Small Water Research Articles

Abstract Lentic freshwater systems such as ponds, lakes and reservoirs play an important role as drinking water sources or recreational venues. Algal and cyanobacterial blooms may pose a risk for water consumers and users, particularly in episodes of proliferation of toxin-produces species. The inactivation with ultraviolet (UV) light is currently used in drinking water purification as well as for ecological restoration of small water bodies. Traditional UV mercury lamps are expected to be replaced by recently developed UV-LEDs. The objective of this study is to evaluate the efficacy of the UV irradiation with LEDs emitting at 275 nm for the inactivation of phytoplanktonic organisms in two reservoirs, using different determination approaches and focusing on the changes on the species composition as well as on the potential production of cyanotoxins after UV exposure. The results revealed that the concentration of viable phytoplankton was reduced by more than 99.9% when applying UV doses of 55.7 mJ cm −2 . However, the UV treatment up to 100 mJ cm −2 promoted the predominance of cyanobacteria with respect to other species, and triggered the production of microcystins, if the treated water is release into a confined environment with availability of light and nutrients.

ABSTRACT The Hindu Kush Himalaya (HKH), known as the “Water Tower of Asia”, faces mounting challenges from climate change, accelerated glacial retreat, intensified land-use changes, and transboundary water management complexities, leading to significant hydrological transformations that threaten regional water sustainability. To address the urgent need for precise water monitoring, we produced the comprehensive 10-meter resolution surface water dataset (HKH-SWD10m) for the HKH region spanning from 2016 to 2022. The dataset is produced by developing a Vision Transformer-based deep learning network optimized for rapid, automated water extraction. The resulting network achieved exceptional performance metrics on our test dataset, with an Overall Accuracy (OA) of 0.9981, an Intersection over Union (IoU) of 0.9734, and a Kappa of 0.9855. Extensive validation using 15,000 stratified random sampling points demonstrated high accuracy with an OA of 0.9787, a Producer’s Accuracy (PA) of 0.9638, a User’s Accuracy (UA) of 0.9856, and a Kappa of 0.9476. Comparative analysis with the 30-meter resolution Global Surface Water (GSW) dataset revealed that HKH-SWD10m is generally consistent with the GSW product but captures more small water bodies while providing superior boundary delineation precision. Based on the HKH-SWD10m dataset, we analyzed changes of surface water in the HKH over the years 2016–2022. Our interannual analysis (2016–2022) not only corroborates previous hydrological findings but reveals novel sub-regional divergence in surface water trends when analyzed through national and basin-level frameworks, suggesting localized climate impacts. This dataset advances hydrological monitoring capabilities by offering unprecedented spatial-temporal resolution for the HKH, serving as a critical resource for water security assessments, ecosystem management, and climate adaptation strategies. The HKH-SWD10m dataset is publicly available through Zenodo (https://doi.org/10.5281/zenodo.15067176) and National Earth System Science Data Center of China (https://doi.org/10.12041/geodata.551748804486886.ver1.db).

A control-oriented hybrid modeling method for small pressurized water reactors based on linear models and neural networks

Reactor power regulation of a small pressurized water reactor based on linear active disturbance rejection control with gain scheduling

Small rural water utilities in the Appalachia region of the US often experience extreme water loss while struggling to maintain water quality compliance. This study quantifies the impact of reducing water loss on distribution system water quality in Martin County, Kentucky. Hydraulic and water quality models were developed, calibrated, and validated using EPANET for chlorine residuals and KYPIPE for trihalomethane (TTHM) formation. The models evaluated water loss reduction scenarios ranging from the current 70% to the industry target of 15%. Results showed that lowering water loss increased residence times, causing chlorine residual declines of 22–68%, with one site falling to the 0.2 mg/L threshold. TTHM concentrations increased by 12–18% in winter–spring and 26–44% in summer–fall, with two sites exceeding the individual 0.080 mg/L maximum contaminant level. These novel findings indicate that reducing water loss can unintentionally degrade water quality, underscoring the need for integrated planning. Recommended mitigation strategies include seasonal operational adjustments, water source and TTHM precursor management, optimized tank management, targeted flushing, and phased infrastructure upgrades. The modeling framework developed offers potential for broader application in other rural systems facing similar challenges.

