Specific survey objectives often cannot be met using only one geophysical method, as each method's results are influenced by the specific physical properties of subsurface materials. In particular, areas susceptible to geological hazards require investigation using more than one method in order to reduce risks to life and property. Instead of analyzing the results from each method separately, this work develops a four-quadrant criterion for classifying areas of levees as safe or weak. The assessment is based on statistically determined thresholds of seismic velocity (P-wave velocity from seismic refraction and S-wave velocity from multichannel analysis of surface waves) and electrical resistivity. Thresholds are determined by subtracting the standard deviation from the mean during performance testing of this correlation technique applied to model data of four horizontal and inclined fracture zones. Compared with results from the crossplot of resistivity and P-wave velocity, crossplot analysis using resistivity and S-wave velocity data provides more reliable information on the soil type, ground stiffness, and lithological characteristics of the levee system. A loose and sandy zone (represented by low S-wave velocity and high resistivity) falling within the second quadrant is interpreted to be a weak zone. This interpretation is well supported by the N values from standard penetrating test for the central core.
Hakyung Kwon;Jae Ah Choi;Moon Young Kim;Suk-Ha Lee
Proceedings of the Korean Society of Crop Science Conference
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2022.10a
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pp.25-25
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2022
Drought becomes frequent and severe because of continuous global warming, leading to a significant loss of crop yield. In soybean (Glycine max [L.]), most of quantitative trait loci (QTLs) analyses for drought tolerance have conducted by investigating yield changes under water-restricted conditions at the reproductive stages. More recently, the necessity of QTL studies to use physiological indices responding to drought at the early growth stages besides the reproductive ones has arisen due to the unpredictable and prevalent occurrence of drought throughout the soybean growing season. In this study, we thus identified QTLs conferring wilting scores and moisture contents of soybean subjected to drought stress in the early vegetative stage using an recombinant inbred line (RIL) population derived from a cross between Taekwang (drought-sensitive) and SS2-2 (drought-tolerant). For the two traits, the same major QTL was located on chromosome 10, accounting for up to 11.5% of phenotypic variance explained with LOD score of 12.5. This QTL overlaps with a reported QTL for the limited transpiration trait in soybean and harbors an ortholog of the Arabidopsis ABA and drought-induced RING-D UF1117 gene. Meanwhile, one of important features of plant drought tolerance is their ability to limit transpiration rates under high vapor pressure deficiency in response to mitigate water loss. However, monitoring their transpiration rates is time-consuming and laborious. Therefore, only a few population-level studies regarding transpiration rates under the drought condition have been reported so far. Via employing an Arduino-based platform, for the reasons addressed, we are measuring and recording total pot weights of soybean plants every hour from the 1st day after water restriction to the days when the half of the RILs exhibited permanent tissue damage in at least one trifoliate. Gradual decrease in moisture of soil in pots as time passes refers increase in the severity of drought stress. By tracking changes in the total pot weights of soybean plants, we will infer transpiration rates of the mapping parents and their RILs according to different levels of VPD and drought stress. The profile of transpiration rates from different levels of severity in the stresses facilitates a better understanding of relationship between transpiration-related features, such as limited maximum transpiration rates, to water saving performances, as well as those to other drought-responsive phenotypes. Our findings will provide primary insights on drought tolerance mechanisms in soybean and useful resources for improvement of soybean varieties tolerant to drought stress.
