A finite difference method for earthquake sequences in poroelastic solids

Induced seismicity (earthquakes caused by injection or extraction of fluids in Earth’s subsurface) is a major, new hazard in the USA, the Netherlands, and other countries, with vast economic consequences if not properly managed. Addressing this problem requires development of predictive simulations of how fluid-saturated solids containing frictional faults respond to fluid injection/extraction. Here, we present a finite difference method for 2D linear poroelasticity with rate-and-state friction faults, accounting for spatially variable properties. Semi-discrete stability and accuracy are proven using the summation-by-parts, simultaneous-approximation-term (SBP-SAT) framework for discretization and boundary condition enforcement. Convergence rates are verified using the method of manufactured solutions and comparison to the analytical solution to Mandel’s problem. The method is then applied to study fault slip triggered by fluid injection and diffusion through high-permeability fault damage zones. We demonstrate that in response to the same, gradual forcing, fault slip can occur in either an unstable manner, as short-duration earthquakes that radiate seismic waves, or as stable, aseismic, slow slip that accumulates over much longer time scales. Finally, we use these simulation results to discuss the role of frictional and elastic properties in determining the stability and nature of slip.     

Tidal Influences on Biotic and Abiotic Factors in the Seomjin River Estuary and Gwangyang Bay,Korea

To assess changes in abiotic and biotic factors between flood and ebb tides, we investigated the seasonal phytoplankton dynamics and environmental conditions along a salinity gradient at 14 stations in the Seomjin River estuary (SRE), Korea, and conducted bioassays to investigate the effect of nutrient addition (+N, +P, and +NP) on phytoplankton growth. Saltwater intrusion upstream was greatly dependent on the amount of freshwater discharge resulting from seasonal rainfall. There was a strong negative correlation between salinity and the nitrate+nitrite concentration (p?<?0.001), and between salinity and the silicate concentration (p?<?0.001), but no clear correlation between salinity and the ammonium concentration, or salinity and the phosphate concentration (p?>?0.01). This indicates that the N and Si loading increased as a result of freshwater input. The algal bioassays showed that high phytoplankton growth rates were usually recorded in response to the +NP treatment, but in the saltwater zone, the phytoplankton community also responded rapidly to the +N treatment, and to the +P treatment in the freshwater zone. The range of nutrient limitation depended on freshwater discharge. The seasonal and horizontal distribution of phytoplankton communities changed along the salinity gradient. The significant differences in abiotic factors between flood and ebb tides play important roles in controlling the biotic factors, including the occurrence of aquatic organisms including microalgae.     

Landslide susceptibility mapping using random forest and boosted tree models in Pyeong-Chang,Korea

Landslides susceptibility maps were constructed in the Pyeong-Chang area, Korea, using the Random Forest and Boosted Tree models. Landslide locations were randomly selected in a 50/50 ratio for training and validation of the models. Seventeen landslide-related factors were extracted and constructed in a spatial database. The relationships between the observed landslide locations and these factors were identified by using the two models. The models were used to generate a landslide susceptibility map and the importance of the factors was calculated. Finally, the landslide susceptibility maps were validated. Finally, landslide susceptibility maps were generated. For the Random Forest model, the validation accuracy in regression and classification algorithms showed 79.34 and 79.18%, respectively, and for the Boosted Tree model, these were 84.87 and 85.98%, respectively. The two models showed satisfactory accuracies, and the Boosted Tree model showed better results than the Random Forest model.     

Groundwater Potential Mapping Using GIS-Based Hybrid Artificial Intelligence Methods

