Unimpaired Flow Data Report

Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

Prepared for: Georgia Department of Natural Resources

Prepared by: ARCADIS U.S., Inc. 2849 Paces Ferry Road Suite 400 Atlanta Georgia 30339 Tel 770.431.8666 Fax 770.435.2666

Our Ref.: GA063853/Rpt 2514

Date: April 12, 2010

This document is intended only for the use of the individual or entity for which it was prepared and may contain information that is privileged, confidential and exempt from disclosure under applicable law. Any dissemination, distribution or copying of this document is strictly prohibited.

Table of Contents

Executive Summary 1

1. Introduction 4

1.1 Need for Unimpaired Flows 4

1.2 Basic and Planning Node Selection 4

2. General Procedures for Unimpaired Flow Development 10

2.1 General Description of Unimpaired Flow Process 10

2.1.1 Reach Cases 11

2.2 Data Inventory and Management 12

2.2.1 Water Use Data 12

2.2.2 Streamflow Data 13

2.2.3 Routing Model Parameterization 13

2.2.4 Reservoir Physical and Operational Data 14

2.2.5 Reservoir Meteorological Data 14

2.2.5.1 Precipitation 15

2.2.5.2 Evaporation Time Series Development 25

2.2.5.3 Reservoir Runoff Coefficient Selection 27

2.2.6 Data Management Tools 32

2.2.7 Data Management Nomenclature 34

2.3 Reservoir Effects Calculation 40

2.3.1 Holdouts 41

2.3.2 Net Evaporation 41

2.3.3 Net Reservoir Effects 42

2.4 Flow Record Filling 42

2.4.1 Statistical Methods 44

2.4.2 Mean Flow Ratio 45

2.4.3 Drainage Area Ratio 46

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2.4.4 Hydrologic Modeling 46

2.5 Local Incremental Flow Computation 47

2.6 Local Incremental Unimpaired Flow Computation 48

2.6.1 Aggregation of Impairments 48

2.6.2 Negative Local Unimpaired Flow Adjustments 48

2.6.3 Selection of Final Local Unimpaired Flow Time Series 49

2.7 Cumulative Unimpaired Flow Computation 50

2.8 Merger of Existing ACT and ACF Incremental Unimpaired Flows 50

2.9 Quality Control of Data 50

3. Apalachicola-Chattahoochee-Flint (ACF) River Basin 54

3.1 ACF Basin Description 54

3.2 Hydrological Data 54

3.2.1 Existing Unimpaired Flows 54

3.2.2 Streamflow Records 56

3.2.3 Reservoir Data 58

3.2.4 Climatological Data 59

3.3 Water Use Data 60

3.4 Reservoir Effects 61

3.4.1 Holdouts 63

3.4.2 Net Evaporation 63

3.4.3 Net Reservoir Effects 66

3.5 Streamflow Filling, Routing, and Reservoir Inflows 67

3.5.1 Methods Summary 67

3.5.2 Buford Dam (BUFORD_R) 68

3.5.3 Columbus (COLUMBUS) 68

3.5.4 Iron City (IRON_CTY) 68

3.5.5 Milford (MILFORD) 69

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3.5.6 West Point Reservoir (WESTPT_R) 70

3.5.7 Walter F. George Reservoir (WFG_R) 70

3.5.8 Jim Woodruff Reservoir (WOODRF_R) 70

3.6 Local Incremental Flow Calculation and Adjustments 70

3.7 Local Incremental Unimpaired Flow Calculation 72

3.7.1 Negative Local Unimpaired Flow Adjustments 72

3.7.2 Selection of Final Local Unimpaired Flow Time Series 73

3.7.3 Special Cases of Negative Incremental Flows 74

3.8 Merger of Existing and Extended Unimpaired Time Series 75

3.9 Quality Control 78

3.10 Cumulative Unimpaired Flows 78

3.11 Conclusions 78

4. Alabama-Coosa-Tallapoosa (ACT) River Basin 79

4.1 ACT Basin Description 79

4.2 Hydrological Data 80

4.2.1 Existing Unimpaired Flows 80

4.2.2 Streamflow Records 80

4.2.3 Reservoir Data 82

4.2.4 Climatological Data 84

4.3 Water Use Data 86

4.4 Reservoir Effects 87

4.4.1 Net Evaporation 87

4.4.2 Methods Summary 89

4.4.3 Allatoona Reservoir (ALATNA_R) 89

4.4.4 Carters Reregulation and Carters Reservoirs (C_REREG and CARTERS_R) 90

4.4.5 Gaylesville (GAYLES) 90

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4.4.6 Rome on the Oostanaula River (ROME_O) 91

4.4.7 Rome on the Etowah River (ROME_E) 92

4.4.8 Kingston (KINGSTON) 92

4.5 Local Incremental Flow Calculation and Adjustments 93

4.6 Local Incremental Unimpaired Flow Calculation 95

4.6.1 Negative Local Unimpaired Flow Adjustments 95

4.6.2 Selection of Final Local Unimpaired Flow Time Series 96

4.7 Merger of Existing and Extended Unimpaired Flow Time Series 96

4.8 Quality Control 97

4.9 Cumulative Unimpaired Flows 97

4.10 Conclusions 98

5. Ocmulgee-Oconee-Altamaha (OOA) Study Basin 99

5.1 OOA Basin Description 99

5.2 Hydrological Data 101

5.2.1 Existing Unimpaired Flows 101

5.2.2 Streamflow Records 101

5.2.3 Reservoir Data 101

5.2.4 Climatological Data 103

5.3 Water Use Data 105

5.4 Reservoir Effects 106

5.4.1 Holdouts 106

5.4.2 Net Evaporation 106

5.4.3 Net Reservoir Effects 109

5.4.4 Minimum Reservoir Releases 110

5.5 Streamflow Filling, Routing, and Reservoir Inflows 110

5.5.1 Methods Summary 111

5.5.2 Jackson (JACKSON) 111

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5.5.3 Penfield (PENFIELD) 112

5.5.4 Vernon (VERNON) 113

5.5.5 Baxley (BAXLEY) 113

5.6 Local Incremental Flow Calculation and Adjustments 114

5.7 Local Incremental Unimpaired Flow Calculation 115

5.7.1 Negative Local Unimpaired Flow Adjustments 116

5.7.2 Selection of Final Local Unimpaired Flow Time Series 116

5.8 Quality Control 117

5.9 Cumulative Unimpaired Flows 118

5.10 Conclusions 118

6. Savannah and Ogeechee (SO) River Basins 119

6.1 SO Basin Description 119

6.2 Hydrological Data 121

6.2.1 Existing Unimpaired Flows 121

6.2.2 Streamflow Records 122

6.3 Water Use Data 124

6.4 Reservoir Effects 126

6.4.1 Reservoir Operational Data 126

6.4.2 Holdouts 126

6.4.3 Net Evaporation 129

6.4.4 Net Reservoir Effects 129

6.5 Streamflow Filling, Routing, and Reservoir Inflows 133

6.5.1 Methods Summary 133

6.5.2 Reservoir Time Series Adjustments 134

6.5.3 Data Time Shifts 137

6.5.4 Russell-Thurmond Pumpback Operation 137

6.5.5 Hartwell Reservoir (HARTWL_R) 137

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6.5.6 Richard B. Russell Reservoir (RBR_R) 140

6.5.7 Thurmond Reservoir (THRMND_R) 142

6.5.8 Burtons Ferry (BURTONS) 143

6.5.9 Kings Ferry (KINGSFY) 145

6.5.10 Augusta and Clyo (AUGUSTA, CLYO) 145

6.5.11 Savannah (SAVANNAH) 145

6.6 Local Incremental Flow Calculation and Adjustments 146

6.6.1 Richard B. Russell Reservoir (RBR_R) 146

6.6.2 Thurmond Reservoir (THRMND_R) 147

6.6.3 Other Nodes 148

6.7 Local Incremental Unimpaired Flow Calculation 149

6.7.1 Special Cases – Reservoir Effects 149

6.7.2 Negative Local Unimpaired Flow Adjustments 149

6.7.3 Selection of Final Local Unimpaired Flow Time Series 150

6.8 Quality Control 151

6.9 Cumulative Unimpaired Flows 152

6.10 Conclusions 152

7. Ochlockonee, Suwannee, Satilla, and St. Mary’s (OSSS) River Basins 153

7.1 OSSS Basin Description 153

7.2 Hydrological Data 153

7.2.1 Streamflow Records 153

7.3 Water Use Data 156

7.4 Streamflow Filling, Routing, and Reservoir Inflows 157

7.4.1 Methods Summary 157

7.4.2 Alapaha (ALAPAHA) 158

7.4.3 Bemiss (BEMISS) 158

7.4.4 Concord (CONCORD) 159

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7.4.5 Fargo (FARGO) 159

7.4.6 Jennings (JENNINGS) 159

7.4.7 Pinetta (PINETTA) 160

7.4.8 Quincy (QUINCY) 160

7.4.9 Quitman (QUITMAN) 160

7.4.10 Statenville (STATVL) 160

7.4.11 Thomasville (THOMASVL) 161

7.4.12 Offman (OFFMAN) 161

7.4.13 Gross (GROSS) 162

7.5 Local Incremental Flow Calculation and Adjustments 162

7.5.1 Concord (CONCORD) 163

7.5.2 Jennings (JENNINGS) 164

7.5.3 Pinetta (PINETTA) 164

7.5.4 Statenville (STATVL) 164

7.5.5 Final Adjustments to Unimpaired Local Incrementals 165

7.6 Local Incremental Unimpaired Flow Calculation 166

7.6.1 Negative Local Unimpaired Flow Adjustments 166

7.6.2 Selection of Final Local Unimpaired Flow Time Series 167

7.7 Quality Control 167

7.8 Cumulative Unimpaired Flows 168

7.9 Conclusions 168

8. Tennessee (TN) River Basin 169

8.1 TN Basin Description 169

8.2 Hydrological Data 169

8.2.1 Streamflow Records 169

8.3 Reservoir Data 172

8.4 Climatological Data 172

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8.5 Water Use Data 173

8.6 Reservoir Effects 173

8.6.1 Reservoir Holdouts and Inflow Calculations 174

8.6.2 Net Evaporation 174

8.6.3 Net Reservoir Effects 174

8.7 Streamflow Filling, Routing, and Reservoir Inflows 175

8.7.1 Methods Summary 175

8.7.2 England (ENGLAND) 176

8.7.3 Chickamauga (CHICKMGA) 177

8.7.4 Blue Ridge Reservoir (BLRIDG_R) 178

8.7.5 Copperhill (COPRHILL) 179

8.7.6 Nottely Dam (NOTLY_R) 181

8.7.7 Chatuge Dam (CHATUG_R) 181

8.7.8 Little Tennessee (LITLE_TN) 182

8.8 Local Incremental Flow Calculation and Adjustments 182

8.9 Local Incremental Unimpaired Flow Calculation 183

8.9.1 Negative Local Unimpaired Flow Adjustments 183

8.9.2 Selection of Final Local Unimpaired Flow Time Series 184

8.10 Quality Control 185

8.11 Cumulative Unimpaired Flows 185

9. References 186

Tables

Table 1-1 Key to Basin and Node Names 6

Table 2-1 Reservoirs Included in the Analysis and Corresponding MAP Time Series 16

Table 2-2 Annual Precipitation Estimates and Corresponding Adjustment Factors for Each Reservoir 24

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Table 2-3 Select Stream Gages and Computed Runoff Coefficients Throughout the Project Area 28

Table 2-4 Runoff Coefficients Specified for Each Reservoir 31

Table 2-5 OOA Intermediate Time Series Pathname Parts 36

Table 2-6 Abbreviation Key 39

Table 3-1 ACF Reservoirs Included in the Analysis and Corresponding MAP Time Series 59

Table 3-2 Sample ACF Precipitation and Evaporation Time Series Data HECDSS Condensed Catalog Listing (from ACFRE.DSS , 2009- 06-23 version) 60

Table 3-3 Sample ACF Aggregate Reach Water Use HECDSS Condensed Catalog Listings (from ACF-unimpaired flow.DSS , 2009-06-29 version) 61

Table 3-4 ACF Reservoir Pre-Development Runoff Coefficients 66

Table 3-5 Sample BUFORD_R Reservoir Effects HECDSS Condensed Catalog Listing (from ACFRE.DSS , 2009-06-23 version) 67

Table 3-6 ACF Streamflow Filling and Routing Summary 68

Table 3-7 MILFORD Multiple Linear Regression Parameters 69

Table 3-8 MILFORD Regression Coefficients 69

Table 3-9 TSTool Command and HECDSS Macro File Listing for ACF Basin Determination 72

Table 3-10 Sample Condensed Catalog Listing of ACF Unimpaired Flow and Component Time Series 75

Table 3-11 ACF Merged Unimpaired Flow Condensed Catalog Listing 77

Table 4-1 ACT Reservoirs Included in the Analysis and Corresponding MAP Time Series 85

Table 4-2 Sample ACT Precipitation and Evaporation Time Series Data HECDSS Condensed Catalog Listing (from ACTRE.DSS, 2009- 06-23 version) 86

Table 4-3 ACT Reservoir Pre-Development Runoff Coefficients 87

Table 4-4 Streamflow Filling Periods and Methods 89

Table 4-5 Monthly MOVE2 Results: Gayles (Dependent) and Routed Summerville (Independent) 91

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Table 4-6 TSTool Command and HECDSS Macro File Listing for ACT Basin Local Incremental Flow Determination 94

Table 5-1 OOA Reservoirs Included in the Analysis and Corresponding MAP Time Series 104

Table 5-2 Sample OOA Precipitation and Evaporation Time Series Data HECDSS Condensed Catalog Listing (from OOARE.DSS , 2009- 06-13 version) 105

Table 5-3 OOA Aggregate Reach Water Use HECDSS Condensed Catalog Listings (from OOA-unimpaired flow.DSS , 2009-06-30 version) 105

Table 5-4 ACF Reservoir Pre-Development Runoff Coefficients 109

Table 5-5 Sample Lake Sinclair (MILLEDGE-SNCLR_R) Reservoir Effects HECDSS Condensed Catalog Listing (from OOARE.DSS , 2009- 06-13 version) 109

Table 5-6 OOA Streamflow Filling and Routing Summary 111

Table 5-7 Annual Multiple Linear Regression Results: Jackson (Y), Macon (X1), and Griffin (X2) 112

Table 5-8 Annual MOVE2 Regression Statistical Results: Penfield (Y) and Greensboro (X) 112

Table 5-9 Annual MOVE2 Regression Statistical Results: Vernon Local (Y) and Reids (X) 113

Table 5-10 Annual Multiple Linear Regression Results: Baxley (Y), Lumber (X1), and Doctown (X2) 114

Table 5-11 TSTool Command and HECDSS Macro File Listing for OOA Basin Local Incremental Flow Determination 115

Table 5-12 Example Condensed Catalog Listing of OOA Unimpaired Flow and Component Time Series 117

Table 6-1 HECDSS Condensed Catalog Listing of SO Study Basin Water Use Data (SO-WU.DSS, 2009-06-29 version) 125

Table 6-2 SO Study Basin Reservoir Effects HECDSS Condensed Catalog Listing (from SORE.DSS, 2009-06-21 version) 130

Table 6-3 SO Study Basin Streamflow Filling and Routing Summary 134

Table 6-4 Russell Inflow Time Shift Summary 137

Table 6-5 Annual MOVE2 Results: Iva Local (Dependent) and Beaverdam Creek (Independent) 139

Table 6-6 Annual MOVE2 Results: Calhoun Falls Local (Dependent) and Mt. Carmel Shifted (Independent) 140

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Table 6-7 Annual MOVE2 Results: Calhoun Falls Local (Dependent) and Bell Back-Routed (Independent) 140

Table 6-8 Annual MOVE2 Results: Calhoun Falls Local (Dependent) and Bell Back-Routed (Independent) 141

Table 6-9 Annual Multiple Linear Regression Results: Augusta Local (Y), Millhaven (X1), and SF_Edisto (X2) 143

Table 6-10 Annual Multiple Linear Regression Results: Burtons Local (Y), Millhaven (X1), and Salkehatchie (X2) 144

Table 6-11 Annual MOVE2 Results: Burtons Local (Dependent) and Shifted Millhaven (Independent) 144

Table 6-12 LDAs and Scaling Ratios for Savannah Local Flow Filling 146

Table 6-13 Annual OLS Results for the Early Period: Thurmond Local (Dependent) and Bell (Independent) 148

Table 6-14 Annual OLS Results for the Second Period: Thurmond Local (Dependent) and Bell (Independent) 148

Table 6-15 Sample Condensed Catalog Listing of SO Unimpaired Flow Component Time Series 150

Table 7-1 Sample OSSS Aggregate Reach Water Use HECDSS Condensed Catalog Listings (from OSSS-unimpaired flow.DSS , 2009-06-26 version 157

Table 7-2 Streamflow Filling and Routing Summary 157

Table 7-3 Monthly MOVE2 Results: Offman (Dependent) and Back-Routed Atkinson (Independent) 161

Table 7-4 TSTool Command for OSSS Basin Local Incremental Flow Determination 165

Table 8-1 HECDSS Catalog Listing for Aggregated Water Use in the TN Basin 173

Table 8-2 TN Streamflow Filling and Routing Summary 175

Table 8-3 Annual Multiple Linear Regression Results: England (Y), Chickmga (X1), and Summerville (X2) 176

Table 8-4 Monthly MOVE2 Results: England (Dependent) and Summerville (Independent) 176

Table 8-5 Annual Multiple Linear Regression Results: Chickmga (Y), Sequatchie (X1), and Summerville (X2) 177

Table 8-6 Monthly MOVE2 Results: Chickmga (Dependent) and Summerville (Independent) 178

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Table 8-7 Monthly MOVE2 Results: Blridg_R Inflows (Dependent) and Dial (Independent) 178

Table 8-8 Monthly MOVE2 Results: Coprhill_Local (Dependent) and Ellijay (Independent) 180

Table 8-9 Monthly MOVE2 Results: Notly_R (Dependent) and Dial (Independent) 181

Table 8-10 Annual Multiple Linear Regression Results: Chatug_R (Y), Dial (X1), and Judson (X2) 182

Table 8-11 LDAs and Scaling Ratios for the Little Tennessee Flow Filling 182

Table 8-12 TSTool Command and HECDSS Macro File Listing for TN Basin Local Incremental Flow Determination 183

Table 8-13 Sample Condensed Catalog Listing of TN Unimpaired Flow and Component Time Series 184

Figures

Figure 2-1 Accumulation Plots for MAP Extension Through 2007 (ACF Reservoirs) 18

Figure 2-2 Double Mass Analysis for MAP Extension Through 2007 (ACT Reservoirs) 19

Figure 2-3 Double Mass Analysis for MAP Extension Through 2007 (OOA Reservoirs) 19

Figure 2-4 Double Mass Analysis for MAP Extension Through 2007 (SO Reservoirs) 20

Figure 2-5 Double Mass Analysis for MAP Extension Prior to 1950 21

Figure 2-6 Accumulation of Precipitation for the Generated MAP and LMRFC MAP for CHICKMGA 22

Figure 2-7 Initial Double Mass Analysis of MAP Time Series at the Tennessee Reservoirs 23

Figure 2-8 Double Mass Analysis of MAP Time Series at the Tennessee Reservoirs After Applying Adjustment 23

Figure 2-9 Sample Adjusted Pan Evaporation and NWS CAP FWS Evaporation Estimates, Allatoona Dam 26

Figure 2-10 Computed Runoff Coefficients (Red) and Runoff Coefficients Specified for Each Reservoir (Yellow) 30

Figure 2-11 Bell, Hartwell, Russell, Thurmond, and Russell+Thurmond Consistency Plots – Before Data Correction 52

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Figure 2-12 Bell, Hartwell, Russell, Thurmond, and Russell+Thurmond Consistency Plots – After Data Correction 53

Figure 3-1 ACF Study Basin Basic and Planning Nodes 55

Figure 3-2 Nodes and Gages Associated with ACF Study Basin Streamflow Filling 57

Figure 3-3 Periods of Record for Gages Associated with ACF Study Basin Streamflow Filling 58

