• Economic and Environmental Geology
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• v.54 no.6
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• pp.649-657
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• 2021

This paper aims to study the impact of natural disasters on per capita income in Vietnam both the short and long-term, specifically impact loss of income caused by the extreme drought 2013 for agriculture, forestry and fishery in Phu Yen Province, Central Vietnam. The study valued economic damage by applying the synthetic control method (SCM), which is a statistical method to evaluate the effect of an intervention (e.g. natural disasters) in different case studies. It estimates what would have happened to the treatment group if it had not received the treatment by constructing a weighted combination of control units (e.g. control provinces). The results showed that the 2013 drought caused a decrease in income per capita, mainly in the agriculture, forestry, and fishery sector in Phu Yen. The reduced income was estimated to be VND 160,000 (1 USD = 23,500 VND (2021)) for one person per month, accounting for 11% of total income per capita and continued to affect the income 6 years later. Therefore, authorities need to invest in preventive solutions such as early and accurate warnings to help people to be more proactive in disaster prevention.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.131-140
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• 2011

In this study, temporal variations of the Advanced Microwave Scanning Radiometer E (AMSR-E) soil moisture products were evaluated using ground based measurements from the Haenam flux monitoring network site for two years (2004 and 2006). Even if there were major comparison issues including spatial resolutions, AMSR-E soil moisture production showed a great potential to replicate temporal variability patterns with ground based measurements. Additional intensive validation efforts should be conducted at a variety of field conditions including vegetation type for better utilization of remotely sensed soil moisture and understanding of the land surface-atmosphere interactions in the view of hydrometeorology.

• Journal of Korea Water Resources Association
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• v.38 no.4 s.153
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• pp.293-300
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• 2005

This study analyzes hydrometeorologic changes after a dam construction, and develops a model related to estimating the geographical boundary hour far hydrometeorologic changes could happen due to a dam construction. The model is applied to several dams, namely Seomjin Dam, Soyang Dam, Andong Dam, and Chungju Dam. Throughout estimating the correlation between albedo and recycling coefficients, the result confirms that the land use changes by dam construction are the critical factor on the recycling of the water in the air. It is also shown that the geographical boundary is highly related to the surface area of a dam. Finally, this model is expected to be applied to estimate its boundary of hydrometeorologic changes by a new dam construction.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1333-1339
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• 2018

Recently, as disasters caused by weather such as heavy rains have increased, interests in forecasting weather and disasters using radars have been increasing, and related studies have also been actively performed. As the Ministry of Environment(ME) has established and operated a radar network on a national scale, utilization of radars has been emphasized. However, persons in charge and researchers, who want to use the data from radars need to understand characteristics of the radar data and are also experiencing a lot of trials and errors when converting and calibrating the radar data from Universal Format(UF) files. Hence, this study developed a Radar Display and Analysis Program(RaDAP) based on Graphic User Interface(GUI) using the Java Programming Language in order for UF-type radar data to be generated in an ASCII-formatted image file and text file. The developed program can derive desired radar rainfall data and minimize the time required to perform its analysis. Therefore, it is expected that this program will contribute to enhancing the utilization of radar data in various fields.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.69-78
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• 1999

In this paper, a neural network approach to forecast Korean regional precipitation is presented. We first analyze the characteristics of the conventional models for time series prediction, and then propose a new model and its learning method for the precipitation forecast. The proposed model is a layered network in which the outputs of a layer are buffered within a given period time and then fed fully connected to the upper layer. This study adopted the dual connections between two layers for the model. The network behavior and learning algorithm for the model are also described. The dual connection structure plays the role of the bias of the ordinary Multi-Layer Perceptron(MLP), and reflects the relationships among the features effectively. From these advantageous features, the model provides the learning efficiency in comparison with the FIR network, which is the most popular model for time series prediction. We have applied the model to the monthly and seasonal forecast of precipitation. The precipitation data and SST(Sea Surface Temperature) data for several decades are used as the learning pattern for the neural network predictor. The experimental results have shown the validity of the proposed model.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1151-1159
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• 2014

In this study, two global simple indices are used to investigate climate variability and change in observations. Land-Ocean Contrast (LOC) is an index of area-averaged surface temperature contrast between land and ocean. Meridional Temperature Gradient (MTG) is defined as the mean meridional temperature gradient in the Northern Hemisphere from mid to high latitude and sub-tropical zonal bands. These indices have direct or indirect effects on changing in atmospheric circulations and atmospheric moisture transport from north-south or east-west into East Asia (EA). In addition, warm season hydrometeorology in EA is highly associated with water supplies for coupled human and natural systems including drinking water, irrigation, hydropower generation as well as fisheries. Therefore, in this study, we developed an empirical separation approach for summer rainfall from typhoon and monsoon. An exploratory analysis was also conducted to identify the regional patterns of summer monsoon precipitation over the Korean peninsula within the context of changes in different types of temperature gradients. The results show significant and consistent changes in summer monsoon rainfall during the summer season (June-September) in South Korea.

