WaterWare description Data management, Objects Monitoring, time series Hydro-meteorological data, forecasts Rainfall-runoff: RRM, floods Irrigation water demand Water budget modelling Water quality: STREAM, SPILL Multi-criteria optimization, DSS User support, system maintenance

Monitoring data: Associated with monitoring stations/GIS Active or passive data transfer in “real-time” with several alternative protocols; Range of time series data display and analysis tools; Directly linked to simulation results (simulated virtual monitoring stations) Data assimilation (4D) for forecasts (nudging of initial conditions) Model calibration and validation

Monitoring stations, current map view and classification, estimated violations from the forecasts

Monitoring station, links to the associated time series of monitoring data (selector at the bottom)

Monitoring station example: reservoir water level

Monitoring time series reservoir (storage level)as linked from a monitoring station OBJECT: overview (upper graph) and selected period (below, marked in red in the overview) sub-periods can be select on a daily/hourly, monthly, or annual basis. Example: multi-year to year.

Monitoring time series as linked from a monitoring station OBJECT: overview (upper graph) and selected period (below, marked in red in the overview)

Monitoring time series as linked from a monitoring station OBJECT: overview (upper graph) and selected period (below, marked in red in the overview), annual to monthly

Monitoring time series as linked from a monitoring station OBJECT: overview (upper graph) and selected period (below, marked in red in the overview), annual to daily/hourly

Monitoring time series as linked from a monitoring station OBJECT: overview (upper graph) and selected period (below, marked in red in the overview) Please note data inserted from “gap filling” marked in ORANGE (lower graph)

Monitoring time series analysis: histogram and basic statistics.

Monitoring time series as linked from a monitoring station OBJECT: overview (upper graph) and selected period (below, marked in red in the overview)

Monitoring time series analysis tool: interactive patching of data gaps.

Zoomed in to hourly data (24 hours), model generated data (MM5 meteorological model)

Rainfall observation data from an arid region (NSW, Australia)

Zoomed in to hourly data (24 hours) of a rare, major rainfall (and flood event), model generated (MM5 dynamic downscaling to hourly data)

Time series data comparison (precipitation, two neighbouring stations).

Overview over a set of neighbouring monitoring stations/time series) test for homogeneity

Overview over a set of neighbouring monitoring stations/time series) test for homogeneity to select input data (basin wide) for the runoff models.

Time series analysis: comparison: reference and a specific observation (or model results) to test observation variability

Monitoring data: Associated with monitoring stations/GIS Active or passive data transfer in “real-time” with several alternative protocols; Range of time series data display and analysis tools; Directly linked to simulation results (simulated virtual monitoring stations) Data assimilation (4D) for forecasts (nudging of initial conditions) Model calibration and validation

User interface examples Overview of a set of different monitoring data interface (display and analysis) functions and styles

Time series analysis: outlier detection based on a number of user defined rules.

Time series analysis: detecting exceedances (stream water level); also used for flood forecasting in real-time mode.

Monitoring data: Associated with monitoring stations/GIS Active or passive data transfer in “real-time” with several alternative protocols; Range of time series data display and analysis tools; Directly linked to simulation results (simulated virtual monitoring stations) Data assimilation (4D) for forecasts (nudging of initial conditions) Model calibration and validation

Time series analysis: comparing observed and simulated values (air pressure, General Hospital Nicosia on Cyprus)

Time series management, real-time acquisition; configuration of the interface to external data sources (data base, web server, data loggers).

Models vs Observations Models obey the conservation laws Observations obey ???? Very limited spatial coverage and resolution, measurement error (pluvimeter, flow) sensor calibration/maintenance,