Figure 3-4 ACF Reservoir Location Map 62

Figure 3-5 BUFORD_R Visual Elevation Screening Example 64

Figure 3-6 Georgia Representative Unregulated Flow Gaging Stations and Average Annual Runoff Coefficients 65

Figure 3-7 Merged BAINBRDG-USACE Local Unimpaired Flow Time Series Data 76

Figure 4-1 Map of the ACT Study Basin 81

Figure 4-2 Nodes and Streamflow Gages Associated with the ACT Study Basin Streamflow Filling 83

Figure 4-3 Period of Record for Gages Used in the ACT Study Basin Streamflow Filling 84

Figure 4-4 Georgia Representative Unregulated Flow Gaging Stations and Average Annual Runoff Coefficients 88

Figure 5-1 OOA Study Basin Basic and Planning Nodes 100

Figure 5-2 Nodes and Gages Associated with OOA Study Basin Streamflow Filling 102

Figure 5-3 Periods of Record for Gages Associated with OOA Study Basin Streamflow Filling 103

Figure 5-4 OOA Reservoir Location Map 107

Figure 5-5 Georgia Representative Unregulated Flow Gaging Stations and Average Annual Runoff Coefficients 108

Figure 6-1 SO Study Basin Basic and Planning Nodes 120

Figure 6-2 Nodes and Gages Associated with SO Study Basin Streamflow Filling 123

Figure 6-3 Periods of Record for Gages Associated with SO Study Basin Streamflow Filling 124

Figure 6-4 SO Study Basin Reservoir Location Map 127

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Figure 6-5 THRMND_R Computed One-Day Holdout Flows 128

Figure 6-6 Burton Reservoir Computed One-Day Holdout Flows 129

Figure 6-7 Hartwell Observed and Reconstructed Storage Time Series 135

Figure 6-8 Russell Observed and Reconstructed Storage Time Series 136

Figure 6-9 Hartwell Observed and Reconstructed Storage Time Series 136

Figure 7-1 OSSS Study Basin Basic and Planning Nodes 154

Figure 7-2 Nodes and Gages Associated with OSSS Study Basin Streamflow Filling 155

Figure 7-3 Periods of Record for Gages Associated with OSSS Study Basin Streamflow Filling 156

Figure 8-1 TN Study Basin Basic and Planning Nodes 170

Figure 8-2 Nodes and Gages Associated with TN Study Basin Streamflow Filling 171

Figure 8-3 Periods of Record for Gages Associated with TN Study Basin Streamflow Filling 172

Appendices

A Glossary

B ACF Study Basin

B1 Monthly Distribution, Reach Aggregation, and Water Use Hindcasting HECDSS Condensed Catalog Listings

B2 Reservoir Effects HECDSS Condensed Catalog Listings

B3 Local Incremental Flow HECDSS Condensed Catalog Listings

B4 Unimpaired Local Incremental Flow HECDSS Condensed Catalog Listings

B5 Unimpaired Cumulative Flow HECDSS Condensed Catalog Listings

B6 Intermediate Time Series Data HECDSS Condensed Catalog Listings

B7 EPD Memorandum on Agricultural Water Use

C ACT Study Basin

C1 Monthly Distribution, Reach Aggregation, and Water Use Hindcasting HECDSS Condensed Catalog Listings

C2 Reservoir Effects HECDSS Condensed Catalog Listings

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C3 Local Incremental Flow HECDSS Condensed Catalog Listings

C4 Unimpaired Local Incremental Flow HECDSS Condensed Catalog Listings

C5 Unimpaired Cumulative Flow HECDSS Condensed Catalog Listings

C6 Intermediate Time Series Data HECDSS Condensed Catalog Listings

D OOA Study Basin

D1 Monthly Distribution, Reach Aggregation, and Water Use Hindcasting HECDSS Condensed Catalog Listings

D2 Reservoir Effects HECDSS Condensed Catalog Listings

D3 Local Incremental Flow HECDSS Condensed Catalog Listings

D4 Unimpaired Local Incremental Flow HECDSS Condensed Catalog Listings

D5 Unimpaired Cumulative Flow HECDSS Condensed Catalog Listings

D6 Intermediate Time Series Data HECDSS Condensed Catalog Listings

E OSSS Study Basin

E1 Monthly Distribution, Reach Aggregation, and Water Use Hindcasting HECDSS Condensed Catalog Listings

E2 Local Incremental Flow HECDSS Condensed Catalog Listings

E3 Unimpaired Local Incremental Flow HECDSS Condensed Catalog Listings

E4 Unimpaired Cumulative Flow HECDSS Condensed Catalog Listings

E5 Intermediate Time Series Data HECDSS Condensed Catalog Listings

F SO Study Basin

F1 Monthly Distribution, Reach Aggregation, and Water Use Hindcasting HECDSS Condensed Catalog Listings

F2 Reservoir Effects HECDSS Condensed Catalog Listings

F3 Local Incremental Flow HECDSS Condensed Catalog Listings

F4 Unimpaired Local Incremental Flow HECDSS Condensed Catalog Listings

F5 Unimpaired Cumulative Flow HECDSS Condensed Catalog Listings

F6 Intermediate Time Series Data HECDSS Condensed Catalog Listings

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G TN Study Basin

G1 Monthly Distribution, Reach Aggregation, and Water Use Hindcasting HECDSS Condensed Catalog Listings

G2 Reservoir Effects HECDSS Condensed Catalog Listings

G3 Local Incremental Flow HECDSS Condensed Catalog Listings

G4 Unimpaired Local Incremental Flow HECDSS Condensed Catalog Listings

G5 Unimpaired Cumulative Flow HECDSS Condensed Catalog Listings

G6 Intermediate Time Series Data HECDSS Condensed Catalog Listings

H Master Local Incremental Flow HECDSS Condensed Catalog Listings

I Master Cumulative Unimpaired Flow HECDSS Condensed Catalog Listings

J USGS Stream Gage Data

K EPD Memorandum on Unimpaired Flow Data Verification

L Data CD

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

Executive Summary

This Unimpaired Flow Data Report describes data, methods, assumptions, and procedures applied to the development of unimpaired flows, the basic hydrologic input to the surface water availability modeling component of the Statewide Water Management Plan. Unimpaired flows are those flows in the main stem of rivers that would have historically occurred if the flows had not been altered by human activities such as water withdrawals, discharges, and installation and operation of flow regulation structures such as dams. In developing unimpaired flows, some human influences cannot be accounted for because either they have not been recorded or they are not readily quantifiable (i.e., the effects of changing land uses on runoff and streamflow). Quantifiable human influences addressed in this study include streamflow regulation effects of manmade reservoirs and water consumption for municipal, industrial, agricultural, and thermal power uses. In some reaches, groundwater pumping reduces surface water flows; these have been taken into account in the development of unimpaired flows. Thus, while flows developed in this study are not entirely unimpaired in the literal sense, they do capture the major reversible human influences.

The period of analysis for unimpaired flows statewide is 1939 through 2007. This 69-year period includes at least six severe, multi-year, regional droughts. Droughts constitute critical periods for water availability analysis and operational simulation of conservation systems in general.

The selected time step for all water use, flow, and meteorological time series data applied is one day. With 76 nodes in six study basins statewide, dozens of time series variables, and up to 25,200 daily values for each, data management challenges alone are enormous and further compounded by the many complex mathematical and statistical programming operations required to be performed on the data.

For each node, calculation of unimpaired flows involved some or all of the following steps:

• Calculation of net water use

- Compilation, aggregation, and hindcasting of current monthly municipal and industrial water withdrawals, wastewater returns, and net water consumption from 1939 to the starting year of present data. The starting year can vary from reach to reach, but is generally between 2000 and 2003.

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

- Compilation and aggregation of historical thermal water use, including withdrawals, returns, and net water consumption

- Compilation and aggregation of historical agricultural surface water withdrawals (assumed to be equivalent to net water consumption for purposes of this study)

- Compilation, aggregation, and hindcasting of municipal, industrial, and agricultural groundwater withdrawals and resulting surface water flow depletions (groundwater effects)

• Computations of reservoir effects (based on available observed reservoir elevation, operator-computed reservoir inflow, and outflow time series)

- Holdout flows (reservoir storage change)

- Pre- and post-reservoir net evaporation (evaporation minus precipitation, runoff)

• Streamflow filling and routing (cumulative historical flows)

- Statistical methods (Maintenance of Variance Extension Type 2, multiple linear regression, ordinary least-squares regression)

- Hydrologic routing and back-routing (Lag-K, variable Lag-K, coefficient method)

- Removal (addition) of reservoir holdout flows, where applicable

- Calculation of reservoir inflows

- Scaling (flow and drainage area ratios)

• Local incremental flow calculation (difference in cumulative historical flows)

• Local incremental unimpaired flow calculation

- Removal (addition) of reach-aggregated net water use (all categories)

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

- Removal (addition) of remaining reservoir effects (holdout and/or net evaporation flows) where applicable

• Local incremental unimpaired flow adjustments (to remove negative incremental flows)

- TSTool AdjustExtremes procedure

- Annual mean flow volume adjustment

- Period of record mean flow volume adjustment

• Merger of extended (2002 to 2007) and existing (1939 to 2001) incremental unimpaired flows (Apalachicola-Chattahoochee-Flint and Alabama-Catoosa- Tallapoosa basins only)

• Quality control procedures

- Manual data adjustments

- Mass balance

- Double mass balance

• Cumulative unimpaired flow development (in progress)

- Reach (between adjacent nodes)

- Sub-basin (between adjacent planning nodes)

- Total (cumulative planning node)

This report describes each of the above-listed procedures in detail and provides case-specific assumptions and rationale for methods selected. Also documented are databases and data management procedures attendant to unimpaired flow development. The adopted approach is comprehensive and produces high-quality unimpaired flow time series data suitable for water availability assessment in both current study and future reservoir system operational modeling applications.

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

1. Introduction

1.1 Need for Unimpaired Flows

Unimpaired flows are defined for purposes of this study as historically observed flows with human influences removed. Human influences considered in derivation of unimpaired flows include flow regulation by and net evaporation from large reservoirs, water withdrawals, and wastewater returns associated with municipal, industrial, thermal power, and agricultural water uses. The use of unimpaired flows, as opposed to historical observed flows, for consumptive use assessments is necessitated by the need to avoid prior appropriation or “grandfathering” of existing water uses as a baseline condition for determination of gross water available to all uses. Moreover, unimpaired flows facilitate the analysis of various uses, whether they are historic, current, or future. The following purposes are served by conversion of streamflow time series data from observed to unimpaired over a uniform, extended period of record:

• Consistent basis for hydrologic and statistical analysis of water availability statewide

• Unbiased assessment of impacts of water uses on water availability within affected river basins

• Equitable basis for formulation and assessment of strategies for effective water management and improved water supply reliability

1.2 Basic and Planning Node Selection

The study area consists of six study basins that are the six major composite river basins designated by the Georgia Environmental Protection Division (EPD) for consumptive use assessment. Study basins are delineated based on hydrologic, topographic, water resource development, water use, and other important considerations in regional planning. Study basin designations are as follows:

• ACF – Apalachicola-Chattahoochee-Flint Basin

• ACT – Alabama-Coosa-Tallapoosa Basin

• SO – Savannah and Ogeechee Basins

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

• OOA – Ocmulgee-Oconee-Altamaha Basin

• OSSS – Ochlockonee, Suwannee, Satilla, and St. Mary’s Basins

• TN – Tennessee

The current scope of the study, including the development of unimpaired flows, was limited to the Georgia or shared portions of the six study basins listed above.

The next level of delineation is the basin level. Basins are defined as individual river watersheds or major tributary watersheds within study basins (e.g., Chattahoochee River basin and Savannah River basin in the ACF and SO study basins, respectively). The third level of delineation is the sub-basin. Sub-basins are defined as watersheds between planning nodes or the total drainage area above the most upstream planning node.

Basic nodes are locations of interest on rivers or major tributary streams where unimpaired flows are derived. In most instances, basic nodes are located at or near U.S. Geological Survey (USGS) stream gages or at dams. With some exceptions (Russell Dam on the Savannah River, W.F. George Dam on the Chattahoochee River), the nearest downstream gage location is preferred to the dam site for basic nodes (i.e., the Chattahoochee gage instead of Jim Woodruff Dam on the Apalachicola). Ideally, basic nodes are located at gages with records of suitable length for direct determination or fill-in of the 1939 to 2007 period of record.

Planning nodes are normally basic nodes for which consumptive use assessments are performed. Planning nodes are located where possible to avoid separation of major utility withdrawals and returns and to avoid separation of planning regions and municipalities served by multiple water utilities (e.g., Metropolitan North Georgia Water Planning District upstream of Whitesburg, Chattahoochee River). One or more basic nodes may be interspersed between planning nodes. An exception to the planning- basic node correspondence is a virtual planning node located at or near the most downstream Georgia location (in some cases outside of Georgia) on rivers for which no observed streamflow data are available.

Local drainage areas (LDAs) are watersheds between basic nodes or the total drainage area above the most upstream basic node. Reaches are river or tributary segments and contributing LDAs between adjacent nodes (basic or planning) or above the most upstream node (basic or planning); reaches are designated by downstream node.

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

Table 1-1 Key to Basin and Node Names

HECDSS B PART HECDSS A HECDSS A PART DEFINED DEFINED PART (Study Basin– HECDSS A PART HECDSS B River or SUFFIX PART Tributary HECDSS A PART PREFIX (River Basin or (Abbreviated Basin) (Study Basin) Tributary Basin) Node Name) Full Node Name ACF-CHATT Apalachicola-Chattahoochee-Flint Chattahoochee River BUFORD_R Buford Dam ACF-CHATT Apalachicola-Chattahoochee-Flint Chattahoochee River NORCROSS Norcross ACF-CHATT Apalachicola-Chattahoochee-Flint Chattahoochee River ATLANTA Atlanta ACF-CHATT Apalachicola-Chattahoochee-Flint Chattahoochee River WHITSBRG Whitesburg ACF-CHATT Apalachicola-Chattahoochee-Flint Chattahoochee River WESTPT_R West Point Reservoir ACF-CHATT Apalachicola-Chattahoochee-Flint Chattahoochee River COLUMBUS Columbus Walter F. George ACF-CHATT Apalachicola-Chattahoochee-Flint Chattahoochee River WFG_R Reservoir ACF-CHATT Apalachicola-Chattahoochee-Flint Chattahoochee River COLUMBIA Columbia ACF-FLINT Apalachicola-Chattahoochee-Flint Flint River MONTEZMA Montezuma ACF-FLINT Apalachicola-Chattahoochee-Flint Flint River ALBANY Albany ACF-FLINT Apalachicola-Chattahoochee-Flint Flint River NEWTON Newton ACF-FLINT Apalachicola-Chattahoochee-Flint Flint River BAINBRDG Bainbridge ACF-ICHACR Apalachicola-Chattahoochee-Flint Ichawaynochaway Creek MILFORD Milford ACF-SPRGCR Apalachicola-Chattahoochee-Flint Spring Creek IRON_CTY Iron City ACF-APCOLA Apalachicola-Chattahoochee-Flint Apalachicola River WOODRF_R Woodruff Dam

ACT-COOSAW Alabama-Coosa-Tallapoosa Coosawattee River CARTERS_R Carters Dam Carters Reregulated ACT-COOSAW Alabama-Coosa-Tallapoosa Coosawattee River C_REREG Dam ACT-COOSAW Alabama-Coosa-Tallapoosa Coosawattee River PINE Pine Chapel ACT-CONASA Alabama-Coosa-Tallapoosa Conasauga River TILTON Tilton ACT-OOSTAN Alabama-Coosa-Tallapoosa Oostanaula River RESACA Resaca Rome at Oostanaula ACT-OOSTAN Alabama-Coosa-Tallapoosa Oostanaula River ROME_O River ACT-ETOWAH Alabama-Coosa-Tallapoosa Etowah River CANTON Canton ACT-ETOWAH Alabama-Coosa-Tallapoosa Etowah River ALATNA_R Allatoona Dam ACT-ETOWAH Alabama-Coosa-Tallapoosa Etowah River KINGSTON Kingston

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

Table 1-1 Key to Basin and Node Names

HECDSS B PART HECDSS A HECDSS A PART DEFINED DEFINED PART (Study Basin– HECDSS A PART HECDSS B River or SUFFIX PART Tributary HECDSS A PART PREFIX (River Basin or (Abbreviated Basin) (Study Basin) Tributary Basin) Node Name) Full Node Name ACT-ETOWAH Alabama-Coosa-Tallapoosa Etowah River ROME_E Rome at Etowah River ACT-COOSA Alabama-Coosa-Tallapoosa Coosa River ROME_C Rome at Coosa River ACT-CHTOOG Alabama-Coosa-Tallapoosa Chatooga River GAYLES Gayles ACT-TALLA Alabama-Coosa-Tallapoosa Tallapoosa River HEFLIN Heflin ACT-LTALLA Alabama-Coosa-Tallapoosa Little Tallapoosa River NEWELL Newell

OOA-MOCNEE Ocmulgee-Oconee-Altamaha Middle Oconee River ATHENS Athens OOA-OCONEE Ocmulgee-Oconee-Altamaha Oconee River PENFIELD Penfield OOA-OCONEE Ocmulgee-Oconee-Altamaha Oconee River MILLEDGE Milledgeville OOA-OCONEE Ocmulgee-Oconee-Altamaha Oconee River DUBLIN Dublin OOA-OCONEE Ocmulgee-Oconee-Altamaha Oconee River VERNON Mount Vernon OOA-OCMULG Ocmulgee-Oconee-Altamaha Ocmulgee River JACKSON Jackson OOA-OCMULG Ocmulgee-Oconee-Altamaha Ocmulgee River MACON Macon OOA-OCMULG Ocmulgee-Oconee-Altamaha Ocmulgee River LUMBER Lumber City OOA-ALTAMA Ocmulgee-Oconee-Altamaha Altamaha River BAXLEY Baxley OOA-OHOOP Ocmulgee-Oconee-Altamaha Ohoopee River REIDS Reidsville OOA-ALTAMA Ocmulgee-Oconee-Altamaha Altamaha River DOCTOWN Doctortown

Ochlockonee-Suwannee-Satilla-St. OSSS-LSATLA Little Satilla River OFFMAN Offerman Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-SATLA Satilla River WAYCROSS Waycross Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-SATLA Satilla River ATKINSON Atkinson Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-SMARYS St. Mary's River MACCLENY MacClenny Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-SMARYS St. Mary's River GROSS Gross Mary’s

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Table 1-1 Key to Basin and Node Names

HECDSS B PART HECDSS A HECDSS A PART DEFINED DEFINED PART (Study Basin– HECDSS A PART HECDSS B River or SUFFIX PART Tributary HECDSS A PART PREFIX (River Basin or (Abbreviated Basin) (Study Basin) Tributary Basin) Node Name) Full Node Name Ochlockonee-Suwannee-Satilla-St. OSSS-SWANEE Suwannee River FARGO Fargo Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-ALAPHA Alapaha River ALAPAHA Alapaha Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-ALAPHA Alapaha River STATVL Statenville Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-ALAPHA Alapaha River JENNINGS Jennings Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-WITHLA Withlacoochee River BEMISS Bemiss Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-OKAPCR Okapilco Creek QUITMAN Quitman Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-WITHLA Withlacoochee River PINETTA Pinetta Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-OCHLKN Ochlockonee River THOMASVL Thomasville Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-OCHLKN Ochlockonee River CONCORD Concord Mary’s Ochlockonee-Suwannee-Satilla-St. OSSS-LITTLE Little River QUINCY Quincy Mary’s

SO-SENECA Savannah-Ogeechee Seneca River KEOWEE_R Lake Keowee SO-SAVNAH Savannah-Ogeechee Savannah River HARTWL_R Hartwell Reservoir SO-SAVNAH Savannah-Ogeechee Savannah River RBR_R Russell B. Reservoir SO-BROAD Savannah-Ogeechee Broad River BELL Bell SO-SAVNAH Savannah-Ogeechee Savannah River THRMND_R Thurmond Reservoir SO-SAVNAH Savannah-Ogeechee Savannah River AUGUSTA Augusta SO-SAVNAH Savannah-Ogeechee Savannah River BURTONS Burtons SO-BRIRCR Savannah-Ogeechee Brier Creek MILLHAVN Millhaven SO-SAVNAH Savannah-Ogeechee Savannah River CLYO Clyo SO-SAVNAH Savannah-Ogeechee Savannah River SAVANNAH Savannah

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

Table 1-1 Key to Basin and Node Names

HECDSS B PART HECDSS A HECDSS A PART DEFINED DEFINED PART (Study Basin– HECDSS A PART HECDSS B River or SUFFIX PART Tributary HECDSS A PART PREFIX (River Basin or (Abbreviated Basin) (Study Basin) Tributary Basin) Node Name) Full Node Name SO-OGCHEE Savannah-Ogeechee Ogeechee River EDEN Eden SO-CNOOCH Savannah-Ogeechee Canoochee River CLAXTON Claxton SO-OGCHEE Savannah-Ogeechee Ogeechee River KINGSFY Kings Ferry

TN-LTENN Tennessee Little Tennessee LITLE_TN Little Tennessee TN-HIAWAS Tennessee Hiwassee River CHATUG_R Chatuge Dam TN-NOTTLY Tennessee Nottely River NOTLY_R Nottely Dam TN-TOCCOA Tennessee Toccoa River BLRIDG_R Blue Ridge Reservoir TN-OCOEE Tennessee Ocoee River COPRHILL Copperhill South Chickamauga TN-SCHKCR Tennessee Creek CHICKMGA Chickamauga TN-LOOKCR Tennessee Lookout Creek ENGLAND England

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

2. General Procedures for Unimpaired Flow Development

2.1 General Description of Unimpaired Flow Process

The starting point for derivation of unimpaired flows is historical observed flows at basic nodes, and at stream gages used to augment missing historical flows at basic and planning nodes. The period of record (POR) required for unimpaired flow calculations is 1939 to 2007. The starting year of the POR, 1939, was selected because this was the starting year of the streamflow data used in the ACT/ACF Comprehensive Study dated July 8, 1997. The year 1939 was chosen as the starting period for the Comprehensive Study because records prior to this date are sparse, and the drought that began in 1939 is included in the POR. Records are very sparse for the previous drought period from 1927 through 1929. The year 2007 was selected as the end date of the POR because complete USGS water use and other data were available for the full year. Adjustments to observed flows to produce unimpaired flows include the following:

• Addition of holdouts, which are defined as changes in storage in upstream reservoirs applied to observed flows, and subtraction of releases from storage from observed flows downstream of reservoirs, resulting in “unregulated” flows

• Addition of net evaporation (evaporation minus precipitation) from upstream reservoirs to downstream observed flows

• Addition of upstream water withdrawals and subtraction of upstream returns from downstream observed flows

The unimpaired flow calculation process in general involves the following steps:

1. Collect and inventory streamflow data, reservoir data, and water use data; identify data gaps and need for data filling or time series data extension.

