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地下水位预测在资源管理、地质灾害预防、生态环境保护、供水安全保障以及科学研究等方面都具有重要意义。本期文献清单精选 Water 期刊有关“地下水位预测”方向的文章，也许能为你提供灵感！
1
Towards Groundwater-Level Prediction Using Prophet Forecasting Method by Exploiting a High-Resolution Hydrogeological Monitoring System
利用Prophet预测方法开发高分辨率水文地质监测系统进行地下水位预测
Davide Fronzi et al.
https://www.mdpi.com/2621716
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原文出自 Water 期刊
Fronzi, D.; Narang, G.; Galdelli, A.; Pepi, A.; Mancini, A.; Tazioli, A. Towards Groundwater-Level Prediction Using Prophet Forecasting Method by Exploiting a High-Resolution Hydrogeological Monitoring System. Water 2024, 16, 152.
2
Enhancing Accuracy of Groundwater Level Forecasting with Minimal Computational Complexity Using Temporal Convolutional Network
利用时域卷积网络以最小的计算复杂度提高地下水位预测的准确度
Adnan Haider et al.
https://www.mdpi.com/2570174
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原文出自 Water 期刊
Haider, A.; Lee, G.; Jafri, T.H.; Yoon, P.; Piao, J.; Jhang, K. Enhancing Accuracy of Groundwater Level Forecasting with Minimal Computational Complexity Using Temporal Convolutional Network. Water 2023, 15, 4041.
3
A Case Study: Groundwater Level Forecasting of the Gyorae Area in Actual Practice on Jeju Island Using Deep-Learning Technique
案例研究：利用深度学习技术对济州岛Gyorae区域地下水位进行实际预测
Deokhwan Kim et al.
https://www.mdpi.com/2173304
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原文出自 Water 期刊
Kim, D.; Jang, C.; Choi, J.; Kwak, J. A Case Study: Groundwater Level Forecasting of the Gyorae Area in Actual Practice on Jeju Island Using Deep-Learning Technique. Water 2023, 15, 972.
4
Groundwater Level Modeling with Machine Learning: A Systematic Review and Meta-Analysis
利用机器学习进行地下水位建模：系统回顾和Meta分析
Arman Ahmadi et al.
https://www.mdpi.com/1547612
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原文出自 Water 期刊
Ahmadi, A.; Olyaei, M.; Heydari, Z.; Emami, M.; Zeynolabedin, A.; Ghomlaghi, A.; Daccache, A.; Fogg, G.E.; Sadegh, M. Groundwater Level Modeling with Machine Learning: A Systematic Review and Meta-Analysis. Water 2022, 14, 949.
5
A Combination of Metaheuristic Optimization Algorithms and Machine Learning Methods Improves the Prediction of Groundwater Level
将元启发式优化算法和机器学习方法的结合提高地下水位的预测
Zahra Kayhomayoon et al.
https://www.mdpi.com/1519198
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原文出自 Water 期刊
Kayhomayoon, Z.; Babaeian, F.; Ghordoyee Milan, S.; Arya Azar, N.; Berndtsson, R. A Combination of Metaheuristic Optimization Algorithms and Machine Learning Methods Improves the Prediction of Groundwater Level. Water 2022, 14, 751.
6
Improving Results of Existing Groundwater Numerical Models Using Machine Learning Techniques: A Review
利用机器学习技术改进现有地下水数值模型的结果：综述
Cristina Di Salvo
https://www.mdpi.com/1742034
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原文出自 Water 期刊
Di Salvo, C. Improving Results of Existing Groundwater Numerical Models Using Machine Learning Techniques: A Review. Water 2022, 14, 2307.
7
A CNN-LSTM Model Based on a Meta-Learning Algorithm to Predict Groundwater Level in the Middle and Lower Reaches of the Heihe River, China
基于Meta学习算法的CNN-LSTM 模型预测中国黑河中下游地下水位
Xingyu Yang and Zhongrong Zhang
https://www.mdpi.com/1754530
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原文出自 Water 期刊
Yang, X.; Zhang, Z. A CNN-LSTM Model Based on a Meta-Learning Algorithm to Predict Groundwater Level in the Middle and Lower Reaches of the Heihe River, China. Water 2022, 14, 2377.
