Urban estuarine areas are exposed to flooding caused by heavy rain and tidal processes in cities lacking adequate infrastructure. Our aim of this paper was to analyze the relationship between precipitation intensity, tidal dynamics, and flooding occurrence in Bel & eacute;m (Par & aacute;, Brazil), located in Guajar & aacute; Bay. Flood-related losses and damage have occurred throughout the city, especially in central consolidated and peripheral areas. The materials and methods included data collected from weather stations (1961-2020) of the National Institute of Meteorology and remote sensing data (1990-2023) from the Climate Hazards Group InfraRed Precipitation with Station dataset. Tide data (2006-2020) were obtained from the Brazilian Navy website, and damage information was collected from news reports, scientific articles, and official databases covering the period from 1987 to 2020. The locations mentioned in these reports were georeferenced and mapped. The results showed that in 1961 and 1990, the months with the highest precipitation were February and March, while during the period from 1991 to 2020, the rainiest months shifted to March and April. Extremely intense rainfall led to flooding-related damage in all city districts. A total of 51 news reports detailing the damage caused by flooding related to excessive rainfall and tides were identified, of which 24 occurred under extremely intense conditions. The highest tides were recorded in 2010, reaching 3.9m, and in 2014, 2015, and 2019, the tides reached 3.8 m at noon. In exposed and vulnerable areas, combined rainfall and high tides are the major causes of flooding, according to analysis of coincidences. The most common damages included loss of furniture and household appliances, interruptions to urban mobility, urban infrastructure damage, and the temporary isolation of residents. The linkages between rain and tides may contribute to risk management and alert purposes.
Soils of arable lands abandoned from agricultural use more than three decades ago were studied within the Central Yakutian Plain at sites located in the zone of the ice complex. Under conditions of climate change, the degradation of the ice complex occurs on abandoned arable lands due to an increase in the depth of seasonal soil thawing. The melting of ground ice underlying large areas of former arable land causes subsidence and deformation of the surface, accompanied by the formation of initial thermokarst landforms. These are revealed as combinations of convex rounded mounds (up to 5-9 m in diameter) and a polygonal network of depressions above thawing ice wedges (0.5-1.5 m deep). The formation of a specific thermokarst microrelief results in changes in the redistribution of moisture on the surface and within the soil, as well as in thawing depth; thus, the water-permafrost regime of thermokarst-affected soils begins to acquire distinct features. As a result, the previously homogeneous soil cover-represented by cultivated pale solonetzic soils of abandoned fields-transforms into a mosaic combination of soils. This includes patches of dark cryogenic solonetz soils on the tops of mounds and light gleyic solonetz soils in the bottoms of depressions, adjacent to typical light solonetz soils developing along the slopes of the microrelief. The main changes affecting the soil cover and soil properties of the studied sites at the initial stages of thermokarst relief dynamics were identified. In particular, the major morphological changes in soil profile structure and the dynamics of such indicators as bulk density, acidity, and field moisture at different elements of the cryogenic microrelief were examined. A significant lightening of the upper soil layers on the slopes of the mounds and in the depressions between them was observed as a result of increased moisture compared to the drier soils of the convex parts of the microrelief. A comparison between cultivated soils and background forest soils was also carried out.
Colluvial deposits are heterogeneous and unconsolidated clastic sediments accumulated at the base of hills or mountain slopes. In recent years, these sediments have received attention in environmental and geological research, as they record valuable data about paleo-tectonic activities, paleoclimate, and weathering conditions in subaerial slopes. This chapter reviews and discusses concepts of colluvial deposits in geosciences and describes lithofacies, depositional processes, models, and practical implications. A combination of field observations, laboratory work, and geotechnical investigations allows for a better understanding of slope processes responsible for colluvial accumulation. These deposits accumulate in various climatic conditions, being transported and deposited mainly by gravity (i.e., mass wasting and mass flow). The main lithofacies are rock falls and debris-flow deposits. Subordinate facies include calcrete/paleosol horizons and water-flow deposits (slope wash). While mass wasting occurs in tectonically unstable periods, soil horizons may develop during periods of tectonic quiescence.
