What's on tap?

Methods development in WCA3a Application to EDEN Quiet desperation The fix Results and discussion

Problem : How to Estimate Water Depths at Ungaged Sites
Dataset –WCA 3a Water-level from 3 sites Water-depth data from 17 sites EDEN grid and vegetation attributes % prairie % sawgrass % slough % upland UTM North UTM South	[larger image]

Approach

Two step ANN model First step: estimate mean water-depths using static model –“spatially interpolating” ANN scheme Second step: estimate water-depths variability using dynamic variables

Two-step Model

[larger image]

Static Model Results

[larger image]

Each “step” represents a different site Model able to generalize water level difference but not the variability

Dynamic Model
5 “index” stations (red dots) Combination of static and dynamic data 5 validation stations (green dots)	[larger image]

Final Model Results

Figure 5. Plot showing measured (light trace) and predicted (dark trace) water depths for Site W8. Predictions are not continuous due to missing data for one or more of the index stations. [larger image]

Hindcasting 25 EDEN Sites
Existing EDEN sites : 7 years (61,400 data points) New EDEN sites : 4 -12 months of data (925-8,760 data points)
	Figure 1. Locations of Everglades Depth Estimation Network (EDEN) gaging stations in southern Florida (modified from Pearlstine and others, 2007). [larger image]

Approach: Similar 2-Step Model

[larger image]

Approach: Similar 2-Step Model
Separate models for each area Number of potential inputs sites reduced using dynamic clustering Hindcast example –W2 Input Sites Sites 63, 64, 65, 3ASW3, and 3AWS	[larger image]

Spatially Interpolating ANN Model Stacked Dataset

[larger image]

Static Model Results

[larger image]

Dynamic Model Results

[larger image]

Initial Water Level Estimate - W2 “Quiet Desperation”
[larger image]	What is going on?
Data for W2 not used to train models

Possible Causes

Datum confusion Gage offset W2 located lower edge of area covered by input sites Limited information content of static variables Did not use difference from a standard signal (decorrelated dynamic variables)

Third-step Model: Error correction

Figure 7. Three-step modeling approach to make final water-level estimates at a station. [larger image]

Error Correction Model Results

[larger image]

[larger image]

Final Hindcast

[larger image]

Summary Statistics for Hindcasting Models

Table 4. Summary statistics for water-level estimates for new Everglades Depth Estimation Network (EDEN) stations. [n, number of data values; R, Pearson coefficient; R2, coefficient of determination; Min, minimum; ft, feet; Max, maximum; ME, mean error; RMSE, root mean square error; PME, percent model error] [Please note: This table is from Open File Report 2007-1350, and the figures referred to in this table are station location maps featured in the report.] Site n R R2 Data range ME RMSE PME Min, in ft Max, in ft Water Conservation Area 1 (fig. 15) North_CA1 41,721 0.943 0.889 13.82 16.38 -0.046 0.134 5.2 South_CA1 43,409 0.991 0.983 12.85 15.90 0.008 0.088 2.9 Water Conservation Area 2 (fig. 17) EDEN11 2,637 0.950 0.902 10.97 13.19 -0.054 0.044 2.0 EDEN13 1,968 0.955 0.912 7.07 7.69 -0.018 0.006 1.0 Water Conservation Area 3A (fig. 20) 3A-5 5,684 0.998 0.995 8.15 10.10 0.002 0.001 0.1 EDEN4 2,399 0.999 0.998 6.96 10.30 0.001 0.002 0.1 EDEN5 1,653 0.999 0.999 8.01 10.20 0.004 0.001 0.1 EDEN8 2,442 0.999 0.999 6.79 9.19 0.001 0.001 0.0 EDEN9 925 0.999 0.998 7.69 10.55 -0.006 0.004 0.1 EDEN12 7,648 0.999 0.998 6.84 9.59 -0.002 0.001 0.0 EDEN14 969 0.906 0.821 8.66 9.59 0.011 0.010 1.1 W2 7,648 0.998 0.995 6.86 9.42 0.008 0.003 0.1 W5 7,648 0.999 0.998 6.84 9.59 -0.001 0.001 0.0 W11 7,628 0.999 0.998 7.08 10.08 -0.012 0.002 0.1 W14 7,628 0.998 0.997 7.00 10.00 -0.013 0.003 0.1 W15 3,859 0.999 0.998 7.47 9.67 -0.001 0.001 0.0 W18 7,628 0.998 0.996 7.92 10.21 -0.000 0.002 0.1 Water Conservation Area 3B (fig. 26) TI-8 5,684 0.996 0.993 4.59 6.16 0.002 0.001 0.1 TI-9 5,684 0.996 0.992 5.29 6.42 0.009 0.001 0.1 EDEN7 2,419 0.998 0.996 5.24 6.96 0.008 0.001 0.1 EDEN10 2,419 0.995 0.990 5.06 6.32 0.007 0.002 0.1 Big Cypress National Preserve (fig. 29) EDEN1 3,864 0.960 0.921 7.13 7.82 0.018 0.003 0.4 EDEN6 1,591 0.984 0.968 8.76 10.73 0.030 0.007 0.4 Everglades National Park (fig. 31) EDEN3 5,294 0.989 0.978 0.07 1.75 -0.042 0.006 0.4 Met1 1,238 0.994 0.989 5.23 5.76 0.000 0.000 0.0

Summary

Estimation of water depth at ungaged sites ANNs able to accurately predict water depths at ungaged sites Use of static and dynamic variable produce a multi-variate “kreiging” of water depths Methodology will be used to hindcast “new” network stations

Questions
Paul Conrads USGS-South Carolina Water Science Center pconrads@usgs.gov