Groundwater is one of the major valuable water resources for the use of communities, agriculture, and industries. In the present study, we have developed three novel hybrid artificial intelligence (AI) models which is a combination of modified RealAdaBoost (MRAB), bagging (BA), and rotation forest (RF) ensembles with functional tree (FT) base classifier for the groundwater potential mapping (GPM) in the basaltic terrain at DakLak province, Highland Centre, Vietnam. Based on the literature survey, these proposed hybrid AI models are new and have not been used in the GPM of an area. Geospatial techniques were used and geo-hydrological data of 130 groundwater wells and 12 topographical and geo-environmental factors were used in the model studies. One-R Attribute Evaluation feature selection method was used for the selection of relevant input parameters for the development of AI models. The performance of these models was evaluated using various statistical measures including area under the receiver operation curve (AUC). Results indicated that though all the hybrid models developed in this study enhanced the goodness-of-fit and prediction accuracy, but MRAB-FT (AUC = 0.742) model outperformed RF-FT (AUC = 0.736), BA-FT (AUC = 0.714), and single FT (AUC = 0.674) models. Therefore, the MRAB-FT model can be considered as a promising AI hybrid technique for the accurate GPM. Accurate mapping of the groundwater potential zones will help in adequately recharging the aquifer for optimum use of groundwater resources by maintaining the balance between consumption and exploitation.     

Northern landscapes in transition: Evidence,approach and ways forward using the Krycklan Catchment Study

Improving our ability to detect changes in terrestrial and aquatic systems is a grand challenge in the environmental sciences. In a world experiencing increasingly rapid rates of climate change and ecosystem transformation, our ability to understand and predict how, when, where, and why changes occur is essential for adapting and mitigating human behaviours. In this context, long-term field research infrastructures have a fundamentally important role to play. For northern boreal landscapes, the Krycklan Catchment Study (KCS) has supported monitoring and research aimed at revealing these changes since it was initiated in 1980. Early studies focused on forest regeneration and microclimatic conditions, nutrient balances and forest hydrology, which included monitoring climate variables, water balance components, and stream water chemistry. The research infrastructure has expanded over the years to encompass a 6790 ha catchment, which currently includes 11 gauged streams, ca. 1000 soil lysimeters, 150 groundwater wells, >500 permanent forest inventory plots, and a 150 m tall tower (a combined ecosystem-atmosphere station of the ICOS, Integrated Carbon Observation System) for measurements of atmospheric gas concentrations and biosphere-atmosphere exchanges of carbon, water, and energy. In addition, the KCS has also been the focus of numerous high resolution multi-spectral LiDAR measurements and large scale experiments. This large collection of equipment and data generation supports a range of disciplinary studies, but more importantly fosters multi-, trans-, and interdisciplinary research opportunities. The KCS attracts a broad collection of scientists, including biogeochemists, ecologists, foresters, geologists, hydrologists, limnologists, soil scientists, and social scientists, all of whom bring their knowledge and experience to the site. The combination of long-term monitoring, shorter-term research projects, and large-scale experiments, including manipulations of climate and various forest management practices, has contributed much to our understanding of boreal landscape functioning, while also supporting the development of models and guidelines for research, policy, and management.     

Observations of neutral hydrogen in the corona

Measurements of the linear polarization degree (p) of the emission in the inner corona (<1.5 R _⊙) in the green and red continuum ranges are discussed. “Excess p” (Δp = pgreen — pred), which reaches its maximum at 1.2–1.3 R _⊙ (<5%) in the polar regions and 20% within large-scale streamers, is present everywhere in the corona. It has been mentioned that excess p can be explained by the presence of neutral hydrogen in the corona.     

