A5079024483- Hydrology and Watershed Management Studies
- Groundwater flow and contamination studies
- Soil and Unsaturated Flow
- Soil and Water Nutrient Dynamics
- Groundwater and Isotope Geochemistry
- Reservoir Engineering and Simulation Methods
- Hydrological Forecasting Using AI
- Plant Water Relations and Carbon Dynamics
- Soil Moisture and Remote Sensing
- Hydrology and Sediment Transport Processes
- Hydrology and Drought Analysis
- Flood Risk Assessment and Management
- Climate change impacts on agriculture
- Climate variability and models
- Irrigation Practices and Water Management
- Greenhouse Technology and Climate Control
- Fault Detection and Control Systems
- Soil erosion and sediment transport
- Karst Systems and Hydrogeology
- Landslides and related hazards
- Wastewater Treatment and Nitrogen Removal
- Bayesian Modeling and Causal Inference
- Probabilistic and Robust Engineering Design
- Model Reduction and Neural Networks
- Groundwater and Watershed Analysis
Lincoln Agritech (New Zealand)
2016-2025
TU Dresden
2016-2025
Norsk Hydro (Germany)
2007-2025
Lincoln University
2006-2024
University of Potsdam
2022-2024
Institute of Hydrology of the Slovak Academy of Sciences
2022
Indian Institute of Technology Kharagpur
2022
Helmholtz Centre for Environmental Research
2022
National Institute of Meteorology
2022
University of Tübingen
2011-2018
Core Ideas A community effort is needed to move soil modeling forward. Establishing an international consortium key in this respect. There a need better integrate existing knowledge models. Integration of data and models challenge modeling. The remarkable complexity its importance wide range ecosystem services presents major challenges the processes. Although progress has occurred last decades, processes remain disjointed between disciplines or services, with considerable uncertainty...
The complexity of karst groundwater flow modelling is reflected by the amount simulation approaches. goal Karst Modelling Challenge (KMC) comparing different approaches on one single system using same data set. Thirteen teams with computational models for simulating discharge variations at springs have applied their respective set coming from Milandre Hydrogeological System (MKHS). include neural networks, reservoir models, semi-distributed and fully distributed models. Four a half years...
Bayesian model selection or averaging objectively ranks a number of plausible, competing conceptual models based on Bayes' theorem. It implicitly performs an optimal trade-off between performance in fitting available data and minimum complexity. The procedure requires determining evidence (BME), which is the likelihood observed integrated over each model's parameter space. computation this integral highly challenging because it as high-dimensional parameters. Three classes techniques to...
Abstract Selecting a “best” model among several competing candidate models poses an often encountered problem in water resources modeling (and other disciplines which employ models). For modeler, the best fulfills certain purpose (e.g., flood prediction), is typically assessed by comparing simulations to data stream flow). Model selection methods find trade‐off between good fit with and complexity. In this context, interpretations of complexity implied different are crucial, because they...
Inverse modeling has become increasingly popular for estimating effective hydraulic properties across a range of spatial scales. In recent years, many different algorithms have been developed to solve complex multiobjective optimization problems. this study, we compared the efficiency Nondominated Sorting Genetic Algorithm (NSGA‐II), Multiobjective Shuffled Complex Evolution Metropolis algorithm (MOSCEM‐UA), and AMALGAM, multialgorithm genetically adaptive search method estimation soil...
In the past two decades significant progress has been made toward application of inverse modeling to estimate water retention and hydraulic conductivity functions vadose zone at different spatial scales. Many these contributions have focused on estimating only a few soil parameters, without recourse appropriately capturing addressing variability. The assumption homogeneous medium significantly simplifies complexity resulting problem, allowing use classical parameter estimation algorithms....
Interactions between the soil, vegetation, and atmospheric boundary layer require close attention when predicting water fluxes in hydrogeosystem, agricultural systems, weather, climate. However, land-surface schemes used large-scale models continue to show deficiencies consistently simulating of energy from subsurface through vegetation layers atmosphere. In this study, multiphysics version Noah model (Noah-MP) was identify processes, which are most crucial for a simultaneous simulation heat...
Abstract A major effect of environment on crops is through crop phenology, and therefore, the capacity to predict phenology for new environments important. Mechanistic models are a tool such predictions, but calibration difficult there no consensus best approach. We propose an original, detailed approach models, which we refer as protocol. The protocol covers all steps in workflow, namely choice default parameter values, objective function, parameters estimate from data, calculation optimal...
Groundwater resources are fully allocated in many coastal aquifers New Zealand. External forces such as a reduction recharge and climate change add additional pressure for sustainable management of the resource. levels unconfined Wairau Aquifer (Marlborough, Zealand) have been declining decades due to both natural human-made reasons  superimposed by strong seasonal variability increasingly also climate-change effects. is abstracted mainly irrigation (viticulture) but municipal...
Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of is prone to statistical bias underestimation uncertainty. In this study, we combine multiobjective optimization Bayesian averaging (BMA) generate forecast ensembles soil hydraulic models. To illustrate our method, observed tensiometric pressure head data at three different depths layered volcanic origin New Zealand. A set seven models calibrated using...
Abstract A Bayesian model averaging (BMA) framework is presented to evaluate the worth of different observation types and experimental design options for (1) more confidence in selection (2) increased predictive reliability. These two modeling tasks are handled separately because aims at identifying most appropriate with respect a given calibration data set, while reliability reducing uncertainty predictions through constraining plausible range both models parameters. For that purpose, we...
[1] Six models with differing representation of the physical process in coupled soil-plant system are tested to simultaneously reproduce dynamics soil water contents, evapotranspiration, and leaf area index during a growing season winter wheat at two contrasting field plots Kraichgau Swabian Alb regions South-West Germany. The main aim study is assessment performance identification structural deficits LEACHN, SUCROS, CERES, GECROS, SPASS as well land-surface model CLM3.5. calibration each...
Abstract Knowledge of drought onset and its relationship with severity (deficit volume) is crucial for providing timely information reservoir operations, irrigation scheduling, devising cropping choices patterns managing surface groundwater water resources. An analysis the between timing deficit volume can help in hazard assessments associated risks. Despite importance, little attention has been paid to understand potential linkage effective monitoring impact assessment. Further, only a few...
Modeling soil hydraulic processes requires robust and stable numerical solutions, also when computational resources are limited. Different challenging problems like sudden changes of pressure or fluxes at the boundary model domain very dry initial conditions challenges for standard solution methods such low-order finite difference element methods. The Method Lines approach is proven to achieve robustness stability while allowing handling different complex models one-dimensional problems. To...
Highly parameterized numerical models of groundwater flow and contaminant transport play a central role in water resources management. Quantifying analysing uncertainties associated with such is key challenge for decision-making, especially under the impacts climate change. Furthermore, an important question often being overlooked model applications where next observation point should be located which state variable observed order to reduce (predictive) uncertainty. We utilize recently...
Key Points concurrent tests of conservative and reactive tracers in streams joint analysis the improved estimation hyporheic parameters Markov chain Monte Carlo methods used to infer parameter distributions
Abstract Hysteretic processes have been recognized for decades as an important characteristic of soil hydraulic behavior. Several studies confirmed that wetting and drying periods cannot be described by a simple functional relationship, some nonequilibrium the water retention characteristics has to taken into account. A large number models describing hysteresis were successfully tested on cores under controlled laboratory conditions. However, its relevance field conditions natural forcings...