Hasil untuk "Physical geography"

Paul W. Rodaway

G. Langran

A reasonable goal for geographic information systems is that they be capable of tracing changes in an area by storing historic and anticipated geographic data. This work provides a conceptual, logical, and physical basis for developing such a capability. It introduces a conceptual model of geographic change that treats only changed data over time, then extends the conceptual model to common geographic data types. The literature of time in information processing is reviewed at length and ways to apply this research to geographic needs are suggested. The discussion extends to such implementation issues as clustering, quality control, and volume control. The later chapters focus on the problem of responding to ad hoc queries to a spatiotemporal database. The discussion introduces a taxonomy of multidimensional access methods. Four distinct classes are selected from the taxonomy and a representative of each class is chosen to implement on small spatiotemporal datasets. Two of the four methods are found to perform acceptably.

Sedigheh Anvari, Jesper Rydén, Ameneh Mianabadi

Study region: The Halil-Rud Basin in Iran, a semi-arid watershed, has been increasingly affected by climate change over the past decades, impacting hydrological processes and water resource Study focus: This study introduces a Nonstationary Standardized Runoff Index (NSRI) to enhance hydrological drought assessment in the Halil-Rud Basin for the period 1980–2019. Using the GAMLSS framework with a time-varying gamma distribution, NSRI models incorporate linear relationships between runoff and hydroclimatic covariates, including precipitation, temperature, potential evapotranspiration, and antecedent runoff. Four models—one stationary (M0) and three nonstationary (M1–M3)—were evaluated across 14 covariate combinations using monthly runoff data from three stations (Pole-Baft, Meidan, Kenaroyeh), comparing drought severity, duration, and intensity. New hydrological insights for the region: Results indicate that nonstationary models consistently outperform the stationary baseline, with M2 (temperature and antecedent runoff) providing the best fit. Analysis of S/NS drought indices along the Halil-Rud Basin reveals that NSRI more accurately captures spatiotemporal drought variability, especially in downstream regions affected by anthropogenic influences. Compared to SSRI, NSRI moderates extreme drought estimates, highlighting the risk of overestimation when using stationary assumptions. These findings demonstrate the value of nonstationary modeling for robust drought monitoring and adaptive water resource management in semi-arid regions.

Marina Rodes-Blanco, Paloma Ruiz-Benito, Inmaculada Aguado et al.

Drought events are becoming more intense, prolonged, and hotter in the Mediterranean region. Forest biomass and tree competition for limiting resources are also increasing due to reductions in management intensity and rural abandonment, increasing the probability of drought-induced forest decline. Future climate change scenarios predict increased warming and drought intensity, highlighting the importance of developing spatio-temporal monitoring systems to identify drought-induced decline and tree mortality events. Despite satellite remote sensing techniques combined with field data represent the most effective approach for developing forest health monitoring systems, our understanding of which sensors, spectral and spatial resolutions are most suitable for detecting forest decline is still limited. In this study, we assessed the potential of Landsat-8/OLI, Sentinel-2/MSI and PlanetScope/SD sensors to detect drought-induced forest decline in Mediterranean Scots pine forests quantifying the influence of spectral resolution, spatial resolution, level of damage and forest cover. Sentinel-2/MSI showed the highest performance, especially when using spectral indices that include SWIR (NDWIswir2, TCW, MDWI) or red edge bands (NDRE1, MTCI) as indicated by the c. 80% correlation with canopy damage. Optimum spatial resolution for all sensors was 20-30 m; however, forest decline detection was strongly affected by forest cover, with forest cover under 50-60% decreasing dieback detection, probably due to the background signal from soil and understory. Together, our results provide key insights for developing drought-induced forest decline and tree mortality monitoring systems in Mediterranean forests using satellite remote sensing.

Luca Laudi, Ofer Dahan, Manuel Sapiano et al.

Study region:: Maltese Islands Study focus:: This study integrates five years of vadose zone (VZ) and groundwater monitoring to identify the dominant non-point sources of nitrate pollution across various agricultural systems. A network of 16 VZ monitoring stations was installed beneath six representative crops (potatoes, fodder, vegetables, vineyards, greenhouses, and orchards) to quantify nitrate buildup and storage. Groundwater samples were collected from the three major aquifer systems of Malta. The analysis couples chemical monitoring with Modified DRASTIC vulnerability modelling to determine how VZ properties, land use, and geological structure influence nitrate delivery to groundwater. New hydrological insights for the region:: The results show that nitrate accumulation in the VZ varies strongly with crop type and geology. Potato cultivation produces the highest VZ nitrate storage and is the dominant source of nitrate loading to the MSLA, while intensive vegetable and greenhouse farming create local contamination hotspots above the Blue Clay and Coastal aquifers. Orchards and vineyards exhibit substantially lower nitrate buildup. Modified DRASTIC modelling highlights VZ thickness and nitrate storage as key controls on aquifer vulnerability. These findings clarify the coupled role of land use and subsurface structure in governing nitrate transport, providing a practical framework for identifying non-point nitrate pollution sources and enhancing groundwater management.

