Hasil untuk "River, lake, and water-supply engineering (General)"

Maria Janicka, Aneta Kutkowska, Jakub Paderewski

In recent years, there has been increasing interest in the floristic diversity of agroecosystems, particularly for plant conservation. While old plantations claim to be more floristically diverse, little is known about this for Salix viminalis L. plantations. The aim of study was to analyse the vegetation accompanying S. viminalis and its dynamics as plantations age. The vegetation was identified in 20 plantations, based on 244 phytosociological relevés. For each species, the following were defined: botanical family, geographical and historical groups, origin of apophytes, biological stability, life-form, botanical class and phytosociological class. The relative coverage of major plant groups was statistically processed using the analysis of variance with a linear mixed model. The flora of S. viminalis plantations is rich and diverse; in central Poland, it consisted of 193 plant species. These species belonged to many phytosociological classes, of which two dominated: Molinio-Arrhenatheretea (46 species) and Artemisietea vulgaris (32 species). Perennial species, meadow, woodland, and shrub apophytes, as well as hemicryptophytes, were prevalent. As the plantations aged, the proportion of perennial species, meadow, woodland, and shrub apophytes increased, while therophytes and anthropophytes declined. Photophilous species dominated mainly in young crops (4–5 years old), but their coverage and frequency decreased over time. With plantations age, vascular flora diversity (total number of species) and coverage of ecologically important groups (Poaceae family, Molinio-Arrhenatheretea class) decreased. These were gradually replaced by mega- and nanophanerophytes and species from the A. vulgaris class. The stabilisation of flora occurred after eight years of willow cultivation.

WANG Yazhong, LIANG Qinzheng, WANG Dong et al.

Axial zoned concrete-faced rockfill dam (CFRD) divides the dam shell along the dam axis. Through the filling of different modulus materials, the three-dimensional deformation of the dam shell can be reduced, and the extruding rupture of high CFRD and even ultra-high CFRD can be improved. Its mechanism and effect are different from those of traditional transverse two-dimensional zoned CFRD. To study the influence of the parameters of the E-B model on the numerical simulation of stress and deformation of the axial zoned CFRD, this paper takes the parameters of the Duncan-Chang E-B model as random variables, takes dam settlement, the deflection of the face slab and axial stress of the face slab as objective functions, and studies the material parameter sensitivity of the axial zoned CFRD through the orthogonal test. The results show that the stress and deformation state is more sensitive to the bulk modulus radix <italic>K</italic>_b, break ratio <italic>R</italic>_f, internal friction angle <italic>φ</italic>₀ and the elasticity modulus radix <italic>K</italic>, and less sensitive to the bulk modulus index <italic>m</italic>.

Jair Koiller

The `lake equation' on a planar domain D with bathymetry b(x,y) is given by $ \partial_t u + (u \cdot {\rm grad}) u= -{\rm grad}\, p \,, \,\,{\rm div} (b u) = 0 \,,\, \text{with}\,\, u \parallel \partial D.$ % \, \,\, \,\,\, \text{),}$$ We focus on Geometric Mechanics aspects, glossing over hard analysis issues. % related to the desingularization. Motivating example is a `rip current' produced by vortex pairs near a beach shore. For uniform slope beach there is a perfect analogy with \ Thomson's vortex rings. The stream function produced by a vortex is defined as the Green function of the operator $- {\rm div} ( {\rm grad} ψ/b)$ with Dirichlet boundary conditions. As in elasticity, the lake equations give rise to pseudoanalytical functions and quasiconformal mappings. Uniformly elliptic equations on closed Riemann surfaces could be called `planet equations'.

Alexandra Mazak-Huemer, Christian Huemer, Michael Vierhauser et al.

With the increasing significance of Research, Technology, and Innovation (RTI) policies in recent years, the demand for detailed information about the performance of these sectors has surged. Many of the current tools are limited in their application purpose. To address these issues, we introduce a requirements engineering process to identify stakeholders and elicitate requirements to derive a system architecture, for a web-based interactive and open-access RTI system monitoring tool. Based on several core modules, we introduce a multi-tier software architecture of how such a tool is generally implemented from the perspective of software engineers. A cornerstone of this architecture is the user-facing dashboard module. We describe in detail the requirements for this module and additionally illustrate these requirements with the real example of the Austrian RTI Monitor.

