LEFT PAGE Demonstra(on scenario: Na#onal Flood Interoperability Experiment Every 3 hours, the US Na2onal Weather Service updates their na2onal 15-‐hr rainfall forecast, pu>ng this workﬂow in mo2on: 1.  Accessing the na2onal high-‐resolu2on weather forecast for precipita2on rates; 2.  Land surface modeling of runoﬀ, downscaled to 3km catchment scale; 3.  Streamﬂow rou2ng simula2on across the US at scale of 3km stream reaches; 4.  Flood inunda2on predic2ons at local scales; 5.  Na2onal aler2ng and support for locally an2cipated ﬂood events and emergency response. Note: results of this project are considered research to inform Na2onal Weather Service; not yet public forecasts. Novel contribu(ons: •  First na2onwide simula2on of streamﬂow in a single model. •  Helping harmonize coordina2on of weather, streamﬂow, and ﬂooding data across federal agencies, vendors, and research communi2es. •  Developed common informa2on model and tools for conver2ng between WaterML and NetCDF. •  Helped advance Tethys hydrologic modeling plaUorm (open source GIS, cloud, Python framework). Beneﬁts •  Be^er & more 2mely informa2on: applies the beneﬁts of sophis2cated forecas2ng methods to all communi2es. •  Improved emergency opera2ons: this approach will improve the informa2on available, through addi2on of streamﬂow and hydraulics mapping to tradi2onal weather maps. “Interoperability seems to be about the integra4on of informa4on. What it’s really about is the coordina4on of organiza4onal behavior.” -‐-‐ David Schell PI: David R Maidment, University of Texas at Aus2n Co-‐PI’s: Alva Couch, Tuds University Ethan Davis, Unidata Dan Ames, Brigham Young University Integra(ng Discrete and Con(nuous Data (DisConBB) 10 Mo(va(on •  Advance our ability to study and relate data and models of discrete and con2nuous phenomena, applied to… •  Improve emergency response and community resilience to ﬂooding events. •  Achieve sustained innova2on in the research-‐to-‐opera2ons process. Problem: •  Carry out near-‐real-‐2me hydrologic simula2ons at high spa2al resolu2on, na2onally, communicated to local level. •  Manage large volumes of 2me series data. •  Provide adequate data density throughout. •  Generate high-‐resolu2on ﬂood inunda2on maps na2onwide. 1. Weather model and forecasts (High Resolu2on Rapid Refresh, NWS) 3km average Catchment-‐level forecasts Weather Precipita#on 2. Land-‐Atmosphere Model (WRF-‐Hydro, NCAR) 4. Probabilis(c ﬂood forecasts Streamﬂow Runoﬀ 3. Streamﬂow rou(ng (CONUS) Rou2ng Applica2on for Parallel computatIon of Discharge (RAPID) at Texas Advanced Compu2ng Center (TACC) Forecasts and Model Workﬂow for Na(onal Flood Interoperability Experiment RIGHT PAGE 1.  2.  3.  4.  5.  Na2onal Weather Service posts 15-‐hr precipita2on forecast every 3 hours. WRF-‐Hydro models runoﬀ, downscaled to 3km catchments. RAPID models streamﬂow for 2.7 million stream reaches (segments) in con2nental US. Probabilis2c ﬂood height is es2mated from streamﬂow & used to determine inunda2on. Steps 1-‐3 complete in less than 1 hour; keeps up with NWS weather forecasts; step 4 varies. 11