Fuchu Dai, C. Lee, Jiyan Li et al.

M. Bhalla, D. Proffitt

Nina Raoult, Natalie Douglas, Natasha MacBean et al.

Abstract Accurately predicting terrestrial ecosystem responses to climate change over long‐timescales is crucial for addressing global challenges. This relies on mechanistic modeling of ecosystem processes through land surface models (LSMs). Despite their importance, LSMs face significant uncertainties due to poorly constrained parameters, especially in carbon cycle predictions. This paper reviews the progress made in using data assimilation (DA) for LSM parameter optimization, focusing on carbon‐water‐vegetation interactions, as well as discussing the technical challenges faced by the community. These challenges include identifying sensitive model parameters and their prior distributions, characterizing errors due to observation biases and model‐data inconsistencies, developing observation operators to interface between the model and the observations, tackling spatial and temporal heterogeneity as well as dealing with large and multiple data sets, and including the spin‐up and historical period in the assimilation window. We outline how machine learning (ML) can help address these issues, proposing different avenues for future work that integrate ML and DA to reduce uncertainties in LSMs. We conclude by highlighting future priorities, including the need for international collaborations, to fully leverage the wealth of available Earth observation data sets, harness ML advances, and enhance the predictive capabilities of LSMs.

Yanmei Li, Jihong Qin, Yuwen Chen et al.

The alpine peatlands in western Sichuan Province are currently experiencing aridification. To understand the effects of aridification on the characteristics of organic carbon release from alpine soils, the soil in the northwest Sichuan Plateau was investigated. Soil columns were incubated under different moisture conditions in situ and in the laboratory, and ultraviolet-visible absorption spectroscopy and three-dimensional fluorescence spectroscopy were used to assess the soil dissolved organic carbon (DOC) levels. The results revealed that (1) the cumulative release of DOC from alpine soil in the northwest Sichuan Plateau decreased with decreasing moisture content. The cumulative release of soil DOC in the laboratory (0–5 cm soil reached 1.93 ± 0.43 g/kg) was greater than that from soil incubated in situ (0–5 cm soil reached 1.40 ± 0.13 g/kg); (2) the cumulative release of DOC in 0–5 cm soil exhibited the greatest response to changes in water content, and the cumulative release of DOC from the 0–5 cm soil layer (1.40 ± 0.13 g/kg) was greater than that from the 5–15 cm soil layer (1.25 ± 0.03 g/kg); and (3) UV-visible absorption spectra and 3D fluorescence spectral characteristics indicated that aridification increases the content of chromophoric dissolved organic matter (CDOM) components with strong hydrophobicity, especially tyrosine components (surface soil increased 39.59~63.31%), in alpine soil DOC. This increase in hydrophobic CDOM components enhances the aromaticity and degree of humification of DOC. Our results revealed that drought inhibits the release of soil DOC, which is unfavorable for the sequestration of organic carbon in alpine soils, potentially resulting in the loss of soil carbon pools and further degradation of alpine ecosystem functions.

J. Jalan, M. Ravallion

Zongze Li, Jinsong Chong, Yawei Zhao et al.

Glacier velocity is one of the crucial parameters in the research of glacier dynamics. Synthetic aperture radar (SAR), as an active microwave sensor, represents a common method to monitor glacier velocity. However, the changes of glacier surface could cause the data missing of glacier velocity due to incoherence. To meet the demand for glacier velocity monitoring, this paper employs the SAR images of Sentinel-1 in long time series and optical images of Sentinel-2 to investigate the velocity of Petermann glacier in 2021. Firstly, the time series of glacier velocity in the whole year of 2021 is obtained by using SAR images. The glacier velocity extracted from the optical image pairs is used as the initial value of the large missing part of the glacier velocity field. Then the spatiotemporal glacier velocity matrix is constructed and empirical orthogonal function (EOF) analysis is carried out. Among them, the glacier velocity is reconstructed by the glacier velocity estimation method based on confidence, and the complete glacier velocity time series is obtained by iterating to minimize the error of the reconstructed glacier velocity. Finally, the obtained time series of Petermann Glacier velocity in 2021 were statistically analyzed. The statistical results quantified the seasonal differences of Petermann Glacier. In addition, the analysis results show that the temporal and spatial variations of Petermann Glacier velocity are affected by topography and temperature.

Nannan Yang, Liangzhi Li, Ling Han et al.

