Small Water Research Articles

Unlocking the potential of ponds and pondscapes as nature-based solutions for climate resilience and beyond: Hundred evidences

Unlocking the full potential of ponds (small water bodies) and pondscapes (network of ponds) as Nature-based Solutions (NbS) is critical pursuit for enhancing ecosystems and societal resilience to climate change and other societal challenges. Despite scattered initiatives for pond/pondscape creation, restoration and management—each considered here a distinct NbS—there is a significant knowledge gap in utilising ponds/pondscapes as effective NbS. We aimed to assess these NbS in terms of their objectives, outcomes, effectiveness, multifunctionality, delivery of potentially conflicting effects, and the implementation process while considering their Nature's Contributions to People (NCPs, i.e., benefits to society). We compiled data on 183 NbS actions implemented across 93 ponds/pondscapes from 24 countries, predominantly from Europe, via a questionnaire distributed to experienced stakeholders implementing NbS in ponds/pondscapes. One single pond/pondscape may imply more than one NbS action. Two-thirds were in rural areas, and one-third in urban settings. Our analysis revealed that Creation of habitat for biodiversity was a primary delivery objective (targeted NCP) in the implementation of most NbS in ponds/pondscapes, often also combined with other NCPs such as Learning and inspiration, Regulation of water quantity, and Physical and psychological experiences, showcasing their intended multifunctionality. Implemented NbS primarily focused on climate change adaptation (especially Regulation of hazards and extreme events, and water quantity) rather than mitigation, with less emphasis on measures like direct greenhouse gas emissions reduction or enhancing carbon sinks. The costs associated with pond's NbS varied significantly depending on factors such as project scope, objectives, location, socio-economic-cultural system, and specific implementation requirements. The creation of ponds/pondscapes often entailed the highest financial investment, much more than their restoration or their management. In conclusion, our study underscores the multifunctionality of ponds/pondscapes and provides insights about their significant potential as cost-effective NbS for enhancing ecosystem and societal resilience to climate change and biodiversity. It underscores the importance of further research to fully understand and measure the diverse range of NbS they offer, particularly in the context of climate change mitigation. Standardised measurements of the NCP provided by these NbS in ponds/pondscapes are essential for validating managers' claims and exploring their role in addressing climate change.

Seasonal Monitoring Method for TN and TP Based on Airborne Hyperspectral Remote Sensing Images

Airborne sensing images harness the combined advantages of hyperspectral and high spatial resolution, offering precise monitoring methods for local-scale water quality parameters in small water bodies. This study employs airborne hyperspectral remote sensing image data to explore remote sensing estimation methods for total nitrogen (TN) and total phosphorus (TP) concentrations in Lake Dianshan, Yuandang, as well as its main inflow and outflow rivers. Our findings reveal the following: (1) Spectral bands between 700 and 750 nm show the highest correlation with TN and TP concentrations during the summer and autumn seasons. Spectral reflectance bands exhibit greater sensitivity to TN and TP concentrations compared to the winter and spring seasons. (2) Seasonal models developed using the Catboost method demonstrate significantly higher accuracy than other machine learning (ML) models. On the test set, the root mean square errors (RMSEs) are 0.6 mg/L for TN and 0.05 mg/L for TP concentrations, with average absolute percentage errors (MAPEs) of 23.77% and 25.14%, respectively. (3) Spatial distribution maps of the retrieved TN and TP concentrations indicate their dependence on exogenous inputs and close association with algal blooms. Higher TN and TP concentrations are observed near the inlet (Jishui Port), with reductions near the outlet (Lanlu Port), particularly for the TP concentration. Areas with intense algal blooms near shorelines generally exhibit higher TN and TP concentrations. This study offers valuable insights for processing small water bodies using airborne hyperspectral remote sensing images and provides reliable remote sensing techniques for lake water quality monitoring and management.

