• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.9-24
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• 2022

Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• Journal of the Korean Geotechnical Society
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• v.35 no.10
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• pp.33-45
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• 2019

In this study, in order to recycle a large amount of rocks and weathered mudstones produced by civil engineering projects such as railways and highways, as materials for roadbeds or embankment materials, circumferential specimens with a diameter of 5 cm and a height of 10 cm were made. A mudstone that weathered rapidly during rainfall was collected from Pohang construction sites. The weathered mudstone passed through a 2 mm sieve. It was prepared with the cement ratio, the sand ratio, curing condition and curing days. Three specimens were prepared according to each condition and then the unconfined compressive test, durability test and SEM analysis were performed to evaluate the engineering properties of the cemented soil. In the case of 28 days cured specimen, the strength of under-water cured specimens was 32-55% and the durability index was about 15% higher than air cured specimens. In addition, when the CR increased from 8% to 16%, the unconfined compressive strength (UCS) of pure mudstone cemented soil under water increased by about 1.6 times and the durability index increased by about 1.9 times. When the SR increased from 0% to 50%, the UCS of the specimen with SR = 10% was slightly less than or equal to specimen with SR = 0%. Then, as the SR became 30-50%, the UCS increased up to 51%. Unlike the UCS, the durability index increased continuously as the SR increased. As a result of SEM analysis, when SR was 50% rather than SR = 0%, the contact between sand particles increased and they were connected to each other. Such contact between these particles resulted in the increase of strength.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.3
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• pp.161-170
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• 2013

Spatio-temporal distribution of soil moisture was studied to improve understanding of hydrological processes at hillslope scale. Using field measurements for three designated periods during the spring, summer and autumn seasons in 2010 obtained from Beomryunsa hillslope located at the Sulmachun watershed, correlation analysis was performed between soil moisture measurements and 18 different terrain attributes (e.g., curvatures and topographic index). The results of correlation analysis demonstrated distinct seasonal variation features of soil moisture in different depths with different terrain attributes and rainfall amount. The relationship between predicted flow lines and distribution of the soil moisture provided appropriate model structures and terrain indices.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.83-90
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• 2023

Due to climate change, the occurrence of abnormal rainfall is increasing, and the intensity and scale of damage caused by heavy rain are increasing every year. In addition, as the frequency of heavy rains becomes more frequent, heavy rains often occur continuously, resulting in large flooding damage that has never been seen before in urban area. When near rivers and coastal areas are impermeable areas, the maximum flow increases rapidly as the rainfall intensity increases, so a comprehensive flood risk evaluation is needed considering the characteristics of the basin. In this study, the flood inundation risk evaluation was analyzed by giving scores on evaluation factors as a measure to prevent inundation in subway stations. Through the flood inundation risk evaluation process considering the comprehensive evaluation index, the flood risk evaluation was conducted on five urban railway stations with a large amount of traffic and floating population that had been inundated in the past. It is judged that by comprehensively analyzing this and establishing a inundation risk grade (grade 1 to 4) to establish a flood measure suitable for the risk grade.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.101-101
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• 2022

In recent years, due to climate change, the livestock industry has become more interested in the production of forage crops. In Korea, more than 74% of forage crops are cultivated in winter rice fields. In particular, Italian ryegrass (IRG) is depends on imports for more than 70% of its seeds. In generally, the IRG rapeseed cultivation method involves sowing from early October to mid-October by drill sowing seeding or spot seedling. However, the sowing period is delayed due to frequent rainfall during. And, same period require a lot of seeds. However, raising seedlings and transplanted IRG will overcome weather conditions and reduce the amount of seeds. This study was intended to be applied to the domestic IRG seed industry in the future through growth and quantity evaluation according to transplant time and planting density for the production of good quality IRG seeds in rice paddy fields. In this study, transplanting time (October 20, October 30, November 10) and planting density (50, 70, and 80) were cultivated at the National Institute of Crop Science in 2021. The amount of fertilizer applied was adjusted to (N-P₂O₅-K₂O) 4.5-12-12 (kg/10a), and then 2.2(kg/10a) of nitrogen was added each year. For the growth survey, leaf area, canopy coverage, plant length, and seed yield were investigated. Along with the transplanting time, the plant length was higher on October 20 than on October 30 and November 10. On the other hand, leaf area index changes differed depending on the transplanting time and planting density, and were particularly high on October 20, 80 density and 70 density, but similar on October 30 and November 10. 1000 seed weight showed no difference with transplanting time and planting density. On the other hand, the seed yield was 215(kg/10a) for 80 density on October 20, 211(kg/10a) for 70 density, 118(kg/10a) for 50 density, and 80 density for October 30 and November 10. and 70 density did not differ. On the other hand, the 50 density on October 30 and November 10 were 164(kg/10a) and 147(kg/10a) respectively. As can be seen from this study, the earlier the transplant, the higher the seed yield. However, the 50 density was reduced in yield compared to the 70 density and 80 density.

