Groundwater Level Prediction in Golpayegan Aquifer Using ANFIS and PSO Combination

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SALARI SEDIGHEH; MOGHADDASI MAHNOOSH; MOHAMMADI GHALENI MEHDI; AKBARI MAHMOOD

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Journal Paper

Paper Information

Journal: Iranian Journal of Soil and Water Research Year:2021 | Volume:52 | Issue:3 Page(s): 721-732

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Title

Groundwater Level Prediction in Golpayegan Aquifer Using ANFIS and PSO Combination

Author(s)

SALARI SEDIGHEH | MOGHADDASI MAHNOOSH | MOHAMMADI GHALENI MEHDI | AKBARI MAHMOOD | Issue Writer Certificate

Keywords

Agglomerative Hierarchical ClusteringQ1

Groundwater Level PredictionQ1

Neuro-Fuzzy Adaptive Inference SystemQ1

Particle Swarm Optimization AlgorithmQ1

Spatial and Temporal AnalysisQ1

Abstract

Groundwater Level Prediction is an essential priority for planning and managing groundwater resources. This study aimed to compare the accuracy of the Neuro-Fuzzy Adaptive Inference System (ANFIS) model with the ANFIS model combined with Particle Swarm Optimization Algorithm (ANFIS+PSO) in predicting the monthly groundwater level of Golpayegan aquifer during 2002-2019. For this purpose, monthly data on rainfall, temperature, pan evaporation in the selected meteorological stations, discharge volume of exploitation wells and groundwater level of observation wells have been used. After Spatial and Temporal Analysis, four observation wells with two input data structures (S1 and S2) were selected to predict the groundwater level. The results of trend and homogeneity tests show a 99% significance of groundwater level changes in the selected observation wells 4, 8, 19 and 20 with a sudden drop of 22, 17, 27 and 2 meters before and after June, September, July and August 2010, respectively. The highest and the lowest accuracy of Groundwater Level Prediction is related to observation wells 20 and 4 with root mean square error values (RMSE) of 2. 37 and 0. 21 m, respectively, related to ANFIS_S1 and ANFIS + PSO_S2 models. Generally, the results of this study indicate that the selection of appropriate structure of input data is more effective than the combination of two models (ANFIS and PSO) in increasing the accuracy of Groundwater Level Prediction. So, that the optimal structure of input data and the combination of optimized algorithm model have increased the accuracy of Groundwater Level Prediction, 44% and 25%, respectively.

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APA: Copy

SALARI, SEDIGHEH, MOGHADDASI, MAHNOOSH, MOHAMMADI GHALENI, MEHDI, & AKBARI, MAHMOOD. (2021). Groundwater Level Prediction in Golpayegan Aquifer Using ANFIS and PSO Combination. IRANIAN JOURNAL OF SOIL AND WATER RESEARCH, 52(3 ), 721-732. SID. https://sid.ir/paper/370921/en

Vancouver: Copy

SALARI SEDIGHEH, MOGHADDASI MAHNOOSH, MOHAMMADI GHALENI MEHDI, AKBARI MAHMOOD. Groundwater Level Prediction in Golpayegan Aquifer Using ANFIS and PSO Combination. IRANIAN JOURNAL OF SOIL AND WATER RESEARCH[Internet]. 2021;52(3 ):721-732. Available from: https://sid.ir/paper/370921/en

IEEE: Copy

SEDIGHEH SALARI, MAHNOOSH MOGHADDASI, MEHDI MOHAMMADI GHALENI, and MAHMOOD AKBARI, “Groundwater Level Prediction in Golpayegan Aquifer Using ANFIS and PSO Combination,” IRANIAN JOURNAL OF SOIL AND WATER RESEARCH, vol. 52, no. 3 , pp. 721–732, 2021, [Online]. Available: https://sid.ir/paper/370921/en

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