Wet Weather Research Articles

“SPATIAL ANALYSIS OF IRRIGATION AND MAJOR OILSEEDS PRODUCTION AND PRODUCTIVITY IN DHARWAD DISTRICT OF KARNATAKA STATE.”

Agriculture is not only an important economic activity but also a farm of social heritage and a way of life for the millions of Indian farmers. Irrigation is playing an important role on growing the oilseeds sector, there is an urgent need to find out ways to increase water supply. In this regard Dharwad district, which is a glomeration of wet and dry weather features and also the mixture of different soils and irrigated and dry cropping system represents a typical region to study the agricultural geography in general and major oilseeds in particular. Edible oilseeds cultivation in India is an integral part of agricultural system, as edible oilseeds are part of food item for the human population. The cultivation of oilseeds are found in all taluks of Dharwad district where annual rain fall to extent of 75 cm is available, besides the availability of irrigation in some parts, coupled with availability of black and red soils that have favored the cultivation of oilseeds

Cover crop planting practices determine their performance in the U.S. Corn Belt

AbstractCover crop growing periods in the western U.S. Corn Belt could be extended by planting earlier. We evaluated both pre‐harvest broadcast interseeding and post‐harvest drilling of the following cover crops: (a) cereal rye (Secale cereale L.) [RYE]; (b) a mix of rye + legumes + brassicas [MIX1], (c) a mix of rye + oat [Avena sativa L.] + legumes + brassicas (MIX2), (d) legumes [LEGU]) and (e) a no cover crop control. These were tested in continuous corn (Zea mays L.) [corn–corn] and soybean [Glycine max (L.) Merr.]–corn systems [soybean–corn] at three sites in Nebraska for their effect on cover crop productivity, soil nutrients, and subsequent corn performance. At the sites with wet fall weather, pre‐harvest broadcasting increased cover crop biomass by 90%, to 1.29 Mg ha−1 for RYE and 0.87 Mg ha−1 for MIX1 in soybean–corn, and to 0.56 Mg ha−1 and 0.39 Mg ha−1 in corn–corn, respectively. At the drier site, post‐harvest drilling increased biomass of RYE and MIX1 by 95% to 0.80 Mg ha−1 in soybean–corn. Biomass N uptake was highest in pre‐harvest RYE and MIX1 at two sites in soybean–corn (35 kg ha−1). RYE and sometimes mixes reduced soil N, but effects on P, K, and soil organic C were inconsistent. In soybean–corn, corn yields decreased by 4% after RYE, and in corn–corn, by 4% after pre‐harvest cover crops. Site‐specific selection of cover crops and planting practices can increase their performance while minimizing impacts on corn.

Occurrence Characterization and Contamination Risk Evaluation of Microplastics in Hefei’s Urban Wastewater Treatment Plant

As one of the primary nodes in the flow of micro-plastics (MPs) in the environment, it is critical to examine and assess the Sewage Treatment, occurrence, and removal of MPs in waste treatment plant (WWTP). This research explored the shape, size, and composition of MPs at various stages of the WWTP process in the south of the city of Hefei, China, in dry and rainy weather conditions, as well as the removal effectiveness of MPs in a three-stage process. The collected MPs were quantitatively and qualitatively examined using an Osmosis electron microscope and micro-FTIR. The pollution risk of MPs in WWTP was assessed using the EU classification, labelling and packaging (CLP) standard and the pollution load index (PLI). The findings revealed that the average abundance of fibrous MPs was greatest in WWTP sewage and sludge, 49.3% and 39.7% in dry weather, and 50.1% and 43.2% in rainy weather, respectively. The average distribution of MPs in the 0–500 μm range was highest in WWTP wastewater and sludge, 64.9% and 60.4% in dry weather and 67.9% and 69.0% in rainy weather, respectively. Finally, the overall removal rate was 87.7% and 83.5%. At the same time, it has been demonstrated that MPs with varied compositions are strongly tied to human activities, and environmental conditions (such as rainy weather) also influence their source. In both dry and wet weather, the amount of polymers and the risk score were linked to the pollution risk of MPs in WWTP. In wet weather, the MPS pollution index was more variable. The pollution indices of MPs in row water and tail water were 2.40 and 2.46, respectively, which were heavily contaminated, and 1.0 and 1.2, which were moderately polluted. MPs in dewatered sludge had severely polluted indexes of 3.5 and 3.4, respectively. As a result, there is still MPs efflux or buildup in sludge during and after the WWTP process, which presents an ecological contamination concern.

