Enhancing NWC Hydrologic Model Calibrations with Data Visualization and Cloud-based Apps for Operational Flood Forecasters

Accurate and timely hydrologic forecasts by the National Weather Service (NWS) River Forecast Centers (RFCs) are essential to saving life and property. Implementation of well-calibrated hydrologic models enables RFCs to improve forecast accuracy while also producing reliable short and long-range ensemble model forecasts. An adequate forecasting model may not perform well if it is inadequately calibrated. Model calibration is often constrained by a lack calibration data, especially for small river basins with high spatial rainfall variability. Rainfall/snow station networks may not be dense enough to accurately estimate the catchment rainfall/SWE. High discharges during flood events are subject to significant error due to flow gauging difficulty. Dynamic changes in catchment conditions (e.g., urbanization; losses in karstic systems) invariably introduce non-homogeneity in the water level and flow data. Understanding these changes and how they impact model calibration can be a challenge and is enabled through good data management and visualization tools. The open source project Tethys Platform has been developed to lower the barrier to creating such tools as apps in a cloud environment and already used to support the new National Water Model (NWM) developed by the NWS. This presentation will highlight the advantages of using various data visualization techniques and apps to communicate and transfer information about model calibration to operational forecasters so they may understand the influence of the calibration on model performance under various conditions. We will discuss calibration challenges in different physiographic/climatic domains. We will also discuss how the NWM apps might be further used to enhance existing model calibrations and forecast products, and to validate forecast information from the NWM in basins that have yet to be calibrated.