Hasil untuk "Physical geography"

Andrea Caragliu, Chiara F. Del Bo, P. Nijkamp

Albert Saiz

Y. Balarajan, S. Selvaraj, S. Subramanian

M. Halliday, Jeannett Martin

M. Westoby, I. Wright

Edward E. Leamer, M. Storper

M. Asim, K. Abdan, M. Jawaid et al.

Natural fibre based composites are under intensive study due to their ecofriendly nature and peculiar properties. The advantage of natural fibres is their continuous supply, easy and safe handling, and biodegradable nature. Although natural fibres exhibit admirable physical and mechanical properties, it varies with the plant source, species, geography, and so forth. Pineapple leave fibre (PALF) is one of the abundantly available wastes materials of Malaysia and has not been studied yet as it is required. A detailed study of chemical, physical, and mechanical properties will bring out logical and reasonable utilization of PALF for various applications. From the socioeconomic prospective, PALF can be a new source of raw material to the industries and can be potential replacement of the expensive and nonrenewable synthetic fibre. However, few studies on PALF have been done describing the interfacial adhesion between fibres and reinforcement compatibility of fibre but a detailed study on PALF properties is not available. In this review, author covered the basic information of PALF and compared the chemical, physical, and mechanical properties with other natural fibres. Furthermore, it summarizes the recent work reported on physical, mechanical, and thermal properties of PALF reinforced polymer composites with its potential applications.

K. Morgan

ABSTRACT Globalisation and digitalisation have been presented as inescapable forces which signal the ‘death of geography’; this article takes issue with this fashionable narrative. The counter argument that ‘geography matters’ is pursued in three ways: first, by questioning the ‘distance-destroying’ capacity of infonnation and communication technologies, where social depth is conflated with spatial reach; second, by arguing that physical proximity may be essential for some forms of knowledge exchange; and third, by charting the growth of territorial innovation systems.

Changshan Wu, Alan T. Murray

E. Lioubimtseva, G. Henebry

A. Barry

Xiaoyu Liu, Wu Zhu, Yuxin Zhou et al.

Following the September 20, 2019 instability event, the Jungong landslide—a large-scale red-bed feature in the upper Yellow River Basin—has exhibited persistent creep, necessitating systematic kinematic analysis to constrain deformation drivers. In this context, we conducted a multidisciplinary approach integrating interferometric synthetic aperture radar (InSAR), unmanned aerial vehicle (UAV) surveys, optical satellite remote sensing, and high-density electrical resistivity tomography (HD-ERT) to investigate its kinematic evolution. Firstly, interferometric processing of SAR imagery from ALOS/PALSAR-1, ALOS/PALSAR-2 and Sentinel-1 systems (March 2007-August 2024) revealed continuous creeping with maximum deformation velocity reaching −129 mm/yr in descending Sentinel-1. Based on morphological and deformation characteristics, the slope was divided into four secondary zones. Through digital image correlation (DIC) of optical images, horizontal displacements exceeding 20 m induced by instability were detected at the front edge of Zone I. The three-dimensional (3D) deformation field was then inverted by combining multi-orbit InSAR observations and a topography-constrained model, revealing significant spatial heterogeneity of displacement characteristics. The maximum velocities in the eastward, northward, and vertical directions were −107, 53, and −71 mm/yr, respectively. Additionally, the internal structure along two profiles was detected using HD-ERT. Finally, a method combining Singular Spectrum Analysis (SSA) and wavelet transform was proposed to quantitatively analyze the temporal relationship between periodic displacements and rainfall. Different zones exhibited varying degrees of correlation with rainfall, with a time lag of approximately 45 days in Zone I. This multidisciplinary approach enhances our understanding of the kinematic behavior of the Jungong landslide, providing critical reference for future hazard assessment.

Elisabetta Loffredo, Nicola Denora, Danilo Vona et al.

