• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.97-105
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• 2020

Recently, Artificial Neural Network receives attention as a data prediction method. Among these, a Long Shot-term Memory (LSTM) model specialized for time-series data prediction was utilized as a prediction method of hydrological time series data. In this study, the LSTM model was constructed utilizing deep running open source library TensorFlow which provided by Google, to predict inflows of multipurpose dams. We predicted the inflow of the Yongdam Multipurpose Dam which is located in the upper stream of the Geumgang. The hourly flow data of Yongdam Dam from 2006 to 2018 provided by WAMIS was used as the analysis data. Predictive analysis was performed under various of variable condition in order to compare and analyze the prediction accuracy according to four learning parameters of the LSTM model. Root mean square error (RMSE), Mean absolute error (MAE) and Volume error (VE) were calculated and evaluated its accuracy through comparing the predicted and observed inflows. We found that all the models had lower accuracy at high inflow rate and hourly precipitation data (2006~2018) of Yongdam Dam utilized as additional input variables to solve this problem. When the data of rainfall and inflow were utilized together, it was found that the accuracy of the prediction for the high flow rate is improved.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1131-1141
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• 2021

In this study, the artificial neural network model is applied for real-time dam inflow prediction and then evaluated for the prediction lead times (1, 3, 6 hr) in dam basins in Korea. For the training and testing the model, hourly precipitation and inflow are used as input data according to average annual inflow. The results show that the model performance for up to 6 hour is acceptable because the NSE is 0.57 to 0.79 or higher. Totally, the predictive performance of the model in dry seasons is weaker than the performance in wet seasons, and this difference in performance increases in the larger basin. For the 6 hour prediction lead time, the model performance changes as the sequence length increases. These changes are significant for the dry season with increasing sequence length compared to the wet season. Also, with increasing the sequence length, the prediction performance of the model improved during the dry season. Comparison of observed and predicted hydrographs for flood events showed that although the shape of the prediction hydrograph is similar to the observed hydrograph, the peak flow tends to be underestimated and the peak time is delayed depending on the prediction lead time.

• Journal of Korean Society on Water Environment
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• v.25 no.3
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• pp.441-451
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• 2009

To evaluate the soil erosion best management practices, many computer models has been utilized over the years. Among those, the USLE and SWAT models have been widely used. These models estimate the soil erosion from the field using empirically-based USLE/MULSE in it. However, these models are not good enough to estimate soil erosion from highland agricultural watershed where severe storm events are causing soil erosion and muddy water issues at the receiving watersheds. Thus, physically-based WEPP watershed version was applied to a watershed, located at Jawoon-ri, Gangwon with very detailed rainfall data, rather than daily rainfall data. Then it was validated with measured sediment data collected at the sediment settling ponds and through overland flow. In this study, very detailed rainfall data, crop management data, soil data reflecting soil reconditioned for higher crop production were used in the WEPP runs. The $R^2$ and the EI for runoff comparisons were 0.88 and 0.91, respectively. For sediment comparisons, the $R^2$ and the EI values were 0.95 and 0.91. Since the WEPP provides higher accuracies in predicting runoff and sediment yield from the study watershed, various slope scenarios (2%, 3%, 5.5%, 8%, 10%, 13%, 15%, 18%, 20%, 23%, 25%, 28%, 30%) were made and simulated sediment yield values were analyzed to develop appropriate soil erosion management practices. It was found that soil erosion increase linearly with increase in slope of the field in the watershed. However, the soil erosion increases dramatically with the slope of 20% or greater. Therefore special care should be taken for the agricultural field with slope greater than 20%. As shown in this study, the WEPP watershed version is suitable model to predict soil erosion where torrential rainfall events are causing significant amount of soil loss from the field and it can also be used to develop site-specific best management practices.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.2
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• pp.35-46
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• 2008

