Improving Flash Food Prediction in Multiple Environments 1 Using a Continuous Hydrologic Model in Support of Flash Flood Predictions Patrick D. Broxton Peter A. Troch, Michael Schaffner, Carl Unkrich, David Goodrich, Hoshin Gupta, Thorsten Wagener, Soni Yatheendradas

Motivation: Considerations for Modeling Extreme Streamflow Events What is a catchment’s ability to absorb precipitation? Precipitation Runoff Baseflow Infiltration Wet Dry Warm Cool Low Potential ET Less Water in Storage More Water in Storage High Potential ET

Motivation: Considerations for Modeling Extreme Streamflow Events What is the “true” precipitation input? Rain Gauges Radar Satellite Observations More Accurate Less Accurate Less Coverage More Coverage Large Scale Small Scale What about Snow?

SM-hsB Overview Soil Moisture – hillslope Bousinesq Model 4 Soil Moisture – hillslope Bousinesq Model Water and energy balance at the land surface Land Surface Module Incorporates Snow Transmission Zone Root Zone hsB Aquifer Deep Aquifer Infiltration ET Subsurface Module Root zone water balance Lateral transport of soil water 1) Keep track of the hydrologic state between flood model runs 2) Distributed so that it can account for spatial variability of terrain and atmospheric forcing

5 Study Sites

Study Sites – New York Watersheds 6 Five watersheds in New York’s Catskill Mountains: Humid catchments that are focus of current efforts a) W. Branch Delaware River (332 sq mi) b) W. Branch Delaware River (134 sq mi) c) Platte Kill (35 sq mi) d) East Brook (25 sq mi) e) Town Brook (14 sq mi)

Study Sites – Arizona Watersheds 7 Three watersheds in southeastern Arizona: Semi-arid catchments to compliment humid catchments a) Sabino Canyon (35.5 sq mi) b) Rincon Creek (44.8 sq mi) c) Walnut Gulch (57.7 sq mi)

Runoff Coefficient (Q/P) Runoff Coefficient (Q/P) Hydrology of New York Watersheds 8 Month Runoff Coefficient (Q/P) 0.4 0.8 1.6 1.2 Delaware River (Walton) Delaware River (Delhi) East Brook Town Brook Plate Kill Jan Dec Nov Oct Sep Aug Jul Jun May Apr Mar Feb Longitude (degrees) 42.2 42.3 42.4 42.5 Latitude (degrees) 75.2 -75 -74.8 -74.6 1050 1100 1150 1200 New York Basins Longitude (degrees) 31.8 32 32.2 32.4 Latitude (degrees) -111 -110.6 -110.2 -109.8 PRISM – Average Yearly Precipitation (mm) 300 400 600 500 700 800 900 Month 0.2 0.6 0.4 0.8 Sabino Canyon Rincon Creek Walnut Gulch Jan Dec Nov Oct Sep Aug Jul Jun May Apr Mar Feb Runoff Coefficient (Q/P) Arizona Basins Date

9 Modeling with SM-hsB

Land Surface Module - Overview 10 Atmospheric Inputs: Shortwave Radiation Longwave Radiation Precipitation Temperature Pressure Humidity Wet Canopy Evaporation/ Snow Interception Trees Precipitation Long Wave Radiation Infiltration/Runoff Shortwave Radiation Wintertime Snowpack Variable Canopy Cover Near-Surface Soil Layer Stream Fully distributed, runs on hourly timesteps (diurnal cycle is important) Based on energy balance principles – similar to Utah Energy Balance Model

Land Surface Module - Calibration 11 Can be run at a point: e.g. Calibrate to a point measurement such as a snow pillow ...or over an area: e.g. Calibrate over an area to remotely sensed data or to a data assimilation system Photo courtesy Jim Porter at NYCDEP Over a multi-year span, it is generally tuned to compare well with SNODAS, but for specific years, it can be refined using other measurements SM-hsB SWE (mm) SNODAS SWE (mm) R2 = 0.81 20 40 60 80 100 120 140 SWE (mm) 1/1/2007 4/1/2007 1/1/2008 4/1/2008 40 80 120