Identification and validation of coding and non-coding RNAs involved in high-temperature-mediated seed dormancy in common wheat.

Seed dormancy (SD) significantly decreases under high temperature (HT) environment during seed maturation, resulting in pre-harvest sprouting (PHS) damage under prolonged rainfall and wet weather during wheat harvest. However, the molecular mechanism underlying HT-mediated SD remains elusiveSeed dormancy (SD) significantly decreases under high temperature (HT) environment during seed maturation, resulting in pre-harvest sprouting (PHS) damage under prolonged rainfall and wet weather during wheat harvest. However, the molecular mechanism underlying HT-mediated SD remains elusive. Here, the wheat landrace 'Waitoubai' with strong SD and PHS resistance was treated with HT from 21 to 35 days post anthesis (DPA). Then, the seeds under HT and normal temperature (NT) environments were collected at 21 DPA, 28 DPA, and 35 DPA and subjected to whole-transcriptome sequencing. The phenotypic data showed that the seed germination percentage significantly increased, whereas SD decreased after HT treatment compared with NT, consistent with the results of previous studies. In total, 5128 mRNAs, 136 microRNAs (miRNAs), 273 long non-coding RNAs (lncRNAs), and 21 circularRNAs were found to be responsive to HT, and some of them were further verified through qRT-PCR. In particular, the known gibberellin (GA) biosynthesis gene TaGA20ox1 (TraesCS3D02G393900) was proved to be involved in HT-mediated dormancy by using the EMS-mutagenized wheat cultivar Jimai 22. Similarly, a novel gene TaCDPK21 (TraesCS7A02G267000) involved in the calcium signaling pathway was validated to be associated with HT-mediated dormancy by using the EMS mutant. Moreover, TaCDPK21 overexpression in Arabidopsis and functional complementarity tests supported the negative role of TaCDPK21 in SD. We also constructed a co-expression regulatory network based on differentially expressed mRNAs, miRNAs, and lncRNAs and found that a novel miR27319 was located at a key node of this regulatory network. Subsequently, using Arabidopsis and rice lines overexpressing miR27319 precursor or lacking miR27319 expression, we validated the positive role of miR27319 in SD and further preliminarily dissected the molecular mechanism of miR27319 underlying SD regulation through phytohormone abscisic acid and GA biosynthesis, catabolism, and signaling pathways. These findings not only broaden our understanding of the complex regulatory network of HT-mediated dormancy but also provide new gene resources for improving wheat PHS resistance to minimize PHS damage by using the molecular pyramiding approach.

Construction and Performance Evaluation of Polyurethane-Bound Porous Rubber Pavement (PRP) Trial Section in the Cold Climate

Porous pavements are designed and used in current construction practices to address environmental and safety issues related to wet weather. Porous rubber pavement (PRP) is a novel porous pavement material consisting of recycled crumb tire rubbers, stone aggregates, and polyurethane binders. The higher permeability (up to 45% of air voids) of PRP and its composition offers excellent benefits to the urban hydrological system and environment. Due to its recent outset in the Canadian climate, its properties and performance are not yet investigated. This research investigates PRP’s properties and performance as pavement material through the construction of two trial sections incorporating three newly developed PRP mixes along with a Control Mix. Samples were obtained from the field and tested in the laboratory to determine the mechanical and durability properties, including indirect tensile strength, moisture-induced damage due to freeze-thaw cycles and permanent deformation. A field evaluation was also performed three times: right after construction, three weeks later and after seven months to determine stiffness, frictional properties, roughness and permeability. The results revealed that all PRP mixes exhibited excellent permeability and retained more than 68% of tensile strength after five freeze-thaw cycles. Although PRP showed significantly lower initial elastic modulus than conventional pavement material, ranging between 28 MPa to 59 MPa, in the springtime none of them went below 23 MPa. Material composition, site geometry and subgrade conditions were found to be the main factors influencing the field performance of PRP pavement.

