Fog computing, an extension of cloud computing services to the edge of the network to decrease latency and network congestion, is a relatively recent research trend. Although both cloud and fog offer similar resources and services, the latter is characterized by low latency with a wider spread and geographically distributed nodes to support mobility and real-time interaction. In this paper, we describe the fog computing architecture and review its different services and applications. We then discuss security and privacy issues in fog computing, focusing on service and resource availability. Virtualization is a vital technology in both fog and cloud computing that enables virtual machines (VMs) to coexist in a physical server (host) to share resources. These VMs could be subject to malicious attacks or the physical server hosting it could experience system failure, both of which result in unavailability of services and resources. Therefore, a conceptual smart pre-copy live migration approach is presented for VM migration. Using this approach, we can estimate the downtime after each iteration to determine whether to proceed to the stop-and-copy stage during a system failure or an attack on a fog computing node. This will minimize both the downtime and the migration time to guarantee resource and service availability to the end users of fog computing. Last, future research directions are outlined.
Multibeam sounding is a high-precision remote sensing method for seabed detection. Seabed topography classification is crucial for marine science research, resource exploration and engineering. When using multibeam data for seabed topography automatic classification, the fuzzy boundaries of different topographic entities, redundancy of multimodal data, and the lack of geological knowledge guidance have led to low classification accuracy. Thus, a knowledge graph-guided vision mamba seabed topography classification network (CUG-STCN) was constructed, consisting of three modules: (1) The long sequence modeling mamba-based encoder addresses the fuzzy seabed topography boundary. It uses 2D-selective-scan to create image blocks in different scanning directions. By combining with the selective state space model to capture long-range dependencies and ensure transmission of spatial context information while maintaining linear computational complexity. (2) The cross-modal information interaction and fusion module addresses the redundancy of multimodal information. By employing a bidirectional information interaction mechanism, it captures the correlations of seabed topography between different modalities and achieving feature fusion. (3) The seabed topography knowledge graph-guided semantic perception module guides the geological knowledge. It constructs seabed topography knowledge vectors through entity query and word embedding, using the similarity between vectors to create a similarity measurement matrix. It provides geological knowledge, enhancing the modeling capability of complex seabed topography relationship. CUG-STCN achieves OA of 90.11% and mIOU of 48.50%, outperforming six mainstream networks, which at most, achieve the OA and mIOU improvements of 5.37% and 14.18%. Notably, the application of CUG-STCN in other regions demonstrates its strong generalization performance.
<p>Human-managed reservoirs alter water flows and storage, impacting the hydrological cycle. Modeling reservoir outflow and storage, which affect water availability for humans and freshwater ecosystems, is challenging because they depend on human decisions. In addition, access to data on reservoir inflows, outflows, storage, and operational rules is very limited. Consequently, large-scale hydrological models either exclude reservoir operations or use calibration-free algorithms to model reservoir dynamics. Nowadays, estimates of reservoir storage anomalies based on remote sensing are a potential resource for calibrating the release algorithms for many reservoirs worldwide. However, the impact of calibration against the storage anomaly on simulated reservoir outflow and absolute storage is unclear. In this study, we address this by using in situ outflow and storage data from 100 reservoirs in the USA (ResOpsUS dataset) to calibrate three reservoir operation algorithms: the well-established Hanasaki algorithm (CH) and two new storage-based algorithms, the Scaling algorithm (SA) and the Weighting algorithm (WA). These algorithms were implemented in the global hydrological model WaterGAP, with their parameters estimated individually for each reservoir and four alternative calibration targets: monthly time series of (1) the storage anomaly, (2) estimated storage (calculated based on the storage anomaly and GRanD reservoir