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Importance of Data in River Forecasting: Observing System Overview

Stakeholders meeting on July 31, 2012 discussed the significance of good data in enhancing forecast accuracy. Examples illustrated the impact of data quality on calibration and forecast outcomes of river flow and flood ratings. The hydrologic model, analysis, and quality control processes were highlighted, emphasizing the role of observed data in decision-making. The meeting also touched upon key observing systems like NRCS SNOTEL, USGS Stream Gauging, and NWS COOP. Attendees learned about the pivotal role data plays in improving river forecasts and the collaboration between various agencies for data collection and analysis.

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Importance of Data in River Forecasting: Observing System Overview

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  1. Observing System Overview Stakeholder MeetingJuly 31, 2012 Kevin Werner NWS Colorado Basin River Forecast Center

  2. Importance of Data Good data is foundational for good forecasts. Bad data ensures bad forecasts

  3. Good calibration – NFVU1 • Enough data, good record, many events…

  4. Mean Absolute Error (1979-1995): 30 cfs Mean Flow (1979-1995): 120 cfs Flood Flow (current rating): 5517 cfs

  5. Poor calibration – MUDN2 • Almost no data, not much of a record, almost no events to calibrate to….

  6. Mean Absolute Error (1979-1995): 56 cfs Mean Flow (1979-1995): 3 cfs Flood Flow (current rating): 1197 cfs

  7. Forecast precip / temp Forecast Process Hydrologic Model Analysis hydrologic expertise & judgment model guidance River Forecast System Weather and Climate Forecasts River Forecasts Outputs Graphics Rules, values, other factors, politics Analysis & Quality Control parameters Observed Data Calibration Decisions

  8. 1983 NWS document

  9. CBRFC Data In • Daily data used in CBRFC daily forecasting: • ~260 precipitation sites • ~330 temperature sites • ~875 river flow, reservoir, and diversions • ~95 reservoir storage

  10. CBRFC Data In circa 1983

  11. Key observing systems NRCS SNOTEL (Randy Julander) USGS Stream Gauging (Pat Lambert) NWS COOP, Radar, etc (Larry Dunn)

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