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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Bahareh Kalantar, Husam A. H. Al-Najjar, Biswajeet Pradhan, Vahideh Saeidi, Alfian Abdul Halin, Naonori Ueda and Seyed Amir Naghibi
Assessment of the most appropriate groundwater conditioning factors (GCFs) is essential when performing analyses for groundwater potential mapping. For this reason, in this work, we look at three statistical factor analysis methods?Variance Inflation Fac...
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Byung-Moon Jun, Yejin Kim, Jonghun Han, Yeomin Yoon, Jeonggwan Kim and Chang Min Park
For this study, we applied activated biochar (AB) and its composition with magnetite (AB-Fe3O4) as adsorbents for the removal of polychlorophenols in model wastewater. We comprehensively characterized these adsorbents and performed adsorption tests under...
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Ivan Gabriel-Martin, Alvaro Sordo-Ward, Luis Garrote and Juan T. García
This paper focuses on proposing the minimum number of storms necessary to derive the extreme flood hydrographs accurately through event-based modelling. To do so, we analyzed the results obtained by coupling a continuous stochastic weather generator (the...
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Masoud Jafari Shalamzari, Wanchang Zhang, Atefeh Gholami and Zhijie Zhang
Site selection for runoff harvesting at large scales is a very complex task. It requires inclusion and spatial analysis of a multitude of accurately measured parameters in a time-efficient manner. Compared with direct measurements of runoff, which is tim...
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