•Estimation of IDF curves for rainfall data comprises a classical task in hydrology.•Stationary assumption can be inadequate and lead to poor quantile estimates.•We model annual maximum series ...conditioned on the daily rainfall.•The Bayesian beta model is used to produce nonstationary IDF curves for Korea.•Model provides future climate IDF curves based on climate change scenarios.
The estimation of intensity-duration-frequency (IDF) curves for rainfall data comprises a classical task in hydrology studies to support a variety of water resources projects, including urban drainage and the design of flood control structures. In a changing climate, however, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to poor estimates of rainfall intensity quantiles. Climate change scenarios built on General Circulation Models offer a way to access and estimate future changes in spatial and temporal rainfall patterns at the daily scale at the utmost, which is not as fine temporal resolution as required (e.g. hours) to directly estimate IDF curves. In this paper we propose a novel methodology based on a four-parameter beta distribution to estimate IDF curves conditioned on the observed (or simulated) daily rainfall, which becomes the time-varying upper bound of the updated nonstationary beta distribution. The inference is conducted in a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters when building the IDF curves. The proposed model is tested using rainfall data from four stations located in South Korea and projected climate change Representative Concentration Pathways (RCPs) scenarios 6 and 8.5 from the Met Office Hadley Centre HadGEM3-RA model. The results show that the developed model fits the historical data as good as the traditional Generalized Extreme Value (GEV) distribution but is able to produce future IDF curves that significantly differ from the historically based IDF curves. The proposed model predicts for the stations and RCPs scenarios analysed in this work an increase in the intensity of extreme rainfalls of short duration with long return periods.
In South Korea, the risk of debris-flow is relatively high due to the country's vast mountainous topographical features and intense continuous rainfall during the summer. Debris-flows can result in ...the loss of human life and severe property damage, which can be made worse due to the poor spatiotemporal predictability of such hazards. Therefore, it is essential to research the preemptive prediction and mitigation of debris-flow hazards. For this purpose, this study developed an ANN model to predict the debris-flow volume based on 63 historical events. By considering the morphology, rainfall, and geology characteristics of the studied area in central South Korea, the data of 15 debris-flow predisposing factors were obtained. Among these data, four predisposing factors (watershed area, channel length, watershed relief, and rainfall data) were selected based on Pearson's correlation analysis to check for significant correlations with the debris-flow volume. To determine the best performing ANN model, a validation testing was carried out involving ten-fold cross-validation with MSE and R2 using both training and validation datasets, which were randomly split into a 7:3 ratio. The model performance validation results showed that an ANN model with two hidden neurons (4×2×1 architecture) had the highest R2 value (0.828) and the lowest MSE (0.022). In addition, in a comparative study with other existing regression models, the ANN model showed better results in terms of adjusted R2 value (0.911) using all datasets. Furthermore, 94% of the observed debris-flow volumes from the ANN model were within 1:2 and 2:1 lines of the predicted volumes. The results of this study have shown the potentiality of the developed ANN model to be a useful resource for decision-making and designing barriers in areas prone to debris-flows in South Korea.
•A prediction model for debris-flow volume based on an artificial neural network (ANN) is proposed and verified.•The systematic procedure of modeling an ANN model for predicting the debris-flow volume is described.•The developed ANN model was compared to other existing regression models.•The ANN model showed better results in terms of predicting the debris-flow volume than the existing regression models.
This article uses an integrated methodology based on a chi-squared automatic interaction detection (CHAID) model combined with analytic hierarchy process (AHP) for pair-wise comparison to assess ...medium-scale landslide susceptibility in a catchment in the Inje region of South Korea. An inventory of 3596 landslide locations was collected using remote sensing, and a random sample comprising 30% of these was used to validate the model. The remaining portion (70%) was processed by the nearest-neighbour index (NNI) technique and used for extracting the cluster patterns at each location. These data were used for model training purposes. Ten landslide-conditioning factors (independent variables) representing four main domains, namely (1) topology, (2) geology, (3) hydrology, and (4) land cover, were used to produce two landslide-susceptibility maps. The first landslide-susceptibility map (LSM1) was produced by overlaying the terminal nodes of the CHAID result tree. The second landslide-susceptibility map (LSM2) was produced using the overlay result of AHP pair-wise comparisons of CHAID terminal nodes. The prediction rate curve results were better with LSM2 (area under the prediction curve (AUC) = 0.80) than with LSM1 (AUC = 0.76). The results confirmed that the integrated hybrid model has superior prediction performance and reliability, and it is recommended for future use in medium-scale landslide-susceptibility mapping.
Evidential belief function (EBF) model was applied and validated for analysis of landslide susceptibility in the Pyungchang area of Korea using geographic information system. Areas of landslide ...occurrence in the study area were determined from the interpretation of aerial photographs and subsequent field surveys. Landslide locations were randomly allocated for landslide susceptibility map generation (70%) and validation (30%) purposes. Maps relevant to landslide occurrence (topography, geology, soil, and forest cover) were assembled in a spatial database, from which 17 landslide-related factors were extracted. The relationships between the observed landslide locations and these factors were identified and quantified using the EBF model. Three relationships were calculated: disbelief (Dis), uncertainty (Unc), and belief (Bel). The quantified relationships between each factor and landslide locations of each factor with known landslides were then used as factor ratings in an overlay analysis to create landslide susceptibility indices and maps. The most representative of the resulting susceptibility maps (the Bel map) was validated using the landslide data reserved for validation. The landslide susceptibility map demonstrates 85.96% accuracy. Thus, the EBF model was found to be effective in terms of prediction accuracy.
