• Korean Journal of Ecology and Environment
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• v.37 no.3 s.108
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• pp.263-271
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• 2004

To collect the basic ecological information about the microbial food webs in eutrophic water system with different residence time, the monthly variation of bacterioplankon (bacteria and small-sized cyanobacteria) and nanoplankton (phytoplankton and protists) were examined from December 2000 to September 2001. Kyungan stream is shorter in resident time (ca.5.4 d) than Seokchon reservoir (ca.72 d), even though they showed the same pattern in precipitation. With the basic environments, we examined the biomass (standing crops and its carbon content) of each plankton collected from the surface water. Large-sized planktons flourished in the time of low temperature, while small planktons were in the time of the high temperature period. Especially, in the Kyungan stream with much disturbance by rainfall and outflow, high diversity showed in term of species and cell morphology, compared to that of Seokchon lake. The time-lag relationship remarkably showed between phytoplankton and bacteria in Seokchon reservoir, and between protists and bacteria in Kyungan stream, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.158-158
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• 2018

Drought is a recurrent natural hazard in Bangladesh. It has significant impacts on agriculture, environment, and society. Well-timed information on the onset, extent, intensity, duration, and impacts of drought can mitigate the potential drought-related losses. Thus, drought characteristics need to be explained in terms of frequency, severity, and duration. This paper aims to characterize the spatial and temporal pattern of meteorological drought using EDI and illustrated drought severity over Bangladesh. Twenty-seven (27) station-based daily rainfall data for the study period of 1981-2015 were used to calculate the EDI values over Bangladesh. The evaluation of EDI is conducted for 4 sub-regions over the country to confirm the historical drought record-developed at the regional scale. The finding shows that on average, the frequency of severe to extreme drought is approximately 0.7 events per year. As a result of the regional analysis, most of the recorded historical drought events were successfully detected during the study period. Additionally, the seasonal analysis showed that the extreme droughts were frequently hit in northwestern, middle portion of the eastern and small portion of central parts of Bangladesh during the Kharif(wet) and Rabi(dry) seasons. The severe drought was affected recurrently in the central and northern regions of the country during all cropping seasons. The study also points out that the northern, south-western and central regions in Bangladesh are comparatively vulnerable to both extreme and severe drought event. The study showed that EDI would be a useful tool to identify the drought-prone area and time and potentially applicable to the climate change-induced drought evolution monitoring at regional to the national level in Bangladesh. The outcome of the present study can be used in taking anticipatory strategies to mitigate the drought damages on agricultural production as well as human sufferings in drought-prone areas of Bangladesh.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.407-407
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• 2019

According to Asian Development Bank report Pakistan is among water scarce countries. Climate scenario on the basis IPCC fifth assessment report (AR5) revealed that annual mean temperature of Pakistan from year 2010-2019 was $17C^o$ which will rise up to $21C^o$ at the end of this century, similarly almost 10% decrease of annual rainfall is expected at the end of the century. It is a changing task in underdeveloped countries like Pakistan to meet the water demands of rapidly increasing population in a changing climate. While many studies have tackled scarcity and stream flow forecasting of the Upper Indus Basin (UIB) Pakistan, very few of them are related to socio-economic and climate change impact on sustainable water management of UIB. This study investigates the pattern of current and future surface water availability for various demand sites (e.g. domestic, agriculture and industrial) under different socio-economic and climate change scenarios in Upper Indus Basin (UIB) Pakistan for a period of 2010 to 2050. A state-of-the-art planning tool Water Evaluation and Planning (WEAP) is used to analyze the dynamics of current and future water demand. The stream flow data of five sub catchment (Astore, Gilgit, Hunza, Shigar and Shoyke) and entire UIB were calibrated and validated for the year of 2006 to 2011 using WEAP. The Nash Sutcliffe coefficient and coefficient of determination is achieved ranging from 0.63 to 0.92. The results indicate that unmet water demand is likely to increase severe threshold and the external driving forces e.g. socio-economic and climate change will create a gap between supply and demand of water.

