Hydrologic forecasting @ EGU2014: it’s time to submit that abstract!
If you’re reading this, chances are that you’ll be interested in the hydrological forecasting programme at the 2014 General Assembly of the EGU, to be held in Vienna from April 27 through May 2, 2014. The programme consists of five sessions, the topics of which range from flash floods to drought management, and from ensemble forecasting and predictive uncertainty to decision making. If you’re interested in hydrological forecasting, there should be something to your liking!
Flash floods and associated hazards: monitoring, forecasting and preparedness strategies
This session focuses on the cycle of flash flood monitoring, forecasting, warning and emergency management. We welcome studies on: i) use of radar, lightning, satellite and storm tracking monitoring for rainfall estimation and nowcasting during flash floods, and ii) emerging techniques for flood prediction and forecasting in poorly gauged areas. Of particular interest are case-studies and other contributions on the multiple hazards (such as debris flows and landslides) triggered during flash floods. Special attention is placed on the analysis of the space-time distribution of impacts, emergency management practices, behavioral response patterns and preparedness procedures. Finally, we solicit studies on understanding the coupling of social and physical dynamics over the space-time scales characteristics of flash floods.
Ensemble hydro-meteorological forecasting
Present your latest research results and practical experiences with ensemble forecasting and see what your colleagues have been up to! Whether your focus is on methods to improve skill of probabilistic forecasts, on meaningful verification standards, on visualisation, training and communication for decision making, or on real-life impact in case studies with operational systems, this is the place to exchange findings and ideas and become part of the HEPEX community.
Hydrological forecasting: Untangling and reducing predictive uncertainty through improved model process description, data assimilation and post-processing
Methods for untangling and estimating the predictive uncertainty of hydrological forecasts – along with reduction through data assimilation, improved model formulation and post-processing – are the subject of this session. Significant challenges remain relating to specification, reduction and understanding of uncertainty. Uncertainty can be reduced through data assimilation or post-processing in real-time. Model types can be varied (catchment, runoff routing, groundwater, coupled meteorological-hydrological) and combine to form complex integrated model networks through which errors propagate. Ways of reducing predictive uncertainty at different scales through improved representation of model process (physics, parameterization, numerical solution, data support and calibration) and error are of special interest to this EGU session.
Drought and water scarcity: hydrological monitoring, modelling and forecasting to improve water management
Droughts and water scarcity are significant issues in many regions of the globe, requiring innovative hydrological monitoring, modelling and forecasting to evaluate their interrelationship as well as the complex impacts on the availability and quality of water resources. It is important to improve the predictive skills and to develop innovative indicators for enhancing our early warning capabilities. The session will address statistical and/or physically-based modelling techniques, aimed at monitoring and forecasting drought and water scarcity. In this context the translation of results into indicators meaningful for decision making are an important aspect. It will bring together scientists and practitioners in the fields of hydrology, meteorology and water resources management, interested in monitoring, modelling and forecasting the interrelationships between drought and water scarcity and their hydrological impacts.
Hydrology and decision making
Hydrologic forecasts are made to facilitate decision-making by reducing uncertainty about the future. Decision-making will have to take the remaining uncertainty into account. This session aims to contribute to a better understanding of the role and value, benefit and usefulness of different types of predictions in decision-making, through real-world examples showing both successes and failures. Contributions may cover predictions for any time and spatial scale, as long as there is a relevant decision problem that is aided by the prediction. Predictions go by different names: forecasts, outlooks, scenarios, estimates – all are equally welcome!
The call for abstracts will close at 1pm CET on January 14.