2. Compute reservoir inflows, holdouts, and releases from storage in river reaches upstream of nodes.

3. Compute net surface evaporation (evaporation less precipitation) from reservoirs in river reaches upstream of nodes.

4. Fill observed streamflow and reservoir inflow time series to produce time series data coverage for the entire 1939 to 2007 POR.

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

5. Compute local incremental flows by routing upstream observed flows and subtracting from (filled) downstream observed flows; negative locals may result depending on multi-hourly variability within daily average flow readings, reach lengths, and routing methods employed.

6. Compute local incremental unimpaired flows by adjusting local incremental flows to remove the following effects of reservoirs and human uses of water:

a. Holdouts and releases from reservoir storage (step 2)

b. Net surface evaporation from reservoirs (step 3)

c. Net diversions (withdrawals less returns) in river reaches between nodes by municipal, industrial, thermal power, and agricultural water users; both direct (surface) water withdrawals and indirect (groundwater) pumping and resulting depletion of surface waters are accounted for in this step of the analysis.

2.1.1 Reach Cases

Unimpaired flows are determined for the downstream node on each reach. In general, there are four types of reaches, described as follows:

• Typical reach – A river or tributary segment and contributing LDAs between adjacent nodes (basic or planning).

• Headwater reach – A river or tributary segment and contributing LDAs above the most upstream node (basic or planning).

• Reach with downstream reservoir – Similar to a typical reach, but the downstream node is a reservoir.

• Reach with intermediate reservoir – Similar to a typical reach, but with one or more reservoirs located on rivers or tributaries between the upstream and downstream nodes of the reach.

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

2.2 Data Inventory and Management

2.2.1 Water Use Data

Computation of unimpaired flows requires removal of the effects of human uses of water – withdrawals and returns – from the historical streamflow record. Water uses considered in this study include municipal, industrial, thermal power, and agricultural irrigation. Removal of these effects is accomplished by adding net uses (withdrawals minus returns) to observed historical flows based on the following procedures:

• Municipal withdrawals and returns are aggregated by reach rather than by individual utilities; utilities may withdraw from and return to different reaches of the same river or return to different rivers or river basins from which withdrawals were made (interbasin transfer). Careful consideration of the location of aggregation points (i.e., planning nodes) is employed to minimize the splitting of returns from withdrawals between different reaches.

• In most instances, thermal power intakes and outfalls are co-located within reaches, and available water use data normally reflect reach net (consumptive) use.

• Estimated agricultural water use data aggregate direct surface and effective surface withdrawals from groundwater pumping.

• Net reach water uses are aggregated for all users and use categories by reach on a daily time step for purposes of unimpaired flow derivation.

Monthly water use data were collected from the earliest date of available monthly withdrawal and return data through 2007. Monthly data are limited to the most recent 10 to 20 years in almost all cases, and most include data gaps that required filling. Data including major (≥ 1 million gallons per day [MGD]) and minor (< 1 MGD) withdrawals and discharges by municipalities, industries, and thermal power plants were obtained in electronic format whenever possible through Georgia EPD, its various district offices, or other public databases with the assistance of Georgia EPD staff. Georgia EPD staff assisted in obtaining water use data from neighboring states of South Carolina and Alabama (through the U.S. Army Corps of Engineers [USACE]). Relationships for determination of net surface water depletions from groundwater pumping for irrigation were also provided by Georgia EPD. The Water Use Data Inventory Report provides further details related to the water use data.

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

2.2.2 Streamflow Data

Streamflow data were obtained primarily from USGS gage records, although reservoir inflows and outflows were in some cases obtained from USACE, the Tennessee Valley Authority (TVA), and private power reservoir operators, such as Georgia Power. Data downloaded from USGS web sites were generally assumed to be correct; however, some errors were identified and presented to USGS for correction. In most cases, USGS gages immediately downstream of reservoirs were used in place of operator- measured reservoir outflows.

2.2.3 Routing Model Parameterization

The Lag-K hydrologic routing model was selected as the routing model for the project. Lag-K is a commonly used routing method that combines the concepts of lagging the inflow to simulate travel time in a river reach and attenuating the wave to simulate the storage-outflow relationship for the reach. The lags for reaches in this study were in units of hours. Because the attenuation (K) is described as the ratio of reach outflow to reach storage, it also has units of hours. The Lag-K model is used by the Southeast River Forecast Center (SERFC), which is the National Weather Service (NWS) office responsible for providing river forecasts throughout Georgia (with the exception of the Tennessee River tributaries) and the Southeast.

SERFC provided the project team with the hydrologic models for its forecast area, from which the project team extracted the Lag-K models and parameters for each river reach in the study area. In some cases, multiple SERFC river reaches were included in a single sub-basin defined for the unimpaired flow study. In those cases, the total lag time for the unimpaired flow reach was estimated as the sum of the lag times in the individual SERFC reaches. The total attenuation for the reach was also estimated as the sum of the individual attenuation values from SERFC reaches.

The NWS Interactive Calibration Program (ICP) was the tool used to calibrate the Lag-K model for most river reaches. ICP is a graphical calibration program. Inputs for a typical Lag-K reach calibration include the time series for the upstream and downstream gages, the parameterized Lag-K model, time series manipulation models to change the time step of a time series, hydrograph display routines that allow the user to compare the downstream observed time series to the lagged and attenuated flows from upstream, and statistical output comparing the downstream observed and routed flows. The routed flows were not a perfect match for the observed downstream flows because they did not include local area contributions to streamflow between

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan gages. However, it was possible to calibrate lag and attenuation parameters by comparing hydrograph characteristics such as timing of peak flows (affected by the lag and the K) and the shape of the recession after a hydrograph peak (affected by the K).

The Lag-K model used for this study allows the lag and K values to be functions of the flow, a technique commonly referred to as the variable Lag-K model. Some reaches used by SERFC included variable Lag-K models and were incorporated into this study. Some unimpaired flow reaches included multiple SERFC reaches, each with variable lag and K models. In some cases with multiple routing models, the models were replaced with a single routing model.

2.2.4 Reservoir Physical and Operational Data

Reservoir physical and operational hydrologic data are available from several sources. Physical data pertain to project physical features and characteristics (e.g., stage- storage-area curves, dam and outlet works dimensions, rating curves, and operational limits). Operational data consist of time series observed or computed reservoir inflows, outflows, pool elevations, and state variables – either naturally occurring or controlled by operational decisions. All physical and time series data pertinent to unimpaired flow derivation have been entered into the USACE Hydrologic Engineering Center Data Storage System (HECDSS) database and have been quality controlled.

Federal reservoir operational data include elevation, inflow, and outflow time series data obtained from TVA and USACE web sites. Physical reservoir data have been obtained from the respective agencies by special request or in the form of reservoir regulation manuals, water control plans, or other published sources.

Private power reservoir data were obtained in electronic or hard-copy formats, primarily from Georgia Power and Duke Energy companies. Hard-copy data were manually interpreted, entered into databases, and quality controlled as necessary.

2.2.5 Reservoir Meteorological Data

To develop unimpaired flows, effects of precipitation and evaporation on reservoir surfaces must also be removed. Consequently, precipitation and evaporation time series for each reservoir included in the study needed to be developed with these appropriate hydrologic runoff coefficients. Total runoff coefficients (as opposed to surface runoff coefficients) are required to include effects of precipitation excess entering the river system via all paths (i.e., surface and groundwater flow). The time

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan series and runoff coefficients were used to account for net evaporation (evaporation less precipitation) losses from the reservoirs over the study period.

Precipitation time series development extended available mean areal precipitation (MAP) time series previously developed by SERFC and the Lower Mississippi River Forecast Center (LMRFC). The evaporation time series development was based on a combination of long-term information from free water surface evaporation maps produced by the National Oceanic and Atmospheric Administration (NOAA) and daily potential evapotranspiration (PET) estimates based on the Hamon method.

2.2.5.1 Precipitation

SERFC and LMRFC have developed MAP time series for sub-basins throughout the state of Georgia. For the majority of the reservoirs included in the study, MAP time series were available for the sub-basin upstream of the reservoir. The MAP sub-basins cover an area equal to or smaller than the LDAs defined for the Georgia EPD project. The MAP time series were originally derived using hourly and daily station data downloaded from the National Climatic Data Center (NCDC) and were quality controlled to remove outliers and long-term bias from the stations. The NWS River Forecast System (NWSRFS) MAP processor was used to compute the MAP time series.1 The MAP processor includes missing data estimation techniques to fill missing precipitation observations prior to computing the MAP. The MAP generation used the Thiessen polygon weighting scheme. The MAP processor was used by Riverside for the extension of the existing MAP time series. The resulting MAP time series were generated on a six-hour time interval and later aggregated to daily values.

Table 2-1 summarizes the MAP time series assigned to each reservoir with the original period of record for each MAP time series. MAP time series were assigned based on the sub-basin encompassing the reservoir in every case except for Georgia Power’s Nacoochee, Rabun, and Tallulah Falls projects, for which an adjacent sub-basin was selected with more representative long-term precipitation. Reservoirs that began operation prior to 1950 are also identified in the table.

1These processors can be found at the following web site: (http://www.nws.noaa.gov/oh/hrl/nwsrfs/users_manual/part2/_pdf/26calb_map.pdf)

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

Table 2-1 Reservoirs Included in the Analysis and Corresponding MAP Time Series

Reservoir Operated MAP MAP Period of A_PART B_PART Reservoir Prior to 1950? Identifier Record ACF-CHATT BUFORD_R Lake Lanier N CMMG1 1/1950 – 12/1999 ACF-CHATT WESTPT_R West Point Lake N WETG1 1/1950 – 12/1999 ACF-CHATT COLUMBUS-HARDNG_R Lake Harding N CLBG1 1/1950 – 12/1999 ACF-CHATT COLUMBUS-GOATR_R Goat Rock Lake N CMUG1 1/1950 – 12/1999 ACF-CHATT COLUMBUS-OLIVER_R Lake Oliver N CMUG1 1/1950 – 12/1999 ACF-CHATT COLUMBUS-BIBB_R Bibb Pond N CMUG1 1/1950 – 12/1999 ACF-CHATT WFG_R Walter F. George N FOGG1 1/1950 – 12/1999 ACF-CHATT COLUMBIA George W. Andrews N COLA1 1/1950 – 12/2004 ACF-APCOLA WOODRF_R Lake Seminole N WDRF1 1/1950 – 12/2004 ACT-COOSAW C_REREG-CARTRS_R Carters Lake Reservoir N CTRG1 1/1950 – 12/2004 ACT-COOSAW C_REREG-REREG_R Carters Rereg N CTSG1 1/1950 – 12/2004 ACT-ETOWAH ALATNA_R Lake Allatoona N CVLG1 1/1950 – 12/2004 OOA-OCMULG JACKSON-JACKSN_R Lake Jackson Y JACG1 1/1950 – 12/1999 OOA-OCONEE MILLEDGE-OCONEE_R Lake Oconee N WDMG1 1/1950 – 12/1999 OOA-OCONEE MILLEDGE-SNCLAIR_R Lake Sinclair N SNCG1 1/1950 – 12/1999 SO-SENECA KEOWEE_R-JOCASS_R Lake Jocassee N JCSS1 1/1950 – 12/1999 SO-SENECA KEOWEE_R Lake Keowee N KEOS1 1/1950 – 12/1999 SO-SAVNAH HARTWL_R-BURTON_R Lake Burton Y TIGG1 1/1950 – 12/1999 SO-SAVNAH HARTWL_R-NACOCH_R Lake Seed Y TIGG1 1/1950 – 12/1999 SO-SAVNAH HARTWL_R-RABUN_R Lake Rabun Y TIGG1 1/1950 – 12/1999 SO-SAVNAH HARTWL_R-TALLUL_R Tallulah Falls Lake Y TIGG1 1/1950 – 12/1999 SO-SAVNAH HARTWL_R-TUGALO_R Lake Tugalo Y HRTG1 1/1950 – 12/1999 SO-SAVNAH HARTWL_R-YONAH_R Lake Yonah Y HRTG1 1/1950 – 12/1999 SO-SAVNAH HARTWL_R Lake Hartwell N HRTG1 1/1950 – 12/1999 SO-SAVNAH RBR_R Lake Russell N RBRS1 1/1950 – 12/1999 SO-SAVNAH THRMND_R J. Strom Thurmond Lake N CHDS1 1/1950 – 12/1999 SO-SAVNAH AUGUSTA-STVNCR_R Stevens Creek Reservoir N AGTG1 1/1950 – 12/1999 TN-TOCCOA BLRIDG_R Blue Ridge Reservoir Y No MAP available TN-NOTTLY NOTLY_R Nottely Reservoir Y No MAP available TN-HIAWAS CHATUG_R Chatuge Lake Y No MAP available

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The required POR of unimpaired flows extends from January 1, 1939 through December 31, 2007. The MAP time series consequently required an extension to produce a complete POR through 2007 at every location. In addition, for those reservoirs operating prior to 1950, the MAP time series needed to be extended back to 1939. No MAP time series were available for the reservoirs located in the Tennessee basin (Blue Ridge, Nottely, and Chatuge reservoirs), so the entire record was generated from available precipitation station data. After extending the six-hour MAP time series, the six-hour data were accumulated to a daily time step and output to the DSS format.

MAP Extension for Existing MAP Time Series: The original input control files and quality-controlled station data were available from SERFC for MAP generation. Station precipitation data were downloaded from NCDC for all stations included in the MAP generation from 1939 through 2007 to extend the existing MAP. These precipitation time series and original MAP input files were then used to generate new MAP time series for the later missing period using the NWSRFS MAP processor.

Excluding the Tennessee basin, three MAP time series required extension prior to 1950 (JACG1, TIGG1, and HRTG1 in Table 2-1 above). Prior to 1948, the NCDC precipitation network was sparser, and many of the stations had to be estimated. In sparse networks, the estimation algorithm in the MAP processor sometimes underestimates station precipitation when there are limited nearby stations with data. This effect was apparent in several cases in accumulation plots. To remedy this problem, new MAP processor input files were created that only utilized stations that reported prior to 1948 to generate updated MAP time series. This eliminated the need to estimate missing data.

Quality Control of Extended MAP Time Series: Various quality control checks were made between the original and extended MAP time series. The MAP time series extension was performed for a period extending prior to that needed to allow a direct comparison between the newly generated MAP time series and the original SERFC MAP time series. The original and updated time series were nearly identical for corresponding days.

Analyses similar to a double mass analysis were completed on the resulting MAP time series to check for consistency between the extended and original periods. Each MAP time series was accumulated over the POR. The average of all the MAP accumulations was then subtracted from each accumulated MAP time series, and the results were plotted to identify any potential shifts over time. Only minor breaks were observed in

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan the slope of the double mass curves, and none appeared at the time of the data extension. Figures 2-1 to 2-5 show the double mass analysis for each MAP time series, except for the Tennessee basin, which had special considerations and is discussed in its own section.

Figure 2-1 Accumulation Plots for MAP Extension Through 2007 (ACF Reservoirs)

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

Figure 2-2 Double Mass Analysis for MAP Extension Through 2007 (ACT Reservoirs)

Figure 2-3 Double Mass Analysis for MAP Extension Through 2007 (OOA Reservoirs)

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Figure 2-4 Double Mass Analysis for MAP Extension Through 2007 (SO Reservoirs)

A similar double mass comparison was completed for the three locations that required extension for the period between 1939 and 1950. The MAP generated for the early period relied on a reduced precipitation station network and produced a MAP with slightly different characteristics before and after 1950, as demonstrated in the double mass plot. The shift in the double mass plot was not large enough to merit adjustments.

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Figure 2-5 Double Mass Analysis for MAP Extension Prior to 1950

Tennessee Basin MAP Development: LMRFC developed MAP time series for forecasting of the Chickamagua Creek sub-basin (node CHICKMGA), but MAP time series were not available for any other TN reservoir sub-basin. Consequently, it was necessary to develop precipitation time series for the three reservoirs, beginning with station precipitation data. The MAP generation was completed in two steps because of the differences in the station network before and after 1950. In the first step, all surrounding stations with more than five years of data between 1950 and 2007 were included to produce the MAP from 1950 to 2007. In the second step, only those stations reporting between 1939 and 1950 were included. MAP time series were generated for the CHICKMGA sub-basin for comparison with the MAP time series generated by LMRFC. The accumulation of both time series is shown on Figure 2-6.

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Figure 2-6 Accumulation of Precipitation for the Generated MAP and LMRFC MAP for CHICKMGA

A double mass analysis was also conducted for the MAP time series at the three TN reservoirs. Figure 2-7 displays the initial double mass analysis, which reveals an apparent shift in the MAP characteristics for Blue Ridge Reservoir around 1969. This shift is likely because of changes in the precipitation network or inconsistencies in the input time series over the period of record. The early period Blue Ridge Reservoir MAP was scaled using a factor of 0.9 for the period before January 1, 1969 to correct for this shift in MAP characteristics; the resulting double mass plot is shown on Figure 2-8.

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Figure 2-7 Initial Double Mass Analysis of MAP Time Series at the Tennessee Reservoirs

Figure 2-8 Double Mass Analysis of MAP Time Series at the Tennessee Reservoirs After Applying Adjustment

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Adjustment for Long-Term Average Precipitation: The amount of precipitation that falls over the reservoirs may differ from the amount that falls over the sub-basins encompassing the reservoirs. In some locations where the variation in precipitation over a sub-basin is high, these differences can be high and result in an overestimation or underestimation of precipitation on reservoir surfaces.