capacity), (3) storage, and (4) outflow. The first two variables can be obtained from freely available global datasets, while the latter two variables are not publicly accessible for most reservoirs. We found that calibrating against outflow did not result in skillful storage simulations for most of the 100 reservoirs and only slightly improved outflow simulations compared to calibration against the three storage-related targets. Compared to the non-calibrated Hanasaki algorithm (DH), calibrating against both the storage anomaly and estimated storage improved the storage simulation, whereas the outflow simulation was only slightly improved. Calibration against the storage anomaly yielded skillful storage simulations for 64 (39), 68 (45), and 66 (45) reservoirs in the case of CH, SA, and WA, respectively, during the calibration (validation) period, compared to just 16 (15) for DH. Using estimated storage instead of the storage anomaly does not offer any added benefit, primarily due to inconsistencies in the observed maximum water storage and storage capacity data from GRanD. The default parameters of the Hanasaki algorithm rarely matched the calibrated parameters, highlighting the importance of calibration. Using observed inflow rather than simulated inflow has a greater impact on improving the outflow simulation than calibration, whereas the opposite is true for the storage simulation. Overall, the performance of the SA and WA algorithms is nearly equal, and both outperform the CH and DH algorithms. Moreover, incorporating downstream water demand into the reservoir algorithms does not necessarily improve modeling performance due to the high uncertainty in demand estimation. Therefore, to improve the modeling of reservoir storage and outflow in large-scale hydrological models, we recommend calibrating either the SA or the WA reservoir algorithm individually for each reservoir against the remote-sensing-based storage anomaly, unless in situ storage data are available, and improving the reservoir inflow simulation.</p>
Understanding forest photosynthetic capacity is essential for monitoring carbon dynamics under global change. UAV-based imaging spectroscopy is a powerful tool for assessing canopy leaf traits, but the extension of spectral-trait relationships to the canopy scale remains unclear. This study uses UAV-based hyperspectral imaging data to evaluate the photosynthetic characteristics of larch forests across different climate zones in China. We investigate UAV-derived imaging spectroscopy for mapping canopy-level leaf physiological traits, including chlorophyll content, leaf nitrogen, and photosynthetic capacity (Vc, max and Jmax) across three distinct climate zones. High-resolution UAV imaging spectral data and ground-based leaf trait measurements, including biochemical (chlorophyll, leaf nitrogen), morphological (leaf mass per area, LMA), and physiological traits (Vc, max and Jmax), were collected from 150 tree crowns at all sites. We developed and validated models for estimating physiological traits from canopy spectra using Partial Least Squares Regression (PLSR), focusing on the transferability of leaf-level models to the canopy scale. The results show that UAV-based canopy spectra can effectively estimate canopy-level Vc, max25 (R2 = 0.56, RMSE = 9.57 μmol CO2 m−2 s−1, nRMSE = 17.7 %) and Jmax25 (R2 = 0.38, RMSE = 34.8, nRMSE = 18.6 %). Additionally, other leaf traits across all climate zones were accurately predicted, including leaf mass per area (LMA), leaf water content (LWC), chlorophyll content (Chl), nitrogen content (Narea), and phosphorus content (Parea), with R2 values ranging from 0.30 to 0.44 and nRMSE between 18.8 % and 24.4 %. Significant differences in canopy trait variability were observed, with Vc, max25 and Jmax25 values driven by climate variability. The range of Vc, max25 (40.5–70.6 μmol CO2 m−2 s−1) and Jmax25 (80.6–120.4 μmol CO2 m−2 s−1) was wider at the ES site compared to the FS and TS sites, indicating that species differences have a greater impact on photosynthetic capacity. These models demonstrated good transferability, showing robust performance across forests in different climate zones with only slight differences in predictive accuracy. However, canopy structure significantly influenced spectral-trait relationships, particularly for Vc, max and Jmax. While canopy structure had a moderate impact on accuracy, canopy-scale models performed slightly lower than leaf-level models in some cases. This study offers new insights into UAV-based imaging spectroscopy for mapping canopy leaf physiological traits and emphasizes the need to understand different physiological mechanisms at the canopy scale when expanding spectral-trait relationships.
