• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.5B
• /
• pp.453-461
• /
• 2009

In this study, a dynamic numerical model, FLDWAV, is used for analyzing the backwater effect of flood stage in YeongWeol station, which is located on the confluence upstream where Pyeongchang river joins Han river. Given various inflow discharges of both main stream and tributary, the feasible stage-discharge relationships at the YeongWeol station and the upstream range of the backwater effect were computed. The results show that the relationships are completely different according to each of the inflow discharges from tributary and the maximum difference of stage is about 4.0 m. Therefore, the development of a single relationship of stage and discharge is very difficult problem in the zone of backwater effect. The increase of stage in the junction due to the lateral inflow has an effect on upstream stage up to about 8.0 km. The well-calibrated and verified dynamic wave routing model will be a useful tool for the flood forecast in the zone of backwater effect rather than conventional hydrological routing model.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.09a
• /
• pp.709-710
• /
• 2005

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.09a
• /
• pp.795-796
• /
• 2005

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.09b
• /
• pp.1220-1221
• /
• 2005

• Journal of Korea Water Resources Association
• /
• v.44 no.7
• /
• pp.523-536
• /
• 2011

The objective of this study is to develop the data driven model for the flood forecasting that are improved the problems of the existing hydrological model for flood forecasting in medium and small streams. Neuro-Fuzzy flood forecasting model which linked the Takagi-Sugeno fuzzy inference theory with neural network, that can forecast flood only by using the rainfall and flood level and discharge data without using lots of physical data that are necessary in existing hydrological rainfall-runoff model is established. The accuracy of flood forecasting using this model is determined by temporal distribution and number of used rainfall and water level as input data. So first of all, the various combinations of input data were constructed by using rainfall and water level to select optimal input data combination for applying Neuro-Fuzzy flood forecasting model. The forecasting results of each combination are compared and optimal input data combination for real-time flood forecasting is determined.

• Korean Journal of Agricultural Science
• /
• v.46 no.4
• /
• pp.843-856
• /
• 2019

Real-time flood prediction has an important role in significantly reducing potential damage caused by floods for urban residential areas located downstream of river basins. This paper presents an effective approach for flood forecasting based on the construction of a deep neural network (DNN) model. In addition, this research depends closely on the open-source software library, TensorFlow, which was developed by Google for machine and deep learning applications and research. The proposed model was applied to forecast the flowrate one, two, and three days in advance at the Son Tay hydrological station on the Red River, Vietnam. The input data of the model was a series of discharge data observed at five gauge stations on the Red River system, without requiring rainfall data, water levels and topographic characteristics. The research results indicate that the DNN model achieved a high performance for flood forecasting even though only a modest amount of data is required. When forecasting one and two days in advance, the Nash-Sutcliffe Efficiency (NSE) reached 0.993 and 0.938, respectively. The findings of this study suggest that the DNN model can be used to construct a real-time flood warning system on the Red River and for other river basins in Vietnam.

• Journal of Korea Water Resources Association
• /
• v.48 no.3
• /
• pp.197-207
• /
• 2015

Modification of travel time is necessary in all Nakdong river basin because hydrological conditions of Nakdong river basin were changed after major rivers project. Also calculation of flood travel time at between sections of weirs is necessary. In this study, flood travel time was calculated using hydraulic model and the latest topographical data from Changnyeong-Haman weir to Nakdong river estuary bank. Analysis of discharge and stage conditions were carried out. 84 of the scenarios were organized according to flow rate, discharge type, boundary conditions, and tributary conditions. Flood travel time of initial and peak were calculated with discharge and stage conditions, respectively. The results of this study will be available in practical business work such as flood forecast warning and weir operation on algae removal.

• International Journal of Computer Science & Network Security
• /
• v.21 no.5
• /
• pp.23-30
• /
• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• Atmosphere
• /
• v.32 no.4
• /
• pp.395-409
• /
• 2022

A new soil moisture initialization scheme is applied to the Korea Meteorological Administration (KMA) Global Seasonal forecasting system version 6 (GloSea6). It is designed to ingest the microwave soil moisture retrievals from Soil Moisture Active Passive (SMAP) radiometer using the Local Ensemble Transform Kalman Filter (LETKF). In this technical note, we describe the procedure of the newly-adopted initialization scheme, the change of soil moisture states by assimilation, and the forecast skill differences for the surface temperature and precipitation by GloSea6 simulation from two preliminary experiments. Based on a 4-year analysis experiment, the soil moisture from the land-surface model of current operational GloSea6 is found to be drier generally comparing to SMAP observation. LETKF data assimilation shows a tendency toward being wet globally, especially in arid area such as deserts and Tibetan Plateau. Also, it increases soil moisture analysis increments in most soil levels of wetness in land than current operation. The other experiment of GloSea6 forecast with application of the new initialization system for the heat wave case in 2020 summer shows that the memory of soil moisture anomalies obtained by the new initialization system is persistent throughout the entire forecast period of three months. However, averaged forecast improvements are not substantial and mixed over Eurasia during the period of forecast: forecast skill for the precipitation improved slightly but for the surface air temperature rather degraded. Our preliminary results suggest that additional elaborate developments in the soil moisture initialization are still required to improve overall forecast skills.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2004.05b
• /
• pp.790-793
• /
• 2004

TM/TC system is composed of control center, reservoirs, pumping stations and twelve canal systems. For this system we developed water management program which includes flood forecast program, drought reduction program, irrigation scheduling program and database program. With these program we expect that operators improve the irrigation efficiencies of the irrigation systems due to the timely irrigation on a right place, in a proper quantity and refute tile cost of maintenance and reduce flood and drought damages. In agricultural engineering respect, the databases including water level, rainfall, the amount of flowing can be useful to the researcher who make a study of hydrology and hydraulics in . rural area. Water management program records all of the TM/TC data to MDB format file per 10 minutes.