• Journal of Korea Water Resources Association
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• v.50 no.4
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• pp.253-261
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• 2017

A lot of nonstationary frequency analyses have been studied in recent years as the nonstationarity occurs in hydrologic time series data. In nonstationary frequency analysis, various forms of probability distributions have been proposed to consider the time-dependent statistical characteristics of nonstationary data, and various methods for parameter estimation also have been studied. In this study, we aim to introduce a parameter estimation method for nonstationary Gumbel distribution using ensemble empirical mode decomposition (EEMD); and to compare the results with the method of maximum likelihood. Annual maximum rainfall data with a trend observed by Korea Meteorological Administration (KMA) was applied. As a result, both EEMD and the method of maximum likelihood selected an appropriate nonstationary Gumbel distribution for linear trend data, while the EEMD selected more appropriate nonstationary Gumbel distribution than the method of maximum likelihood for quadratic trend data.

• Agribusiness and Information Management
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• v.9 no.2
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• pp.1-11
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• 2017

Introduction: To analyze the impact of marketing losses on efficiency in transacting banana in Kurnool district of SRZ in Andhra Pradesh and to assess the opinions of the farmers on the constraints in transacting banana. Research back ground, Materials and Methods: The study relies exclusively on primary information obtained from the banana farmers of Kurnool District. Purposive sampling procedure was followed for the selection of the study area. Top two mandals in the district and top two villages in each mandal are selected in accordance with the area under cultivation of banana. Probability proportion to size was followed regarding the selection of sample farmers and accordingly 60 marginal, 37 small and 23 other farmers were selected and thereby, the total sample size was 120. Result and Discussion: Three marketing channels were identified in the marketing of banana in Kurnool district viz., Producer ${\rightarrow}$ Local-exporter ${\rightarrow}$ Wholesaler ${\rightarrow}$ Retailer ${\rightarrow}$ Consumer (Channel-I), Producer ${\rightarrow}$ Wholesaler ${\rightarrow}$ Cart-vendor ${\rightarrow}$ Consumer (Channel-II) and Producer ${\rightarrow}$ Juice-holder ${\rightarrow}$ Consumer (Channel-III). With the inclusion of marketing losses in the price spread analysis of banana in all the three channels, the marketing costs of all the intermediaries were increased and thereby, the farmer's share in consumer's rupee and Net Marketing Margins of the agencies are on the decline. So, without inclusion of marketing losses, the farmer's share in consumer's rupee and Net Marketing Margins of all the agencies are overvalued. The higher the marketing losses, the more is the negative impact on farmer's net selling price, net marketing margins of the intermediaries and marketing efficiency. The sample farmers are facing major problems in marketing of banana like frequent price fluctuations, unorganized marketing and lack of transportation facilities on priority basis. Suggestions: It is suggested to educate the farmers regarding the optimum maturity index for harvest, use of mechanical harvesters, proper placement of fruits during storage and ripening, better packaging and cushioning technologies to absorb shocks during transportation, strengthening of storage facilities and transport facilities, encourage co-operative marketing etc., to promote marketing efficiency of banana in the study area.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.515-522
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• 2017

This study investigated the runoff characteristics containing NPS pollutants in urban areas and estimated the optimal number of storm events to be monitored. 13 residential areas, 8 commercial areas, 9 transportation areas and 11 industrial areas were selected to be monitored located in urban areas. Monitoring was performed from 2008 to 2016 with a total of 632 rainfall events. As a result, it was found that commercial area needs priority NPS management compared to other landuses because the commercial area has high runoff coefficient and NPS pollutant EMC compared with other landuses. The annual monitoring frequency for each landuse was estimated to be 11 to 14 times for industrial area, 12 to 14 times for transportation area, 11 to 13 times for commercial area and 22 to 25 times for residential area. Even with the use of accumulated monitoring data for several years, there is still high probability of uncertainty due to high error in some pollutant items, and it is necessary to establish monitoring know-how and data accumulation to reduce errors by continuous monitoring.

• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.853-865
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• 2014

Hydrologic dam risk analysis depends on complex hydrologic analyses in that probabilistic relationship need to be established to quantify various uncertainties associated modeling process and inputs. However, the systematic approaches to uncertainty analysis for hydrologic risk analysis have not been addressed yet. In this paper, two major innovations are introduced to address this situation. The first is the use of a Hierarchical Bayesian model based regional frequency analysis to better convey uncertainties associated with the parameters of probability density function to the dam risk analysis. The second is the use of Bayesian model coupled HEC-1 rainfall-runoff model to estimate posterior distributions of the model parameters. A reservoir routing analysis with the existing operation rule was performed to convert the inflow scenarios into water surface level scenarios. Performance functions for dam risk model was finally employed to estimate hydrologic dam risk analysis. An application to the Dam in South Korea illustrates how the proposed approach can lead to potentially reliable estimates of dam safety, and an assessment of their sensitivity to the initial water surface level.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.439-450
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• 2016

For the design of infrastructures controlling the flood events at ungauged basins, this study tries to find the regional flood frequencies using peak flow data generated by the spatial extension of flood records. The Chungju Dam watershed is selected to validate the possibility of regional flood frequency analysis using the spatially extended flood data. Firstly, based on the index flood method, the flood event data from the spatial extension method is evaluated for 22 mid/smaller sub-basins at the Chungju Dam watershed. The homogeneity of the Chungju dam watershed was assessed in terms of the different size of watershed conditions such as accumulated and individual sub-basins. Based on the result of homogeneity analysis, this watershed is heterogeneous with respect to individual sub-basins because of the heterogeneity of rainfall distribution. To decide the regional probability distribution, goodness-of fit measure and weighted moving averages method from flood frequency analysis were adopted. Finally, GEV distribution was selected as a representative distribution and regional quantile were estimated. This research is one step further method to estimate regional flood frequency for ungauged basins.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.161-172
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• 2003

