Dry Weather Periods Research Articles

Isotope-based source assessment of water flowing from storm sewer systems to a receiving river during dry weather periods

Urban stormwater management systems, particularly storm sewers, are critical for managing runoff in urban areas. These systems are designed to function during wet weather events; however, field-based observations of these systems suggest that they may also be active flow pathways in dry weather conditions, ultimately contributing to streamflow. Unlike dry weather flow in wastewater systems, storm sewer dry weather flow has not been thoroughly explored. This research used stable isotopes of oxygen and hydrogen in water to examine the sources of dry weather flow from storm sewers in a highly urban catchment. A stable isotope mixing model was applied at the outfalls of two stormwater catchments and the receiving Black Creek, located in Toronto, Canada. Findings suggest that during dry periods, storm sewers receive non-stormwater inputs from tap water, wastewater, and groundwater, along with some precipitation, and that these sources may constitute up to 19 % of Black Creek's flow at the watershed scale. Seasonal patterns in flow and water sources were observed for the Black Creek and outfalls. At one outfall, dry weather flow was predominantly from the water distribution system (i.e., tap water and/or wastewater) throughout spring, summer, and fall. In contrast, at the second outfall, groundwater dominated in spring and summer, and groundwater and water distribution were equally proportioned in fall. Black Creek baseflow comprises a dynamic mix of water sources that at times are similar to the sources observed at the stormwater outfalls. Considering these findings, future work should incorporate strategic sampling of additional outfalls, and multiple years of data collection to explore inter-annual variability in these processes and focus on replicating a similar study in other urban watersheds with different climates and/or water infrastructure design. The study findings highlight that our understanding of dry weather flow from storm sewers is relatively limited, emphasizing the need for further exploration of this phenomenon to inform urban hydrological modelling, water quality studies, and urban water management.

Maximizing Antioxidant Potential in Picual Virgin Olive Oil: Tailoring Agronomic and Technological Factors with Response Surface Methodology.

Over the past years, a prolonged drought has affected Spain, raising significant concerns across various sectors, especially agriculture. This extended period of dry weather is profoundly affecting the growth and development of olive trees, potentially impacting the quality and quantity of olive oil produced. This study aims to assess the impact of agronomic factors, i.e., olive maturation and irrigation management, as well as the technological factors involved in the production process, on the antioxidant content of Picual virgin olive oil. Mathematical models were developed to maximize the concentration of polyphenols, orthodiphenols, chlorophylls, carotenes, and tocopherols in olive oils. Findings indicate that increasing the malaxation temperature from 20 to 60 °C and reducing the mixing time from 60 to 20 min positively influenced the polyphenol and orthodiphenol content. Although irrigation did not significantly affect the polyphenols, pigments, and α-tocopherol contents, it may enhance the β- and γ-tocopherol content. Optimal conditions for producing antioxidant-enriched virgin olive oils involved olives from rainfed crops, with a moisture index of 3-4, and a 60-min malaxation process at 60 °C. Under these conditions, the total phenol content doubled, pigment content increased fourfold, and α-tocopherol content rose by 15%. These findings provide relevant knowledge to interpret the year-to-year variation in both organoleptic and analytical profiles of virgin olive oils.

Severity of topsoil compaction controls the impact of skid trails on soil ecological processes

