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217 results on '"Javadi, Saman"'

1. Decline in Irans groundwater recharge.

Author

Noori, Roohollah, Maghrebi, Mohsen, Jessen, Søren, Bateni, Sayed, Heggy, Essam, Javadi, Saman, Noury, Mojtaba, Pistre, Severin, Abolfathi, Soroush, and AghaKouchak, Amir

Abstract

Groundwater recharge feeds aquifers supplying fresh-water to a population over 80 million in Iran-a global hotspot for groundwater depletion. Using an extended database comprising abstractions from over one million groundwater wells, springs, and qanats, from 2002 to 2017, here we show a significant decline of around -3.8 mm/yr in the nationwide groundwater recharge. This decline is primarily attributed to unsustainable water and environmental resources management, exacerbated by decadal changes in climatic conditions. However, it is important to note that the formers contribution outweighs the latter. Our results show the average annual amount of nationwide groundwater recharge (i.e., ~40 mm/yr) is more than the reported average annual runoff in Iran (i.e., ~32 mm/yr), suggesting the surface water is the main contributor to groundwater recharge. Such a decline in groundwater recharge could further exacerbate the already dire aquifer depletion situation in Iran, with devastating consequences for the countrys natural environment and socio-economic development.

Published
2023

5. Artificial Intelligence Hybrid Deep Learning Model for Groundwater Level Prediction Using MLP-ADAM

Author

Zarafshan, Pejman, Javadi, Saman, Roozbahani, Abbas, Hashemy, Seyed Mehdi, Zarafshan, Payam, and Etezadi, Hamed

Subjects
Computer Science - Machine Learning, Physics - Geophysics
Abstract

Groundwater is the largest storage of freshwater resources, which serves as the major inventory for most of the human consumption through agriculture, industrial, and domestic water supply. In the fields of hydrological, some researchers applied a neural network to forecast rainfall intensity in space-time and introduced the advantages of neural networks compared to numerical models. Then, many researches have been conducted applying data-driven models. Some of them extended an Artificial Neural Networks (ANNs) model to forecast groundwater level in semi-confined glacial sand and gravel aquifer under variable state, pumping extraction and climate conditions with significant accuracy. In this paper, a multi-layer perceptron is applied to simulate groundwater level. The adaptive moment estimation optimization algorithm is also used to this matter. The root mean squared error, mean absolute error, mean squared error and the coefficient of determination ( ) are used to evaluate the accuracy of the simulated groundwater level. Total value of and RMSE are 0.9458 and 0.7313 respectively which are obtained from the model output. Results indicate that deep learning algorithms can demonstrate a high accuracy prediction. Although the optimization of parameters is insignificant in numbers, but due to the value of time in modelling setup, it is highly recommended to apply an optimization algorithm in modelling.

Published
2021

19. Climate Change and Its Impact on Runoff and Sediment Yield (Case Study: Dez River Dam, Iran)

Author

Eini, Mohammad Reza, Mohammadi, Kourosh, Najib, Reza, Javadi, Saman, Golmohammadi, Golmar, Pisello, Anna Laura, Editorial Board Member, Hawkes, Dean, Editorial Board Member, Bougdah, Hocine, Editorial Board Member, Rosso, Federica, Editorial Board Member, Abdalla, Hassan, Editorial Board Member, Boemi, Sofia-Natalia, Editorial Board Member, Mohareb, Nabil, Editorial Board Member, Mesbah Elkaffas, Saleh, Editorial Board Member, Bozonnet, Emmanuel, Editorial Board Member, Pignatta, Gloria, Editorial Board Member, Mahgoub, Yasser, Editorial Board Member, De Bonis, Luciano, Editorial Board Member, Kostopoulou, Stella, Editorial Board Member, Pradhan, Biswajeet, Editorial Board Member, Abdul Mannan, Md., Editorial Board Member, Alalouch, Chaham, Editorial Board Member, O. Gawad, Iman, Editorial Board Member, Nayyar, Anand, Editorial Board Member, Amer, Mourad, Series Editor, Chenchouni, Haroun, editor, Chaminé, Helder I., editor, Khan, Md Firoz, editor, Merkel, Broder J., editor, Zhang, Zhihua, editor, Li, Peiyue, editor, Kallel, Amjad, editor, and Khélifi, Nabil, editor

Published
2022
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21. Improvement of GIS-Based DRASTIC Model Using Step-Wise Weight Assessment Ratio Analysis (SWARA) and Two New Hybrid Frameworks (Iran)

Author

Torkashvand, Maryam, Neshat, Aminreza, Javadi, Saman, Yousefi, Hossein, Förstner, Ulrich, Series Editor, Rulkens, Wim H., Series Editor, Salomons, Wim, Series Editor, Ksibi, Mohamed, editor, Ghorbal, Achraf, editor, Chakraborty, Sudip, editor, Chaminé, Helder I., editor, Barbieri, Maurizio, editor, Guerriero, Giulia, editor, Hentati, Olfa, editor, Negm, Abdelazim, editor, Lehmann, Anthony, editor, Römbke, Jörg, editor, Costa Duarte, Armando, editor, Xoplaki, Elena, editor, Khélifi, Nabil, editor, Colinet, Gilles, editor, Miguel Dias, João, editor, Gargouri, Imed, editor, Van Hullebusch, Eric D., editor, Sánchez Cabrero, Benigno, editor, Ferlisi, Settimio, editor, Tizaoui, Chedly, editor, Kallel, Amjad, editor, Rtimi, Sami, editor, Panda, Sandeep, editor, Michaud, Philippe, editor, Sahu, Jaya Narayana, editor, Seffen, Mongi, editor, and Naddeo, Vincenzo, editor

Published
2021
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