Journal of the Korean Institute of Landscape Architecture
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v.49
no.6
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pp.27-36
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2021
At a time when the equitable use of urban parks is gradually emerging as a social issue, this study was initiated to expand the influence of urban parks by improving the quality of park services, thereby resolving areas not covered by urban park services. This study targeted the Hangang Park in Seoul, where the qualitative service of parks shows the greatest difference. The influence relationship between the qualitative services of the park and the user's sphere of influence, which indicates the distribution of park users, was proposed to assess the influence of improvements in the quality of service. As a research method, the top three districts and the bottom three districts were selected through the Han River Park user satisfaction survey conducted from 2017 to 2019, and a qualitative service evaluation was carried out. It was derived using the data acquired in September. Afterward, by performing a spatial autocorrelation analysis on the user's sphere of influence, additional verification of the user's sphere of influence was performed numerically and visually. As a result of the study, the user influence in the top three districts, with high-quality service, was stronger and wider than that of the lower three districts. It was confirmed that the quality of service of the park affects the user influence. This shows that to realize park equity, it is necessary to improve the quality of services through continuous management and improvement of individual parks and the creation of new parks. This study has significance in that it recognizes the limitations of research on park services from a supplier's point of view and evaluates the qualitative services of parks from the perspective of actual park users. We propose an alternative to deal with the lower the park deprivation index.
The dominant land use at the Seonakdong river watershed is paddy and forest areas and the Seonakdong river stands still. Thus, the water pollution in the Seonakdong river is becoming more serious for the non-point source. In this study, SWAT(Soil and Water Assessment Tool) model was evaluated for simulation of flow and water quality behaviors in Seonakdong river. To perform the calibration and verification of the SWAT model, the measurements of discharge and water quality were performed for the period from 2006 to 2007 at 5 gauging stations in Seonakdong river. The $R^2$ value for discharge and water quality were 0.86 and 0.70 respectively for calibration after the sensitive analysis. The $R^2$ value for discharge and water quality were 0.81 and 0.51 respectively for verification. The simulation results show that BOD value in the river tends to decrease after the opening of gates and the patterns of TN and TP concentrations are similar as that of BOD. The gate operators need to determine how to supply water in drought season for effective water quality improvement. This study shows that the SWAT model, which is capable of simulating hydrologic and water quality behaviors temporarily and spatially at watershed scale, could be used to get the gate operation rule for the water quality management in Seonakdong river.
Proceedings of the Korea Water Resources Association Conference
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2006.05a
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pp.2-11
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2006
In the processes of hydrological cycle, when precipitation reaches the ground surface, water may become surface runoff or infiltrate into soil and then possibly further percolate into groundwater aquifer. A part of the water is returned to the atmosphere through evaporation and transpiration. Soil moisture dynamics driven climate fluctuations plays a key role in the simulation of water transfer among ground surface, unsaturated zone and aquifer. In this study, a one-layer canopy and a four-layer soil representation is used for a coupled soil-vegetation modeling scheme. A non-zero hydraulic diffusivity between the deepest soil layer modeled and groundwater table is used to couple the numerical equations of soil moisture and groundwater dynamics. Simulation of runoff generation is based on the mechanism of both infiltration excess overland flow and saturation overland flow nested in a numerical model of soil moisture dynamics. Thus, a comprehensive hydrological model integrating canopy, soil zone and aquifer has been developed to evaluate water resources in the plain region of Huaihe River basin in East China and simulate water transfer among precipitation, surface water, soil moisture and groundwater. The newly developed model is capable of calculating hydrological components of surface runoff, evapotranpiration from soil and aquifer, and groundwater recharge from precipitation and discharge into rivers. Regional parameterization is made by using two approaches. One is to determine most parameters representing specific physical values on the basis of characterization of soil properties in unsaturated zone and aquifer, and vegetations. The other is to calibrate the remaining few parameters on the basis of comparison between measured and simulated streamflow and groundwater tables. The integrated modeling system was successfully used in the Linhuanji catchment of Huaihe plain region. Study results demonstrate that (1) on the average 14.2% of precipitation becomes surface runoff and baseflow during a ten-year period from 1986 to 1995 and this figure fluctuates between only 3.0% in drought years of 1986, 1988, 1993 and 1994 to 24.0% in wet year of 1991; (2) groundwater directly deriving from precipitation recharge is about 15.0% t of the precipitation amount, and (3) about half of the groundwater recharge flows into rivers and loses through evaporation.
As the infrastructures and populations are the condensed in the mega city, urban flood management becomes very important due to the severe loss of lives and properties. For the more accurate calculation of runoff from the urban catchment, hourly or even minute rainfall data have been utilized. However, the time steps of the measured or forecasted data under climate change scenarios are longer than hourly, which causes the difficulty on the application. In this study, daily rainfall data was disaggregated into hourly using the stochastic method. Based on the historical hourly precipitation data, Gram Schmidt orthonormalization process and K-Nearest Neighbor Resampling (KNNR) method were applied to disaggregate daily precipitation into hourly. This method was originally developed to disaggregate yearly runoff data into monthly. Precipitation data has smaller probability density than runoff data, therefore, rainfall patterns considering the previous and next days were proposed as 7 different types. Disaggregated rainfall was resampled from the only same rainfall patterns to improve applicability. The proposed method was applied rainfall data observed at Seoul weather station where has 52 years hourly rainfall data and the disaggregated hourly data were compared to the measured data. The proposed method might be applied to disaggregate the climate change scenarios.
