Books and Book Chapters
3. M. Ye, and A.S. Elshall, Machine Learning and Artificial Intelligence in Geoscience: Principles and Applications, World Scientific Publishing (In-Preparation)
2. Elshall, A.S., M. Ye, and Y. Wan, Chapter 11 - Groundwater sustainability in a digital world, In: Letcher, T.M., (Eds.), Water and Climate Change: Sustainable Development, Politics, and Social Issues, Elsevier, Amsterdam, doi.org/10.1016/B978-0-323-99875-8.00012-4
1. Elshall, A.S., J. Castilla-Rho, A.I. El-Kadi, C. Holley, T. Mutongwizo, D. Sinclair, and M. Ye (2021), Sustainability of groundwater, In: Goldstein M.I., and D.A. DellaSala (Eds.), Imperiled: The Encyclopedia of Conservation, Reference Module in Earth Systems and Environmental Sciences, Elsevier, Amsterdam
doi.org/10.1016/B978-0-12-821139-7.00056-8
doi.org/10.1016/B978-0-12-821139-7.00056-8
Publications in Peer-Reviewed Journals
19. Elshall, A.S., and M. Ye , Numerical daemons in Monte Carlo estimation of Bayesian model evidence, SIAM/ASA Journal on Uncertainty Quantification (In-Review)
18. Elshall, A.S., M. Ye, S.A. Kranz, J. Harrington, X. Yang, Y. Wan, and M. Maltrud (2022), Application-specific optimal weighting of global climate models: A red tide example, Climate Services, 28, 100334,
doi.org/10.1016/j.cliser.2022.100334
doi.org/10.1016/j.cliser.2022.100334
17. Mohammadpour, A., A.A. Zarei, R. Dehbandi, R. Khaksefidi, E. Shahsavani, S. Rahimi, A.S. Elshall, and A. Azhdarpoor (2022), Comprehensive assessment of water quality and associated health risks in an arid region in south Iran, Regulatory Toxicology and Pharmacology, 135, 105264,
doi.org/10.1016/j.yrtph.2022.105264
doi.org/10.1016/j.yrtph.2022.105264
16. Elshall, A.S., M. Ye, S.A. Kranz, J. Harrington, X. Yang, Y. Wan, and M. Maltrud (2022), Earth system models for regional environmental management of red tide: Prospects and limitations of the current generation models and next generation development, Environmental Earth Sciences, 81, 256
doi.org/10.1007/s12665-022-10343-7
doi.org/10.1007/s12665-022-10343-7
15. Elshall, A.S., M. Ye, S.A. Kranz, J. Harrington, X. Yang, Y. Wan, and M. Maltrud (2022), Subset selection for improving predictions of Earth system models for regional environmental management of red tide, Frontiers in Earth Science, 10:786223, doi.org/10.3389/feart.2022.786223
14. Bremer, L.L., A.S. Elshall, C.A. Wada, L. Brewington, J. Delevaux, A. El-Kadi, C. Voss, and K., Burnett (2021), Effects of land-cover and watershed protection futures on sustainable groundwater management in a heavily utilized aquifer in Hawai‘i (USA), Hydrogeology Journal, 29, 1749–1765
doi.org/10.1007/s10040-021-02310-6
doi.org/10.1007/s10040-021-02310-6
13. Elshall, A.S., M. Ye, and M. Finkel (2020), Evaluating two multi-model simulation-optimization approaches for managing groundwater contaminant plumes, Journal of Hydrology, 590, 1254272
doi.org/10.1016/j.jhydrol.2020.125427
doi.org/10.1016/j.jhydrol.2020.125427
12. Burnett,K., A.S. Elshall, C.A. Wada, A. Arik, A. El-Kadi, C. Voss, J. Delevaux, and L.L. Bremer (2020), Incorporating historical spring discharge protection into sustainable groundwater management: A case study from Pearl Harbor Aquifer, Hawai‘i, Frontiers in Water, 2:14. doi.org/10.3389/frwa.2020.00014
11. Elshall, A.S., A.D. Arik, A. El-Kadi, S. Pierce, M. Ye, C. A. Wada, K.M. Burnett, L.L. Bremer, and G. Chun (2020), Groundwater sustainability : A review of the interactions between science and policy, Environmental Research Letters, 15 , 093004. doi.org/10.1088/1748-9326/ab8e8c
10. Elshall, A.S., and M. Ye (2019), Making steppingstones out of stumbling blocks: A Bayesian model
evidence estimator with application to groundwater transport model selection. Water, 11(8), 1579. doi.org/10.3390/w11081579
evidence estimator with application to groundwater transport model selection. Water, 11(8), 1579. doi.org/10.3390/w11081579
9. Elshall, A.S., M. Ye, G.-Y. Niu and G. A. Barron-Gafford (2019), Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy , Geoscientific Model Development, 12, 2009-2032. doi.org/10.5194/gmd-12-2009-2019
8. Elshall, A.S., M. Ye, Y. Pei, F. Zhang, G.-Y. Niu and G. A. Barron-Gafford (2018), Relative model score: A scoring rule for evaluating ensemble simulations with application to microbial soil respiration modeling, Stochastic Environmental Research and Risk Assessment, 32(10), 2809–2819.
