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实施和评估不同的技术来修改地下水脆弱性评估的DRAASTIC方法:来自突尼斯Bouficha含水层的案例研究

Ilias Siarkos¹, Madiha Arfaoui², Ourania Tzoraki³

¹Department of Marine Sciences, University of the Aegean, 81100, Mytilene, Greece. isiarkos@aegean.gr.

Environmental science and pollution research international

|July 15, 2023

概括

结合土地利用和遗传算法的DRASTIC-L-GA方法显著提高了地下水脆弱性评估的准确性. 这种加强的方法对于突尼斯有效地保护和管理地下水至关重要.

科学领域:

水文地质学水文地质学
环境科学环境科学
水资源管理水资源管理

背景情况:

评估地下水的脆弱性对于保护水资源至关重要.
剧烈的方法被广泛使用,但受到主观性和不确定性的困扰.
提高DRASTIC的效率对于准确评估污染潜力至关重要.

研究的目的:

修改和增强用于地下水脆弱性评估的DRASTIC方法.
使用统计和遗传算法将土地使用影响纳入并优化参数权重.
为了比较修改后的DRASTIC框架在突尼斯的Bouficha含水层中的性能.

主要方法:

将土地使用 (L) 纳入DRASTIC框架 (DRASTIC-L).
使用统计分析 (DRASTIC-L-SA) 和遗传算法 (DRASTIC-L-GA) 来优化DRASTIC-L.
使用酸盐度相关性 (斯皮尔曼的 ρ,CI) 评估框架.

主要成果:

根据所选择的指标,DRASTIC-L-GA框架表现出卓越的性能.
遗传算法提供了比统计方法更有效的非线性修改.
标准的DRASTIC方法显著低估了研究区域的污染潜力.

结论:

德拉斯蒂克-L-GA框架是最适合在布菲查水层地下水脆弱性的评估.
修改后的DRASTIC方法,特别是GA优化,比传统方法提供了更高的准确性.
准确的脆弱性评估对于有针对性的地下水保护战略至关重要.

关键词:

水层污染的脆弱性水层污染的脆弱性这是极端的,极端的.遗传算法遗传算法遗传算法亚酸盐是一种酸盐.优化优化优化优化统计方法统计方法

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