The difference in precipitation between the reservoir area and the encompassing sub- basin was accounted for by considering average annual historical precipitation estimates derived from the gridded 800-m Spatial Climate Analysis Service (Oregon State University) Parameter-Elevation Regressions on Independent Slopes Model (PRISM). From this gridded data set, the 1971 to 2000 average annual precipitation was computed for every reservoir over its surface area (or a point representing the reservoir if a polygon was not available to represent the reservoir).

The precipitation time series for each reservoir was adjusted by scaling the time series by the ratio of the average annual precipitation over the reservoir, estimated from the PRISM data set, to the average MAP over the sub-basin for the equivalent period (1971 to 2000). See the Adjustment Factor column in Table 2-2 for the scaling ratio corresponding to each reservoir. This adjustment ensures that the long-term volume represented by the precipitation time series matches the long-term average over the reservoir available from the PRISM data set. Table 2-2 lists PRISM and MAP annual precipitation estimates for the 1971 to 2000 period and the corresponding adjustment factor for each reservoir.

Table 2-2 Annual Precipitation Estimates and Corresponding Adjustment Factors for Each Reservoir

Adjustment A_PART B_PART Reservoir PRISM (in) MAP (in) Factor ACF-CHATT BUFORD_R Lake Lanier 56.0 61.4 0.91 ACF-CHATT WESTPT_R West Point Lake 53.1 53.2 1.00 ACF-CHATT COLUMBUS-HARDNG_R Lake Harding 51.2 52.8 0.97 ACF-CHATT COLUMBUS-GOATR_R Goat Rock Lake 50.7 50.8 1.00 ACF-CHATT COLUMBUS-OLIVER_R Lake Oliver 48.9 50.8 0.96 ACF-CHATT COLUMBUS-BIBB_R Bibb Pond 48.8 50.8 0.96 ACF-CHATT WFG_R Walter F. George 53.7 50.9 1.05 ACF-CHATT COLUMBIA George W. Andrews 55.7 54.0 1.03 ACF-APCOLA WOODRF_R Lake Seminole 56.7 54.6 1.04 ACT-COOSAW C_REREG-CARTRS_R Carters Lake 59.2 61.3 0.97

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Table 2-2 Annual Precipitation Estimates and Corresponding Adjustment Factors for Each Reservoir

Adjustment A_PART B_PART Reservoir PRISM (in) MAP (in) Factor ACT-COOSAW C_REREG-REREG_R Carters Rereg 57.1 58.3 0.98 ACT-ETOWAH ALATNA_R Lake Allatoona 53.5 52.8 1.01 OOA-OCMULG JACKSON-JACKSN_R Lake Jackson 48.7 47.4 1.03 OOA-OCONEE MILLEDGE-OCONEE_R Lake Oconee 47.7 48.3 0.99 OOA-OCONEE MILLEDGE-SNCLAIR_R Lake Sinclair 47.3 47.0 1.01 SO-SENECA KEOWEE_R-JOCASS_R Lake Jocassee 68.1 81.9 0.83 SO-SENECA KEOWEE_R Lake Keowee 57.9 67.2 0.86 SO-SAVNAH HARTWL_R-BURTON_R Lake Burton 71.0 70.5 1.01 SO-SAVNAH HARTWL_R-NACOCH_R Lake Seed 72.6 70.5 1.03 SO-SAVNAH HARTWL_R-RABUN_R Lake Rabun 69.3 70.5 0.98 SO-SAVNAH HARTWL_R-TALLUL_R Tallulah Falls Lake 66.9 70.5 0.95 SO-SAVNAH HARTWL_R-TUGALO_R Lake Tugalo 61.2 59.9 1.02 SO-SAVNAH HARTWL_R-YONAH_R Lake Yonah 59.8 59.9 1.00 SO-SAVNAH HARTWL_R Lake Hartwell 52.1 59.9 0.87 SO-SAVNAH RBR_R Lake Russell 48.3 49.3 0.98 SO-SAVNAH THRMND_R J. Strom Thurmond Lake 47.4 47.4 1.00 SO-SAVNAH AUGUSTA-STVNCR_R Stevens Creek 47.7 47.1 1.01 TN-TOCCOA BLRIDG_R Blue Ridge 62.9 60.5 1.04 TN-NOTTLY NOTLY_R Nottely 59.9 68.1 0.88 TN-HIAWAS CHATUG_R Chatuge Lake 58.2 59.9 0.97

2.2.5.2 Evaporation Time Series Development

Evaporation time series were developed in cooperation with Georgia EPD staff for calculation of reservoir net evaporation flows. Long-term monthly evaporation estimates developed by NOAA were combined with daily PET estimates computed from temperature data using the Hamon method to produce evaporation estimates for every reservoir. These estimates capture the long-term average evaporation characteristics as well as daily variation in evaporation.

Long-Term Evaporation Estimation: Free water surface evaporation estimation can be problematic because of data quality problems in measured evaporation data. Using

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan quality-controlled pan evaporation and meteorological data, NOAA developed annual and seasonal free water surface evaporation maps for the contiguous United States (NOAA Technical Reports NWS 33 and 34, 1982). NWS later digitized these maps and developed monthly free water surface evaporation grids as part of its Calibration Assistance Program (CAP).

The monthly evaporation grids present a consistent method to derive average monthly free water surface evaporation at every reservoir. The monthly free water surface evaporation estimates from these grids were compared with free water surface evaporation estimates using long-term, monthly pan evaporation data downloaded from NCDC and an assumed pan coefficient (reported in pan coefficient maps from NOAA Technical Report NWS 34). The distributions of the two free water surface estimates generally agree well for stations with better quality data. Differences between estimates did not show consistent trends. The largest discrepancies were caused by erroneous pan evaporation data. A sample comparison for one pan station is shown on Figure 2-9.

Comparison of Adjusted Pan evap and CAP FWS evap GA-0181 : ALLATOONA DAM 2 (nearest reservoir: Allatoona)

6

5

4

3

2

1

Monthly Free Water Surface Evap (in) Surface Monthly Free Water 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Pan data FWS evap (in) CAP FWS evap

Figure 2-9 Sample Adjusted Pan Evaporation and NWS CAP FWS Evaporation Estimates, Allatoona Dam

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Because of the data quality problems at many pan stations and the availability of the monthly free water surface evaporation grids, these grids were used to derive total long-term monthly evaporation estimates at every reservoir using geographic information system (GIS) tools.

Daily PET Estimation: Staff members from Georgia EPD generated daily PET time series for every reservoir using the Hamon PET option of the Watershed Data Management Utility (WDMUtil) program, a utility program associated with the U.S. Environmental Protection Agency (EPA) Hydrological Simulation Program – Fortran (HSPF). The Hamon PET calculation requires time series of daily maximum and minimum temperatures and latitude as inputs. For each reservoir, the daily maximum and minimum temperature time series were estimated from surrounding stations, as described in a separate memo (Georgia EPD 2009-05-18 [PET Calculations].pdf).

Daily PET estimates were generated for 11 locations, with some reservoirs grouped together because of their proximity.

Combination of Long-Term Free Water Surface Evaporation and Daily PET: The PET estimates computed from the Hamon method required adjustment to remove the effects of transpiration and capture the long-term average free water surface evaporation. First, for each reservoir, the average monthly PET was computed for the analysis period corresponding to the NOAA evaporation atlases (1950 to 1976). The ratio of free water surface evaporation to PET was then calculated for every month. After computing the monthly ratios, a daily time series of adjustment factors was generated by assigning the monthly ratio values to the 15th of the month and linearly interpolating the mid-month values. Finally, this daily time series of adjustment factors was multiplied by the daily PET time series to generate a daily time series of free water surface evaporation.

2.2.5.3 Reservoir Runoff Coefficient Selection

After a reservoir has been initially filled and placed in operation, the runoff fraction is increased from the pre-reservoir basin runoff fraction to 100 percent over the reservoir surface. The difference between 100 percent runoff and the basin runoff fraction represents the incremental increase in runoff from the reservoir that needs to be accounted for in the unimpaired flow calculation. An analysis was performed to determine appropriate basin runoff fractions (runoff coefficients) for each reservoir location.

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

The runoff coefficient analysis involved identifying streamflow locations throughout the project area with minimal amounts of upstream streamflow regulation and long streamflow records. A total of 21 sites were identified. After these sites were identified, the average annual precipitation over the drainage area above each gage was estimated using the gridded PRISM data set for the 1971 to 2000 period. The average annual streamflow for the equivalent time period was computed for each stream gage. If streamflow data were missing over the analysis period, the average annual streamflow was computed from the available data. The resulting mean annual streamflow was divided by the drainage area to produce a mean annual depth of runoff over the sub-basin. The ratio of the depth of runoff to mean areal precipitation represents the runoff coefficient for that sub-basin. Table 2-3 summarizes runoff coefficient calculation results for the selected gage locations.

After computing runoff coefficients for the selected stream gage locations, the results were spatially plotted on a map. Considering runoff coefficients from surrounding gage locations and the annual precipitation distribution, runoff coefficients were manually selected for each of the reservoir locations in the project area. Computed and selected runoff coefficients are presented on Figure 2-10, and runoff coefficients for each reservoir are tabulated in Table 2-4.

Table 2-3 Select Stream Gages and Computed Runoff Coefficients Throughout the Project Area

Data Mean Mean Mean Coverage, Annual Annual Annual Gage 1971– Drainage Flow Precip. Flow Runoff Location Number 2000 (%) Area (mi²) (cfs) (in) (in) Coefficient Bell 02192000 100 1420 1841 51.4 17.6 0.34 Millhaven 02198000 100 646 610 47.6 12.8 0.27 Canton 02392000 100 615 1271 61.0 28.0 0.46 Tilton 02387000 100 689 1287 59.1 25.4 0.43 Milford 02353500 100 626 775 52.4 16.8 0.32 Iron_City 02357000 69 483 527 54.5 14.8 0.27 Athens 02217500 100 392 536 53.0 18.5 0.35 Kinchafoonee 02350600 70 194 227 50.1 15.9 0.32 Choctawhatchee 02361000 100 717 979 56.0 18.5 0.33 Griffin 02344500 100 267 350 50.6 17.8 0.35 SF_Edisto 02173000 70 723 719 48.2 13.5 0.28 StevensCreek 02196000 83 539 452 48.0 11.4 0.24

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

Table 2-3 Select Stream Gages and Computed Runoff Coefficients Throughout the Project Area

Data Mean Mean Mean Coverage, Annual Annual Annual Gage 1971– Drainage Flow Precip. Flow Runoff Location Number 2000 (%) Area (mi²) (cfs) (in) (in) Coefficient Saluda-Greenville 02162500 62 296 664 64.1 30.5 0.48 Alcovy-Covington 02208450 96 184 248 52.0 18.2 0.35 MurderCr-Eatonton 02221525 79 192 164 48.5 11.6 0.24 LittleR-Eatonton 02220900 78 266 238 48.7 12.1 0.25 LittleTenn-Prentiss 03500000 100 135 398 71.5 40.1 0.56 FrenchBroadRiver-Blantyre 03443000 100 296 1065 74.2 48.8 0.66 Tellico 03518500 37 129 310 68.3 32.5 0.48 EF_Pidgeon 03456500 100 49 147 67.4 40.3 0.60 FrenchBroadRiver_Rossman 03439000 100 71 247 76.6 47.5 0.62

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

Figure 2-10 Computed Runoff Coefficients (Red) and Runoff Coefficients Specified for Each Reservoir (Yellow)

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Table 2-4 Runoff Coefficients Specified for Each Reservoir

Runoff A_PART B_PART Reservoir Coefficient SO-SENECA KEOWEE_R-JOCASS_R Lake Jocassee 0.55 SO-SAVNAH RBR_R Lake Russell 0.35 SO-SAVNAH AUGUSTA-STVNCR_R Stevens Creek 0.25 OOA-OCMULG JACKSON-JACKSN_R Lake Jackson 0.30 OOA-OCONEE MILLEDGE-OCONEE_R Lake Oconee 0.25 OOA-OCONEE MILLEDGE-SNCLAIR_R Lake Sinclair 0.25 ACF-CHATT BUFORD_R Lake Lanier 0.40 ACF-CHATT WESTPT_R West Point Lake 0.33 ACF-CHATT COLUMBUS-HARDNG_R Lake Harding 0.33 ACF-CHATT COLUMBUS-GOATR_R Goat Rock Lake 0.33 ACF-CHATT COLUMBUS-OLIVER_R Lake Oliver 0.33 ACF-CHATT COLUMBUS-BIBB_R Bibb Pond 0.33 ACF-CHATT COLUMBIA George W. Andrews Lake 0.31 ACF-APCOLA WOODRF_R Lake Seminole 0.28 ACT-COOSAW C_REREG-REREG_R Carters Lake Rereg 0.45 ACT-COOSAW C_REREG-CARTRS_R Carters Lake 0.45 ACT-ETOWAH ALATNA_R Lake Allatoona 0.45 TN-HIAWAS CHATUG_R Chatuge Lake 0.50 TN-TOCCOA BLRIDG_R Blue Ridge 0.50 SO-SAVNAH HARTWL_R-TUGALO_R Lake Tugalo 0.50 SO-SAVNAH HARTWL_R-TALLUL_R Tallulah Falls Lake 0.55 SO-SAVNAH HARTWL_R-RABUN_R Lake Rabun 0.55 SO-SAVNAH HARTWL_R-NACOCH_R Lake Seed 0.55 SO-SAVNAH HARTWL_R-BURTON_R Lake Burton 0.55 SO-SAVNAH HARTWL_R-YONAH_R Lake Yonah 0.50 SO-SENECA KEOWEE_R Lake Keowee 0.50 ACF-CHATT WFG_R Walter F. George 0.32 SO-SAVNAH THRMND_R J. Strom Thurmond Lake 0.25 SO-SAVNAH HARTWL_R Lake Hartwell 0.40 TN-NOTTLY NOTLY_R Nottely 0.50

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2.2.6 Data Management Tools

Three primary data management tools were used in this study: HECDSS, TSTool, and DSSMATH. Microsoft Excel was also used.

HECDSS is a software system designed for storage, retrieval, mathematical and statistical analysis, and display of time series and paired water resources data. Interaction with HECDSS is accomplished through:

• FORTRAN utilities that allow entry, editing, cataloging, and graphical display of information

• FORTRAN application programs that perform calculations and read from and write to the database

• Application of HEC programs (e.g., STATS) that read from and write to databases

• HECDSSVue software incorporating many of the features of the standalone utilities and application programs, and which runs interactively in a Windows environment

• The HECDSS Data Exchange add-in for Excel

• The Riverside Technology, inc. (RTi) TSTool software program

The FORTRAN utilities and application programs may be run interactively or in batch mode and additionally may execute complex instruction sets through the use of macros. HECDSSVue and the Data Exchange add-in are superior to the utilities for interactive application and display but less suited to conditional calculations and batch processing. HECDSSVue provides for creation and importation of scripts, but these capabilities are less accessible and well-documented in comparison to HECDSS and do not permit batch execution of multiple DSS utilities and application programs in sequence, each with different data and instruction sets.

The TSTool software program provides capabilities to read from and write to a HECDSS file and to perform a range of time series manipulations, routings, calculations, and statistical analyses. The program allows definition of commands through a graphical user interface (GUI), stores commands in text files for efficient reprocessing, includes the capability to run Python scripts for more complex processing, and allows batch or interactive processing. TSTool includes some

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan functionality not available through the HECDSS utilities and application programs but does not include all of the same functionality available through the suite of HEC tools.

This project utilized a combination of tools to perform specific tasks related to the unimpaired flow calculations, depending upon the requirements of a task. Because HECDSS utilities and TSTool commands files allow efficient codification and documentation of stepwise unimpaired flow calculations, these tools were used for most of the processing involved in the project. TSTool and HECDSSVue will be used for graphical display and inspection of data, and the Data Exchange add-in will be used principally for exchange of data between DSS files and Excel worksheets.

Through the course of the project, the project team worked to determine the most appropriate tool for a specific processing application. Template macros or command files were created to ensure consistent calculation procedures between river basins.

Data editing capabilities are embodied in the HECDSS utilities and in HECDSSVue permit cataloging, copying, deleting, renaming, duplicating, and merging of records. A critical distinction to be noted is that maximum pathname length (number of characters) is limited in HECDSS utilities in comparison to HECDSSVue or in the Excel Data Exchange add-in. As a consequence, conventions subsequently prescribed limit pathname length to allow full exchange of data between HECDSS utilities, HECDSSVue, and Excel.

Mathematical operations that can be performed on time series data using HECDSS utilities (and in most cases HECDSSVue as well) normally fall into the following categories:

• General (e.g., unit conversions, interpolation, screening)

• Arithmetic (e.g., addition, multiplication, exponentiation, logarithms)

• Time interval conversion (e.g., regular-to-irregular, regular-to-regular from one minute to one year)

• Hydrologic (e.g., routing, rating table interpolation, time shift adjustment, multiple linear regression, data interpolation)

As previously noted, batch programs and macros were employed in this study for execution of complex instruction sets. HECDSSVue provides for creation and

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan importation of scripts, but these capabilities are less accessible and well-documented in comparison to HECDSS and do not permit batch execution of multiple DSS utilities and application programs in sequence, each with different data and instruction sets. Lastly, it should also be noted that HECDSS routines normally operate on blocks (arrays) of time series data simultaneously rather than sequentially by time step. Scalar and paired-data operations are permitted if data types are compatible.

DSSMATH is an application program that enables mathematical manipulation of data stored in HECDSS. The program provides capabilities for mathematical, statistical, and conditional computations; data conversion and transformation, such as stage to flow; unit and time step conversion; screening; and estimation of missing or erroneous values. The program may be used in an automated batch environment for processing a real-time data stream, or it can be used interactively to perform ad-hoc operations.

2.2.7 Data Management Nomenclature

The following, from the HECDSS Users Guide, March 1995, describes the concept of pathnames in HECDSS:

DSS records are referenced by their pathnames. The pathname consists of up to 80 characters and is delimited by a slash "/", as follows:

/A/B/C/D/E/F/

For example, a brief description of the pathname for time series data is as follows:

Pathname Part Description A River basin or project name B Location or gage identifier C Data variable, e.g., FLOW, PRECIP D Starting date for block of data, such as 01JAN1981 for daily data in 1981 E Time interval, e.g., 1DAY, 3HOUR, 1MON F Additional user-defined description to further define the data, e.g., PLAN A

In keeping with the HECDSS convention, the following nomenclature was used in the HECDSS pathnames for the water use data:

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

A_PART B_PART C_PART D_PART E_PART F_PART Study Basin- Reach Name- Data Period of Time Step Source or Means of River Basin Facility Name Variable - Record Deriving-Water Use Type Description

Below is an example of the HECDSS pathnames for water use time series:

A_PART B_PART C_PART D_PART E_PART F_PART OOA-OCONEE VERNON-WLMHS FLOW-DIV RET MGD 01JAN1980- 1MON OBS-M 01JAN2000

A similar nomenclature was developed for the intermediate time series (which include filling, routing, reservoir, and local incremental flow time series) as well as for the unimpaired flow time series. The A, D, and E pathname parts for the intermediate time series and unimpaired flow time series follow the same nomenclature as the water use time series described above. The B parts in the intermediate time series and unimpaired flow time series contain only the reach name except for observed time series at USGS gage sites, which also include the gage number after the reach name. The B part for time series that are forward- or back-routed always show the name of the reach to which the flow is being routed. The C pathname part for the intermediate time series contains the flow type.

The six different flow types in the intermediate time series are:

• FLOW-CUM – Cumulative flow

• FLOW-LOC INC – Local incremental flow

• FLOW-RES – Reservoir inflows and releases

• FLOW-HOLDOUT – Reservoir holdouts

• FLOW-NET RE – Net reservoir effects

• STOR-RES – Reservoir storage

The C part for the intermediate time series also indicates whether the time series was forward-routed, back-routed, filled, or manually adjusted. In addition, the C part for the reservoir time series describes whether the time series is an inflow or outflow.

