Geun Ae Park

HSPF and SWAT Modelling for Identifying Runoff Reduction Effect of Nonpoint Source Pollution by Rice Straw Mulching on Upland Crops

This study is to assess the reduction of non-point source pollution loads for rice straw mulching of upland crop cultivation at a watershed scale. For Byulmi-cheon watershed (1.21 ) located in the upstream of Gyeongan-cheon, the HSPF (Hydrological Simulation Program-Fortran) and SWAT (Soil and Water Assesment Tool), physically based distributed hydrological models were applied. Before evaluation, the model was calibrated and validated using 9 rainfall events. The Nash-Sutcliffe model efficiency (NSE) for streamflow using the HSPF was 0.62~0.76 and the determination coefficient () for water quality (sediment, total nitrogen T-N, and total phosphorus T-P) were 0.72, 0.62, and 0.63 respectively. The NSE for streamflow using the SWAT were 0.43~0.81 and the for water quality (sediment, T-N, and T-P) were 0.54, 0.87, and 0.64 respectively. From the field experiment of 16 rainfall events, the rice straw cover condition reduced surface runoff average 10.0 % compared to normal surface condition. By handling infiltration capacity (INFILT) in HSPF model, the value of 16.0 mm/hr was found to reduce about 10.0 % reduction of surface runoff. For this condition, the reduction effect of sediment, T-N, and T-P loads were 87.2, 28.5, and 85.1 % respectively. By handling soil hydraulic conductivity (SOL_K) in SWAT model, the value of 111.2 mm/hr was found to reduce about 10.0 point reduction of surface runoff. For this condition, the reduction effect of sediment, T-N, and T-P loads were 80.0, 83.2, and 78.7 % respectively. The rice straw surface covering was effective for removing surface runoff dependent loads such as sediment and T-P.

Projection of future climate change impacts on nonpoint source pollution loads for a forest dominant dam watershed by reflecting future vegetation canopy in a Soil and Water Assessment Tool model.

This study is to assess the future impact of climate change on hydrological behavior considering future vegetation canopy prediction and its propagation to nonpoint source pollution (NPS) loads. The SWAT (Soil and Water Assessment Tool) model was used for the assessment. For a forest dominant ChungjuDam watershed of South Korea, the MIROC3.2hires climate data of SRES A1B and B1 scenarios were adopted and downscaled for the watershed. The future vegetation canopy information was projected by the monthly relationship between Terra MODIS (MODerate resolution Imaging Spectroradiometer) LAI (Leaf Area Index) and temperature. The future predicted LAI increased up to 1.9 in 2080s April and October because of the temperature increase 3.6 degrees C and 5.3 degrees C respectively. By reflecting the future LAI changes, the future estimated percent changes of maximum annual dam inflow, SS, T-N, and T-P were + 42.5% in 2080s A1B,-35.6% in 2020s A1B,+73.7% in 2080s A1B and-21.0% in 2080s B1 scenario respectively. The increase of T-N load was from the increase of subsurface lateral flows and the groundwater recharges by the future rainfall increase. The decrease of T-P load was by decrease of sediment load during wet days because the effect of LAI increase is greater than the increase of rainfall.

Evaluation of Evapotranspiration and Soil Moisture of SWAT Simulation for Mixed Forest in the Seolmacheon Catchment

Common practice of Soil Water Assessment Tool (SWAT) model validation is to use a single variable (i.e., streamlfow) to calibrate SWAT model due to the paucity of actual hydrological measurement data in Korea. This approach, however, often causes errors in the simulated results because of numerous sources of uncertainty and complexity of SWAT model. We employed multi-variables (i.e., streamflow, evapotranspiration, and soil moisture), which were measured at mixed forest in Seolmacheon catchment (), in order to assess the performance and reduce the uncertainties of SWAT model output. Meteorological and surface topographical data of the catchment were obtained as basic input variables and SWAT model was calibrated using daily data of streamflow (Jan. - Dec.), evapotranspiration (Sep. - Dec.), and soil moisture (Jun. - Dec.) collected in 2007. The model performance was assessed by comparing its results with the observation (i.e., streamflow of 2003 to 2008 and evapotranspiration and soil moisture of 2008). When the multi-variable measurements were used to calibrate the SWAT model, the model results showed better agreement with the measurements compared to those using a single variable measurement by showing increases in coefficient of determination () from 0.72 to 0.76 for streamflow, from 0.49 to 0.59 for soil moisture, and from 0.52 to 0.59 for evapotranspiration. The findings highlight the importance of reliable and accurate collective observation data for improving performance of SWAT model and promote its facilitation for estimating more realistic hydrological cycles at catchment scale.