doi.org/10.1007/s00477-018-1592-3
doi.org/10.1007/s00477-018-1592-3
7. Samani, S., M. Ye, F. Zhang, Y. Pei, G. Tang, A. S. Elshall and A. A. Moghaddam (2018), Impacts of prior parameter distributions on Bayesian evaluation of groundwater model complexity, Water Science and Engineering, 11(2), 89-100. doi.org/10.1016/j.wse.2018.06.001
6. Liu, P, A.S. Elshall, M. Ye, P. Beerli, X. Zeng, D. Lu, M. C. Hill, and Y. Tao (2016), Evaluating model probabilities using Markov chain Monte Carlo with thermodynamics integration, Water Resources Research, 52 ( 2), 734–758. doi.org/10.1002/2014WR016718
5. Elshall, A.S., H. Pham, L. Yan, F.T.-C. Tsai and M. Ye (2015), Parallel inverse modeling and uncertainty quantification of computationally demanding groundwater flow models using covariance matrix adaptation, Journal of Hydrologic Engineering, 20(8), 04014087. doi.org/10.1061/(ASCE)HE.1943-5584.0001126
4. Zhang, X, G.-Y. Niu, A.S. Elshall, M. Ye, G.A. Barron-Gafford and M. Pavao-Zuckerman (2014), Assessing five evolving microbial enzyme models against field measurements from a semiarid savannah: What are the mechanisms of soil respiration pulses? Geophysical Research Letters, 41(18), 6428–6434.
doi.org/10.1002/2014GL061399
doi.org/10.1002/2014GL061399
3. Elshall, A.S., and F.T.-C. Tsai (2014) Constructive epistemic modeling of groundwater flow with geological structure and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119.
doi.org/10.1016/j.jhydrol.2014.05.027
doi.org/10.1016/j.jhydrol.2014.05.027
2. Elshall, A.S., F.T.-C. Tsai, and J.S. Hanor (2013), Indicator geostatistics for reconstructing Baton Rouge aquifer-fault hydrostratigraphy, Louisiana, USA, Hydrogeology Journal, 21(8), 1731-1747.
doi.org/10.1007/s10040-013-1037-5
doi.org/10.1007/s10040-013-1037-5
1. Tsai, F. T.-C., and A.S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation, Water Resources Research, 49(9), 5520–5536. doi.org/10.1002/wrcr.20428
Ph.D. Dissertation
Tile: Characterization and uncertainty analysis of siliciclastic aquifer-fault system
Advisor: Dr. Frank T.-C. Tsai
Funding Sources: U.S. National Science Foundation and U.S. Geological Survey
Tile: Characterization and uncertainty analysis of siliciclastic aquifer-fault system
Advisor: Dr. Frank T.-C. Tsai
Funding Sources: U.S. National Science Foundation and U.S. Geological Survey
M.Sc. Thesis
Title: Practical design optimization of pump-and-treat systems at complex real-world sites using evolution strategies
Advisors: Dr. Michael Finkel | Dr. Olaf Cirpka | Dr. Peter Bayer
Funding Source: Evolution and Ecology Forum, Tübingen
Title: Practical design optimization of pump-and-treat systems at complex real-world sites using evolution strategies
Advisors: Dr. Michael Finkel | Dr. Olaf Cirpka | Dr. Peter Bayer
Funding Source: Evolution and Ecology Forum, Tübingen