Efficient prediction and precise depiction of heavy metal concentrations in urban soil are essential for mitigating non-point source pollution and safeguarding public health. Therefore, this research investigated the estimation of soil heavy metal concentrations derived from Gaofen-5 (GF-5) hyperspectral images calibrated by the direct standardization (DS) algorithm. The inversion strategy for soil heavy metal concentrations in response to the two-dimensional soil spectral index (2D-SSI) was proposed by coupling Pearson correlation coefficient (r) and competitive adaptive reweighting algorithm (CARS) for feature selection. The results indicated that the optimal models based on 2D-SSI outperform the models based on calibrated, filtered original spectral bands. For Pb, Cu, Cd, and Hg, the optimal model determination coefficients for the validation data set (RV2) were 0.871 (SVM), 0.883 (BPNN), 0.834 (PLSR), and 0.907 (PLSR), respectively. The spectral features were highlighted in the two-dimensional feature space, and the predicted distribution of heavy metal concentrations was aligned with the observed ground measurements. This study revealed that the prediction strategy based on DS-corrected GF-5 AHSI images with constructed 2D-SSI features can serve as a reliable technical approach for soil heavy metal prediction and pollution prevention.

J. Pucher, Ralph Buehler, D. Bassett et al.

C. Quesada, J. Lloyd, L. Anderson et al.

Abstract. The tropical forests of the Amazon Basin occur on a wide variety of different soil types reflecting a rich diversity of geologic origins and geomorphic processes. We here review the existing literature about the main soil groups of Amazonia, describing their genesis, geographical patterns and principal chemical, physical and morphologic characteristics. Original data is also presented, with profiles of exchangeable cations, carbon and particle size fraction illustrated for the principal soil types; also emphasizing the high diversity existing within the main soil groups when possible. Maps of geographic distribution of soils occurring under forest vegetation are also introduced, and to contextualize soils into an evolutionary framework, a scheme of soil development is presented having as its basis a chemical weathering index. We identify a continuum of soil evolution in Amazonia with soil properties varying predictably along this pedogenetic gradient.

N. Kinoshita, K. Sueki, K. Sasa et al.

A tremendous amount of radioactivity was discharged because of the damage to cooling systems of nuclear reactors in the Fukushima No. 1 nuclear power plant in March 2011. Fukushima and its adjacent prefectures were contaminated with fission products from the accident. Here, we show a geographical distribution of radioactive iodine, tellurium, and cesium in the surface soils of central-east Japan as determined by gamma-ray spectrometry. Especially in Fukushima prefecture, contaminated area spreads around Iitate and Naka-Dori for all the radionuclides we measured. Distributions of the radionuclides were affected by the physical state of each nuclide as well as geographical features. Considering meteorological conditions, it is concluded that the radioactive material transported on March 15 was the major contributor to contamination in Fukushima prefecture, whereas the radioactive material transported on March 21 was the major source in Ibaraki, Tochigi, Saitama, and Chiba prefectures and in Tokyo.

Helen Essell, Paul J Krusic, Jan Esper et al.

Existing global mean surface temperature reconstructions for the Holocene lack high-frequency variability that is essential for contextualising recent trends and extremes in the Earth’s climate system. Here, we isolate and recombine archive-specific climate signals to generate a frequency-optimised record of interannual to multi-millennial temperature changes for the past 12 000 years. Average temperatures before ∼8000 years BP and after ∼4000 years BP were 0.26 (±2.84) °C and 0.07 (±2.11) °C cooler than the long-term mean (0–12 000 years BP), while the Holocene Climate Optimum ∼7000–4000 years BP was 0.40 (±1.86) °C warmer. Biased towards Northern Hemisphere summer temperatures, our multi-proxy record captures the spectral properties of transient Earth system model simulations for the same spatial and season domain. The new frequency-optimised trajectory emphasises the importance and complex interplay of natural climate forcing factors throughout the Holocene, with an approximation of the full range of past temperature changes providing novel insights for policymakers addressing the risks of recent anthropogenic warming.

J.P. Rodrigue

The emergence of e-commerce as a dominant retail paradigm is associated with a rapid shift in the commercial footprint towards distributional-based consumption. Through the analysis of the geographical expansion, market coverage, and functional specialization of Amazon's distribution network, the research underlines that digitalization has a pronounced physicality. E-commerce is favoring a transition from the conventional retail freight landscape towards a new physicality of freight distributions involving purpose-designed facilities, modes, and channels. The case of Amazon underlines a consistent locational behavior to achieve a distributional hierarchy of facilities granting logistical access to consumer markets. The distributional hierarchy is organized in three stages, which are procurement and fulfillment, distribution, and last-mile.

C. Leal, B. Chaix, B. Chaix

J. Coyne

Richard M. Palin

The Earth is a dynamic, ever-changing planet, and there exist many feedbacks and cycles that operate within and between its subsystems. Interactions between processes operating in the solid Earth, atmosphere, hydrosphere, and biosphere have become increasingly better understood in recent years, given advances made in observational techniques that provide data at ever-higher spatial and temporal resolution. Indeed, the relationships that metamorphism has with classically disparate areas of Earth science, such as biogeoscience, economic geology, and natural hazards, are becoming progressively clearer as more petrologists are applying their knowledge, tools, and techniques to cross-disciplinary studies. In this review, I outline the role that metamorphism and metamorphic rocks play within various geosystems and indicate some areas in which directed future research may lead to notable breakthroughs in our understanding of the structure and functioning of the Earth as a whole.