• Journal of The Korean Society of Agricultural Engineers
• /
• v.65 no.5
• /
• pp.25-35
• /
• 2023

The estuary reservoir is a major source of agricultural water in Korea; for effective and sustainable water resource management of the estuary reservoir, it is crucial to comprehensively consider various water resource factors, including water supply, flood, and pollutant management, and analyze future runoff changes in consideration of environmental changes such as climate change. The objective of this study is to estimate the impact of future climate change on the runoff characteristics of an estuary reservoir watershed. Climate data on future Shared Socioeconomic Pathway (SSP) scenarios were derived from two Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 6 (CMIP6). The Hydrological Simulation Program-Fortran (HSPF) was used to simulate past and future long-term runoff of the Ganwol estuary reservoir watershed. The findings showed that as the impact of climate change intensified, the average annual runoff in the future period was higher in the order of SSP5, SSP3, SSP1, and SSP2, and the ratio of runoff in July decreased while the ratio of runoff in October increased. Moreover, in terms of river flow regime, the SSP2 scenario was found to be the most advantageous and the SSP3 scenario was the most disadvantageous. The findings of this study can be used as basic data for developing sustainable water resource management plans and can be applied to estuary reservoir models to predict future environmental changes in estuary reservoirs.

• Journal of Soil and Groundwater Environment
• /
• v.13 no.5
• /
• pp.20-32
• /
• 2008

Runoff characteristics of the Oedocheon in Jeju island were investigated using the long-term stream stage monitoring data. At the Cheonah valley in the upstream area and Oedocheon downstream, annual runoff occurred 21 and 12 times, respectively, and their average runoff periods were 21 days and 12 days, respectively. Stream stage response time to rainfall was 4 hours, and storm-water transfer from the upstream, Cheonah valley, to the Oedocheon downstream took about 2 hours. The stream discharge measurements had been carried out from Feb. 2004 to Jul. 2005, and showed that normal discharge of the Oedocheon was 0.39 $m^3$/sec in average. Stage-discharge curves were developed to estimate base flow (normal discharge) and (direct) surface runoff. The base flow separations by a numerical filtering technique illustrated that annual surface runoff and base flow accounted respectively for 31.8${\sim}$36.5%, 63.5${\sim}$68.2% of the total stream discharge.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2007.05a
• /
• pp.15-21
• /
• 2007

Due to a decreasing tendency of river runoff in the Laohahe River basin in North China, quantitative analysis was made with the aid of the conceptual Xinanjiang model under the background of nature climate variability as well as human-induced climate change according to the long-term observational hydrometeorological data. In the past, the human effect on surface water resources was estimated by investigating the impact of human activities on each item in the equation of water balance, so as to calculate water quantity of each item in the original natural status. It seems to be clear conceptually. It is appropriate just for the case of direct impact, such as water transfer from one basin to another, water storage by various scales of hydraulic projects, besides a huge amount of investigation and indeterminate statistics data when applied in practice. It is difficult for us to compute directly water consumption due to the implementation of measures for soil conservation, the improvement of farming techniques in agriculture, the growth of population in towns and villages, and the change of socioeconomic structure. In view of such situation, the Xinanjiang model was used to separate human impact from the climatic impact on water resources. Quantitatively human activity made river runoff decrease by 1.02, 50.67, 58.06 mm in 1960's, 1970's, 1980's, respectively, while by 97.2 mm in 1990's in the sense of annual average in the Laohahe River basin.

• Journal of Korean Society of Forest Science
• /
• v.99 no.4
• /
• pp.559-567
• /
• 2010

This study was conducted to investigate the hydrological characteristics of groundwater level change and rainfall hydrological runoff processes caused by tunnel construction at Milbot bog located in Mt. Cheonseong. Data were collected from July 2004 to May 2008. The results were summarized as follows: The occurrence time of the direct runoff caused by unit rainfall at the Milbot bog were tended to be slower than those at general mountainous basin. Also, runoff did not sensitively respond to amount of rainfall at the most of the long and short term hydrograph. The annual runoff rates from 2004 to 2008 were 0.26, 0.13, 0.16, 0.25 and 0.27, respectively, slightly increased after 2005 regardless of the tunnel construction. Thus, the function of Milbot bog will be weakened, and it supposed to be changed to land in the future because of increasing annual runoff. The annual runoff rate for 4 years was 0.19, which is greatly lower than that of general mountainous basin. The recession coefficient of the direct runoff in short term hydrograph was ranged to 0.89~0.97, which is much larger than that of the general mountainous basin, 0.2~0.8. The recession coefficient of base flow ranged from 0.93 to 0.99, which are similar to general mountainous watershed's values. Groundwater level of Milbot bog increased or decreased in proportion to rainfall intensity, and in the descending time after the groundwater level was reached at peak point, it tends to be decreased very slowly. Also, groundwater level increased or decreased maintaining relatively high value after precedent rainfall. Groundwater level was highest during summer with heavy rainfall, but was lowest during winter. Average groundwater levels decreased annually from 2004 to 2008, -8.48 cm, -14.60 cm, -20.46 cm, -20.11 cm, -28.59 cm, respectively. Therefore, it seems that the Milbot bog is becoming dry and losing its function as a bog.