Water vapor content prediction based on neural network model selection and optimal fusion

Accurately predicting the evolution of water vapor content has significant practical engineering implications for accurately determining the timing of artificial rain enhancement operations. However, the nonlinear, unstable, and chaotic nature of water vapor content presents considerable challenges to its precise prediction. To address this, our research proposes a combined prediction model, based on a neural network model selection mechanism and small sample water vapor content data observed by microwave radiometers in the Zhengzhou area. This combined model utilizes seven neural network models as candidate models and dynamically selects the optimal three models as the central prediction components via evaluation indicators. Additionally, we employ the maximum information coefficient method to preserve the optimal input features and use a time-varying rate wave mode decomposition algorithm as the front-end processing module. This module processes the original water vapor content sequence and extracts relevant latent information. Finally, we incorporate the African vulture intelligent optimization algorithm as the backend processing component to optimize the weighted combination coefficients, achieving the integration of prediction results. Experimental results reveal that the Mean Absolute Percentage Errors (MAPE) of the proposed model on three types of water vapor content datasets are 0.208%, 0.876%, and 0.369%, respectively. This suggests a predictive performance improvement of at least 10% compared to existing models. The prediction model proposed in this study not only establishes an accurate and reliable mechanism for predicting water vapor content but also offers more comprehensive decision support information for weather modification operations.

Windows into the Recent Past: Simple Biotic Indices to Assess Hydrological Stability in Small, Isolated Ponds

This article presents the four biotic indices used to assess the hydrological stability of small, fishless, lowland ponds in northern Poland’s post-glacial landscape. The assessment was based on the analyses of the relative abundance of selected macroinvertebrate taxa caught using standard and non-lethal methods. The indices were derived from a multi-year analysis of data on invertebrate composition, abiotic water parameters, and publicly available satellite data. This allowed for the reconstruction of hydrological stability, including fluctuations in water level and surface area, as well as the frequency of drying, in small water bodies in the 5–10 years before sampling. The numerical relationships between the parameters describing hydrological stability and the relative abundance of several invertebrate taxa were described. A multiple regression analysis showed that hydrological stability was generally more strongly related to faunal composition than the other abiotic parameters. The indices used in this study can be a useful tool, particularly in citizen science. It is important that their numerical bases can be easily modified depending on the local conditions.

Improving spatial resolution of chlorophyll-a in the Mediterranean sea based on machine learning

The objective of this study is to increase the spatial resolution of data on the level of chlorophyll-a in the Mediterranean Sea using satellite images and ground measurements. The goal of this study is to develop an information technology based on machine learning to create chlorophyll-a concentration maps with high spatial resolution for the pilot areas of the Mediterranean Sea. Traditional ground-based methods for measuring chlorophyll-a are time-consuming, expensive, and have limited spatial and temporal coverage. Therefore, satellite observations have become an effective tool for monitoring chlorophyll-a over large areas. Low spatial resolution satellite data such as GCOM-C/SGLI and Sentinel-3 OLCI allow measurements of chlorophyll-a concentration at the sea surface. However, these data have limited accuracy and spatial resolution, which creates challenges for monitoring local changes in coastal zones and small water areas. Tasks: to analyze available satellite data and ground-based measurements of chlorophyll-a for the Mediterranean Sea; to investigate the correlation between satellite data of different spatial resolutions and ground measurements; to select informative features from satellite data for building machine learning models; and to develop models for increasing the spatial resolution of chlorophyll-a based on regression and machine learning algorithms. Obtained results: information technology combining satellite data with ground measurements in the Google Earth Engine cloud platform is proposed; correlations between satellite measurements of chlorophyll-a and ground data are investigated; models based on Random Forest and Multilayer Perceptron with coefficients of determination up to 0.36 and correlation of 0.6 with test data are built; chlorophyll-a maps with a spatial resolution of 10 m are created for the pilot area near Cyprus. Conclusions. The developed information technology allows the effective combination of satellite data of different spatial resolutions and ground measurements to increase the accuracy and detail of chlorophyll-a maps in the Mediterranean Sea. Further research involves improving the preprocessing of satellite data, using more features, involving data from other regions, and applying more sophisticated machine learning models.

Influence of Varying Oil-Water Contents on the Formation of Crude Oil Emulsion and Its Demulsification by a Lab-Grown Nonionic Demulsifier.

