• Title/Summary/Keyword: 범용토양유실공식

Search Result 49, Processing Time 0.025 seconds

The Estimation of Soil Runoff in the Man-dae Cheun Basin by the using RUSLE Method (RUSLE 방법을 이용한 만대천 유역의 토사유출량 산정)

  • Choi, Han-Kuy;Park, Soo-Jin;Guk, Seong-Pyo
    • Journal of Industrial Technology
    • /
    • v.30 no.B
    • /
    • pp.99-108
    • /
    • 2010
  • This study was intended to estimate the soil runoff at the basin of Mandaechun where the measure needs to be taken to deal with the increasing muddy water resulting from soil runoff during wet season and torrential rain at the high reaches of the Soyang lake where highland vegetables are cultivated and soil replacement for improvement is carried out every two to three years. The study was carried out in such a way of identifying the topographic factors using geographical spatial data from Water Management Information System (WAMIS) and ARC-VIEW program and estimating the soil runoff by rainfall frequency using Revised Universal Soil Loss Equation (RUSLE), and furthermore, evaluating the soil runoff contribution at the basin of Mandaechun based on estimate of the soil runoff by section.

  • PDF

Estimation of Soil Loss Changes and Sediment Transport Path Using GIS and Multi-Temporal RS data (GIS 및 다시기 RS 자료를 이용한 토양손질량 변화 및 이동경로 추정)

  • 권형중;박근애;김성준
    • Spatial Information Research
    • /
    • v.10 no.1
    • /
    • pp.139-152
    • /
    • 2002
  • The purpose of this study is to estimate temporal soil loss change according to long-term land cover changes using G1S and RS. Revised USLE(Universal Soil Loss Equation) factors were prepared by using point rainfall data, DEM(Digital Elevation Model), soil map and land cover map. During the past two decades, land cover changes were traced by using Landsat MSS and TM data. As a result, forest area in 2000 has decreased 25.3 $km^2$ compared with that in 1990. Soil loss has decreased 3751.2 tou/yr. On the other hand, upland area has increased 22.5 $km^2$. Soil loss of upland has increased 5395.4 to/yr. Therefore, soil loss in 2000 increased 6.3 kg/$m^2$/yr compared with that in 1990. This was mainly caused by the increased upland area.

  • PDF

Runoff in upland soils at a torrential rain with soil texture and slopeness (집중강우시 우리나라 밭토양의 토성별 경사도별 물유출 양상)