Geographic locations and geo-trails are often dispersed, and their accessibility is subject to rapid changes, which can have detrimental effects on the environment, tourism, and economy. Geo-trail planning faces challenges due to geographic dispersion and varying accessibility, impacting sustainable tourism, environmental conservation, and visitor safety. This study aimed to identify the optimal geo-trail route of 12 distinct geo-sites for climbers, eco-tourists, and general tourists in the Mount Damavand region, Iran. A genetic algorithm (GA) was used to solve this multi-objective geo-trail route optimization. The GA model adhered to route connectivity and non-repetition constraints through minimizing total distance, travel time, and cost while maximizing access to services and key attractions from the perspectives of tourists and eco-tourists. The model was implemented in MATLAB (population size: 50; iterations: 100; mutation probability: 0.5) and integrated with ArcGIS for spatial analysis. The GA algorithm converged to a stable solution with an objective function value of 4.718, improved from an initial average of 8.74. The optimal route spanned 105 km and 1033 minutes, connecting key sites including Emamzadeh (S6), Glacier (S10), and Ask (S12). The performance of the GA was benchmarked against three reference approaches: the nearest neighbor (NN) heuristic, a random search baseline, and ant colony optimization (ACO). While both GA and ACO vastly outperformed simple heuristics, the choice between them may depend on specific implementation constraints or desired solution characteristics (e.g., GA's ease of parallelization vs. ACO's faster initial convergence). The GA exhibited greater robustness, with a coefficient variation of 0.9% across runs versus 2.4% for ACO. This demonstrates the effectiveness of GAs in solving complex geotourism routing problems and provides a data-driven framework for sustainable trail planning. The proposed approach enhances visitor experience, supports intelligent tourism management, and minimizes environmental impacts, offering a scalable model for mountainous and ecologically sensitive regions.
The volumes of CO2 released at some basaltic volcanoes (e.g., Etna, Stromboli) significantly exceed the limits of solubility in silicate melt, indicating flushing by deep, CO2-rich fluids from crustal and mantle sources. A similar flushing mechanism in silicic magmatic systems has been less evident. Here, we propose that H2Ou2013CO2 contents in quartz-hosted melt inclusions (MIs) can serve as an indicator of interaction between hydrous rhyolitic magma and carbonic fluid. Numerical modeling of this interaction process at the single-bubble scale, accounting for volatile diffusivity dependencies on water content, demonstrates that a uniformly dehydrated melt with highly variable CO2 concentrations can form on relatively short timescales. In natural magma bodies where bubble coalescence and escape occur, this process generates melt compositions that form subvertical arrays on H2Ou2013CO2 diagrams. Such compositions, preserved in melt inclusions, are commonly found in pyroclastic deposits from catastrophic intraplate rhyolitic eruptions, such as those of the Yellowstone caldera. Reinterpretation of extensive published MI data from the pre-Huckleberry Ridge Tuff-A ashfall deposits at Yellowstone reveals episodes of carbonic fluid-magma interaction that likely initiated explosive eruptions. The first eruptive cycle is associated with flushing at the basal boundary layer of the magma chamber by a fluid enriched in CO2 and Li. The resulting bubbly layer would ascend rapidly, being captured in the earliest erupted magma that forms the base of the ash sequence. MIs from this level show a strong positive correlation between CO2 and Li concentrations. In contrast, a significant negative correlation between CO2 and Li is observed in MIs from near the top of the 2-meter-thick ash sequence. This pattern is attributed to a second, distinct flushing episode by a Li-poor fluid, which culminated in the massive early Huckleberry Ridge Tuff (HRT-A) ignimbrite eruption that overlies the ashfall deposits. Other samples exhibit a strong positive correlation between Li and H2O, explainable by syneruptive diffusive loss of both components. Diffusive water loss from reentrants and MIs consistently indicates a syneruptive magma decompression rate of ~0.02u20130.06 MPa/s. Finally, the unusual population of reentrants and MIs with uniformly low H2O (1u20131.5 wt.%) but variable-to-high CO2 contents at the top of the ash section can be explained by dehydration during interaction with (or formation from) a water-poor melt. This melt was likely generated by remelting of largely solidified rhyolite, underplated by basalt, as an alternative or complementary process to CO2 flushing.