Land Surface Module - Simulation 12 Preliminary results for 2009-2010 Snow Season in W. Branch Delaware River Watershed All precipitation inputs are derived from the MPE January 15,2010 100 mm 50 mm SWE (mm) 12/1/2009 1/1/2010 2/1/2010 3/1/2010 Date 40 80 120 160 200 4/1/2010 January 25,2010 February 15,2010 February 28,2010

Subsurface Module - Overview 13 Root Zone Water Balance / Baseflow ET Infiltration Runoff Root Zone Streamflow Routing Transmission Zone hsB Aq. Baseflow hsB Aquifer Deep Aquifer Deep Aq. Baseflow Semi distributed, runs on daily or hourly timesteps

Streamflow/Baseflow/Runoff (mm) Subsurface Module - Calibration 14 Calibration procedure relies on a baseflow separation Portions of the model are reconstructed from the steamflow signatures (hydrology backwards) Deep Aquifer HSB Aquifer Streamflow/Baseflow/Runoff (mm) Log(Streamflow-mm) Baseflow Streamflow Runoff 1/1/2005 4/2/2006 7/3/2007 5 10 15 10/1/2008 12/31/2009 20 30 40 50 60 70 Effective Time (days) Date 35 1 2 -1 25 Calibration procedure based on that developed by Gustavo Carrillo and Peter Troch at the University of Arizona

Normalized Streamflow Generation log(Streamflow – mm/day) Subsurface Module - Simulation 15 Simulation for Delaware River (Walton) using MPE as input Model Data 1/1/2005 4/2/2006 7/3/2007 10/1/2008 12/31/2009 20 40 60 Streamflow (mm/day) 5 10 15 Baseflow (mm/day) Normalized Streamflow Generation Normalized Water Year Precipitation 0.2 0.4 0.6 0.8 1 Data Model log(Streamflow – mm/day) 20 40 60 80 100 10-1 101 Probability of Exeedance Data Model Catchment NSE Baseflow NSE Streamflow Delaware River (Walton) 0.61 0.34 Delaware River (Delhi) 0.62 0.10 East Brook 0.58 0.48 Town Brook 0.65 0.41 Platte Kill Catchment NSE Baseflow NSE Streamflow Sabino Canyon 0.10 0.41 Rincon Creek -3.34 -0.96 Walnut Gulch No Baseflow

Benefits of Modeling With SM-hsB 16 Yields many useful modeled quantities for flood forecasting Baseflow Model Data Modeled Soil Moisture Modeled Transpiration 1/1/2005 4/2/2006 7/3/2007 10/1/2008 12/31/2009 BF (mm/day) SM (%) Transp. (mm/day) 20 10 30 40 5 Storage (mm) hsB Aquifer Storage Discharge (mm) 15 Initial Conditions Modeled soil moisture Modeled water storage Potential and actual evapotranspiration Aquifer depth Precipitaiton Estimates Modeled SWE Snow and Snowmelt Storage-discharge relationships that can be inverted to estimate precipitation from streamflow

Summary 17 hsB-SM has been implemented in all NY watersheds, most AZ watersheds Snow module reproduces wintertime snowpacks; subsurface module works well in the W. Branch Delaware River Basin Model yields useful information such as snowmelt rates, estimates of catchment “wetness”, and can be useful for estimating rainfall/snowmelt from streamflow response Although it has not yet been coupled with a flash flood model (KINEROS2), statistical combinations of rainfall and e.g. soil moisture suggest that there is information to be gained from using model data Correlation with Flood Size - Top 10 Events Total Precip Soil Moisture Combined Deleware River (Walton) 0.80 0.43 0.88 Deleware River (Delhi) 0.65 0.59 0.82 East Brook 0.02 0.00 0.06 Town Brook 0.68 0.01 Platte Kill 0.48 0.05 0.72 AVERAGE 0.52 0.22 0.66

18 18 Acknowlegements Funding comes from a COMET grant (UCAR Award S09-75794) Special thanks to Mike Schaffner, Peter Troch, Gustavo Carrillo, Jim Porter, Glenn Horton, and others

19 19 Questions