ABSTRACT Small and fragmented surface water bodies play critical roles in local hydrology, ecosystem functioning, and climate regulation. However, the prevalent 10-m resolution of current large-scale water products fails to adequately capture these features, limiting their applicability in high-precision monitoring and ecological assessments. To address this gap, we developed a novel method for generating sub-metre surface water maps using freely available Sentinel-1/2 imagery. Our workflow involves four key steps: (1) extracting seven spectral features to enhance the spectral separability of surface water; (2) developing a deep learning-based semantic segmentation framework that integrates super-resolution reconstruction; (3) generating sub-metre reference data via object-based classification of high-resolution Google Earth imagery; and (4) training and applying the model across four representative regions in China. The resulting maps achieved high accuracy (precision: 97.22%–98.22%; recall: 97.82%–98.77%; F1-score: 97.63%–98.50%) and demonstrated a substantially improved detection rate for small water bodies compared to the 10-m ESA WorldCover v100 product and the Automated Water Extraction Index (AWEI). In addition to enhanced spatial fidelity, the proposed method is fully transferable across regions and offers strong potential for temporal analysis, thereby supporting high-resolution, long-term monitoring of surface water dynamics from existing medium-resolution archives. This study presents a practical and adaptable framework for improving the accuracy of surface water mapping by utilizing open-access satellite imagery, with potential for application across diverse geographic contexts and sustainability-driven initiatives.

The diversity of water clusters is due not only to the different hydrogen (H-) bond network topology but also to the different arrangement of hydrogen atoms (protons) in the H-bonds. The polyhedral shape is typical for the smallest water clusters. Gas hydrate cavities are also polyhedral, which increases the practical interest in studying the properties of polyhedral water clusters. For theory, the structural homogeneity of these clusters, in which all molecules are in equivalent positions, is of particular importance. It is no coincidence that a simple discrete model of intermolecular interactions was initially developed for polyhedral water clusters. The model of strong and weak effective H-bonds (SWEB model) allows classifying the entire set of proton configurations by energy. This article is devoted to the study of the energetics of proton configurations of all three-coordinated water polyhedra with the number of molecules less than 20. The peculiarity of this article is that the selection of candidates for the lowest-energy configurations is carried out using the discrete approach, taking into account the number of the most preferred types of H-bonds, a simplified estimate of the total dipole moment and the number of molecules located in the planes of the square faces.

Single-crystal layered perovskite heterostructures provide a scalable platform for potentially realizing emergent properties recently seen in mechanically stacked monolayers. We report two new layered perovskite heterostructures M2(PbCl2)(AMCHC)2(PbCl4)·2H2O (1_M where M = Na+, Li+; AMCHC = +NH3CH2C6H10COO-) crystallizing in the chiral, polar space group C2. The heterostructures exhibit alternating layers of a lead-chloride perovskite and an intergrowth comprising corner-sharing PbCl4(η2-COO)2 polyhedra with bridging equatorial chlorides and terminal axial oxygen ligands. Small alkali metal cations and water molecules occupy the cavities between the polyhedra in the intergrowth layer. The heterostructures display wide bandgaps, two closely spaced excitonic features in their optical spectra, and strong second harmonic generation. The calculated band structure of 1_Na features a Type-I quantum-well structure, where the electron-hole correlation function corresponding to the lowest excited state points to electron-hole pairs localized within a single inorganic layer (intralayer excitons), as seen in typical layered halide perovskites. In contrast, calculations show that 1_Li adopts a Type-II quantum-well structure, with electrons and holes in the lowest excited state residing in different inorganic layers (interlayer excitons). Calculations on model complexes suggest that these changes in band alignment, between Type-I and Type-II quantum-well structures, are driven by the placement of the alkali metal and the orientation of the water molecules, changing the electrostatic potential-energy profiles of the heterostructures. Thus, this study sets the stage for accessing different alignments of the perovskite and intergrowth bands in bulk perovskite heterostructures that self-assemble in solution.

