Search Results (24,939)

This study investigated the distribution of sedimentary phosphorus (P) species along an area of a rapid current at the southern coast of Zhoushan Island. The objective of this study was to improve the understanding of P cycling in a zone of rapid water cycling. Results showed that the average percentage of each P form to total P (TP) was in the following order: apatite P (Ca-P; 52%) was found in the most abundant, followed by organic P (OP; 16%), exchangeable-P (Ex-P; 14%), detrital P (De-P; 11%), and iron-bound P (Fe-P; 7%). Ca-P showed a trend of an increasing concentration from a location at the west (ZS1 has mean Ca-P = 45.6 mg kg⁻¹) toward the east (ZS2 has mean Ca-P = 82.69 mg kg⁻¹) and south-east (ZS3 has mean Ca-P = 82.17 mg kg⁻¹); De-P also increased from 15.12 mg kg⁻¹ at ZS1 to 22.53 mg kg⁻¹ at ZS2 and 27.45 mg kg⁻¹ at ZS3, but the three bioavailable P species, OP, Ex-P, and Fe-P, decreased from the west toward the east of the coastal area. Results along the cores showed the occurrences of sediment P adsorption and release throughout the time span from the 1930s to the present, with an overall trend of decreasing Ca-P and TP from the bottom to surface sediments. There was a tendency of Ca-P formation at the expense of Ex-P and OP release during transport and organic matter decomposition. The likely impact of climate change in the coastal zone would be an increased temperature resulting in elevated organic matter decomposition and P release. Full article

This study explores the impacts of climate change on the number of dry days and very heavy precipitation days within Iran’s metropolises. Focusing on Tehran, Mashhad, Isfahan, Karaj, Shiraz, and Tabriz, the research utilizes the sixth phase of the Coupled Model Intercomparison Project (CMIP6) Global Circulation Models (GCMs) to predict future precipitation conditions under various Shared Socioeconomic Pathways (SSPs) from 2025 to 2100. The study aims to provide a comprehensive understanding of how climate change will affect precipitation patterns in these major cities. Findings indicate that the SSP126 scenario typically results in the highest number of dry days, suggesting that under lower emission scenarios, precipitation events will become less frequent but more intense. Conversely, SSP585 generally leads to the lowest number of dry days. Higher emission scenarios (SSP370, SSP585) consistently show an increase in the number of very heavy precipitation days across all cities, indicating a trend towards more extreme weather events as emissions rise. These insights are crucial for urban planners, policymakers, and stakeholders in developing effective adaptation and mitigation strategies to address anticipated climatic changes. Full article

Climate change is making water management increasingly difficult due to rising temperatures and unpredictable rainfall patterns, impacting crop water availability and irrigation needs. This study investigated the ability of machine learning and satellite remote sensing to monitor water status and physiology. The research focused on predicting different eco-physiological parameters in an irrigated peach orchard under Mediterranean conditions, utilizing multispectral reflectance data and machine learning algorithms (extreme gradient boosting, random forest, support vector regressor); ground data were acquired from 2021 to 2023 in the south of Italy. The random forest model outperformed in predicting net assimilation (R² = 0.61), while the support vector machine performed best in predicting electron transport rate (R² = 0.57), Fv/Fm ratio (R² = 0.66) and stomatal conductance (R² = 0.56). Random forest also proved to be the most effective in predicting stem water potential (R² = 0.62). These findings highlighted the potential of integrating machine learning techniques with high-resolution satellite imagery to assist farmers in monitoring crop health and optimizing irrigation practices, thereby addressing the challenges determined by climate change. Full article

In order to explore the feasibility of using algae to treat the fly ash leachate from a safe landfill site, leachate samples taken from a certain safe landfill site in Wenzhou City were treated with two different microalgae, Chlorella vulgaris and Scenedesmus obliquus, and the effectiveness of each treatment was evaluated in terms of its efficiency of pollutant removal. The effects of conditions such as pretreatment of leachate by sterilization, the initial concentration of leachate, and the addition of nutrients on pollutant removal efficiency and algae growth were studied. Sterilization of the leachate was found to have a relatively small impact on the growth of C. vulgaris and S. obliquus, as well as the removal of pollutants from the leachate. Therefore, sterilization treatment may not be necessary for engineering applications. Algal growth and the removal of pollutants were optimal when the leachate was used at a concentration of 10%, but when the leachate concentration was 30% or higher, the growth of both algae was weakened. The inclusion of 0.2 g/L K₂HPO₄·3H₂O and 0.06 g/L ammonium ferric citrate in the system led to higher algal growth and pollutant removal. The chlorophyll a levels of C. vulgaris and S. obliquus were 555.53% and 265.15%, respectively, and the nitrogen removal rates were also the highest, reaching 59.51% and 56.69%, respectively. This study optimized the cultivation conditions of a microalgae treatment leachate system, providing technical support and a theoretical basis for the practical engineering of a harmless treatment of leachate. Full article