This study describes how varying oil/water contents affect emulsion formation and the impact they have on emulsion droplet size, viscosity, and interfacial behavior. Crude oil (continuous phase) volume fractions of 40, 50, 60, and 70 vol % were probed in the various W/O emulsions formed. Experimental results from optical morphology revealed the emulsion droplets kept reducing as the crude oil fraction kept increasing, while the droplets were nearly unnoticeable in the emulsions derived from 60 and 70% crude oil. The viscosity-shear rate of emulsions produced from 40, 50, and 60 vol % crude oil exhibited a non-Newtonian behavior owing to the substantial volume of water content in their emulsions, whereas the viscosity-shear rate of the emulsion with 70 vol % crude oil exhibited a Newtonian behavior similar to the pure crude oil, suggesting a thorough blending of oil-water at this crude oil fraction. Besides, the viscosity-temperature measurements revealed that the viscosity of these emulsions diminished as the temperature increased and the viscosity reduction became more noticeable in an emulsion comprising 70 vol % crude oil. In the interfacial assessment, the increased crude oil content in the produced emulsion led to a sharp reduction in the interfacial tension (IFT). The IFT values after 500 s contacts between the emulsion and water (surrounding phase) were 11.86, 10.02, 8.08, and 6.99 mN/m for 40, 50, 60, and 70 vol % crude oil, respectively. Demulsification experiments showed that water removal becomes more challenging with a large volume of crude oil and a small water content. Demulsification performances of the lab-grown nonionic demulsifier (NID) after 10 h of demulsification activity at room temperature (25 °C) were 98, 90, 17.5, and 10% for the emulsions formed from 40, 50, 60, and 70 vol % crude oil, respectively, indicating that the demulsification degree decreases with an increasing crude oil content. Viscosity-time determination was applied to affirm the activity of NID on the emulsion formulated with a 50% crude oil fraction. The injection of NID in this emulsion triggered a sharp viscosity reduction, indicating the adsorption of NID at the oil-water interface and disruption of emulsifiers, enabling emulsion stability.

High-Density, Conformable Conducting Polymer-Based Implantable Neural Probes for the Developing Brain.

Neurologic and neuropsychiatric disorders substantially impact the pediatric population, but there is a lack of dedicated devices for monitoring the developing brain in animal models, leading to gaps in mechanistic understanding of how brain functions emerge and their disruption in disease states. Due to the small size, fragility, and high water content of immature neural tissue, as well as the absence of a hardened skull to mechanically support rigid devices, conventional neural interface devices are poorly suited to acquire brain signals without inducing damage. Here, the authors design conformable, implantable, conducting polymer-based probes (NeuroShanks) for precise targeting in the developing mouse brain without the need for skull-attached, rigid mechanical support structures. These probes enable the acquisition of high spatiotemporal resolution neurophysiologic activity from superficial and deep brain regions across unanesthetized behavioral states without causing tissue disruption or device failure. Once implanted, probes are mechanically stable and permit precise, stable signal monitoring at the level of the local field potential and individual action potentials. These results support the translational potential of such devices for clinically indicated neurophysiologic recording in pediatric patients. Additionally, the role of organic bioelectronics as an enabling technology to address questions in developmental neuroscience is revealed.

Divergence of zooplankton assemblages in unstable fishless and stable fish ponds

This study aimed to achieve a better understanding of the features of zooplankton assemblages in small water bodies and their biodiversity and composition in relation to the presence of fish and accompanying environmental characteristics. This study was conducted in 16 mid-field ponds. Compositional and biodiversity indexes and ordination methods were used to analyze the relationship between zooplankton assemblages in unstable fishless and stable fish ponds. A total of 121 zooplankton taxa were identified. Compositional indicators revealed significant differences in zooplankton assemblages between fish ponds (FPs) and fishless ponds (FLPs). Canonical correspondence analysis indicated that variation in zooplankton assemblages depended on the ponds’ features. Most of the high trophic state indicator species were present only in FPs or occurred sporadically in FLPs. Rarefaction and extrapolation indicated a higher number of zooplankton taxa in FPs than in FLPs. The stability of the ecosystem was essential for maintaining the high species richness of zooplankton. Diversity indices were not influenced by variations in species composition or environmental differences among ponds. Diversified pond types are necessary to maintain the heterogeneity of mid-field ponds, which support the high regional biodiversity of zooplankton assemblages.

