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首页> 外文期刊>Open Journal of Modern Hydrology >Quantitative Regionalization of W. Mujib-Wala Sub-Watersheds (Southern Jordan) Using GIS and Multivariate Statistical Techniques
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Quantitative Regionalization of W. Mujib-Wala Sub-Watersheds (Southern Jordan) Using GIS and Multivariate Statistical Techniques

机译:使用GIS和多变量统计技术的W.Mujib-瓦拉次流域(南约旦)的定量区划

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In arid and semi-arid watersheds, sustainable management of natural resources (i.e. land, water and ecological resources), and watershed management are crucial issues in applied morphometric studies. Geomorphometric parameters and their interrelationships are of paramount importance in characterizing the morphology, topography, geology and structure, hydrological potential, and geomorphic evolution of such catchments. An analysis of spatial characteristics and morphological development of the demarcated 76 sub-watersheds related to W. Mujib-Wala catchment, was carried out using ASTER DEM and GIS. Multivariate statistical techniques such as Principal Component Analysis (PCA), Cluster Analysis (CA), and Discriminant Analysis (DA), were also employed to assess different aspects of drainage networks, and their morphometric properties. Principal Component Analysis (PCA) reduces the 22 morphometric parameters to five components, which explain 90.4% of total variance. The relationship of these components to the morphometric variables and to the individual sub-watersheds was evaluated, and then the degree of inter-correlation among the morphometric descriptors was explored. The 76 sub-watersheds were classified according to their individual relation to the components, and similarities in their morphometric characteristics. Regionalization of sub-watertsheds was achieved using hierarchical Cluster Analysis (CA). The validity of the resultant cluster groups was tested statistically by means of Discriminant Analysis. The present investigation provides information which highlights the benefit of geomorphometric analysis and multivariate statistics in modeling hydrological responses: i.e., surface runoff and sediment yield, hydrological assessment, water resources planning, and watershed management. Furthermore, the results can be useful for soil and water conservation planning, and assessment of flash floods potential.
机译:在干旱和半干旱的流域,自然资源的可持续管理(即土地,水和生态资源),流域管理是应用形态学研究的重要问题。地质形状参数及其相互关系非常重要,在表征形态,地形,地质和结构,水文潜力和这种集水区的地貌演变方面具有至关重要的重要性。使用ASTER DEM和GIS进行了与W.Mujib-瓦拉集水相关的划分的76个子流域的空间特征和形态学发展分析。多变量统计技术如主成分分析(PCA),聚类分析(CA)和判别分析(DA),以评估排水网络的不同方面及其形态学性质。主成分分析(PCA)将22个形态学参数减少到五个组分,该参数解释总方差的90.4%。评估这些组分对形态变量和各个子流域的关系,然后探讨了形态学描述符之间的相互关系程度。 76个子流域根据其与组件的个人关系进行分类,其形态学特征的相似性。使用分层聚类分析(CA)实现了亚水路的区域化。通过判别分析统计测试所得群集组的有效性。本研究提供了凸显地质形状分析和多元统计数据在模拟水文反应中的益处的信息:即表面径流和沉积物产量,水文评估,水资源规划和流域管理。此外,结果可用于水土保持规划,以及闪蒸洪水潜力的评估。

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