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The F part for the intermediate time series provides notes related to each time series. Observed time series are designated with OBS in the F part. The F part for routed time series describes the reach from which the flow was routed, the routing method used, and whether the time series being routed has been filled. Below are the A, B, C, and F intermediate time series pathname parts for the Ocmulgee-Oconee-Altamaha study basin, followed by a key that provides a description for abbreviations used.

Table 2-5 OOA Intermediate Time Series Pathname Parts

A B C F JACKSON OOA-OCMULG JACKSON-02210500 FLOW-CUM OBS OOA-OCMULG MACON-02213000 FLOW-CUM OBS ACF-FLINT GRIFFIN-022344500 FLOW-CUM OBS OOA-STHRVR MCDONOUGH-02204500 FLOW-CUM OBS OOA-OCMULG JACKSON-JACKSN_R FLOW-NET RE COMP 1DAY OOA-OCMULG JACKSON FLOW-CUM UNREG OOA-OCMULG MACON FLOW-CUM UNREG OOA-OCMULG JACKSON FLOW-CUM BRT MACON UNREG VLK OOA-OCMULG JACKSON FLOW-CUM FILL JKSN-UNREG MCN-UNREG-BRT GRFN-OBS MRG OOA-OCMULG JACKSON FLOW-CUM FILL JKSN-UNREG FILLED MRG 0MINR

OOA-OCMULG JACKSON-02210500 FLOW-CUM UNREG-FILLED-MREG 0MINR MACON OOA-OCMULG MACON-02213000 FLOW-CUM OBS OOA-OCMULG MACON FLOW-CUM OBS UNREG OOA-OCMULG JACKSON FLOW-CUM FILL JKSN-UNREG FILLED MRG 0MINR OOA-OCMULG MACON FLOW-CUM FRT JACKSON FILL VLK OOA-OCMULG MACON FLOW-LOC INC COMP-0ADJ LOC-3 OOA-OCMULG MACON-02213000 FLOW-LOC INC COMP-0ADJ LOC-3 LUMBER OOA-OCMULG LUMBER-02215500 FLOW-CUM OBS OOA-OCMULG MACON-02213000 FLOW-CUM OBS

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Table 2-5 OOA Intermediate Time Series Pathname Parts

A B C F OOA-OCMULG LUMBER FLOW-CUM FRT MACON OBS VLK OOA-OCMULG LUMBER FLOW-LOC INC COMP-0ADJ LOC-3 OOA-OCMULG LUMBER-02215500 FLOW-LOC INC COMP-0ADJ LOC-3 ATHENS OOA-MOCNEE ATHENS-02217500 FLOW-CUM OBS PENFIELD OOA-OCONEE PENFIELD-02218300 FLOW-CUM OBS OOA-OCONEE GREENSBORO- FLOW-CUM OBS 02218500 OOA-MOCNEE ATHENS-02217500 FLOW-CUM OBS OOA-OCONEE PENFIELD FLOW-CUM BRT GREENSBORO OBS STBI OOA-OCONEE PENFIELD FLOW-CUM FILL GREENSBORO BRT MV2 OOA-OCONEE PENFIELD FLOW-CUM FRT ATHENS OBS VLK OOA-OCONEE PENFIELD FLOW-LOC INC COMP-0ADJ LOC-3 OOA-OCONEE PENFIELD-02218300 FLOW-LOC INC COMP-0ADJ LOC-3 MILLEDGE OOA-OCONEE MILLEDGE-02223000 FLOW-CUM OBS OOA-OCONEE PENFIELD-02218300 FLOW-CUM OBS OOA-APALAC BUCKHEAD-02219500 FLOW-CUM OBS OOA-OCONEE MILLEDGE FLOW-CUM + OBS 0MINR MINR OOA-OCONEE PENFIELD FLOW-CUM FILL GREENSBORO BRT MV2 OOA-OCONEE MILLEDGE FLOW-CUM FRT PENFIELD FILL VLK OOA-OCONEE MILLEDGE FLOW-LOC INC COMP-0ADJ LOC-3 OOA-OCONEE MILLEDGE-02223000 FLOW-LOC INC COMP-0ADJ LOC-3 DUBLIN OOA-OCONEE DUBLIN-02223500 FLOW-CUM OBS OOA-OCONEE MILLEDGE-02223000 FLOW-CUM OBS OOA-OCONEE DUBLIN FLOW-CUM FRT MILLEDGE OBS VLK OOA-OCONEE DUBLIN FLOW-LOC INC COMP-0ADJ LOC-3 OOA-OCONEE DUBLIN-02223500 FLOW-LOC INC COMP-0ADJ LOC-3

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Table 2-5 OOA Intermediate Time Series Pathname Parts

A B C F VERNON OOA-OCONEE VERNON-02224500 FLOW-CUM OBS OOA-OCONE DUBLIN-02223500 FLOW-CUM OBS OOA-OCONE VERNON FLOW-CUM FILL DUBLIN FRT MV2 OOA-OCONE VERNON FLOW-CUM FRT DUBLIN OBS VLK OOA-OCONEE VERNON FLOW-LOC INC COMP-0ADJ LOC-3 OOA-OCONEE VERNON-02224500 FLOW-LOC INC COMP-0ADJ LOC-3 BAXLEY OOA-ALTAMA BAXLEY-02225000 FLOW-CUM OBS OOA-OCMULG LUMBER-02215500 FLOW-CUM OBS OOA-ALTAMA DOCTOWN-02226000 FLOW-CUM OBS OOA-ALTAMA BAXLEY FLOW-CUM BRT DOCTOWN OBS VLK OOA-ALTAMA BAXLEY FLOW-CUM FRT LUMBER OBS VLK OOA-ALTAMA BAXLEY FLOW-CUM FILL LMBR-FRT DCTWN-BRT MRG OOA-OCONE VERNON FLOW-CUM FILL DUBLIN FRT MV2 OOA-OCONEE BAXLEY FLOW-CUM FRT VERNON FILL VLK OOA-ALTAMA BAXLEY FLOW-CUM SUM LUMBER OBS VLK+VERNON FILL VLK OOA-ALTAMA BAXLEY FLOW-LOC INC COMP-0ADJ LOC-3 OOA-ALTAMA BAXLEY-02225000 FLOW-LOC INC COMP-0ADJ LOC-3 REIDS OOA-OHOOP REIDS-02225500 FLOW-CUM OBS DOCTOWN OOA-ALTAMA DOCTOWN-02226000 FLOW-CUM OBS OOA-OHOOP REIDS-02225500 FLOW-CUM OBS OOA-ALTAMA DOCTOWN FLOW-CUM FRT BAXLEY FILL VLK OOA-ALTAMA DOCTOWN FLOW-CUM FRT REIDS OBS VLK OOA-ALTAMA DOCTOWN FLOW-CUM SUM BAXLEY FILL VLK+REIDS OBS VLK OOA-ALTAMA DOCTOWN FLOW-LOC INC COMP-0ADJ LOC-3 OOA-ALTAMA DOCTOWN-02226000 FLOW-LOC INC COMP-0ADJ LOC-3

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Table 2-6 Abbreviation Key

Abbreviation Definition 0ADJ Zero adjusted 0ADJ- LOC-3 Zero adjusted by 3 days on either side of negative value ADJ Adjusted AVG Average BRT Back-routed CFS Cubic feet per second CUM Cumulative FILL Filled FRT Forward-routed or downstream-routed HOLDOUT Reservoir holdouts IN Inflow INC Incremental INTERP Interpolated LOC Local LOW Low flows LRG Linear regression. Ordinary least squares. MANADJ Manual adjust MINR Minimum reservoir releases MRG Multiple linear regression MV2 MOVE2 NET RE Net reservoir effects OBS Observed OUT Outflow PER1 Period one PER2 Period two REV Revised SCL Scaled SMT Smoothed STBI Shift time by interval STOR-RES Reservoir storage

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Table 2-6 Abbreviation Key

Abbreviation Definition SUM Summation TVA Tennessee Valley Authority UNREG Unregulated USACE U.S. Army Corps of Engineers VLK Variable lag and k

The C parts in the Study Basin-UIF.dss files are one of three main categories:

1. FLOW-DIV NET (DIV stands for diversion) is the summed water use time series by reach for each type (industrial, municipal, thermal, agricultural, groundwater).

2. FLOW-LOC INC (LOC INC stands for local incremental) is the local unimpaired time series or the local observed time series.

3. FLOW DIV NET, FLOW EVAPNET, FLOW HOLDOUT, and FLOW-NET RE are all time series related to reservoirs and reservoir effects.

The unimpaired flow F parts are designated with UNIMP for the raw unimpaired flow. For the adjustments made to remove negatives from the unimpaired flows (described later in this report), an abbreviation for the method of adjustment follows UNIMP in the F part.

2.3 Reservoir Effects Calculation

Reservoirs impact the natural streamflow by (1) storing and releasing water from storage and by (2) changing the runoff characteristics over the reservoir surface area, resulting in evaporation losses from the reservoir surface area and increased runoff from precipitation falling on the reservoir surface rather than the land. To derive unimpaired flows, effects of reservoir regulation must be removed from raw local incremental flows (i.e., filled/observed cumulative flows at the downstream node less routed [to the downstream node] cumulative filled/observed flows at the upstream node). Two major reservoir influences on streamflow are (1) holdouts (regulation of downstream flows from controlled or uncontrolled reservoir releases), and (2) net evaporation (evaporation and precipitation on the reservoir surface after construction and runoff from the land surface area inundated by the reservoir prior to its construction). In general, reservoir effects are computed for storage reservoirs (federal

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan and private power), but are ignored for small run-of-river projects where evaporation losses are small and holdouts are negligible.

2.3.1 Holdouts

Holdout flows are daily change in reservoir storage, such that when added to reservoir outflows (if known) produce cumulative reservoir inflows in accordance with the basic continuity relationship:

I – O = ∆S

Where:

I = Reservoir inflow O = Reservoir outflow (release) ∆S = Holdout (flow units)

Holdouts may be computed whether or not reservoir releases are known. When they are known, holdouts may be used to calculate reservoir inflows and unregulated cumulative reservoir inflows (i.e., O + ∆S). The sign convention adopted for this purpose considers holdouts ( I > O ) as positive and releases from storage ( I < O ) as negative.

The reservoir elevation and inflow time series used in holdout derivation were plotted and inspected for erroneous values. All such values were corrected by examining the trend of adjacent data and adjusting the erroneous values intuitively to be in line with the observed trend.

2.3.2 Net Evaporation

Net evaporation reservoir effects consist of the following:

• Post-development evaporation minus precipitation on the reservoir surface (1)

• Pre-development runoff from the land surface area currently inundated by the reservoir (i.e., runoff that would have occurred had the reservoir not been constructed) (2)

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Net evaporation effects reflect the differential pre- and post-reservoir development conditions, or (1) – (2) above.

Calculation of net evaporation time series flows applied evaporation and precipitation time series data previously described (Section 2.2.5) to post- and pre-reservoir runoff coefficients, computed as ratios of annual precipitation to runoff at representative unregulated stream gages at various locations in Georgia, shown on Figure 2-10.

For the post-reservoir condition, runoff coefficients are assumed to be unity (100 percent runoff), and the resulting net evaporation relationship embodied in the reservoir effects DSS macros is as follows:

NEVAP (cfs) = [(EV (ft / day) – P (ft / day)) * A (ac) + ROC * P (ft / day) * A (ac)] * 0.504 (dsf / ac-ft)

2.3.3 Net Reservoir Effects

Net reservoir effects are aggregate holdouts and net evaporation as previously described. However, these are applied at separate stages in development of unimpaired flows, as follows:

• Holdouts for reservoirs located at the outlet of a LDA are applied during filling and routing for determination of local incremental flows.

• Holdouts for intermediate reservoirs between nodes are applied in the local incremental unimpaired flow calculation.

• Net evaporation is applied as the final reservoir effect in conjunction with net water use in the determination of local incremental unimpaired flows.

2.4 Flow Record Filling

Continuous streamflow records are required for every node from January 1, 1939 through December 31, 2007 as a starting point from which unimpaired flows are developed, with the exception of the ACT and ACF basins, for which existing unimpaired flows were available from January 1, 1939 through December 31, 2001 for most nodes. Nodes for which unimpaired flows were developed were generally placed at long-term stream gaging locations. Nevertheless, many of the node locations do not have continuous records of streamflow over this POR. Missing streamflow records

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan were estimated based on a variety of techniques to produce continuous observed flow records at every location.

When performing streamflow filling at each location, the following basic criteria were followed. All filling options were considered independently for each case.

• In general, when filling a downstream gage with an upstream time series, the upstream gage was first routed downstream using a variable Lag-K model. Negative variable lags were considered when filling an upstream gage with a downstream time series. If using tributary gages, lagging the filling gages forward or backward in time was considered to better align the filling gage with the gage being filled.

• For filling of locations found below reservoirs or farther downstream, alternate methods were investigated to fill the local flow instead of the total flow at the gage.

• Both multiple linear regression and single regression were explored with reasonable combinations of nearby gages that appeared hydrologically significant.

• An F-test was used to decide if the use of multiple linear regression was merited and how many gages to include. For locations where multiple linear regression was advantageous, the DSSMATH program was used to determine the multiple linear regression coefficients and the resulting filled time series.

• If a single variable was used to develop the regression relationship, the preference was to use monthly Maintenance of Variance Extension Type 2 (MOVE2) relationships. The resulting time series was then investigated to determine if major discontinuities were found at the month boundaries. If discontinuities were found, an annual MOVE2 relationship was used instead. Monthly relationships were not considered for cases using multiple linear regression because of limitations in the DSSMATH utility; alternate methods of performing a filling using monthly multiple linear regression relationships were not considered.

• In some specific instances for which no gage records exist (e.g., Savannah), mean flow or drainage area ratios were used.

• The time series resulting from filling were examined for negative flows that resulted from the regression relationship. Generally, when small numbers of small negative values were found in a time series, those flows were set to zero, and flow volumes

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were adjusted accordingly. Time series that resulted in larger negative values or extended periods of negatives were corrected with other methods, including annual and POR flow volume adjustments.

• In cases where only a few days of data were missing in a time series, missing values were filled using linear interpolation between data points on either end of the missing period.

2.4.1 Statistical Methods

The appropriate filling method for a particular location was determined based on the availability of data for surrounding gages and the strength of regression coefficients. With weak correlations, alternate approaches were investigated as subsequently described.

The primary method for filling missing time series data involved development of a regression relationship using the MOVE2 statistical method. 2 MOVE2 differs from traditional least-squares regression in its ability to preserve the mean and standard deviation of the observed data at the analyzed location and to use information from the reference (independent) station for the filling period. MOVE2 may be used to derive linear relationships.

For each analyzed location, the strength of the regression relationship was evaluated by considering the correlation coefficient, visual scatter plots of the two gages, physical location of gages, length of overlapping record, and potential benefits or limitations of other record-filling options. For gages located on the same stream, the independent time series was routed up or downstream as previously described. Monthly regression relationships were developed when possible, although the strength of the monthly relationships and length of overlapping data determined whether monthly or annual regression relationships were utilized. In each case, scatter plots of independent and dependent gage time series data permitted visual assessment of the validity of the relationship. A linear regression equation should normally represent the relationship between the dependent and independent time series. In some cases, information from multiple stream gages was used to estimate missing discharge values at a location.

2 Hirsch, R.M., 1982. A comparison of four streamflow record extension techniques: Water Resources Research , v. 18, no. 4, p. 1081-1088.

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Multiple gages may be summed or weighted based on expected relationships, or multiple linear regression analysis may be performed to determine the optimal combination of time series to use for filling.

One example of utilizing multiple gages to fill data is a location with an incomplete record situated between upstream and downstream gages with complete records. In this case, the intermediate drainage areas are used to weight the data in the regression relationship.

Selection of filling methodology considers hydraulic connectivity as well as physical and hydrologic similarities between watersheds. In cases where no logical combination of gages based on physical similarities is apparent, however, multiple linear regression analysis was performed to weight gages appropriately. Once the appropriate influencing gages and weights were determined, the MOVE2 statistical method generally worked well in the final analysis.

In some cases, one gage may provide a superior regression relationship for high-flow months, and another gage may provide the same for low-flow months. Depending on the consistency and physical explanation for this effect, different gages may be used to fill different months of a data record. This method was considered; however, preference was given to utilization of a single gage or combination of gages to fill a given data period over a flow-related conditional approach to fill specific months.

Lastly, because of differences in available periods of record between gages, it was sometimes necessary to use one gage with a superior regression relationship to fill missing data for the period corresponding to its data record and one or more additional gages with less preferable correlations to fill the remainder of the period of record.

2.4.2 Mean Flow Ratio

The ratio of observed flows for overlapping months provides a useful means to fill a missing period when two gages do not correlate well with each other. One example would involve filling missing reservoir inflows using an upstream gage. Computed reservoir inflow time series tend to be noisy and may not correlate well with an upstream gage. The inflow time series could be filled by multiplying the observed upstream flows (routed to the reservoir) by the ratio of the mean monthly discharge of observed reservoir inflow and upstream gage flow. This method preserves flow volume of the downstream gage with the more natural temporal patterns of the upstream gage.

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2.4.3 Drainage Area Ratio

If there is little or no overlapping period of record between a node and a gage, then a statistically significant regression relationship cannot be developed. In this case, the independent and dependent time series can be related based on physical basin characteristics. The simplest method for estimating ungaged flow is the drainage-area ratio method, in which the independent time series is multiplied by the ratio of contributing drainage areas of the dependent and independent gages. This method is appropriate when the ungaged site is on the same stream as the gaged site and the ratio of the drainage areas at the two sites is between 0.5 and 1.5.

2.4.4 Hydrologic Modeling

During the Plan of Study, hydrologic modeling was identified as a potential option for streamflow filling for cases for which more traditional filling options are limited. SERFC and LMRFC maintain Sacramento Soil Moisture Accounting (SAC-SMA) hydrologic models for their real-time forecast systems. These models use MAP over a sub-basin and determine the streamflow produced by the basin as a result of the MAP input and dynamic soil moisture conditions. The existing NWS hydrologic models may be used to fill missing streamflow data for a basin by running historical MAP time series through the models to produce a synthetic streamflow time series. The forecast centers maintain historical MAP time series that could be used for this purpose.

The use of hydrologic modeling was investigated for a single location (Chickamauga Creek in the TN study basin). At this location, no upstream or downstream gages were available for filling purposes. The best regression-based filling option was to use multiple linear regression with the Sesquatchie and Summerville gages for one period and monthly MOVE2 relationships with Summerville for a second period. The independent gages are located in nearby river basins (see Figure 8-2). The multiple linear regression yielded fairly good results (R² = 0.80 for the multiple linear regression); the monthly MOVE2 relationships were not as strong (R² = 0.45 – 0.79). The hydrologic modeling yielded superior correlations over the observed data period both statistically (R² = 0.91) and visually.

The results were presented to and discussed with Georgia EPD staff to determine if hydrologic modeling should be utilized for filling of this gage record and for others at other locations. During these discussions, it was decided that although the modeling yielded superior results, the additional complexity, difficulty for others to reproduce the results, and challenges with future streamflow extension did not warrant the

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan incremental increase in accuracy that would be gained through the application of this option.

2.5 Local Incremental Flow Computation

Application of the previously described techniques, singly or in combination, produced complete time series with no missing data of cumulative flows for each of the nodes and complete time series of both inflow and outflow over the required period of record for reservoirs. The next step in the process was to calculate local incremental flows from the computed total flows in each basin. For headwater nodes, local incremental flows are the same as total flows. For downstream nodes, local incremental flows were computed using TSTool for each basin with the following steps:

• Read upstream filled time series.

• Route the upstream time series to the downstream location.

• Subtract the routed flows from the total filled time series at the downstream location. The result is the local incremental flow for the downstream point.

For reservoirs, the filled reservoir inflow time series was used in the local incremental flow calculation for the reservoir node. The reservoir outflow time series was used in the local incremental flow calculation for the node below the reservoir.

The local incremental flows do not yet represent unimpaired flows. Water withdrawals, agricultural diversions, return flows, and other losses or gains constitute final adjustments to local incremental flows resulting in unimpaired flows.