This study has evaluated the stream gauge network with the main emphasis on if the current stream gauge network can catch the runoff characteristics of the basin. As the evaluation of the stream gauge network in this study does not consider a special purpose of a stream gauge, nor the effect from a hydraulic structure, it becomes an optimization of current stream gauge network under the condition that each stream gauge measures the natural runoff volume. This study has been applied to the Nam-Han River Basin for the optimization of total 31 stream gauge stations using the entropy concept. Summarizing the results are as follows. (1) The unit hydrograph representing the basin response from rainfall can be transferred into a probability density function for the application of the entropy concept to optimize the stream gauge network. (2) Accurate derivation of unit hydrographs representing stream gauge sites was found the most important part for the evaluation of stream gauge network, which was assured in this research by comparing the measured and derived unit hydrographs. (3) The Nam-Han River Basin was found to need at least 28 stream gauge stations, which was derived by considering both the shape of the unit hydrograph and the runoff volume. If considering only the shape of the unit hydrograph, the number of stream gauges required decreases to 23.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.189-189
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• 2016

To generate information that contributes to climate change risk management, it is important to perform a precise assessment on the impact in diverse aspects. Considering this academic necessity, Japanese government launched continuous research project for the climate change impact assessment, and one of the representative project is Program for Risk Information on Climate Change (Sousei Program), Theme D; Precise Impact Assessment on Climate Change (FY2012 ~ FY2016). In this research program, quantitative impact assessments have been doing from a variety of perspectives including natural hazards, water resources, and ecosystems and biodiversity. Especially for the natural hazards aspect, a comprehensive impact assessment has been carried out with the worst-case scenario of typhoons, which cause the most serious weather-related damage in Japan, concerning the frequency and scale of the typhoons as well as accompanying disasters by heavy rainfall, strong winds, high tides, high waves, and landslides. In this presentation, a framework of comprehensive impact assessment with the worst-case scenario under the climate change condition is introduced based on a case study of Theme D in Sousei program There are approx. 25 typhoons annually and around 10 of those approach or make landfall in Japan. The number of typhoons may not change increase in the future, but it is known that a small alteration in the path of a typhoon can have an extremely large impact on the amount of rain and wind Japan receives, and as a result, cause immense damage. Specifically, it is important to assess the impact of a complex disaster including precipitation, strong winds, river overflows, and high tide inundation, simulating how different the damage of Isewan Typhoon (T5915) in 1959 would have been if the typhoon had taken a different path, or how powerful or how much damage it would cause if Isewan Typhoon occurs again in the future when the sea surface water temperature has risen due to climate changes (Pseudo global warming experiment). The research group also predict and assess how the frequency of "100-years return period" disasters and worst-case damage will change in the coming century. As a final goal in this research activity, the natural disaster impact assessment will extend not only Japan but also major rivers in Southeast Asia, with a special focus on floods and inundations.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.299-316
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• 2019

The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.169-177
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• 2010

Recently due to the typhoon and extreme rainfall induced by abnormal weather and climate change, the probability of severe damage to human life and property is rapidly increasing. Thus it is necessary to create adequate and reliable flood risk map in preparation for those natural disasters. The study area is Seo-gu in Daegu which is located near Geumho river, one of the tributaries of Nakdong river. Inundation depth and velocity at each time were calculated by applying FLUMEN model to the target area of interest, Seo-gu in Daegu. And the research of creating flood risk map was conducted according to the Downstream Hazard Classification Guidelines of USBR. The 2-dimensional inundation analysis for channels and protected lowland with FLUMEN model was carried out with the basic assumption that there's no levee failure against 100 year precipatation and inflow comes only through the overflowing to the protected lowland. The occurrence of overflowing was identified at the levee of Bisan-dong located in Geumho watershed. The level of risk was displayed for house/building residents, drivers and pedestrians using information about depth and velocity of each node computed from the inundation analysis. Once inundation depth map and flood risk map for each region is created with this research method, emergency action guidelines for residents can be systemized and it would be very useful in establishing specified emergency evacuation plans in case of levee failure and overflowing resulting from a flood.

• Atmosphere
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• v.34 no.3
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• pp.305-317
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• 2024

The study examines the effects of parameters that define the characteristics of raindrops on the simulated precipitation during the summer season over Korea using the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) cloud microphysics scheme. Prescribed parameters, defining the characteristics of hydrometeors in the WDM6 scheme such as a_R, b_R, and f_R in the fall velocity (V_R) - diameter (D_R) relationship and shape parameter (𝜇_R) in the number concentration (N_R) - D_R relationship, presents different values compared to the observed data from Two-Dimensional Video Disdrometer (2DVD) at Boseong standard meteorological observatory during 2018~2019. Three experiments were designed for the heavy rainfall event on August 8, 2022 using WRF version 4.3. These include the control (CNTL) experiment with original parameters in the WDM6 scheme; the MUR experiment, adopting the 50th percentile observation value for 𝜇_R; and the MEDI experiment, which uses the same 𝜇_R as MUR, but also includes fitted values for a_R, b_R, and f_R from the 50th percentile of the observed V_R - D_R relationship. Both sensitivity experiments show improved precipitation simulation compared to the CNTL by reducing the bias and increasing the probability of detection and equitable threat scores. In these experiments, the raindrop mixing ratio increases and its number concentration decreases in the lower atmosphere. The microphysics budget analysis shows that the increase in the rain mixing ratio is due to enhanced source processes such as graupel melting, vapor condensation, and accretion between cloud water and rain. Our study also emphasizes that applying the solely observed 𝜇_R produces more positive impact in the precipitation simulation.