Soil moisture is one of the important components in hydrological processes and also controls the subsurface flow mechanism at a hillslope scale. In this study, time series of soil moisture were measured at a hillslope located in Gwangneung National Arboretum, Korea using a multiplex Time Domain Reflectometry(TDR) system measuring soil moisture with bi-hour interval. The Box-Jenkins transfer function and noise model was used to estimate spatial distributions of soil moisture histories between May and September, 2007. Rainfall was used as an input parameter and soil moisture at 10 cm depth was used as an output parameter in the model. The modeling process consisted of a series of procedures(e.g., data pretreatment, model identification, parameter estimation, and diagnostic checking of selected models), and the relationship between soil moisture and rainfall was assessed. The results indicated that the patterns of soil moisture at different locations and slopes along the hillslope were similar with those of rainfall during the measurment period. However, the spatial distribution of soil moisture was not associated with the slope of the monitored location. This implies that the variability of the soil moisture was determined more by rainfall than by the slope of the site. Due to the influence of vegetation activity on soil moisture flow in spring, the soil moisture prediction in spring showed higher variability and complexity than that in early autumn did. This indicates that vegetation activity is an important factor explaining the patterns of soil moisture for an upland forested hillslope.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.375-383
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• 2012

Soil erosion has been emphasized as serious environmental problem affecting water quality in the receiving waterbodies. Recently, Best Management Practices (BMPs) have been applied at a field to reduce soil erosion and its effectiveness in soil erosion reduction has been monitored with various methods. Although monitoring at fields/watershed outlets would be accurate way for these ends, it is not possible at some fields/watersheds due to various limitations in direct monitoring. Thus modeling has been suggested as an alternative way to evaluate effects of the BMPs. Most models, which have been used in evaluating hydrology and water quality at a watershed, could not reflect rainfall intensity in runoff generation and soil erosion processes. In addition, source codes of these models are not always public for modification/enhancement. Thus, runoff-sediment evaluation system using hourly rainfall data and vegetated filter strip (VFS) evaluation module at field level were developed using open source MapWindow GIS component in this study. This evaluation system was applied to Bangdongri, Chuncheonsi to evaluate its prediction ability and VFS module in this study. The NSE and $R^2$ values for runoff estimation were 0.86 and 0.91, respectively, and measured and simulated sediment yield were 15.2 kg and 16.5 kg indicating this system, developed in this study, can be used to simulate runoff and sediment yield with acceptable accuracies. Nine VFS scenarios were evaluated for effectiveness of soil erosion reduction. Reduction efficiency of the VFS was high when sediment inflow was small. As shown in this study, this evaluation system can be used for evaluation BMPs with local rainfall intensity and variations considered with ease-of-use GIS interface.

• Journal of Korea Water Resources Association
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• v.48 no.2
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• pp.115-126
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• 2015

In recent years, debris flow disaster has occurred in multiple locations between high and low mountainous areas simultaneously with a flooding disaster in urban areas caused by heavy and torrential rainfall due to the changing global climate and environment. As a result, these disasters frequently lead to large-scale destruction of infrastructures or individual properties and cause psychological harm or human death. In order to mitigate these disasters more effectively, it is necessary to investigate what causes the damage with an integrated model of both disasters at once. The objectives of this study are to analyze the mechanism of debris flow for real basin, to determine the PMP and run-off discharge due to the DAD analysis, and to estimate the influence range of debris flow for fan area according to the scenario. To analyse the characteristics of debris flow at the real basin, the parameters such as the deposition pattern, deposit thickness, approaching velocity, occurrence of sediment volume and travel length are estimated from DAD analysis. As a results, the peak time precipitation is estimated by 135 mm/hr as torrential rainfall and maximum total amount of rainfall is estimated by 544 mm as typhoon related rainfall.

