Tanja Liesch

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Nico GoldscheiderProfessor for Hydrogeology, Karlsruhe Institute of TechnologyEmail yang diverifikasi di kit.edu
Andreas WunschFraunhofer IOSBEmail yang diverifikasi di iosb.fraunhofer.de
Marc OhmerDepartment of Hydrogeology, Karlsruhe Institute of TechnologyEmail yang diverifikasi di kit.edu
Julian XankeDVGW - Technologiezentrum Wasser (German Water Centre)Email yang diverifikasi di tzw.de
Stefan BrodaFederal Institute for Geosciences and Natural Resources (Bundesanstalt für Geowissenschaften undEmail yang diverifikasi di bgr.de
Nadine GoeppertProfessor, Freie Universität BerlinEmail yang diverifikasi di fu-berlin.de
Zhao ChenSenior scientist / Lecturer / Group leader, Institute for Groundwater Management (TU Dresden)Email yang diverifikasi di tu-dresden.de
Natasa RavbarEmail yang diverifikasi di zrc-sazu.si
Naomi MazzilliAvignon UniversitéEmail yang diverifikasi di univ-avignon.fr
Guillaume CinkusPostdoctoral researcherEmail yang diverifikasi di umontpellier.fr
Kathrin MenbergInstitute of Applied Geosciences, Karlsruhe Institut of Technology (KIT)Email yang diverifikasi di kit.edu
Jakob ZopfiUniversität BaselEmail yang diverifikasi di zopfi.com
Moritz F LehmannUniversity of BaselEmail yang diverifikasi di unibas.ch
Laurence GillTrinity College DublinEmail yang diverifikasi di tcd.ie
Pierre-Yves JeanninInstitut suisse de spéléologie et de karstologie, ISSKAEmail yang diverifikasi di isska.ch
Jean-Baptiste CharlierBRGM, UMR G-Eau, MontpellierEmail yang diverifikasi di brgm.fr
Stefan GeyerHelmholtz Zentrum für Umweltforschung - UFZEmail yang diverifikasi di ufz.de
Felix GrimmeisenOkeanos Smart Data Solutions GmbH

Ikuti

Tanja Liesch

Senior Hydrogeologist, Karlsruhe Institute of Technology KIT

Email yang diverifikasi di kit.edu - Beranda

Hydrogeology Numerical Modeling Statistics Artificial Intelligence Machine Learning


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX) A Wunsch, T Liesch, S Broda Journal of Hydrology 567, 743-758, 2018	224	2018
Groundwater level forecasting with artificial neural networks: a comparison of long short-term memory (LSTM), convolutional neural networks (CNNs), and non-linear … A Wunsch, T Liesch, S Broda Hydrology and Earth System Sciences 25 (3), 1671-1687, 2021	216	2021
Uranium in groundwater—fertilizers versus geogenic sources T Liesch, S Hinrichsen, N Goldscheider Science of the Total Environment 536, 981-995, 2015	149	2015
Deep learning shows declining groundwater levels in Germany until 2100 due to climate change A Wunsch, T Liesch, S Broda Nature communications 13 (1), 1221, 2022	128	2022
Isotopic constraints on water source mixing, network leakage and contamination in an urban groundwater system F Grimmeisen, MF Lehmann, T Liesch, N Goeppert, J Klinger, J Zopfi, ... Science of the Total Environment 583, 202-213, 2017	83	2017
Karst modelling challenge 1: Results of hydrological modelling PY Jeannin, G Artigue, C Butscher, Y Chang, JB Charlier, L Duran, L Gill, ... Journal of Hydrology 600, 126508, 2021	69	2021
On the optimal selection of interpolation methods for groundwater contouring: An example of propagation of uncertainty regarding inter-aquifer exchange M Ohmer, T Liesch, N Goeppert, N Goldscheider Advances in Water Resources 109, 121-132, 2017	68	2017
Quantification and possible causes of declining groundwater resources in the Euro-Mediterranean region from 2003 to 2020 J Xanke, T Liesch Hydrogeology Journal 30 (2), 379-400, 2022	59	2022
Comparison of GRACE data and groundwater levels for the assessment of groundwater depletion in Jordan T Liesch, M Ohmer Hydrogeology Journal 24 (6), 1547, 2016	55	2016
Impact of managed aquifer recharge on the chemical and isotopic composition of a karst aquifer, Wala reservoir, Jordan J Xanke, N Goeppert, A Sawarieh, T Liesch, J Kinger, W Ali, H Hötzl, ... Hydrogeology Journal 23 (5), 1027-1040, 2015	42	2015
Karst spring discharge modeling based on deep learning using spatially distributed input data A Wunsch, T Liesch, G Cinkus, N Ravbar, Z Chen, N Mazzilli, H Jourde, ... Hydrology and Earth System Sciences 26 (9), 2405-2430, 2022	41	2022
Aquifer responses to long-term climatic periodicities T Liesch, A Wunsch Journal of Hydrology 572, 226-242, 2019	39	2019
Numerical long-term assessment of managed aquifer recharge from a reservoir into a karst aquifer in Jordan J Xanke, H Jourde, T Liesch, N Goldscheider Journal of hydrology 540, 603-614, 2016	37	2016
Contamination risk and drinking water protection for a large-scale managed aquifer recharge site in a semi-arid karst region, Jordan J Xanke, T Liesch, N Goeppert, J Klinger, N Gassen, N Goldscheider Hydrogeology Journal 25 (6), 1795, 2017	36	2017
Modelling groundwater over-extraction in the southern Jordan Valley with scarce data P Alfaro, T Liesch, N Goldscheider Hydrogeology Journal 25 (5), 1319, 2017	34	2017
Groundwater level forecasting with artificial neural networks: A comparison of LSTM, CNN and NARX A Wunsch, T Liesch, S Broda Hydrol. Earth Syst. Sci. Discuss 552, 1-23, 2020	28	2020
Feature-based groundwater hydrograph clustering using unsupervised self-organizing map-ensembles A Wunsch, T Liesch, S Broda Water Resources Management 36 (1), 39-54, 2022	26	2022
Open-loop geothermal heating by combined extraction–injection one-well systems: A feasibility study A Rode, T Liesch, N Goldscheider Geothermics 56, 110-118, 2015	25	2015
Deep learning shows declining groundwater levels in Germany until 2100 due to climate change, Nat. Commun., 13, 1221 A Wunsch, T Liesch, S Broda	22	2022
Comparison of artificial neural networks and reservoir models for simulating karst spring discharge on five test sites in the Alpine and Mediterranean regions G Cinkus, A Wunsch, N Mazzilli, T Liesch, Z Chen, N Ravbar, J Doummar, ... Hydrology and Earth System Sciences Discussions 2022, 1-41, 2022	18	2022

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