PURPOSES : The skid resistance between tires and the pavement surface is an important factor that directly affects driving safety and must be considered when evaluating the road performance. In especially wet conditions, the skid resistance of the pavement surface decreases considerably, increasing the risk of accidents. Moreover, poor drainage can lead to hydroplaning. This study aimed to develop a prediction equation for the roughness coefficient—that is, an index of frictional resistance at the interface of the water flow and surface material—to estimate the thickness of the water film in advance to prevent human and material damage. METHODS : The roughness coefficient can be changed depending on the surface material and can be calculated using Manning's theory. Here, the water level (h), which is included in the cross-sectional area and wetted perimeter calculations, can be used to calculate the roughness coefficient by using the water film thickness measurements generated after simulating specific rainfall conditions. In this study, the pavement slope, drainage path length, and mean texture depth for each concrete surface type (non-tined, and tined surfaces with 25-mm and 16-mm spacings) were used as variables. A water film thickness scale was manufactured and used to measure the water film thickness by placing it vertically on top of the pavement surface along the length of the scale protrusion. Based on the measured water film thickness, the roughness coefficient could be back-calculated by applying Manning's formula. A regression analysis was then performed to develop a prediction equation for the roughness coefficient based on the water film thickness data using the water film thickness, mean texture depth, pavement slope, and drainage path length as independent variables. RESULTS : To calculate the roughness coefficient, the results of the water film thickness measurements using rainfall simulations demonstrated that the water film thickness increased as the rainfall intensity increased under N/T, T25, and T16 conditions. Moreover, the water film thickness decreased owing to the linear increase in drainage capacity as the mean texture depth and pavement slope increased, and the shorter the drainage path length, the faster the drainage, resulting in a low water film thickness. Based on the measured water film thickness data, the roughness coefficient was calculated, and it was evident that the roughness coefficient decreased as the rainfall intensity increased. Moreover, the higher the pavement slope and the shorter the drainage path length, the faster the drainage reduced the water film thickness and increased the roughness coefficient (which is an indicator of the friction resistance). It was also evident that as the mean texture depth increased, the drainage capacity increased, which also reduced the roughness coefficient. CONCLUSIONS : As the roughness coefficient of the concrete road surface changes based on the environmental factors, road geometry, and pavement surface characteristics, we developed a prediction equation for the concrete pavement roughness coefficient that considered these factors. To validate the proposed prediction equation, a sensitivity analysis was conducted using the water film thickness prediction equation from previous studies. Existing models have limitations on the impact of the pavement type and rainfall intensity and can be biased toward underestimation; in contrast, the proposed model demonstrated a high correlation between the calculated and measured values. The water film thickness was calculated based on the road design standards in Korea—in the order of normal, caution, and danger scenarios—by using the proposed concrete pavement roughness coefficient prediction model under rainy weather conditions. Specifically, because the normal and caution stages occur before the manifestation of hydroplaning, it should be possible to prevent damage before it leads to the danger stage if it is predicted and managed in advance.

산지하천 만곡부의 홍수피해를 줄이고자 사다리꼴 단면의 돌출줄눈을 하천옹벽에 설치하였다. 본 연구에서는 사다리꼴 형상에 의한 흐름저항 효과를 파악하고자 개수로 측벽에 사다리꼴 돌출줄눈을 설치하여 수리실험을 수행하였다. 벽면조도가 κ형에 해당하는 λnυ가 6, 9, 12인 경우에 대해 유량에 따른 흐름특성을 파악하였다. 흐름저항은 돌줄줄눈의 설치간격이 멀어짐에 따라 전반적으로 증가하였다. 고유량 조건에서 최대마찰계수는 λnυ가 9일 때 발생하였다. 사다리꼴 돌출줄눈은 정사각형 돌출줄눈과 비교해 흐름저항은 상대적으로 작았지만, 사다리꼴의 형상저항은 전체흐름저항의 평균 62%를 차지했다. 벽면조도 증가에 따른 흐름저항 효과를 극대화하기 위한 사다리꼴 돌출줄눈의 최적 설치간격은 돌출줄눈 높이의 9∼12배 범위임을 확인하였다.

사면에서의 세류간 토양침식은 빗물방울의 지표면 타격에 의한 토양입자의 박리와 면상흐름에 의한 토사이송의 상호작용에 의한 결과이다. 본 연구는 토양입자를 박리하는 강우동력과 유사이송에 기여하는 면상흐름동력을 토양침식을 위한 에너지 소비율 측면에서 새롭게 정의하고, 강우유발 면상흐름에 의한 세류간 토양침식의 유효동력 함수를 제시하였다. 강우, 경사, 유출과 관계된 인자들에 따른 강우 ․ 면상흐름의 동력을 평가하고, 기존 연구 자료를 바탕으로 이 함수의 상수들을 분석하였다. 또한 강우와 면상흐름 동력의 상대적인 크기 변화는 세류간 토양침식의 물리적 과정과 수문학적 반응을 반영함을 확인하였다. 지표유출 및 토양침식 실측자료를 세류간침식 평가 모형들에 적용한 결과 강우 ․ 면상흐름동력 함수가 가장 높은 정확도를 보여 세류간 토양침식 평가에 적합하다는 것을 확인하였다.