预测沿海多层含水层的地下水酸盐含量:一种基于地理统计和数据的方法
Md Abdullah-Al Mamun1, Abu Reza Md Towfiqul Islam2, Mst Nazneen Aktar3
1Department of Data Science, Tampere University, Finland.
The Science of the total environment
|September 6, 2024
概括
这项研究确定了孟加拉沿海地下水酸盐的关键驱动因素,使用先进的建模来预测度. 这些发现支持可持续的水资源管理和保护这一重要资源的努力.
科学领域:
- 环境科学 环境科学
- 水文地质学 水文地质学
- 数据科学数据科学数据科学
背景情况:
- 地下水对于孟加拉沿海地区的供水至关重要.
- 关于影响和预测地下水酸盐水平的因素的研究有限.
- 对于该地区的未来来说,对该资源的可持续管理至关重要.
研究的目的:
- 为了确定地下水酸盐度的驱动因素.
- 为了预测沿海多层含水层的地下水酸盐含量.
- 制定可持续地下水资源管理的战略.
主要方法:
- 结合地缘统计建模,自组织地图 (SOM) 和数据驱动算法 (CatBoost,GBM,LSTM,SVR).
- 分析了380个地下水样本,使用了15个预测参数.
- 使用RMSE,R2,MAE和CC等指标评估预测准确度.
主要成果:
- 索姆确定了与水化学相关的三个不同的空间模式.
- CatBoost模型表现出卓越的预测性能 (训练中的R2=0.999,测试中的R2=0.989).
- 酸盐溶解,盐水入侵和农业排水被确定为导致酸盐水平升高的关键因素.
结论:
- CatBoost模型提供了一种可靠和一致的方法来预测地下水酸盐.
- (Na+), (K+) 和 (Mg2+) 显著影响预测的准确性.
- 这些发现对于制定沿海地下水资源保护计划至关重要.
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