• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.199-199
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• 2017

Sustainable wheat production is of paramount importance for attaining/maintaining the food self-sufficiency status of the rapidly growing nation of Pakistan. However, the average wheat yield per unit area has been dwindling in recent years and the climate-induced variations in rainfall patterns and temperature regimes, during the wheat growth period, are believed to be the reason behind this decline. Crop growth simulation models are powerful tools capable of playing pivotal role in evaluating the climate change impacts on crop yield or productivity. This study was aimed to predict the plausible variations in the wheat yield for future climatic trends so that possible mitigation strategies could be explored. For this purpose, Aquacrop model v. 4.0 was employed to simulate the wheat yield under present and future climatology of the largest agricultural province of Punjab in Pakistan. The data related to crop phenology, management and yield were collected from the experimental plots to calibrate and validate the model. The future climate projections were statistically downscaled from five general circulation models (GCMs) and compared with the base line climate from 1980 to 2010. The model was fed with the projected climate to simulate the wheat yield based on the RCP (representative concentration pathways) 4.5 and 8.5. Under the worst, most likely future scenario of temperature rise and rainfall reduction, the crop yield decreased and water footprint, especially blue, increased, owing to the elevated irrigation demands due to accelerated evapotranspiration rates. The modeling results provided in this study are expected to provide a basic framework for devising policy responses to minimize the climate change impacts on wheat production in the area.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.963-978
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• 2020

Earthquakes can induce a large number of landslides and cause very serious property damage and human casualties. There are two issues in study on earthquake-induced landslides: (1) slope stability analysis under seismic loading and (2) debris flow run-out analysis. This study aims to review technical studies related to the development and application of earthquake-induced landslide models (seismic slope stability analysis). Moreover, a pilot application of a physics-based slope stability model to Mt. Umyeon, in Seoul, with several earthquake scenarios was conducted to test regional scale seismic landslide mapping. The earthquake-induced landslide simulation model can be categorized into 1) Pseudo-static model, 2) Newmark's dynamic displacement model and 3) stress-strain model. The Pseudo-static model is preferred for producing seismic landslide hazard maps because it is impossible to verify the dynamic model-based simulation results due to lack of earthquake-induced landslide inventory in Korea. Earthquake scenario-based simulation results show that given dry conditions, unstable slopes begin to occur in parts of upper areas due to the 50-year earthquake magnitude; most of the study area becomes unstable when the earthquake frequency is 200 years. On the other hand, when the soil is in a wet state due to heavy rainfall, many areas are unstable even if no earthquake occurs, and when rainfall and 50-year earthquakes occur simultaneously, most areas appear unstable, as in simulation results based on 100-year earthquakes in dry condition.

• Atmosphere
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• v.31 no.2
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• pp.185-198
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• 2021

In this study, we examined a spatial downscaling method based on Gradient and Inverse Distance Squared (GIDS) weighting to produce high-resolution grid data from a numerical weather prediction model over Korean Peninsula with complex terrain. The GIDS is a simple and effective geostatistical downscaling method using horizontal distance gradients and an elevation. The predicted meteorological variables (e.g., temperature and 3-hr accumulated rainfall amount) from the Limited-area ENsemble prediction System (LENS; horizontal grid spacing of 3 km) are used for the GIDS to produce a higher horizontal resolution (1.5 km) data set. The obtained results were compared to those from the bilinear interpolation. The GIDS effectively produced high-resolution gridded data for temperature with the continuous spatial distribution and high dependence on topography. The results showed a better agreement with the observation by increasing a searching radius from 10 to 30 km. However, the GIDS showed relatively lower performance for the precipitation variable. Although the GIDS has a significant efficiency in producing a higher resolution gridded temperature data, it requires further study to be applied for rainfall events.