ABSTRACT Abundant water resources in rice cultivation areas foster ecological symbiosis through small water bodies; however, these systems are also potential hotspots for greenhouse gas (GHG) emissions. Driven by economic incentives, these aquatic systems have transitioned from natural states to extensive aquaculture and subsequently to intensive, complicating the quantification of emission dynamics and underlying mechanisms. We conducted an annual GHG flux monitoring and metagenomic analysis across four agricultural water systems in Hubei, China. These waterbodies cover both traditional and aquaculture‐oriented types: traditional paddy field ditches (PD), crayfish ditches (CD, converted from PD in 2017), crayfish aquaculture ponds (CP, converted from CD in 2020), and fish aquaculture ponds (FP, converted from PD in 2008). Our findings reveal that all systems acted as net GHG sources, but their global warming potential (GWP) varied over 15‐fold (636–10,049 kg CO 2 ‐eq ha −1 y −1 ), driven by substrate properties and environmental gradients. CD exhibited the highest GWP, where metagenomics revealed carbon input elevated methanogenic gene abundance by 2.15‐fold compared to PD, establishing methane (CH 4 ; contributing 79.9% of the GWP) as the primary contributor. In contrast, continuous aeration in FP suppressed CH 4 emissions but induced substantial nitrous oxide (N 2 O) release through nitrate accumulation. Both denitrification and nitrification pathways contributed substantially to N 2 O production in FP, leading to the second‐highest GWP. Notably, the meticulous cultivation of aquatic plants, aimed at augmenting oxygen release and nitrogen uptake in CP, unexpectedly not only reduced CH 4 emissions but also transformed the system into a sink for both CO 2 and N 2 O through coordinated microbial community restructuring and substrate properties. This transition was accompanied by reduced gene abundances associated with nitrification, denitrification, and TCA cycle pathways, ultimately achieving the lowest GWP among the four systems. In summary, our study elucidates novel insights into the limiting factors governing GHG emissions under land‐use transitions in agricultural small water bodies, while providing actionable strategies for climate change mitigation.

The endangered lake minnow, Rhynchocypris percnurus (Pallas, 1814), has been known from Lithuanian inland waters for over 20 years, but we have a very limited understanding of its current population size. The main purpose of this study was to provide a concise account of the species in Lithuania, including a rough assessment of threats to its populations and habitats. In 2018–2019, we investigated 360 small water bodies across the country, all of which were potentially suitable for lake minnows. Results revealed that lake minnows were present in only 12 water bodies, all concentrated in one regional park in the southern part of the country. However, by 2024 the species had gone extinct at nine of these sites due to habitat loss. At present (2025), only one viable Lithuanian population of this species can be considered to exist. Our results conclusively show that the species is on the very edge of extinction. Urgent action is needed to protect this species in Lithuanian waters, with special emphasis on revitalizing its most suitable habitats and translocating fish from the only currently known population in Lithuania.

Abstract Greenhouse gas emissions from Arctic tundra ponds and permafrost thaw provide important positive feedbacks to global warming. However, a high landscape heterogeneity and small size of ponds make it challenging to assess trends in surface water extent and associated carbon and energy fluxes, especially in the understudied Eastern Siberian tundra. Here, we show that surface water extent in these landscapes can be highly dynamic, shaped by small-scale pond processes. Using a time-series of aerial imagery at 12 cm resolution spanning eight years (2014–2021), we classified surface water at three sites in Kytalyk National Park and traced all 465 ponds (i.e. patches of surface water) larger than 1 m2. The total surface water extent at the sites varied between 102%-124% relative to the time-series mean, without significant trends in contrast to previous reports. Individual pond area fluctuated by 52% on average, and two thirds of ponds were present for less than six years. One-quarter of ponds showed evidence for thermokarst or vegetation colonisation as drivers of change, based on our high-resolution surface elevation models. These findings highlight that tundra ponds in Siberia can be highly dynamic in nature and stresses the need for improved change detection of very small surface water bodies in remote sensing analyses to better model carbon and energy fluxes in the tundra biome.

In order to mitigate defects in asphalt pavements and enhance the performance of asphalt mixtures, the incorporation of fibers into these mixtures has emerged as an effective strategy. Traditional asphalt mixture modification typically involves the addition of a single type of fiber; however, this method is no longer sufficient to meet the performance requirements of asphalt mixtures and has certain limitations. This research represents the inaugural effort to concurrently integrate bamboo fiber and ceramic fiber into asphalt mixtures, with the objective of harnessing the beneficial properties of both fibers to improve high-temperature stability, low-temperature crack resistance, and water stability. The performance of the asphalt mixture was assessed through a series of tests, including wheel rutting, small beam bending, freeze-thaw splitting, and water immersion Marshall tests. The optimal combinations of fiber content were identified utilizing the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methodologies. Additionally, the microscopic modification mechanisms of the fibers within the asphalt mixtures were investigated through scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The findings demonstrate that the incorporation of a bamboo-ceramic fiber composite significantly enhances the high-temperature performance and water stability of the base asphalt mixture by as much as 40% and 30%, respectively, while also improving low-temperature performance by a minimum of 8%. The two types of fibers exhibit synergistic benefits. Utilizing the AHP-TOPSIS model, the optimal blend ratio was identified as 0.3% bamboo fiber and 0.6% ceramic fiber. The incorporation of these fibers occurs through a physical process that does not involve the formation of new chemical bonds, thereby enhancing the road performance of the asphalt mixture through mechanisms such as adsorption, bridging, and tackifying effects.

