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Development of a novel method to monitor the temporal change in the location of the freshwater-saltwater interface and time series models for the prediction of the interface

机译:开发一种新颖的方法来监视淡水-盐水界面位置的时间变化以及用于预测界面的时间序列模型

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摘要

The monitoring and prediction of temporal change in the location of the freshwater-saltwater interface including the groundwater level (GWL) is the essential information for effective management of coastal aquifer, especially for managing the saltwater intrusion. A simple and novel method for monitoring temporal change in the location of the freshwater-saltwater interface was developed and evaluated by applying to a coastal aquifer in Jeju Island, resulted in obtaining time series data of the freshwater-saltwater interface level (FSL) successfully. And applicability of artificial neural network-based time series models to prediction of the GWL and the FSL is evaluated using the observed data from the site. The prediction result shows that the input configuration including autoregressive components enhances the model performance and the recursive prediction models can be useful for the long-term prediction of the GWL and the FSL in this case study.
机译:监测和预测包括地下水位(GWL)在内的淡水-盐水界面位置的时间变化是有效管理沿海含水层,尤其是管理咸水入侵的重要信息。通过在济州岛的一个沿海含水层上开发和评估一种简单新颖的监测淡水-盐水界面位置时间变化的方法,成功获得了淡水-盐水界面水平(FSL)的时间序列数据。并使用现场观测数据评估了基于人工神经网络的时间序列模型对GWL和FSL预测的适用性。预测结果表明,在这种情况下,包括自回归分量的输入配置可增强模型性能,并且递归预测模型可用于GWL和FSL的长期预测。

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