Zobrazeno 1 - 10
of 99
pro vyhledávání: '"Abderrahim Jardani"'
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 51, Iss , Pp 101632- (2024)
Study region: Northern Metropolitan France. Study focus: Assessing long-term changes in groundwater is crucial for understanding the impacts of climate change on aquifers and for managing water resources.However, long-term groundwater level (GWL) rec
Externí odkaz:
https://doaj.org/article/7a21d7656dc94d8292a889df725f85e7
Missing data is the first major problem that appears in many database fields for a set of reasons. It has always been necessary to fill them, which becomes unavoidable and more complicated when the missing periods are longer. Several machine-learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46e37657deabd220c8d629b9f1577885
https://doi.org/10.5194/egusphere-egu23-4970
https://doi.org/10.5194/egusphere-egu23-4970
Autor:
Sivarama Krishna Reddy Chidepudi, Nicolas Massei, Abel Henriot, Abderrahim Jardani, Delphine Allier
This study aims to investigate the use of deep learning techniques, with or without data pre-processing for simulating groundwater levels. Two approaches are compared: (1) a single (local) station approach, where a separate model is trained for each
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c14c9490fab6ba70ebf7e17a5d56364
https://doi.org/10.5194/egusphere-egu23-3535
https://doi.org/10.5194/egusphere-egu23-3535
Publikováno v:
Water; Volume 15; Issue 9; Pages: 1773
Water quality monitoring is essential for managing water resources and ensuring human and environmental health. However, obtaining reliable data can be challenging and costly, especially in complex systems such as estuaries. To address this problem,
Autor:
Sivarama Krishna Reddy Chidepudi, Nicolas Massei, Abderrahim Jardani, Abel Henriot, Delphine Allier, Lisa Baulon
The development of groundwater levels (GWL) simulations, based on deep learning (DL) models, is gaining traction due to their success in a wide range of hydrological applications. GWL Simulations allow generating reconstructions to be used for explor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7723244df6dbaa4a8d109d508fac4c9
https://doi.org/10.22541/essoar.167397479.92071086/v1
https://doi.org/10.22541/essoar.167397479.92071086/v1
Autor:
Sivarama Krishna Reddy Chidepudi, Nicolas Massei, Abderrahim Jardani, Abel Henriot, Delphine Allier, Lisa Baulon
Publikováno v:
Science of The Total Environment. 865:161035
Groundwater level (GWL) simulations allow the generation of reconstructions for exploring the past temporal variability of groundwater resources or provide the means for generating projections under climate change on decadal scales. In this context,
Autor:
M T Vu, Abderrahim Jardani
Publikováno v:
Geophysical Journal International. 225:1319-1331
SUMMARY In general, the inverse problem of electrical resistivity tomography (ERT) is treated using a deterministic algorithm to find a model of subsurface resistivity that can numerically match the apparent resistivity data acquired at the ground su
Publikováno v:
Hydrogeology Journal. 28:2713-2726
Imaging characterization of a heterogeneous alluvial aquifer at a decametric scale is presented. The characterization relies on responses to oscillatory pumping tests led in two different wells and at two different periods of oscillation (5 and 10 mi
Publikováno v:
Hydrogeology Journal. 28:2559-2571
The hydraulic characterization of a highly anthropized coastal aquifer in France is presented. The current industrial operations of the study site prevent the use of standard ‘active’ hydrogeological investigation methods (pumping, slug tests). H
Publikováno v:
Geophysical Journal International
Geophysical Journal International, Oxford University Press (OUP), 2020, 221, pp.1469-1483. ⟨10.1093/gji/ggaa082⟩
Geophysical Journal International, Oxford University Press (OUP), 2020, 221, pp.1469-1483. ⟨10.1093/gji/ggaa082⟩
SUMMARY We present an inversion algorithm to reconstruct the spatial distribution of the electrical conductivity from the analysis of magnetometric resistivity (MMR) data acquired at the ground surface. We first review the theoretical background of M