25 citations as recorded by crossref.

1. Citizen science: A new perspective to advance spatial pattern evaluation in hydrology J. Koch et al. 10.1371/journal.pone.0178165
2. Quantifying spatial uncertainty in rock through geostatistical integration of borehole data and a geologist's cross-section D. Boyd et al. 10.1016/j.enggeo.2019.105246
3. Toward real-time three-dimensional mapping of surficial aquifers using a hybrid modeling approach M. Friedel et al. 10.1007/s10040-015-1318-2
4. Assessing hydrological model predictive uncertainty using stochastically generated geological models X. He et al. 10.1002/hyp.10488
5. Markov based transition probability geostatistics in groundwater applications: assumptions and limitations A. Langousis et al. 10.1007/s00477-017-1504-y
6. The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models J. Koch et al. 10.5194/gmd-11-1873-2018
7. Research on appropriate borehole density for establishing reliable geological model based on quantitative uncertainty analysis Q. Sun et al. 10.1007/s12517-019-4533-7
8. Integrating multiple scales of hydraulic conductivity measurements in training image-based stochastic models K. Mahmud et al. 10.1002/2014WR016150
9. Estimation and scaling of hydrostratigraphic units: application of unsupervised machine learning and multivariate statistical techniques to hydrogeophysical data M. Friedel 10.1007/s10040-016-1452-5
10. Multiple point statistical simulation using uncertain (soft) conditional data T. Hansen et al. 10.1016/j.cageo.2018.01.017
11. Finding patterns in subsurface using Bayesian machine learning approach H. Wang 10.1016/j.undsp.2018.10.006
12. Probabilistic predictions using a groundwater model informed with airborne EM data P. Marker et al. 10.1016/j.advwatres.2017.03.002
13. Combining 3D geological modelling techniques to address variations in geology, data type and density – An example from Southern Denmark F. Jørgensen et al. 10.1016/j.cageo.2015.04.010
14. Spatial validation of large-scale land surface models against monthly land surface temperature patterns using innovative performance metrics J. Koch et al. 10.1002/2015JD024482
15. A Segmentation Approach for Stochastic Geological Modeling Using Hidden Markov Random Fields H. Wang et al. 10.1007/s11004-016-9663-9
16. Large-Scale $$\hbox {CO}_2$$ CO 2 Storage in a Deep Saline Aquifer: Uncertainties in Predictions Due to Spatial Variability of Flow Parameters and Their Modeling S. Bouquet et al. 10.1007/s11242-015-0590-x
17. Bayesian approach for probabilistic site characterization assimilating borehole experiments and Cone Penetration Tests C. Wang et al. 10.1016/j.enggeo.2016.04.002
18. Three-dimensional geological modelling of AEM resistivity data — A comparison of three methods A. Høyer et al. 10.1016/j.jappgeo.2015.02.005
19. Modeling complex aquifer systems: a case study in Baton Rouge, Louisiana (USA) H. Pham & F. Tsai 10.1007/s10040-016-1532-6
20. Spatial Sensitivity Analysis of Simulated Land Surface Patterns in a Catchment Model Using a Set of Innovative Spatial Performance Metrics J. Koch et al. 10.1175/JHM-D-16-0148.1
21. Modeling Depth of the Redox Interface at High Resolution at National Scale Using Random Forest and Residual Gaussian Simulation J. Koch et al. 10.1029/2018WR023939
22. Where are the limits of model predictive capabilities? J. Refsgaard et al. 10.1002/hyp.11029
23. Importance of geological information for assessing drain flow in a Danish till landscape A. Hansen et al. 10.1002/hyp.13338
24. Constraining distance-based multipoint simulations to proportions and trends G. Mariethoz et al. 10.1016/j.envsoft.2015.07.007
25. Uncertainty assessment of spatially distributed nitrate reduction potential in groundwater using multiple geological realizations A. Hansen et al. 10.1016/j.jhydrol.2014.07.013