  • Jung, Kang-Ho;Hur, Seung-Oh;Ha, Sang-Geon
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2005.05b
    • /
    • pp.255-259
    • /
    • 2005
  • 본 연구는 1981-1991년 농업과학기술원 라이시미터에서 수집한 결과를 이용하여 집중강우시 경사지 밭토양의 물유출 특성을 구명하였다. $7\~9$월 집중강우시 토양 침투수나 지표 유거수는 농업지역에서 환경으로 물질이 이동하는 주요 경로이며 특히 경사지 밭토양에서 지표 유거수는 토양유실의 주원인 중 하나이기 때문에 이에 대한 이해는 매우 중요하다. 이를 위해 강우량, 지표 유거수량, 지하 침투수량 측정 자료 중 호우주의보가 발령되는 일강우량 80mm이상일 때를 대상으로 하여 토성과 경사도에 따른 강우량과 유거수, 침투수의 관계를 분석하였다. 강우량이 적을 때 강우에 대한 침투수와 유거수의 비율은 강우시 표토의 토양수분함량에 많은 영향을 받는다. 이는 표토의 토양수분함량에 따라 유출 또는 침투 발생 유효강우량이 결정되기 때문이다. 강우량이 적을 때의 유거수량과 침투수량을 판단하기 위해 범용토양유실예측공식(Universal soil loss equation, USLE)에서는 0.5 inch 즉, 12.5 mm 이상의 강우를 유출에 대한 유효강우로 가정하고 있으며 많은 모형에서 토양의 침투속도, 포장용수량, 강우시점의 토양수분함량의 함수로 유출 또는 침투 유효강우량을 산정하고 있다. 그러나 강우량이 클 때는 강우에 대한 침투수와 유거수에 비율에 토양수분함량이 미치는 영향이 비교적 적기 때문에 토양의 수분함량에 대한 고려없이 강우와 침투수, 유거수에 대한 관계를 평가하는 것이 가능하였다. 경사도 $10\%$, 경사장 15m, 피복작물 콩인 양토를 기준으로 할 때 강우량과 침투수의 관계는 $I_{10}(mm)=0.44R(mm)+5.8(r^2=0.55)$이었다. y절이 발생한 이유는 이전 강우에 의해 침투되고 있는 물이 있음을 함축하며 기울기 0.40은 강우의 $40\%$가 지하로 침투하였음을 의미한다. 침투수량은 토성별로 양토를 1.0으로 기준할 때 사양토가 1.12로 가장 컸고, 식양토 0.94, 식토 0.91로 평가되었다. 이는 토성간의 침투속도 및 투수속도의 경향이 반영된 것이다. 경사에 따라서는 경사도가 증가할수록 지수적으로 감소하였으며 $10\% 경사일 때를 기준으로 $I(mm)=I_{10}{\times}1.17{\times}e^{-0.0164s(\%)}$로 나타났다. 같은 조건에서 강우량과 유거수의 관계는 $Ro_{10}(mm)=5.32e^{0.11R(mm)}(r^2=0.69)$로 나타났다. 이는 토양의 투수특성에 따라 강우량 증가에 비례하여 점증하는 침투수와 구분되는 현상이었다. 경사와 토양이 같은 조건에서 나지의 경우 역시 $Ro_{B10}(mm)=20.3e^{0.08R(mm)(r^2=0.84)$로 지수적으로 증가하는 경향을 나타내었다. 유거수량은 토성별로 양토를 1.0으로 기준할 때 사양토가 0.86으로 가장 작았고, 식양토 1.09, 식토 1.15로 평가되어 침투수에 비해 토성별 차이가 크게 나타났다. 이는 토성이 세립질일 수록 유거수의 저항이 작기 때문으로 생각된다. 경사에 따라서는 경사도가 증가할수록 증가하였으며 $10\% 경사일 때를 기준으로 $Ro(mm)=Ro_{10}{\times}0.797{\times}e^{-0.021s(\%)}$로 나타났다.

  • PDF

Study on improvement of USLE P factor considering topography and cultivation method (지형 및 경작 방법을 반영한 범용토양유실량 산정공식 보전관리 인자 개선 연구)

  • Sung, Yunsoo;Lee, Gwanjae;Lee, Gwanjae;Han, Jeongho;Kim, Jonggun;Lim, Kyoung Jae;Kim, Ki Sung
    • Journal of Wetlands Research
    • /
    • v.21 no.2
    • /
    • pp.163-172
    • /
    • 2019
  • The USLE P factor is a factor that varies depending on how croplands are managed and cultivated. Previous studies tend to overestimate the amount of soil loss because the factor was estimated from the slope of the watershed rather than the estimate of each cultivated land. In addition, the accuracy of estimating the soil loss is decreasing due to the fact that the factor is calculated without considering various conditions of cultivated land defined by Wishmeier and Smith. In order to overcome these problems, the Ministry of Environment (MOE) has proposed to establish the topsoil notification and calculate the P factor according to the cultivation methods (e.g., tillage system, support practice). However, it is required to apply the conditions proposed in the United States to domestic circumstances as it is causing uncertainties. Thus, this study selected the watersheds where soil loss was serious (Haean, Jaun, Banbyeoncheon), measured the actual slopes and slope lengths, and examined the crop, tillage systems, and support practice for each cultivated land. The P factors were recalculated considering the actual conditions of cultivated land and compared to the factors proposed by the previous studies (MOE). As the result of the study, the P factors calculated based on the previous studies were 0.8 ~ 1.0 in three watersheds. On the other hand, it is confirmed that there is a significant difference between the factors notified by MOE and estimated by reflecting the topography and cultivation methods in this study. Therefore, it is considered that the research for developing the cultivation conditions to calculate the P factor suitable for the domestic environment should be continuously carried out.