• Korean Journal of Agricultural Science
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• v.10 no.2
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• pp.324-333
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• 1983

Modeling of longterm runoff is theoritically based on waterbalance analysis. Simplified equation of water balance with rainfall, evapotranspiration and soil moisture storage could be formulated into regression model with variables of rainfall, pan evaporation and previous-month streamflow. The hydrologic response of water shed could be represented lumpedly, qualitatively and deductively by regression coefficients of water-balance regression model. Characteristics of regression modeling of water-balance were summarized as follows; 1. Regression coefficient $b_1$ represents the rate of direct runoff component of precipitation. The bigger the drainage area, the less $b_1$ value. This means that there are more losses of interception, surface detension and transmission in the downstream watershed. 2. Regression coefficient $b_2$ represents the rate of baseflow due to changes of soil moisture storage. The bigger the drainage area and the milder the watershed slope, the bigger b, value. This means that there are more storage capacity of watershed in mild downstream watershed. 3. Regression coefficient $b_3$ represents the rate of watershed evaporation. This depends on the s oil type, soil coverage and soil moisture status. The bigger the drainage area, the bigger $b_3$ value. This means that there are more watershed evaporation loss since more storage of surface and subsurface water would be in down stream watershed. 4. It was possible to explain the seasonal variation of streamflow reasonably through regress ion coefficients. 5. Percentages of beta coefficients what is a relative measure of the importance of rainfall, evaporation and soil moisture storage to month streamflow are approximately 89%, 9% and 11% respectively.

• Journal of Korean Society of Disaster and Security
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• v.15 no.1
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• pp.1-12
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• 2022

An automatic optimization technique is used to estimate the optimal parameters of the hydrologic model, and different hydrologic response results can be provided depending on objective functions. In this study, the parameters of the event-based rainfall-runoff model were estimated using various objective functions, the reproducibility of the hydrograph according to the objective functions was evaluated, and appropriate objective functions were proposed. As the rainfall-runoff model, the storage function model(SFM), which is a lumped hydrologic model used for runoff simulation in the current Korean flood forecasting system, was selected. In order to evaluate the reproducibility of the hydrograph for each objective function, 9 rainfall events were selected for the Cheoncheon basin, which is the upstream basin of Yongdam Dam, and widely-used 7 objective functions were selected for parameter estimation of the SFM for each rainfall event. Then, the reproducibility of the simulated hydrograph using the optimal parameter sets based on the different objective functions was analyzed. As a result, RMSE, NSE, and RSR, which include the error square term in the objective function, showed the highest accuracy for all rainfall events except for Event 7. In addition, in the case of PBIAS and VE, which include an error term compared to the observed flow, it also showed relatively stable reproducibility of the hydrograph. However, in the case of MIA, which adjusts parameters sensitive to high flow and low flow simultaneously, the hydrograph reproducibility performance was found to be very low.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.155-166
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• 2020

In this study, we applied the Radar-AWS Rainrates (RAR), weather radar-based quantitative precipitation estimations (QPEs), to the Yongdam study watershed in order to perform the flood runoff simulation and calculate the inflow of the dam during flood events using hydrologic model. Since the Yongdam study watershed is a representative area of the mountainous terrain in South Korea and has a relatively large number of monitoring stations (water level/flow) and data compared to other dam watershed, an accurate analysis of the time and space variability of radar rainfall in the mountainous dam watershed can be examined in the flood modeling. HEC-HMS, which is a relatively simple model for adopting spatially distributed rainfall, was applied to the hydrological simulations using HEC-GeoHMS and ModClark method with a total of eight independent flood events that occurred during the last five years (2014 to 2018). In addition, two NCL and Python script programs are developed to process the radar-based precipitation data for the use of hydrological modeling. The results demonstrate that the RAR QPEs shows rather underestimate trends in larger values for validation against gauged observations (R² 0.86), but is an adequate input to apply flood runoff simulation efficiently for a dam watershed, showing relatively good model performance (E_NS 0.86, R² 0.87, and PBIAS 7.49%) with less requirements for the calibration of transform and routing parameters than the spatially averaged model simulations in HEC-HMS.