A probabilistic decision support tool for prediction and management of rainfall-related poor water quality events for a drinking water treatment plant

A data-driven Bayesian Network (BN) model was developed for a large Australian drinking water treatment plant, whose raw water comes from a river into which a number of upstream dams outflow water and smaller tributaries flow. During wet weather events, the spatial distribution of rainfall has a crucial role on the incoming raw water quality, as runoff from specific sub-catchments usually causes significant turbidity and conductivity issues, as opposed to larger dam outflows which have typically better water quality. The BN relies on a conceptual model developed following expert consultation, as well as a combination of different types (e.g. water quality, flow, rainfall) and amount (e.g. high-frequency, daily, scarce depending on variable) of historical data. The validated model proved to have acceptable accuracy in predicting the probability of different incoming raw water quality ranges, and can be used to assess different scenarios (e.g. timing, flow) of dam water releases, for the purpose of achieving dilution of the tributary's poor-quality water and mitigate related drinking water treatment challenges.

Dynamic characteristics of microplastics under tidal influence and potential indirect monitoring methods

Rivers are an important channel for the transport of microplastics from inland areas to the ocean. It is of great significance to explore the dynamic changes in microplastic pollution characteristics under tidal fluctuations to understand the exchange of microplastics between rivers and oceans. In this study, the occurrence of microplastics in typical tidal channels in the lower reaches of the Dong River was investigated during the wet and dry weather seasons, and high frequency continuous dynamic monitoring of microplastics was carried out in a typical tidal cross section during a tidal cycle. The abundances of microplastics during wet and dry weather seasons were 3.97–102.87 ± 28.63 item/m3 and 5.43–56.43 ± 14.32 item/m3, respectively. The microplastics generally exhibited a fluctuating growth pattern, with low contents in the upstream area and high contents in the downstream area, and the abundance of microplastics differed greatly in the different functional zones. The dynamic monitoring results showed that the abundance of microplastics was clearly affected by the tides, in that it increased during the flood tide and decreased during the ebb tide, with abundances ranging from 11.15 to 95.26 item/m3. In addition, there was a significant linear relationship between the abundance of microplastics and flow in the typical tidal cross section. The relationship between the response of microplastic pollution characteristics and tides combined with local hydrometeorological factors may be a potentially effective real-time monitoring method for assessing microplastic pollution indirectly.

Smart management of combined sewer overflows: From an ancient technology to artificial intelligence

AbstractSewer systems are an essential part of sanitation infrastructure for protecting human and ecosystem health. Initially, they were used to solely convey stormwater, but over time municipal sewage was discharged to these conduits and transformed them into combined sewer systems (CSS). Due to climate change and rapid urbanization, these systems are no longer sufficient and overflow in wet weather conditions. Mechanistic and data‐driven models have been frequently used in research on combined sewer overflow (CSO) management integrating low‐impact development and gray‐green infrastructures. Recent advances in measurement, communication, and computation technologies have simplified data collection methods. As a result, technologies such as artificial intelligence (AI), geographic information system, and remote sensing can be integrated into CSO and stormwater management as a part of the smart city and digital twin concepts to build climate‐resilient infrastructures and services. Therefore, smart management of CSS is now both technically and economically feasible to tackle the challenges ahead. This review article explores CSO characteristics and associated impact on receiving waterbodies, evaluates suitable models for CSO management, and presents studies including above‐mentioned technologies in the context of smart CSO and stormwater management. Although integration of all these technologies has a big potential, further research is required to achieve AI‐controlled CSS for robust and agile CSO mitigation.This article is categorized under: Engineering Water > Sustainable Engineering of Water Science of Water > Water and Environmental Change