• Korean Journal of Environmental Agriculture
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• v.40 no.4
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• pp.270-278
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• 2021

BACKGROUND: Horticultural plant growth under field and/or greenhouse conditions is affected by the climate changes (e.g., temperature, humidity, and rainfall). Therefore investigation of hydroponics on field horticultural crops is necessary for year-round production of the plants regardless of external environment changes under plant factory system with artificial light sources. METHODS AND RESULTS: Common sage (Salvia plebeia), nasturtium (Tropaeolum majus), and hooker chive (Allium hookeri) plants were hydroponically culturing in the plant factory with blue-red-white LEDs (Light-Emitting Diodes) and fluorescent lights (FLs). Leaf numbers of common sage under mixture LED and FL treatments were 134% and 98% greater, respectively than those in the greenhouse condition. In hooker chives, unfolded leaf numbers were 35% greater under the artificial lights and leaf elongation was inhibited by the conventional sunlight compared to the artificial light treatments. Absorption pattern of NO₃-N composition in hydroponic solution was not affected by the different light qualities. CONCLUSION(S): Plant factory system with different light qualities could be applied for fresh-leaf production of common sage, nasturtium, and hooker chive plants culturing under field and/or greenhouse. Controlled light qualities in the system resulted in significantly higher hydroponic growth of the plants comparing to conventional greenhouse condition in present.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.5
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• pp.1-10
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• 2019

Due to the climate change the drought had been occurring more frequently in recent two decades as compared to the previous years. The change in the pattern and frequency of the rainfall have a direct effect on the farming sector; therefore, the quantitative estimation of water supply is necessary for efficient agricultural water reservoir management. In past researches, there had been several studies conducted in estimation and evaluation of water supply based on the irrigational water requirement. However, some researches had shown significant differences between the theoretical and observed data based on this requirement. Thus, this study aims to propose an approach in estimating reservoir rate based on empirical method that utilized observed reservoir rate data. The result of these two methods in comparison with the previous one is seen to be more fitted for both R2 and RMSE with the observed reservoir rate. Among these procedures, the method that considers the drought year data shows more fitted outcomes. In addition, this new method was verified using 15-year (2002 to 2006) linear regression equation and then compare the preceeding 3-year (1999 to 2001) data to the theoretical method. The result using linear regression equation is also perceived to be more closely fitted to the observed reservoir rate data than the one based on theoretical irrigation water requirement. The new method developed in this research can therefore be used to provide more suitable supply data, and can contribute to effectively managing the reservoir operation in the country.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.33-44
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• 2019

Due to the recent climate change realization (timing, rainfall pattern changes), the flow regime is changing according to the watershed. The long-term change of flow regime is causing a significant change in structure and function of aquatic ecosystems. However, there is no analysis from the viewpoint of the aquatic ecosystem including flow rate alteration and ecological characteristics as well as the climate change connection in Korea yet. Therefore, We quantitatively assessed the impact of present-future flow regime alteration due to climate change on the Pseudopungtungia nigra habitat in the Mankyung river and floodplain area. As a result, it was confirmed that extreme hydrological conditions such as flood and drought are intensified in the future than the present. Especially, the changes of flow regime characteristics were clarified by comparing and analyzing the magnitude, frequency, duration, rate of change, and by linking flow regime characteristics with physical habitat analysis, it could be suggested that climate change would significantly increase the risk of future ecological changes.