• Journal of the Korean earth science society
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• v.43 no.3
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• pp.367-385
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• 2022

This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5417-5422
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• 2013

This research was performed in order to improve the goodness of fit of paddy rice production forecasting using MODIS images and to find out appropriate explanatory variables in the forecasting model. The aim of this paper is to review the use of satellite images for the survey of paddy rice production in Korea. Many developed countries, including the United States, Australia, and Japan, have been using satellite images to produce agricultural statistics such as crop production, cultivated acreage, etc. The survey accuracy of crop production by using satellite images, however, is not satisfied in practical use. In this paper, we reviewed several methods to increase the survey accuracy of rice production statistics, gained from satellite images. Rice was selected for this study because its cultivated area and production amount could be more easily identified than other crops by using satellite images. The MODIS images were used because they involved more appropriate images to estimate and analyze rice production. This study estimated yield functions by using the NDVIs, gained from paddy rice yields and annual average isothermal lines, and the meteorological variables such as sunshine hours, rainfall, and temperature during ripening stage. As a result of yield function estimation, the goodness of fit(R-squared) for the models was shown from 0.768 to 0.891. In this study, it is noteworthy academically and practically that vegetation index(NDVIs) identified by annual average isothermal lines and meteorological variables are very useful for estimating yield functions.

• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.163-174
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• 2017

This study developed the prototype of the system and implemented its main functions, which is the intelligent integrated agricultural water management information system and service (IaWAMISS). The developed system was designed to be able to collect, process and analyze the agricultural water information of spatially dispersed reservoirs in whole country and spatial geographic information distributed in various systems of other organizations. The system, IaWAMISS, is also possible to provide the reproduced information services in each reservoir and space units, such as agricultural water demand and supply analysis and drought prediction, to the people, experts, and policy makers. This study defined the 6 step modules to develop the system, which are to design the components of intelligent integrated information system, to derive the utilization contents of existing systems, to design the new development elements for IaWAMISS, to design the reservoir information system can be used by managers of city and county, to designate the monitoring reservoirs managed by city and county, and finally to prepare the sharing system between organizations with the existing information systems. In order to implement the prototype of the system, this study shows the results for three important functions of the system: spatial integration of reservoirs' information, data link integration between the existing systems, and intelligent analysis program development to assist decision support for agricultural water management. For the spatial integration with the reservoir water information of the Korea Rural Community Corporation, this study get IaWAMISS to receive the real-time reservoir storage information from the measurement facility installed in the municipal management reservoir. The data link integration connecting databases of the existing systems, was implemented by integrating the meteorological information of the Korea Meteorological Administration with IaWAMISS, so that the rainfall forecast data could be derived and used. For the implementation of the intelligent analysis program, this study also showed the results of analysis and prediction of agricultural water demand and supply amount, estimation of Palmer drought index, analysis of flood risk area in typhoon course region, and analysis of the storage status of reservoirs related to each storm. This study confirmed the possibility and efficiency of an useful system development through the prototype design and implementation of IaWAMISS. By solving the preliminary 6 step modules presented in this study, it is possible not only to efficiently manage water by spatial unit, but also to provide the service of information and to enhance the relevant policy and national understanding to the people.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1247-1260
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• 2018

This study investigated the effect of arctic oscillation by analyzing the cross-correlation characteristics between the arctic oscillation index (AOI) and the number of typhoons occurred in the North Pacific, the number of typhoons affecting South Korea, total rainfall amount and number of rainy days during the monsoon season in South Korea. For this analysis, the monthly AOI data were transformed into the average data about January and seasonal AOI data representing winter, spring, fall and winter. The typhoon data and monsoon data were all those collected annually. The data period for this analysis was determined to be from 1961 to 2016 by considering the data available. Based on this analysis, it was found that the arctic oscillation has a weak but statistically significant effect on the monsoon characteristics of South Korea. However, the level of effect was not consistent over the data period but varied significantly periodically. For example, the cross-correlation coefficient derived for the recent 10 years was estimated to be higher than 0.8, but was simply insignificant during the 30 years before the last decade. The overall effect of arctic oscillation on the occurrence of typhoon was found to be statistically insignificant, but was also fluctuating periodically to show somewhat significant effect. Finally, it should be mentioned that the effect of arctic oscillation on the typhoon and monsoon had been changing by turns from 1960s to 2000s. However, in the 2010s, it happened that the effect of arctic oscillation has become significant on both typhoon and monsoon in South Korea.