A biochar (BC) generated by the pyrogasification of wood chips from authorized forestry cuts was extensively characterized and evaluated for its efficacy in retaining/releasing two agrochemicals, namely the fungicide penconazole (PEN), the herbicide S-metolachlor (S-MET), and the xenoestrogen bisphenol A (BPA) widely present in industrial effluents. The elemental composition of BC was evaluated using CN elemental analysis and total reflection X-ray fluorescence (TXRF) spectroscopy which showed the abundance of elements typically found in BCs (Ca, K, P) along with essential trace elements such as Fe and Mn. Scanning electron microscopy coupled with energy-dispersive X-ray analysis (SEM-EDX) described the surface features of BC along with the major surface elements, while Brunauer–Emmett–Teller (BET) analysis revealed, as expected, a large specific surface area (366 m² g⁻¹). High porosity (0.07 cm³ g⁻¹) was demonstrated by the density functional theory (DFT) method, while Fourier transform infrared (FT-IR) spectroscopy highlighted the presence of a prominent aromatic structure and the abundance of reactive functional groups responsible for the binding of the compounds. The sorption/desorption capacity of BC was studied by means of sorption kinetics and isotherms in batch trials, and by modeling the experimental data with various theoretical equations. All compounds reached sorption equilibrium on BC very rapidly, following preferentially pseudo-second-order kinetics. Freundlich adsorption constants of PEN, S-MET, and BPA were 37.3, 13.2, and 11.6 L g⁻¹, respectively, thus demonstrating the great affinity of BC for hydrophobic pollutants. The adsorption process was hysteretic as only a small fraction of each compound was slowly desorbed from BC. The overall results obtained highlighted the great potential of BC of acting as a biosorbent of contaminants, which is of great importance for the containment of pollution in agricultural soils and for limiting the entry of toxic compounds into the human and animal food chain.

Ilias G. Pechlivanidis, Jude Lubega Musuuza

Study region: Lake Hume in Australia and Harsha Lake in USA. Study focus: Large-scale hydrological models (LSHMs), though important for both scientific and societal reasons, require the representation of many unknown features that influence river system response. However, current model identification practices in catchment modelling cannot lead to robust LSHMs for local decision-making. To address this, it is necessary to customise the models by integrating local data and knowledge from various sources (e.g. in-situ and earth observations) and fluxes. We present a framework to customize LSHMs for impactful local applications and showcase this using the global WWH hydrological model as the reference LSHM. New hydrological insights: We present significant improvements in modelling streamflow and actual and potential evapotranspiration, following WWH refinements to include local lakes and reservoir management. Local streamflow measurements and earth observations from NASA MODIS evapotranspiration products were used to re-calibrate the locally adapted model, leading to spatial consistency in performance. Combining multiple variables and metrics during model identification improved streamflow performance and robustness, with combination sets reducing variability and enhancing representation of diverse hydrological processes, highlighting the need for tailored metric and variable selection. This underpins the importance of including informative data in customized multi-objective modelling chains. Finally, incorporating reservoir management improved simulation of a regulated system, with local insights informing reservoir parameterization in LSHMs and bridging the gap to global-scale applications.

Denis Donadel, Gabriele Crestanello, Giulio Morandini et al.

Industrial Control Systems (ICS) manage critical infrastructures like power grids and water treatment plants. Cyberattacks on ICSs can disrupt operations, causing severe economic, environmental, and safety issues. For example, undetected pollution in a water plant can put the lives of thousands at stake. ICS researchers have increasingly turned to honeypots -- decoy systems designed to attract attackers, study their behaviors, and eventually improve defensive mechanisms. However, existing ICS honeypots struggle to replicate the ICS physical process, making them susceptible to detection. Accurately simulating the noise in ICS physical processes is challenging because different factors produce it, including sensor imperfections and external interferences. In this paper, we propose SimProcess, a novel framework to rank the fidelity of ICS simulations by evaluating how closely they resemble real-world and noisy physical processes. It measures the simulation distance from a target system by estimating the noise distribution with machine learning models like Random Forest. Unlike existing solutions that require detailed mathematical models or are limited to simple systems, SimProcess operates with only a timeseries of measurements from the real system, making it applicable to a broader range of complex dynamic systems. We demonstrate the framework's effectiveness through a case study using real-world power grid data from the EPIC testbed. We compare the performance of various simulation methods, including static and generative noise techniques. Our model correctly classifies real samples with a recall of up to 1.0. It also identifies Gaussian and Gaussian Mixture as the best distribution to simulate our power systems, together with a generative solution provided by an autoencoder, thereby helping developers to improve honeypot fidelity. Additionally, we make our code publicly available.

Samantha Israel, Sanjana Kunkolienkar, Ana Goulart et al.

