Flooding from torrential rain occurs in a short amount of time, while drought lasts for a longer period; the former may inflict huge losses in terms of both life and property. For these reasons, considerable research has been performed in the field of flood control system development. A physical model is mainly used for flood forecasting and warning. However, physical rainfall-runoff models for the conventional flood forecasting process require extensive information and data, and include uncertainties that can accumulate errors during the modeling process. On the other hand, ANFIS, which is a data-driven model combining the neural network and fuzzy techniques, can decrease the amount of physical data required for the construction of a conventional model and easily construct and evaluate a flood forecasting model using only rainfall and water level data. However, data-driven models have the disadvantage that they do not provide mathematical and physical logic, so that there are no logical correlations between the input and output data of the model. This study analyzes the characteristics of a data-driven model, ANFIS, according to its functional options and input data, such as changes in the clustering radius and the training data length. In addition, the suitability of ANFIS is evaluated through comparison with the results of HEC-HMS, which is widely used for rainfall-runoff models. In this study, the neuro-fuzzy technique is applied to the Cheongmicheon Basin using the observed precipitation and stream level data from 2008 to 2011.

Although available water resources are limited, water demand is continuously increasing due to population increases, economic development, and additional uses, such as recreational and environmental uses. Constructing new reservoirs has traditionally been the approach to develop new water resources. However, such construction can be hampered by negative perceptions, adverse environmental effects, and opposition from NGOs to dam construction. Although Andong and Imha reservoirs are located close to each other, and they have similar hydrological and meteorological characteristics, the storage capacity of Imha reservoir is only about half that of Andong reservoir. This makes the operation of both reservoirs inefficient. This paper evaluates the effect of a diversion tunnel connecting Andong and Imha in the flood season. Water yield and spillway release reduction capability with 95% reliability were analyzed using historical daily inflows data for 30 years. By changing the reservoir operation methods, the reservoir system performance was evaluated. The system operation of the reservoirs with the diversion tunnel showed better results than the individual operation.

In the conventional flood forecasting process, a rainfall-runoff model is used to predict runoff at a specific location. However, the process of determining the required parameters for the model is sometimes very complicated and requires extensive information and data. In addition, considerable amount of uncertainties may be included during the parameter estimation processes. Errors can occur during the pre-processing and main processing stages of the modeling, and errors from each step accumulate into the model result. In this study, a neuro-fuzzy technique is used to minimize the amount of uncertainties included in a conventional flood forecasting model for more accurate forecasting of floods. The adaptive neuro-fuzzy inference system (ANFIS), which is a data-driven model that combines a neural network and the fuzzy technique, can decrease the amount of physical data required for constructing a conventional model. By using only rainfall and water level data, ANFIS can easily construct and evaluate a flood forecasting model. Furthermore, the model construction process is relatively simple, and reliable results can be efficiently obtained in a reasonably short time once the model is developed. The developed model is applied to the Tancheon basin in Korea. The water level at the Daegok Bridge, which is located downstream of Tancheon, is forecast by the neuro-fuzzy method. The applicability and suitability of the model are studied by comparing the result with the observed stream level data from 2007 to 2011 in the Tancheon basin area. Tancheon is a tributary of the Han River and begins from the city of Yongin in Gyeonggi-do. It has a total length of 35.6 km and an area of 302 km 2 . The water level data from t + 1 to t + 18 is estimated by ANFIS using 10-min interval data. The results showed that the average height error was 24.48% and the average RMSE was 0.367 m.

The rainfall characteristics is changing in Korea due to a climate change and global warming occurring all over the world. Because mean annual precipitation is increasing while the total precipitation days are decreasing, ultimately the rainfall intensity is increasing. Considerable losses are expected because of abnormal floods. Accordingly, it is necessary to establish the reasonable countermeasures to cope with disaster due to a climate change by suggesting diverse alternatives. The goals of this study are to assess the vulnerability for abnormal floods, to analyze the disaster decrease capability by applying the diverse disaster prevention alternatives, and to derive the suitable alternative. The South Han River Basin selected as a test basin controls floods only with Chungju multi-purpose reservoir and levee. Since the flood control capacity of Chungju reservoir seems not to be sufficient compared to its large catchment area, the operation of Chungju reservoir may affect the state of flood damages in the upstream and downstream of the reservoir. The flood discharge close to the design flood occurred at Yeoju bridge, which is the one of the main control points in the test basin, from July of 2006 storm. That shows the weakness for flood protection in the test basin. Accordingly, the flood event of 2006 is analyzed and the storm events equivalent to 1 ~ 1.5 times are simulated for the basin vulnerability. Finally, the flood decrease alternatives are established based on the analyzed flood vulnerability and the capability of flood management is assessed for each alternative in case of PMF occurrence in Chungju reservoir basin. The results show that the development of a new reservoir, one of the structural methods is the most efficient alternative if the suitable reservoirs system operation is accomplished.

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