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Calibration at Finer Time and Space Scales

Calibration at Finer Time and Space Scales. Hydrologic Modeling Challenges. We cannot directly apply physical laws to some components of the hydrologic cycle because boundary conditions and system properties are unknown at all locations, e.g. Exact soil depth or plant rooting depth is unknown

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Calibration at Finer Time and Space Scales

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  1. Calibration at Finer Time and Space Scales LMRFC March, 2009

  2. Hydrologic Modeling Challenges • We cannot directly apply physical laws to some components of the hydrologic cycle because boundary conditions and system properties are unknown at all locations, e.g. • Exact soil depth or plant rooting depth is unknown • Soil matrix hydraulic properties are unknown (e.g. hydraulic conductivity) • Underground flow paths are unknown • Errors and uncertainty in data an models • Model and data errors tend to increase at higher resolutions • Modeling ungauged locations • Difficult to verify models • Difficult to determining warning thresholds LMRFC March, 2009

  3. Calibration with NEXRAD at smaller spatial and temporal scales Anytime a model is calibrated at one spatial and temporal scale it should be recalibrated if the time/space scale changes LMRFC March, 2009

  4. 1.6 surface 1.4 TCI 1.2 interflow 1.0 0.8 direct Scaled runoff value supplemental 0.6 0.4 primary 0.2 1X1 2X2 4X4 8X8 16X16 32X32 64X64 Sub-basin scale in HRAP bins Relative sensitivity of SAC runoff components to sub-basin scale. Runoff values have been normalize by the value at the 8X8 scale. LMRFC March, 2009

  5. Expectations: Effect of Data Errors and Modeling Scale (a) Lumped Basin (b) Basin disaggregated into 4 cells “Truth Scale” and “Truth Simulation” (d) Basin disaggregated into 100 cells (c) Basin disaggregated Into 16 cells LMRFC March, 2009

  6. Expectations: Effect of Data Errors and Modeling Scale Noise 0% 25% 50% 75% 30 25 ‘Truth’ is simulation from 100 sub-basin model 20 , % Ek 15 Simulation error compared to fully distributed Relative error, 10 5 clean data 0 100 1 10 (distributed) (lumped) Relative Sub - basin Scale A/ A k Data errors (noise) may mask the benefits of fine scale modeling. In some cases, they may make the results worse than lumped simulations. LMRFC March, 2009

  7. Distributed model (uncalibrated). Each point is an average peak flow error from approximately 25 events over an eight year study period Oct 1996-Sept.2004. Log-linear regression for distributed model data Scaling relationship for an uncertainty index (Rq) from Carpenter and Georgakakos (2004) (secondary axis) Model Errors as a Function of Scale Flash floods 260 LMRFC March, 2009

  8. DMIP 2 Results Overall Rmod vs Basin Size Calibrated Models LMRFC March, 2009 Sprin Wsilo Caves Dutch KNSO2 Elm Powel Connr Savoy Lanag ELDO2 BLUO2 SLOA4 TIFM7 TALO2 37 sq km 2484 sq km

  9. Tools • XDMS spatial display (ABRFC) • ICP PLOT-TS time series display • Stat-Q statistics program • Calibration Assistance Program (CAP) • Soils • Parameters • Calb MAPX • Calb MAP (1 hour) LMRFC March, 2009

  10. Basin Shape: Case 2 - XDMS Plots of Radar Rainfall TALO2 TALO2 TALO2 TALO2 T=10 T=11 You can use XDMS now! T=12 T=13 LMRFC March, 2009 July 1, 1999 event. Rain fall on 6/30/99 hours 10,11,12, and 13

  11. Distributed Model Implementation • Use with, not instead of, lumped model at same time step • Part of natural progression to finer scales Lumped 6-hr Lumped 1-hour Distributed 1-hour • Calibration is good training process for forecasting • Current: • DHM: operation in NWS for headwaters, locals • HL-RDHM: Large area, soil moisture, FFG, etc • Feedback to OHD LMRFC March, 2009

  12. Distributed and Lumped Operations 200 160 Flow (CMS) 120 80 40 0 4/3/99 0:00 4/3/99 12:00 4/4/99 0:00 4/4/99 12:00 4/5/99 0:00 4/5/99 12:00 4/6/99 0:00 Hydrograph at Location A 200 Distributed Lumped Observed 160 A 120 Flow (CMS) 80 40 B 0 4/3/99 0:00 4/3/99 12:00 4/4/99 0:00 4/4/99 12:00 4/5/99 0:00 4/5/99 12:00 4/6/99 0:00 Hydrograph at Location B 200 160 Use with, not instead of lumped model Flow (CMS) 120 80 40 0 4/3/99 0:00 4/3/99 12:00 4/4/99 0:00 4/4/99 12:00 4/5/99 0:00 4/5/99 12:00 4/6/99 0:00 LMRFC March, 2009 Hydrographs at Basin Outlet

  13. Distributed Modeling for Operational River Forecasts Case 1: October 23, 2007 24-hour Rainfall Black Creek near Brooklyn, Miss. 5 inches in 24 hours Basin Location LMRFC March, 2009

  14. Distributed Modeling for Operational River Forecasts Actual River Forecast: Black Cr. At Brooklyn, Miss. Oct. 23, 2007 Distributed model Observed flow Lumped model LMRFC March, 2009

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