The purpose of this research is to develop a new method for automatically optimizing the seawall cross-section with composite slopes and a berm, considering both overtopping discharge and construction cost. Minimizing these competing multi-objectives is highly challenging due to the intricate geometry of seawalls. In this study, the surrogate model optimization algorithm DYCORS (Dynamic COordinate search using Response Surface models) is employed to search for the optimal seawall geometry, coupled with the ANN (Artificial Neural Network) model for determining the overtopping discharge. A total of 20 trials have been run to evaluate the performance of our methodology. Even the worst-performing Trial 7 among these 20 trials shows a satisfactory performance, with a reduction of 17.67% in overtopping discharge and a 12.1% decrease in cost compared to the original solution. Furthermore, compared to other optimization schemes using GAs (Genetic Algorithms) with the same decision vectors, constraints, and multi-objective functions, the methodology has been proven to be more effective and robust. Additionally, when facing different combinations of wave conditions and water levels, there was a 27.8% reduction in objective function value compared to the original solution. The optimal results indicate that this method can still be effectively applied for optimizing the seawall cross-section as it is a general method. Full article

The Great Salt Lake entered the zeitgeist of environmental concern in 2022 when a coalition of scientists and activists warned in a highly publicized report that the lake might be just five years away from complete desiccation, a possibility one state official warned was tantamount to an “environmental nuclear bomb”. Shortly thereafter, an unpredicted and unprecedented pluvial winter resulted in an increase in inflow, temporarily halting the lake’s decline and prompting Utah’s governor to mock the dire prediction as “a joke”, an outcome that speaks to the tension between agenda-setting and trust-building that researchers face when sharing worst-case warnings, particularly those based on short-term variability. Here, we describe a robust relationship between the lake and groundwater in the surrounding region and demonstrate how coupled models can thus be used to improve lake elevation predictions, suggesting that while the situation may not be as dire as some have warned, the lake remains at long-term risk as a result of climate warming. We further suggest that efforts to communicate the risk of future desiccation should be informed by stochastic variability and guided by long-term fluctuations in the total water storage of the endorheic lake’s watershed. Full article

Over a period of 30 years (1993–2022), headwater catchments in the Slavkov Forest (Czech Republic) exhibited a robust increase in stream water DOC (dissolved organic carbon) concentrations following a significant reduction in acidic atmospheric deposition. Sulfur deposition decreased from 34 kg ha⁻¹ yr⁻¹ in 1993 to 2.6 kg ha⁻¹ yr⁻¹ in 2022. Three Norway-spruce-dominated research sites—Černý Potok (CEP), a 15.2 ha peatbog catchment, Lysina (LYS), a 27.3 ha granitic catchment, and Pluhův Bor (PLB), a 21.6 ha serpentinite catchment, were investigated. The three–year average DOC concentration increased from 48.2 mg L⁻¹ (1993–1995) to 68.3 mg L⁻¹ (2020–2022) at CEP (0.69 mg L⁻¹ yr⁻¹). LYS showed an increase from 16.9 mg L⁻¹ to 25.4 mg L⁻¹ (0.30 mg L⁻¹ yr⁻¹ annually). The largest increase was recorded at PLB, with an increase from 15.7 mg L⁻¹ to 36.7 mg L⁻¹ (0.89 mg L⁻¹ yr⁻¹). A decline in ionic strength was identified as the main driver of the DOC increase. The annual runoff declined significantly at CEP and LYS from 465 mm to 331 mm as a result of rising air temperatures and reduced precipitation between 2014 and 2022. PLB (average of 266 mm) did not show a statistically significant decline. Recently, PLB experienced significant deforestation that likely lowered transpiration and thus increased catchment runoff. As a result, DOC fluxes did not change significantly at CEP (average 210 kg ha⁻¹ yr⁻¹) and LYS (90 kg ha ⁻¹ yr⁻¹). However, PLB’s DOC flux more than doubled, increasing from 44 to 106 kg ha⁻¹ yr⁻¹. Drivers connected with global change, such as increasing temperatures, or potential chemical drivers, such as reductions in Al concentrations and pH changes, were not able to explain the observed changes in DOC concentra tions and fluxes. Full article

