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Comparison of machine learning models for predicting groundwater level, case study: Najafabad region

Zarafshan Pejman, Etezadi Hamed, Javadi Saman, Roozbahani Abbas, Hashemy S. Mehdi, Zarafshan Payam

Acta Geophysica

2023

Vol. 71, no. 4

1817--1830

Water resources, consisting of surface water and groundwater, are considered to be among the crucial natural resources in most arid and semiarid regions. Groundwater resources as the sustainable yields can be predicted, whereas this is one of the important stages in water resource management. To this end, several models such as mathematical, statistical, empirical, and conceptual can be employed. In this paper, machine learning and deep learning methods as conceptual ones are applied for the simulations. The selected models are support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), and multilayer perceptron (MLP). Next, these models are optimized with the adaptive moment estimation (ADAM) optimization algorithm which results in hybrid models. The hyper-parameters of the stated models are optimized with the ADAM method. The root mean squared error (RMSE), mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R2) are used to evaluate the accuracy of the simulated groundwater level. To this end, the aquifer hydrograph is used to compare the results with observations data. So, the RMSE and R2 show that the accuracy of the machine learning and deep learning models is better than the numerical model for the given data. Moreover, the MSE is approximately the same in all three cases (ranging from 0.7113 to 0.6504). Also, the total value of R2 and RMSE for the best hybrid model is 0.9617 and 0.7313, respectively, which are obtained from the model output. The results show that all three techniques are useful tools for modeling hydrological processes in agriculture and their computational capabilities and memory are similar.

Sustainable exploitation of groundwater resources considering the effects of climate change and land use to provide adaptation solutions (case study of the Hashtgerd plain)

Hanifehlou Abolfazl, Hosseini Seyed Abbas, Javadi Saman, Sharafati Ahmad

Acta Geophysica

2022

Vol. 70, no 4

1829--1846

Population growth and increasing demand for water have posed a significant challenge to access to safe water resources. Climate change and land use in the not-too-distant future add to the complexity of this challenge. Therefore, it is essential to achieve reliable methods for predicting changes in aquifer storage to plan for the sustainable use of groundwater resources. This study aimed to investigate the management, protection, and sustainable use of groundwater resources under climate change and land use change conditions. In this regard, groundwater supply and demand in one of the important plains in Iran (Hashtgerd plain) for 2020 as the base year was simulated to forecast the trends until 2050 by considering climate change and land use to develop management scenarios to adapt to these conditions using the WEAP model. First, climate change prediction was performed using the HadGEM2-ES model under two emission scenarios, RCP2.6, and RCP8.5, of the IPCC Fifth Assessment Report. The LARS-WG model was used to downscale the climatic data, while land use mapping was performed using Landsat satellite images of 1990, 2005, and 2020 in ENVI 5.3 software. Then, the Markov chain method implemented in TerrSet software was used to model land use change for 2050. The effect of climate change and land use on the decrease of groundwater level was then simulated using the MODFLOW model for the period 2020–2050. In order to manage the water allocation in the area, the information obtained from MODFLOW was transferred to the WEAP model using Link Kitchen interface software. The effects of various management scenarios such as increasing irrigation efficiency, reducing the loss of drinking water distribution networks, and allocating water from the transmission line were evaluated on the adaptation to climate change and land use for a 30-year period. The results showed that with the simultaneous con sideration of climate change and land use in the most critical state, the average drop in groundwater level would reach 58 m during the study period, and aquifer reserves will be reduced by more than 50%. The evaluation of management scenarios showed that their implementation not only will protect aquifer reserves but, in addition to meeting 100% of the water needs, will result in sustainable exploitation of groundwater resources.