Natural radionuclides in groundwater in the Danyang area were investigated to characterize the behaviors of uranium and radon with respect to lithology and physico-chemical components, which can aid our understanding of their occurrence, properties, and origins. To this end, a total of 100 groundwater samples were collected and analyzed, and radionuclide levels were used to construct detailed concentration maps. The water type of the groundwater, assessed using a Piper diagram, is mainly Ca-Na-$HCO_3$. The concentrations of uranium range from 0.02 to $251.0{\mu}g/L$ (average, $3.85{\mu}g/L$) and only 1% exceed USEPA's MCL (Maximum Contaminant Level). Uranium is enriched in groundwaters of Cretaceous granites and Precambrian metamorphic rocks, whereas it is depleted in groundwaters of sedimentary rocks. The concentrations of radon range from 13 to 28,470 pCi/L (average, 2397 pCi/L). Only 15% of the samples exceed AMCL (Alternative Maximum Contaminant Level) of 4000 pCi/L. The radon concentration is highest in groundwater of Cretaceous granites and lowest in groundwater of sedimentary rocks. In conclusion, the distribution and occurrence of radionuclides are intimately related to the basic geological characteristics of the rocks in which the radiogenic minerals are primarily contained. The behavior of uranium is only weakly related to that of radon (correlation coefficient = 0.15). There are also weak correlations between radionuclides and the main chemical components, pH, EC, Eh, and well depth. Of note, the correlation coefficient between radon and $SiO_2$ is 0.68, and that between radon and $HCO_3$ is -0.48. Factor analysis shows that radionuclides behave somewhat independently of each other because there are no significant factors that control the behavior of chemical components as well as radionuclides. The detailed concentration maps during this study will be used to establish useful database of radionuclide distribution and geological properties throughout Korea.
A field technique for assessing the transmissive fractures in an aquifer was applied to a fractured rock formation in Youngchun area Korea. Geological mapping and detailed acoustic borehole teleview(BHTV) logging were performed to obtain information about the fractures. The study area consists predominantly of two types of fractures. The fracture sets of low angle partings such as bedding and sheeting plains have strike N70-80$^{\circ}$W, 25$^{\circ}$-30$^{\circ}$SW and N3S$^{\circ}$W, 12$^{\circ}$NE, respectively. In areas of high fractures, on the other hand, the major fracture sets show strike N80$^{\circ}$W and dip 70$^{\circ}$-85$^{\circ}$SW, N10$^{\circ}$E.85$^{\circ}$SE in sedimentry rocks, N40-50$^{\circ}$E.85$^{\circ}$SE/85$^{\circ}$NE, N70$^{\circ}$E.80$^{\circ}$SE, and N7$^{\circ}$-75$^{\circ}$W.80$^{\circ}$SW in granites and volcanic rocks. Injection tests have been performed to identify discrete production zones and quantify the vertical distribution of hydraulic conductivity. The calculated hydraulic conductivities range from 3.363E-10 to 2.731E-6, showing that the difference between maximum and minimum value is four order of magnitude. Dominant section in hydraulic conductivity is extensively fractured. Geophysical logging was carried out to clarify characterization of the distribution of fracture zones. Transmissive fractures were evaluated through the comparison of the results obtained by each method. The temperature logs appeared to be a good indicator that can distinguish a high transmissive fractures from a common fractures in hydraulic conductivity. In numerous cases, evidence of fluid movement was amplified in the temperature gradient log. The fracture sets of N70-80$^{\circ}$W.60-85$^{\circ}$NE/SW N75-80$^{\circ}$W.25-30$^{\circ}$SW, N50-64$^{\circ}$W.60-85$^{\circ}$NE, N35-45$^{\circ}$E.65-75$^{\circ}$SE, and N65-72$^{\circ}$E.80$^{\circ}$SE/60$^{\circ}$NW were idenfied as a distinct transmissive fractures through the results of each tests.
