Inicio  /  Water  /  Vol: 15 Par: 4 (2023)  /  Artículo
ARTÍCULO
TITULO

Predicting Groundwater Level Based on Machine Learning: A Case Study of the Hebei Plain

Zhenjiang Wu    
Chuiyu Lu    
Qingyan Sun    
Wen Lu    
Xin He    
Tao Qin    
Lingjia Yan and Chu Wu    

Resumen

In recent years, the groundwater level (GWL) and its dynamic changes in the Hebei Plain have gained increasing interest. The GWL serves as a crucial indicator of the health of groundwater resources, and accurately predicting the GWL is vital to prevent its overexploitation and the loss of water quality and land subsidence. Here, we utilized data-driven models, such as the support vector machine, long-short term memory, multi-layer perceptron, and gated recurrent unit models, to predict GWL. Additionally, data from six GWL monitoring stations from 2018 to 2020, covering dynamical fluctuations, increases, and decreases in GWL, were used. Further, the first 70% and remaining 30% of the time-series data were used to train and test the model, respectively. Each model was quantitatively evaluated using the root mean square error (RMSE), coefficient of determination (R2), and Nash?Sutcliffe efficiency (NSE), and they were qualitatively evaluated using time-series line plots, scatter plots, and Taylor diagrams. A comparison of the models revealed that the RMSE, R2, and NSE of the GRU model in the training and testing periods were better than those of the other models at most groundwater monitoring stations. In conclusion, the GRU model performed best and could support dynamic predictions of GWL in the Hebei Plain.

 Artículos similares

       
 
Sarra Bel Haj Salem, Aissam Gaagai, Imed Ben Slimene, Amor Ben Moussa, Kamel Zouari, Krishna Kumar Yadav, Mohamed Hamdy Eid, Mostafa R. Abukhadra, Ahmed M. El-Sherbeeny, Mohamed Gad, Mohamed Farouk, Osama Elsherbiny, Salah Elsayed, Stefano Bellucci and Hekmat Ibrahim    
In the Zeroud basin, a diverse array of methodologies were employed to assess, simulate, and predict the quality of groundwater intended for irrigation. These methodologies included the irrigation water quality indices (IWQIs); intricate statistical anal... ver más
Revista: Water

 
Junaid Khan, Eunkyu Lee, Awatef Salem Balobaid and Kyungsup Kim    
Groundwater level (GWL) refers to the depth of the water table or the level of water below the Earth?s surface in underground formations. It is an important factor in managing and sustaining the groundwater resources that are used for drinking water, irr... ver más
Revista: Applied Sciences

 
Xicai Gao, Shuai Liu, Tengfei Ma, Cheng Zhao, Xichen Zhang, Huan Xia and Jianhui Yin    
The main Jurassic coal seams of the Ordos Basin of northwest mining area have special hosting conditions and complex hydrogeological conditions, and the high-intensity coal mining of the coal seams is likely to cause groundwater loss and negative effects... ver más
Revista: Applied Sciences

 
Ismail Mohsine, Ilias Kacimi, Vincent Valles, Marc Leblanc, Badr El Mahrad, Fabrice Dassonville, Nadia Kassou, Tarik Bouramtane, Shiny Abraham, Abdessamad Touiouine, Meryem Jabrane, Meryem Touzani, Abdoul Azize Barry, Suzanne Yameogo and Laurent Barbiero    
In order to facilitate the monitoring of groundwater quality in France, the groundwater bodies (GWB) in the Provence-Alpes-Côte d?Azur region have been grouped into 11 homogeneous clusters on the basis of their physico-chemical and bacteriological charac... ver más
Revista: Hydrology

 
Wanru Li, Mekuanent Muluneh Finsa, Kathryn Blackmond Laskey, Paul Houser and Rupert Douglas-Bate    
Predicting groundwater levels is challenging, especially in regions of water scarcity where data availability is often limited. However, these regions have substantial water needs and require cost-effective groundwater utilization strategies. This study ... ver más
Revista: Water