The available data on the dissolved fluoride content and the saturation degree by fluorite in waters of the world ocean and large continental reservoirs were critically reviewed. It was shown that evaporative concentrating of dissolved salts in the autonomous marine basins cannot cause chemogenic fluorite precipitation, which can occur only with additional supply of fluoride from external sources (river runoff, volcanic exhalations, and terrigenous aerosols). The contribution of external fluoride sources should be at least 1.5u20134 times of the mass of fluoride supplied with seawater. As such, saturation of waters by CaF2 and the fluorite formation is possible in large drying continental reservoirs of the arid zone that have no direct connection with the world ocean. An assumption about a two-stage mechanism of authigenic fluorite formation in carbonate rocks was made. At the first stage, freshly formed finely dispersed carbonate sediments uptake fluoride from seawater as a result of sorption and coprecipitation. In the second stage, during the recrystallization of the primary solid phase, its partial purification occurs, which is accompanied by the release of some of the uptaken fluoride into the pore solutions. This causes an increase in the dissolved fluoride concentration in the pore waters to values sufficient for fluorite precipitation.
Volcanic risk monitoring and assessment are fundamental components of geohazard management, especially in the context of densely inhabited and socio-economically vulnerable regions. Traditional surface-based monitoring techniques, while valuable, often fall short in detecting deep, subsurface processes that precede eruptive events, particularly in areas where social, infrastructural, and logistical constraints hinder the deployment of high-resolution seismic surveys. These limitations are especially critical in volcanic settings where communities are exposed to multiple layers of risk, not only from natural hazards but also from structural inequalities and uneven access to protective measures. To address these challenges, we introduce a novel framework based on Self-Aware Joint Inversion, an adaptive, learning-driven method for the integration of multi-physics geophysical data. By combining seismic and non-seismic geophysical approaches, such as electrical resistivity tomography, gravity, and electromagnetic methods, within a self-optimizing joint inversion technique, our approach enables the dynamic and high-resolution imaging of subsurface processes that are directly linked to magma and fluid migration. Unlike conventional models that often remain shallow or static, this methodology offers time-lapse capabilities and deeper investigation, thereby enabling early detection of phenomena critical to volcanic risk forecasting. The method was tested on synthetic case studies simulating realistic volcanic conditions, enabling rigorous evaluation of resolution, adaptability, and potential operational performance. Results indicated that this approach can reconstruct subsurface anomalies associated with pre-eruptive activity, even in scenarios where classical monitoring frameworks would fail. Beyond its scientific contribution, this methodology is explicitly designed to be non-invasive and scalable, making it particularly suitable for application in sensitive inhabited zones.
Peatlands play a critical role in global carbon cycling, long-term ecological dynamics, and climate-carbon feedbacks, making their formation processes a key focus of global change research. The Ningshao Plain, a coastal lowland in eastern China, contains extensive Holocene peat deposits that developed mainly between similar to 7.0 and 2.5 cal ka BP. However, the mechanisms driving peatland formation in this region remain poorly understood. In this study, we present new diatom data from the well-dated T1041 profile at the Tianluoshan site in the Ningshao Plain, integrated with published pollen and carbonized seed records, to investigate the drivers of three mid-Holocene peat-forming episodes at 6.5-6.4, 5.2-5.1, and 4.4-4.3 cal ka BP. These peat layers formed under contrasting hydrological conditions, yet each is overlain by flooding deposits, likely associated with storm surges and/or extreme rainfall. Such event layers introduced substantial clastic materials into the wetlands, resulting in waterlogging and persistent anaerobic conditions conducive to peat accumulation. Our results indicate that peatland deposits in the Ningshao Plain constitute sensitive archives of abrupt hydrological responses to mid-Holocene weak monsoon events.
