GSIS 공간분석 기법을 활용한 토양침식 잠재성 평가에 관한 연구 = A Study on the Evaluation of Soil Erosion Potential using GSIS Spatial Analysis Method

다국어 초록 (Multilingual Abstract)

Soil erosion by outflow of water or rainfall has caused many environmental problems as declining agricultural productivity, damaging pasture and preventing flow of water. As the interest in environment is increasing lately, soil erosion is considered as a serious problem, whereas the systematic regulation and analysis for that have not established yet.
Yongdam Dam was completed on October, 2001 and there needs to evaluate soil erosion contents in Dam management like as water capacity, environmental contamination et al.
There are several models such as ANSWER, WEPP, RUSLE in evaluating soil erosion and This research used RUSLE erosion model which could expect general soil erosion connected easily with GSIS data.
RUSLE's input factors are composed of rainfall runoff factor(R), soil erodibility factor(K), slope length factor(L), slope steepness factor(S), cover management factor(C) and support practice factor(P). The general equation used to extract L, S factor on the RUSLE to be oriented for agricultural area has some limitation to apply whole watershed. Therefore, in this study we used a revised empirical equation applicable to the watershed by grid on the GSIS.
This research shows the method of extracting factor entered model which expects soil erosion by GSIS. Also, we analyzed RUSLE factors by watershed being analyzed with watershed extraction algorithm. Then we could calculate the minimum, maximum, mean and standard deviation of RUSLE factors by watershed.
This study evaluated soil erosion potential to yongdam watershed that is located in the upper stream of Kum-River and acquired results as below.
First, Rainfall data of 9 raingauge around yongdam watershed were selected and carried out spline interpolation to show continuous rainfall phenomenon efficiently and rainfall erosivity factor was extracted.
Second, Fuzzy membership function was applied into soil map being used to calculate soil erodibility factor and this study could present soil type more efficiently as real phenomenon and minimize great error being occurred in boundary of soil map.
Third, for overcoming existing research extracted topographic factor with only slope this study extracted slop length factor and slope steepness factor individually. Especially, slope length factor derived from the equation of Desmet and Govers considered an area of the total number of cells considered and then divided by the contour length of the observation cell to convert area into a hillslope length.
Fourth, Cover management factor was extracted with applying landcover map being classified from recent LANDSAT TM Imagery with Maximum Likelihood Method and extract support practice factor with landcover map and slope map.
Fifth, this study could present monthly soil erosion by topographic factor using monthly rainfall data. But, it could be different according to topographic factor, therefore it is need to calibrate using sample data.
Last, the supply of base data could be on accurate soil erosion modeling by applying RUSLE factor being calculated with spatial analysis method into the input factor of soil erosion model.

목차 (Table of Contents)

• 목차
• 표목차 = ⅳ
• 그림목차 = ⅵ
• 약어 = ⅶ
• ABSTRACT = ⅰⅹ
• 제1장 서론 = 1
• 1.1 연구배경 및 목적 = 1
• 1.2 연구연혁 = 2
• 1.3 연구범위 및 방법 = 7
• 제2장 토양침식과 비유사량 산정 = 9
• 2.1 토양침식 = 9
• 2.1.1 토양침식과정 = 9
• 2.1.2 GSIS내에서의 침식모형 = 15
• 2.1.3 침식모형의 종류 = 17
• 2.1.4 침식모형 선정 = 21
• 2.2 비유사량 산정 = 24
• 2.2.1 비유사량 산정 방법 = 24
• 2.2.2 비유사량 실측자료 = 28
• 2.2.3 연구방향 = 30
• 제3장 RUSLE 모형 = 33
• 3.1 RUSLE 논리 = 33
• 3.2 RUSLE 인자 = 34
• 3.2.1 토양침식량 = 34
• 3.2.2 강우침식인자 = 34
• 3.2.3 토양침식인자 = 39
• 3.2.4 지형인자 = 45
• 3.2.5 식생피복인자 = 51
• 3.2.6 경작인자 = 52
• 제4장 GSIS 경계표현 및 격자 모형화 = 55
• 4.1 경계표현 모형 = 55
• 4.1.1 지리경계표현 = 55
• 4.1.2 퍼지경계표현 = 57
• 4.2 격자 모형화 = 59
• 4.2.1 자료구조 = 59
• 4.2.2 격자분석 기능 = 61
• 4.2.3 응용사례 = 64
• 제5장 적용 및 분석 = 68
• 5.1 공간적 범위 = 68
• 5.2 자료구축 및 응용 S/W = 68
• 5.3 하천 및 유역추출 = 70
• 5.4 RUSLE 인자추출 및 분석 = 72
• 5.4.1 강우침식인자 = 72
• 5.4.2 토양침식인자 = 78
• 5.4.3 침식사면의 길이인자 = 87
• 5.4.4 침식사면의 경사인자 = 91
• 5.4.5 지형인자 = 96
• 5.4.6 식생피복인자 = 97
• 5.4.7 경작인자 = 100
• 5.5 토양침식량 분석 = 102
• 5.5.1 유역별 평균 토양침식량 = 102
• 5.5.2 월별 토양침식량 = 103
• 5.6 하천의 비유사량 산정 = 110
• 제6장 결론 = 113
• 참고문헌 = 115
• 부록 = 130
• 지형인자(LS) 추출 AML 코드 = 131