Characterising continental shelf waves and their drivers for the southeast coast of Australia

Low-lying, developed areas in New South Wales (NSW) are susceptible to extended periods of inundation, which cannot be attributed to tides or local synoptic conditions. This inundation is often associated with relatively small water level anomalies but is persistent enough to damage the built environment. Due to their long duration, continental shelf waves (CSWs) are one of the mechanisms of concern associated with extended coastal inundation. These waves are caused by a range of synoptic disturbances occurring along the mid-latitudes and they travel anticlockwise along the coast (in the southern hemisphere), reaching low latitudes of NSW. This study investigates the characteristics of CSWs that travel along the NSW coast, their generation and propagation mechanisms in relation to local synoptic and oceanic conditions, and their potential modulation by two major large-scale climate modes: the El Niño/Southern Oscillation and the Southern Annular Mode (SAM). We used time series of daily tidal residuals from 1994 to 2015 from nine locations along the NSW coast and used a peak over threshold approach to identify 29 waves which had an average amplitude of 0.3 m, mean period of 15 days (ranging from 8 to 20 days), and a highest occurrence in autumn and winter. The generation of CSWs is tightly coupled to the subpolar jet, the belt of westerlies, and the subtropical ridge, confirming that large-scale atmospheric circulation is a key element in the generation and propagation of CSWs. Through analyses of the inverse barometer, we found that CSWs propagate freely up to the north coast of NSW, independent of local weather conditions. We also found that CSWs are more frequent during the positive phase of SAM combined with La Niña and during neutral SAM combined with El Niño events. This study provides the longest database to date of CSWs for NSW, alongside new insights into their characteristics and timing and frequency of occurrence. Importantly, this information can be used to monitor their occurrence and forecast their impact, including the number of days taken for a wave to reach different locations along the NSW coast.

Response of Chironomids (Diptera, Chironomidae) to Environmental Factors at Different Spatial Scales.

Factors responsible for species distribution of benthic macroinvertebrates, including responses at different spatial scales, have been previously investigated. The aim of the present research was to review the most relevant factors explaining chironomid species distribution focusing on factors operating at different spatial scales, such as latitude, longitude, altitude, substrate, salinity, water temperature, current velocity, conductivity, acidity, dissolved oxygen, nutrient content etc. acting at regional levels and at a large or small water basin level. Data including chironomid species abundances from different lentic and lotic waters in Italy and other surrounding countries were analyzed using partial canonical correspondence analysis (pCCA) and multiple discriminant analysis (DISCR). Spatial analyses, including univariate Moran's I correlograms, multivariate Mantel correlograms and Moran's eigenvector maps (MEMs), were thereafter carried out. The results showed that habitat type, including different types of lotic waters (i.e., kryal, crenal, rhithral, potamal) and different lake types (i.e., littoral, sublittoral, profundal zones), is the most significant factor separating chironomid assemblages, while spatial factors act only as indirect influencers.

Wave trapping by porous breakwater near a wall under the influence of ocean current

In this paper, oblique water wave interaction with a surface piercing box-type porous structure placed in front of a vertical rigid wall is investigated in the presence of current, which flows parallel to vertical wall. The current speed is considered distinct in different subdomains. However, in a particular subdomain current speed is uniform throughout the water depth. In this analysis, Sollitt and Cross model is used for the study of wave motion inside the porous structure. Employing small amplitude linear water wave theory, the present model of our interest is developed into a boundary value problem and solved analytically using the eigenfunction expansion method. Using the developed solution, the reflection coefficient and hydrodynamic wave forces on porous structure are computed for different values of parameters: the dimension of porous structure, the friction coefficient of porous structure, the current speed of following current and opposing current. This research paper suggests that suitable arrangement of rigid walls and surface-piercing partially extended porous structures can be an effective and economical approach for guiding ocean currents and protecting marine facilities against wave attacks.