Typical Meteorological Years (TMYs) are synthetic annual datasets constructed from long-term observations to represent the characteristic climatic conditions of a location. Rather than reproducing extreme events, a TMY captures the typical variability of key meteorological parameters and is widely used in energy system modeling, building performance simulations, and climate-responsive design. Although TMYs have been developed for many regions worldwide, no comprehensive effort has been made for Saudi Arabia, despite its rapidly growing interest in solar energy. In this study, we present the first derivation of TMYs for thirty sites across the country. Hourly observations of global, direct, and diffuse horizontal irradiance, air temperature, relative humidity, and mean and maximum wind speed were quality-controlled and processed. The modified Sandia National Laboratories method, based on the Finkelstein-Schafer (FS) statistical procedure, was applied to select representative months and assemble each TMY. Graphical diagnostics and statistical indicators were used to evaluate the agreement between the generated TMYs and long-term climatological averages. The results demosntrated that the constructed TMYs successfully reproduce the typical meteorological behavior at all sites, providing reliable input data for solar-energy assessments and other climate-sensitive applications in Saudi Arabia.
The geotechnical characterisation of silty soils remains a challenge due to their transitional behaviour and high variability. In Finland, silts are widespread but poorly represented in existing correlations, which are largely based on clays or sands. Current practice often relies on Weight Sounding (Painokairaus, PK) and Combined Static-Dynamic Penetration Testing (Puristinheijari, PH), supported by empirical guidelines developed several decades ago. While these methods are costeffective, their reliability in silts is uncertain and often conservative. In this study, we reported results from a benchmarking campaign at the Haistila test site in south-west Finland, where PK, PH, and piezocone penetration tests (CPTU) were performed independently by Tampere University and Ramboll Finland Oy. The objective was to quantify variability between methods and operators, and to assess implications for geotechnical design. Results showed that CPTU provided the most repeatable measurements, with cone tip resistance showing the lowest relative error and coefficient of variation. In contrast, PH results displayed greater variability, particularly in torque, and resulted in possibly conservative design parameters according to national guidelines. The findings confirmed that PK and PH are useful for stratigraphic profiling but not for parameter derivation in silts. CPTU, if calibrated with laboratory data, offers a more robust alternative and highlights the need for updated, silt-specific correlations in Finland.
Blasting is the most commonly used method for rock fragmentation in open-pit mining. Its objective is to achieve an adequate particle size for subsequent stages; however, not all the energy is utilized, and some energy is transformed into undesirable effects. Among these effects, flyrock is one of the most hazardous, as it endangers the safety of personnel, machinery, and infrastructure. Over the years, numerous flyrock prediction models have been developed based on different blasting and ground parameters. In the present study, a new predictive model is proposed for the maximum distance reached by a rock fragment based on the velocity obtained using an analogy with the Navier-Stokes equations. The development of the model considered three fundamental stages of fragment projection: (i) detonation of the explosive, which produces pressure on the blasthole perimeter owing to gas expansion, (ii) propagation of the kinetic energy transmitted through the rock mass until it reaches the propelled rock fragment, and (iii) trajectory of the flyrock. The resulting model depends on rock parameters (rock density), explosive parameters (density and energy of the explosive), design parameters (charge length, blasthole diameter, and burden), and a site-specific constant K, which can be determined using multiple regression analysis of the measured field data. A model consistency comparison was developed using Monte Carlo simulations, evaluating 100,000 realizations, demonstrating its potential for use. Similarly, a sensitivity analysis was performed, which verified that the burden was the parameter with the greatest influence within the model, whereas rock density had the least impact. Finally, as a future line of work, its application is proposed in ground conditions under different scenarios to strengthen its use in defining safety zones during blasting and to deepen the physical understanding and meaning of parameter K, as its current interpretation still presents some degree of uncertainty.