For some basins, negative flows were computed when the routed flows were subtracted from the total downstream flows. These values resulted from a variety of causes, including routing errors, errors in observed flow values, small local flows compared to the total flow, and water use or losses to groundwater.

The negative flows were dealt with differently in different locations. Generally, negatives resulting from routing errors or minor errors in recorded flows could be effectively adjusted for using the AdjustExtremes command in TSTool over a limited time window. This piece of the negative flow adjustment was completed at the local incremental flow stage of the computations.

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AdjustExtremes is not an appropriate option for long, continuous periods of negative flows, which could be the result of natural stream losses, water use, or other computational errors. These longer periods of negatives were adjusted at the final stage of unimpaired flow development.

2.6 Local Incremental Unimpaired Flow Computation

The final stage of local incremental unimpaired flow determination involves aggregation and removal of remaining impairments (human influences) – principally reservoir effects and net water uses – from local incremental flows.

2.6.1 Aggregation of Impairments

The sign convention adopted in calculation of reservoir effects and net water uses removes these impairments by summation and addition to local incremental flows. The following impairments are included:

• Pre- and post-reservoir development is merged in the reservoir effects macros to produce a continuous 1939 to 2007 record of holdouts, net evaporation, and net reservoir effects. Because reservoir holdouts are added to observed flows to remove effects of reservoir releases for filling, routing, and determination of local incremental flows, generally only remaining net evaporation effects are restored (added) at the unimpaired flow calculation stage in reaches affected by reservoirs.

• Net consumptive water use in all categories considered in this study (municipal, industrial, thermal, agricultural, and groundwater effects on surface water) are summed and restored (added) to local incremental flows for all reaches.

Calculation of local incremental unimpaired flows is therefore described by the following equation:

UIF = LIF + NETEVAP + NET WU M+I+T+A+GW (cfs)

2.6.2 Negative Local Unimpaired Flow Adjustments

A no-negative local incremental unimpaired flow policy was adopted for this study in consideration of potential application to water availability assessments subject to various minimum flow constraints, including annual or monthly 10-year, seven-day low flow. Moreover, many reservoir system operational models do not allow for negative

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan local incremental flows; the utility of unimpaired flows computed in this study is maximized by systematic “intelligent” removal of negative values with minimal alteration to surrounding non-negative values, as opposed to cruder methods employed by operational models.

While negative local incremental flows were removed to the maximum extent possible by refinements to reservoir holdouts, routing and filling procedures, and short-duration (three- to five-day) smoothing and averaging, some residual negatives remained at the unimpaired flow determination stage. To remove these, three approaches were employed, listed as follows in order of minimum number of adjacent time periods adjusted:

• The AdjustExtreme TSTool procedure, which averages values on either side of the negative value for as many days as necessary to produce a non-negative result. This method works best with intermittent as opposed to continuous periods of negative flows. Where extended periods of negative flows occur, the AdjustExtreme procedure produces multi-month periods of constant low flow.

• Annual adjustment – A DSSMATH procedure that increases all negative flows to zero and reduces all positive values by a factor equal to the ratio of the original (with negatives) annual average flow to the adjusted (no negatives) annual average flow.

• POR adjustment – Same as annual adjustment with the reduction factor computed using 1939 to 2007 POR average flow ratios.

2.6.3 Selection of Final Local Unimpaired Flow Time Series

Final local unimpaired flow selection is predicated on the basic requirement for no residual negative flows in the following order of preference:

• Unadjusted unimpaired flow (F = UNIMP)

• TSTool AdjustExtreme method if the initial time series did not have extended periods of negative flows that when adjusted result in periods longer than those produced by the annual or POR adjustment (F = UNIMP–0ADJ LOC)

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

• DSSMATH annual adjustment (F = UNIMP–0ADJ ANNUAL)

• DSSMATH POR adjustment (F = UNIMP–0ADJ POR)

Final local unimpaired flow time series selection is denoted by an asterisk at the end of the F pathname denoting the adjustment required (e.g., F= UNIMP–0ADJ ANNUAL*).

2.7 Cumulative Unimpaired Flow Computation

Following Georgia EPD approval of local unimpaired flow data documented in this report, partial and full cumulative unimpaired flow time series data will be developed by aggregation and routing of applicable upstream local, partial cumulative, and cumulative unimpaired flows to downstream nodes.

2.8 Merger of Existing ACT and ACF Incremental Unimpaired Flows

The development of ACT and ACF unimpaired flows required the 2002 to 2007 record extension to be merged with the existing 1939 to 2001 record developed for reservoir system operational models used in connection with interstate water allocation negotiations, litigation, and evaluation of USACE ACF water control policies. For reaches where the LDA for existing and extended incremental unimpaired flows corresponded, no further adjustments were necessary. The record extension was simply appended to the existing record. In these cases, the B part pathnames reflect nodes adopted for the current study rather than operational model control points.

For reaches where the LDAs do not correspond, existing local unimpaired flows either had to be aggregated or disaggregated to produce a consistent 1939 to 2007 local unimpaired flow record.

2.9 Quality Control of Data

Because primary quality control was performed at each stage of a basin’s unimpaired flow development (water use data, reservoir effects, and filling/routing), as described in the above sections, the final stage of quality control relied on (1) visual inspection and comparison of local unimpaired flow time series plots, (2) comparison of average local unimpaired flow volumes, and (3) consistency plots, in which individual nodes are grouped and differences between accumulated unimpaired flow for individual nodes and average accumulated unimpaired flow for the group are compared.

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As an example for consistency plot applications, the procedure revealed some problems in distribution of Russell and Thurmond computed unimpaired flows after 1984 – about the time pumpback operations at Russell began. Figure 2-11 shows a sharp drop in Russell local inflows and a corresponding, albeit more gradual, increase in Thurmond local inflows post-1984. Careful reexamination and reinterpretation of inflow, outflow, and pumping data provided by the Savannah District of USACE showed no apparent cause of the consistency error. Moreover, Figure 2-11 shows the sum of Russell and Thurmond inflows to be uniformly consistent before and after 1984. Consequently, it appears that there is a high degree of uncertainty in the Russell releases and pumpback flows, but that continuity is preserved between the drawdown of Thurmond’s storage and the refill of Russell’s. Because neither RBR_R nor THRMND_R are planning nodes, the distribution of local unimpaired flows between the projects does not present a major problem for water availability analysis. However, the distributional effects on the accuracy of reservoir system operational models will be much more pronounced, and as such the causes of the inconsistencies should be identified and the local incremental flows (and resulting unimpaired flows) corrected, should these data be applied to this purpose. Figure 2-12 shows the consistency plot of the corrected data. The uniformity of the plots of the time series (i.e., no breaks in the trend like the sharp drop in Russell seen in Figure 2-11) is a strong indication of the appropriateness of the corrected data.

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Figure 2-11 Bell, Hartwell, Russell, Thurmond, and Russell+Thurmond Consistency Plots – Before Data Correction

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Figure 2-12 Bell, Hartwell, Russell, Thurmond, and Russell+Thurmond Consistency Plots – After Data Correction

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3. Apalachicola-Chattahoochee-Flint (ACF) River Basin

3.1 ACF Basin Description

The ACF basin drains an area of 19,600 square miles in northern and western Georgia, southeastern Alabama, and a portion of northwestern Florida. The Apalachicola River basin is mostly in the state of Florida with one major tributary, the Chipola River, extending into Alabama. The Chattahoochee River basin extends from the headwaters of Lake Lanier to its confluence with the Flint River basin in Lake Seminole. The Flint River basin is entirely within the state of Georgia.

Chattahoochee River flows are highly regulated by a series of federal storage reservoirs and several pondage and run-of-river private power reservoirs. Federal reservoirs operate for multiple purposes, including flood control, water supply, hydropower, navigation, water quality, recreation, and aquatic habitat and species protection. The Flint River is largely unregulated and has no federal or private power storage reservoirs. The most downstream ACF planning node for purposes of this study is the Chattahoochee gage, which is in Florida just downstream of Woodruff Dam. The four federal reservoirs (Lanier [BUFORD_R], West Point [WESTPT_R], W.F. George [WFG_R], and Woodruff [(WOODRF_R]) comprise basic or planning nodes for surface water availability assessment purposes, whereas the smaller private power reservoirs are not collocated with basic or planning nodes. The ACF study basin map showing node locations and LDAs for each node is shown on Figure 3-1.

3.2 Hydrological Data

3.2.1 Existing Unimpaired Flows

Unique to the ACF and ACT study basins is the existence of daily unimpaired flow time series data developed during the ACF and ACT Comprehensive Studies for the 1939 to 1993 period of record. These data were later extended through 2001. Georgia EPD has elected to retain these data for the current study and to extend it from 2002 through 2007 to match the 1939 to 2007 POR adopted statewide. Therefore, for all nodes coinciding with ACF Basin Comprehensive Study control points, only the 2002 to 2007 record extension was required. The Iron City and Milford nodes, however, located on tributaries to the Flint River, required generation of a complete 1939 to 2007 time series. Existing and extended unimpaired flow time series data were subsequently merged with adjustments necessitated by differences in LDAs between the current

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Figure 3-1 ACF Study Basin Basic and Planning Nodes

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The existing (1939 to 2001) unimpaired flow data are contained in the ACFCUM_8.DSS file developed by the USACE Mobile District in September 2003. These data are derived for all basic and planning nodes subsequently selected for this study and for a significant number of intermediate locations (e.g., Georgia Power reservoirs between West Point Dam and Columbus). Despite intensive data adjustment and smoothing, negative unimpaired local inflows persist at several of these intermediate points. The aggregated unimpaired flows, however, contain a smaller amount of negative flows at basic nodes selected for the current study. The adjustments employed include the negatives of the unsmoothed 2003 District unimpaired flows being processed with the same techniques as this study used for the 2002 to 2007 data.

3.2.2 Streamflow Records

Approximately 170 stream gage stations are located within the ACF basin, of which approximately 25 have continuous data covering most of the 2002 to 2007 period for which unimpaired flows are to be extended; 18 of these cover the entire period. All nodes in the ACT required complete time series for 2002 through 2007, with the exception of IRON_CTY and MILFORD, which required complete time series from 1939 through 2007. Gage locations are shown on Figure 3-2, and PORs for gages used in filling are shown on Figure 3-3.

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Figure 3-2 Nodes and Gages Associated with ACF Study Basin Streamflow Filling

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Figure 3-3 Periods of Record for Gages Associated with ACF Study Basin Streamflow Filling

3.2.3 Reservoir Data

Detailed operational data (pool elevations, releases, and computed inflows) were obtained in electronic form for the four USACE multipurpose reservoirs in the basin (Buford Dam, West Point, W.F. George, and Jim Woodruff). Daily elevation time series data for the Georgia Power pondage and storage reservoirs between West Point and Columbus (Bartletts Ferry, Goat Rock, Oliver, and North Highlands) were also available for the 2002 to 2007 period. Calculation of reservoir inflows and local incremental flows at downstream nodes (where reservoirs are not located at nodes) involves addition of reservoir holdouts (cumulative change in storage reflecting differences in reservoir outflows and inflows) to observed reservoir releases or cumulative downstream flows. Local unimpaired flows further adjust local incremental flows for differential net evaporation (evaporation minus precipitation) falling on the reservoir surface prior to and since reservoir construction. Calculation of holdout and net evaporation flow time series is enabled by application of reservoir elevation time series to elevation-storage and elevation-area curves. These paired physical data were obtained from USACE HEC-5 model input data developed during the ACF Comprehensive Study and from Georgia Power records.

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3.2.4 Climatological Data

Precipitation: Required for determination of reservoir net evaporation effects are NWS SERFC and LMRFC MAP time series for sub-basins throughout the state of Georgia. For the majority of the reservoirs included in the study, MAP time series were available for LDAs upstream of the reservoir. The MAP sub-basins cover an area equal to or smaller than the LDAs. The MAP time series were originally derived using hourly and daily station data downloaded from NCDC and quality controlled to remove outliers and long-term bias from the stations. The NWSRFS MAP processor was used to compute the MAP time series. The processor includes missing data estimation techniques to fill missing precipitation observations prior to MAP computation using the Thiessen polygon weighting scheme. The resulting MAP time series were generated on six-hour time intervals and subsequently aggregated to daily values. Table 3-1 summarizes the MAP time series assigned to each ACF reservoir with the original POR for each.

Table 3-1 ACF Reservoirs Included in the Analysis and Corresponding MAP Time Series

Operated Prior to MAP A_PART B_PART Reservoir 1950? Identifier MAP POR ACF-CHATT BUFORD_R Lake Lanier N CMMG1 1/1950 – 12/1999 ACF-CHATT WESTPT_R West Point Lake N WETG1 1/1950 – 12/1999 ACF-CHATT COLUMBUS- Lake Harding N CLBG1 1/1950 – 12/1999 HARDNG_R ACF-CHATT COLUMBUS- Goat Rock Lake N CMUG1 1/1950 – 12/1999 GOATR_R ACF-CHATT COLUMBUS- Lake Oliver N CMUG1 1/1950 – 12/1999 OLIVER_R ACF-CHATT COLUMBUS- Bibb Pond N CMUG1 1/1950 – 12/1999 BIBB_R ACF-CHATT WFG_R Walter F. George N FOGG1 1/1950 – 12/1999 ACF-CHATT COLUMBIA George W. Andrews N COLA1 1/1950 – 12/2004 ACF- WOODRF_R Lake Seminole N WDRF1 1/1950 – 12/2004 APCOLA

Evaporation: Free water surface evaporation estimation can be problematic because of data quality problems in measured evaporation data. Using quality-controlled pan evaporation and meteorological data, NOAA developed annual and seasonal free water surface evaporation maps for the contiguous United States (NOAA Technical

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Reports NWS 33 and 34, 1982). NWS later digitized these maps and developed monthly free water surface evaporation grids. The monthly evaporation grids present a consistent method to derive average monthly free water surface evaporation at every reservoir. Monthly free water surface evaporation estimates from these grids were compared with free water surface evaporation estimates using long-term, monthly pan evaporation data downloaded from NCDC and an assumed pan coefficient (reported in pan coefficient maps from NOAA Technical Report NWS 34). The distribution of the two free water surface estimates generally agree well for stations with better quality data. Only slight spatial variation in evaporation estimates was observed between the upper, middle, and lower ACF basin reservoirs (north to south).

Georgia EPD staff generated daily PET time series for every reservoir using the Hamon PET option of the WDMUtil program, a utility program associated with the U.S. EPA HSPF. The Hamon PET calculation requires time series of daily maximum and minimum temperatures and latitude as inputs. For each reservoir, the daily maximum and minimum temperature time series were estimated from surrounding stations. Daily PET estimates were generated for 11 locations with some reservoirs grouped together because of their proximity. Precipitation and evaporation time series data used in development of ACF basin unimpaired flows are applicable only to reservoirs and contained in ACFRE.DSS ; sample pathname listings are shown in Table 3-2.

Table 3-2 Sample ACF Precipitation and Evaporation Time Series Data HECDSS Condensed Catalog Listing (from ACFRE.DSS , 2009-06-23 version) T1 ACF-APCOLA WOODRF_R EVAP ADJ HAMON 1DAY 01JAN1957 - 01JAN2007 T2316 ------PRECIP SERFC MAP 1DAY 01JAN1957 - 01JAN2007 T2847 ACF-CHATT BUFORD_R EVAP ADJ HAMON 1DAY 01JAN1959 - 01JAN2007 T2316 ------PRECIP SERFC MAP 1DAY 01JAN1959 - 01JAN2007 T6495 - - - - - COLUMBUS-HARDNG_R EVAP ADJ HAMON 1DAY 01JAN2000 - 01JAN2007 T6495 - - - - - COLUMBUS-HARDNG_R PRECIP SERFC MAP 1DAY 01JAN2000 - 01JAN2007 T2847 ACF-CHATT WESTPT_R EVAP ADJ HAMON 1DAY 01JAN1975 - 01JAN2007 T2316 ------PRECIP SERFC MAP 1DAY 01JAN1975 - 01JAN2007

3.3 Water Use Data

The Water Use Data Inventory Report documents present (2002 to 2007) and, for the IRON_CTY and MILFORD reaches, hindcasted (1939 to 2001) consumptive water uses within the ACF basin of the following types:

• Municipal and industrial water use (withdrawals, discharges/returns) in Georgia and net consumptive uses by Alabama in the Chattahoochee basin

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• Thermal power water use (withdrawals, discharges/returns, and net consumption) in Georgia

• Estimated agricultural irrigation water use in Georgia (see Appendix B7)

• Groundwater use and effects on surface water withdrawals for all use categories within Subarea 4 of the upper Floridan Aquifer (principally ACF-FLINT)

Net uses of each type are aggregated by reach and summed to produce an aggregate water demand for each reach. Reach aggregate water use is added to local incremental flows and combined with reservoir effects as applicable (both subsequently described) to produce local incremental unimpaired flows. Sample HECDSS pathnames for ACF water uses are shown in Table 3-3. Note that there are no reaches in the ACF basin with all five use categories listed above.

No modifications or adjustments were made to reach aggregate water uses built into the existing ACF unimpaired flow time series contained in ACFCUM_8.DSS for the 2002 to 2007 record extension.

Table 3-3 Sample ACF Aggregate Reach Water Use HECDSS Condensed Catalog Listings (from ACF-unimpaired flow.DSS , 2009-06-29 version) T1 ACF-APCOLA WOODRF_R FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN2001 - 01JAN2007 T8 ------COMP-REACH-A 1DAY 01JAN2001 - 01JAN2007 T15 ------COMP-REACH-G 1DAY 01JAN2001 - 01JAN2007 T22 ------COMP-REACH-I 1DAY 01JAN2001 - 01JAN2007 T29 ------COMP-REACH-M 1DAY 01JAN2001 - 01JAN2007 T1332 ACF-CHATT COLUMBUS FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN2001 - 01JAN2007 T1339 ------COMP-REACH-A 1DAY 01JAN2001 - 01JAN2007 T1346 ------COMP-REACH-I 1DAY 01JAN2001 - 01JAN2007 T1353 ------COMP-REACH-M 1DAY 01JAN2001 - 01JAN2007 T1360 ------COMP-REACH-T 1DAY 01JAN2001 - 01JAN2007 T4760 ACF-ICHACR MILFORD FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T4829 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T4898 ------COMP-REACH-G 1DAY 01JAN1939 - 01JAN2007 T4967 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T5036 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007

3.4 Reservoir Effects

For purposes of ACF basin unimpaired flow development, reservoir effects are computed for storage reservoirs (federal and private power) but are ignored for small run-of-river projects where evaporation losses are small and holdouts negligible. However, the evaporation effects of the Georgia Power run-of-river reservoirs are used in unimpaired flow development. Figure 3-4 presents the locations of ACF reservoirs for which reservoir effects were calculated.

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Figure 3-4 ACF Reservoir Location Map

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3.4.1 Holdouts

USACE maintains historical reservoir elevation, release, and computed inflow time series data for its reservoirs in the ACF basin. These data permit visual screening, verification, and reconciliation of USACE-computed inflows and holdout-adjusted inflows, assuming USACE releases data or downstream gage data control. Inflow verification was not performed on the private power (Georgia Power) ACF reservoirs because none were collocated with basic or planning nodes. For the Columbus reach, cumulative observed flows were adjusted for aggregate Georgia Power reservoir holdouts to determine unregulated cumulative flows.

Various smoothing adjustments were applied to reservoir holdouts, but only the COMP 1DAY (or COMP 1DAY-REV, where applicable) holdout flow time series were applied to derivation of unregulated inflows. COMP 1DAY-REV reflects revisions to observed reservoir elevation time series based on visual screening of anomalous data, illustrated on Figure 3-5. These adjustments significantly reduced outlier holdouts (i.e., one-day changes from large negative to large positive values inconsistent with reservoir operational policy).

3.4.2 Net Evaporation

Calculation of net evaporation in the ACF basin applied evaporation and precipitation time series data previously described (Section 3.2.4) to post- and pre-reservoir runoff coefficients, computed for the ACF basin as ratios of annual precipitation to runoff at representative unregulated stream gages at various locations in Georgia, shown on Figure 3-6.