• The Journal of Engineering Geology
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• v.16 no.2 s.48
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• pp.135-143
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• 2006

This study presents the results of a series of laboratory scale slope failure experiments aimed at clarifying the process and the condition leading to the initiation of rainfall-induced slope failures. For the evaluation of hydrologic response of the model slopes in relation the process of failure initiation, measurements were focused on the changes in volumetric water content during the initiation process. The process leading to failure initiation commences by the development of a seepage face. It appears reasonable to conclude that slope failures are a consequence of the instability of seepage area formed at the slope surface during rainfall period. Therefore, this demonstrates the importance of monitoring the development seepage area for useful prediction about the timing of a particular failure event. The hydrologic response of soil slopes leading to failure initiation is characterized by three phases (phase I, II and III) of significant increase in volumetric water content in association with the ingress of wetting front and the rise of groundwater level within the slope. The period of phase III increase in volumetric water content can be used to initiate advance warning towards a failure initiation event. Therefore, for the concept outlined above, direct and continuous monitoring of the change in volumetric water content is likely to provide the possibility for the development of a reliable and effective means of predicting the occurrence of rainfall-induced slope failures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.439-447
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• 2019

In this study, experiments were conducted to establish appropriate measures for slopes with high risk of collapse and to obtain results for minimizing slope collapse damage by detecting the micro-displacement of soil in advance by installing a laser sensor and a vibration sensor in the landslide reduction model experiment. Also, the behavior characteristics of the soil layer due to rainfall and moisture ratio changes such as pore water pressure and moisture were analyzed through a landslide reduction model experiment. The artificial slope was created using granite weathering soil, and the resulting water ratio(water pressure, water) changes were measured at different rainfall conditions of 200mm/hr and 400mm/hr. Laser sensors and vibration sensors were applied to analyze the surface displacement, and the displacement time were compared with each other by video analysis. Experiments have shown that higher rainfall intensity takes shorter time to reach the limit, and increase in the pore water pressure takes shorter time as well. Although the landslide model test does not fully reflect the site conditions, measurements of the time of detection of displacement generation using vibration sensors show that the timing of collapse is faster than the method using laser sensors. If ground displacement measurements using sensors are continuously carried out in preparation for landslides, it is considered highly likely to be utilized as basic data for predicting slope collapse, reducing damage, and activating the measurement industry.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.687-699
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• 2018

Understanding rain infiltration into the ground is an important feature of landslide risk evaluation. In this study, a landslide risk index for the study area is suggested, wherein the result of the landslide risk evaluation, based on the factor of safety (FS), is used. The landslide risk index is a landslide risk prediction index that utilizes the saturated depth ratio of the ground. Based on the landslide risk result for the study area, it was found that the FS was first to decrease. However, it gradually became convergent over the 50-year rainfall intensity study period, a result that is similar to the relationship between the saturated depth ratio and soil thickness. Moreover, saturated depth was also found to be deeper on gentle slopes than steep slopes. As such, the landslide risk index, based on the Inhu-ri study result, is thus suggested. Additionally, the suggested landslide risk index was compared and analyzed against the rainfall intensity of previous landslide experience. Results thus revealed that almost all landslides that occurred were over 0.7, which is the second grade, based on the landslide risk index.

• Journal of Korea Water Resources Association
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• v.55 no.9
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• pp.657-668
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• 2022

With the occurrence of localized heavy rain while river flow has increased, both flow and rainfall cause riverside flood damages. As the degree of damage varies according to the level of social and economic impact, it is required to secure sufficient forecast lead time for flood response in areas with high population and asset density. In this study, the author established a flood risk matrix using ensemble rainfall runoff modeling and evaluated its applicability in order to increase the damage reduction effect by securing the time required for flood response. The flood risk matrix constructs the flood damage impact level (X-axis) using flood damage data and predicts the likelihood of flood occurrence (Y-axis) according to the result of ensemble rainfall runoff modeling using LENS rainfall data and as well as probabilistic forecasting. Therefore, the author introduced a method for determining the impact level of flood damage using historical flood damage data and quantitative flood damage assessment methods. It was compared with the existing flood warning data and the damage situation at the flood warning points in the Taehwa River Basin and the Hyeongsan River Basin in the Nakdong River Region. As a result, the analysis showed that it was possible to predict the time and degree of flood risk from up to three days in advance. Hence, it will be helpful for damage reduction activities by securing the lead time for flood response.