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Eric Jones Senior Hydrologist Lower Mississippi River Forecast Center 89 th AMS Meeting.

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Presentation on theme: "Eric Jones Senior Hydrologist Lower Mississippi River Forecast Center 89 th AMS Meeting."— Presentation transcript:

1 Eric Jones Senior Hydrologist Lower Mississippi River Forecast Center 89 th AMS Meeting

2 July 2007 - Began development and implementation Used NWS OHD Research Distributed Hydrologic Model V2.0. SACSMA used for rainfall-runoff No snow model used Rating curve method of routing Initially used basins 3, expanded to 7 Calibrated before implemented Verification done on initial three basins Black Creek at Brooklyn, MS (BKN) Leaf River at Collins, MS (CLS) Emory River at Oakdale, TN (OAK)

3 BKN CLS OAK

4 ++= Basin Model % bias Daily RMSE Corr Coef (CMSD) CLS Distrib0.2546.380.724 Lumped-14.1041.840.748 BKN Distrib9.4118.940.810 Lumped14.9715.290.791 OAK Distrib-1.2844.060.889 Lumped-15.8841.740.895

5 January 2008- October 2008 Simulated Lumped vs Distributed models Not adjusted to stage observations No runtime modifications included in lumped model Statistics on forecasts +24 hours Used quality controlled multi-sensor precipitation est. Mean average PE used for distributed model Mostly computed PE used for lumped model

6 BKN Distrib Lumped CLS Distrib Lumped OAK Distrib Lumped

7 BKN Distrib Lumped CLS Distrib Lumped OAK Distrib Lumped

8 BKN Dist Lump CLS OAK Dist Lump

9 One square = 4 km 2 Distrib Lumped Obs

10 Distrib Lumped Obs One square = 4 km 2

11 Distrib Lumped Obs One square = 4 km 2

12 Distrib Lumped Obs

13 Distrib Lumped Obs One square = 4 km 2

14 Distrib Lumped Obs

15 One square = 4 km 2 Distrib Lumped Obs

16 Distrib Lumped Obs

17 Distrib Lumped Obs

18 Distrib Lumped Obs

19 Unadjusted routing Adjusted routing Observed Forecast Flood stage Observed Forecast Flood stage

20 Distributed model vs lumped model Distributed model does better in some cases Shape of distributed hydrograph appears to be better Suggestions for hydrologic forecasters Should base forecasts using data from both models


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