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Figure 3-5 BUFORD_R Visual Elevation Screening Example

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Figure 3-6 Georgia Representative Unregulated Flow Gaging Stations and Average Annual Runoff Coefficients

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Pre-development runoff coefficients applied to ACF reservoirs are listed in Table 3-4. For the post-reservoir condition, runoff coefficients are assumed to be 100 percent runoff. The resulting net evaporation relationship embodied in the reservoir effects DSS macros is as follows:

NEVAP (cfs) = [(EV (ft / day) – P (ft / day))* A (ac) + ROC * P (ft / day) * A (ac)] * 0.504 (dsf / ac-ft)

Table 3-4 ACF Reservoir Pre-Development Runoff Coefficients

A_Part B_Part Reservoir Name Runoff Coefficient ACF-CHATT BUFORD_R Lake Lanier 0.40 ACF-CHATT WESTPT_R West Point Lake 0.33 COLUMBUS- ACF-CHATT HARDNG_R Lake Harding 0.33 COLUMBUS- ACF-CHATT GOATR_R Goat Rock Lake 0.33 COLUMBUS- ACF-CHATT OLIVER_R Lake Oliver 0.33 ACF-CHATT COLUMBUS-BIBB_R Bibb Pond 0.33 George W. ACF-CHATT COLUMBIA Andrews Lake 0.31 ACF-APCOLA WOODRF_R Lake Seminole 0.28

3.4.3 Net Reservoir Effects

Net reservoir effects are aggregate holdouts and net evaporation as previously described. However, these are applied at separate stages in development of unimpaired flows, as follows:

• Holdouts are applied during filling and routing for determination of local incremental flows.

• Net evaporation is applied as the remaining reservoir effect, in conjunction with net water use, in the determination of local incremental unimpaired flows.

A sample reservoir effects condensed catalog listing for BUFORD_R is provided in Table 3-5.

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Table 3-5 Sample BUFORD_R Reservoir Effects HECDSS Condensed Catalog Listing (from ACFRE.DSS , 2009-06-23 version)

3.5 Streamflow Filling, Routing, and Reservoir Inflows

Unimpaired flow development removes human impacts – net water uses and reservoir regulation (holdouts and net evaporation) – from observed streamflows or computed gross reservoir inflows. All nodes in the ACF basin required complete time series for 2002 through 2007, and the IRON_CITY and MILFORD nodes required complete time series from 1939 through 2007.

3.5.1 Methods Summary

Table 3-6 lists streamflow filling periods and methods for the ACF study basin. Many streamflow records were complete over the required periods of analysis and consequently required no filling.

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Table 3-6 ACF Streamflow Filling and Routing Summary

Filled Streamflow or Node Reservoir Inflow Period Filling Method/Gage(s) Used for Filling BUFORD_R 1/1/02 – 12/31/07 Inflow mass balance COLUMBUS 1/18/02 – 12/31/07 Fill using Columbus_new directly IRON_CITY 5/1/71 – 12/19/76 Multiple linear regression (Newton, Milford) 10/1/78 – 6/6/82 Multiple linear regression (Newton, Milford) MILFORD 1/1/39 – 9/1/39 Multiple linear regression (back-routed Bainbridge, Iron City, Newton) WESTPT_R 1/1/02 – 12/31/07 Inflow: mass balance WFG_R 1/1/02 – 12/31/07 Inflow: mass balance WOODRF_R 1/1/02 – 12/1/07 Inflow: mass balance

Specific filling and holdout calculations are subsequently described.

3.5.2 Buford Dam (BUFORD_R)

Buford Dam inflows were computed by mass balance of observed outflows and changes in reservoir storage (holdouts). Outflows were based on observed flows at the BUFORD_R gage just downstream of the dam, and added to daily change in reservoir storage (holdouts positive, storage releases negative). Large negative inflows (i.e., larger than net evaporation) potentially associated with erroneous reservoir elevation readings were visually screened and removed, and remaining large negative values were removed using the AdjustExtreme command in TSTool. No filling of Buford Dam inflows or outflows was required.

3.5.3 Columbus (COLUMBUS)

A single period of missing streamflow data for Columbus extended from 1/18/2002 – 12/31/2007, due to relocation of the gage. Missing records were filled using the Columbus_new #02341505 gage located downstream of the original gage.

3.5.4 Iron City (IRON_CTY)

The Iron City streamflow record contained missing data for two periods (5/1/1971 – 12/19/1976 and 10/1/1978 – 6/6/1982). The missing local flow was filled using nearby tributary gages. The following specific steps were completed:

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• Newton and Milford gage records were used to determine a multiple linear regression relationship with Iron City. In order to run the multiple linear regression, zero flows in the observed Iron City record were replaced with 0.0001 cfs using the ReplaceValue command in TSTool prior to computing the regression relationship.

• This multiple linear regression relationship was used to fill both missing data periods at Iron City. Table 3-7 presents the resulting regression equation and correlation from the filling. Negative values and values of 0.0001 set in step 1 were replaced with zeros in TSTool.

Table 3-7 MILFORD Multiple Linear Regression Parameters

Y = A + BX1 + CX2 Period A B C R2 Annual –180.4 0.03 0.64 0.709

3.5.5 Milford (MILFORD)

The Milford streamflow record contained missing data for one period (1/1/1939 – 9/30/1939). Missing flow was filled by back-routing and multiple linear regression using nearby tributary gages, described as follows:

• Downstream Bainbridge flow was back-routed upstream to the Milford gage.

• Back-routed Bainbridge flow, Iron City, and Newton gage records were used to develop a least-squares multiple linear regression relationship with Milford. Regression coefficients are listed in Table 3-8.

• The least-squares multiple regression equation was used to fill the missing data periods at Milford.

Table 3-8 MILFORD Regression Coefficients

Y = A + BX1 + CX2 +DX3 Period A B C D R2 Annual 60.9 0.48 0.08 –0.031 0.773

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3.5.6 West Point Reservoir (WESTPT_R)

West Point Reservoir inflows were computed by mass balance of observed outflows and changes in reservoir storage (holdouts). Outflows were based on observed flows at the WESTPT_R gage just downstream of the dam, and added to daily change in reservoir storage. Large negative inflows (in excess of net evaporation) potentially associated with erroneous reservoir elevation readings were visually screened and removed, and remaining large negative values removed using the AdjustExtreme command in TSTool. No filling of West Point inflows or outflows was required.

3.5.7 Walter F. George Reservoir (WFG_R)

Walter F. George Reservoir inflows were computed by mass balance of USACE observed outflows (daily releases) and changes in reservoir storage (holdouts). Large negative inflows (in excess of net evaporation) potentially associated with erroneous reservoir elevation readings were visually screened and removed, and remaining large negative values were removed using the AdjustExtreme command in TSTool. No filling of W. F. George inflows or outflows was required.

3.5.8 Jim Woodruff Reservoir (WOODRF_R)

Woodruff Reservoir inflows were computed by mass balance of observed outflows and changes in reservoir storage (holdouts). Outflows were based on observed flows at the WOODRF_R gage (also known as the Chattahoochee gage) just downstream of the dam, and added to daily change in reservoir storage. Large negative inflows (in excess of net evaporation) potentially associated with erroneous reservoir elevation readings were visually screened and removed, and remaining large negative values were removed using the AdjustExtreme command in TSTool. No filling of West Point inflows or outflows was required.

3.6 Local Incremental Flow Calculation and Adjustments

Calculations described above produced complete time series (no missing data) of cumulative “semi-impaired” (i.e., reservoir holdouts removed but net evaporation and water use remaining included) flows and reservoir inflows and outflows over the required periods of record. Local incremental flows were next calculated by subtraction of routed upstream cumulative flows from downstream cumulative flows. For headwater nodes, local incremental flows are the same as cumulative flows. For

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan downstream nodes, local incremental flows were computed using TSTool commands executing the following steps:

• Read upstream filled cumulative flow time series.

• Route the upstream cumulative flow time series to the downstream location.

• Subtract the routed upstream cumulative flows from the downstream cumulative filled time series, resulting in local (impaired) incremental flow at the downstream location.

For reservoirs, the filled reservoir inflow time series was used in the local incremental flow calculation for the reservoir node. The reservoir outflow time series was used in the local incremental flow calculation for the node downstream of the reservoir.

As previously stated, local incremental flows do not yet represent unimpaired flows. Water withdrawals, agricultural diversions, return flows, reservoir net evaporation, and other losses or gains are added to the local incremental flows in the final step to produce unimpaired flows.

In some reaches, negative local incremental flows resulted from the subtraction of routed upstream cumulative flows from downstream cumulative flows. These negative values result from a variety of causes, including routing discrepancies (e.g., lag times), errors in observed flow values, small local flows relative to cumulative flows, and water use or losses to groundwater. Adjustments to remove negative local incremental flows were limited to refinements to filling and/or routing procedures, with final adjustments to remove all negative local incremental flows performed after final aggregation of local incremental flows, reach net water uses, and remaining reservoir effects in the unimpaired local incremental flows.

Table 3-9 lists TSTool command files and HECDSS macros applied to ACF filling, routing, and local incremental flow calculation.

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Table 3-9 TSTool Command and HECDSS Macro File Listing for ACF Basin Determination

COLUMBUS_fill.TSTool Filling for Columbus IRONCTY_fill.TSTool Filling for Iron City IronCityMLR.MCO Multiple linear regression (MLR) for Iron City MILFORD_fill.TSTool Filling for Milford MilfordMLR.MCO MLR for Milford Populates all observed time series to be InitialPopulate_ACF_dss.TSTool used in the filling for the ACF basin Run_ACF_Filling.TSTool Runs files to fill all nodes in the ACF basin Computes local incremental flows at each ComputeLocalIncrementals-ACF.TSTool node in the ACF basin

3.7 Local Incremental Unimpaired Flow Calculation

The final stage of local incremental unimpaired flow determination involves aggregation and removal of remaining impairments (human influences) – principally reservoir effects and net water uses – from local incremental flows.

3.7.1 Negative Local Unimpaired Flow Adjustments

In general, negative local unimpaired flows are not realistic, but an indication of inaccuracies or errors in development. Therefore, a no-negative local incremental unimpaired flow policy was adopted for this study, in consideration of potential application to water availability assessments subject to various minimum flow constraints, including annual or monthly 7Q10 (seven-day minimum streamflow with a 10-year recurrence interval). However, on rare occasions, negative local unimpaired flows are realistic, namely, if a stream is losing flow to groundwater. Such locations may be of interest for future detailed study. Moreover, many reservoir system operational models do not allow for negative local incremental flows. The utility of unimpaired flows computed in this study is maximized by systematic “intelligent” removal of negative values with minimal alteration to surrounding non-negative values, as opposed to cruder methods employed by operational models.

While negative local incremental flows were removed to the maximum extent possible by refinements to reservoir holdouts, routing and filling procedures, and short-duration (three to five days) smoothing and averaging, some residual negatives remained at the unimpaired flow determination stage. To remove these, three approaches were

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan employed, listed as follows in order of minimum number of adjacent time periods adjusted:

• The AdjustExtreme TSTool procedure, which averages values on either side of the negative value for as many days as necessary to produce a non-negative result. This method works best with intermittent as opposed to continuous periods of negative flows. Where extended periods of negative flows occur, the AdjustExtreme procedure produces multi-month periods of constant low flow.

• Annual adjustment – A DSSMATH procedure that increases all negative flows to zero and reduces all positive values by a factor equal to the ratio of the original (with negatives) annual average flow to the adjusted (no negatives) annual average flow.

• POR adjustment – Same as annual adjustment with the reduction factor computed using 1939 to 2007 POR average flow ratios.

3.7.2 Selection of Final Local Unimpaired Flow Time Series

Final local unimpaired flow selection is predicated on the basic requirement for no residual negative flows in the following order of preference:

• Unadjusted unimpaired flow (F = UNIMP)

• TSTool AdjustExtreme method, assuming no continuous constant-flow periods greater than the annual or POR adjustment (F = UNIMP–0ADJ LOC)

• DSSMATH annual adjustment (F = UNIMP–0ADJ ANNUAL)

• DSSMATH POR adjustment (F = UNIMP–0ADJ POR)

Final local unimpaired flow time series selection is denoted by an asterisk at the end of the F pathname denoting the adjustment required (e.g., F= UNIMP–0ADJ ANNUAL*). Example ACF DSS pathnames for unimpaired flows and local inflow, reservoir effects, and water use constituents are shown in Table 3-10.

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3.7.3 Special Cases of Negative Incremental Flows

In 2005, some large negatives appeared in Jim Woodruff incremental flows during high-flow events at Iron City. These negatives were believed to be caused by inaccuracies in Woodruff outflows. Namely, as a result of unaccounted-for seepage at Woodruff not returning to the river upstream of the Chattahoochee gage, the outflow estimates, which are the Chattahoochee gage readings, are lower than the true total outflow – Chattahoochee plus seepage. Because the outflow estimate is low, inflow estimates will also be low. Thus, the likelihood of negative incremental flows is increased because incrementals are the difference of Iron City flows routed downstream to Woodruff. No adjustments were made to the Woodruff outflows since a means of estimating this seepage is not known. A report by L. Elliott Jones and Lynn J. Torak 3 provides an excellent qualitative measure on the effects of Lake Seminole and provides insight to the event described above. Unfortunately, the findings are not on as fine a scale as needed to be applicable to unimpaired flow derivation. However, an area of future work could be a refinement of this study to a resolution applicable to unimpaired flow derivation.

In May 2003, a large rain event upstream of Lanier produced a high-flow event that rapidly moved downstream. Below West Point, large negative incremental flows were produced. These negatives stem partly from inaccuracies between the general routing parameters used and those that would apply to such a special event. However, the main cause appears to be inaccuracies in gage readings, particularly at Columbus and Columbia, with USGS estimates of fair to poor, indicating that recordings are within 15 percent at best.

3Jones, L. Elliott, and Torak, Lynn J., 2004. Simulated Effects of Impoundment of Lake Seminole on Ground-Water Flow in the Upper Floridan Aquifer in Southwestern Georgia and Adjacent Parts of Alabama and Florida: U.S. Geological Survey, Scientific Investigations Report 2004-5077, p. 22.

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Table 3-10 Sample Condensed Catalog Listing of ACF Unimpaired Flow and Component Time Series T670 ACF-CHATT BUFORD_R FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN2001 - 01JAN2007 T677 ------COMP-REACH-A 1DAY 01JAN2001 - 01JAN2007 T684 ------COMP-REACH-I 1DAY 01JAN2001 - 01JAN2007 T691 ------COMP-REACH-M 1DAY 01JAN2001 - 01JAN2007 T698 ------FLOW-EVAPNET POST RES 1DAY 01JAN1939 - 01JAN2007 T767 ------POST-PRE RES 1DAY 01JAN1939 - 01JAN2007 T836 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T905 ------FLOW-LOC INC FILLED 1DAY 01JAN1939 - 01JAN2007 T974 ------UNIMP 1DAY 01JAN2001 - 01JAN2007 T981 ------UNIMP-0ADJ ANNUAL 1DAY 01JAN2001 - 01JAN2007 T988 ------UNIMP-0ADJ LOC 1DAY 01JAN2002 - 01JAN2007 T994 ------UNIMP-0ADJ LOC* 1DAY 01JAN1939 - 01JAN2007 T1063 ------UNIMP-0ADJ POR 1DAY 01JAN2001 - 01JAN2007 T1070 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007

3.8 Merger of Existing and Extended Unimpaired Time Series

The final step in development of ACF unimpaired flows required the 2002 – 2007 record extension to be merged with the existing 1939 – 2001 record developed for reservoir system operational models used in connection with interstate water allocation negotiations, litigation, and evaluation of USACE ACF water control policies. For reaches where the LDA for existing and extended incremental unimpaired flows corresponded, no further adjustments were necessary and the record extension was simply appended to the existing record. In these cases, the B part pathnames reflect nodes adopted for the current study rather than operational model control points.

For reaches where the LDAs do not correspond, existing local unimpaired flows either had to be aggregated or disaggregated to produce a consistent 1939 – 2007 local unimpaired flow record. Two methods of adjustment for merger of existing and extended local incremental unimpaired flow time series data are described as follows:

• Basic or planning (Georgia EPD) node LDA made up of multiple operational model (USACE) control point LDAs. In this case, the USACE 1939 – 2001 local unimpaired flows are aggregated into the new (Georgia EPD) LDA and appended to the 2002 – 2007 Georgia EPD local unimpaired flow extension. Merged B part pathnames are designated by node identification followed by “-EPD,” (e.g., ATLANTA-EPD and COLUMBUS-EPD).

• Operational model (USACE) control point LDA made up of multiple (new) Georgia EPD node LDAs. In this case, the USACE 1939 – 2001 LDA is larger than the Georgia EPD 2002 – 2007 LDA. As a consequence, USACE local unimpaired flows before 2002 are appended to aggregated Georgia EPD local unimpaired flows afterward to create a new 1939 – 2007 aggregate unimpaired flow record with the B part pathname identified by “-USACE” to denote its suitability for

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operational modeling. The constituent LDA Georgia EPD 1939 – 2007 local unimpaired flows are then subtracted from the -USACE local unimpaired flow record to create an “-EPD” 1939 – 2007 local unimpaired flow time series. This procedure was applied to Woodruff and Bainbridge, to which 1939 – 2007 local unimpaired flows developed for the IRON_CTY and MILFORD tributary reaches were subtracted respectively from the aggregate (-USACE) 1939 – 2007 local unimpaired flows to create a 1939 – 2007 WOODRUFF and BAINBRDG-EPD local unimpaired flow record. The WOODRUFF and BAINBRDG-USACE unimpaired flow record is suitable for ACF operational modeling, and the WOODRUFF and BAINBRDG-EPD record for the purposes of this study.

Because no adjustments were made to existing ACF 1939 – 2001 local unimpaired flows and all negative values were removed (using previously described procedures) from the 2002 – 2007 unimpaired flow extension, residual negative values in the existing data are carried through to the merged 1939 – 2007 local unimpaired flows, an example of which is shown on Figure 3-7. F part designation for final merged 1939 – 2007 time series is “UNIMP 1939-2007.” The condensed catalog of constituent and merged ACF basin unimpaired flow time series data is listed in Table 3-11.