Abstract Skid trails are a major management‐induced disturbance in temperate forest ecosystems with considerable impact on soil ecological processes that are so far poorly understood. In German forests, skid trails comprise 10%–20% of the forest area that is potentially affected by soil compaction through heavy machinery. We systematically investigated the influence of skid trails on physical, chemical and microbiological soil parameters at 84 paired plots across four Central European forest types. In low mountain forests with steeper topography, skid trails had more drastic effects than in lowland forests. Skid trails in low mountain areas showed a decrease in the C to N ratio of microbial biomass (MBC/MBN), as well as increased microbial (MBC/SOC) and enzyme activities leading to faster carbon turnover (lower C/N, EOC/EN) and increased CO2 losses (CO2/SOC) from the soil. The overall effects of the skid trails in lowland forests were small. On base‐poor soils, we found an increase in the MBC/MBN ratio, while skid trails in base‐rich lowland soils showed a reduction in CO2/SOC, suggesting a proportional increase in soil carbon storage. Regardless of region‐specific effects, the relative increase in the bulk density of the fine soil was identified as a ‘golden trait’ that determined the effects of skid trails on many soil parameters, as shown by negative correlations with SOC, N, MBC, MBN, MBP, MBC/SOC and CO2/SOC and positive ones with the activities of certain hydrolytic enzymes. Synthesis and applications: Our data clearly showed that carbon conversion processes and soil respiration leading to significant carbon and nutrient losses increased significantly on skid trails in low mountain regions with relatively steep slopes, which was in sharp contrast to lowland sites. The strong context dependence of our findings suggests that the mapping of soil conditions in terms of slope, substrate and moisture with high spatial resolution is mandatory to assess the vulnerability of sites to soil compaction by heavy machinery. Based on such vulnerability analysis, negative impacts can be minimised through the designation of permanently fixed skid trails, technical adaptation of vehicles (e.g. wide base tyres) as well as careful planning and timing of management operations that should be restricted to dry weather and soil moisture conditions or periods of frost.

Investigating First Flush Occurrence in Agro-Urban Environments in Northern Italy

The first flush (FF) phenomenon is commonly associated with a relevant load of pollutants, raising concerns about water quality and environmental management in agro-urban areas. An FF event can potentially transport contaminated water into a receiving water body by activating combined sewer overflow (CSO) systems present in the drainage urban network. Therefore, accurately characterizing FF events is crucial for the effective management of sewer systems and for limiting environmental degradation. Given the ongoing controversy in the literature regarding the delineation of FF event occurrences, there is an unavoidable necessity for further investigations, especially experimental-based ones. This study presents the outcomes of an almost two-year field campaign focused on assessing the water quantity and quality of two combined sewer systems in Northern Italy. For this purpose, various hydro-meteorological variables, including precipitation, flow rate, temperature, and solar radiation, in addition to water quality analytics, were measured continuously to capture stormwater events. Throughout the monitoring period, sixteen stormwater events were identified and analyzed using five indices usually adopted in the literature to identify FF occurrences. The results indicate that there is a strong positive correlation between the mass first flush ratios calculated for nutrients and three factors, including maximum rainfall intensity, maximum flow rate, and antecedent dry weather period. Furthermore, rainfall duration was found to possess a strong negative correlation with the mass first flush ratios calculated for nutrients. However, for the same rainfall event, the occurrence of FF has never been unanimously confirmed by the indices examined in this study. Moreover, different macro-groups of pollutants can behave differently. Thus, it becomes apparent that relying solely on a priori analyses, without the support of data from experimental monitoring campaigns, poses a risk when designing actions for the mitigation of FF occurrences.

Predicting Forest Fire Hotspots with Carbon Emission Insights Using Random Forest and Gradient Boosting Regression

This research paper focuses on predicting the dispersion of carbon emissions, a crucial indicator for identifying potential forest fire hotspots in the wooded regions of Sumatra Island, Indonesia. Forest fires, often triggered by extended periods of dry weather, result in significant environmental degradation, impacting both the ecosystem and the economy. Furthermore, health concerns arise from smoke inhalation, leading to respiratory problems. To achieve this predictive capability, we harnessed valuable datasets, including GFED4.1s for carbon emissions and ERA5 for historical climate indicators, spanning from 1998 to 2022. Employing supervised learning ensemble methods, specifically Random Forest Regression (RFR) and Gradient Boosting Regression (GBR), we sought to forecast carbon emissions. It is noteworthy that our predictions encompassed carbon emission values from 1998 to 2023, providing insights into recent trends. Our analysis showed that GBR did better than RFR in terms of evaluation metrics, with a root mean square error (RMSE) of 10.87 and a mean absolute error (MAE) of 2.91. This was done by carefully tuning the hyperparameters. Additionally, our study highlighted that precipitation, temperature, and humidity were the primary climate factors influencing carbon emission values.