Hanwen Zhang, Laura A. Stevens, Ian J. Hewitt et al.

Subglacial blisters form due to the rapid drainage of supraglacial lakes into grounded ice sheets, and are characterised by elastic ice uplift and transient ice-velocity anomalies. Although blister occurrence is confirmed by observations, the dynamics of blisters and their impacts on ice flow remain poorly represented in current subglacial hydrology models, as typical cavity-channel system models cannot capture short-timescale blister formation, propagation, and relaxation. Here we present a unified, self-consistent modelling framework that directly couples blister evolution with the subglacial drainage system, extending existing subglacial hydrology models to account for transient responses to rapid lake drainage events. Numerical simulations, validated by field observations, reveal distinct seasonal behavior: during summer, lake drainage generates short-lived blisters that rapidly leak water into a pre-existing drainage system of efficient, channelised water pathways, whereas winter drainage results in persistent blisters that propagate and serve as the primary meltwater pathway at the ice-bed interface. The dynamics of blister propagation and leakage in our model are governed by effective viscosity and a characteristic leakage length scale, which reflects the connection between the blister and the surrounding hydrological network. This unified model offers a valuable tool for investigating blister dynamics and their interplay with subglacial hydrology, facilitating the interpretation of observed surface uplift and ice-velocity variations following supraglacial lake drainage events.

Yuriy A. Fedorov, Dmitry N. Garkusha, Aleksey E. Kosolapov et al.

We have analyzed and summarized comprehensive original data and published materials dealing with issues of investigation of CH4 discharges and absorption in artificial and natural water bodies.

Monika Gierszewska, Tomasz Berezowski

The flooding extent area in a river valley is related to river gauge observations. The higher the water elevation, the larger the flooding area. Due to synthetic aperture radar\textquoteright s (SAR) capabilities to penetrate through clouds, radar images have been commonly used to estimate flooding extent area with various methods, from simple thresholding to deep learning models. In this study, we propose a physics-guided neural network for flooding area detection. Our approach takes as input data the Sentinel 1 time-series images and the water elevations in the river assigned to each image. We apply the Pearson correlation coefficient between the predicted sum of water extent areas and the local water level observations of river water elevations as the loss function. The effectiveness of our method is evaluated in five different study areas by comparing the predicted water maps with reference water maps obtained from digital terrain models and optical satellite images. The highest Intersection over Union (IoU) score achieved by our models was 0.89 for the water class and 0.96 for the non-water class. Additionally, we compared the results with other unsupervised methods. The proposed neural network provided a higher IoU than the other methods, especially for SAR images registered during low water elevation in the river.

Runlong Yu, Chonghao Qiu, Robert Ladwig et al.

This paper introduces a \textit{Process-Guided Learning (Pril)} framework that integrates physical models with recurrent neural networks (RNNs) to enhance the prediction of dissolved oxygen (DO) concentrations in lakes, which is crucial for sustaining water quality and ecosystem health. Unlike traditional RNNs, which may deliver high accuracy but often lack physical consistency and broad applicability, the \textit{Pril} method incorporates differential DO equations for each lake layer, modeling it as a first-order linear solution using a forward Euler scheme with a daily timestep. However, this method is sensitive to numerical instabilities. When drastic fluctuations occur, the numerical integration is neither mass-conservative nor stable. Especially during stratified conditions, exogenous fluxes into each layer cause significant within-day changes in DO concentrations. To address this challenge, we further propose an \textit{Adaptive Process-Guided Learning (April)} model, which dynamically adjusts timesteps from daily to sub-daily intervals with the aim of mitigating the discrepancies caused by variations in entrainment fluxes. \textit{April} uses a generator-discriminator architecture to identify days with significant DO fluctuations and employs a multi-step Euler scheme with sub-daily timesteps to effectively manage these variations. We have tested our methods on a wide range of lakes in the Midwestern USA, and demonstrated robust capability in predicting DO concentrations even with limited training data. While primarily focused on aquatic ecosystems, this approach is broadly applicable to diverse scientific and engineering disciplines that utilize process-based models, such as power engineering, climate science, and biomedicine.