• Journal of Wetlands Research
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• v.23 no.4
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• pp.372-380
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• 2021

Non-point source pollutants and high-concentration livestock wastewater are reported as major factor of water pollution in water system and wet-land. So, LID is suggested as a method to manage of them. wet-lands is presented as effective method for management of NPS from agriculture and livestock farm area based on various NPS reduction mechanism. In this research, the application of wet-lands was evaluated based on monitoring and modeling of agriculture and livestock farm in J city, Jeollabuk-do. As a resutl, EMC during rainfall event was found to be about 27 times higher than dry season based on a BOD. indicating that the management of non-point pollutants is urgent. Modeling-based wet-land reduction efficiency was BOD 57.5%, TN 48.9% and Tp 64.2%. However, removal efficiency of wet-land tends to decrease during the winter and large amounts of rainfall runoff occur, it is necessary to manage of wet-land. Based on the results of this research, wet-land could be proposed as an alternative to stable management of NPS in agriculture and livestock farm area.

• Journal of Korean Society on Water Environment
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• v.26 no.5
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• pp.841-849
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• 2010

Soil erosion is an natural phenomenon. However accelerated soil erosion has caused many environmental problems. To reduce soil loss from a watershed, many management practices have been proposed worldwide. To develop proper and efficient soil erosion best management practices, soil erosion rates should be estimated spatially and temporarily. The Universal Soil Loss Equation (USLE) and USLE-based soil erosion and sediment modelling systems have been developed and tested in many countries. The Sediment Assessment Tool for Effective Erosion Control (SATEEC) system has been developed and enhanced to provide ease-of-use interface to the USLE users. However many researchers and decision makers have requested to enhance the SATEEC system for simulation of soil erosion and sediment reflecting effects of single storm event. Thus, the SATEEC R factors were estimated based on 5 day antecedent rainfall data. The SATEEC 2.1 daily R factor was applied to the study watershed and it was found that the R2 and EI values (0.776 and 0.776 for calibration and 0.927 and 0.911 for validation) with the daily R were greater than those (0.721 and 0.720 for calibration and 0.906 and 0.881 for validation) with monthly R, which was available in the SATEEC 2.0 system. As shown in this study, the SATEEC with daily R can be used to estimate soil erosion and sediment yield at a watershed scale with higher accuracy. Thus the SATEEC with daily R can be efficiently used to develop site-specific soil erosion best management practices based on spatial and temporal analysis of soil erosion and sediment yield at a daily-time step, which was not possible with USLE-based soil erosion modeling system.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1083-1091
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• 2010

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. However, widely used estimation schemes fail to describe the realistic variability of daily precipitation field. We compare and contrast the performance of statistical methods for the spatial estimation of precipitation in two hydrologically different basins, and propose a two-step process for effective daily precipitation estimation. The methods assessed are: (1) Inverse Distance Weighted Average (IDW); (2) Multiple Linear Regression (MLR); (3) Climatological MLR; and (4) Locally Weighted Polynomial Regression (LWP). In the suggested simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before applying IDW scheme (one of the local scheme) to estimate the amount of precipitation separately on wet days. As the results, the suggested method shows the better performance of daily rainfall interpolation which has spatial differences compared with conventional methods. And this technique can be used for streamflow forecasting and downscaling of atmospheric circulation model effectively.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.263-274
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• 2013

In this study we evaluated the hydrological applicability of multi-satellite precipitation estimates. Three high-resolution global multi-satellite precipitation products, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), the Global Satellite Mapping of Precipitation (GSMaP), and the Climate Precipitation Center (CPC) Morphing technique (CMORPH), were applied to the Coupled Routing and Excess Storage (CREST) model for the evaluation of their hydrological utility. The CREST model was calibrated from 2002 to 2005 and validated from 2006 to 2009 in the Chungju Dam watershed, including two years of warm-up periods (2002-2003 and 2006-2007). Areal-averaged precipitation time series of the multi-satellite data were compared with those of the ground records. The results indicate that the multi-satellite precipitation can reflect the seasonal variation of precipitation in the Chungju Dam watershed. However, TMPA overestimates the amount of annual and monthly precipitation while GSMaP and CMORPH underestimate the precipitation during the period from 2002 to 2009. These biases of multi-satellite precipitation products induce poor performances in hydrological simulation, although TMPA is better than both of GSMaP and CMORPH. Our results indicate that advanced rainfall algorithms may be required to improve its hydrological applicability in South Korea.