Search Results (11)

Tidal flats play a vital role in coastal ecosystems by supporting biodiversity, mitigating natural hazards, and functioning as blue carbon reservoirs. However, monitoring their geomorphological changes remains challenging due to high turbidity, shallow depths, and tidal variability. Conventional approaches—such as satellite remote sensing, acoustic sounding, and topographic LiDAR—face limitations in resolution, accessibility, or coverage of submerged areas. Airborne bathymetric LiDAR (ABL), which uses green laser pulses to detect reflections from both the water surface and seabed, has emerged as a promising alternative. Unlike traditional discrete-return data, full waveform analysis offers greater accuracy, resolution, and reliability, enabling more flexible point cloud generation and extraction of additional signal parameters. A critical step in ABL processing is waveform decomposition, which separates complex returns into individual components. Conventional methods typically assume fixed models with three returns (water surface, water column, bottom), which perform adequately in clear waters but deteriorate under shallow and turbid conditions. To address these limitations, we propose an adaptive progressive Gaussian decomposition (APGD) tailored to tidal flat environments. APGD introduces adaptive signal range selection and termination criteria to suppress noise, better accommodate asymmetric echoes, and incorporates a water-layer classification module. Validation with datasets from Korea’s west coast tidal flats acquired by the Seahawk ABL system demonstrates that APGD outperforms both the vendor software and the conventional PGD, yielding higher reliability in bottom detection and improved bathymetric completeness. At the two test sites with different turbidity conditions, APGD achieved seabed coverage ratios of 66.7–70.4% and bottom-classification accuracies of 97.3% and 96.7%. Depth accuracy assessments further confirmed that APGD reduced mean depth errors compared with PGD, effectively minimizing systematic bias in bathymetric estimation. These results demonstrate APGD as a practical and effective tool for enhancing tidal flat monitoring and management. Full article

To foster innovation in stored energy solutions and advance the development of green energy, this work presents a novel energy storage patented technology which involves storing energy in subsurface fractures through pumping. A new mechanical model was established to examine how variations in fracture size and operating parameters (i.e., injection and flow-back rates) modulate the scale and efficiency of energy storage under various geological conditions, and an optimized design scheme is proposed. The study demonstrates that both the scale and efficiency of energy storage are influenced by geological conditions. Selecting reservoirs with greater fracture toughness or lower permeability can achieve higher efficiency. Additionally, increasing reservoir fracture toughness also significantly enhances the scale of energy storage. Variations in geological conditions have a small impact on the optimal design of fracture size and injection/flow-back rate. Whether dealing with shallow penny-shaped fractures or deep elliptical fractures, using a moderate injection/flow-back rate in larger fractures is the optimal approach. The model presented in this paper is essential for tackling design challenges and interpreting data in subsurface pumping energy storage field applications. Full article

The Zigui Basin, located in the Three Gorges Reservoir Area, has developed numerous landslides due to its interlayering of sandstone and mudstone, geological structure, and reservoir operations. This study identifies a fourth type of landslide failure mode: an oblique-dip slope wedge (OdSW) landslide, based on the Wanshuitian landslide. Following four heavy rainfall events from 3 to 13 July 2024, this landslide exhibited significant deformation on the 17th and was completely destroyed within 40 min. The dimensions of the landslide were 350 m in length, 160 m in width, and 20 m in thickness, with a volume estimated at 8.0 × 10⁵ m³. The characteristics of landslide deformation and the changes in moisture content within the shallow slide body were ascertained using unmanned aerial vehicles, moisture meters, and mobile phone photography. The landslide was identified to have occurred within the weathered residual layer of mudstone, situated between two sandstone layers, with the eastern boundary defined by an inclined rock layer. Upon transitioning into the accelerated deformation stage, the landslide initially exhibited uniform overall sliding deformation, culminating in accelerated deformation destruction. The dip structure created terrain disparities, resulting in a step-like terrain on the left bank and gentler slopes on the right bank, with interbedded soil and rock in a shallow layer, because the interlayered soft and hard geological conditions caused varied weathering and erosion patterns on the riverbank slopes. The interbedded weak–hard stratum layer fostered the development of the oblique-dip slope wedge landslide. Based on the improved Green–Ampt model, we developed a stability prediction methodology for an oblique-dip slope wedge landslide and determined the rainfall infiltration depth threshold of the Wanshuitian landslide (9.8 m). This study aimed not merely to sharpen the evolution mechanism and stability prediction of the Wanshuitian landslide but also to formulate more effective landslide-monitoring strategies and emergency management measures. Full article