Assessment of Climate Change Impact on Evapotranspiration and Soil Moisture in a Mixed Forest Catchment Using Spatially Calibrated SWAT Model

This study is to evaluate the future climate change impact on hydrological components in the Seolmacheon () mixed forest catchment located in the northwest of South Korea using SWAT (Soil and Water Assessment Tool) model. To reduce the uncertainty, the model was spatially calibrated (2007~2008) and validated (2009~2010) using daily observed streamflow, evapotranspiration, and soil moisture data. Hydrological predicted values matched well with the observed values by showing coefficient of determination () from 0.74 to 0.91 for streamflow, from 0.56 to 0.71 for evapotranspiration, and from 0.45 to 0.71 for soil moisture. The HadGEM3-RA future weather data of Representative Concentration pathway (RCP) 4.5 and 8.5 scenarios of the IPCC (Intergovernmental Panel on Climate Change) AR5 (Assessment Report 5) were adopted for future assessment after bias correction of ground measured data. The future changes in annual temperature and precipitation showed an upward tendency from to and from 7.9% to 20.4% respectively. The future streamflow showed an increase from 0.6% to 15.7%, but runoff ratio showed a decrease from 3.8% to 5.4%. The future predicted evapotranspiration about precipitation increased from 4.1% to 6.8%, and the future soil moisture decreased from 4.3% to 5.5%.

The Applicability Study on Non-Point Source Pollution Assessment in a Small Agricultural Watershed Using High Resolution Satellite Image (QuickBird)

This study is to test the applicability of QuickBird satellite image for Non-Point Source (NPS) pollution assessment of a small agricultural watershed. Soil and Water Assessment Tool (SWAT) model was adopted and the model was calibrated for a 255.4 km2 watershed using Landsat land use data. For model application with QuickBird image, a precise agricultural land use map of 1.21 km2 area located in the upstream watershed was produced by field investigation. The model was run with the combination of three DEM (2 m, 10 m and 30 m), land use (QuickBird, 1/25,000 and Landsat), and 1/25,000 soil map respectively. The hydrological results showed that the watershed average CN (Curve Number) of QucikBird land use was 0.4 and 1.8 higher than those of 1/25,000 (produced by IRS-1C and Landsat) and Landsat land use. Based on QucikBird land use CN value, the increased CN value caused 1.33 % and 3.39 % increase of total runoff under AMC (Antecedent Moisture Content)-II condition respectively. The NPS loadings from the model prediction showed that the sediment, T-N and T-P of QuickBird land use showed 23.7 %, 43.3 % and 48.4 % higher value than those of 1/25,000 land use and 50.6 %, 50.8 % and 56.9 % higher value than those of Landsat land use respectively.

Assessment of Climate Change Impact on the Inflow to Agricultural Reservoir and the Streamflow of a Watershed in South Korea