Habitat selection by Grevy's zebra (Equus grevyi): Conservation implications

AbstractUnderstanding the spatial dynamics of landscape use by free‐ranging herbivores is essential for species management and conservation in its natural environment. We used Ivelv’s selection index, binary logistic regression analyses and stepwise regression to understand how environmental factors shape habitat selection by the Grevy’s zebra (Equus greyvi). We measured biotic, abiotic and human factors that may influence presence or absence of Grevy’s zebra in Samburu‐Laikipia landscape and showed: (1) during wet periods, percentage perennial grasses, livestock density and grass quality had the greatest effect on Grevy’s zebra presence; but (2) during dry weather periods a different suite of factors determined their landscape distribution, namely, the percentage of tree and bush density, distance to water and overall grass abundance. In addition, different Grevy’s zebra demographic and reproductive classes varied in their response to environmental selective forces, thus demonstrating flexibility in their patterns of habitat selection. While we recommend more detailed studies on how abiotic and biotic interact to shape habitat selection patterns, our findings underscored the need of maintaining both dry and wet season habitats to ensure essential grazing area refugia. Our findings show that ‘soft’ development with controlled livestock stocking rates within the landscape will enhance Grevy’s zebra conservation.

SPECIFIC FEATURES OF INTRODUCTION AND PROSPECTS OF THE GENUS ROBINIA L. USE IN LANDSCAPING OF VINNITYSA

After analyzing data from the literature sources, it was found that R. viscosa, which ranks second after R. pseudoacacia in terms of the introduction process involvement, is characterized by less winter hardiness. According to Kachalov A.A. [10], R. viscosa proved its winter-hardiness in conditions of the east, northern and middle parts of Ukraine and Transcarpathia. In Vinnytsia conditions, it withstands frosts up to -30˚С. In Moldova (Chisinau R. pseudoacacia tolerates winter well and bears fruit. As a result of the research, it was established that winter hardiness of the genus Robinia L. species in conditions of introduction was 1-2 (3) points. The introduced genus Robinia L. species and forms, which were objects of the research, in conditions of Vinnytsia were able to withstand negative temperatures (up to -32˚C) without significant damage. According to the obtained data, it was established that the genus Robinia L. representatives belong to the drought-resistant species and are able to withstand a long period of dry and rainless weather. The level of drought resistance of the studied species and forms according to the Pyatnytskyi S.S. scale equals to 4-5 points. According to the Pyatnytskyi S.S. light-demanding scale, R. pseudoacacia belongs to the most photophilous tree species – heliophytes. It was also defined that such species as R. pseudoacacia, R. holdtii, R. ambigua are fully acclimatized, R. viscosa, R. luxurians are well acclimatized. Their acclimatization numbers are: R. pseudoacacia = 100, R. viscosa = 86, R. luxurians = 86, R. holdtii = 95, R. ambigua = 94. Having analyzed the studied species in terms of their decorative characteristics, it was found that the time of decorativeness in the genus Robinia L. species is divided into two periods: the first is the flowering one, and the second – the time of leaf pigmentation change. According to our observations, the studied representatives received 5 points of decorativeness according to the Kalinichenko O.A. method in the following time periods: 1) from 05.15.2022 to 06.15.2022 – the time of flowering; 2) from 18.08.2022 to 20.09.2022 – leaf colour change.

Substrate moisture variations of extensive green roofs with different structural configurations in a semi-arid region: Observational data and dynamic simulation

Substrate moisture condition is crucial for hydrological performance, water management and plant survival of green roofs. To date, the behaviour of long-term substrate moisture of green roofs in various climate regions has not been well understood. In this study, 24 months continuous field monitoring of substrate moisture content within nine extensive green roof modules with varies structural configurations was conducted to investigate the impacts of structural configurations and meteorological factors on substrate moisture content, and identify the key parameters for simulating the long-term substrate moisture dynamics. Results showed that green roofs planted with SedumSpectabilehave the highest mean volumetricwater content (VWC) (0.12–0.15 m3/m3) compared to other plant species considered. Green roofs with 5-cm substrate depth had lower mean VWC (0.07–0.08 m3/m3) than other substrate depths. The average substrate moisture loss rate of green roofs in summer and autumn seasons was 1.35 and 1.22 mm/day, respectively, which was higher than the spring (0.73 mm/day) and winter (0.64 mm/day) seasons for 2021. There were significant differences in mean VWC of green roofs among substrate material types. The mean VWC of green roofs was gradually enhanced from 0.12 to 0.14 m3/m3 as the substrate depth increased from 5 cm to 15 cm. The differences of mean VWC among vegetation types were all extremely significant (p < 0.001). The relative humidity was the most significant influencing factor on the average VWC level (correlation coefficient r = 0.42), with antecedent dry weather period (ADWP) had less significant effects on substrate VWC (r = 0.33), and followed by precipitation depth (r = 0.27). However, there was no significant relationship between air temperature and average VWC level of green roofs as well as total solar radiation. Nash-Sutcliffe efficient (NSE) values of the model simulations ranged from 0.70 to 0.81, and the mean absolute relative error (MAE) values ranged from 1.25 to 2.36, which indicated the model can adequately simulate the long-term substrate moisture content dynamics of green roofs. The crop coefficient and maximum water holding capacity of the substrate were the key parameters affecting long-term moisture content simulation of green roofs. These results could provide scientific suggestions for selecting suitable structural configuration to enhance water holding capacity of extensive green roofs in arid climates.