Operational analysis of lake Tana under climate change, Upper Blue Nile Basin, Ethiopia

The excessive abstraction of lake water affects its sustainability and is common in Lake Tana. Hence this study aims to develop operation rule curves for optimum operation of Lake Tana reservoir by considering the effects of small and large-scale irrigation water abstraction, Hydropower demand, and climate change. The data used in this study were produced by two Global Circulation Models (GCMs) (MIROC5 and MPI) under two Representative Concentration Pathways (RCP4.5 and RCP8.5) in the 2040s (2020–2049) and 2070s (2050–2079). For RCP4.5 and RCP 8.5 scenarios of the 2040s- and 2070s-time domains, lake temperature exhibits an upward trend. The lake rainfall also will show an increase for the 2040s and 2070s under both RCP scenarios. The outcome showed that in all future scenarios, lake evaporation under RCP4.5 of 2040s and 2070s rise between 3.6 % to 7 % and 4.6 % to 19, respectively, while for RCP8.5 of 2040s and 2070s increases between 4.6 % to 9.9 % and 9.2 % to 24.7 %. The surface water inflow increased for RCP4.5 (2070s) and RCP8.5 (2040s), whereas it declined for RCP4.5 (the 2040s) and RCP8.5 (2070s. Under both scenarios, the average value of the time-based and volumetric reliability in the 2040s and 2070s is less than 80 %. The reservoir will take a very long time to recover from the shortfall as the resilience levels are below 50 %. Additionally, the dimensionless vulnerability was less than 50 %, indicating that there won't be a shortage of inflow to meet demand at the reservoir. Based on evaluation, the reservoir will not probably perform well in any way because of the rise in upstream abstractions. To guide the operation of the reservoir, operation rule curves were developed using the Hec-ResSim model. Generally, the government, decisions, and policymakers should set a water resources management plan not trigger normal functioning of the Lake system.

AiWATERS: an artificial intelligence framework for the water sector

The presence of Artificial Intelligence (AI) and Machine Learning (ML) applications has led to its widespread adoption across diverse domains. AI is making its way into industry, beyond research and academia. Concurrently, the water sector is undergoing a digital transformation. Water utilities in the United States are at different stages in their journey of digital transformation, and the decision makers in water sector, who are non-expert stakeholders in AI applications, need to better understand this technology to make informed decisions. While AI has numerous benefits to offer, there are also many challenges related to data, model development, knowledge integration and ethical concerns that should be considered before implementing it for real world applications. Civil engineering is a licensed profession where critical decision making is involved. Therefore, trust in any decision support technology is critical for its acceptance in real-world applications. Therefore, this research proposes a framework called aiWATERS (Artificial Intelligence for the Water Sector) which can serve as a guide for the water utilities to successfully implement AI in their system. Based on this framework, we conduct pilot interviews and surveys with various small, medium, and large water utilities in the United States (US) to capture their current state of AI implementation and identify the challenges faced by them. The research findings reveal that most of the water utilities in the United States are at an early stage of implementing AI as they face concerns regarding the black box nature, trustworthiness, and sustainability of AI technology in their system. The aiWATERS framework is intended to help the utilities navigate through these issues in their journey of digital transformation.

Predicting Model Biases of the APOLLO3 Neutronics Code Using Machine Learning: Toward a Multiscale and Multifidelity Approach

As part of the verification, validation, and uncertainty quantification process applied to neutronics deterministic codes, there is a requirement to expand the validation domain, especially to accommodate new third-generation reactors. The objective of the present work is to estimate the numerical biases arising from the several approximations used in deterministic codes and across different points in the phase space. Typically, this is accomplished by comparing the deterministic code to be validated with a Monte Carlo or stochastic reference code (without significant approximations). Since these reference calculations are computationally expensive, this paper proposes an alternative approach for predicting model biases of the APOLLO3® deterministic code for third-generation pressurized water reactors using machine learning algorithms. Three types of metamodels are employed (polynomial regression, kriging, and neural networks). Two scales are investigated, from a single assembly to a cluster of 3 × 3 assemblies [small two-dimensional (2-D) core], with model biases evaluated for APOLLO3 schemes with various levels of accuracy (lattice and core solvers, with high- to low-fidelity approaches). For the small 2-D core, numerical biases are observed for reactivity and power peak, representing both global and local quantities of interest. Throughout the study, the best results are achieved using kriging or neural networks, even if polynomial regression provides satisfactory predictions in some cases. The possibility of predicting biases for different quantities is also introduced. In conclusion, this paper discusses the prospects of extending the applicability of these metamodels to small and large third-generation pressurized water reactor cores, the idea being to potentially use these metamodels to support safety demonstrations for the new reactors in the long term.