Muhammad Naveed Zafar, Denys Dutykh, Pierre Sabatier et al.

Mass movements and delta collapses are significant sources of tsunamis in lacustrine environments, impacting human societies enormously. Palaeotsunamis play an essential role in understanding historical events and their consequences along with their return periods. Here, we focus on a palaeo event that occurred during the Younger Dryas to Early Holocene climatic transition, ca., 12,000 years ago in the Lake Aiguebelette (NW Alps, France). Based on highresolution seismic and bathymetric surveys and sedimentological, geochemical, and magnetic analyses, a seismically induced large mass transport deposit with an initial volume of 767172 m3 was identified, dated and mapped. To investigate whether this underwater mass transport produced a palaeotsunami in the Lake Aiguebelette, this research combines sedimentary records and numerical models. Numerical simulations of tsunamis are performed using a viscoplastic landslide model for tsunami source generation and two-dimensional depth-averaged nonlinear shallow water equations for tsunami wave propagation and inundation modelling. Our simulations conclude that this sublacustrine landslide produced a tsunami wave with a maximum amplitude of approximately 2 m and run-up heights of up to 3.6 m. The modelled sediment thickness resulting from this mass transport corroborates well with the event deposits mapped in the lake. Based on our results, we suggest that this sublacustrine mass transport generated a significant tsunami wave that has not been reported previously to the best of our knowledge.

C. P. Neema, P. N. Vinayachandran

Along the east coast of India (ECI), local winds are oriented alongshore during the summer monsoon, favouring coastal upwelling. The East India Coastal Current (EICC) during this period converges at 17$^{\circ}$N with northward flow from the south and southward flow from the north. A high-resolution Ocean general circulation model (OGCM) which includes runoff from major rivers (RIVER) simulates the upwelling along the east coast of India during the summer monsoon reasonably well. The model simulation shows that the upwelling increases towards south, where salinity influence is lesser compared to the northern parts. The presence of rivers suppresses upwelling, the depth of the source of subsurface water becomes shallow from 100 to 60 m, and reduces the SST cooling by 0.5$^{\circ}$C owing to the increase in stratification of the water column.

Gede Adi Wiguna Sudiartha, Tsuyoshi Imai

Operating temperature significantly affects biogas output, process stability, and microbial communities involved in anaerobic digestion. There are several unanswered questions regarding how microbial communities adapt in correlation with biogas production performance, especially when a digester fails to maintain thermophilic conditions. In this study, long-term lab-scale anaerobic digestion was carried out using two fed-batch reactors at 55°C, with subsequent decreases in temperature to 48°C and 45°C. Within the first month of incubation, methane (CH4) production increased by approximately 11.18% following a reduction in temperature from 55°C to 48°C. However, the methane production decreased by 33% after the temperature was downshifted to 45°C. Despite the difference in methane production, the thermophilic methanogen population in both reactors declined significantly in the first month with a temperature decrease. After two months of incubation, these methanogenic communities recovered faster at 48°C than at 45°C, which was highlighted by the rapid colonization of Methanosaeta, Methanobacterium, and Methanothermobacter. Notably, Methanosaeta was the most abundant methanogen under all temperature conditions, indicating its thermotolerance.

Markus Velten, Robert Schöne, Thomas Ilsche et al.