Urban nature-based solutions (NBSs) are widely implemented to collect, store, and infiltrate stormwater. This study addressed infiltration rate as a measure of the performance of bioretention solutions. Quick scan research was conducted, starting with mapping over 25 locations of implemented green infrastructure in Riga, Latvia. Basic information, such as location, characteristics, as well as photos and videos, has been uploaded to the open-source database ClimateScan. From this, eight bioswales installed in the period 2017–2022 were selected for hydraulic testing, measuring the infiltration capacity of bio-retention solutions. The results show a high temporal and spatial variation of infiltration rate for the bioswales, even those developed with similar designs: 0.1 to 7.7 m/d, mean 2.0 m/d, coefficient of variation 1.0. The infiltration capacity decreased after saturation: a 30% to 58% decrease in infiltration rate after refilling storage volume. The variation in infiltration rate as well as infiltration rate decrease on saturation is similar to other full-scale studies done internationally. The infiltration rate of most bioswales falls within the range specified by international guidelines, all swales empty within 48 h. Most bioswales empty several times within one day, questioning the effectiveness of water retention and water availability for dry periods. The results are of importance for stakeholders involved in the implementation of NBS and will be used to set up Latvian guidelines for design, construction, and maintenance. Full article

Ceramsites are extensively employed as substrates for adsorbents in studies focused on phosphorus adsorption, leaving ceramsites crafted from diatomite less explored. Diatomite-based ceramsite, with its distinct porous architecture and surface silanol functionalities, is adept at supporting a variety of metal oxides, presenting a distinct advantage over other ceramsite variants. In light of this, the present study embarked on producing diatomite-based ceramsite using diatomite as the foundational material, subsequently enhancing it through the incorporation of Fe, thus yielding an Fe-modified diatomite-based ceramsite. Through adsorption testing, the modified ceramsite demonstrated a significantly improved adsorption capacity of 4.06 mg P/g, marking a substantial enhancement from the initial capacity of 0.9 mg P/g. The process of phosphorus adsorption exhibited a strong alignment with the Langmuir isotherm model and the pseudo-second-order kinetic model. In-depth analyses employing XRD, FTIR, zeta potential, and XPS techniques have revealed that the principal mechanisms driving the adsorption process are centered on interactions involving electrostatic forces, the formation of chemical precipitates, and the exchange of ligands. This investigation not only opens new avenues for the application of diatomite-based ceramsite but also lays down a theoretical foundation for its modification, thereby enriching the spectrum of its utility. Full article

Spectral analysis is an effective tool for processing seismic signals, particularly when time-domain characteristics are challenging to capture. In this study, we developed a method using P-wave signals to calculate the power spectrum, enabling the estimation of two spectral parameters—peak frequency and shape factor—for earthquakes recorded by regional seismic networks in the Xiangjiaba (XJB) reservoir area from 2010 to 2015. The temporal evolution of the two spectral parameters was analyzed, revealing that the mean values of individual spectral parameters remain relatively stable despite variations in reservoir water levels. However, a notable increase in the ratio of the shape factor to the peak frequency is observed when the XJB reservoir reaches its maximum water level, suggesting its potential as a precursor indicator for reservoir-induced seismicity (RIS). Furthermore, we performed spatial interpolation on the spectral parameters, and the results show that reservoir impoundment significantly influences the spatial distribution of these parameters. In addition, several regions between the two faults in the tail section of the XJB reservoir exhibit an elevation in the proposed precursor indicator. This study presents a new approach for monitoring and early warning of RIS. Full article

Accurate and reliable short-term runoff prediction plays a pivotal role in water resource management, agriculture, and flood control, enabling decision-makers to implement timely and effective measures to enhance water use efficiency and minimize losses. To further enhance the accuracy of runoff prediction, this study proposes a FA-LSTM model that integrates the Firefly algorithm (FA) with the long short-term memory neural network (LSTM). The research focuses on historical daily runoff data from the Dahuangjiangkou and Wuzhou Hydrology Stations in the Xijiang River Basin. The FA-LSTM model is compared with RNN, LSTM, GRU, SVM, and RF models. The FA-LSTM model was used to carry out the generalization experiment in Qianjiang, Wuxuan, and Guigang hydrology stations. Additionally, the study analyzes the performance of the FA-LSTM model across different forecasting horizons (1–5 days). Four quantitative evaluation metrics—mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R²), and Kling–Gupta efficiency coefficient (KGE)—are utilized in the evaluation process. The results indicate that: (1) Compared to RNN, LSTM, GRU, SVM, and RF models, the FA-LSTM model exhibits the best prediction performance, with daily runoff prediction determination coefficients (R²) reaching as high as 0.966 and 0.971 at the Dahuangjiangkou and Wuzhou Stations, respectively, and the KGE is as high as 0.965 and 0.960, respectively. (2) FA-LSTM model was used to conduct generalization tests at Qianjiang, Wuxuan and Guigang hydrology stations, and its R² and KGE are 0.96 or above, indicating that the model has good adaptability in different hydrology stations and strong robustness. (3) As the prediction period extends, the R² and KGE of the FA-LSTM model show a decreasing trend, but the whole model still showed feasible forecasting ability. The FA-LSTM model introduced in this study presents an effective new approach for daily runoff prediction. Full article