The volumes of CO2 released at some basaltic volcanoes (e.g., Etna, Stromboli) significantly exceed the limits of solubility in silicate melt, indicating flushing by deep, CO2-rich fluids from crustal and mantle sources. A similar flushing mechanism in silicic magmatic systems has been less evident. Here, we propose that H2O-CO2 contents in quartz-hosted melt inclusions (MIs) can serve as an indicator of interaction between hydrous rhyolitic magma and carbonic fluid. Numerical modeling of this interaction process at the single-bubble scale, accounting for volatile diffusivity dependencies on water content, demonstrates that a uniformly dehydrated melt with highly variable CO2 concentrations can form on relatively short timescales. In natural magma bodies where bubble coalescence and escape occur, this process generates melt compositions that form subvertical arrays on H2O-CO2 diagrams. Such compositions, preserved in melt inclusions, are commonly found in pyroclastic deposits from catastrophic intraplate rhyolitic eruptions, such as those of the Yellowstone caldera. Reinterpretation of extensive published MI data from the pre-Huckleberry Ridge Tuff-A ashfall deposits at Yellowstone reveals episodes of carbonic fluid-magma interaction that likely initiated explosive eruptions. The first eruptive cycle is associated with flushing at the basal boundary layer of the magma chamber by a fluid enriched in CO2 and Li. The resulting bubbly layer would ascend rapidly, being captured in the earliest erupted magma that forms the base of the ash sequence. MIs from this level show a strong positive correlation between CO2 and Li concentrations. In contrast, a significant negative correlation between CO2 and Li is observed in MIs from near the top of the 2-meter-thick ash sequence. This pattern is attributed to a second, distinct flushing episode by a Li-poor fluid, which culminated in the massive early Huckleberry Ridge Tuff (HRT-A) ignimbrite eruption that overlies the ashfall deposits. Other samples exhibit strong positive correlation between Li and H2O, explainable by syneruptive diffusive loss of both components. Diffusive water loss from reentrants and MIs consistently indicates a syneruptive magma decompression rate of similar to 0.02-0.06 MPa/s. Finally, the unusual population of reentrants and MIs with uniformly low H2O (1-1.5 wt.%) but variable-to-high CO2 contents at the top of the ash section can be explained by dehydration during interaction with (or formation from) a water-poor melt. This melt was likely generated by remelting of largely solidified rhyolite, underplated by basalt, as an alternative or complementary process to CO2 flushing.
Mountain pine bark beetles (MPBB, Dendroctonus ponderosae) are a primary driver of tree mortality in pine-dominant North American forests. To characterize the spatiotemporal dynamics of MPBB infestations in lodgepole pine forests of north central Colorado, we analyzed Landsat spectral trends for 2005 and 2009. Using a stratified random sampling design (N = 1,021), we classified land cover trajectories to identify stable forests, infestation, fire, clear-cutting, and regrowth sites. A Random Forest (RF) classifier was developed to detect infestation presence and predict mortality severity. The model achieved high classification accuracies of 96% (2005) and 97% (2009), while the regression for mortality severity yielded a strong fit (R-2 = 0.878) with a low Root Mean Square Error (RMSE = 0.1425). A rigorous topographic analysis revealed that infestation risk is strongly non-random: South-facing slopes exhibited 9.0 times higher odds of infestation compared to north-facing slopes, likely driven by solar insolation and water stress. However, limitations remain in detecting low-severity mortality (<25% canopy loss) and distinguishing species-specific responses in mixed stands. A simple binary classification of "disturbed" versus "undisturbed, " as is the primary output of many earlier studies, is insufficient for prioritizing management actions. To address these challenges, we propose integrating multi-source data fusion (e.g., Landsat and Sentinel-2), leveraging UAV-based sub-pixel validation, and utilizing phenological metrics from Harmonized Landsat-Sentinel (HLS) data. These advanced approaches, combined with the RF modeling demonstrated, offer a pathway for more precise, early-warning monitoring of forest health in complex topographic landscapes. In addition, this approach can be used for future studies designed to track the location of trees that have developed self-immunity to the beetles with the hope of reforesting with seedlings of these resistant trees.
