Real-Time Cartography in Operational Hydrology

For improved flood management, hydrologists in crisis committees need the most current information in a customizable, dynamic and geo-referenced form to better advise their peers or the public. Increase of lead time is achieved by providing interactive, visual methods in a cartographic monitoring infrastructure, allowing hydrologists to retrieve and bundle their desired flood information in a time-saving way. Vast amounts of real-time data are valorized by novel methods which facilitate their integrated, interactive and individual use in time-critical hydrological situations. Novel data modeling and data access methods are introduced for real-time and large time series data. The involved problems are tackled by (1) a central spatiotemporal database which handles historical, real-time and forecast data, by (2) a decentralized Web-based cartographic user interface, i.e., by providing maps to access data, and by (3) various interactive tools on this interface for map manipulation and data exploration.

Autorentext

Dr. Christophe Lienert, MSc: Master studies in geography, specialization in hydrology, University of Berne. PhD studies in cartography and geoinformation, ETH Zurich. Head of hydrometry division, Canton of Aargau, Switzerland. Vice-chair of the International Cartographic Association commission on Cartography in Early Warning and Crisis Management.

Klappentext

For improved flood management, hydrologists need the most actual information in a customizable, dynamic and geo-referenced form to better advise their peers or the public. Increase of lead time is achieved by providing interactive, visual methods in a cartographic monitoring infrastructure, allowing hydrologists to retrieve and bundle their desired flood information in a time-saving way. Vast amounts of real-time data are valorized by novel methods which facilitate their integrated, interactive and individual use in time-critical hydrological situations. Novel data modeling and data access methods are introduced for real-time and large time series data. The involved problems are tackled by (1) a central spatiotemporal database which handles historical, real-time and forecast data, by (2) a decentralized Web-based cartographic user interface, i.e., by providing maps to access data, and by (3) various interactive tools on this interface for map manipulation and data exploration.