Modern processors, in particular within the server segment, integrate more cores with each generation. This increases their complexity in general, and that of the memory hierarchy in particular. Software executed on such processors can suffer from performance degradation when data is distributed disadvantageously over the available resources. To optimize data placement and access patterns, an in-depth analysis of the processor design and its implications for performance is necessary. This paper describes and experimentally evaluates the memory hierarchy of AMD EPYC Rome and Intel Xeon Cascade Lake SP server processors in detail. Their distinct microarchitectures cause different performance patterns for memory latencies, in particular for remote cache accesses. Our findings illustrate the complex NUMA properties and how data placement and cache coherence states impact access latencies to local and remote locations. This paper also compares theoretical and effective bandwidths for accessing data at the different memory levels and main memory bandwidth saturation at reduced core counts. The presented insight is a foundation for modeling performance of the given microarchitectures, which enables practical performance engineering of complex applications. Moreover, security research on side-channel attacks can also leverage the presented findings.

Huiyu Li, Nicholas Ayache, Hervé Delingette

In privacy-preserving machine learning, it is common that the owner of the learned model does not have any physical access to the data. Instead, only a secured remote access to a data lake is granted to the model owner without any ability to retrieve data from the data lake. Yet, the model owner may want to export the trained model periodically from the remote repository and a question arises whether this may cause is a risk of data leakage. In this paper, we introduce the concept of data stealing attack during the export of neural networks. It consists in hiding some information in the exported network that allows the reconstruction outside the data lake of images initially stored in that data lake. More precisely, we show that it is possible to train a network that can perform lossy image compression and at the same time solve some utility tasks such as image segmentation. The attack then proceeds by exporting the compression decoder network together with some image codes that leads to the image reconstruction outside the data lake. We explore the feasibility of such attacks on databases of CT and MR images, showing that it is possible to obtain perceptually meaningful reconstructions of the target dataset, and that the stolen dataset can be used in turns to solve a broad range of tasks. Comprehensive experiments and analyses show that data stealing attacks should be considered as a threat for sensitive imaging data sources.

Timur M. Aksyanov, Olga V. Gorelits

Information on water bodies on the territory of the Russian Federation is contained in the State Water Register (SWR). Water bodies that have not yet been represented in the State Water Register are actually taken out of the legal framework of the Water Code of the Russian Federation. In order for a water body to be included in the register, its status - type and kind – must be established. One of the objects, information about which is still lacking in the SWR, is the so-called South Agrakhan reservoir, formed on the site of the southern part of the water area of the Agrakhan Bay of the Caspian Sea. The South Agrakhan reservoir is currently considered as part of the sea bay, and its status has not been established.

Tingen Zhu, Wenping Li, Weichi Chen

A study on the risk of Cretaceous water inrush in the Ordos Basin in China is of great significance to the safe production and environmental protection of the western coal seam. This paper selects the following five key influencing factors for Cretaceous water inrush: the coal seam mining thickness, rock quality designation, distance between the top boundary of the water-conducting fracture zone and the bottom boundary of the Cretaceous system, the thickness of the Cretaceous aquifer, and the height of the water head. Furthermore, based on an analysis of geological and hydrogeological conditions of the Yingpanhao coal mine, the comprehensive weights of these factors were found using a fuzzy analytic hierarchy process and the entropy method (FAHP-EM) to be 0.27, 0.25, 0.22, 0.08, and 0.18, respectively. This paper describes the use of ArcGIS's spatial overlay analysis to create a risk assessment zoning map using these weightings. By comparing the evaluation results of the FAHP-EM and the water inrush coefficient method, it is shown that the FAHP-EM provides additional insight in assessing the risk of coal seam roof water inrush. The research results of this paper provide a theoretical basis for coal mining safety in western China to assess water inrush. HIGHLIGHTS Based on the fuzzy analytic hierarchy process and the entropy method (FAHP-EM), a method for evaluating the risk of water inrush from coal roof is proposed.; This paper selects the following five key influencing factors for Cretaceous water inrush: the coal seam mining thickness, rock quality designation, distance between the top boundary of the water-conducting fracture zone and the bottom boundary of the Cretaceous system, the thickness of the Cretaceous aquifer, and the height of the water head, established the Cretaceous water disaster evaluation system.; Based on an analysis of geological and hydrogeological conditions of the Yingpanhao coal mine, this paper uses the FAHP-EM to create a risk assessment zoning map.;

Feras A. Batarseh, Rasika Mohod, Abhinav Kumar et al.