Spatio‐temporal variations of wet and dry spells in Iran and their association with large‐scale climatic indices

AbstractThe spatial and temporal variations of wet and dry spells may be related to large‐scale climatic indices. To date, no comprehensive study has been conducted on Iran's spatial and temporal variations of wet and dry spells. To fill this gap, 14 wet/dry spell indices were calculated for 512 rain gauges across Iran from 1985 to 2016. The modified non‐parametric Mann–Kendall test was then used to examine the temporal variations of wet and dry spell indices. Whether any relationships between spell indices and 13 large‐scale climatic indicators existed was determined. The maps showing the degree of correlation between wet/dry spell indices and two climatic indicators that reflect short‐ and long‐term El Niño oscillation were presented. The results demonstrated that precipitation typically occurs in bursts of 1 or 2 days in length, with most of the annual precipitation coming from a few exceptionally heavy or extreme events. Most dry spells in Iran occur from 6 to 27 days or longer. The length, frequency, and intensity of wet spells declined in southern Iran while expanding in northern Iran. However, extreme wet spells have intensified significantly across the country. When El Niño occurs, Iran experiences wetter weather. However, long‐term oscillations in sea‐surface temperatures in the Pacific Ocean are found to be significantly correlated with wet/dry spells, outperforming those obtained for shorter periods. A smaller portion of the country showed a significant correlation in extreme spell indices, though.

Enhancing farmer linkages to markets in developing countries through mapping of supply chains and optimising transport

Getting products to market where transport infrastructure is underdeveloped or unreliable is a major barrier to agricultural development, particularly in less-developed countries. Transport represents a high proportion of farm gate costs of moving livestock and crops to processors and local markets throughout the region. This is confounded by poor transport network infrastructure throughout the supply chain, wet weather accessibility constraints, food losses in transit, and congestion. Evidence-based approaches can inform transport and logistics infrastructure investments at different locations to maximise cost reductions.The Transport Network Strategic Investment Tool (TraNSIT) was developed by Australia’s national science agency, the Commonwealth Scientific and Industrial Research Organisation (CSIRO), to map freight movement and associated costs. The tool was applied to create the largest supply chain analysis ever conducted in Australia, mapping more than 170 commodities and 25 million vehicle trips per year. It is used extensively by the Federal and state governments to inform over $5 billion per year in major infrastructure and freight strategies.Drawing on experience through an investment by the Australian Government in partnership with agencies in Vietnam and Indonesia, we show how the TraNSIT methods can be extended and implemented in these developing countries. Several challenges are addressed around securing commitment from key in-country ministries and state-owned enterprises, accessing quality data, and modelling freight and supply chains that differ considerably to those in developed countries. Applications to key cropping and livestock commodities are used to demonstrate how TraNSIT can be used to analyse existing supply chains and test scenarios for various infrastructure investments.

Estimation and Assessment of the Root Zone Soil Moisture from Near-Surface Measurements over Huai River Basin

Root zone soil moisture (RZSM) is a vital variable for agricultural production, water resource management and runoff prediction. Satellites provide large-scale and long-term near-surface soil moisture retrievals, which can be used to estimate RZSM through various methods. In this study, we tested the utility of an exponential filter (ExpF) using in situ soil moisture by optimizing the optimal characteristic time length T_opt for different soil depths. Furthermore, the parameter analysis showed that T_opt correlated negatively with precipitation and had no significant correlation with selected soil properties. Two approaches were taken to obtain T_opt: (1) optimization of the Nash–Sutcliffe efficiency coefficient (NSE); (2) calculation based on annual average precipitation. The precipitation-based T_pre outperformed the station-specific T_opt and stations-averaged T_opt. To apply the ExpF on grid scale, the precipitation-based T_pre considering spatial variability was adopted in the ExpF to obtain RZSM from a new soil moisture dataset RF_SMAP_L3_P (Random Forest Soil Moisture Active Passive_L3_Passive) continuous in time and space over Huai River Basin. Finally, the performance of RF_SMAP_L3_P RZSM (0–100 cm) was evaluated using in situ measurements and compared with mainstream products, for instance, Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity Level 4 (SMOS L4) RZSM. The results indicated that RF_SMAP_L3_P RZSM could captured the temporal variation of measured RZSM best with R value of 0.586, followed by SMAP L4, which had the lowest bias value of 0.03, and SMOS L4 significantly underestimated the measured RZSM with bias value of −0.048 in the basin. Higher accuracy of RF_SMAP_L3_P RZSM was found in the flood period compared with the non-flood period, which indicates a better application for ExpF in wetter weather conditions.

