Applied Water Science最新文献

This study evaluated the efficiency of an on-site household greywater treatment system for indirect human reuse and for domestic lawn irrigation. This helps in the reduction in the disparity between water demand and supply that is facing the rapidly increasing global populace. Natural household greywater was settled and then conventionally filtered by using two types of non-woven geotextile media; thermally bonded and needle punched. A third woven cotton textile media was also experimented and all the non-woven geotextile media were tested in single and double layers and combined with the woven cotton textile layer. The different filter media configurations were tested for a period of one year operation (six runs) with two filtration rates of 15.00 and 25.00 m³/m²/day for each run. For all runs, the final treated effluent was disinfected using calcium hypochlorite prior to reuse. The double layer needle punched non-woven geotextile media together with the woven cotton textile media gave the best removal efficiencies; 96.34 ± 1.85% for turbidity 81.87 ± 6.43% for BOD₅, 97.49 ± 1.68% for TSS, 75.35 ± 3.99% for CODt, 99.59% for E.coli. The soluble CODs removal efficiencies were negligible (below 3%) in the first four runs with non-woven geotextile media and increased to 28.05 ± 4.29% when the woven cotton textile media was added. In general, the system was found to save about 63% of the daily water consumption reflecting a net 22.50% reduction in the daily water billing costs for the whole household.

In South Korea, the snowy season spans from October to April, and the annual average snowfall varies significantly depending on specific regions, latitudes, and elevations, ranging from 0 to 260 cm. The average annual snowfall in South Korea is 25.1 cm. Despite of the relatively shallow snowfall depth, over the past decade, South Korea has experienced approximately 120 million dollars in damages attributed to snow-related incidents. In this study, the DPSIR (Driver-Pressure-State-Impact-Response) framework was employed to consider the meteorological and socioeconomic factors to calculate the snow damage vulnerability. A total of 17 indicators were taken into account to comprehend meteorological conditions, socioeconomic factors, and historical damage records from 1994 to 2020. However, due to the limited availability of meteorological observatories and changes in greenhouse design standards, accurately estimating the snow damage amount poses challenges. Therefore, based on the vulnerability, the risk levels were classified into four categories and estimated snow damage generated by the categorized models was compared with those of the model constructed using the entire dataset. The categorized models offer improved estimation results, as the meteorological and socioeconomic characteristics within each category differ and should be addressed separately in modeling. Among the categorized models, the Green zone exhibited the best results, primarily because it did not include outlier snow damage incidents. The developed model in this study could be utilized to mitigate the impact of heavy snowfall and prioritize snow removal regions.

Floods caused by dam failures can cause huge losses of life and property, especially in estuarine areas and valleys. In spite of all the capabilities and great improvements reached by man in the construction of dams and their structures, they will remain helpless before the powerful forces of nature, especially those related to tectonic activation, and the occurrence of earthquakes of different intensities.

The region extending from the Ilisu Dam in Turkey to the Mosul Dam in Iraq was chosen as an area for this study, and the HEC-RAS application was used to simulate the collapse of the Ilisu Dam due to a major earthquake, to know the magnitude of the risks and losses that could result from this. The Ilisu Dam was built very close to a highly tectonically active fault system, particularly the East Anatolian Fault (EAF), which is one of the largest tectonically active faults in the world with a length of 500 km. This region has witnessed past and present earthquakes of high magnitude (M > 7), especially in the EAF, so the construction of the Ilisu Dam near the EAF fault system is of great concern, as it was built in a basin with very complex seismic activity and geology.

Using the HEC-RAS simulation application, the study found that the flood resulting from the collapse of the Ilisu Dam would reach the edges of the Mosul Dam Lake in just 13 h. With a flow of more than 100,000 m³/s, more than 10 billion m3 of water will flow into the Mosul Dam Lake within four days of the disaster. This will lead to the collapse of the Mosul Dam and direct the flood wave of the collapse of these dams towards Baghdad through Mosul, Tikrit, and Samarra. This could pose risks to all Iraqi cities located within the Iraqi sedimentary plain (Mesopotamia), from south of the Mosul Dam up to Basra, in a scenario similar to Noah’s Flood.

