota to keep water clean in the same manner as do CWs, which I demonstrate using evidence from excavations and settlement maps, sediment cores and current wetlands, and the iconographic and hieroglyphic records. The next step is to combine what we know about ancient Maya reservoirs in conjunction with what is currently known about CWs to better address future water needs.

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.

Assessing the effectiveness of nature-based solutions-strengthened urban planning mechanisms in forming flood-resilient cities

Cities have experienced rapid urbanization-induced harsh climatic events, especially flooding, inevitably resulting in negative and irreversible consequences for urban resilience and endangering residents' lives. Numerous studies have analyzed the effects of anthropogenic practices (land use changes and urbanization) on flood forecasting. However, non-structural mitigation's effectiveness, like Nature-Based Solutions (NBS), has yet to receive adequate attention, particularly in the Middle East and North Africa (MENA) region, which have become increasingly significant and indispensable for operationalizing cities efficiently. Therefore, our study investigated the predictive influence of incorporating one of the most common NBS strategies called low-impact development tools (LID) (such as rain gardens, bio-retention cells, green roofs, infiltration trenches, permeable pavement, and vegetative swale) during the urban planning of Alexandria, Egypt, which experiences the harshest rainfall annually and includes various urban patterns. City characteristics-dependent 14 LID scenarios were simulated with recurrence intervals ranging from 2 to 100 years using the LID Treatment Train Tool (LID TTT), depending on calibrated data from 2015 to 2020, by the Nash-Sutcliffe efficiency index and deterministic coefficient, and root-mean-square error with values of 0.97, 0.91, and 0.31, respectively. Our findings confirmed the significant effectiveness of combined LID tools on total flood runoff volume reduction by 73.7%, revealing that different urban patterns can be used in flood-prone cities, provided LID tools are considered in city planning besides grey infrastructure to achieve optimal mitigation. These results, which combined multiple disciplines and were not explicitly mentioned in similar studies in developing countries, may assist municipalities' policymakers in planning flood-resistant, sustainable cities.

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.

Enhanced Escherichia coli removal from stormwater with bermudagrass-derived activated biochar filtration systems

Stormwater treatment and reuse can alleviate water pollution and scarcity while current sand filtration systems showed low treatment performance for stormwater. For enhancing E. coli removal in stormwater, this study applied the bermudagrass-derived activated biochars (BCs) in the BC-sand filtration systems for E. coli removal. Compared with the pristine BC (without activation), the FeCl3 and NaOH activations increased the BC carbon content from 68.02% to 71.60% and 81.22% while E. coli removal efficiency increased from 77.60% to 81.16% and 98.68%, respectively. In all BCs, the BC carbon content showed a highly positive correlation with E. coli removal efficiency. The FeCl3 and NaOH activations also led to the enhancement of roughness of BC surface for enhancing E. coli removal by straining (physical entrapment). The main mechanisms for E. coli removal by BC-amended sand column were found to be hydrophobic attraction and straining. Additionally, under 105-107 CFU/mL of E. coli, final E. coli concentration in NaOH activated BC (NaOH-BC) column was one order of magnitude lower than those in pristine BC and FeCl3 activated BC (Fe-BC) columns. The presence of humic acid remarkably lowered the E. coli removal efficiency from 77.60% to 45.38% in pristine BC-amended sand column while slightly lowering the E. coli removal efficiencies from 81.16% and 98.68% to 68.65% and 92.57% in Fe-BC and NaOH-BC-amended sand columns, respectively. Moreover, compared to pristine BC, the activated BCs (Fe-BC and NaOH-BC) also resulted in the lower antibiotics (tetracycline and sulfamethoxazole) concentrations in the effluents from the BC-amended sand columns. Therefore, for the first time, this study indicated NaOH-BC showed high potential for effective treatment of E. coli from stormwater by the BC-amended sand filtration system compared with pristine BC and Fe-BC.