• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.172-172
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• 2020

In recent years, soil erosion has come to be regarded as an essential environmental problem in human life. Soil erosion causes various on- and off-site problems such as ecosystem destruction, decreased agricultural productivity, increased riverbed deposition, and deterioration of water quality in streams. To solve these problems caused by soil erosion, it is necessary to quantify where, when, how much soil erosion occurs. Empirical erosion models such as the Universal Soil Loss Equation (USLE) family models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well by utilizing big data related to climate, geography, geology, land use, etc. within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models remain powerful tools to distinguish erosion-prone areas at the macro scale but physics-based models are necessary to better analyze soil erosion and deposition and eroded particle transport. In this study, the physics-based Surface Soil Erosion Model (SSEM) was upgraded based on field survey information to produce sediment yield at the watershed scale. The modified model (hereafter MoSE) adopted new algorithms on rainfall kinematic energy and surface flow transport capacity to simulate soil erosion more reliably. For model validation, we applied the model to the Doam dam watershed in Gangwon-do and compared the simulation results with the USLE outputs. The results showed that the revised physics-based soil erosion model provided more improved and reliable simulation results than the USLE in terms of the spatial distribution of soil erosion and deposition.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.150-150
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• 2021

Soil erosion due to climate change is one of the global environmental issues. Especially, Korea is vulnerable to soil erosion as the frequency of extreme rainfall events and rainfall intensity are increasing. Soil erosion causes various problems such as reduced farmlands, deterioration of water quality in rivers, etc. To these severe problems, understanding the process of soil erosion is the first process. Then, it is necessary to quantify and analyze soil ersoion using an erosion model. Soil erosion models are divided into empirical, conceptual, and physics-based models according to the structures and characteristics of models. This study used GSSHA (Gridded Surface Subsurface Hydrologic Analysis), the physics-based erosion model, running on WMS (Watershed Modeling System) to analyze soil erosion vulnerability of the CheonCheon watershed. In addition, we compared the six sediment transport capacity formulas provided in the model and evaluated the equations fir on this study site. Therefore, this result can be as a primary tool for soil conservation management.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.66-73
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• 2017

Empirical erosion models like Universal Soil Loss Equation (USLE) models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well utilizing big data related to climate, geography, geology, land use, etc within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models are still powerful tools to distinguish the erosion-prone areas at large scale, but physics-based models are necessary to better analyze soil erosion and deposition as well as the eroded particle transport. In this study a physics-based soil erosion modeling system was developed to produce both runoff and sediment yield time series at watershed scale and reflect them in the erosion and deposition maps. The developed modeling system consists of 3 sub-systems: rainfall pre-processor, geography pre-processor, and main modeling processor. For modeling system validation, we applied the system for various erosion cases, in particular, rainfall-runoff-sediment yield simulation and estimation of probable maximum sediment (PMS) correlated with probable maximum rainfall (PMP). The system provided acceptable performances of both applications.

• Korean Journal of Agricultural Science
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• v.51 no.3
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• pp.375-389
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• 2024

Soil erosion, a critical environmental issue primarily driven by water and wind, has severe consequences, including the loss of fertile agricultural land, degradation of water quality, and sediment accumulation in riverbeds. This study utilized the SSEM (surface soil erosion model), a physically-based distributed model, to simulate the rainfall-runoff-sediment dynamics associated with short-term rainfall events in the Naerin River basin. A spatial analysis of erosion and deposition was conducted, taking into account topographical factors such as local slope and overland flow length. The study area was segmented into six sub-catchments using Strahler's stream order method to examine the correlation between geographic factors and erosion or deposition. The findings revealed that erosion was predominant within flow path distances of 0 - 1 km (adjacent to the river) and 3 - 4 km (in the upper catchment areas). Notably, deposition did not occur in areas beyond 2.5 km from the river. Furthermore, it was observed that average erosion depth increased on steeper slopes (exceeding 0.3 - 0.4 degrees), whereas deposition was absent in these steep slope classes.

• Journal of the Korean GEO-environmental Society
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• v.21 no.4
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• pp.5-17
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• 2020

In recent years, the frequency of heavy rainfall associated with high rainfall intensity has been continuously increasing due to the effects of climate change; and thus also causes an increase in watershed soil erosion. The existing estimation techniques, used for the prediction of soil erosion in Korea have limitations in predicting the: average soil erosion in watersheds, and the soil erosion associated with abnormal short-term rainfall events. Therefore, it is necessary to consider the characteristics of torrential rainfall, and utilize physics-based model to accurately determine the soil erosion characteristics of a watershed. In this study, the rainfall kinetic energy equation, in the form of power function, is proposed by applying the probability density function, to analyze the rainfall particle distribution. The distributed rainfall-erosion model, which utilizes the proposed rainfall kinetic energy equation, was utilized in this study to determine the soil erosion associated with various typhoon events that occurred at Cheoncheon watershed. As a result, the model efficiency parameters of the model for NSE and RMSE are 0.036 and 4.995 ppm, respectively. Therefore, the suggested soil erosion model, coupled with the proposed rainfall-energy estimation, shows accurate results in predicting soil erosion in a watershed due to short-term rainfall events.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.84-84
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• 2021

전 지구적 기후변화로 세계 곳곳은 이례적인 홍수와 가뭄 등으로 많은 재산 및 인명 피해가 발생하고 있다. 우리나라의 경우, 강우 강도가 크고 단기간 많은 양의 비가 내리는 집중호우의 빈도가 급격히 증가하고 있다. 또한, 우리나라의 국토는 약 70%가 산지로 이루어져 있고, 경사가 험준한 지형을 지니고 있어 강우 시 유출이 급격히 발생하는 것이 특징이다. 이러한 기후 패턴과 지형적 특성으로 인하여 토양침식이 가중되고 있으며, 그중 강원도의 경우 산지 곳곳에 위치한 고랭지 밭으로 인해 강우 시 많은 양의 토사가 유실되어 농경지가 감소하고 있으며, 유실된 토사의 하천 유입으로 인한 하천 통수능력의 저하와 수질 악화 등 다양한 문제를 발생시키고 있다. 본 연구에서는 물리기반 모형인 SSEM (SSORii Erosion Model)을 이용하여 강원도 평창군에 위치한 도암댐 유역의 필지를 중심으로 침식과 퇴적의 양상을 분석해보고자 하였다. SSEM은 단기 강우 사상을 모의할 수 있고, 침식과 퇴적의 시·공간적 변동성을 반영할 수 있어 침식이 언제, 어디서, 얼마나 발생하였는지 식별이 가능한 모형이다. 연구분석 결과, 대부분의 필지에서 침식과 퇴적이 발생하였으며, 그중 도심지 주변에 위치한 필지에서 많은 토양침식이 발생하는 것으로 분석되었다. 이는 본 유역의 현장 조사 당시 육안으로 확인한 침식의 실태와 상당 부분 일치하고 있음을 보여준다.