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首页> 外文期刊>Environmental Monitoring and Assessment >Assessment of aquifer vulnerability using a developed 'GODL' method (modified GOD model) in a schist belt environ, Southwestern Nigeria
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Assessment of aquifer vulnerability using a developed 'GODL' method (modified GOD model) in a schist belt environ, Southwestern Nigeria

机译:在尼日利亚西南部的Schist皮带环境中使用发达的“GODL”方法(修改神模型)评估含水层脆弱性

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摘要

Developing a predictive decision model for assessing the vulnerability of hidden groundwater reservoir formation to contamination risk via unavoidable anthropogenic activities is a key to managing water resources looming security crisis globally. This study explored multiple and robust methodologies including GIS, analytical hierarchy process (AHP)-based data mining, statistical and geophysical techniques for developing a novel "GODL" vulnerability method: a modified GOD model to ameliorate these challenges. The input for the modeling was based on the 65 located depth sounding geophysical data occupied in a schist belt environ, Southwestern Nigeria. From the geophysical data interpreted results, four factors, namely, groundwater hydraulic confinement (G), aquifer overlying strata (O), depth to water table (D), and longitudinal conductance (L), regarded as aquifer vulnerability causative factors (AVCFs) were derived. The GIS-based produced AVCFs' themes were synthesized by employing the conventional GOD and the AHP-driven GODL algorithms. Based on these algorithms applied results, the GOD-based aquifer vulnerability prediction zone map and GODL-based aquifer vulnerability prediction zone (AVPZ) map were produced in GIS environment. The produced AVPZ maps were validated by applying the statistical model evaluation to the water chemistry correlation results. The validation result exhibits 70% prediction accuracy for the developed GODL model compared with 66% for the GOD model. The GODL model demonstrated better performance than the GOD model. The AVPZ maps produced in this study can be used for precise decision-making process in environmental planning and groundwater management.
机译:开发用于通过不可避免的人为活动评估隐藏地下水库形成的污染风险的脆弱性的预测决策模型是水资源管理迫在眉睫的全球性安全危机的关键。本研究探讨多种和健壮方法包括地理信息系统,层次分析法(AHP)系的数据挖掘,统计和开发一种新的“GODL”漏洞方法地球物理技术:改性GOD模型来改善这些挑战。用于建模的输入是基于65位于测深的片岩带ENVIRON,尼日利亚西南部占据地球物理数据。从地球物理数据解释的结果,四个因素,即地下水液压约束(G),含水层上覆岩层(O),深度水位(d),和纵向电导(L),视为含水层脆弱致病因素(AVCFs)而得。基于GIS的产生AVCFs'主题是通过采用常规GOD和AHP驱动GODL算法合成。基于这些算法应用于结果,基于GOD含水层脆弱预测区地图和GODL基于含水层脆弱预测区(AVPZ)地图是在GIS环境中产生。所产生的AVPZ地图由应用统计模型评价水的化学性质相关结果验证。用于将显影的GODL模型验证结果显示出70%预测准确度66%为GOD模型进行比较。该GODL模型展示了比GOD模式更好的性能。在这项研究中映射产生的AVPZ可用于环境规划和地下水管理精确的决策过程。

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