A Study to Determine the Rainfall Erosivity Factor of Universal Soil Loss Equation using Recent Rainfall Data (최근 강수 자료를 이용한 범용토양유실공식의 강우침식능인자 정의에 관한 연구)

  • Kim, Jonggun;Jang, Jin Uk;Seong, Gak Gyu;Cha, Sang Sun;Park, Youn Shik
    • Journal of The Korean Society of Agricultural Engineers
    • /
    • v.60 no.6
    • /
    • pp.13-20
    • /
    • 2018
  • Universal Soil Loss Equation (USLE) has been widely used to estimate potential soil loss because USLE is a simple and reliable method. The rainfall erosivity factor (R factor) explains rainfall characteristics. R factors, cited in the Bulletin on the Survey of the Erosion of Topsoil of the Ministry of Environment in the Republic of Korea, are too outdated to represent current rainfall patterns in the Republic of Korea. Rainfall datasets at one minute intervals from 2013 to 2017 were collected from fifty rainfall gauge stations to update R factors considering current rainfall condition. The updated R factors in this study were compared to the previous R factors which were calculated using the data from 1973 to 1996. The coefficient of determination between the updated and the previous R factors shows 0.374, which means the correlation is not significant. Therefore, it was concluded that the previous R factors might not explain current rainfall conditions. The other remarkable result was that regression equations using annual rainfall data might be inappropriate to estimate reasonable R factors because the correlation between annual rainfall and the R factors was generally unsatisfy.

A Study to Determine the Slope Length and Steepness Factor of Universal Soil Loss Equation with Determining and Adapting Major Slope Length at Field Scale (필지 단위 주경사장 산정 및 적용을 통한 범용토양유실공식 지형인자 산정 개선 연구)

  • Park, Youn Shik;Park, Jong-Yoon;Jang, Won Seok;Kim, Jonggun
    • Journal of The Korean Society of Agricultural Engineers
    • /
    • v.61 no.6
    • /
    • pp.55-65
    • /
    • 2019
  • Universal Soil Loss Equation (USLE) is to estimate potential soil loss and has benefit in use with its simplicity. The equation is composed of five factors, one of the factors is the slope length and steepness factor (LS factor) that is for topographic property of fields to estimate potential soil loss. Since the USLE was developed, many equations to compute LS was suggested with field measurement. Nowadays the factor is often computed in GIS software with digital elevation model, however it was reported that the factor is very sensitive to the resolution of digital elevation model. In addition, the digital elevation model of high resolution less than 3 meter is required in small field application, however these inputs are not associate with the empirical models' backgrounds since the empirical models were derived in 22.1 meter field measurements. In the study, four equation to compute LS factor and two approaches to determine slope length and steepness were examined, and correction factor was suggested to provide reasonable precision in LS estimations. The correction factor is computed with field area and cell size of digital elevation model, thus the correction factor can be adapted in any USLE-based models using LS factor at field level.

A Study to Evaluate and Remedy Universal Soil Loss Equation Application for Watersheds and Development Projects (범용토양유실공식의 유역단위 및 개발사업에 대한 적용방안 검토 및 보완에 관한 연구)

  • Woo, Won Hee;Chae, Min Suh;Park, Jong-Yoon;Lee, Hanyong;Park, Youn Shik
    • Journal of The Korean Society of Agricultural Engineers
    • /
    • v.65 no.3
    • /
    • pp.29-42
    • /
    • 2023
  • Universal Soil Loss Equation (USLE) is suggested and employed in the policy to conserve soil resources and to manage the impact of development, since soil loss is very essential to nonpoint source pollution management. The equation requires only five factors to estimate average annual potential soil loss, USLE is simplicity provides benefits in use of the equation. However, it is also limitation of the model, since the estimated results are very sensitive to the five factors. There is a need to examine the application procedures. Three approaches to estimate potential soil loss were examined, In the first approach, all factors were prepared with raster data, soil loss were computed for each cell, and sum of all cell values was determined as soil loss for the watersheds. In the second approach, the mean values for each factor were defined as representing USLE factors, and then the five factors were multiplied to determine soil loss for the watersheds. The third approach was same as the second approach, except that the Vegetative and Mechanical measure was used instead of the Cover and management factor and Support practice factor. The approaches were applied in 38 watersheds, they displayed significant difference, moreover no trends were detected for the soil loss at watersheds with the approaches. Therefore, it was concluded that there is a need to be developed and provided a typical guideline or public systems so that soil loss estimations have consistency with the users.