Waste Heat Recovery from a Drier Receiver of an A/C Unit Using Thermoelectric Generators

Thermoelectric generators (TEGs) are considered promising devices for waste heat recovery from various systems. The Seebeck effect can be utilized to generate power using the residual heat emitted by the filter dryer receiver (FDR) of an air conditioning (A/C) system, which would otherwise go to waste. The study aims to build a set of thermoelectric generators (TEG) to collect the waste heat of the FDR and generate low-power electricity. A novel electrical circuit with two transformers is designed and fabricated to produce a more stable voltage for operation and charging. The thermoelectric generator (TEGs) was installed on the FDR of the A/C unit. The test showed that climate conditions have a significant impact on the output power generated from the system. The results showed that the peak voltage recorded in the current study is 5.2 V per day (wet, cold, and wind weather) with an output power of 0.2 W. These values are acceptable for powering the load and charging a single battery with 3.5 V as the voltage increases battery 0.1 V/20 min charge. A case study of operating the emergency signs in a building was considered. The current heat recovery system is deemed to be easily installed and can be connected to a network of TEGs to produce more power.

Development of a Water Quality Management Model for Dry Rivers in Arid Regions: Application on Wadi Rumah, Saudi Arabia

In dry rivers, urban wastewater discharge forms a pond in the dry period, and surface runoff shapes a longer pond in the wet period. A water quality management model developed for dry rivers is applied on Wadi Rumah in Saudi Arabia. The sub-basin was delineated from 30-m × 30-m spatial resolution digital elevation model. Hydrologic loss, runoff rates, and time of concentration were determined using the soil conservation service curve number, soil conservation service unit hydrograph methods, and Kirpich formula. Hydrologic Engineering Center Hydrologic Modeling System estimated the wet weather flows for 10 low-to-medium rainfall events. A steady-state hydrodynamic model including river flows, effluent discharge, and evaporation and infiltration losses estimated the hydraulic retention time for the explicit case of ponding conditions of dry rivers. Mass balance and first-order kinetics modeled the physical (total dissolved solid and total suspended solid), chemical (biochemical oxygen demand, dissolved oxygen, chemical oxygen demand, NH3, PO4, and Cl2), and microbiological (total coliform and fecal coliform) parameters. The hydrodynamic model and biokinetic rate coefficients were calibrated with satellite images, reported literature, and field measurements. A water quality index compared the aggregated water quality against the standards for 4 intended uses. The study yields “very good” water quality for restricted and unrestricted irrigation for the dry period, “fair” for livestock drinking, and “marginal” for fishery and recreation for the dry period, while water quality remained “marginal” for all the uses in the wet period. Water quality management implies regular water quality monitoring, continuous improvement of treatment facilities, and flood plain management initiatives for the long-term sustainability of dry rivers in arid regions.

