• Journal of Environmental Science International
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• v.16 no.7
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• pp.805-811
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• 2007

The purpose of this study was to invesitigate relationship between rainfall water quality and precipitation characteristic during the accumulated rainfall and rainless period. As the results of the analysis, rainfall water quality was improved in the rainfall duration. Correlation coefficients between rainwater quality and accumulated rainfall were $0.88{\sim}0.99$ except $Cl^-$. and that between rainless period and initial rainfall water quality were $0.62{\sim}0.75$. During the Asian dust event, concentration of the turbidity, BOD and electric conductivity were high. Therefore, it shows that the rainfall water quality is effected by atmospheric conditions before the rainfall events.

• East Asian Economic Review
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• v.27 no.4
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• pp.273-301
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• 2023

This study investigates the impacts of long-term climate variability on household consumption in Indonesia, a country highly vulnerable to climate change. The analysis combines household survey data from nearly 5,998 families with satellite-derived weather data from NASA POWER spanning 30 years. We use the long-term variability in temperature and precipitation as a proxy for climate change. This study examines the impact of climate change which proceeds over the long term, unlike previous studies concerning one-off or short-term climate events. In addition, using satellite data enhances the accuracy of households' exposure to climate variability. The analysis finds that households in a village with higher temperature and precipitation variability significantly consume less food. This implies that households more exposed to climate change are at higher risk of malnutrition in developing countries. This study has a limitation that it cannot rule out the potential endogeneity of choosing a climate-vulnerable residential location due to economic poorness.

• Journal of Astronomy and Space Sciences
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• v.32 no.4
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• pp.317-325
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• 2015

Energy spectra of electron microbursts from 170 keV to 340 keV have been measured by the solid-state detectors aboard the low-altitude (680 km) polar-orbiting Korean STSAT-1 (Science and Technology SATellite). These measurements have revealed two important characteristics unique to the microbursts: (1) They are produced by a fast-loss cone-filling process in which the interaction time for pitch-angle scattering is less than 50 ms and (2) The e-folding energy of the perpendicular component is larger than that of the parallel component, and the loss cone is not completely filled by electrons. To understand how wave-particle interactions could generate microbursts, we performed a test particle simulation and investigated how the waves scattered electron pitch angles within the timescale required for microburst precipitation. The application of rising-frequency whistler-mode waves to electrons of different energies moving in a dipole magnetic field showed that chorus magnetic wave fields, rather than electric fields, were the main cause of microburst events, which implied that microbursts could be produced by a quasi-adiabatic process. In addition, the simulation results showed that high-energy electrons could resonate with chorus waves at high magnetic latitudes where the loss cone was larger, which might explain the decreased e-folding energy of precipitated microbursts compared to that of trapped electrons.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.804-806
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• 2003

Probable Maximum Precipitation (PMP) is essential in the design of hydraulic structures such as dams, weirs and flood control structures. Up to the present, PMP has been derived from any proper single storm which can have a large error. PMP values should be evaluated from many historic heavy storm events from all over the country. Since this can be done at the spots of storm occurring and the calculated PMP from all spots in the country can be correlated. The objectives of this study are therefore to evaluate PMP from historic heavy storm data from 1972 to 2000 by using meteorological method, then to correlate and to present the results using GIS. The maximized rainfall depths can be calculate from depth of heavy rainfall and dew point temperature, and then can be analyzed for each rainfall duration to obtain spatial rainfall distribution by using GIS. The depth-area-duration relationship of maximized rainfall can be obtained and this helps to develop enveloped curves . The results from this study are a set of contour maps of PMP for each rainfall duration for all over the country and the depth-area-duration relationships for the area of 100 to 50,000 km.$^{2}$ at duration of 1, 2 and 3 days.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.176-176
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• 2023

The Tonle Sap is the richest and diverseness of freshwater ecosystem in Southeast Asia, receiving nurturing water flows from the Mekong and its immediate basin. In addition, the rapid development in the Tonle Sap Lake (TSL) Basin, and flood inundation may threaten the natural diversities and characteristics. The impacts of flood inundation in 11 sub-basins contributing to the Tonle Sap Lake were assessed using the Rainfall-Runoff-Inundation (RRI) model to quantify the potential magnitude and extent of the flooding. The RRI model is set up by using gauged rainfall data to simulate the information of river discharge and flood inundation of huge possible flood events. Moreover, two satellite precipitation products (SPPs), CHIRPS and GSMaP, within respectively spatial resolutions of 0.05° and 0.1°, are utilized as an input for the RRI model to simulate river discharge, flood depth, and flood extent for the great TSL Basin of Cambodia. This study used statistical indicators such as NSE, PBIAS, RSR, and R2 as crucial indices to evaluate the performance of the RRI model. Therefore, the findings of this study could provide promising guidance in hydrological modeling and the significant implications for flood risk management and disaster preparedness in the region.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.37-49
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• 2023