The effects of climate change are particularly pronounced in cities, where urban green infrastructure—such as trees, parks, and green spaces—plays a vital role in both climate adaptation and mitigation. This study assesses the carbon sequestration potential of urban forests in Budapest, the capital city of Hungary, which lies at the intersection of the Great Hungarian Plain and the Buda Hills, and is traversed by the Danube River. The city is characterized by a temperate climate with hot summers and cold winters, and a diverse range of soil types, including shallow Leptosols and Cambisols in the limestone and dolomite hills of Buda, well-developed Luvisols and Regosols in the valleys, Fluvisols and Arenosols in the flood-affected areas of Pest, and Technosols found on both sides of the city. The assessment utilizes data from the National Forestry Database and the Copernicus Land Monitoring Service High Resolution Layer Tree Cover Density. The results show that Budapest’s urban forests and trees contribute an estimated annual carbon offset of −41,338 tCO₂, approximately 1% of the city’s total emissions. The urban forests on the Buda and Pest sides of the city exhibit notable differences in carbon sequestration and storage, age class structure, tree species composition, and naturalness. On the Buda side, older semi-natural forests dominated by native species primarily act as in situ carbon reservoirs, with limited additional sequestration capacity due to their older age, slower growth, and longer rotation periods. In contrast, the Pest-side forests, which are primarily extensively managed introduced forests and tree plantations, contain a higher proportion of non-native species such as black locust (Robinia pseudoacacia) and hybrid poplars (Populus × euramericana). Despite harsher climatic conditions, Pest-side forests perform better in carbon sink capacity compared to those on the Buda side, as they are younger, with lower carbon stocks but higher sequestration rates. Our findings provide valuable insights for the development of climate-resilient urban forestry and planning strategies, emphasizing the importance of enhancing the long-term carbon sequestration potential of urban forests. Full article

Floating photovoltaic (FPV) systems can play an important role in energy transition. Yet, so far, not much is known about the effects of FPV systems on water quality and ecology. A sun-tracking FPV system (24% coverage) was installed on a shallow drinking water reservoir. We observed for the first time that benthic cyanobacteria (blue-green algae), which can deteriorate water quality, developed massively under the FPV system, while macrophytes and benthic algae, such as Chara (stonewort), mostly disappeared. Calculations of light availability explain this shift. The natural mixing of the water column was hardly affected, and the average temperature of the reservoir was not altered significantly. Biofouling of the water-submerged part of the FPV system consisted mostly of a massive attachment of Dreissena mussels, which affected water quality. Water bird numbers and concentrations of faecal bacteria were similar after the installation of the FPV system. Especially in shallow, transparent water bodies, there is a significant risk of FPV systems promoting the growth of undesirable benthic cyanobacteria. Overall, these new insights can aid water managers and governmental institutions in assessing the risks of FPV systems on water quality and the ecology of inland waters. Full article