Density and climate effects on age‐specific survival and population growth: consequences for hibernating mammals

AbstractThe impact of factors such as density dependence, food availability and weather are known to be important for predicting population change in a wide range of species. However, a challenge in ecology is understanding the contributory and interactive role of these drivers on populations. This is necessary to design effective conservation and management strategies. Using data from long‐term studies of five hazel dormouse Muscardinus avellanarius populations in Europe, we tested the relationship between population density and weather and their impact on demographic rates. We used an integrated population modelling approach, estimating age‐specific overwinter survival, annual population growth and fecundity rates. We found strong negative effects of population density, precipitation and winter temperature on population growth rates. This suggests that warmer and wetter weather negatively affects dormouse survival for both adults and juveniles, but we found subtle differences in these effects between age classes. We also identified an interaction between weather measures and population density on age‐specific survival, possibly as a result of weather impacts during hibernation. Although we found low winter temperature was positively associated with population growth, we found evidence consistent with density dependence. We discuss our results in the context of woodland habitat conservation management.

Surveillance, Diversity and Vegetative Compatibility Groups of Fusarium oxysporum f. sp. vasinfectum Collected in Cotton Fields in Australia (2017 to 2022)

Cotton (Gossypium hirsutum) is a billion-dollar crop in regional New South Wales (NSW) and Queensland, Australia. Fusarium wilt (FW) caused by Fusarium oxysporum f. sp. vasinfectum (Fov) is an economically important disease. Initial disease losses of up to 90% when the disease was first detected resulted in fields being taken out of cotton production. The disease is now well-managed due to the adoption of highly resistant varieties. However, annual disease surveys recently revealed that the disease dynamic has changed in the past few seasons. With relatively mild and wet weather conditions during the 2021/22 growing season, FW was detected in eight surveyed valleys in NSW and Queensland, with the disease incidence as high as 44.5% and 98.5% in individual fields in early and late seasons, respectively. Fov is genetically distinct and evolved from local Fusarium oxysporum strains. Additionally, the pathogen was reported to evolve rapidly under continuous cotton cropping pressure. However, our knowledge of the genetic composition of the prevailing population is limited. Sequences of the translation elongation factor alpha 1 (TEF1) revealed that 94% of Fusarium isolates recovered from FW-infected cotton were clustered together with known Australian Fov and relatively distant related to overseas Fov races. All these isolates, except for nine, were further confirmed positive with a specific marker based on the Secreted in Xylem 6 (SIX6) effector gene. Vegetative compatibility group (VCG) analyses of 166 arbitrarily selected isolates revealed a predominance of VCG01111. There was only one detection of VCG01112 in the Border Rivers valley where it was first described. In this study, the exotic Californian Fov race 4 strain was not detected using a specific marker based on the unique Tfo1 insertion in the phosphate (PHO) gene. This study indicated that the prevalence and abundance of Fov across NSW and Queensland in the past five seasons was probably independent of its genetic diversity.

Understanding subjective and situational factors of wind turbine noise annoyance

One of the most relevant acceptance factors of local wind turbines (WTs) are noise emissions. To better understand why some residents experience stress effects from wind turbines a field study with strongly annoyed residents (SAR) was conducted. A convenience sample of residents (N = 148) in the proximity of a wind farm in Germany were interviewed using a standardised questionnaire. Objective features, such as number of visible WTs and distance to the nearest WT, could not explain the experienced noise annoyance substantially. Instead, SAR were characterised by a negative perception of both procedural as well as distributive fairness, the assumed decrease of property value due to the WTs, a negative attitude towards the local wind farm (but not to WTs in general), and higher noise sensitivity. Additionally, SAR reported to be affected daily during the night in their bedrooms, while other residents experience annoying situations more likely when they are directly exposed to WTs. Fast wind speeds, wet weather and, occasionally, frost or fog were associated with annoying situations. In accord with recent research, we recommend to increase consideration of participation and fairness in the initial planning of a wind farm to increase acceptance and reduce annoyance. Additionally, to reduce the fear of negative health impacts and to increase acceptance, mitigation measures depending on specific weather conditions seem to be promising.

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.