Estimating plant biomass in wetland ecosystems using remote sensing and mathematical models is crucial for assessing carbon sequestration potential and for wetland conservation, management, and research. This study proposes a two-step framework for aboveground biomass (AGB) estimation in the Qilihai Wetland by integrating UAV LiDAR, hyperspectral images, and 2.5 m-resolution ZY-1 02E satellite imagery. First, biomass was estimated for seven regions using UAV data by comparing support vector machine (SVM), extreme gradient boosting (XGBoost), gradient boosting machine (GBM), and random forest (RF) models to identify the optimal estimation model. The results showed that RF achieved the highest prediction accuracy (R2 = 0.922), with canopy height, vegetation type, and several narrowband indices identified as key predictors, while SVM performed the poorest (R2 = 0.616). Second, UAV-derived biomass was applied to the satellite image to compare five models (SVM, XGBoost, GBM, RF, and the convolutional neural network (CNN)). CNN achieved the best performance (R2 = 0.806), outperforming RF (R2 = 0.721) and significantly surpassing the accuracy of direct field–satellite modeling (R2 = 0.434). The high-resolution AGB map revealed clear spatial heterogeneity, with higher biomass in mixed regions of Phragmites australis and Typha orientalis and in communities closer to water sources. By integrating the predictive capabilities of CNN with the interpretability of RF, this two-step framework significantly enhanced the robustness and ecological relevance of biomass estimation. The findings underscore the pivotal role of multi-source data fusion in improving the accuracy of wetland AGB estimates. Moreover, the high-resolution biomass distribution map provides essential guidance for the conservation, management, and ecological restoration of the Qilihai Wetland.
Anjali Thomas, Adrian McDonald, James Renwick
et al.
This study quantifies the influences of anthropogenic forcing to date on precipitation over Aotearoa New Zealand (ANZ). Large ensembles of simulations from the weather@home regional climate model experiments are analysed under two scenarios, a natural (NAT) or counter-factual scenario which excludes human-induced changes to the climate system and an anthropogenic (ANT) or factual scenario. The impacts of anthropogenic forcing on precipitation are analysed in the context of large-scale circulation types characterized using an existing Self Organizing Map classification. The combined effect of both thermodynamics and dynamics are compared with values expected from the Clausius–Clapeyron (C–C) relation. Changes in the precipitation intensity due to greenhouse gas-forced temperature rise are lower than the expected C–C value. However extreme precipitation changes approach the C–C value for some circulation types. Specifically westerly flows enhance precipitation change across ANZ relative to the C–C rate, particularly over the West Coast. Conversely, northwesterly flows reduce the change over the North Island relative to the C–C value. Moreover, the wet day frequency generally reduces in the ANT scenario relative to NAT, reductions are largest on the West Coast of the South Island for westerly flows. Additionally, the frequency of days with extreme precipitation rises over ANZ for most circulation patterns, except in Northland and for northwesterly flows. This underscores the combined influence of dynamics and thermodynamics in shaping both precipitation intensity and frequency patterns across ANZ.
Breanna Rivera Waterman, Gonzalo Alcantar, Samantha G. Thomas
et al.
Study region: Regional precipitation gradient across Kansas, USA. Study focus: As precipitation increases, baseflow and surface runoff generally increase, but it is unclear whether they increase proportionally and how proportions respond to climate and land use changes. This study examined variation in streamflow components of perennial streams across the study region and its relationships with watershed properties. We evaluated streamflow components with hydrograph separation and used Spearman’s rank correlation tests and principal component analysis (PCA) to assess spatial trends (28 sites) and Mann-Kendall and Sen’s Slope tests to assess temporal relationships (9 sites, 1960–2018). New hydrological insights for region: Runoff and baseflow both increase eastward with precipitation but the increase is greater for runoff. As such, baseflow index (BFI, baseflow/streamflow) decreases with increasing precipitation, potentially reflecting the limits of infiltration on recharge/runoff partitioning. Spatial patterns in variables that influence infiltration (land use and soil texture) also vary with precipitation, consistent with long-term influences of climate on landscapes. Since 1960, the watersheds included in our temporal analysis experienced small, mainly insignificant increases in precipitation and temperature and large, significant increases in irrigation. During this time, BFI increased significantly only in semi-arid, agriculture-dominated catchments overlaying higher permeability deposits. These findings underscore the importance of watershed characteristics as controls on current spatial patterns in streamflow and BFI and also the sensitivity of streamflow and BFI to climate and land use changes over time.
