Applied Water Science最新文献

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.

Soil moisture movement reveals the hydrological environment and irrigation characteristics of plants, which is very important and basic hydrological problem. A soil moisture movement algorithm based on cellular automata suitable for greenhouse was proposed to simulate the lateral flow and vertical penetration of soil water in different soil layers. Artemisia annua was used as an experimental plant, and two numerical simulations were set up to determine the minimum water replenishment and the degree of upward soil modification. To verify the performance of the model, corn was used as an experimental plant for application simulation. The numerical simulation results show that the effect of only water for plant cells is superior to soil cells, and the disturbance behavior of the underlying soil layer should be minimized during the cultivation process. The average MAE/RMSE of all soil layers is 0.86/1.06 and in deep layer (50 cm and 60 cm) is 0.53/0.64. It shows the model has a certain prediction and simulation ability, especially in deep soil layers. The proposed algorithm can simply calculate soil flow, set the minimum water replenishment, and evaluate the water replenishment efficiency, which can provide a theoretical reference for the water replenishment and soil replacement scheme.

Herein, a 3D sponge-like polypyrrole/TiO₂ (Ppy-TiO₂) composite aerogel was developed for the first time to remove hydroxybenzotriazole (HOBt) from water. Mesoporous TiO₂ was prepared via a sol–gel method, and then the Ppy-TiO₂ composite hydrogel was prepared by oxidative polymerization and converted to aerogel by freeze-drying. The morphological, compositional, and surface characteristics of the prepared materials were detailly characterized. The characterization studies revealed that pure anatase mesoporous TiO₂ nanoparticles were successfully prepared and incorporated into amorphous 3D Ppy with a porous chain-like network structure. Coupling Ppy and TiO₂ extended the light absorption to the visible region and decreased the electron/hole recombination rate. The performance studies revealed that the Ppy-TiO₂ composite has higher adsorption and photocatalytic activities than the sum of the individual components. Optimum performance was obtained at pH 5.3 using 0.25 g/L of the Ppy-TiO₂ composite with a Ppy: TiO₂ mass ratio of 1:1. The intermolecular hydrogen bonding was pivotal in the adsorption process which was multilayer. The degradation of HOBt occurs primarily by holes, then superoxide anion radicals. The total organic carbon (TOC) analysis showed a 90% reduction in carbon content after 30 min of treatment. The toxicity study indicated that the photocatalytic process decreased the toxicity of the HOBt solution. The synergism between adsorption and photocatalysis, easy separation, and reusability promote the application of Ppy-TiO₂ composite aerogel for water treatment.

Biographene was prepared through the pyrolysis of Acacia nilotica waste using diverse temperatures and time spans. The obtained materials were characterized using scanning electron microscope (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectrometry (EDX), X-ray diffraction analysis (XRD), and Fourier transform infrared spectroscopy (FTIR) methods. The data obtained indicated that when the temperature and time increased, the texture of the biographene became more porous with greater carbon content. The effect of various variables on Cd(II) adsorption, using the optimized biographene product, was investigated, and the results revealed that the optimum pH was 4 and the maximum adsorption capacity was 118.9 mg/g. The Langmuir isotherm model and pseudo-second-order kinetic model best fit the equilibrium data, indicating the adsorptive behavior of the as-prepared biographene implying a homogenous monolayer surface. The recyclability investigation elucidates the remarkable potentiality of up to five consecutive cycles. As such, the biographene-based Acacia nilotica could be considered a sustainable candidate for cadmium removal from polluted water.