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Affinity propagation approach for catchment classification applied to arid catchments
Journal of African Earth Sciences ( IF 2.2 ) Pub Date : 2021-09-10 , DOI: 10.1016/j.jafrearsci.2021.104374
Asep Hidayatulloh 1 , Sameer Bamufleh 1 , Anis Chaabani 1 , Abdullah Al-Wagdany 1 , Amro Elfeki 1
Affiliation  

One of the major issues in the arid region is the availability of hydrological data for hydrological studies of the catchments for water resources projects. Since the Kingdom of Saudi Arabia (KSA) is a huge country and contains many arid catchments it is awfully expensive and time-consuming to make hydrological networks for studying all these catchments. Therefore, the Affinity Propagation (AP) clustering technique is proposed to cluster catchments into groups that are similar in morphological, hydrological, and land cover characteristics and defining an exemplar (a representative catchment) to each group. This catchment is utilized for the installation of a detailed hydrological network. The hydrological response of that catchment can be transferred and scaled appropriately to other catchments in the cluster since they are hydrologically and morphologically similar. A pilot study is performed on 18 sub-catchments in the southwestern part of KSA. GIS software is used to extract catchment attributes and the clustering process is performed using the AP cluster packages in R software. The results show that four clusters are obtained based on the morphological attributes (twenty-eight attributes), five clusters based on hydrological attributes (twelve attributes), and three clusters based on land cover and CN (three kinds of land cover as attributes). The AP clustering technique was evaluated by the construction of a correlation matrix that shows a high correlation of 0.817–0.999. This study provides a robust technique that is effective and efficient to identify the similarity of catchments and can help hydrologists to develop a catchment management application in arid regions.



中文翻译:

适用于干旱流域的流域分类的亲和传播方法

干旱地区的主要问题之一是能否获得用于水资源项目集水区水文研究的水文数据。由于沙特阿拉伯王国 (KSA) 是一个幅员辽阔的国家,包含许多干旱集水区,因此为研究所有这些集水区而建立水文网络非常昂贵且耗时。因此,Affinity Propagation (AP) 聚类技术被提议用于将流域聚类到形态、水文和土地覆盖特征相似的组中,并为每个组定义一个示例(一个代表性的流域)。该集水区用于安装详细的水文网络。该流域的水文响应可以适当地转移和缩放到集群中的其他流域,因为它们在水文和形态上是相似的。对 KSA 西南部的 18 个子流域进行了试点研究。GIS 软件用于提取流域属性,聚类过程使用 R 软件中的 AP 聚类包进行。结果表明,基于形态属性得到4个聚类(28个属性),5个基于水文属性的聚类(12个属性),3个基于土地覆盖和CN(3种土地覆盖作为属性)的聚类。AP 聚类技术通过构建相关矩阵进行评估,该矩阵显示 0.817-0.999 的高相关性。干旱地区流域管理应用。

更新日期:2021-09-22
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