Year |
Citation |
Score |
2020 |
Wang H, Asefa T, Wanakule N, Adams A. Application of Decision-Support Tools for Seasonal Water Supply Management that Incorporates System Uncertainties and Operational Constraints Journal of Water Resources Planning and Management. 146: 5020008. DOI: 10.1061/(Asce)Wr.1943-5452.0001225 |
0.434 |
|
2020 |
Wang H, Bracciano D, Asefa T. Evaluation of Water Saving Potential for Short-Term Water Demand Management Water Resources Management. 34: 3317-3330. DOI: 10.1007/S11269-020-02615-3 |
0.412 |
|
2019 |
Wang H, Asefa T, Bracciano D, Adams A, Wanakule N. Proactive water shortage mitigation integrating system optimization and input uncertainty Journal of Hydrology. 571: 711-722. DOI: 10.1016/J.Jhydrol.2019.01.071 |
0.458 |
|
2018 |
Chang S, Graham W, Geurink J, Wanakule N, Asefa T. Evaluation of impacts of future climate change and water use scenarios on regional hydrology Hydrology and Earth System Sciences. 22: 4793-4813. DOI: 10.5194/Hess-22-4793-2018 |
0.423 |
|
2018 |
Chang S, Graham W, Geurink J, Wanakule N, Asefa T. Evaluation of impact of climate change and anthropogenic change on regional hydrology Hydrology and Earth System Sciences Discussions. 1-43. DOI: 10.5194/Hess-2018-91 |
0.402 |
|
2018 |
Panaou T, Asefa T, Nachabe MH. Keeping Us Honest: Examining Climate States and Transition Probabilities of Precipitation Projections in General Circulation Models Journal of Water Resources Planning and Management. 144: 04018008. DOI: 10.1061/(Asce)Wr.1943-5452.0000910 |
0.328 |
|
2018 |
Wang H, Asefa T. Impact of different types of ENSO conditions on seasonal precipitation and streamflow in the Southeastern United States International Journal of Climatology. 38: 1438-1451. DOI: 10.1002/Joc.5257 |
0.321 |
|
2016 |
Fullerton TM, Walke AG, Asefa T. Short‐Run Water Demand Forecast Accuracy for the Tampa Bay Area Journal American Water Works Association. 108. DOI: 10.5942/Jawwa.2016.108.0011 |
0.429 |
|
2016 |
Tian D, Martinez CJ, Asefa T. Improving Short-Term Urban Water Demand Forecasts with Reforecast Analog Ensembles Journal of Water Resources Planning and Management. 142: 04016008. DOI: 10.1061/(Asce)Wr.1943-5452.0000632 |
0.447 |
|
2015 |
Asefa T, Adams A, Wanakule N. A Level-of-Service Concept for Planning Future Water Supply Projects under Probabilistic Demand and Supply Framework† Journal of the American Water Resources Association. 51: 1272-1285. DOI: 10.1111/1752-1688.12309 |
0.395 |
|
2015 |
Asefa T. Innovative Systems-Based Decision Support: Tales for the Real World Journal of Water Resources Planning and Management. 141: 1815001. DOI: 10.1061/(Asce)Wr.1943-5452.0000565 |
0.408 |
|
2014 |
Asefa T, Wanakule N, Adams A, Shelby J, Clayton J. On the Use of System Performance Metrics for Assessing the Value of Incremental Water-Use Permits Journal of Water Resources Planning and Management. 140: 4014012-4014012. DOI: 10.1061/(Asce)Wr.1943-5452.0000388 |
0.473 |
|
2014 |
Asefa T, Adams A, Kajtezovic-Blankenship I. A tale of integrated regional water supply planning: Meshing socio-economic, policy, governance, and sustainability desires together Journal of Hydrology. 519: 2632-2641. DOI: 10.1016/J.Jhydrol.2014.05.047 |
0.433 |
|
2014 |
Asefa T, Clayton J, Adams A, Anderson D. Performance evaluation of a water resources system under varying climatic conditions: Reliability, Resilience, Vulnerability and beyond Journal of Hydrology. 508: 53-65. DOI: 10.1016/J.Jhydrol.2013.10.043 |
0.457 |
|
2013 |
Asefa T, Adams A. Reducing bias-corrected precipitation projection uncertainties: a Bayesian-based indicator-weighting approach Regional Environmental Change. 13: 111-120. DOI: 10.1007/S10113-013-0431-9 |
0.326 |
|
2009 |
Asefa T. Ensemble streamflow forecast: a GLUE-based neural network approach. Journal of the American Water Resources Association. 45: 1155-1163. DOI: 10.1111/J.1752-1688.2009.00351.X |
0.387 |
|
2007 |
Asefa T, Wanakule N, Adams A. Field-scale application of three types of neural networks to predict ground-water levels Journal of the American Water Resources Association. 43: 1245-1256. DOI: 10.1111/J.1752-1688.2007.00107.X |
0.456 |
|
2007 |
Gill MK, Asefa T, Kaheil Y, McKee M. Effect of missing data on performance of learning algorithms for hydrologic predictions: Implications to an imputation technique Water Resources Research. 43. DOI: 10.1029/2006Wr005298 |
0.455 |
|
2006 |
Gill MK, Asefa T, Kemblowski MW, McKee M. Soil moisture prediction using support vector machines Journal of the American Water Resources Association. 42: 1033-1046. DOI: 10.1111/J.1752-1688.2006.Tb04512.X |
0.718 |
|
2006 |
Asefa T, Kemblowski M, McKee M, Khalil A. Multi-time scale stream flow predictions: The support vector machines approach Journal of Hydrology. 318: 7-16. DOI: 10.1016/J.Jhydrol.2005.06.001 |
0.75 |
|
2006 |
Khalil AF, McKee M, Kemblowski M, Asefa T, Bastidas L. Multiobjective analysis of chaotic dynamic systems with sparse learning machines Advances in Water Resources. 29: 72-88. DOI: 10.1016/J.Advwatres.2005.05.011 |
0.74 |
|
2005 |
Asefa T, Kemblowski M, Urroz G, McKee M. Support vector machines (SVMs) for monitoring network design. Ground Water. 43: 413-22. PMID 15882333 DOI: 10.1111/J.1745-6584.2005.0050.X |
0.737 |
|
2005 |
Khalil AF, McKee M, Kemblowski M, Asefa T. BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS Journal of the American Water Resources Association. 41: 195-208. DOI: 10.1111/J.1752-1688.2005.Tb03728.X |
0.722 |
|
2005 |
Khalil A, McKee M, Kemblowski M, Asefa T. Sparse Bayesian learning machine for real-time management of reservoir releases Water Resources Research. 41. DOI: 10.1029/2004Wr003891 |
0.757 |
|
2005 |
Asefa T, Kemblowski M, Lall U, Urroz G. Support vector machines for nonlinear state space reconstruction: Application to the Great Salt Lake time series Water Resources Research. 41: 1-10. DOI: 10.1029/2004Wr003785 |
0.738 |
|
2004 |
Asefa T, Kemblowski MW, Urroz G, McKee M, Khalil A. Support vectors-based groundwater head observation networks design Water Resources Research. 40. DOI: 10.1029/2004Wr003304 |
0.727 |
|
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