► Landslides locations were identified by aerial photograph and field surveys. ► Three independent relationships were calculated: disbelief, uncertainty and belief. ► The calculated independent relationships were integrated. ► The integrated belief map was converted into the landslide susceptibility map. ► The most representative of the resulting susceptibility maps was validated.
Artificial recharge of groundwater increases the water level in an aquifer, which can be used for water security in a drought-prone region. This study was conducted to identify the interval of ...injection wells in a small basin upstream of a watershed. For the pilot test, 11 injection wells were installed, in which individual and simultaneous injections were performed. The rates of the individual and simultaneous injections ranged from 0.49–38.13 and 0.04–11.48 m
3
/d, respectively. Simultaneous injection resulted in a reduced injection rate of approximately 4.4–95.4% compared to that of individual injection owing to the interference effect of the injection wells. Moreover, the hydraulic conductivity of each well and the radius of influence were used to analyze the interference effect during injection using the Thiem-Dupuit equation. The interference effect between injection wells was evaluated by increasing the space from 2 to 15 m at four recharge lines (total length: 340 m) within the study area, and the expected injection rate was calculated as the rates of 220.85–58.95 m
3
/d. On the other hand, construction cost for installing injection wells became higher at 2 m interval than at 15 m. Therefore, there was no significant increase in construction cost per 1-m
3
injection volume as well as decrease in total injection rate if the well interval was > 5 m and the optimum interval of injection well was suggested to be at least 5 m. Drought-prone areas are generally excluded from water-welfare benefits and are economically fragile; consequently, when developing an artificial recharge facility, injection wells should be designed considering the security of suitable amount of water with economic feasibility.
The middle Darriwilian carbon isotope excursion (MDICE) event is first documented from central eastern Korea (Taebaeksan Basin), the eastern part of the Sino-Korean Block, and is well correlated with ...global carbon isotope chemostratigraphy. The Korean MDICE record shows three broad positive peaks and complements records from the Middle Ordovician peri-Gondwanan epeiric seas showing incomplete records due to disconformity. This study reconstructed paleoceanographic conditions with nitrogen isotopic compositions and clay mineral compositions to understand the causes of carbon isotope excursions. The heavier excursion in nitrogen isotopic curve and abrupt increase of kaolinite in the early MDICE interval are interpreted as a result of epeiric sea denitrification associated with strong seawater stratification, and the main cause of those conditions was likely increased precipitation in the adjacent land. Subsequent sea-level rise caused an anti-estuarine circulation in the Taebaeksan sea and increased the organic carbon burial in the adjacent basin setting, which might have sustained the MDICE. The documentation of the MDICE event in this study supports the view that the MDICE occurred globally. This study provides not only information on the regional paleoceanographic conditions that occurred in the Middle Ordovician epeiric seas during the course of MDICE, but also reports that the MDICE event occurred as a response to seawater circulation associated with global sea-level rising in the Middle Ordovician.
•MDICE (Middle Darriwilian carbon isotope excursion) is gaining global recognition.•MDICE is reported for the first time in the Sino-Korean Block.•The causes of δ13C excursions were tracked with δ15N and clay mineral compositions.•MDICE is interpreted as an oceanographic event related to global sea-level rising.
Cyclic hydraulic fracturing, which employs cyclic injection with alternating high and low injection rates or pressurization, is suggested to assist in reducing induced seismicity. Our laboratory work ...demonstrates the impact of cyclic hydraulic fracturing on tensile-dominated fracturing of intact Pocheon granite core specimens. Cyclic injection of water reduces the breakdown pressure by up to ∼20% and the maximum acoustic emission amplitude is reduced by ∼14 dB on average. We observe hydraulic fractures in granite specimens through using computed tomography. Cyclic hydraulic fracturing creates complex fractures with more branches and smaller apertures compared with those created by continuous injection. The average injectivity of the fractured specimens by cyclic injection is smaller than the injectivity measured on specimens fractured by continuous injection.
The Neoproterozoic igneous rocks in the northern and southern Gyeonggi Massifs in the southern Korean Peninsula are important for the interpretation of the Neoproterozoic tectonic evolution of the ...Korean Peninsula and northeastern Asia. The Gonamsan and Chuncheon metabasites in the northern Gyeonggi Massif intruded in a within-plate tectonic setting at ca. 851–873 Ma and 888 Ma, respectively. The Nb/Yb ratios (7–23) of these metabasites represent enriched mid-ocean ridge basalt (E-MORB) to ocean island basalt (OIB) characteristics. Most zircons found within the Gonamsan metabasites have positive εHf(t) values and Paleoproterozoic to Mesoproterozoic isotopic model ages (TDM2). These metabasites have initial 87Sr/86Sr ratios that range between 0.7033 and 0.7058 and εNd(t) values of −0.68 to 5.02. These geochemical characteristics of these metabasites indicate that these rocks formed in a rift-related environment.