The purpose of this study is to analyze the possibility of future droughts by calculating the Standardized Groundwater level Index(SGI) after predicting groundwater level using Long Short Term Memory (LSTM) model. The groundwater level of the Kumho River basin was predicted for the next three years by using the LSTM model, and it was validated through RMSE after learning with observation data except the last three years. The temporal SGI was calculated by using the prediction data and the observation data. The calculated SGI was interpolated within the study area, and the spatial SGI was calculated as the average value for each catchment using the interpolated SGI. The possibility of spatio-temporal drought was analyzed using calculated spatio-temporal SGI. It is confirmed that there is a spatio-temporal difference in the possibility of drought. Through the improvement of deep learning model and diversification of validation method, it is expected to obtain more reliable prediction results and the expansion of study area can be used to respond to drought nationwide, and furthermore it can provide important information for future water resource management.
Yun, Jin I.;Kim, Soo-Ock;Kim, Jin-Hee;Kim, Dae-Jun
Korean Journal of Agricultural and Forest Meteorology
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v.15
no.4
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pp.320-331
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2013
The National Center for AgroMeteorology (NCAM) has designed a risk management solution for individual farms threatened by the climate change and variability. The new service produces weather risk indices tailored to the crop species and phenology by using site-specific weather forecasts and analysis derived from digital products of the Korea Meteorological Administration (KMA). If the risk is high enough to cause any damage to the crops, agrometeorological warnings or watches are delivered to the growers' cellular phones with relevant countermeasures to help protect their crops against the potential damage. Core techniques such as scaling down of weather data to individual farm level and the crop specific risk assessment for operational service were developed and integrated into a cloud based service system. The system was employed and implemented in a rural catchment of 50 $km^2$ with diverse agricultural activities and 230 volunteer farmers are participating in this project to get the user-specific weather information from and to feed their evaluations back to NCAM. The experience obtained through this project will be useful in planning and developing the nation-wide early warning service in agricultural sector exposed to the climate and weather extremes under climate change and climate variability.
SWMM (Storm Water Management Model) has been widely used in the world as a typical model for flood runoff analysis of urban areas. However, the calibration of the model is difficult, which is an obstacle to easy application. The purpose of the study is to develop an automatic calibration module of the SWMM linked with SCE-UA (Shuffled Complex Evolution-University of Arizona) algorithm. Generally, various objective functions may produce different optimization results for an optimization problem. Thus, five single objective functions were applied and the most appropriate one was selected. In addition to the objective function, another objective function was used to reduce peak flow error in flood simulation. They form a multiple objective function, and the optimization problem was solved by determination of Pareto optima. The automatic calibration module was applied to the flood simulation on the catchment of the Guro 1 detention reservoir and pump station. The automatic calibration results by the multiple objective function were more excellent than the results by the single objective function for model assessment criteria including error of peak flow and ratio of volume between observed and calculated flow. Also, the verification results of the model calibrated by the multiple objective function were reliable. The program could be used in various flood runoff analysis in urban areas.
Journal of Korean Society of Disaster and Security
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v.14
no.4
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pp.9-15
/
2021
The frequency of flash floods in mountainous areas is increasing due to the abnormal weather that occurs increasingly in the recent, and it causes human and material damages is increasing. Various plans for disaster mitigation have been established, but artificial plans such as raising embankment and dredging operation are inappropriate for valleys and rivers in national parks that prioritize nature protection. In this study, flood risk assessment was conducted for Gyeryongsan National Park in Korea using the WMS (Watershed Modeling System)which is rainfall runoff model for valleys and rivers in the catchment. As the result, it was simulated that it is flooding in three sub-catchments (Jusukgol, Sutonggol, Dinghaksa) of a total in Gyeryongsan National Park when rainfall over the 50 years return period occurs, and it was confirmed that the risk of trails and facilities what visitors are using was high. The risk of trails in national parks was quantitatively presented through the results of this study, and we intend to present the safe management guidelines of national parks in the future.
Understanding the characteristics of reservoir water quality is fundamental in reservoir ecosystem management. The water quality of reservoirs is affected by various factors including hydro-morphology of reservoirs, land use/cover, and human activities in their catchments. In this study, we classified 83 major reservoirs in South Korea based on nine physicochemical factors (pH, dissolved oxygen, chemical oxygen demand, total suspended solid, total nitrogen, total phosphorus, total organic carbon, electric conductivity, and chlorophyll-a) measured for five years (2015~2019). Study reservoirs were classified into five main clusters through hierarchical cluster analysis. Each cluster reflected differences in the water quality of reservoirs as well as hydromorphological variables such as elevation, catchment area, full water level, and full storage. In particular, water quality condition was low at a low elevation with large reservoirs representing cluster I. In the comparison of eutrophication status in major reservoirs in South Korea using the Korean trophic state index, in some reservoirs including cluster IV composed of lagoons, the eutrophication was improved compared to 2004~2008. However, eutrophication status has been more impaired in most agricultural reservoirs in clusters I, III, and V than past. Therefore, more attention is needed to improve the water quality of these reservoirs.
Due to the growing concern over forecasting extreme weather events such as droughts caused by climate change, there has been a rising interest in seasonal meteorological forecasts that offer ensemble predictions for the upcoming seven months. Nonetheless, limited research has been conducted in South Korea, particularly in assessing their effectiveness at the catchment-scale. In this study, we assessed the accuracy of ECMWF's seasonal forecasts (including precipitation, temperature, and evapotranspiration) for the period of 2011 to 2020. We focused on 12 multi-purpose reservoir catchments and compared the forecasts to climatology data. Continuous Ranked Probability Skill Score method is adopted to assess the forecast skill, and the linear scaling method was applied to evaluate its impact. The results showed that while the seasonal meteorological forecasts have similar skill to climatology for one month ahead, the skill decreased significantly as the forecast lead time increased. Compared to the climatology, better results were obtained in the Wet season than the Dry season. In particular, during the Wet seasons of the dry years (2015, 2017), the seasonal meteorological forecasts showed the highest skill for all lead times.
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