Exploring Influencing Factors and Innovative Solutions for Sustainable Water Management on Green Roofs: A Systematic Quantitative Review

Green roofs are becoming popular in urban areas due to their potential benefits, including energy efficiency, urban heat island mitigation, and stormwater management. However, their water consumption can negatively impact water resources. Therefore, carefully managing the water consumption of green roofs is crucial to ensure they do not exacerbate existing water scarcity issues. This review explores the influencing factors and innovative solutions that increase the sustainability of water management on green roofs. A systematic quantitative review was conducted on published studies on green roofs. The review highlighted that while small-scale experimental studies are almost saturated, large-scale monitoring studies are still lacking. Modelling and assessing green roof settings based on climatic conditions and water availability and consumption are essential for successful water management. Using integrated technologies and sensing systems can increase water management efficiency and sustainability. Rainwater may be sufficient as a water source for green roofs in wet climates, while irrigation is still needed in other climates. Phytoremediation and biosorption can potentially increase runoff water quality. Improving hydrological performance by increasing rainwater retention and reducing water consumption capacity can reduce demand for other water resources and effectively manage small storms, mitigating pressure on city infrastructure and increasing water quality. Seeking non-potable sources, such as greywater, or harvesting enough rainwater to be used for irrigation during dry weather periods is highly advantageous for improving the sustainability of green roofs.

Increased likelihood of compound dry and hot extremes in India

Compound dry and hot extremes (CDHE) are periods of prolonged dry and hot weather. Their joint occurrence typically impacts society and nature stronger compared to the occurrence of the single hazards. Understanding the likelihood, variability and drivers of CDHE is challenging due to the complexity of the climate system involving interactions and feedbacks among atmosphere-land processes. In this study, we first investigate the role of the dependence between precipitation and temperature for the likelihood of CDHEs. We demonstrate that both the dependence strength and its type, i.e. the degree of tail dependence, substantially affect the CDHE likelihood. We then analyze the space-time variation of CDHE characteristics during the Indian Summer Monsoon across India for the period 1961–2014. We find strong negative association and substantial tail dependence between precipitation and temperature in some regions. Event coincidence analysis reveals that low soil moisture preconditioned by dry extremes is responsible for 55–65% of CDHE occurrence. Our analysis of the temporal evolution of CDHE characteristics finds an increasing negative association between precipitation and temperature leading to a 2 to 3-fold rise of CDHE frequency for some regions of India.

The Thermal Effect of Various Local Park Settings: A Simulation-Based Case Study of Sunshine Coast, Australia

Local parks are widely used to mitigate urban heat islands. However, the increase of dry weather periods in subtropical climates has caused natural grass failure, leading some city councils to replace it with artificial grass. Therefore, this study investigates various local park settings to assess the performance of different ground covers (i.e., irrigated and non-irrigated natural grass, bare soil, and artificial grass) and the influence that tree proximity has on them, as well as the total thermal performance of the investigated local parks. This study finds that non-irrigated parks could harm park users’ health due to the high concentration of mean radiant temperature (MRT) around trees. Although the surface temperature of the artificial grass was higher (2.60 °C) than that of asphalt during periods of peak temperature, the parks using artificial grass performed better at reducing air temperature and enhancing thermal comfort than the ones with dry grass or bare soil, where both tree proximity and soil water content played significant roles. However, artificial grass negatively affected night cooling, resulting in a poorer daily performance. This study discusses the influence of various park settings on air temperature, MRT, thermal comfort, surface temperature, soil temperature, and water content. In addition, various recommendations and settings are offered to direct decision makers and future studies.