The composition and distribution of macro-invertebrates of benthic species can be influenced by water quality. The primary objective of this study was to understand the spatial distribution and composition of macro-invertebrates of benthic nature in the upper Awash River below and above Ginchi Town. The study was carried out for a period of three months from February 2020 to April 2020, and macro-invertebrates samples were collected from three stations using Surber sampler with 500 (upmu)m/mesh size and 25 cm × 25 cm (0.0625 m²) of sampling area coverage. The present study showed that, in the study area, there was a low density of macro-invertebrates and species richness in general with a comparative difference between the pool riffle habitats in density and family richness. And the total abundance of benthic macro-invertebrates showed a positive correlation with NO₃-N, dissolved oxygen, and total phosphorus, while a negative correlation with all the other physicochemical parameters measured during the study period. Spatial and monthly variations in the diversity and richness of benthic macro-invertebrates were attributed to the effects of human action and changes in environmental factors. So, the water shade management system should be applied to control pollution factors that can affect the macro-benthic fauna community.

One of the challenging issues in surface water resources management is the optimal operation of multi-dam systems. In addition to the applicability in determining the optimal pattern of operation of existing dams, this approach can be implemented in specifying the optimal capacity of under design dams. In this research, the simulation–optimization technique is used along with the reservoir zoning method in order to specify the optimal role curve of each of the dams in a multi-dam system (i.e., the Marun and Jarreh dams) in monthly intervals. The objective of this study is to develop a multi-objective algorithm on the basis of the zoning of reservoirs for the optimal operation of multi-dam systems. In this technique, instead of increasing the reliability of supplying demands in the whole period regardless the dry months, some of the inflow of rainy periods is stored in dam reservoirs to be consumed in dry months in order to mitigate the severity of deficiency. To examine the efficiency of the proposed model, the results obtained from the system operation in the current conditions are compared under two scenarios including optimal and reference. In the reference scenario, during 30-years, in some dry and low-water years, especially in the last six years of planning, the percentage of the demand supply is zero or less than five percent in several consecutive months. After optimizing the system, the minimum supply percentage in critical and dry months reaches 30 to 60 percent. Also, in the optimization scenario, the percentage of downstream ecological demands is improved. This research indicates that using the solution of this research leads to the better management of reservoirs in multi-dam systems and reduces the severity of deficiency in supplying various uses in low-water months.

The 2022 flood events in Quetta, Pakistan, caused severe damage to the economy, properties, and lives. Therefore, flood risk mapping to identify flood-prone areas is essential for planners and decision-makers to take critical protective measures to control the effects of flooding. This study focuses on mapping flood-prone regions in the Quetta district of Pakistan using an analytical hierarchy process (AHP) and a geographic information system (GIS). The factors influencing flood used in the present study were topographic witness index (TWI), elevation, slope, land use, land cover, precipitation, stream distance, drainage density, and soil type. Weights and ranks were allocated separately to all factors through AHP and were interpreted in a GIS environment. The produced flood hazard model of the study area depicted four zones. These zones ranged from low (19.49%), moderate (43.34%), high (28.30%), to very high (8.87%). The model was further validated through previous flood events in the study area. Around 90% of flood hazard events in the past took place mainly in the produced model's very high and high zones, which is why the current model is reliable. Finally, integrating geospatial approaches with AHP in flood hazard mapping is a quick, reliable, and affordable method that may be utilized in the area.

In response to increasing flood risks driven by the climate crisis, urban areas require advanced forecasting and informed decision-making to support sustainable development. This study seeks to improve the reliability of reservoir-based flood forecasting and ensure adequate lead time for effective response measures. The main objectives are to predict hourly downstream flood discharge at a reference point, compare discharge predictions from a single reservoir with a four-hour lead time against those from three reservoirs with a seven-hour lead time, and evaluate the accuracy of data-driven approaches. The study takes place in the Han River Basin, located in Seoul, South Korea. Approaches include two non-deep learning (NDL) (random forest (RF), support vector regression (SVR)) and two deep learning (DL) (long short-term memory (LSTM), gated recurrent unit (GRU)). Scenario 1 incorporates data from three reservoirs, while Scenario 2 focuses solely on Paldang reservoir. Results show that RF performed 4.03% (in R²) better than SVR, while GRU performed 4.69% (in R²) better than LSTM in Scenario 1. In Scenario 2, none of the models showed any outstanding performance. Based on these findings, we propose a two-step reservoir-based approach: Initial predictions should utilize models for three upstream reservoirs with long lead time, while closer to the event, the model should focus on a single reservoir with more accurate prediction. This work stands as a significant contribution, making accurate and well-timed predictions for the local administrations to issue flood warnings and execute evacuations to mitigate flood damage and casualties in urban areas.