• Journal of Korean Society on Water Environment
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• v.35 no.1
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• pp.28-34
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• 2019

This study analyzed the occurrence pattern of Dolichospermum (= Anabaena) in the Bukhan river from March 2012 to December 2014 in order to identify the genotypes of Dolichospermum. Furthermore, 16S rRNA were analyzed to identify the genotypes of Dolichospermum that occurred in 2015 which were then compared to the reference sequence deposited at NCBI. During this period, the occurrence of Dolichospermum was highly correlated to water temperature. In the year 2012 and 2013, Dolichospermum appeared in Lake Cheongpyeong (CP), Sambong (SB), and Lake Paldang (P2) between July and August. However, in 2014, it appeared in SB and P2, but not in CP. This reduction in appearance was attributed to the decreased inflow to Lake Uiam as a result of low rainfall in 2014 as compared to 2012. In July 2015, the Dolichospermum 16S rRNA genotype was confirmed in five locations; Lake Cheongpyeong (CP), Seojong (SJ), Songchon Sewage Treatment Plant (SC), Joan (P4), and Lake Paldang (PD). Anabaena crassa of spiral clone, A. planctonica of linear clone, and A. circinalis of spiral clone exhibited high genetic similarity with the reference sequence. The 16r RNA genotype showed approximately 3 % sequence variation between the locations and were more similar to each other in locations that were closer.

• 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 Society of Agricultural Engineers
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• v.66 no.1
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• pp.1-13
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• 2024

This study assessed the efficacy of improving the accuracy of reservoir water level prediction models by employing automated machine learning models and efficient cross-validation methods for time-series data. Considering the inherent complexity and non-linearity of time-series data related to reservoir water levels, we proposed an optimized approach for model selection and training. The performance of twelve models was evaluated for the Obong Reservoir in Gangneung, Gangwon Province, using the TPOT (Tree-based Pipeline Optimization Tool) and four cross-validation methods, which led to the determination of the optimal pipeline model. The pipeline model consisting of Extra Tree, Stacking Ridge Regression, and Simple Ridge Regression showed outstanding predictive performance for both training and test data, with an R² (Coefficient of determination) and NSE (Nash-Sutcliffe Efficiency) exceeding 0.93. On the other hand, for predictions of water levels 12 hours later, the pipeline model selected through time-series split cross-validation accurately captured the change pattern of time-series water level data during the test period, with an NSE exceeding 0.99. The methodology proposed in this study is expected to greatly contribute to the efficient generation of reservoir water level predictions in regions with high rainfall variability.

• Journal of Environmental Policy
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• v.9 no.2
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• pp.157-184
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• 2010

Global climate change is destroying the water circulation balance by changing rates of precipitation, recharge and discharge, and evapotranspiration. The Intergovernmental Panel on Climate Change (IPCC 2007) makes "changes in rainfall pattern due to climate system changes and consequent shortage of available water resource" a high priority as the weakest part among the effects of human environment caused by future climate changes. Groundwater, which occupies a considerable portion of the world's water resources, is related to climate change via surface water such as rivers, lakes, and marshes, and "direct" interactions, being indirectly affected through recharge. Therefore, in order to quantify the effects of climate change on groundwater resources, it is necessary to not only predict the main variables of climate change but to also accurately predict the underground rainfall recharge quantity. In this paper, the authors selected a relevant climate change scenario, In this context, the authors selected A1B from the Special Report on Emission Scenario (SRES) which is distributed at Korea Meteorological Administration. By using data on temperature, rainfall, soil, and land use, the groundwater recharge rate for the research area was estimated by period and embodied as geographic information system (GIS). In order to calculate the groundwater recharge quantity, Visual HELP3 was used as main model for groundwater recharge, and the physical properties of weather, temperature, and soil layers were used as main input data. General changes to water circulation due to climate change have already been predicted. In order to systematically solve problems associated with how the groundwater resource circulation system should be reflected in future policies pertaining to groundwater resources, it may be urgent to recalculate the groundwater recharge quantity and consequent quantity for using via prediction of climate change in Korea in the future and then reflection of the results. The space-time calculation of changes to the groundwater recharge quantity in the study area may serve as a foundation to present additional measures for the improved management of domestic groundwater resources.