Study region: Chahannur Lake, an inland lake of the Inner Mongolia Plateau, is located in the typical agro-pastoral ecotone, China. Study focus: Change of lake area is highly sensitive to climate change and human activities, but the internal driving mechanism so far remains unclear. In this study, the spatiotemporal distribution of Chahannur Lake over the past 30 years was accurately extracted using the NDVI data, and the corresponding driver analysis was conducted. New hydrological insights for the region: Before 2000, Chahannur Lake was always remaining watery state throughout the year and the maximum area reached 90 km2; however, after 2000 it became a seasonal lake with a long-term dry state. During the observed period, the recovery of water body had only occurred in two stages both of which belonged to historically heavy rain years, and the maximum lake area was only 40 km2. Although the climate has tended to be warm and humid after 2000, it cannot completely reverse the lake’s drying. Additionally, the irrigated arable increased by 392 km2 in 2000–2017, and the increased arable consumed substantial groundwater for meeting agricultural demands, which consequently caused rapid shrinkage of the Lake. Notably, the increase of NDVI is widely distributed in irrigated arable with high water-consuming crops. Overall, groundwater over-exploitation and strong water consumption from crops have jointly led to the drying of Chahannur lake.
High-quality leaf area index (LAI) data is essential for regional and global ecology, climate and environment research. However, there are still many quality problems in the continuity of current LAI time series products. Here we developed a new comprehensive three-step reconstruction method (GANSG) for satellite-retrieved LAI time series data based on generative adversarial network, improving the Savitzky-Golay (S-G) filter and median absolute deviation filter. We applied GANSG to the reconstruction of MODIS LAI data in China from 2001 to 2019. The reconstruction results show that the new method based on the unsupervised deep learning framework has an advantage in interpolating low-quality LAI with high precision. The new method can better retain high-quality pixel information to smoothen the interpolated LAI time series by improving the traditional S-G filter. Compared with the five other methods, including the adaptive S-G filter, double logistic, asymmetric Gaussian, modified temporal spatial filter and spatial temporal S-G filter, qualitative analysis showed the new method has a more resilient ability to handle the continuous loss of high-quality pixels and identify the phenological features of biomes. Quantitative analysis based on station observation showed that the new method performs best among the other three methods, with the optimal correlation coefficient of 0.84 relative to station observation and the lowest root mean square error of 0.71 m2/m2.
CAMILA MARCON DE CARVALHO LEITE, MARIA JULIA MODESTO LERIANO, NATÁLIA PELINSON
et al.
Dentre as lacunas relacionadas ao planejamento do uso das águas, estão inseridas as dificuldades que envolvem o monitoramento e caracterização dos sistemas de aquíferos. Este trabalho tem como objetivo estudar a variação dos parâmetros de águas subterrâneas localizadas no município de São Carlos (SP), assim como verificar suas tendências hidroquímicas ao longo do período amostral. Para tanto, foram selecionados 3 poços de abastecimento público, em que foram realizadas 5 campanhas de coletas (para os poços 1 e 3) e 4 campanhas (para o poço 2), em diferentes fases do ano hidrológico. Considerou-se a heterogeneidade hidroquímica e litoestatigráficana na seleção dos poços amostrados.As amostras de águas subetrrâneas foram caracterizadas hidroquímicamente (íons principais) e apresentadas em gráficos de distribuição em função do tempo. Dentre os parâmetros avaliados, apenas os íons bicarbonato e cálcio apresentaram variação temporal significativa para os três poços estudados, sendo consequência da variação do pH da água. Isso também acarretou na variação expressiva da condutividade elétrica dessas amostras. Por outro lado, em alguns poços, também se verificou variação de nitrato, potássio e cloreto, que também refletem na condutividade elétrica. Todos os parâmetros apresentaram concetração inferior aos valores máximos estabelecidos pela resolução CONAMA 396 de 2008.
River, lake, and water-supply engineering (General), Physical geography
Rafael Albuquerque Xavier, Jadson dos Santos Maciel, Virgínia Mirtes de Alcântara Silva
A Carta Geológica da Folha Boqueirão, escala 1:100.000, elaborada pelo Serviço Geológico do Brasil foi utilizada para analisar a vulnerabilidade erosiva a partir dos parâmetros geológicos e geomorfológicos. Para tanto, foi utilizado a metodologia de Creppani (2001) e Xavier et. al. (2014), para analisar a vulnerabilidade geológica e geomorfológica respectivamente. Como argumentação teórica, discutem-se os conceitos de “limites de intemperismo” e “limites de transporte” de Gilbert (1877). Os resultados mostraram a predominância da estabilidade geológica e geomorfológica da área de estudo. Rochas resistentes ao intemperismo e o relevo suave marcam a paisagem. O regime pluviométrico não favorece a atuação da pedogênese, e a ocorrência de chuvas concentradas promove a aceleração dos processos erosivos superficiais que, em alguns casos, remove todo o manto de intemperismo, formando os lajedos rochosos. Conclui-se que as ideias de Gilbert (1877) são válidas para auxiliar no entendimento da morfodinâmica em ambientes semiáridos e que as características geológicas são variáveis fundamentais neste sistema.
