• Journal of Korea Water Resources Association
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• v.35 no.3
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• pp.275-284
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• 2002

In this study, a method of random resampling of residuals from stochastic models such as the Monte-Carlo model, the lag-one autoregressive model(AR(1)) and the periodic lag-one autoregressive model(PAR(1)), has been adopted to generate a large number of long traces of annual and monthly steamflows. Main advantage of this resampling scheme called the Bootstrap method is that it does not rely on the assumption of population distribution. The Bootstrap is a method for estimating the statistical distribution by resampling the data. When the data are a random sample from a distribution, the Bootstrap method can be implemented (among other ways) by sampling the data randomly with replacement. This procedure has been applied to the Yongdam site to check the performance of Bootstrap method for the streamflow generation. and then the statistics between the historical and generated streamflows have been computed and compared. It has been shown that both the conventional and Bootstrap methods for the generation reproduce fairly well the mean, standard deviation, and serial correlation, but the Bootstrap technique reproduces the skewness better than the conventional ones. Thus, it has been noted that the Bootstrap method might be more appropriate for the preservation of skewness.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.137-137
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• 2021

In this study we aimed to enhance streamflow prediction skill of a land-surface hydrological model, WRF-Hydro, over one of the snow dominated catchments lies in Himalayan mountainous range, Astore. To assess the response of the Himalayan river flows to climate change is complex due to multiple contributors: precipitation, snow, and glacier melt. WRF-Hydro model with default glacier module lacks generating streamflow in summer period but recently developed WRF-Hydro-CROCUS model overcomes this issue by melting snow/ice from the glaciers. We showed that by implementing WRF-Hydro-CROCUS model over Astore the results were significantly improved in comparison to WRF-Hydro with default glacier module. To constraint the model with the observed streamflow we chose 17 sensitive parameters of WRF-Hydro, which include groundwater parameters, surface runoff parameters, channel parameters, soil parameters, vegetation parameters and snowmelt parameters. We used Dynamically Dimensioned Search (DDS) method to calibrate the daily streamflow with the Nash-Sutcliffe efficiency (NSE) being greater than 0.7 both in calibration (2009-2010) and validation (2011-2013) period. Based on the number of iterations per parameter, we found that the parameters related to channel and runoff process are most sensitive to streamflow. The attempts to address the responses of the streamflows to climate change are still very weak and vague especially northwest Himalayan Part of Pakistan and this study is one of a few successful applications of process-based land-surface hydrologic model over this mountainous region of UIB that can be utilized to have an in-depth understanding of hydrological responses of climate change.

• The Journal of Engineering Geology
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• v.34 no.2
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• pp.263-277
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• 2024

The availability of groundwater in the Yeoncheon area, South Korea, was estimated using the distributed hydrological model SWAT-K to calculate recharge rates based on land use and soil distribution. Model calibration and validation results were consistent between observed and simulated streamflows, with coefficients of determination of 0.75~0.97. Calculated groundwater recharge rates varied temporospatially, with lower rates in winter and spring than in summer. Estimated recharge rates were compared with the baseflow index of natural streamflow to assess the validity of estimated recharge amounts. Groundwater development potential was determined by calculating the recharge amount for a 10-year period by statistical frequency analysis, confirming it to be 11.5% of annual precipitation.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.993-1003
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• 2023

Due to the increasing greenhouse gas emissions, the global mean temperature has risen by 1.1℃ compared to pre-industrial levels, and significant changes are expected in functioning of water supply systems. In this study, we assessed impacts of climate change and instreamflow management on water supply reliability in the Geum River basin, Korea. We proposed univariate climate response functions, where mean precipitation and potential evaporation were coupled as an explanatory variable, to assess impacts of climate stress on multiple water supply reliabilities. To this end, natural streamflows were generated in the 19 sub-basins with the conceptual GR6J model. Then, the simulated streamflows were input into the Water Evaluation And Planning (WEAP) model. The dynamic optimization by WEAP allowed us to assess water supply reliability against the 2020 water demand projections. Results showed that when minimizing the water shortage of the entire river basin under the 1991-2020 climate, water supply reliability was lowest in the Bocheongcheon among the sub-basins. In a scenario where the priority of instreamflow maintenance is adjusted to be the same as municipal and industrial water use, water supply reliability in the Bocheongcheon, Chogang, and Nonsancheon sub-basins significantly decreased. The stress tests with 325 sets of climate perturbations showed that water supply reliability in the three sub-basins considerably decreased under all the climate stresses, while the sub-basins connected to large infrastructures did not change significantly. When using the 2021-2050 climate projections with the stress test results, water supply reliability in the Geum River basin was expected to generally improve, but if the priority of instreamflow maintenance is increased, water shortage is expected to worsen in geographically isolated sub-basins. Here, we suggest that the climate response function can be established by a single explanatory variable to assess climate change impacts of many sub-basin's performance simultaneously.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.20-30
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• 2008

This study is to analyse the hydrological behavior of agricultural reservoir using SWAT model. For the upsteam watershed of Gongdo water level gauge station in Anseongcheon watershed, the streamflows at 2 reservoir (Gosam and Geumgwang) locations and Gongdo station were simulated with reservoir inclusion and exclusion. The daily water surface area and storage have been calculated considering the stage-storage curve function of the reservoir. Afterwards, the reservoir operation module in SWAT was modified from original module in SWAT for daily reservoir discharge simulated by water balance equation. Model validation results were Nash-Sutcliffe model efficiency coefficients value of 0.55, root mean square error value of 2.33 mm/day. On the other hand, the simulation results of two reservoir exclusion were Nash-Sutcliffe model efficiency coefficients value of 0.37, root mean square error value of 2.91 mm/day. The difference of Nash-Sutcliffe model efficiency coefficients between the simulation results of two reservoir inclusion and exclusion at Gongdo station was 0.18. This is caused by the storage and release operation of agricultural reservoirs for the runoff occurred at 2 reservoir watersheds.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.77-91
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• 2011