• Korean Journal of Ecology and Environment
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• v.50 no.3
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• pp.337-354
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• 2017

Cyanobacteria Aphanizomenon population is widely distributed in the world, and well known as harmful algae by producing toxins and off-flavor materials, thus belonging to one of the taxa that became more interested in the field of limnoecology. In this study, the frequency, intensity, and duration of Aphanizomenon occurrence were increased with the abnormal drawdown of water level in the winter in Boryeong Reservoir, and the spatial and temporal characteristics of them are compared with each other in the perspective of hydrometeorology (1998 to 2017) and limnology (2010 to 2017). In Korea, Aphanizomenon flourished mainly in high temperature, and the appearance in the low temperature was rare in total five times. The harmful cyanobacteria Aphanizomenon was observed in the low temperature (December to February) in Boryeong Reservoir from 2014, and then reached a maximum value of $2,160cells\;mL^{-1}$ in January 2017. In addition, the period exceeding $1,000cells\;mL^{-1}$ at this time was more than 3 months. This was simultaneously associated with abnormal water level fluctuation in the low temperature ($<10^{\circ}C$). The large drawdown of water level in the winter season has the potential to promote or amplify the germination and development of harmful algae. Also, subsequent water quality and ecological impacts(e.g., algal toxins and off-flavor substances) need to be considered carefully.

• Atmosphere
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• v.16 no.2
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• pp.97-110
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• 2006

This study investigates the response of a typhoon model to the change of the sea surface temperature (SST) throughout the model integration. The SST change is parameterized as a formulae of which the magnitude is given as a function of not only the intensity and the size but the moving speed of tropical cyclone. The formulae is constructed by referring to many previous observational and numerical studies on the SST cooling with the passage of tropical cyclones. Since the parameterized cooling formulae is based on the mathematical expression, the resemblance between the prescribed SST cooling and the observed one during the period of the numerical experiment is not complete nor satisfactory. The agreements between the prescribed and the observed SST even over the swath of the typhoon passage differ from case to case. Numerical experiments are undertaken with and without prescribing the SST cooling. The results with the SST cooling do not show clear evidence in improving the track prediction compared to those of the without-experiments. SST cooling in the model shows its swath along the incomplete simulated track so that the magnitude and the distribution of the sea surface cooling does not resemble completely with the observed one. However, we have observed a little improvement in the intensity prediction in terms of the central pressure of the tropical cyclone in some cases. In case where the model without the SST treatment is not able to yield a correct prediction of the filling of the tropical cyclone especially in the decaying stage, the pulling effect given by the SST cooling alleviates the over-deepening of the model so that the central pressure approaches toward the observed value. However, the opposite case when the SST treatment makes the prediction worse may also be possible. In general when the sea surface temperature is reduced, the amount of the sensible and the latent heat from the ocean surface become also reduced, which results in the weakening of the storms comparing to the constant SST case. It turns out to be the case also in our experiments. The weakening is realized in the central pressure, maximum wind, horizontal temperature gradient, etc.

• Journal of Environmental Policy
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• v.4 no.1
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• pp.21-38
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• 2005

In this study, a model for analyzing the spatial effect of large dam reservoirs on local hydrometeorology was developed, and then actually applied to the Seomjingang Dam, Soyanggang Dam, Andong Dam, and Chungju Dam. The application included the analysis of land use using the satellite images to derive the change in albedo before and after the dam construction. Summarizing the modeling procedure and its application results are as follows. (1) The change in albedo was found to be closely related with the size of the dam, also the spatial limit of albedo change were estimated to be 10-20km for the Seomjingang Dam, 40km for the Soyanggang Dam, 20-30km for the Andong Dam, and 50km for the Chungju Dam. (2) The change in the coefficient of recycle (ratio of internal supply of moisture to the total available moisture) was found to be big within the narrow boundary of the. dam, but become smaller as the boundary becomes larger. (3) The correlation between the albedo and. coefficient of recycle was found high. Thus, it could be concluded that the change in land use due to dam construction has much effect on the moisture circulation structure. (4) The spatial range of hydrometeorogic effect was compared with the water surface area of dam reservoir. The result showed that the spatial range sensitively increased up to $50km^2$ of water surface area.