In the papers collected in Man's Impact on the Hydrological Cycle in the United Kingdom Hollis gives us a fascinating view of the concerns and approaches of practising hydrologists in the late 1970s. Hollis, a physical geographer from University College London, spent most of his research career considering the way that humans acted to change their surroundings, looking first at the impact of urbanisation on flooding and later at the management of wetlands. The papers in this book cover a wide range of subjects, from the impact of forestry to the effects of house building on channel morphology and function. Many provide valuable reviews and insights into contemporary thinking on the effect of humans on the UK environment, and the modern reader will discover much of value in the ideas and approaches described in this book.
The companion paper by Zou et al. shows that the annual and semiannual variations in the peak F2-layer electron density (NmF2) at midlatitudes can be reproduced by a coupled thermosphere-ionosphere computational model (CTIP), without recourse to external influences such as the solar wind, or waves and tides originating in the lower atmosphere. The present work discusses the physics in greater detail. It shows that noon NmF2 is closely related to the ambient atomic/molecular concentration ratio, and suggests that the variations of NmF2 with geographic and magnetic longitude are largely due to the geometry of the auroral ovals. It also concludes that electric fields play no important part in the dynamics of the midlatitude thermosphere. Our modelling leads to the following picture of the global three-dimensional thermospheric circulation which, as envisaged by Duncan, is the key to explaining the F2-layer variations. At solstice, the almost continuous solar input at high summer latitudes drives a prevailing summer-to-winter wind, with upwelling at low latitudes and throughout most of the summer hemisphere, and a zone of downwelling in the winter hemisphere, just equatorward of the auroral oval. These motions affect thermospheric composition more than do the alternating day/night (up-and-down) motions at equinox. As a result, the thermosphere as a whole is more molecular at solstice than at equinox. Taken in conjunction with the well-known relation of F2-layer electron density to the atomic/molecular ratio in the neutral air, this explains the F2-layer semiannual effect in NmF2 that prevails at low and middle latitudes. At higher midlatitudes, the seasonal behaviour depends on the geographic latitude of the winter downwelling zone, though the effect of the composition changes is modified by the large solar zenith angle at midwinter. The zenith angle effect is especially important in longitudes far from the magnetic poles. Here, the downwelling occurs at high geographic latitudes, where the zenith angle effect becomes overwhelming and causes a midwinter depression of electron density, despite the enhanced atomic/molecular ratio. This leads to a semiannual variation of NmF2. A different situation exists in winter at longitudes near the magnetic poles, where the downwelling occurs at relatively low geographic latitudes so that solar radiation is strong enough to produce large values of NmF2. This circulation-driven mechanism provides a reasonably complete explanation of the observed pattern of F2 layer annual and semiannual quiet-day variations.
Maíra Correia de Menezes, André Belo Azevedo, Rafaela Oliveira Vieira
et al.
A existência de uma relação entre o escoamento superficial e o subterrâneo é notadamente reconhecida e fundamentada no ciclo hidrológico. Porém, com as diversas alterações antrópicas, especialmente nos centros urbanos, esta relação pode sofrer alterações cujas relações não sejam de fácil determinação. Dentro desse cenário, este artigo visa analisar as possíveis relações, em termos de qualidade, entre as águas superficiais e subterrâneas na bacia do rio Jacarecica. Esta bacia hidrográfica está posicionada no centro urbano da capital alagoana, em plena expansão e que vem sofrendo alterações no que diz respeito ao uso do solo, com a criação de inúmeros conjuntos habitacionais e aumento acelerado das áreas impermeabilizadas. Como resultado, os parâmetros qualitativos apresentaram significativa dispersão, exceto para a alcalinidade em um dos trechos monitorados.
River, lake, and water-supply engineering (General), Physical geography