Assessment of sources, environmental, ecological, and health risks of potentially toxic elements in urban dust of Moscow megacity, Russia

Potentially toxic elements (PTEs) in urban dust of Moscow megacity and related risks have been studied. 78 samples were collected in the Moscow downtown in sites with different anthropogenic load, namely, major highways, residential area, and recreation zones. The concentrations of PTEs in urban dust were determined by ICP-MS and ICP-AES. Then, environmental, ecological and health risks of PTEs in urban dust were assessed. In addition, potential sources of PTEs in dust were identified. It is shown that Moscow dust is mainly contaminated by Sb, Zn, Pb, Cd, Cu, Sn, and Mo, which according to the data of principal component and correlation analyses can be attributed to anthropogenic sources (non-exhaust vehicle emissions). Potential ecological risk factor demonstrates that Cu, Mo, and Cd have moderate potential ecological risks in 13% of studied area, while Sb has this risk in 62% of area. Potential ecological risk indices indicate that 41% of studied territory is of moderate ecological risk. Concerning the human risks through ingestion, dermal contact, and inhalation pathways, PTEs in Moscow dust have no significant non-carcinogenic risks for adults. However, the value of total hazard index for children is 1.8 showing that non-carcinogenic risks may occur. Moreover, possible carcinogenic risks caused by Cr are evaluated. The finding of the present study can be used for ecological management in the megacity to reduce both ecological and human risks. A special attention should be given to periods of hot and dry weather and to traffic-related emissions.

Performance monitoring of constructed floating wetlands: Treating stormwater runoff during the construction phase of an urban residential development

In the context of climate change and global trend towards greenfield urbanisation, stormwater and transported pollutants are expected to increase, impairing receiving environments. Constructed floating wetlands (CFWs) can improve stormwater retention pond performance. However, performance data are currently largely restricted to mesocosm experiments, limiting design enhancement fit for field implementation. The present 12-month field study aims to fill part of these gaps by identifying limitations and necessary design improvements for CFWs on a large retention pond/lake. Water in a 2.6-ha lake receiving stormwater from a 45-ha urban area under development in subtropical Queensland, Australia, was recirculated during dry weather periods to minimise algal growth and the risks of blooms. Pollutant removal efficiencies of two full-scale CFWs were evaluated during storm events and dry weather periods as a function of inlet and outlet pollutant concentrations, flow and rainfall. Inlet TSS and TN concentrations in runoff during the construction phase of the development exceeded required water quality limits while TP inflow concentrations were low and often below the detection limit. Median pollutant load reduction efficiencies during storm-events were − 20 % TSS, −2 % TN and 22 % TP at CFW1 and 51 % TSS, 3 % TN and 17 % TP at CFW2, respectively. TSS and TN concentration removal efficiencies at CFW1 were low and highly variable, partly due to low inlet concentrations, high flow velocities and short hydraulic retention times (<1 day). However, CFW1 significantly reduced TSS concentrations during dry weather periods. In contrast, CFW2 significantly reduced TSS concentrations during both storm events and during inter-event periods. This study highlights treatment limitations associated to the operational conditions of CFWs at field-scale not identifiable in a mesocosm-scale study. Further research is necessary to investigate treatment performance of CFWs during the operational phase of the development with higher nutrient levels.