The aim is the forecast of the leptospirosis epidemic manifestations for 2025 in the Russian Federation based on an analysis of the long-term incidence and the epizootiological monitoring data from 2024. Leptospirosis foci are a worldwide public health problem. In the Russian Federation, the average annual incidence of leptospirosis for 2000–2024 (excluding 2020–2021) is 0.39±0.084 per 100 thousand population, mainly sporadic cases are registered, mortality remains high and varies from 2.1 to 8.4 %. In 2024, human leptospirosis was established in all federal districts with maximum incidence levels in the North-Western and Southern federal Districts. Infection with pathogenic Leptospira in small mammals and water was detected in 60 subjects of the Russian Federation in all federal districts. The main volume of the population specific prevention falls on the Southern Federal District and accounts 85.5 % from 15,156 vaccinated. Human disease risks persist in areas with active leptospirosis natural foci, especially in the Central, Far Eastern and North-Western Federal Districts. Imported cases of infection are possible both from highly endemic countries and between the territories of the Russian Federation.

Accurate mapping of small water structures and streambeds is essential for hydrological modeling, erosion control, and landscape management. While traditional geodetic methods such as GNSS and total stations provide high precision, they are time-consuming and require specialized equipment. Recent advances in mobile technology, particularly smartphones equipped with LiDAR sensors, offer a potential alternative for rapid and cost-effective field data collection. This study assesses the accuracy of the iPhone 14 Pro's built-in LiDAR sensor for mapping streambeds and retention structures in challenging terrain. The test site was the Dílský stream in the Oslavany cadastral area, characterized by steep slopes, rocky surfaces, and dense vegetation. The stream channel and water structures were first surveyed using GNSS and a total station and subsequently re-measured with the iPhone. Several scanning workflows were tested to evaluate field applicability. Results show that the iPhone LiDAR sensor can capture landscape features with useful accuracy when supported by reference points spaced every 20 m, achieving a vertical RMSE of 0.16 m. Retention structures were mapped with an average positional error of 7%, with deviations of up to 0.20 m in complex or vegetated areas. The findings highlight the potential of smartphone LiDAR for rapid, small-scale mapping, while acknowledging its limitations in rugged environments.

Influences of coil diameter and pitch of helical-coiled tubes on flow instability in OTSG of small modular pressurized water reactor

Machine learning-driven method for in-situ high-frequency CH4 measurement in paddy fields based on water-soil-air factors: A case study of the Yangtze River Basin.

Rainfall can significantly reduce pond methane emissions by depressing ebullition.

Climate change (CC) is altering the working conditions for water suppliers. To enhance preparedness, CC has been emphasised in the risk-based approach (RBA) and water safety planning guidelines. We studied how the RBA approach has been applied in small water supplies in the Nordic countries to mitigate CC related risks and impacts. We interviewed small water supply operators and authorities in each country, followed up by government-level queries on guidelines and legislation. We found that small water supplies have experienced consequential incidents associated with a changing climate. Heavy rains, drought, changes in cold climate hydrology, and landslides were most frequently mentioned. Many of the supplies, however, had not experienced any effects, possibly because groundwater is the main water source for small water supplies in the region. Importantly, the effects of a changing climate were scarcely discussed, and CC receives limited or no attention in governmental guidelines. However, in Norway, the CC preparedness was analysed on a municipal level, and Finland and Sweden have tools for CC preparedness, but separately from the RBA. Small suppliers are concerned about over-burdening with multiple guidelines, frameworks, and tools. Therefore, we conclude that CC would be best addressed through integration into RBA and water safety planning regulation and implementation.

Classification of polyhedral small water clusters by {N,N,N,N} notations and study on numbers of surface hydrogen bonds and surface hydrogen-bonded rings

Technical and economic analysis of pump-as-turbine systems versus commercial turbines for harnessing energy from small water potentials