Charles University, Faculty of Science IAHS T. G. Masaryk Water Research Institute USGS International Hydrological Programme International Association of Hydrogeologists International Association of Hydraulic Engineering and Research
Nederlandse Hydrologische Vereniging, Netherlands Hydrological Society Česká asociace hydrogeologů, Czech Association of Hydrogeologists

NAVRCHOLU.cz
 

Topics

The HydroPredict’2008 conference solicits presentations on innovative technologies and methods of data collection, analysis, integration (combined use) of data and modelling, new techniques and tools for assessment of model performance, and case studies of both successful and problematic applications for the following topics related to problems in hydrology, ecology, and water resources management.

Presentations that address integration (combined use) of data collection, analysis and modelling are particularly welcome.

Topics T1 through T21 are listed in the sequence as they will often occur in time throughout a project or a study:

[T1] formulate the study plan to guide the investigation and to serve project goals, including uncertainty in model predictions

[T2] determine how well we need to understand a natural system, from both theoretical and measurement perspectives, for different types of predictions to be useful

[T3] select prediction scenarios and other strategies for model application

[T4] test basic theory and conceptual models, jointly or independently

[T5] identify the importance of space/time scale and resolution on data collection methods and priorities and prediction relevance, accuracy, and uncertainty

[T6] apply upscaling and downscaling to couple different types of models, e.g., hydraulic models, catchments models, vadose zone models, and groundwater models

[T7] design field data collection (monitoring, measurements, etc.) and processing, using the model

[T8] evaluate data quality and incorporate this evaluation in model development and hypothesis testing

[T9] determine the information needed to provide model parameter values and, thus, predictions

[T10] employ data to develop models, including calibration (inverse modelling) and parameter estimation

[T11] identify relations among the required model prediction reliability, and availability and quality of model input data

[T12] apply models – with their uncertain predictions – to solve engineering and scientific problems, e.g., by simulation of various prediction scenarios and other strategies

[T13] test models to determine if they are adequate to represent natural processes of concern

[T14] check the accuracy of predictions (analysis of model prediction uncertainty), to see whether model predictions are useful for practical applications

[T15] focus and report on methods and approaches that produce the most useful predictions

[T16] isolate additional data requirements and evaluate the effects new data are expected to have on prediction reliability

[T17] translate predictions into societal requirements

[T18] explain predictions and their reliability to stakeholders and the public and how they can cope with uncertainty in their decision-making process

[T19] analyze the costs and benefits of monitoring versus prediction reliability

[T20] conduct post-audit to determine whether or not long-term predictions were accurate and what difficulties might have arisen in applying models for water-resources management

[T21] integrate monitoring and modelling strategies for engineering, design and management

[T--] other subjects

Each of the three fields involved – hydrology, ecology, and water resources management, and their domain of intersection – has its own specific aspects, flavours and problems. Some of these are listed below. For this conference, the problems would be addressed in the context of the topics T1 through T21, listed above.

Hydrology Examples

  • Developing models and using predictions from models that represent
    • floods and low flows in rivers
    • transport of sediments and contaminants (including TMDL) in rivers, lakes, and estuarine environments
    • recharge, surface processes, and groundwater-surface water interactions
    • saturated-unsaturated coupled groundwater modelling and fracture-flow modeling
    • subsurface transport, including particle tracking, plume migration, and capture zone modeling
    • reactive transport in groundwater
    • virus and colloid transport in soil and groundwater
    • bioremediation
    • seawater intrusion and other density-dependent processes
    • flow and transport through fractured rocks
    • denitrification
  • Constraining groundwater models using geological, hydrogeological, and geophysical data:
  • Upscaling and regional/large-scale groundwater modelling
  • Identifying approaches to best represent processes that occur at a range of scales – from a single river to an entire catchment, including groundwater-surface water interactions
  • Determining how well can models can be used to predict landslides caused by saturated conditions
  • Which spatial data can support distributed rainfall-runoff models: how can it reduce prediction uncertainty

Ecology Examples

  • Are descriptors of ecological systems helpful for modelling the status of groundwater/surface-water related systems and solving the problems?
  • Measurements and modelling of ecological descriptors (abiotic factors, etc.) of the groundwater system important to ecologists
  • Monitoring of groundwater (saturated, unsaturated, shallow, deep) and its application for predictive modelling for ecological purposes
  • Interaction of ecology and groundwater recharge, discharge, chemistry, and biology
  • Relationships between abiotic environmental conditions and occurrence of groundwater-dependent species (vegetation etc.), and monitoring and modelling for these abiotic factors (quantity, chemistry, dynamics)
  • Integrated modelling of saturated-unsaturated and surface-water systems, with applications for ecology-related studies (wetlands, riverine systems, etc.)
  • Spatial and temporal scale differences between hydrological and ecological processes and their influence on predictions
  • Monitoring (mapping) and modelling for
    • groundwater seepage (quantity, chemistry, dynamics, etc.) to surficial ecosystems, with applications for ecology-related studies
    • wetland ecology and the role of groundwater
    • riverine (riparian) ecology and the role of groundwater
    • biogeochemical cycles such as carbon and nitrogen as affected by the interaction of groundwater and ecology
    • removal of nitrogen and pesticides from groundwater by biogeochemical processes
    • groundwater contamination effects on ecological systems and processes
    • interactions and feedbacks between groundwater, vegetation and precipitation
    • restoration of groundwater-dependent ecosystems

Water Resources Management Examples

  • Groundwater management and protection of groundwater
  • Conjunctive use of surface and groundwater systems
  • The role of societal preferences in water resources management strategies
  • Handling uncertainties in water management strategies
  • What can be learned by applying scenario runs in water resources management
  • Consideration of social, ecological and economic objectives in water resources management
  • Risk in the context of water resources management, such as risk reducing strategies
  • Predictions and the public and NGOs in water resources management