D. Erdal

发表

Joint inference of groundwater–recharge and hydraulic–conductivity fields from head data using the ensemble Kalman filter

O. Cirpka, D. Erdal, 2015 .

Global Sensitivity Analysis and Adaptive Stochastic Sampling of a Subsurface-Flow Model Using Active Subspaces

O. Cirpka, D. Erdal, 2019 .

Preconditioning an ensemble Kalman filter for groundwater flow using environmental-tracer observations

O. Cirpka, D. Erdal, 2017 .

Comparison of Two Ensemble Kalman-Based Methods for Estimating Aquifer Parameters from Virtual 2-D Hydraulic and Tracer Tomographic Tests

O. Cirpka, D. Erdal, C. Leven, 2020 .

Soil moisture prediction with the ensemble Kalman filter: Handling uncertainty of soil hydraulic parameters

I. Neuweiler, D. Erdal, N. Brandhorst, 2017 .

The importance of state transformations when using the ensemble Kalman filter for unsaturated flow modeling: Dealing with strong nonlinearities

I. Neuweiler, M. A. Rahman, D. Erdal, 2015 .

Presentation and discussion of the high resolution atmosphere-land surface subsurface simulation dataset of the virtual Neckar catchment for the period 2007–2015

S. Attinger, H. Hendricks Franssen, S. Kollet, 2020 .

Technical Note: Improved sampling of behavioral subsurface flow model parameters using active subspaces

O. Cirpka, D. Erdal, 2020, Hydrology and Earth System Sciences.

A Stochastic Framework to Optimize Monitoring Strategies for Delineating Groundwater Divides

Olaf A. Cirpka, Ana González-Nicolás, Wolfgang Nowak, 2020, Frontiers in Earth Science.

A Non‐Local Richards Equation to Model Unsaturated Flow in Highly Heterogeneous Media under Nonequilibrium Pressure Conditions

M. Dentz, I. Neuweiler, D. Erdal, 2012 .

Sampling behavioral model parameters for ensemble-based sensitivity analysis using Gaussian process emulation and active subspaces

Olaf A. Cirpka, Wolfgang Nowak, Daniel Erdal, 2020, Stochastic Environmental Research and Risk Assessment.

Global sensitivity analysis and adaptive stochastic sampling of a subsurface-flow model using active subspaces

Olaf A. Cirpka, Daniel Erdal, O. Cirpka, 2019, Hydrology and Earth System Sciences.

The value of simplified models for spin up of complex models with an application to subsurface hydrology

Olaf A. Cirpka, Gabriele Baroni, Daniel Erdal, 2019, Comput. Geosci..

Estimating effective model parameters for heterogeneous unsaturated flow using error models for bias correction

Insa Neuweiler, Daniel Erdal, J. Huisman, 2012 .

Using a bias aware EnKF to account for unresolved structure in an unsaturated zone model

Insa Neuweiler, Ute Wollschläger, Daniel Erdal, 2014 .

Comparison of Two Ensemble-Kalman Filter Based Methods for Estimating Aquifer Parameters from Real 3-D Hydraulic and Tracer Tomographic Tests

O. Cirpka, D. Erdal, C. Leven, 2020, Geosciences.