This paper presents research concerning dewatered areas in the littoral zones of the Kaunas hydropower plant (HPP) reservoir in Lithuania. It is a multipurpose reservoir that is primarily used by two large hydropower plants for power generation. As a result of the peaking operation regime of the Kaunas HPP, the large quantity of water that is subtracted and released into the reservoir by the Kruonis pumped storage hydropower plant (PSP), and the reservoir morphology, i.e., the shallow, gently sloping littoral zone, significant dewatered areas can appear during drawdown operations. This is especially dangerous during the fish spawning period. Therefore, reservoir operation rules are in force that limit the operation of HPPs and secure other reservoir stakeholder needs. There is a lack of knowledge concerning fish spawning locations, how they change, and what areas are dewatered at different stages of HPP operation. This knowledge is crucial for decision-making and efficient reservoir storage management in order to simultaneously increase power generation and protect the environment. Current assessments of the spawning sites are mostly based on studies that were carried out in the 1990s. Surveying fish spawning sites is typically a difficult task that is usually carried out by performing manual bathymetric measurements due to the limitations of sonar in such conditions. A detailed survey of a small (approximately 5 ha) area containing several potential spawning sites was carried out using Unmanned Aerial Vehicles (UAV) equipped with multispectral and conventional RGB cameras. The captured images were processed using photogrammetry and analyzed using various techniques, including machine learning. In order to highlight water and track changes, various indices were calculated and assessed, such as the Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), Visible Atmospherically Resistant Index (VARI), and Normalized Green-Red Difference Index (NGRDI). High-resolution multispectral images were used to analyze the spectral footprint of aquatic macrophytes, and the possibility of using the results of this study to identify and map potential spawning sites over the entire reservoir (approximately 63.5 km²) was evaluated. The aim of the study was to investigate and implement modern surveying techniques to improve usage of reservoir storage during hydropower plant drawdown operations. The experimental results show that thresholding of the NGRDI and supervised classification of the NDWI were the best-performing methods for the shoreline detection in the fish spawning sites. Full article

Bathymetric LiDAR technology is a technology used for simultaneous data acquisition regarding the morphology of the bottom of water reservoirs and the surrounding coastal zone, realized from the air, e.g., by plane or drone. Contrary to the air topographic LiDAR, which uses an infrared wavelength of 1064 nm, bathymetric LiDAR systems additionally use a green wavelength of 532 nm. The green laser can penetrate the water, which makes it possible to measure the depth of shallow water reservoirs, rivers, and coastal sea waters within three Secchi depths. This article presents the theoretical basis for the construction of a green laser. Against the background of other methods of measuring the bottom of water reservoirs, the technology using waves from the visible light range is presented in detail in the assessment of the bottom morphology of shallow water reservoirs. The possibilities of using green laser in lidar bathymetry implemented in particular in non-navigable regions are shown. The results of the researchers’ work on river processes (erosion, sedimentation), design of stream restoration, determination of morphometric parameters of the riverbed, as well as assessment of the topography of the marine coastal bottom zones are summarized. The development direction of lidar bathymetry is discussed. Full article

Re-establishment of submerged macrophytes and especially charophyte vegetation is a common aim in lake management. If revegetation does not happen spontaneously, transplantations may be a suitable option. Only rarely have transplantations been used as a tool to support threatened submerged macrophytes and, to a much lesser extent, charophytes. Such actions have to consider species-specific life strategies. K-strategists mainly inhabit permanent habitats, are perennial, have low fertility and poor dispersal ability, but are strong competitors and often form dense vegetation. R-strategists are annual species, inhabit shallow water and/or temporary habitats, and are richly fertile. They disperse easily but are weak competitors. While K-strategists easily can be planted as green biomass taken from another site, rare R-strategists often must be reproduced in cultures before they can be planted on-site. In Sweden, several charophyte species are extremely rare and fail to (re)establish, though apparently suitable habitats are available. Limited dispersal and/or lack of diaspore reservoirs are probable explanations. Transplantations are planned to secure the occurrences of these species in the country. This contribution reviews the knowledge on life forms, dispersal, establishment, and transplantations of submerged macrophytes with focus on charophytes and gives recommendations for the Swedish project. Full article