The liquefaction phenomenon that occurred during the Pohang earthquake (ML=5.4) brought new awareness to the people about the risk of liquefaction caused by the earthquake. Liquefaction hazard maps with 2 km grid made in 2014 used more than 100,000 borehole data for the whole country, and regions without soil investigation data were produced using interpolation. In the mapping of macro liquefaction hazard for the whole country, the site amplification effect and the ground water level 0 m were considered. Recently, the Ministry of Public Administration and Security (2018) published a new site classification method and amplification coefficient of the common standard for seismic design. Therefore, it is necessary to rewrite the liquefaction hazard map reflecting the revised amplification coefficient. In this study, the results of site classification according to the average shear wave velocity in soils before and after revision were compared in the whole country. Also, liquefaction assessment results were compared in Gangseo-gu, Busan. At this time, two ground accelerations corresponding to the 500 and 1,000 years of return period and two ground water table, 5 m for the average condition and 0 m the extreme condition were applied. In the drawing of liquefaction hazard map, a 500 m grid was applied to secure a resolution higher than the previous 2 km grid. As a result, the ground conditions that were classified as SC and SD grounds based on the existing site classification standard were reclassified as S2, S3, and S4 through the revised site classification standard. Also, the result of the Liquefaction assessments with a return period of 500 years and 1,000 years resulted in a relatively overestimation of the LPI applied with the ground amplification factor before revision. And the results of this study have a great influence on the liquefaction assessment, which is the basis of the creation of the regional liquefaction hazard map using the amplification factor.
The occurrence, distribution, and hydrogeochemical characteristics of uranium and radon in groundwater within different lithologies in Gyeongnam and Gyeongbuk provinces were investigated. A total of 201 groundwater samples from sedimentary rocks taking a large portion of the geology and from igneous rocks taking a small portion of the geology were analyzed and examined using factor analysis. Their radionuclide levels were used to construct detailed concentration maps. The groundwater types, defined using a Piper diagram, are mainly Ca-$HCO_3$ with less Na-$HCO_3$. Among the samples, one site exceeds $30{\mu}g/L$ of uranium (i.e., the maximum contaminant level of the USEPA) and three sites exceed 4,000 pCi/L of radon (i.e., the alternative maximum contaminant level). No samples were found to exceed the 15 pCi/L level of gross alpha or the 5 pCi/L level of radium. The concentration of uranium ranges from 0.02 to $53.7{\mu}g/L$, with a mean of $1.56{\mu}g/L$, a median of $0.47{\mu}g/L$, and a standard deviation of $4.3{\mu}g/L$. The mean concentrations of uranium for the different geological units increase in the following order: Shindong Group, Granites, Hayang Group, Yucheon Group, and Tertiary sedimentary rocks. The concentration of radon ranges from 2 to 8,740 pCi/L, with an mean of 754 pCi/L, a median of 510 pCi/L, and a standard deviation of 907 pCi/L. The mean radon concentrations for the investigated geological units increase in the following order: Granites, Yucheon Group, Tertiary sedimentary rocks, Hayang Group and Shindong Group. According to the factor analysis for each geological unit, uranium and radon behave independently of each other with no specific correlation. However, radionuclides show close relationships with some components. Regional investigations of radionuclides throughout the country require an integrated approach that considers the main lithological units as well as administrative districts.
Korean Journal of Agricultural and Forest Meteorology
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v.8
no.2
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pp.86-96
/
2006
Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.
Rhizoctonia solani [Thanatephorus cucumeris (frank) Donk], one of the major soil-borne plant pathogens with world-wide distribution, can cause great damages on various crops. In Korea, sheath blight on rice caused by this pathogen is the major concern, and active studies on this pathogen have been performed. However, most of these studies were concerned with pathogenicity of the isolates instead of molecular analyses of different AGs of R. solani. Therefore, in this study, thirty isolates of Rhizoctonia solani collected from various sources were used for the analyses of genetic relationships among themselves and for the rapid anastomosis grouping with RAPD method. As a result, thirty isolates of known and unknown AGs were grouped into five subgroups and each group included AG-1, AG-2, AG-3, AG-4, and AG-5. RS-1 isolate was found to be closely related to AG-5. Isolates RS-4, RS-14, RS-17, and RS-16 were found to be closely related to AG-2-2(III B). Isolate RS-13 was closely related to AG-4, isolates RS-8 and RS-10 were closely related to AG-1(I B), and isolates RS-7 and RS-21 were closely related to AG-2-2(IV). Isolate RS-19 was closely related to AG-1(I C), and isolates RS-3, RS-5, RS-18, RS-6, and RS-15 were found to be closely related to AG-1.
Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.
This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.
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