Document Type : پژوهشی
Authors
1 Associate Professor, Geography Department, Payame Noor University, Tehran. Iran
2 Scientific Member of Agriculture & Natural Resources Reserch Center of Ilam Provience, Iran
Abstract
Extent Abstract
Introduction
One way to decrease flood damage is to zone the potential of flood in watersheds. In other words, separating the flooding areas and determining the effective factors in flooding can play a special role in preparing a suitable medium and long term policy making for optimal exploitation of lands. Some of the studies which were based on zoning the potential of flooding worldwide and Iran includes Hawkins (1979), James et al. (1980), Bales et al. (1981), Enayat Rasoul et al. (1994), Suwanwerakamator (1994), Singh (1997), Francisco et al. (1998), Stephen (2002), Sinnakaudan et al. (2003), Sanyal and Lu (2004), Levy (2005), Meyer et al. (2009), Cook et al. (2009), Qin et al. (2011), Bakhtyari Kia et al. (2011), Al-Ghamdi et al. (2012), Ismail et al. (2013), Demir and Kisi (2016); in Iran: Qaemi and Morid (1375), Qanavati and Farajzadeh (1379), Abdi and Rasouli (1380), Omidvar et al. (1389), Malekian et al. (1391), Lajevardi et al. (1392), Nasrinnejad et al. (1393). In this research, Mishkhas watershed was studied in terms of flooding potential using multivariate statistical methods of factor and cluster analysis and geographical information system (GIS). Finally, the watershedflooding map was drawn in three classes of low, moderate and high. Zoning the flooding potential in this watershed can help reduce the damage caused by this natural hazard. Such studies can be a basis for future planning of regional and local developments.
Methodology
One of the appropriate criteria for understanding the potential of flooding in basins is classifying them according to geometry, physiography, permeability, and climatic criteria. In this study, the topography maps of geographic organization (1:50000), and the geological map of vegetation (1:250000), land use, soil maps of Ilam province (1392), precipitation data, and multivariate statistical methods of factor and cluster analysis have been used. In this research, Mishkhas watershed was divided into 12 sub-watersheds and their flooding intensity was classified into 3 classes. According to the aim of the research, the maximum instant debit, daily precipitation, and the date of watershed floods during the statistical period were selected. In addition, the effective criteria in watershed flooding was calculated using ArcGIS software including geometry, physiography, permeability, and climatic parameters for Mishkhas sub-watersheds. Then, they were analyzed using factor analysis and 28 parameters were summarized in the form of 5 main factors (form, stream, slope, drainage, and runoff). Finally, the intensity of the sub-watersheds' flooding were c 3 high, moderate, and low classes according to the mentioned criteria.
Discussion
In this research, the total criteria which were used were operating by a type R factor analysis.
The results of this research decreased 28 initial criteria to 5 superior factors including (1) form, (2) stream, (3) slope, (4) drainage, and (5) runoff. According to calculations done on the criteria in the first factor, sub-watersheds 1, 2, 3, 5, 9, 11, and 12 with the highest flooding, sub-watersheds 6, 8, 10 with moderate flooding and sub-watersheds 4 and 7 with the lowest flooding intensity were identified. The first factor indicated the reverse relationship between the watershed's form and flooding intensity. That is, the more its length and area, the less its flooding intensity.
In the second factor (stream) it was specified that sub-watersheds 1, 10, 3, and 12 have high flooding, sub-watersheds 7, 8, 5, 2, and 9 have moderate flooding, and sub-watersheds 11, 4, and 6 have low flooding. It was also indicated a reverse relationship between stream density and flooding intensity. In the third factor (slope), it was specified that sub-watersheds 6, 5, 1, 9, 10, and 11 have high flooding intensity, sub-watersheds 2, 4, and 8 have moderate flooding intensity, and sub-watersheds 7 and 12 have low flooding intensity. The sub-watersheds with high flooding intensity are located in northeastern and eastern parts of the basin which are mostly mountainous and have high height difference and slope. Sub-watersheds with low flooding intensity have little height difference, low slope, and relatively suitable vegetation. The calculations done on the fourth factor (drainage) indicated that sub-watersheds 12, 7, 4, and 2 have high flooding intensity, sub-watersheds 5, 6, 10, and 11 have moderate flooding predisposition, and sub-watersheds 1, 3, 8, and 9 have low flooding predisposition. Sub-watersheds with high flooding have been operated as the main drain of watershed. The results indicated that 33% of sub-watersheds have high flooding in terms of drainage factor. According to calculations done on the fifth factor (runoff) sub-watersheds 12, 3, 4, and 5 have high flooding intensity, sub-watersheds 1, 2, 6, and 8 have moderate flooding intensity and, sub-watersheds 7, 9, 10, and 11 have low flooding intensity. According to the factor's score, Mishkhas watershed is divided into three high, moderate, and low flooding classes and the zoning map of sub-watersheds' flooding intensity has been prepared.
Conclusion
In this research, factor analysis and cluster analysis were used for studying the flooding intensity of Mishkhas watershed and the role of sub-watersheds in flooding of this area. According to factor analysis results, 28 initial criteria reduced to 5 factors including form, stream, slope, drainage, and runoff. Analyzing the factors indicated that sub-watersheds 3, 5, 8, and 9 in form factor, sub-watersheds 1, 6, and 11 in slope factor, sub-watersheds 2 and 7 in drainage factor, and sub-watersheds 4, 12, and 10 in runoff factor have extra flood hazard intensity. Sub-watersheds were divided into 3 groups including high, moderate, and low flood producing based on the similarity of flooding intensity, erosion, vegetation, and human activities. For separating the sub-watersheds in homogenous groups, three homogenous groups were identified after data standardization by a standard model and applying Euclidean distance and Ward method. The first group's sub-watersheds 1, 2, 3, 4, 5, and 6 have high power to produce run off because of having high height and slope, low vegetation and permeability, and high flooding capacity. The second group's sub-watersheds 7, 8, 11, and 12 have high power to produce runoff, because of high slope, low vegetation, high height, low permeability, and high flooding power. In the third group's sub-watersheds 9 and 10, the flow was decreased because of decreasing the slope and increasing the permeability, so they indicated lower power to produce runoff. In fact, sub-watersheds play fundamental roles in flooding of this watershed that affect large downstream agricultural lands.
Keywords
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