在溶解氧数据上进行地理加权的韦布尔回归建模,以分析东卡利曼坦河流水质量
Suyitno Suyitno1, Darnah1, Memi Nor Hayati1
1Statistics Study Program, Department of Mathematics, Faculty of Mathematics and Natural Sciences, Mulawarman University.
MethodsX
|January 1, 2026
概括
东加利曼丹的河水质量正在恶化,受到铁和温度等因素的影响. 新的地理加权韦布尔回归 (GWWR) 模型有效地绘制这些空间趋势.
科学领域:
- 环境科学 环境科学
- 空间统计的空间统计.
- 水质监测 水质监测
背景情况:
- 河流水质 (RWQ) 对生态系统健康和人类使用至关重要.
- 传统的回归模型可能无法捕捉环境数据中的空间异质性.
- 了解溶解氧 (DO) 的空间变化是评估RWQ的关键.
研究的目的:
- 引入和应用地理加权韦布尔回归 (GWWR) 模型用于RWQ的空间分析.
- 绘制RWQ并确定东加利曼坦的关键影响因素.
- 将韦布尔回归 (WR) 的应用扩展到空间异质的环境数据.
主要方法:
- 开发了地理加权韦布尔回归 (GWWR) 模型.
- 将GWWR应用于东卡利曼坦地区溶解氧 (DO) 水平的空间环境数据.
- 使用空间韦布尔生存,累积分布,危险和平均回归模型来分析RWQ特征.
主要成果:
- 该GWWR模型有效地映射了RWQ及其空间决定因素.
- 东加利曼丹的河水质量在2024年呈现下降的一般趋势.
- 影响RWQ降解的关键因素包括溶解的铁,总酸盐,水温和生物化学氧气需求.
结论:
- GWWR模型是分析空间变化的环境数据的一个有价值的工具.
- 该研究强调了影响东加利曼坦河流水质量的关键因素.
- 结果为有针对性的水资源管理和保护工作提供了洞察力.
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