This study tries to find a streambed scouring and sedimentation characteristics through the Rosgen(1994)'s stream classification system while experiencing several flood events. The Jinwee and Osan streams, the tributaries of Anseongcheon were selected. The streams showed type C or type E. By the classification results, two Type C tributaries one Type C stream and one Type E tributary were selected. For the four selected stream reaches, the analysis of streambed change was implemented by using numerical model CCHE2D (Center for Computational Hydroscience and Engineering). To prepare the inlet boundary conditions of each stream, the WMS (Watershed Modeling System) HEC-1 was used and the streamflows of 50, 80, and 100-year return period were generated and the outlet boundary was set to an open boundary condition. The simulation results showed that when the flood pulse periodically the streambed changes also appears regularly. The results can be used to acquire the basic data for stream restoration.

• Korean Journal of Ecology and Environment
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• v.40 no.1
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• pp.155-162
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• 2007

Water balance is the major factor in forest ecosystem, and is closely related to the vegetation and topographic characteristics within a watershed. The hydrologic response of a forest watershed was investigated with the hydrological model. The deterministic, lumped parameter model (BROOK90) was selected and used to evaluate the applicability of the model for simulating daily runoff on the steep, forested watershed. The model was calibrated and validated against the streamflow data measured at the Bukmoongol watershed. The deviation in runoff volume $(D_v)$ was -1.7% for the calibration period, and the $D_v$ value for the validation period was 4.6%. The correlation coefficient (r) and model efficiency (E) on monthly basis were 0.922,0.847, respectively, for the calibration period, while the r- and E-value for the validation period were 0.941, 0.871, respectively. Overall, the simulated streamflows were close to the observations with respect to total runoff volume, seasonal runoff volume, and baseflow index for the simulation period. BROOK90 model was able to reproduce the trend of runoff with higher correlation during the simulation period.

• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.481-493
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• 2012

The Uncertainty of drought events can be regarded as supernatural phenomena so that the uncertainty of water supply system will be also uncontrollable. Decision making for water supply system operation must be dealt with in consideration of hydrologic uncertainty conditions. When ultimate small quantity of precipitation or streamflow lasts, water supply system might be impacted as well as stream pollution, aqua- ecosystem degradation, reservoir dry-up and river aesthetic waste etc. In case of being incapable of supplying water owing to continuation of severe drought, it can make the damage very serious beyond our prediction. This study analyzes comprehensively sustained drought impacts on the Han River Basin Water Supply System. Drought scenarios consisted of several sustained times and return periods for 5 sub-watersheds are generated using a stochastic hydrologic time series model. The developed drought scenarios are applied to assess water supply performance at the Paldang Dam. The results show that multi-year drought events reflecting spatial hydrologic diversity need to be examined in order to recognize variation of the unexpected drought impacts.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.694-698
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• 2008

In hydrology, it is a difficult task to deal with multivariate time series such as modeling streamflows of an entire complex river system. Normal distribution based model such as MARMA (Multivariate Autorgressive Moving average) has been a major approach for modeling the multivariate time series. There are some limitations for the normal based models. One of them might be the unfavorable data-transformation forcing that the data follow the normal distribution. Furthermore, the high dimension multivariate model requires the very large parameter matrix. As an alternative, one might be decomposing the multivariate data into independent components and modeling it individually. In 1985, Lins used Principal Component Analysis (PCA). The five scores, the decomposed data from the original data, were taken and were formulated individually. The one of the five scores were modeled with AR-2 while the others are modeled with AR-1 model. From the time series analysis using the scores of the five components, he noted "principal component time series might provide a relatively simple and meaningful alternative to conventional large MARMA models". This study is inspired from the researcher's quote to develop a multivariate simulation model. The multivariate simulation model is suggested here using Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Three modeling step is applied for simulation. (1) PCA is used to decompose the correlated multivariate data into the uncorrelated data while ICA decomposes the data into independent components. Here, the autocorrelation structure of the decomposed data is still dominant, which is inherited from the data of the original domain. (2) Each component is resampled by block bootstrapping or K-nearest neighbor. (3) The resampled components bring back to original domain. From using the suggested approach one might expect that a) the simulated data are different with the historical data, b) no data transformation is required (in case of ICA), c) a complex system can be decomposed into independent component and modeled individually. The model with PCA and ICA are compared with the various statistics such as the basic statistics (mean, standard deviation, skewness, autocorrelation), and reservoir-related statistics, kernel density estimate.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.144-159
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• 2006

Hydrological models are tools intended to realistically represent the basin's complex system in which hydrological characteristics result from a number of physical, vegetative, climatic, and anthropomorphic factors. Spatially distributed hydrological models were first developed in the 1960s, Remote sensing(RS) data and Geographical Information System(GIS) play a rapidly increasing role in the field of hydrology and water resources development. Although very few remotely sensed data can applied in hydrology, such information is of great. One of the greatest advantage of using RS data for hydrological modeling and monitoring is its ability to generate information in spatial and temporal domain, which is very crucial for successful model analysis, prediction and validation. In this paper, SLURP model is selected as semi-distributed hydrological model and MODIS Leaf Area Index(LAI), Normalized Difference Vegetation Index(NDVI) as Remote sensing input data to hydrological modeling of Kyung An-chen basin. The outlet of the Kyung An stage site was simulated, We evaluated two RS data, based on ability of SLURP model to simulate daily streamflows, and How the two RS data influence the sensitivity of simulated Evapotranspiration.