The Neoproterozoic metabasites from the Dangjin area in the southwestern Gyeonggi Massif can be subdivided into arc and rift types. The Dangjin arc-type metabasites intruded at ca. 820–833 Ma. These metabasites have Nb/Yb ratios of 4–7, Nb/U ratios of 3.58–27.5 and show an increase in Th/Nb ratios with increasing La/Sm ratios. Most zircons from these metabasites have negative εHf(t) values and Paleoproterozoic-Archean TDM2 ages, except one that has positive εHf(t) values and a Mesoproterozoic TDM2 age. Most these metabasites have initial 87Sr/86Sr ratios of 0.7048–0.7105 and negative εNd(t) values from −11.67 to −5.25. These geochemical characteristics indicate that the arc type Dangjin metabasites experienced crustal contamination during differentiation in an arc tectonic environment.
The rift-related Dangjin metabasites intruded at ca. 793 Ma in a similar manner to the Gonamsan and Chuncheon metabasites. The Nb/Yb ratios (8–11) of these metabasites are higher than those of the arc-type metabasites. These metabasites have lower initial 87Sr/86Sr ratios of 0.704 and higher εNd(t) values of 1.96 than the Dangjin arc-type metabasites. Together with the results of previous work, this study indicates that the tectonic setting of the Dangjin-Hongseong area was an arc during the period 820–900 Ma and then changed into a rift during the period 703–793 Ma.
The Neoproterozoic igneous rocks in the northern Gyeonggi Massif can be correlated with those formed in the within-plate tectonic setting in the southern and southeastern margins of the North China Craton during the period 830–930 Ma. On the other hand, the Neoproterozoic igneous rocks in the southwestern Gyeonggi Massif can be correlated to the Neoproterozoic arc- and rift-related igneous rocks in the northern margin of South China Craton, which intruded during 850–871 and 637–820 Ma, respectively.
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•Rift related events occurred in the northern Gyeonggi Massif (NGM) at 742–888 Ma•The arc-related igneous rocks intruded the southwestern GM (SGM) during 820–900 Ma•The SGM was intruded by rift-related igneous rocks at 703–793 Ma•The Neoproterozoic rocks in the NGM can be correlated with the North China Craton•The Neoproterozoic rocks in the SGM can be correlated with the South China Craton
StarCraft (Blizzard Entertainment, 1998) is a real-time strategy video game, placing the player in command of three extraterrestrial races fighting against each other for strategic control of ...resources, terrain, and power. Simon Dor examines the game’s unanticipated effect by delving into the history of the game and the two core competencies it encouraged: decoding and foreseeing. Although StarCraft was not designed as an e-sport, its role in developing foreseeing skills helped give rise to one of the earliest e-sport communities in South Korea. Apart from the game’s clear landmark status, StarCraft offers a unique insight into changes in gaming culture and, more broadly, the marketability and profit of previously niche areas of interest. The book places StarCraft in the history of real-time strategy games in the 1990s—Dune II, Command & Conquer, Age of Empires—in terms of visual style, narrative tropes, and control. It shows how design decisions, technological infrastructures, and a strong contribution from its gaming community through Battle.net and its campaign editor were necessary conditions for the flexibility it needed to grow its success. In exploring the fanatic clusters of competitive players who formed the first tournaments and professionalized gaming, StarCraft shows that the game was key to the transition towards foreseeing play and essential to competitive gaming and e-sports.
•Robust cost function is developed to train corrupted groundwater level data.•Cost function eliminates the need for cumbersome noise and outlier preprocessing.•Cost function can be effectively ...applied to data affected by external influences.
In the present study, a cost function is developed for the robust training of recurrent neural-network models using groundwater-level data that are corrupted by outliers and noise. The optimal cost function in this study utilizes least trimmed squares (LTS) with asymmetric weighting (AW) and the Whittaker smoother (WS), which have different outlier- or noise-rejecting mechanisms. The developed cost function is benchmarked with other cost functions in the training of a long short-term memory (LSTM) model using data from the Gangjin–Seongjeon and Pohang–Gibuk monitoring wells in South Korea, the results of which are then compared to the validation data. Based on comparisons of the validation results, it is confirmed that the optimal cost function is the most successful in rejecting the influence of outliers during the training process when applied to data from the Gangjin–Seongjeon monitoring well. It is also demonstrated that the estimation results based on this optimal cost function can effectively identify outliers in groundwater-level data. For the Pohang–Gibuk monitoring well data, the optimal cost function without AW exhibits superior regularizing performance by generating the lowest mean estimation error. Using this cost function, the influence of persistent noise is mostly canceled out, and the estimation results reflect the regular changes in the water table level of a shallow aquifer over time. The developed robust cost function can potentially be employed in many hydrogeological applications, such as the monitoring of groundwater resources, the prediction and analysis of water table levels, and the identification of changes in aquifer processes. The cost function is also expected to be useful for many other field applications in which the data are susceptible to external influences.
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