• Journal of Korea Water Resources Association
• /
• v.53 no.12
• /
• pp.1193-1201
• /
• 2020

This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.149-149
• /
• 2022

Accurate quantitative evaluation of baseflow contribution to streamflow is imperative to address seasonal drought vulnerability, flood occurrence and groundwater management concerns for efficient and sustainable water resources management in watersheds. Several baseflow separation algorithms using recursive filters, graphical method and tracer or chemical balance have been developed but resulting baseflow outputs always show wide variations, thereby making it hard to determine best separation technique. Therefore, the current global shift towards implementation of artificial intelligence (AI) in water resources is employed to compare the performance of deep learning models with conventional hydrograph separation techniques to quantify baseflow contribution to streamflow of Piney River watershed, Tennessee from 2001-2021. Streamflow values are obtained from the USGS station 03602500 and modeled to generate values of Baseflow Index (BI) using Web-based Hydrograph Analysis (WHAT) model. Annual and seasonal baseflow outputs from the traditional separation techniques are compared with results of Long Short Term Memory (LSTM) and simple Gated Recurrent Unit (GRU) models. The GRU model gave optimal BFI values during the four seasons with average NSE = 0.98, KGE = 0.97, r = 0.89 and future baseflow volumes are predicted. AI offers easier and more accurate approach to groundwater management and surface runoff modeling to create effective water policy frameworks for disaster management.

• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 2005.10a
• /
• pp.241-246
• /
• 2005

Doam watershed is located at alpine areas in the Kangwon province. The annual average precipitation, including snow accumulation during the winter, at the Doam watershed is significantly higher than other areas. Thus, pollutant laden runoff and sediment discharge from the alpine agricultural fields are causing water quality degradation at the Doam watershed. To estimate soil erosion from the agricultural fields, the Universal Soil Loss Equation (USLE) has been widely used because of its simplicity to use. The USLE rainfall erosivity (R) factor is responsible for impacts of rainfall on soil erosion. Thus, use of constant R factor for the Doam watershed cannot reflect variations in precipitation patterns, consequently soil erosion estimation. In the early spring at the Doam watershed, the stream flow increases because of snow melt, which results in erosion of loosened soil experiencing freezing and thaw during the winter. However, the USLE model cannot consider the impacts on soil erosion of freezing and thaw of the soil. Also, it cannot simulate temporal changes in USLE input parameters. Thus, the Soil and Water Assessment Tool (SWAT) model was investigated for its applicability to estimate soil erosion at the Doam watershed, instead of the widely used USLE model. The SWAT hydrology and erosion/sediment components were validated after calibration of the hydrologic component. The $R^2$ and Nash-Sutcliffe coefficient values are higher enough, thus it was found the SWAT model can be efficiently used to simulate hydrology and sediment yield at the Doam watershed. The effects of snow melt on SWAT estimated stream flow and sediment were investigated using long-term precipitation and temperature data at the Doam watershed. It was found significant amount of flow and sediment in the spring are contributed by melting snow accumulated during the winter. Thus, it is recommend that the SWAT model capable of simulating snow melt and long-term weather data needs to be used in estimating soil erosion at alpine agricultural land instead of the USLE model for successful soil erosion management at the Doam watershed.

