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Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis

机译:使用GIS和多准则决策分析在伊朗Yasooj地区进行洪灾灾害分区

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Flood is considered to be the most common natural disaster worldwide during the last decades. Flood hazard potential mapping is required for management and mitigation of flood. The present research was aimed to assess the efficiency of analytical hierarchical process (AHP) to identify potential flood hazard zones by comparing with the results of a hydraulic model. Initially, four parameters via distance to river, land use, elevation and land slope were used in some part of the Yasooj River, Iran. In order to determine the weight of each effective factor, questionnaires of comparison ratings on the Saaty's scale were prepared and distributed to eight experts. The normalized weights of criteria/parameters were determined based on Saaty's nine-point scale and its importance in specifying flood hazard potential zones using the AHP and eigenvector methods. The set of criteria were integrated by weighted linear combination method using ArcGIS 10.2 software to generate flood hazard prediction map. The inundation simulation (extent and depth of flood) was conducted using hydrodynamic program HEC-RAS for 50- and 100-year interval floods. The validation of the flood hazard prediction map was conducted based on flood extent and depth maps. The results showed that the AHP technique is promising of making accurate and reliable prediction for flood extent. Therefore, the AHP and geographic information system (GIS) techniques are suggested for assessment of the flood hazard potential, specifically in no-data regions.
机译:在过去的几十年中,洪水被认为是全球范围内最常见的自然灾害。对于洪水的管理和缓解,需要洪灾潜在风险绘图。本研究旨在通过与水力模型结果进行比较来评估层次分析法(AHP)识别潜在洪灾危险区的效率。最初,在伊朗Yasooj河的某些部分使用了四个参数,分别是到河流的距离,土地利用,海拔和坡度。为了确定每个有效因素的权重,准备了一份以萨蒂规模进行比较的问卷,并分发给八位专家。根据Saaty的9点量表及其在使用AHP和特征向量法指定洪水潜在危险区中的重要性,确定标准/参数的标准化权重。使用ArcGIS 10.2软件通过加权线性组合方法对标准集进行集成,以生成洪水灾害预测图。使用水动力程序HEC-RAS对50年和100年间隔洪水进行了淹没模拟(洪水的程度和深度)。基于洪水范围和深度图对洪水灾害预测图进行了验证。结果表明,层次分析法有望对洪水范围进行准确可靠的预测。因此,建议使用AHP和地理信息系统(GIS)技术来评估洪水灾害的可能性,特别是在无数据区域。

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