Power grids and their cyber infrastructure are classified as Critical Energy Infrastructure/Information (CEII) and are not publicly accessible. While realistic synthetic test cases for power systems have been developed in recent years, they often lack corresponding cyber network models. This work extends synthetic grid models by incorporating cyber-physical representations. To address the growing need for realistic and scalable models that integrate both cyber and physical layers in electric power systems, this paper presents the Scalable Automatic Model Generation Tool (SAM-GT). This tool enables the creation of large-scale cyber-physical topologies for power system models. The resulting cyber-physical network models include power system switches, routers, and firewalls while accounting for data flows and industrial communication protocols. Case studies demonstrate the tool's application to synthetic grid models of 500, 2,000, and 10,000 buses, considering three distinct network topologies. Results from these case studies include network metrics on critical nodes, hops, and generation times, showcasing effectiveness, adaptability, and scalability of SAM-GT.

N. Blomley

T. Zakaluk, J. Jódar, A. González-Ramón et al.

Zeng Jinyu, Lian Chenfang, Yin Siyu et al.

Based on wind profile radar data, this paper aims at different typhoon processes landed and affected Fujian from 2011 to 2019, according to the nature of typhoon rainstorm, it can be classified into outer precipitation before typhoon landed, main body precipitation and precipitation at the rear of typhoon, the change of the characteristic quantities in approaching time of the occurrence of short-term heavy rainfall was analyzed, and the typhoon case in 2020 was back calculated. The results show that, the characteristics of low-level jet streams (maximum wind speed at low altitude, minimum height of jet streams, and low-level jet stream index), as well as the magnitude of vertical wind shear below 700 hPa, have important indicative significance for the occurrence of short-term heavy rainfall. (1) More than 80 % of short-term heavy rainfall occurred 3 h before the low-level jet stream already existed. The maximum wind speed below 2 km was basically close to a normal distribution, and the occurrence of heavy precipitation showed a bimodal pattern. The percentage of wind speed between 8 and 32 m/s was the highest, exceeding 85 %. The wind direction of the strong wind is mainly NE, SE, and SW. Classification analysis showed that the distribution characteristics of wind speed of the main precipitation were the same as before, but the wind direction SE was higher than NE. The wind speed of pre-landfall precipitation was basically skewed, and the occurrence time of heavy precipitation followed a normal distribution. The percentage of wind speed between 16 and 32 m/s was the highest, and the wind direction was the same as before classification. The maximum wind speed of precipitation in the rear was basically bimodal distribution, with a relatively even distribution, and the wind direction was mainly SE and SW. (2) In the 3 h before the occurrence of short-term heavy precipitation, there was an increase in the maximum wind speed value, a decrease in the minimum extension height, and an increase in the low-level jet stream index I. As short-term heavy rainfall approached, the intensity of the low-level jet stream remained high and its proportion increased. The minimum achievable extension height gradually decreased and remained stable at a low value. In the first 2 h of heavy rainfall, the wind speed reached its maximum, the extension height was the lowest, and the low-level jet stream index I was the highest. Classifying and discussing it, the precipitation in the rear was different, and the lowest height decreased to the lowest at the time of occurrence, at which point the I value reached its maximum. The characteristics of the other two categories were the same as before the classification. (3) The vertical wind shear from the ground to different isobaric surfaces gradually decreased with the increase of height. With the approach of short-term heavy rainfall, the vertical wind shear of each layer basically decreased gradually, after the beginning of heavy rainfall, which decreased to the minimum. The characteristics of main body precipitation were the same as before the classification. Pre-landfall precipitation, in addition to the gradual decrease of vertical wind shear from the ground to 925 hPa, both 850 hPa and 700 hPa increased first and then decreased, vertical wind shear decreased to the minimum after the beginning of heavy rainfall. Precipitation at rear of typhoon, vertical wind shear from ground to 700 hPa increased compared with that before the occurrence of heavy rainfall, while wind shear from ground to 925 hPa and 850 hPa showed the characteristics of decreasing when heavy rainfall occurred. (4)The median values of various physical quantities before the occurrence of typhoon short-term heavy rainfall were selected as the thresholds of short-term heavy rainfall will occur. The intensity of LLJ is about 21 m/s, the lowest height is about 0.65 km, the LLJ index I is about 36 × 10−3s−1. Vertical wind shear from the ground to 925 hPa, 850 hPa and 700 hPa are respectively about 15.9 × 10−3s−1, 11.2 × 10−3s−1 and 5.1 × 10−3s−1.

Ioannis Liritzis

The non-linear trend of evolution of ancient cultures is decisively affected by climatic change, landscape changes, and more [...]