Is there a fast track (“Darmstrasse”) for fluids in the small intestine? Evidence from magnetic resonance imaging

BackgroundThe transit and distribution pattern of fluids in the small intestine is a key parameter for the dissolution and absorption of drugs. Although some information is known about the small intestinal water content after administration of fluid volumes and meals, the intestinal transit of orally ingested fluids and solutions has been barely investigated. The aim of this three-arm, cross-over, 9-subject human study was to investigate the transit of orally ingested water in the small intestine under fasting and postprandial conditions using MRI. To identify the ingested water, manganese gluconate, which can be identified with T1-weighted MRI sequences, was added as a marker. Using Horos (DICOM software), quantification of the distribution of Mn2+ ions in the gastrointestinal tract in fasted versus fed state (standard meal by FDA guidance and a light meal) was possible. The distribution and approximate wetted intestinal length was very similar in the fasting and postprandial states, suggesting rapid transport of water ingested after a meal through the chyme-filled small intestine in continuation of the “Magenstrasse” (stomach road). In some subjects, manganese gluconate reached deeper parts of the small intestine even more quickly in the postprandial state than in the fasting arm of the study. A deeper understanding of the behaviour of solutes in the gastrointestinal tract is fundamental to a mechanistic explanation for the kinetic interaction between food and drug intake (food effects).

The effect of curved membrane electrode assemblies on performances of parallel and interdigitated flow field PEMFCs with wavelike gas channels

The effect of curved membrane electrode assemblies (MEAs) on performances of parallel and interdigitated flow field PEMFCs with wavelike gas channels (GCs) are for the first time investigated at various curved MEA deformation levels, where the curved MEA is triggered by the pressure difference between anodes and cathodes. The results show that on the cathode side of parallel flow field PEMFCs with wavelike GCs, the oxygen consumption and liquid water generation are small with the increased MEA deformation level at the high operation voltage being larger than 0.8 V, leading to the constant cell performance, that is, leading to the constant output current density. However, the current density is first increased and then decreased with the increased MEA deformation level at the low operation voltage being less than 0.8 V. Because at the low operation voltage, the oxygen consumption and liquid water generation are significantly increased and affected by the increased MEA deformation level. When the MEA deformation level is increased at the high operation voltage being larger than 0.8 V, the current density of interdigitated flow PEMFCs with wavelike GCs is also constant because of small oxygen consumptions and liquid water generations. However the oxygen consumption and liquid water generation are large enough and depend on the oxygen transport and liquid water removal at the low operation voltage being less than 0.8 V. At the low voltage, the oxygen transport and liquid water removal are modified by the increased MEA deformation level. Consequently the current density is first decreased and then increased at the low operation voltage.

Overheated children's playgrounds in Central European cities: The effects of surfaces and shading on thermal exposure during hot summer days

Thermal exposure in children's playgrounds is a specific issue in relation to outdoor thermal comfort. In moderate climate regions, playgrounds are prone to overheating on hot summer days. When aiming for a safe design for playgrounds, different thermal conditions with various active surfaces and shading solutions, both natural and artificial, should be considered. Twelve case studies were performed in four Czech cities to quantify the differences in thermal exposure between individual types of active surface and shading, using mean radiant temperature and the biometeorological indices UTCI and PET (plus its experimental child-specific adjustments) as an expression of the thermal environment on hot summer days. The highest thermal exposure appeared above gravel, followed by rubber. Nevertheless, apart from a slightly lower thermal exposure above maintained lawn, substantial positive microclimatic effect of natural surfaces, such as bark mulch, sand, or a small water pool, was not confirmed. In terms of shading, trees provide more pronounced cooling effect than shade sails, but even the latter are effective in substantially reducing heat stress. Analyses of experimental adjustment of PET further indicate the importance of considering the specifics of a child's organism and behavioural adaptation measures when addressing thermal comfort and heat stress in playgrounds.