This study is to assess the effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water supply using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. Before the future analysis, the SLURP model was calibrated using the 6 years daily streamflow records (1998-2003) and validated using 3 years streamflow data (2004-2006) for a 366.5 km2 watershed including two agricultural reservoirs (Geumgwang and Gosam) located in the upper middle part of South Korea. The calibration and validation results showed that the model was able to simulate the daily streamflow well considering the reservoir operation for paddy irrigation and flood discharge, with a coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.7 to 0.9 and 0.5 to 0.8 respectively. At first, the analysis of historical hydrologic trend was investigated by the simulated SLURP model run using the 30 years weather data from 1977 to 2006 and the results was analysed by Mann-Kendall trend test. Next as a main analysis, the future potential climate change impact was assessed using the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change). The future weather data for the year 2020s, 2050s and 2080s was downscaled by Change Factor method through bias-correction using 30 years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land covers were predicted by modified CA (cellular automata)-Markov technique using the time series land cover data from Landsat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998 - 2005) data. The future (2020s, 2050s and 2080s) reservoir inflow, the temporal changes of reservoir water level and its impact to downstream streamflow watershed were analyzed for the A2 and B2 climate change scenarios based on a base year (2005) using the prepared future climate data, land cover and vegetation cover information. At an annual temporal scale, the reservoir inflow and water level change of the agricultural reservoir were projected to big decrease in autumn under all possible combinations of conditions. The future streamflow decreased slightly, where as the evapotranspiration was projected to increase largely for all possible combinations of the conditions.

A Modified CA-Markov Technique for The Prediction of Future Land Use Change

The purpose of this study is to suggest a prediction method of land use change by modifying CA-Markov technique. In the modified method, a logarithmic function was reflected for the trend of past land use change of each item. Data of water quality protection area and green belt area were considered to include systematic factor. In addition, the minimal preserved probability that is the percent of upper limit of land use change between land use classes in the process of prediction was applied to prevent unrealistic prediction of future land use. The prediction results of original and modified CA-Markov were evaluated by comparing indices (a: the ratio of matched cell number of the predicted to the total cell number of the known, b: the ratio of matched cell number of the predicted to the total cell number as sum of sets of the known and the predicted, g: the ratio of cell number of the predicted to the cell number of the known) which compare the spatial fit between the known and the predicted. For Anseongcheon watershed (371.1 km2), the 2000 land uses were predicted using the 3 past land use data (1985, 1990, 1995). The values of a, b, and g for urban area were 0.69, 0.63, 0.80 for the modified CA-Markov and 0.52, 0.45, 0.68 for the original CA-Markov respectively.

A grid-based KIneMatic wave STOrm Runoff Model (KIMSTORM) for flood watch of Korea Water Resources Corporation

A grid-based KIneMatic wave STOrm Runoff Model (KIMSTORM) which predicts temporal variation and spatial distribution of saturated overland flow, subsurface flow and stream flow in a watershed is described. The model adopts the single overland flowpath algorithm and simulates surface and/or subsurface water depth at each cell by using water balance of hydrologic components. In this study, the original KIMSTORM was reprogrammed with FORTRAN 90 code by enhancing the infiltration module from Huggins and Monke to GAML (Green-Ampt and Mein-Larson), being able to treat both radar rainfall data and point rainfall data, building the pre- and post-processors for the model input and output respectively, and automatic evaluation module for the predicted result. The model was tested for a 2,293 km2 dam watershed of South Korea using five typhoon events with 500 m spatial resolution. The model result was tested by the coefficient of determination (R2), Nash and Sutcliffe model efficiency (E), deviation of runoff volumes (Dv), relative error of the peak discharge (EQp), and absolute error of the time to peak discharge (ETp). The average values for model calibration and verification were 0.913, 0.884, 9.36 %, 0.080, and 0.88 hr respectively. The sensitivity analysis of model parameter shows that the initial soil moisture content, Manning’s roughness coefficient of stream, effective soil depth were sensitive to runoff volume and peak discharge.

NETWORKING MODELING OF PADDY IRRIGATION SYSTEM USING ARCHYDRO GIS

During the past decades in South Korea, there have been several projects to reduce water demand and save water for paddy irrigation system by automation. This is called as intensive water management system by telemetering of paddy ponding depth and canal water level and telecontrol of water supply facilities. This study suggests a method of constructing topology-based irrigation network system using GIS tools. For the network modeling, a typical agricultural watershed included reservoirs, irrigation and drainage canals, pumping stations was selected. ArcHydro tools composed of edge, junction, waterbody and watershed were used to construct hydro-network. Arc Hydro data model was then designed and the network was successfully built using the HydroID. Visualization using ArcHydro tools could display table property of each object.