Underwater Explosion (UWE) Analysis of the ROKS Cheonan Incident

The underwater explosion (UWE) resulting in the sinking of the South Korean warship, ROKS Cheonan occurred on March 26 2010. Raw data was analyzed from several 3-component stations—Baengyeong-do Korea Meteorological Administration (KMA) station (BAR), Ganghwa KMA station (GAHB), Incheon Incorporated Research Institutions for Seismology (IRIS) station (INCN), the short-period station—Deokjeok-do KMA station (DEI), as well as from the seismo-acoustic array Baengyeong-do Korea Institute of Geoscience and Mineral Resources (KIGAM) station (BRDAR). The ROKS Cheonan incident has been investigated by both the Multinational Civilian-Military Joint Investigation Group (Ministry of National Defense, 2010) and Hong (Bull Seism Soc Am 101:1554–1562, 2011). Their respective methods and conclusions are also presented in this study. One of the main differences between their findings and ours is that we deducted that the fundamental bubble frequency was 1.01 Hz with a subsequent oscillation of 1.72 Hz. Also, in contrast to findings by the MCMJIG and Hong, our analysis shows the first reverberation frequency to be 8.5 Hz and the subsequent one to be ≈25 Hz. The TNT-equivalent charge weight (seismic yield) and seismic magnitude were estimated from an observed bubble frequency of 1.01 Hz and the analytical model of a bubble pulse. From the data analyzed, we deducted that the seismic yield would be about 136 kg of TNT, which is equivalent to the individual yield of a large number of land control mines (LCM) which were abandoned in the vicinity of the ROKS Cheonan incident by the Republic of Korea (ROK) Navy in the 1970s (Ministry of National Defense 2010). Also, whereas both the MCMJIG and HONG estimated the local magnitude at 1.5, our findings came to the conclusion of a local magnitude of approximately 2.04 based on the bubble frequency of 1.01 Hz measured on the vertical component of BAR station data considering the empirical relationship between charge weight (TNT yield) and underwater explosion magnitude. Strong high-frequency signals collected at the 3-component BAR station approximately 30 s after P-wave arrivals and infrasound records at BRDAR clearly indicate powerful acoustic phases and N-waves caused by a relatively shallow UWE. T-phases are also observed on seismograms and spectra at 15–17 Hz on the DEI, GAHB, and INCN stations.     

The occurrence of cyanobacteria and microcystins in the Hoan Kiem Lake and the Nui Coc reservoir (North Vietnam)

The occurrence of increasing blooms of toxic cyanobacteria in freshwaters has received much attention due to the ability of many cyanobacteria to produce potent cyanotoxins. In this paper, the occurrence of dominant cyanobacteria and the concentration of microcystins (MCs) analysis were investigated monthly from July 2008 to April 2009 in the Hoan Kiem Lake and from February to April 2009 in the Nui Coc reservoir. Concentrations of intracellular MCs from water, bloom samples, and isolated strains were quantified by using high performance liquid chromatography (HPLC). During the study period, the microscopic examination of the phytoplankton samples showed the dominance of the genus Microcystis in the water environment of the Hoan Kiem Lake and the Nui Coc reservoir. The toxin analysis by HPLC demonstrated the presence of two MC variants: MC-LR and MC-RR in water samples. Total concentrations of the toxins in filtered samples from surface water ranged from non-detected to 0.91 μg L^?1 at Nui Coc reservoir and they ranged from 2.1 to 46.0 μg L^?1 at Hoan Kiem Lake. The results of the HPLC analysis confirmed the production of MCs in bloom samples (ranged from 115.9 to 184.6 μg L^?1 in the Hoan Kiem Lake and from 726.5 to 1116 μg L^?1 in the Nui Coc reservoir) and isolated strains of Anabaena sp. and Microcystis with the concentration of MC ranging from 152 to 396.2 μg g^?1 dry mass, respectively.     

Non-parametric simulations-based conditional stochastic predictions of geologic heterogeneities and leakage potentials for hypothetical CO2 sequestration sites

The present study focuses on understanding the leakage potentials of the stored supercritical CO₂ plume through caprocks generated in geostatistically created heterogeneous media. For this purpose, two hypothetical cases with different geostatistical features were developed, and two conditional geostatistical simulation models (i.e., sequential indicator simulation or SISIM and generalized coupled Markov chain or GCMC) were applied for the stochastic characterizations of the heterogeneities. Then, predictive CO₂ plume migration simulations based on stochastic realizations were performed and summarized. In the geostatistical simulations, the results from the GCMC model showed better performance than those of the SISIM model for the strongly non-stationary case, while SISIM models showed reasonable performance for the weakly non-stationary case in terms of low-permeability lenses characterization. In the subsequent predictive simulations of CO₂ plume migration, the observations in the geostatistical simulations were confirmed and the GCMC-based predictions showed underestimations in CO₂ leakage in the stationary case, while the SISIM-based predictions showed considerable overestimations in the non-stationary case. The overall results suggest that: (1) proper characterization of low-permeability layering is significantly important in the prediction of CO₂ plume behavior, especially for the leakage potential of CO₂ and (2) appropriate geostatistical techniques must be selectively employed considering the degree of stationarity of the targeting fields to minimize the uncertainties in the predictions.