The Variation of Surface Runoff according to Climate Change Scenario (기후변화 시나리오에 따른 지표유출량 변화)

  • Son, Minwoo;Byun, Jisun;Park, Byeoungeun
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2018.05a
    • /
    • pp.356-356
    • /
    • 2018
  • 기후변화는 자연적 요인보다는 인간의 활동으로부터 기인하는 것으로 알려진다. 지구 온난화의 영향으로 우리나라의 평균 기온은 상승하고 있으며, 강수량 또한 증가추세에 있다. 이러한 미래 기온의 상승과 강수량의 변화는 나아가 수문 순환에 영향을 미치며, 수자원의 효과적인 이용을 위하여 기후변화에 따른 수문 순환 특성을 파악하는 것은 매우 중요하다. 이에 본 연구에서는 국제 수문 프로그램의 대상 유역 중 하나로 장기간의 강우-유출 자료가 구축되어있는 청미천 유역을 대상으로, 기후변화에 따른 지표 유출량 변화를 살펴본다. 기후변화를 전망하기 위한 방법으로 인간 활동이 대기에 미치는 복사량으로 온실 가스 농도를 정의하는 시나리오인 대표농도경로(Reperentative Concentration Pathway, RCP)를 적용하였다. 기상청에서 제공되는 여러 RCP 시나리오 중 기후변화가 현재의 추세를 쫓아 상승 형태를 나타내는 RCP 8.5 시나리오와 저감 정책이 어느 정도 실현되어 형태가 안정된 RCP 4.5 시나리오 두 개를 선정하였다. 기후변화 시나리오는 근본적으로 불확실성을 포함하기 때문에, 특정 기후변화를 가정하기 보다는 특성이 대비되는 두 개 시나리오를 적용하여 기후변화의 발달 정도에 따른 유출량 변화를 살펴보고자 한다. 장기간의 수문 순환 특성을 모의하기 위하여 준 분포형 장기유출 모형인 Soil and Water Assessment Tool(SWAT)을 이용하며, SWAT에서 요구되는 방대한 양의 매개변수들은 매개변수의 최적값 산정 프로그램인 SWAT Calibration and Uncerntianty Programs (SWAT-CUP)을 통해 얻는다. 과거의 강우-유출 자료로부터 구축된 SWAT 모형에 기후변화 시나리오를 적용함으로써 기후변화 시나리오에 따른 지표유출량 변화를 살펴볼 수 있다. 구축된 SWAT 모형을 이용하여 모의를 한 결과, 두 개 시나리오 모두에서 청미천 유역의 지표유출량이 증가하는 것으로 나타났으며 RCP 4.5 시나리오보다 RCP 8.5 시나리오에서 더 많은 유출이 발생할 것으로 전망된다. 유출량의 증가와 함께 총 부유사량 또한 증가 추세에 있으며, RCP 8.5 시나리오에서 더 많은 유출이 계산된다. 이러한 유출량의 증가는 강수량, 기온, 일사량, 풍속, 습도와 같은 기후 특성의 변화가 고려된 결과로 판단된다. 기후변화에 따른 총 유사량의 증가는 범용토양 유실공식에서 강우 에너지의 증가로 인해 유출량과 동일한 양상을 띠는 것으로 판단된다.

  • PDF

Spatial Rainfall Considering Elevation and Estimation of Rain Erosivity Factor R in Revised USLE Using 1 Minute Rainfall Data and Program Development (고도를 고려한 공간강우분포와 1분 강우자료를 이용한 RUSLE의 강우침식인자(R) 산정 및 프로그램 개발)

  • JUNG, Chung-Gil;JANG, Won-Jin;KIM, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.19 no.4
    • /
    • pp.130-145
    • /
    • 2016
  • Soil erosion processes are affected by weather factors, such as rainfall, temperature, wind, and humidity. Among these factors, rainfall directly influences soil erosion by breaking away soil particles. The kinetic energy of rainfall and water flow caused by rain entrains and transports soil particles downstream. Therefore, in order to estimate soil erosion, it is important to accurately determine the rainfall erosivity factor(R) in RUSLE(Revised Universal Soil Loss Equation). The objective of this study is to evaluate the average annual R using 14 years(2002~2015) of 1 minute rainfall data from 55 KMA(Korea Meteorological Administration) weather stations. The R results from 1 min rainfall were compared with previous R studies using 1 h rainfall data. The determination coefficients($R^2$) between R calculated using 1 min rainfall data and annual rainfall were 0.70-0.98. The estimation of 30 min rainfall intensity from 1 min rainfall data showed better $R^2$ results than results from 1 h rainfall data. For estimation of physical spatial rain erosivity(R), distribution of annual rainfall was estimated by IDW(Inverse Distance Weights) interpolation, taking elevation into consideration. Because of the computation burden, the R calculation process was programmed using the python GUI(Graphical User Interface) tool.