Real-time variabilities in microplastic abundance and characteristics of urban surface runoff and sewer overflow in wet weather as impacted by land use and storm factors

Urban surface runoff (USR) and drainage system overflows during wet weather (WWF) play a key role in shaping water pollution. Particularly, the impact of large amounts of microplastic pollution on urban water bodies is unclear. We conducted an in-field investigation in six central urban drainage systems along Suzhou Creek in the Shanghai megacity of China and identified the impacts of storm factors and land use on the real-time dynamic changes in microplastic abundance and characteristics in USR and WWF. Microplastic abundances ranged from 228.3 ± 105.4–4969.51 ± 348.8, 309.3 ± 144.3–5195.8 ± 425.5, and 130.0 ± 30.0–8500.0 ± 1241.0 particles/L in the traffic and residential catchment USR, and the WWF, respectively. Under similar storm factor conditions, we observed correlations between environmental factors and microplastic abundance, especially the polymer type, verifying the significant role of land use. The microplastic abundance were 90.2 particles/L higher in the traffic catchment USR than in the residential catchment USR. Notably, we found unique microplastic polymers comprising ethylene vinyl acetate copolymer and thermoplastic elastomers in the residential and traffic catchment USR, respectively. However, land use had a minimum impact on the size and shape of microplastics: small-sized and film microplastics dominated in both USR types. We found statistical evidence of the widespread correlations between microplastic abundance and storm factors (accumulated storm depth and WWF flow) in both USR and WWF. The first flush phenomenon of microplastic dynamics was found in both USR and WWF. Microplastic characteristics also changed dynamically with storm time. With heavy storm factors, polypropylene and small-sized (<1 mm) microplastics in USR events increased and then decreased. This was also true for WWF events in granular and polyethylene terephthalate microplastics. Our results can facilitate the targeted mitigation of emerging pollutants to enhance stormwater management strategies and prevent future contamination.

Assessment of extraneous water inflow in separate sewerage system by different quantitative methods

Extraneous water that inflow to the sewage system is basically divided into two streams—accidental water (mainly rainwater) and infiltration water. The aim of the research was to assess the amount of extraneous water inflow to the considered system. Five different quantitative approaches were applied. Three well-known methods were used: the triangle method, the minimum night flow method, and the moving minimum method. The annual balance of water consumption and sewage supply to the wastewater treatment plant were calculated. Also, some analysis of sewage discharge during wet and dry weather was carried out. The study covered data from 6 years from 2014 to 2019. It was established that the main source of extraneous water was infiltration, because three methods which concern both streams (triangle method, minimum night flow, variability in wet and dry weather) confirm the conclusion. Merely the moving minimum method results differ from the others. In this investigation, accidental water (basically rainwater inflow) poses a significantly less share in the total volume of sewage compared to infiltration water. The total amount of extraneous water was estimated as in the range from 38 to 53% of annual sewage supply to wastewater treatment plant, depending on the year. Share of infiltration and accidental water is changing in different methods. Share of infiltration was in a range between 18 and 68%, depending on the year and the method used. Share of accidental water was in a range between 7 and 22%.

Spatial and temporal evolution characteristics of meteorological drought in the Northwest of Yellow River Basin and its response to large-scale climatic factors

Abstract The Northwest of Yellow River Basin (YRB) is an arid and semi-arid region. This study employs wavelet analysis, dry area coverage, drought frequency, and Mann–Kendall test trend to investigates the evolution characteristics of drought in the Northwest of YRB and the impact of macro climatic conditions on drought. The scale of season and year Standardized Precipitation Evapotranspiration Index (SPEI) was mostly represented as alternating dry and wet weather in this region. SPEI decreased significantly in each season, indicating increased drought. The drought situation changed abruptly in 1968, and the change was more obvious around 2000. Drought trend in autumn is more noticeable than in the other three seasons. The average annual dry area covers 34%. The drought frequency in each station at the annual scale was between 30.78% and 46.15%, its high values are mainly concentrated in the western region. The main cycles of annual SPEI changes are 37 and 5 years; spring is 45 and 10 years; summer is 20 and 5 years; autumn is 36, 10, and 5 years; winter is 45, 22, and 5 years. Furthermore, drought occurrence and changes are closely related to large-scale climatic factors, with El Niño-Southern Oscillation having the greatest impact on drought.