• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.2
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• pp.39-52
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• 2020

A high quality, long-term, high-resolution precipitation dataset is an essential in climate analyses and global water cycles. Rainfall data from station observations are inadequate over many parts of the world, especially North Korea, due to non-existent observation networks, or limited reporting of gauge observations. As a result, satellite-based rainfall estimates have been used as an alternative as a supplement to station observations. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and global coverage. CHIRPS is a global precipitation product and is made available at daily to seasonal time scales with a spatial resolution of 0.05° and a 1981 to near real-time period of record. In this study, we analyze the applicability of CHIRPS data on the Korean Peninsula by supplementing the lack of precipitation data of North Korea. We compared the daily precipitation estimates from CHIRPS with 81 rain gauges across Korea using several statistical metrics in the long-term period of 1981-2017. To summarize the results, the CHIRPS product for the Korean Peninsula was shown an acceptable performance when it is used for hydrological applications based on monthly rainfall amounts. Overall, this study concludes that CHIRPS can be a valuable complement to gauge precipitation data for estimating precipitation and climate, hydrological application, for example, drought monitoring in this region.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.178-182
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• 2005

In the forthcoming 21C, the development of cultural lives depends on that the water demand will increase or not. On the opposite site of that circumstance, many factors of the small watersheds will influence directly on how to cover the surface of watersheds with land use, no planning developing watersheds, and the rearrangement of small rivers. Especially as the extraordinary climatic Phenomena, exhaust of $CO_2$ and destruction of 03 layer, water resource and water foresting content of the small watersheds will be decreased by confusing on the malting a plan of water resources. For example, those are Typhoon Rusa in 2002, Typhoon Maemi in 2003 and heavy storms in 2004. This study area has three group and one of them having three small watersheds, total five small watersheds. That is, Sabukmyeon small watersheds in Chuncheon, Three small watersheds in Wonju(Jeoncheon, Jupocheon and Hasunamcheon), and Suipcheon in Yanggu-Gun which are located far away each other three group and different precipitation data. According to the land use such as dry field(or farm), rice field, forest land. building site and others in small watersheds, the amount of runoff will be impacted by monthly precipitation. The comparison between the runoff was getting from Kajiyama Formula and calculated runoff from multi-linear regressed equations by land use Percentage was performed with different precipitation data and different small watersheds. Its correlations which are estimated by coefficient of correlation will be accepted or not, as approached 1.0000 values. As the monthly water resources amount is estimated by multi-linear regressed equations with different precipitation data and different small watersheds having no gauging station, we make a plan in order to demand and supply the water quantity from small river watersheds during return periods.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.29-37
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• 2017

In this study, we analyzed the impacts of land surface characteristics on spatially and temporally distributed soil moisture values at the Yongdam and Soyang-river dam watersheds in 2014 and 2015. The soil moisture, NDVI (Normalized Difference Vegetation Index) and temperature values at the spatio-temporal scales were estimated using satellite-based MODIS (MODerate Resolution Imaging Spectroradiometer) products. Then the Pearson correlations between soil moisture and land surface characteristics (NDVI, temperature and DEM-digital elevation model) were estimated and analyzed, respectively. Overall, the monthly soil moisture values at the time step were highly influenced by the precipitation amounts. Also, the results showed that the soil moisture has the strong correlation with DEM while the temperature was inversely correlated with the soil moisture. However the monthly correlations between NDVI and soil moisture were highly varied along the time step. These findings indicated that water loss near the land surface are highly occurred by soil and plant activities as evapotranspiration and infiltration during the no/less precipitation period. But the high precipitation amounts reduce the impacts of land surface characteristics because of saturated condition of land surface. Thus these results demonstrated that soil moisture values are highly correlated with land surface characteristics. Our findings can be useful for water resources/environmental management, agricultural drought, etc.

• Journal of Climate Change Research
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• v.7 no.4
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• pp.397-405
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• 2016

For better understand of the soil respiration characteristic in ecosystem, it is necessary to accurately determine the daily, monthly and seasonal $CO_2$ flux related to various environmental factors. In general, soil respiration is being measured on a sunny day. But soil respiration is known to be affected by soil temperature and soil moisture content. In case of forestry, changes in soil moisture content are entirely dependent on rainfall. If we calculated the monthly soil respiration measured based on sunny days data only, it could be a factor that loses credibility soil respiration. On this study, we measured soil respiration on Pinus koraiensis plantation at Mt. Taehwa of Gwangju, Gyeonggi-do on sunny and rainy days in 2012, using Automatic Open-Closed Chamber system (AOCC) and portable $CO_2$ analyzer (GMP343). Then we computed the regression equations using sunny days data, precipitation less than 10 mm data, and precipitation over 10 mm data. At first, there were no significant differences in observed data and computed data. But less than 10 mm precipitation, computed data was 26.5% lower than observed data. Precipitation over 10 mm, on the other hand, the former was 29.3% higher than the latter. In each case, it showed significant differences between observed and computed data (p<0.05). So if we computed regression equation using soil respiration measured sunny days only, about 30% of annual soil respiration could be overestimated. Through further study, we suggest the subdivision and computation of regression equation on the basis of the rainfall intensity.

