混合模型用于每日流量和负载预测
DoYeon Lee1, Jihoon Shin2, TaeHo Kim3
1School of Environmental Engineering, University of Seoul, Dongdaemun-gu, Seoul 02504, Republic of Korea
概括
一个新的混合模型,SWAT-RETAIN,通过将土壤和水评估工具 (SWAT) 与反向时间注意力机制 (RETAIN) 结合起来,准确地预测每日流量和总 (TP) 负载. 这种方法提高了流域的水质预测.
科学领域:
- 环境科学 环境科学
- 水文学的水文学
- 水资源管理 水资源管理
背景情况:
- 气候和土地利用变化等环境因素对水质产生重大影响.
- 现有的预测模型 (基于过程和数据的) 在准确性和范围上有局限性.
- 准确预测水质参数对于有效的流域管理至关重要.
研究的目的:
- 开发和评估一个新的混合模型,SWAT-RETAIN,用于预测每日流量和总 (TP) 负载.
- 提高流域水质预测的准确性和时间分辨率.
- 解决现有的个人建模方法的局限性.
主要方法:
- 开发了一个混合模型,将土壤和水评估工具 (SWAT) 与反向时间注意力机制 (RETAIN) 集成在一起.
- 利用空间,气象和水文数据构建SWAT模型,以生成高时间分辨率的数据.
- 将SWAT-RETAIN模型应用于韩国Hwangryong河流域进行验证.
主要成果:
- SWAT-RETAIN模型在测试组上预测流量 (NSE:0.45) 和TP负载 (NSE:0.50) 的准确性很高.
- 使用流量持续时间和负载持续时间曲线验证性能.
- 该模型实现了对多个水质变量的有效同时预测.
结论:
- SWAT-RETAIN混合模型为流域水质提供了增强的时间分辨率和预测性能.
- 这种综合方法有效地克服了独立模型的局限性.
- SWAT-RETAIN显示了在预测更大,更复杂的流域中各种水质变量的应用潜力.
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