So-Ra Ahn

Watershed modeling for assessing climate change impact on stream water quality of Chungju Dam watershed.

This study is to assess the future potential impact of climate change on stream water quality for a 6,581.1 km dam watershed using SWAT (Soil and Water Assessment Tool) model. The ECHAM5-OM climate data of IPCC (The Intergovernmental Panel on Climate Change) A2, A1B, and B1 emission scenarios were adopted and the future data (2007-2099) were corrected using 30 years (1977-2006, baseline period) weather data and downscaled by Change Factor (CF) method. After model calibration and validation using 6 years (1998-2003) observed daily streamflow and monthly water quality (SS, T-N, and T-P) data, the future (2020s, 2050s and 2080s) hydrological behavior and stream water quality were projected.

Assessment of the Potential Water Supply Rate of Agricultural Irrigation Facilities Using MODSIM - For Geum River Basin -

To prepare for agricultural droughts, the potential discharge to the water supply of irrigation facilities during drought periods is important. Using the MODSIM (Modified SIMYLD) model, water balance networks that consider irrigation facilities were designed for the Geum River Basin, and the potential discharge to the agricultural water supply of irrigation facilities were evaluated by running the model using data for 36 years (1967-2002). It was found that agricultural water deficiencies occurred during the drought years more than in the other years. The agricultural water deficiencies in 1994, 1995, and 2001, the representative drought years, were 745.8 million m, 661.1 million m, and 696.8 million m, respectively. The average potential discharge to the water supply of the sub-basin was 99.1 % in the cases of municipal and industrial water, and 84.4 % in the case of agricultural water. The potential discharge to the water supply in 1994, 1995, and 2001 were 74.8 %, 79.2 %, and 77.9 %, respectively, which are lower than those of the other years` sub-basin average. In the analysis of the contribution of each irrigation facility, the contributions of pumping stations and diversions were calculated as 32.5 %, and of culverts and wells, 4.0 %. During the drought periods, the pumping stations and diversions contributed to a certain level.

Error influence of radar rainfall estimate on rainfall-runoff simulation

Radar systems have been widely employed to measure precipitation and predict flood risks. However, radar as a rainfall measuring device and the produced rainfall estimate contain uncertainties and errors resulting from sources such as mis-calibration, beam blockage, anomalous propagation, and ground clutter. Previously, these radar errors have been individually studied. However, in practical applications, separating and estimating these errors are not possible. In the current study, to analyze the effects of radar rainfall errors, especially for their effect on the peak discharge, through a synthetic runoff simulation, a spatial error model based on univariate Gaussian random numbers was employed. Furthermore, a Monte Carlo simulation, one of the most widely used techniques for intensive simulation toward obtaining practical results, was performed. The results indicated that the variability of the peak discharge increases as the assumed true rainfall increases. In addition, the higher standard deviation of the tested radar rainfall error leads to a higher peak discharge bias. To investigate the cause of this bias, an additional simulation was performed. This simulation revealed that the regression line for the peak discharge corresponding to rainfall amount increases quadratically. The results show that the higher bias is a result of the higher deviation of peak discharges in the cells, with a greater than mean rainfall, even with the same number of cells for lower and higher rainfall amounts.

Hydrological Drought Assessment of Agricultural Reservoirs based on SWSI in Geum River Basin

This study proposes a method to evaluate agricultural reservoirs drought by modifying SWSI (Surface Water Supply Index). The method was applied to Geum river basin and the results were represented as spatially distributed information. The SWSI evaluates hydrological drought of watershed unit by selectively applying one or all of the components of snowpack, precipitation, streamflow and reservoir storage. South Korea has 22 % of agricultural area, and rice paddy covers 64 % among them. Usually paddy fields scattered along stream are irrigated by so many small agricultural reservoirs. It is difficult to evaluate agriculture drought by the little information and large number of agricultural reservoirs. In this study, seven agricultural reservoirs over 10 million ton storage capacity were selected in Geum river basin, and the SWSI was evaluated for both upstream and downstream of the reservoirs using 16 years data (1991-2006). Using the results, multiple regression analyses with precipitation and reservoir storage as variables were conducted and the equations were applied to other watersheds. The spatial results by applying regression equations showed that the severe and moderate drought conditions of July and September in 1994, June in 1995, and May in 2001 were well expressed by the watershed unit.

Comparison of Nonpoint Source Nutrients Load from Upland Tillage and No-Tillage Crop Cultivation Areas by HSPF Watershed Modeling

Abstract. This study is to evaluate the watershed scale effect of nonpoint source (NPS) pollution loads by tillage and no-tillage application of upland crop areas using HSPF (Hydrological Simulation Program-Fortran). Byulmi-cheon catchment (1.21 km²) located in upstream of Gyeongan-cheon watershed located in the northwest of South Korea was adopted and the hourly rainfall, discharge and stream water quality data were used for evaluation. The field scale experiment for tillage and no-tillage conditions was conducted to get the runoff and water quality from plots of 3 % and 8 % slopes under radish and wild sesame cultivation. The HSPF model was calibrated using 23 rainfall events from 2012 to 2013 with 0.61 average Nash-Sutcliffe model efficiency for runoff (Q) and 0.58, 0.61, and 0.62 determination coefficients for sediment, total nitrogen (T-N), and total phosphorus (T-P) respectively. For tillage and no-tillage HSPF modeling, the parameters of soil bulk density and soil infiltration capacity for upland crop areas were controlled for tillage effect evaluation. The catchment runoff ratio, sediment, T-N and T-P under no-tillage condition were reduced by 10.3 %, 56.7 %, 18.3 % and 35.9 % respectively compared to tillage condition.

The Effect of Meteorological Factors on the Temporal Variation of Agricultural Reservoir Storage

The purpose of this paper is to analyze the relationship between meteorological factors and agricultural reservoir storage, and predict the reservoir storage by multiple regression equation selected by high correlated meteorological factors. Two agricultural reservoirs (Geumgwang and Gosam) located in the upsteam of Gongdo water level gauging station of Anseong-cheon watershed were selected. Monthly reservoir storage data and meteorological data in Suwon weather station of 21 years (1985-2005) were collected. Three cases of correlation (case 1: yearly mean, case 2: seasonal mean dividing a year into 3 periods, and case 3: lagging the reservoir storage from 1 month to 3 months under the condition of case 2) were examined using 8 meteorological factors (precipitation, mean/maximum/minimum temperature, relative humidity, sunshine hour, wind velocity and evaporation). From the correlation analysis, 4 high correlated meteorological factors were selected, and multiple regression was executed for each case. The determination coefficient () of predicted reservoir storage for case 1 showed 0.45 and 0.49 for Geumgwang and Gosam reservoir respectively. The predicted reservoir storage for case 2 showed the highest of 0.46 and 0.56 respectively in the period of April to June. The predicted reservoir storage for 1 month lag of case 3 showed the of 0.68 and 0.85 respectively for the period of April to June. The results showed that the status of agricultural reservoir storage could be expressed with couple of meteorological factors. The prediction enhanced when the storage data are divided into periods rather than yearly mean and especially from the beginning time of paddy irrigation (April) to high decrease of reservoir storage (June) before Jangma.