• Journal of Korea Water Resources Association
• /
• v.53 no.12
• /
• pp.1143-1157
• /
• 2020

In this study, a criteria for the SWAT model calibration method in SWAT-CUP which considers multi-site and multi-variable observations was presented. For its application, the SWAT model was simulated using long-term observed flow, soil moisture, and evapotranspiration data in Yongdam study watershed, investigating the hydrological runoff characteristics and water balance in the water cycle analysis. The model was calibrated with different parameter values for each sub-watershed in order to reflect the characteristics of multiple observations through one-by-one calibration, appropriate settings of model simulation run/iteration number (1,000 simulation runs in the first iteration and then 500 simulation runs for the following iterations), and executions of partial and all run in SWAT-CUP. The flow simulation results of watershed outlet point, ENS 0.85, R2 0.87, and PBIAS -7.6%, were compared with the analysis results (ENS 0.52, R2 0.54, and PBIAS -22.4%) applied in the other batch (i.e., non one-by-one) calibration approach and showed better performances of proposed method. From the simulation results of a total of 15 years, it was found that the total runoff (streamflow) and evapotranspiration rates from precipitation are 53 and 39%, and the ratio of surface runoff and baseflow (i.e., sum of lateral and return flow, and recharge deep aquifer) are 35 and 65%, respectively, in Yongdam watershed. In addition, the analytical amount of available water (i.e., water yield), including the total annual streamflow (daily average 21.8 m3/sec) is 6.96 billion m3 per year (about 540 to 900 mm for sub-watersheds).

• Journal of Korean Society of Rural Planning
• /
• v.11 no.4 s.29
• /
• pp.67-74
• /
• 2005

The Doam watershed is located at alpine areas and the annual average precipitation, including snow accumulation, is significant higher than other areas. Thus, pollutant laden runoff and sediment discharge from the alpine agricultural fields are causing water quality degradation at the Doam watershed. To estimate soil erosion from the agricultural fields, the Universal Soil Loss Equation (USLE) has been widely used because of its simplicity to use. In the early spring at the Doam watershed, the stream flow increases because of snow melt, which results in erosion of loosened soil experiencing freezing and thaw during the winter. Also, extremely torrential rainfall, such as the typhoons 'RUSA' in 2002 and 'MAEMI' in 2003, caused significant amounts of soil erosion and sediment at the Doam watershed. However, the USLE model cannot simulate impacts on soil erosion of freezing and thaw of the soil. It cannot estimate sediment yield from a single torrential rainfall event. Also, it cannot simulate temporal changes in USLE input parameters. Thus, the Soil and Water Assessment Tool (SWAT) model was investigated for its applicability to estimate soil erosion at the Doam watershed, instead of the widely used USLE model. The SWAT hydrology and erosion/sediment components were validated after calibration of the hydrologic component. The R$^2$ and Nash-Sutcliffe coefficient values are higher enough, thus it is found the SWAT model can be efficiently used to simulate hydrology and sediment yield at the Doam watershed. The effects of snow melt on SWAT estimated stream flow and sediment were investigated using long-term precipitation and temperature data at the Doam watershed. It was found significant amount of flow and sediment in the spring are contributed by melting snow accumulated during the winter. Two typhoons in 2002 and 2003, MAEMI and RUSA, caused 33% and 22% of total sediment yields at the Doam watershed, respectively. Thus, it is recommended that the SWAT model, capable of simulating snow melt, sediment yield from a single storm event, and long-term weather data, needs to be used in estimating soil erosion at alpine agricultural areas to develop successful soil erosion management instead of the USLE.

• Spatial Information Research
• /
• v.20 no.3
• /
• pp.39-50
• /
• 2012

The objective of this study is the quantitative analysis of climate change effects by performing several statistical analyses with hydrometeorological data sets for past 30 years in Geum river watershed. Temperature, precipitation, relative humidity data sets were collected from eight observation stations for 37 years(1973~2009) in Geum river watershed. River level data was collected from Gongju and Gyuam gauge stations for 36 years(1973~2008) considering rating curve credibility problems and future long-term runoff modeling. Annual and seasonal year-to-year variation of hydrometeorological components were analyzed by calculating the average, standard deviation, skewness, and coefficient of variation. The results show precipitation has the strongest variability. Run test, Turning point test, and Anderson Exact test were performed to check if there is randomness in the data sets. Temperature and precipitation data have randomness and relative humidity and river level data have regularity. Groundwater level data has both aspects(randomness and regularity). Linear regression and Mann-Kendal test were performed for trend test. Temperature is increasing yearly and seasonally and precipitation is increasing in summer. Relative humidity is obviously decreasing. The results of this study can be used for the evaluation of the effects of climate change on water resources and the establishment of future water resources management technique development plan.