8
Groundwater Level Prediction with Machine Learning to Support Sustainable Irrigation in Water Scarcity Regions
利用机器学习进行地下水位预测以支持缺水地区的可持续灌溉
Wanru Li et al.
https://www.mdpi.com/2504670
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原文出自 Water 期刊
Li, W.; Finsa, M.M.; Laskey, K.B.; Houser, P.; Douglas-Bate, R. Groundwater Level Prediction with Machine Learning to Support Sustainable Irrigation in Water Scarcity Regions. Water 2023, 15, 3473.
9
Dynamic Changes in Groundwater Levelunder Climate Changes in the Gnangara Region, Western Australia
西澳大利亚州格南加拉地区气候变化下地下水位的动态变化
Feihe Kong et al.
https://www.mdpi.com/1440374
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原文出自 Water 期刊
Kong, F.; Xu, W.; Mao, R.; Liang, D. Dynamic Changes in Groundwater Level under Climate Changes in the Gnangara Region, Western Australia. Water 2022, 14, 162.
10
Predicting Groundwater Level Based on Machine Learning: A Case Study of the Hebei Plain
基于机器学习的地下水位预测：以河北平原为例
Zhenjiang Wu et al.
https://www.mdpi.com/2148772
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原文出自 Water 期刊
Wu, Z.; Lu, C.; Sun, Q.; Lu, W.; He, X.; Qin, T.; Yan, L.; Wu, C. Predicting Groundwater Level Based on Machine Learning: A Case Study of the Hebei Plain. Water 2023, 15, 823.
11
Spatiotemporal Distribution and Statistical Analysis of Abnormal Groundwater Level Rising in Poyang Lake Basin
鄱阳湖流域地下水位异常上升的时空分布与统计分析
Ziyi Song et al.
https://www.mdpi.com/1675946
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原文出自 Water 期刊
Song, Z.; Lu, C.; Zhang, Y.; Chen, J.; Liu, W.; Liu, B.; Shu, L. Spatiotemporal Distribution and Statistical Analysis of Abnormal Groundwater Level Rising in Poyang Lake Basin. Water 2022, 14, 1906.
12
Groundwater Level Prediction with Deep Learning Methods
使用深度学习方法预测地下水位
Hsin-Yu Chen et al.
https://www.mdpi.com/2458742
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原文出自 Water 期刊
Chen, H.-Y.; Vojinovic, Z.; Lo, W.; Lee, J.-W. Groundwater Level Prediction with Deep Learning Methods. Water 2023, 15, 3118.
13
Minimizing Errors in the Prediction of Water Levels Using Kriging Technique in Residuals of the Groundwater Model
利将克里金技术应用于地下水模型的残差中最大限度地减少水位预测误差
Alireza Asadi and Kushal Adhikari
https://www.mdpi.com/1476762
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原文出自 Water 期刊
Asadi, A.; Adhikari, K. Minimizing Errors in the Prediction of Water Levels Using Kriging Technique in Residuals of the Groundwater Model. Water 2022, 14, 426.
14
Groundwater Level Trend Analysis and Prediction in the Upper Crocodile Sub-Basin, South Africa
南非the Upper Crocodile Sub-Basi地下水位趋势分析与预测
Tsholofelo Mmankwane Tladi et al.
https://www.mdpi.com/2445262
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原文出自 Water 期刊
Tladi, T.M.; Ndambuki, J.M.; Olwal, T.O.; Rwanga, S.S. Groundwater Level Trend Analysis and Prediction in the Upper Crocodile Sub-Basin, South Africa. Water 2023, 15, 3025.
15
A Hybrid Coupled Model for Groundwater-Level Simulation and Prediction: A Case Study of Yancheng City in Eastern China
地下水位模拟与预测的混合耦合模型：以中国东部盐城为例
Manqing Hou et al.
https://www.mdpi.com/2189924
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原文出自 Water 期刊
Hou, M.; Chen, S.; Chen, X.; He, L.; He, Z. A Hybrid Coupled Model for Groundwater-Level Simulation and Prediction: A Case Study of Yancheng City in Eastern China. Water 2023, 15, 1085.
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