This research aims to propose management strategies to mitigate eutrophication caused by inefficient wastewater treatment plants in Colombia. The information analyzed was provided by environmental authorities such as IDEAM, CORANTIOQUIA, and CORNARE in Antioquia, where the average concentrations of phosphorus in wastewater from municipal, livestock, and industrial activities are 5.1, 30.6, and 29.1 mg P/L. The total nitrogen concentrations are 77, 143, and 121 mg N/L, respectively, surpassing the limit concentrations stated by the European Union, the United States, and Mexico, among others, while Colombia has not established its own limits. Including limitations for nutrient concentrations will align Colombia with the 2050 Sustainable Development Goals (SDGs), where microalgae species like Chlorella or Scenedesmus could be used in wastewater treatment systems for municipalities and industries. These microalgae can capture organic matter, nutrients, and greenhouse emissions and reduce the concentrations observed in natural water. They could also be an alternative for capturing heavy metals and some pollutants of emerging concern. In addition to the ecological and social benefits, the algal biomass could be valorized by transforming it into biological products such as fuels, fertilizers, and pigments when micropollutants are not present, reducing operational costs for treatment systems. Full article

Citizen science is considered one of the most appropriate tools to raise public awareness of environmental issues. With the aim of improving knowledge on river environments, this article presents a web application for mobile phones and other portable devices that allows, through the active participation of society, the collection of detailed and systematic information on the main problems facing rivers. The initiative uses a web viewer (Tagus Web Viewer—TagusWV) developed as a pilot project in the Tagus River basin (Spain). This web viewer allows information on river pressures to be collected and the aggregated data to be visualised and extracted for interpretation and analysis. Pressure is defined as any use or activity, legal/illegal, authorised/unauthorised, that has an impact on water quality, morphology, river dynamics or the ecosystem. The data are mainly collected by different groups of citizens. In addition to contributing to the environmental education of citizens involved in a river environment, the data provided in the TagusWV are of particular interest to river managers. The tool is designed to be relevant for any river basin in the world, by simply loading the map, the names of the rivers and the corresponding locations. Full article

Foreshore slope is crucial in designing beach berm nourishment schemes and understanding coastal responses to wave forces. Beach berm nourishment often suffers from a high loss rate, necessitating theoretical research and design parameter comparison to mitigate these losses early on. This study uses Bagnold’s energy conservation method and the small-angle approximation method to establish a relationship between cross-shore sediment transport and foreshore slope. The feedback mechanism between these factors shows that when the foreshore slope is fewer than 10 degrees, a smaller initial slope results in a reduced rate of sediment transport. Over time, the foreshore slope decreases and eventually reaches equilibrium, promoting the formation of an offshore sandbar, which helps reduce sediment loss. Using data from Guanhu Beach in Dapeng Bay, this study constructs a realistic numerical beach model to simulate the dynamic behavior of beach profiles with varying foreshore slopes under the influence of monsoon waves and storm surges. The simulation results support the feedback mechanism findings, demonstrating that profiles with minimal foreshore slopes experience the least initial sediment loss, thus facilitating sandbar formation more effectively. These insights can inform beach berm nourishment strategies, emphasizing early-stage efforts to expand beach areas and reduce sediment loss. Full article

The porosity of freshwater ice and sea ice is one of the main parameters that determine their strength. The strength of ice varies over a wide range of values, and the differences in the intensity of the mechanisms of ice porosity formation in different water areas can be one of the possible reasons for these variations. The water mass contains gases in two forms: gases dissolved in the water mass, as well as gas bubbles that are formed when wind waves break up, and bubbles that float up from the seabed. This article presents the results of an analysis of the role of each of these forms in the formation of gas inclusions (pores) in the crystal structure of ice. The results showed that the main source of gas pores in ice crystals is the gas bubbles coming to the surface from the bottom, formed during the decomposition of bottom sediments or during gas leaks from near-bottom oil and gas fields. The possibility of gas bubbles occurring and rising to the ice–water boundary depends on the presence of bottom sources of the gases, the intensity of dissolution of the bubbles and the depth of the water area. Therefore, the variation in the porosity and the strength of ice over the space of the water areas can be associated with the changes in their depths, and the presence and location of the natural gas sources. Full article