Recovery efficiency is a key factor in decision-making in oil and gas projects. Although structural setup and well type considerably influence waterflood recovery, few studies have explored the performance of highly deviated wells during the waterflooding of complex shallow reservoirs. Here, we applied numerical simulations to investigate the performance of vertical, horizontal, multilateral, and highly deviated wells during waterflooding of complex shallow reservoirs using the J1 Oilfield as a case study. Recovery efficiencies of 31%, 33%, 31%, and 26% could be achieved for vertical, horizontal, multilateral, and highly deviated wells, respectively. The gas production rate was 39% higher in the vertical wells than in the other types. Highly deviated wells yielded the highest water-cut (80%) over a short period. Highly deviated wells delivered the least production, and, despite branching laterals, multilateral wells were also not the most productive. Our results provide insights into the performance of different well types during the waterflooding of green heterogeneous non-communicating reservoirs and present an example of the successful practical application of waterflooding as an initial recovery mechanism when oil is near the bubble point. This study indicated that multilateral wells are not a panacea in reservoir development. Highly deviated wells are the ideal choice for the shallow, heterogeneous non-communicating reservoirs when economic and environmental impact are considered in decision-making. Well design should be a case-by-case study considering reservoir characteristics, economics, and environment impact. Full article

Stormwater represents a complex and dynamic component of the urban water cycle. Hydrologic models have been used to study pre- and post-development hydrology, including green infrastructure. However, many of these models are applied in urban environments with very little formal verification and/or benchmarking. Here we present the results of an intercomparison study between a distributed model (Gridded Surface Subsurface Hydrologic Analysis, GSSHA) and a lumped parameter model (the US Environmental Protection Agency (EPA) Storm Water Management Model, EPA-SWMM) for an urban system. The distributed model scales to higher resolutions, allows for rainfall to be spatially and temporally variable, and solves the shallow water equations. The lumped model uses a non-linear reservoir method to determine runoff rates and volumes. Each model accounts for infiltration, initial abstraction losses, but solves the watershed flow equations in a different way. We use an urban case study with representation of green infrastructure to test the behavior of both models. Results from this case study show that when calibrated, the lumped model is able to represent green infrastructure for small storm events at lower implementation levels. However, as both storm intensity and amount of green infrastructure implementation increase, the lumped model diverges from the distributed model, overpredicting the benefits of green infrastructure on the system. We performed benchmark test cases to evaluate and understand key processes within each model. The results show similarities between the models for the standard cases for simple infiltration. However, as the domain increased in complexity the lumped model diverged from the distributed model. This indicates differences in how the models represent the physical processes and numerical solution approaches used between each. When the distributed model results were used to modify the representation of impermeable surface connections within the lumped model, the results were improved. These results demonstrate how complex, distributed models can be used to improve the formulation of lumped models. Full article

Spectral images from remote sensing platforms are extensively used to estimate chlorophyll-a (chl-a) concentrations for water quality studies. Empirical models used for estimation are often based on physical principles related to light absorption and emission properties of chl-a and generally relying on spectral bands in the green, blue, and near-infrared bands. Because the physical characteristics, constituents, and algae populations vary widely from lake to lake, it can be difficult to estimate coefficients for these models. Many studies select a model form that is a function of these bands, determine model coefficients by correlating remotely-measured surface reflectance data and coincidentally measured in-situ chl-a concentrations, and then apply the model to estimate chl-a concentrations for the entire water body. Recent work has demonstrated an alternative approach using simple statistical learning methods (Multiple Linear Stepwise Regression (MLSR)) which uses historical, non-coincident field data to develop sub-seasonal remote sensing chl-a models. We extend this previous work by comparing this method against models from literature, and explore model performance for a region of lakes in Central Utah with varying optical complexity, including two relatively clear intermountain reservoirs (Deer Creek and Jordanelle) and a highly turbid, shallow lake (Utah Lake). This study evaluates the suitability of these different methods for model parameterization for this area and whether a sub-seasonal approach improves performance of standard model forms from literature. We found that while some of the common spectral bands used in literature are selected by the data-driven MLSR method for the lakes in the study region, there are also other spectral bands and band interactions that are often more significant for these lakes. Comparison of model fit shows an improvement in model fit using the data-driven parameterization method over the more traditional physics-based modeling approaches from literature. This suggests that the sub-seasonal approach and exploitation of information contained in other bands helps account for lake-specific optical characteristics, such as suspended solids and other constituents contributing to water color, as well as unique (and season-specific) algae populations, which contribute to the spectral signature of the lake surface, rather than only relying on a generalized optical signature of chl-a. Consideration of these other bands is important for development of models for long-term and entire growing season applications in optically diverse water bodies. Full article