Comparing paleo reconstructions of warm and cool season streamflow (1400–2018) for the North and South Saskatchewan River sub-basins, Western Canada

The North and South Saskatchewan River sub-basins comprise the Saskatchewan River Basin (SRB), which originates in the eastern slopes of the Rocky Mountains of Alberta (Canada) and Montana (USA), extending across the vast landscape of three Canadian Provinces. The SRB is the most populated region of the Northern Great Plains, where water demands from agriculture, industry, and municipalities can be a substantial proportion of supply during periods of low flow and hydrological drought. Changing climatic conditions and shifts between periods of extreme wet and dry weather emphasize the need for a better understanding of past and future seasonal variability of the surface water balance within and between the sub-basins. Climate extremes, such as hydrological drought and excessive moisture conditions occurring simultaneously can create detrimental effects. Using a multi-species network of over 80 tree-ring chronologies, warm (May through August) and cool (December through April) season streamflow (1400–2018) were independently reconstructed for the North and South Saskatchewan River sub-basins. Departures from seasonal flow and spectral and wavelet analyses of the reconstructions indicate significant variability at inter-annual and multi-decadal scales.

Estimating dry deposition of atmospheric aerosols to urban surfaces by rain washoff

Atmospheric aerosols accumulate onto urban surfaces by dry deposition and are subsequently washed off by rain. If there is a sufficiently long period of dry weather, it may be possible to estimate the dry deposition rate of a chemical species by measuring its concentration in runoff from the surface and its concentration in fresh rain. This hypothesis was tested for horizontal surrogate surfaces exposed to the atmosphere in Syracuse, New York. In each experiment, two flat disks 1 m diameter with 2.54 cm rims and two disks of similar size but without rims were exposed to the atmosphere on the roof of Hinds Hall at Syracuse University to collect dry deposition of aerosol fluoride, chloride, sulfate, potassium, calcium, and strontium. Airborne concentrations were measured simultaneously to calculate dry deposition velocities. Dry deposited material on the flat disks was removed using a Teflon scraper after a few days of exposure, just prior to a rainstorm. In the subsequent storm, sequential samples of runoff from the rimmed disks and fresh rain were collected. The concentrations in fresh rain were subtracted from the concentrations in the runoff to calculate dry deposition fluxes, which were compared to fluxes measured by scraping the flat disks prior to rain. Results showed that sufficient removal of dry deposited material was possible to estimate dry deposition fluxes. Ratios of the mean dry deposition flux onto the rimmed disks to the mean dry deposition flux onto the flat disks had an overall average of 0.89 for all chemical species. This ratio mean and standard deviation was 0.94±0.30 for fluoride, 0.59±0.54 for chloride, 1.0±0.10 for sulfate, 0.80±0.28 for potassium, 1.0±0.03 for calcium, and 0.93±0.12 for strontium. However, some dry deposition fluxes to the rimmed disks were smaller than those to the flat disks in cases where the wet deposition flux was at least one half of the contribution to the total flux. This suggests the importance of having antecedent dry periods of at least several days to use this method to estimate dry deposition of aerosols and to minimize the role of contaminants in the fresh rain contributing significantly to the total concentration in the runoff samples. Future work includes testing this method on rooftops and other horizontal urban surfaces, which may enable reliable estimates of dry deposition rates to urban areas.

Butterflies (Lepidoptera: Papilionoidea) of northwestern and western Crete (Greece) in early July, with the finding of new larval host plant for Lampides boeticus

During the summer of 2021 northwestern and western areas of the Greek island of Crete were surveyed, in order to confirm certain observations of the diurnal butterfly fauna of the island. Research was focused especially on the unsurveyed north-western parts of the island, as well as surveying the species that are extending their areal (Cacyreus marshalli (Butler), Lampides boeticus (L.)). From 47 species reported from the island, 23 were observed. The surveys were all carried out during an especially hot and dry weather period (30-37 °C), between 30th of June and 6th of July. Additionally, a new larval host plant for L. boeticus was confirmed, as oviposition of females on Campsis radicans (Seem.) was observed on several occasions.

Climate change can be seen through a disaster medicine lens.

Climate change can be seen through a disaster medicine lens.