Effects of liquid water injection on flame surface topology and propagation characteristics in spray flames: A direct numerical simulation analysis

The effects of water injection on flame surface topology and local flame propagation characteristics have been analyzed for statistically planar turbulent n-heptane spray flames with an overall (i.e., liquid + gaseous) equivalence ratio of unity using carrier-phase direct numerical simulations. Most fuel droplets have been found to evaporate as they approach the flame even though some droplets can survive until the burnt gas side is reached, whereas water droplets do not significantly evaporate ahead of the flame and the evaporation of water droplets starts to take place in the reaction zone and is completed within the burnt gas. However, the gaseous-phase combustion occurs predominantly in fuel–lean mode although the overall equivalence ratio remains equal to unity. The water injection has been found to suppress the fuel droplet-induced flame wrinkling of the progress variable isosurface under the laminar condition, and this effect is particularly strong for small water droplets. However, turbulence-induced flame wrinkling masks these effects, and thus, water injection does not have any significant impact on flame wrinkling for the turbulent cases considered here. The higher rate of evaporation and the associated high latent heat extraction for smaller water droplets induce stronger cooling effects, which weakens the effects of chemical reaction. This is reflected in the decrease in the mean values of density-weighted displacement speed with decreasing water droplet diameter. The weakening of flame wrinkling as a result of injection of small water droplets is explained through the curvature dependence of the density-weighted displacement speed. The combined influence of cooling induced by the latent heat extraction of water droplets and flame surface flattening leads to a decrease in volume-integrated burning rate with decreasing water droplet diameter in the laminar cases, whereas the cooling effects are primarily responsible for the drop in burning rate with decreasing water droplet diameter in the turbulent cases.

Ecological restoration trajectory of the Taitema Lake wetland in arid northwest China: A 36-year wetland health assessment using Landsat time series data

The Taitema Lake wetland in the lower reaches of the Tarim River (northwest China) is sensitive to hydrological changes and provides necessary ecosystem functions for biodiversity conservation. Monitoring and evaluating the long-term dynamics of the Taitema Lake wetland is essential for conserving and restoring regional wetland ecosystems. This paper used a dense time series of Landsat images from 1986 to 2021 to map the Taitema Lake wetlands. It analyzed the annual and seasonal variations of the wetlands by ten ecological indicators, which include area extent, vegetation, hydrology, and landscape features. A systematic assessment of the ecological quality of the wetlands over the past 36 years, along with their influencing factors, was conducted from the perspective of wetland health. The results showed that (1) the recovered water areas and the wetlands showed a clear trend of ecological restoration since 2000, accompanied by an increased fragmentation. The total wetland area increased from 69.95 km2 in 1986 to 1164.47 km2 in 2021, with a 15.6-fold increase, and the vegetation area increased twentyfold to 639.84 km2. (2) The wetness in the core zone increased consistently across seasons, coupled with a simultaneous vegetation expansion surrounding the core zone. The areas with increasing wetness levels account for 48 % during winter and spring, and the areas with vegetation expansion account for 81 % and 72 % in summer and autumn, respectively. (3) The wetland ecological health status recovered to a “Good” level in 2021 and has not reached the “Excellent” status. The expansion of the water body is the primary driver behind the promotion of wetland ecological recovery. Small water bodies within the area range of 0.05 to 0.1 km2 notably exhibited the most stimulating effects on the wetlands. Thus, increasing the count of smaller water bodies helps rehabilitate vegetation growth and mitigating the water supply’s stress to sustain large lacustrine bodies.

Avoidable Cost Concept on Reducing Production Costs of Refillable Drinking Water Industry SME

Production costs are related to the determination of selling prices so they need to be controlled to control prices in the market. Production costs affect the level of profitability of the company. The purpose of this study is to exploit the extent to which avoidable costs can be reduced in determining production costs. By making some adjustments to production costs such as making efficiency, the production amount of the company's profitability can increase compared to the production costs that are still high. The research was conducted in several small industry-based refillable drinking water industries in the Moncong Loe Region. The analysis technique used is descriptive quantitative with cost accounting calculation method. The results showed that there is a possibility of avoiding some production costs of the refill drinking water industry. Because ineffective costs can be reduced. Based on the evaluation, it can be seen that the production costs applied so far are still high by the indirect raw material costs used. Indirect labor costs also exist but are still seen as costs for routine work. Thus, production costs can be controlled by avoiding some costs so that the selling price can be reduced.