The system dynamics approach was conducted to optimize genotype patterns in various climatic and water availability scenarios, to address the water productivity improvement of the Sefidrood irrigation network. The studied cropping pattern scenarios were SD1 (the continuation of current trends), SD2 (the reduction in the cultivated area), SD3 (replacing modified crops on an annual basis), and SD4 (increasing the annual cultivated area of Hashemi type rice). Moreover, the impacts of irrigation efficiency improvements and water resources management strategies on the physical and economic water productivity indices were studied. The results indicated that the SD3 scenario has the most positive impact on water productivity with 0.45 kg/m³ increases. However, a questionnaire survey revealed that this scenario that belongs to the increase in the modified genotype area cannot be recommended due to cooking quality and low prices. The Hashemi genotype was the favorite rice among farmers and experts. Also, analyzing the irrigation efficiency improvement scenario showed that this strategy has a limited impact on the physical and economic water productivity. Increasing the capacity of local rainwater storage pools, Ab-bandans, and increasing the drainage water reuse had the highest water productivity in the condition of river water reduction and uncertain water availability.

Water microbial contamination is a serious issue that poses a risk to both animal and human health. One hundred and twenty water were samples collected from main water source and drinkers from a poultry farm. Different bacterial pathogens were isolated from water sources. Escherichia (E.) coli, Pseudomonas (P.) aureoginosa, (Salmonella) Salmonella (s). Typhimurim, Aeromonas (A.) hydrophila at different percentages. Variable degree of bacterial resistance to some commercial disinfectants commonly used to disinfect water system (iodine, terminator and H₂O₂). Nanoparticles were used to control bacteria in water. About the safety investigation for the prepared nanomaterials, the work results demonstrated that zinc oxide (ZnO) nanoparticles (NPs) exhibit the highest safety profile among the manufactured materials. The median fatal dose (LD₅₀) for ZnO NPs was determined to be 3709 mg/kg body weight. In comparison, the LD₅₀ values for zeolites and nanocomposites were 3251 mg/kg and 2658 mg/kg, respectively. Therapeutic dosages were estimated based on the LD₅₀. Zeolite NPs, ZnO NPs and ZnO/zeolite NPs showing promising results in control of those bacteria. It was concluded that the escalating resistance of bacteria to disinfectants have led to a need to find alternative such as nanoparticles that proved promising results in control of pathogens, particularly it showed a safe effect on laboratory animals.

The administration of cytostatic drugs in chemotherapy is steadily increasing, triggering thus a risk to the environment. Identifying powerful ways to effectively remove these hazardous pollutants from hospital and effluent wastewater before they discharge into the aquatic environment remains a critical and challenging task. Adsorption is among the most effective ways to treat contaminated water due to the wide availability and selectivity of the adsorbents besides the simplicity and the low start-up costs of the technique. In this work, a geopolymer, elaborated from an illito-kaolinitic clay (Douiret region of Tunisia) and industrial waste (silica fume and phosphogypsum), has been tested as promising decontamination of the cytostatic drugs paclitaxel (PCX) and irinotecan (IRI) from water samples. The foamed geopolymer was characterized using X-ray diffraction, Fourier transform infrared, scanning electron microscopy and thermogravimetric analysis before and after adsorption. Adsorption batch assays were performed using different concentrations of PCX and IRI, contact times and environmental conditions. The geopolymer had an excellent removal efficiency (almost 100% for PCX and 89% for IRI) using 20 mg of adsorbent and 2.5 mg/L of each drug concentration. The characterization results showed that cytostatic drugs were adsorbed to the geopolymer through physical interactions, pore filling, electrostatic attraction and hydrogen bonding. The specific surface area and pore volume of the geopolymer were 82.23 m²/g and 0.19 cm³/g, respectively. In addition to its cost-effective properties, the geopolymer demonstrated excellent efficiency in contaminated natural samples (including influent, effluent wastewater and surface water) denoting a great application for water purification.