Examining How a Smart Rainwater Harvesting System Connected to a Green Roof Can Improve Urban Stormwater Management

This study quantified how a smart rainwater harvesting cistern that collected stormwater runoff from a green roof reduced stormwater flow into a combined sewer system (CSS) during wet-weather flow. The studied smart rainwater harvesting cistern collected runoff from a green roof located in Bronx, New York City; it used the Continuous Monitoring and Adaptive Control (CMAC) smart sensor provided by OptiRTC, Inc., to regulate the water flow from the cistern. The cistern collected stormwater runoff from the roof, usually draining completely after 24 h of dry weather. However, the smart sensor used weather forecasting data, and if additional rainfall was predicted immediately following another storm, the cistern only drained a specific amount, calibrated to mitigate the CSO. Five years of data from the cistern system were used to understand the role of the cistern’s smart sensor in reducing stormwater flow into the CSS during storms. The study results demonstrate that connecting the smart cistern system to the green-roof maximized stormwater collection (compared with the green roof alone) for storm sizes between 2 mm and 25 mm and for antecedent dry-weather periods greater than 2 days. The total of 65.2% of rainfall retained over the monitoring period by the green roof alone increased to 75.6% when considering the total stormwater retained and detained together by the green roof and cistern, thus yielding a 10% improvement. The study results also demonstrate that the smart sensor’s use of weather forecasting data failed to improve system performance.

Simulating annual runoff retention performance of extensive green roofs: A comparison of four climatic regions in China

The hydrologic performance of green roofs can be notably influenced by local climatic conditions. The majority of studies have focused on event-based retention performance of particular green roof configuration and climatic condition, making it difficult to predict green roof retention and formulate an efficient green roof configuration in a new location. To date, limited studies have assessed and compared annual or long-term runoff retention performance of green roofs in different climatic regions, and the impacts of climatic conditions on reduction effectiveness of green roofs remain unclear. In this study, a water balance model of green roofs coupling evapotranspiration rate estimation was developed to simulated the annual retention performance of green roofs. Four cities located in different climatic regions of China were selected to compare their average annual and seasonal runoff retention performances of extensive green roofs using 11 years of meteorological data, and assess the impacts of substrate storage capacity, vegetation types parameters and rainfall patterns on runoff retention performance among climatic regions. Results showed that average annual runoff retention in the dry continental climate of Lanzhou was 73.8%, which was higher than that in the humid climatic regions of Beijing (48.9%), Chongqing (45.2%) and Shenzhen (30.0%). Average runoff retention performance of extensive green roofs was the highest in spring for Beijing and Lanzhou, and in winter for Chongqing and Shenzhen. In Lanzhou and Beijing, the enhancement of increases in substrate water storage capacity on runoff retention was higher; and in Chongqing and Shenzhen, the impact for increases in crop coefficients (i.e. higher water use plants) was more efficient. Runoff retention performances of extensive green roofs were significantly decreased as rainfall depth increased. Longer antecedent dry weather period significantly lowered antecedent substrate moisture and resulted in higher runoff retention performances of extensive green roofs. These results can assist to formulate an efficient green roof configuration in local climatic condition and spatially allocate appropriate sites to optimize retention performance of green roofs.

Using multiple isotopes to identify sources and transport of nitrate in urban residential stormwater runoff.

Increased nitrogen (N) from urban stormwater runoff aggravates the deterioration of aquatic ecosystems as urbanisation develops. The sources and transport of nitrate (NO3-) in urban stormwater runoff were investigated by analysing different forms of N, water isotopes (δD-H2O and δ18O-H2O), and NO3- isotopes (δ15N-NO3- and δ18O-NO3-) in urban stormwater runoff in a residential area in Hangzhou, China. The results showed that the concentrations of total N and nitrate N in road runoff were higher than those in roof runoff. Moreover, high concentrations of dissolved organic N and particulate N led to high total nitrogen (TN) concentrations in road runoff (mean: 3.76mg/L). The high δ18O-NO3- values (mean: + 60 ± 13.1‰) indicated that atmospheric deposition was the predominant NO3- source in roof runoff, as confirmed by the Bayesian isotope mixing model (SIAR model), contributing 84-98% to NO3-. Atmospheric deposition (34-92%) and chemical fertilisers (6.2-54%) were the main NO3- sources for the road runoff. The proportional contributions from soil and organic N were small in the road runoff and roof runoff. For the initial period, the NO3- contributions from atmospheric deposition and chemical fertilisers were higher and lower, respectively, than those in the middle and late periods in road runoff during storm events 3 and 4, while an opposite trend of road runoff in storm event 7 highlighted the influence of short antecedent dry weather period. Reducing impervious areas and more effective management of fertiliser application in urban green land areas were essential to minimize the presence of N in urban aquatic ecosystems.