The field of artificial intelligence (AI) is witnessing a recent upsurge in research, tools development, and deployment of applications. Multiple software companies are shifting their focus to developing intelligent systems; and many others are deploying AI paradigms to their existing processes. In parallel, the academic research community is injecting AI paradigms to provide solutions to traditional engineering problems. Similarly, AI has evidently been proved useful to software engineering (SE). When one observes the SE phases (requirements, design, development, testing, release, and maintenance), it becomes clear that multiple AI paradigms (such as neural networks, machine learning, knowledge-based systems, natural language processing) could be applied to improve the process and eliminate many of the major challenges that the SE field has been facing. This survey chapter is a review of the most commonplace methods of AI applied to SE. The review covers methods between years 1975-2017, for the requirements phase, 46 major AI-driven methods are found, 19 for design, 15 for development, 68 for testing, and 15 for release and maintenance. Furthermore, the purpose of this chapter is threefold; firstly, to answer the following questions: is there sufficient intelligence in the SE lifecycle? What does applying AI to SE entail? Secondly, to measure, formulize, and evaluate the overlap of SE phases and AI disciplines. Lastly, this chapter aims to provide serious questions to challenging the current conventional wisdom (i.e., status quo) of the state-of-the-art, craft a call for action, and to redefine the path forward.

Ufuk Beyaztas, Han Lin Shang, Zaher Mundher Yaseen

In this research, a functional time series model was introduced to predict future realizations of river flow time series. The proposed model was constructed based on a functional time series's correlated lags and the essential exogenous climate variables. Rainfall, temperature, and evaporation variables were hypothesized to have substantial functionality in river flow simulation. Because an actual time series model is unspecified and the input variables' significance for the learning process is unknown in practice, it was employed a variable selection procedure to determine only the significant variables for the model. A nonparametric bootstrap model was also proposed to investigate predictions' uncertainty and construct pointwise prediction intervals for the river flow curve time series. Historical datasets at three meteorological stations (Mosul, Baghdad, and Kut) located in the semi-arid region, Iraq, were used for model development. The prediction performance of the proposed model was validated against existing functional and traditional time series models. The numerical analyses revealed that the proposed model provides competitive or even better performance than the benchmark models. Also, the incorporated exogenous climate variables have substantially improved the modeling predictability performance. Overall, the proposed model indicated a reliable methodology for modeling river flow within the semi-arid region.

Yongsheng Cui, Chengzhong Pan, Chunlei Liu et al.

Rainfall erosivity is an important factor to be considered when predicting soil erosion. Precipitation data for 1971–2010 from 39 stations located in the Loess Plateau of China were collected to calculate the spatiotemporal variability of rainfall erosivity, and the long-term tendency of the erosivity was predicted using data from the HadGEM2-ES model. Statistical analyses were done using Mann–Kendall statistic tests and ordinary Kriging interpolation. The results showed that the annual mean rainfall erosivity in the Loess Plateau decreased from 1,286.02 MJ mm hm−2 h−1 a−1 in 1971–1990 to 1,201.46 MJ mm hm−2 h−1 a−1 in 1991–2010 and mainly occurred in July to August. The rainfall erosivity decreased from the southeast to the northwest of the Loess Plateau and was closely related to the annual precipitation amount. However, the effect of annual precipitation on rainfall erosivity weakened under climate change: the annual precipitation increased and the rainfall erosivity decreased. Climate change, however, had little influence on the spatial variation in rainfall erosivity in the Loess Plateau. The results obtained can facilitate the prediction of spatial and temporal variations in soil erosion in the Loess Plateau. HIGHLIGHTS Both precipitation and rainfall erosivity showed an insignificant decreasing trend for 1971–2010.; The climate model predicts an increasing precipitation but decreasing rainfall erosivity.; South and southeast of the Loess Plateau are areas susceptible to rainfall erosion under climate change.;