• Journal of the Korean earth science society
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• v.43 no.4
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• pp.539-556
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• 2022

In the coastal areas of Jeju Island, composed of volcanic rocks, saltwater intrusion occurs due to excessive pumping and geological characteristics. Groundwater level and electrical conductivity (EC) in multi-depth monitoring wells in coastal areas were characterized from 2005 to 2019. During the period of the lowest monthly precipitation, from November 2017 until February 2018, groundwater level decreased by 0.32-0.91 m. During the period of the highest monthly precipitation, from September 2019 until October 2019, groundwater level increased by 0.46-2.95 m. Groundwater level fluctuation between the dry and wet seasons ranged from 0.79 to 3.73 m (average 1.82 m) in the eastern area, from 0.47 to 6.57 m (average 2.55 m) in the western area, from 0.77 to 8.59 m (average 3.53 m) in the southern area, and from 1.06 to 12.36 m (average 5.92 m) in the northern area. In 2013, when the area experienced decreased annual precipitation, at some monitoring wells in the western area, the groundwater level decreased due to excessive groundwater pumping and saltwater intrusion. Based on EC values of 10,000 ㎲/cm or more, saltwater intrusion from the coastline was 10.2 km in the eastern area, 4.1 km in the western area, 5.8 km in the southern area, and 5.7 km in the northern area. Autocorrelation analysis of groundwater level revealed that the arithmetic mean of delay time was 0.43 months in the eastern area, 0.87 months in the northern area, 10.93 months in the southern area, and 17.02 months in the western area. Although a few monitoring wells were strongly influenced by nearby pumping wells, the cross-correlation function of the groundwater level was the highest with precipitation in most wells. The seasonal autoregressive integrated moving average model indicated that the groundwater level will decrease in most wells in the western area and decrease or increase in different wells in the eastern area.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.366-372
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• 2019

The PRISM model has been used to estimate precipitation in South Korea where observation data are readily available at a large number of weather station. However, it is likely that the PRISM model would result in relatively low reliability of precipitation estimates in North Korea where weather data are available at a relatively small number of weather stations. Alternatively, a hybrid method has been developed to estimate the precipitation distribution in area where availability of climate data is relatively low. In the hybrid method, Regression coefficients between the precipitation-terrain relationships are applied to a low-resolution precipitation map produced using the PRISM. In the present study, a hybrid approach was applied to North Korea for estimation of precipitation distribution at a high spatial resolution. At first, the precipitation distribution map was produced at a low-resolution (2,430m) using the PRISM model. Secondly, a deviation map was prepared calculating difference between altitudes of synoptic stations and virtual terrains produced using 270m-resolution digital elevation map (DEM). Lastly, another deviation map of precipitation was obtained from the maps of virtual precipitation produced using observation data from the synoptic weather stations and both synoptic and automated weather station (AWS), respectively. The regression equation between precipitation and terrain was determined using these deviation maps. The high resolution map of precipitation distribution was obtained applying the regression equation to the low-resolution map. It was found that the hybrid approach resulted in better representation of the effects of the terrain. The precipitation distribution map for the hybrid approach had similar spatial pattern to that for the existing method. It was estimated that the mean annual cumulative precipitation of entire territory of North Korea was 1,195mm with a standard deviation of 253mm.

• Communications for Statistical Applications and Methods
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• v.16 no.5
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• pp.851-858
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• 2009

In the last decades, there has been much interest in climate variability because its change has dramatic effects on humanity. Especially, the precipitation data are measured over space and their spatial association is so complicated. So we should take into account such a spatial dependency structure while analyzing the data. However, in linear models for analyzing the data, data sets show severely skewed distribution. In the paper, we consider the Box-Cox transformation to satisfy the normal distribution prior to the analysis, and employ a Bayesian hierarchical framework to investigate the spatial patterns. The data set we considered is monthly average precipitation of the third quarter of 2007 obtained from 347 automated monitoring stations in Contiguous South Korea.

• Atmosphere
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• v.18 no.2
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• pp.83-95
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• 2008

In this study we have investigated the preceding eighteen large-scale climate indices with a lead time from zero to twelve months that have an influence on the variability of temperature and precipitation in Korea in order to understand which climate indices are overall available as predictors for long-range forecasting. We also have studied the dynamic link between preceding large-scale climate indices and regional climate using singular value decomposition analysis (SVDA) and correlation analysis (CA). Based on the coupled mode between large-scale circulation and regional climate, and correlation pattern between the preceding large-scale climate indices and large-scale circulation, the level of significance on climate indices as a predictor for monthly mean temperature and precipitation was evaluated for 5 and 1% level.