Multi-time scale stream flow predictions: The support vector machines approach T Asefa, M Kemblowski, M McKee, A Khalil Journal of hydrology 318 (1-4), 7-16, 2006 | 346 | 2006 |
SOIL MOISTURE PREDICTION USING SUPPORT VECTOR MACHINES1 MK Gill, T Asefa, MW Kemblowski, M McKee JAWRA Journal of the American Water Resources Association 42 (4), 1033-1046, 2006 | 304 | 2006 |
Performance evaluation of a water resources system under varying climatic conditions: Reliability, Resilience, Vulnerability and beyond T Asefa, J Clayton, A Adams, D Anderson Journal of Hydrology 508, 53-65, 2014 | 163 | 2014 |
Support vectors–based groundwater head observation networks design T Asefa, MW Kemblowski, G Urroz, M McKee, A Khalil Water Resources Research 40 (11), 2004 | 115 | 2004 |
Effect of missing data on performance of learning algorithms for hydrologic predictions: Implications to an imputation technique MK Gill, T Asefa, Y Kaheil, M McKee Water resources research 43 (7), 2007 | 99 | 2007 |
Multiobjective analysis of chaotic dynamic systems with sparse learning machines AF Khalil, M McKee, M Kemblowski, T Asefa, L Bastidas Advances in Water Resources 29 (1), 72-88, 2006 | 92 | 2006 |
Support vector machines for nonlinear state space reconstruction: Application to the Great Salt Lake time series T Asefa, M Kemblowski, U Lall, G Urroz Water resources research 41 (12), 2005 | 68 | 2005 |
Sparse Bayesian learning machine for real‐time management of reservoir releases A Khalil, M McKee, M Kemblowski, T Asefa Water Resources Research 41 (11), 2005 | 58 | 2005 |
Support vector machines (SVMs) for monitoring network design T Asefa, M Kemblowski, G Urroz, M McKee Groundwater 43 (3), 413-422, 2005 | 58 | 2005 |
Improving short-term urban water demand forecasts with reforecast analog ensembles D Tian, CJ Martinez, T Asefa Journal of Water Resources Planning and Management 142 (6), 04016008, 2016 | 35 | 2016 |
BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1 AF Khalil, M McKee, M Kemblowski, T Asefa JAWRA Journal of the American Water Resources Association 41 (1), 195-208, 2005 | 32 | 2005 |
Impact of different types of ENSO conditions on seasonal precipitation and streamflow in the Southeastern United States H Wang, T Asefa International Journal of Climatology 38 (3), 1438-1451, 2018 | 29 | 2018 |
Proactive water shortage mitigation integrating system optimization and input uncertainty H Wang, T Asefa, D Bracciano, A Adams, N Wanakule Journal of Hydrology 571, 711-722, 2019 | 27 | 2019 |
Evaluation of impacts of future climate change and water use scenarios on regional hydrology S Chang, W Graham, J Geurink, N Wanakule, T Asefa Hydrology and Earth System Sciences 22 (9), 4793-4813, 2018 | 27 | 2018 |
Evaluation of water saving potential for short-term water demand management H Wang, D Bracciano, T Asefa Water Resources Management 34 (10), 3317-3330, 2020 | 24 | 2020 |
A tale of integrated regional water supply planning: Meshing socio-economic, policy, governance, and sustainability desires together T Asefa, A Adams, I Kajtezovic-Blankenship Journal of hydrology 519, 2632-2641, 2014 | 22 | 2014 |
Field‐Scale Application of Three Types of Neural Networks to Predict Ground‐Water Levels1 T Asefa, N Wanakule, A Adams JAWRA Journal of the American Water Resources Association 43 (5), 1245-1256, 2007 | 18 | 2007 |
Application of decision-support tools for seasonal water supply management that incorporates system uncertainties and operational constraints H Wang, T Asefa, N Wanakule, A Adams Journal of Water Resources Planning and Management 146 (6), 05020008, 2020 | 17 | 2020 |
Support vector machines approximation of flow and transport models in initial groundwater contamination network design T Asefa, MW Kemblowski Eos Trans. AGU 83 (47), 2002 | 17 | 2002 |
Evaluating the potential impact of climate change on the hydrology of Ribb catchment, Lake Tana Basin, Ethiopia DW Ayalew, T Asefa, MA Moges, SM Leyew Journal of Water and Climate Change 13 (1), 190-205, 2022 | 15 | 2022 |