Rainfall data is one of the most important data in hydrologic modeling. In this study, the impacts of spatial resolution of precipitation data on hydrological responses were assessed using SWAT in the Santa Fe River Basin, Florida. High correlations were found between the FAWN and NLDAS rainfall data, which are observed weather data and simulated weather data based on observed data, respectively. FAWN-based scenarios had higher maximum rainfall and more rainfall days and events compared to NLDAS-based scenarios. Downstream areas showed lower correlations between rainfall and peak discharge than upstream areas due to the characteristics of study site. All scenarios did not show significant differences in base flow, and showed less than 5% of differences in high flows among NLDAS-based scenarios. The impact of resolution will appear differently depending on the characteristics of the watershed and topography and the applied model, and thus, is a process that must be considered in advance in runoff simulation research. The study suggests that applying the research method to watersheds in Korea may yield more pronounced results, and highlights the importance of considering data resolution in hydrologic modeling.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1669-1679
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• 2020

This study examines the washing effect of precipitation on particulate matter (PM) and the rainwater quality (pH, electrical conductivity (EC), water-soluble ions concentration). Of six rain events in total, rainwater samples were continuously collected every 50 mL from the beginning of the precipitation using rainwater collecting devices at Pukyong National University, Busan, South Korea, from March 2020 to July 2020. The collected rainwater samples were analyzed for pH, EC, and water-soluble ions (cations: Na+, Mg2+, K+, Ca2+, NH4+, and anions: Cl-, NO3-, SO42-). The concentrations of particulate matter were continuously measured during precipitation events with a custom-built PM sensor node. For initial rainwater samples, the average pH and EC were approximately 4.3 and 81.9 μS/cm, and the major ionic components consisted of NO3- (5.4 mg/L), Ca2+ (4.2 mg/L), Cl- (4.1 mg/L). In all rainfall events, rainwater pH gradually increased with rainfall duration, whereas EC gradually decreased due to the washing effect. When the rainfall intensities were relatively weak (<5 mm/h), PM10 reduction efficiencies were less than 40%. When the rainfall intensities were enhanced to more than 7.5 mm/h, the reduction efficiencies reached more than 60%. For heavy rainfall events, the acidity and EC, as well as ions concentrations of initial rainwater samples, were higher than those in later samples. This appears to be related to the washing effect of precipitation on PM10 in the atmosphere.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.4
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• pp.1-8
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• 2002

Comparison between the Tropical Rainfall Measuring Mission(TRMM)/Precipitation Radar(PR) and the C-band doppler radar at Cheju, Kunsan and Pusan, operated by the Korean Meteorological Administration (KMA), is conducted for validation of the surface precipitation structure, and for calibration of KMA radar instrument. Data used in validation was selected for seven rain events in the south region of about $36^{\circ}N$ and at TRMM overflight in Korea, during the summer season of 2000. Quantitatively comparing radar reflectivities from two different platforms that have different view angles, bandwidths and frequencies is a challenging task. For the comparison, the precipitation patterns are projected on the same area for TRMM PR. Through the comparison, it is realized that the reflectivity from ground-based radar is under estimated, compared to TRMM/PR observations. We discuss that is underestimation may be produced by many factors(system performance, topography, etc).

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.1017-1028
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• 2009

NSRPM (Neyman-Scott Rectangular Pulse Model) is one of the common model for generating future precipitation time series in stochastical hydrology. There are 5 parameters to compose the NSRPM model for generating precipitation time series. Generally parameter estimation using moment has some problems related with increased objective functions and shows different results in accordance with random variable generating models. In this study, direct parameter estimation method was proposed to cover with disadvantages of parameter estimation using moment. To apply the direct parameter estimation, generating stochastical data variance in accordance with numbers of precipitation events of NSRPM was done. Both kinds of methods were applied at the Cheongju gauge station data. Precipitation time series were generated using 4 different random variable generator, and compared with observed time series to check the accuracies. As a results, direct method showed more stable and better results.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.225-236
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• 2020

It is not easy to provide sufficient lead time for flood forecast in urban and small mountain basins using on-ground rain gauges, because the time concentration in those basins is too short. In urban and small mountain basins with a short lag-time between precipitation and following flood events, it is more important to secure forecast lead times by predicting rainfall amounts. The Han River Flood Control Office (HRFCO) in South Korea produces short-term rainfall forecasts using the Mcgill Algorithm for Precipitation-nowcast by Lagrangian Extrapolation (MAPLE) algorithm that converts radar reflectance of rainfall events. The Flash Flood Research Center (FFRC) in the Korea Institute of Civil Engineering and Building Technology (KICT) installed a flash flood forecasting system using the short-term rainfall forecast data produced by the HRFCO and has provided flash flood information in a local lvel with 1-hour lead time since 2019. In this study, we addressed the flash flood forecasting system based on the radar rainfall and the assessed the accuracy of the forecasting system for the recorded flood events occurred in 2019. A total of 31 flood disaster cases were used to evaluate the accuracy and the forecast accuracy was 90.3% based on the probability of detection.