Figure 3-7 Merged BAINBRDG-USACE Local Unimpaired Flow Time Series Data

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Table 3-11 ACF Merged Unimpaired Flow Condensed Catalog Listing Tag A Part B Part C Part F Part E Part D Part

T1 ACF-APCOLA WOODRF_R FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T71 ------UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T140 ACF-CHATT ATLANTA FLOW-LOC INC UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T209 ------ATLANTA-EPD FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T279 ------BUFORD_R FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T349 ------UNIMP-0ADJ LOC* 1DAY 01JAN1939 - 01JAN2007 T418 ------COLUMBIA FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T488 ------UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T557 ------COLUMBUS FLOW-LOC INC UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T626 ------COLUMBUS-EPD FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T696 ------NORCROSS FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T766 ------UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T835 ------WESTPT_R FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T905 ------UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T974 ------WFG_R FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T1044 ------UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T1113 ------WHITSBRG FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T1183 ------UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T1252 ACF-FLINT ALBANY FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T1322 ------UNIMP-0ADJ LOC* 1DAY 01JAN1939 - 01JAN2007 T1391 ------BAINBRDG FLOW-LOC INC UNIMP-0ADJ LOC* 1DAY 01JAN1939 - 01JAN2007 T1460 ------BAINBRDG-EPD FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T1530 ------BAINBRDG-USACE FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T1600 ------MONTEZMA FLOW-LOC INC UNIMP* 1DAY 01JAN1939 - 01JAN2007 T1669 ------MONTEZMA-EPD FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T1739 ------NEWTON FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T1809 ------UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T1878 ACF-ICHACR MILFORD FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T1948 ------UNIMP* 1DAY 01JAN1939 - 01JAN2007 T2017 ACF-SPRGCR IRON_CTY FLOW-LOC INC UNIMP 1939-2007 1DAY 01JAN1938 - 01JAN2007 T2087 ------UNIMP* 1DAY 01JAN1939 - 01JAN2007 T2156 APALACHICOLA BLOUNTSTOWN FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2219 ------CHATTAHOOCHEE FLOW_INC UNIMP_CMA0 1DAY 01JAN1939 - 01JAN2001 T2282 ------JIM WOODRUFF FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2345 ------SUMATRA FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2408 CHATTAHOOCHEE ATLANTA FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2471 ------BARTLETTS FERRY FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2534 ------BUFORD FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2597 ------COLUMBUS FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2660 ------GEORGE ANDREWS FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2723 ------GOAT ROCK FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2786 ------MORGAN FALLS FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2849 ------NORCROSS FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2912 ------NORTH HIGHLANDS FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T2975 ------OLIVER FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T3038 ------W.F.GEORGE FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T3101 ------WEST POINT G FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T3164 ------WEST POINT R FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T3227 ------WHITESBURG FLOW_INC UNIMP_CMA7 1DAY 01JAN1939 - 01JAN2001 T3290 FLINT ALBANY FLOW_INC UNIMP_CMA5 1DAY 01JAN1939 - 01JAN2001 T3353 ------BAINBRIDGE FLOW_INC UNIMP_CMA5 1DAY 01JAN1939 - 01JAN2001 T3416 ------GRIFFIN FLOW_INC UNIMP_CMA0 1DAY 01JAN1939 - 01JAN2001 T3479 ------MONTEZUMA FLOW_INC UNIMP_CMA0 1DAY 01JAN1939 - 01JAN2001 T3542 ------NEWTON FLOW_INC UNIMP_CMA5 1DAY 01JAN1939 - 01JAN2001

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3.9 Quality Control

Because primary quality control was performed at each stage of the ACF basin’s unimpaired flow development (water use data, reservoir effects, and filling/routing), final stage quality control relied on (1) visual inspection and comparison of pre- and post- 2002 merged local unimpaired flow time series plots, (2) comparison of average local unimpaired flow volumes pre- and post-2002, (3) consistency plots, in which individual nodes are grouped and differences between accumulated unimpaired flow for individual nodes and average accumulated unimpaired flow for the group are compared, and (4) comparison of similar runs in different model platforms. These checks revealed no major discrepancies between the pre- and post-2002 local unimpaired flow data. Observable differences are (1) the absence of negative values in the 2002 – 2007 record extension, and (2) comparatively reduced flashiness of the 1939 – 2001 data as a result of the extensive use of five- and seven-day smoothing in their derivation.

3.10 Cumulative Unimpaired Flows

Following Georgia EPD approval of local unimpaired flow data documented in this report, partial and full cumulative unimpaired flow time series data will be developed by aggregation and routing of applicable upstream local, partial cumulative, and cumulative unimpaired flows to downstream nodes.

3.11 Conclusions

Table 3-11 indicates that five- and seven-day centered-moving average (CMA) smoothing was employed extensively in development of the existing 1939 – 2001 unimpaired flow data. As a consequence, the data appear much less flashy than the 2002 – 2007 record extended in this study, which did not use smoothing. However, CMA may be subsequently applied to the extended period data to produce more visually consistent time series results and to reduce the number of 0- and near-0 flows produced by elimination of negative values.

Adjustments to remove negative local unimpaired flows from the existing 1939 – 2007 data may also be desirable to ensure their suitability for (1) combining and routing to produce various cumulative unimpaired flow time series at planning or multiple basic nodes, and (2) calculating low-flow statistics imposed as constraints on water availability assessments performed using the River Basin Planning Tool. If negative adjustments are required, the same approaches adopted for the ACF unimpaired flow extension (AdjustExtreme, annual, and POR adjustments) are recommended.

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4. Alabama-Coosa-Tallapoosa (ACT) River Basin

4.1 ACT Basin Description

The ACT basin drains an area of 14,739 square miles in Georgia and Alabama. Approximately 5,299 square miles of the basin are in Georgia, and approximately 9,440 square miles are in Alabama. The confluence of the Coosa and Tallapoosa rivers forms the Alabama River near Wetumpka, Alabama, and the Alabama and Tombigbee rivers merge to form the Mobile River near Calvert, Alabama. This study addresses the unimpaired flows of the Georgia portion of the ACT basin only.

The Georgia portion of the Coosa River basin and its tributary streams occupy a 4,579-square-mile area of the northwest corner of the state (Figure 4-1). Downstream of Georgia, the Coosa River basin covers a 5,353-square-mile area of Alabama. North of Georgia, a 127-square-mile area lies in Tennessee. A distinct dry season usually occurs from mid-summer to late fall. Winter is the wettest season and March the wettest month, on average. The mean annual temperature is about 60 degrees Fahrenheit.

The Coosa River basin contains several major rivers, as well as manmade reservoirs. The Coosa River itself is formed by the confluence of the Oostanaula and Etowah rivers near Rome, Georgia. The Oostanaula River in turn is formed by the confluence of the Conasauga and Coosawattee rivers. The basin also contains the Chattooga River, which joins the Coosa River in Alabama.

Three dams are located within the Georgia portion of the Coosa River basin, while a fourth, Weiss Dam in Alabama, has an impoundment that extends into Georgia. Within Georgia, multipurpose projects have been constructed to harness the power potential of headwater streams, beginning with Allatoona Dam, constructed on the Etowah River by USACE and completed in December 1949, followed by Carters Dam on the Coosawattee River, completed in November 1974. There is also a reregulation dam below Carters Dam that captures water for pumpback and moderates the impacts of hydropower generation flow.

The Tallapoosa River basin within Georgia consists of the Tallapoosa River itself and the Little Tallapoosa River. The basin drains a total area of 4,680 square miles, of which 720 square miles are in Georgia and 3,960 square miles are in Alabama. A distinct dry season occurs from mid-summer to late fall. Rainfall is usually greatest in

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March and least in October. The mean annual temperature is about 61 degrees Fahrenheit.

4.2 Hydrological Data

4.2.1 Existing Unimpaired Flows

Unique to the ACF and ACT study basins is the existence of daily unimpaired flow time series data developed during the ACF and ACT Comprehensive Studies for the 1939 to 1993 POR. These data were later extended through 2001. Georgia EPD has elected to retain these data for the current study and to extend the data from 2002 through 2007 to match the 1939 to 2007 POR adopted statewide. Therefore, for all nodes coinciding with ACT Basin Comprehensive Study control points, only the 2002 to 2007 record extension was required. However, the Gayles node, located on the Chattooga River, and the Rome at Oostanaula node, located on the Oostanaula River, required generation of a complete 1939 to 2007 time series. Existing and extended unimpaired flow time series data were subsequently merged, with adjustments necessitated by differences in LDAs between the current study and the Comprehensive Study (i.e., intermediate control points between nodes or nodes not originally designated as control points). The merged time series will permit water availability assessments for statewide water planning as well as application of ACT reservoir system operational models (e.g., HEC-5 and ResSim) for water management and water allocation purposes.

The existing (1939 to 2001) unimpaired flow data are contained in the ACTCUM_6.DSS file developed by the USACE Mobile District in September 2003. These data are derived for all basic and planning nodes subsequently selected for this study. Despite intensive data adjustment and smoothing, negative unimpaired local inflows persist at several of these intermediate points. The aggregated unimpaired flows, however, contain less negative flows at basic nodes selected for the current study.

4.2.2 Streamflow Records

Approximately 37 stream gage stations are located within the Georgia and nearby downstream portions of the ACT basin, of which 14 are suitable for planning. Basic nodes have continuous data covering all of the 2002 to 2007 period for which unimpaired flows are to be extended. Ten nodes have continuous data covering most of the 1939 to 2007 period, and six of these cover the entire 1939 to 2007 period.

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Figure 4-1 Map of the ACT Study Basin

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All nodes in the ACT basin required time series with no missing data for 2002 through 2007, with the exception of GAYLES and ROME_O, which required complete time series from 1939 through 2007. Gage locations are shown on Figure 4-2, and periods of record for gages used in filling are shown on Figure 4-3.

4.2.3 Reservoir Data

Detailed operational data (pool elevations, releases, and computed inflows) were obtained in electronic form for the two USACE multipurpose reservoirs in the basin (Allatoona and Carters). Calculation of reservoir inflows and local incremental flows at downstream nodes (where reservoirs are not located at nodes) involves the addition of reservoir holdouts (cumulative change in storage reflecting differences in reservoir outflows and inflows) to observed reservoir releases or cumulative downstream flows. Local unimpaired flows were further adjusted for differential net evaporation (evaporation minus precipitation) falling on the reservoir surface prior to and since reservoir construction. Calculation of holdout and net evaporation flow time series is enabled by application of reservoir elevation time series to elevation-storage and elevation-area curves. These paired physical data were obtained from USACE HEC-5 model input data developed during the ACT Comprehensive Study and Georgia Power records. Said model paired physical data can also be found in the Alabama Coosa River Basin Water Control Manual.

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Figure 4-2 Nodes and Streamflow Gages Associated with the ACT Study Basin Streamflow Filling

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Figure 4-3 Period of Record for Gages Used in the ACT Study Basin Streamflow Filling

4.2.4 Climatological Data

Precipitation: Required for determination of reservoir net evaporation effects are NWS SERFC and LMRFC MAP time series for sub-basins throughout the state of Georgia. For the majority of the reservoirs included in the study, MAP time series were available for the LDAs upstream of the reservoir. The MAP sub-basins cover an area equal to or smaller than the LDAs. The MAP time series were originally derived using hourly and daily station data downloaded from NCDC and quality controlled to remove outliers and long-term bias from the stations. The NWSRFS MAP processor was used to compute the MAP time series. The processor includes missing data estimation techniques to fill missing precipitation observations, prior to MAP computation using the Thiessen polygon weighting scheme. The resulting MAP time series were generated on six-hour time intervals, and subsequently aggregated to daily values. Table 4-1 summarizes the MAP time series assigned to each ACT reservoir with the original POR for each.

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Table 4-1 ACT Reservoirs Included in the Analysis and Corresponding MAP Time Series

Operated Prior to MAP MAP Period A_PART B_PART Reservoir 1950? Identifier of Record ACT- C_REREG- 1/1950 – COOSAW CARTRS_R Carters Lake N CTRG1 12/2004 ACT- C_REREG- Carters 1/1950 – COOSAW REREG_R Rereg N CTSG1 12/2004 ACT- Lake 1/1950 – ETOWAH ALATNA_R Allatoona N CVLG1 12/2004

Evaporation: Free water surface evaporation estimation can be problematic because of data quality problems in measured evaporation data. Using quality-controlled pan evaporation and meteorological data, NOAA developed annual and seasonal free water surface evaporation maps for the contiguous United States (NOAA Technical Reports NWS 33 and 34, 1982). NWS later digitized these maps and developed monthly free water surface evaporation grids. The monthly evaporation grids present a consistent method to derive average monthly free water surface evaporation at every reservoir. Monthly free water surface evaporation estimates from these grids were compared with free water surface evaporation estimates using long-term, monthly pan evaporation data downloaded from NCDC and an assumed pan coefficient (reported in pan coefficient maps from NOAA Technical Report NWS 34). The distributions of the two free water surface estimates generally agree well for stations with better quality data. Only slight spatial variation in evaporation estimates was observed between the upper, middle, and lower ACT basin reservoirs (north to south).

Georgia EPD staff generated daily PET time series for every reservoir using the Hamon PET option of the WDMUtil program, a utility program associated with the U.S. EPA HSPF. The Hamon PET calculation requires time series of daily maximum and minimum temperatures, and latitude as inputs. For each reservoir, the daily maximum and minimum temperature time series were estimated from surrounding stations. Daily PET estimates were generated for 11 different locations throughout the state, with some reservoirs grouped together because of their proximity. Precipitation and evaporation time series data used in development of ACT basin unimpaired flows are applicable only to reservoirs, and contained in ACTRE.DSS , sample pathname listings for which are shown in Table 4-2.

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Table 4-2 Sample ACT Precipitation and Evaporation Time Series Data HECDSS Condensed Catalog Listing (from ACTRE.DSS, 2009-06-23 version)

7 ACT- 01JAN1975 – ADJ CARTERS_R EVAP 1DAY COOSAW 01JAN2007 HAMON 8 NOAA ACT- 01JAN1975 – CARTERS_R EVAP 1DAY EVAP COOSAW 01JAN2007 ATLAS ACT- 01JAN1975 – SERFC 45 CARTERS_R PRECIP 1DAY COOSAW 01JAN2007 MAP ACT- 01JAN1951 – ADJ 105 ALATNA_R EVAP 1DAY ETOWAH 01JAN2007 HAMON NOAA ACT- 01JAN1951 – 106 ALATNA_R EVAP 1DAY EVAP ETOWAH 01JAN2007 ATLAS ACT- FLOW- 01JAN1951 – POST 127 ALATNA_R 1DAY ETOWAH PREC 01JAN2007 RES ACT- 01JAN1975 – SERFC 45 CARTERS_R PRECIP 1DAY COOSAW 01JAN2007 MAP

4.3 Water Use Data

The Water Use Data Inventory Report documents present (2002 to 2007) and, for the Gayles reach and the Rome at Oostanaula reach, hindcasted (1939 to 2001) consumptive water uses within the ACT basin of the following types:

• Municipal and industrial water use (withdrawals, discharges/returns) in Georgia

• Thermal power water use (withdrawals, discharges/returns, and net consumption) in Georgia

• Agricultural irrigation water use in Georgia

Net uses of each type are aggregated by reach and summed to produce an aggregate water demand for each reach. Reach aggregate water use is added to local incremental flows and combined with reservoir effects as applicable (both subsequently described) to produce local incremental unimpaired flows.

No modifications or adjustments were made to reach aggregate water uses built into the existing ACT unimpaired flow time series contained in ACTCUM_6.DSS for the 2002 to 2007 record extension.

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4.4 Reservoir Effects

USACE maintains historical reservoir elevation, release, and computed inflow time series data for its reservoirs in the ACT basin. These data permit visual screening, verification, and reconciliation of USACE-computed inflows and holdout-adjusted inflows, assuming USACE release data or downstream gage data control.

Various smoothing adjustments were applied to reservoir holdouts, but were not needed, and thus unsmoothed holdouts were applied to the derivation of unregulated flows. Reservoir elevation time series were visually screened of anomalous data. These adjustments significantly reduced outlier holdouts (i.e., one-day changes from large negative to large positive values inconsistent with reservoir operational policy).

4.4.1 Net Evaporation

Calculation of net evaporation in the ACT basin applied evaporation and precipitation time series data (described below) to post- and pre-reservoir runoff coefficients, computed for the ACT basin as ratios of annual precipitation to runoff at representative unregulated stream gages at various locations in Georgia, shown on Figure 4-4.

Pre-development runoff coefficients applied to ACT reservoirs are listed in Table 4-3.

Reservoir Runoff Coefficient Selection: When a reservoir is present, the runoff fraction is increased from the pre-reservoir basin runoff fraction to 100 percent over the reservoir surface. The difference between 100 percent runoff and the basin runoff fraction represents the incremental increase in runoff because of the reservoir that needs to be accounted for in the unimpaired flow calculation.

Table 4-3 ACT Reservoir Pre-Development Runoff Coefficients

A_Part B_Part Reservoir Name Runoff Coefficient C_REREG- Carters Lake ACT-COOSAW REREG_R Reservoir 0.45 C_REREG- Carters Lake ACT-COOSAW CARTRS_R Reservoir 0.45 ACT-ETOWAH ALATNA_R Lake Allatoona 0.45

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Figure 4-4 Georgia Representative Unregulated Flow Gaging Stations and Average Annual Runoff Coefficients

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4.4.2 Methods Summary

Table 4-4 summarizes streamflow filling periods and methods for the ACT basin. Many streamflow records were complete over the required periods of analysis and consequently required no filling. The TILTON, CANTON, RESACA, PINE, HEFLIN, and NEWELL streamflow time series were complete over the analysis period and required no filling. However, although the PINE gage period of record was complete, this study determined that flows during the period of August to December 2005 were too high as a result of a gage error. USGS concurred and adjusted the record in accordance with its review. The locations of gages are identified on the map on Figure 4-2, and the period of record for each gage is depicted on Figure 4-3. The following sections present the details of streamflow filling for each location.

Table 4-4 Streamflow Filling Periods and Methods

Node Missing Period Filling Method/Gage(s) Used for Filling ALATNA_R 1/02 – 12/07 Inflow: mass balance C_REREG/ 1/02 – 12/07 Inflow: mass balance CARTERS_R GAYLES 1/39 – 12/58 Route Summerville and fill using MOVE2 10/67 – 9/84 Route Summerville and fill using MOVE2 KINGSTON 1/02 – 12/07 Scaled local flows between Allatoona and Rome_E ROME_O 1/39 – 9/39 Scaled difference between Rome_C and Rome_E ROME_E 1/02 – 12/07 GA1Loop scaled based on the mean flow ratio

Specific filling and holdout calculations are subsequently described.

4.4.3 Allatoona Reservoir (ALATNA_R)

Allatoona Reservoir inflows were computed based on observed outflows and changes in reservoir storage. The following specific steps were completed:

1. The Allatoona Reservoir inflows were computed by calculating a mass balance at the reservoir using the Alatna_R gage just downstream of the reservoir outfall and the daily change in storage time series. Negative values were removed using the AdjustExtremes command in TSTool.

No filling was required for the reservoir inflows or outflows.

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4.4.4 Carters Reregulation and Carters Reservoirs (C_REREG and CARTERS_R)

The Carters Reregulation and Carters reservoirs include pumpback facilities that pump from Carters Reregulation Reservoir to Carters Reservoir. A pumping time series for the facility was not available. Therefore, the inflow from Carters Reservoir into Carters Reregulation Reservoir could not be directly computed. Instead, the time series at a gage just below the Carters Reregulation Reservoir outfall and the combined storage time series of both reservoirs were used to compute a total inflow into the reservoir system. The total inflow was then partitioned into the inflows from the Carters Reregulation and Carters sub-basins.

The inflows at the C_REREG and CARTERS_R nodes were computed for 1/1/2002 – 12/31/2007. The total inflow was computed using a mass balance by means of a downstream gage and combined storage time series. The total inflow was portioned using a tributary gage. The following specific steps were completed:

1. The daily change in storage time series for both Carters Reregulation and Carters reservoirs was summed.

2. The total inflow into Carters Reservoir for the period was computed by calculating a mass balance using the C_Rereg gage just downstream of the Carters Reregulation Reservoir outfall and the combined daily change in storage time series.

3. The Talking_Rock gage, found in the Carters Reregulation sub-basin, was scaled by drainage area ratio and routed downstream to the outlet based on reach length to determine the inflow into Carters Reregulation Reservoir.

4. The Carters Reregulation inflow time series was subtracted from the computed total inflow to determine the inflow into Carters Reservoir.

4.4.5 Gaylesville (GAYLES)

The Gaylesville streamflow record contained missing data for two periods (1/1/1939 – 12/31/1958 and 10/1/1967 – 9/30/1984). The missing flow was filled using an upstream gage. The following specific steps were completed:

1. The upstream Summerville flow was routed downstream to the Gaylesville gage.

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2. The two missing data periods were filled using a monthly MOVE2 relationship with the routed Summerville gage. Table 4-5 presents the resulting monthly regression equations and statistics from the filling.

Table 4-5 Monthly MOVE2 Results: Gayles (Dependent) and Routed Summerville (Independent)

Y = A + BX Root Mean Square Error Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg January 73.7 1.76 0.9384 273.94 919.76 0.30 February 146.25 1.63 0.9495 335.19 1,148.45 0.29 March 127.76 1.68 0.9451 365.26 1,289.56 0.28 April –13.01 1.91 0.9327 242.22 826.3 0.29 May 55.09 1.69 0.9223 253.71 590.77 0.43 June –21.48 2.03 0.9213 112.1 348.15 0.32 July 43.55 1.71 0.842 161.92 345.26 0.47 August –2.79 1.9 0.7396 71.07 220.61 0.32 September 47.12 1.4 0.9153 98.48 222.97 0.44 October 20.29 1.69 0.933 145.06 278.72 0.52 November –5.03 1.92 0.9527 145.81 434.18 0.34 December 36.39 1.8 0.959 176.35 634.26 0.28

4.4.6 Rome on the Oostanaula River (ROME_O)

The Rome_O streamflow record contained missing data for one period (1/1/1939 – 9/30/1939). The downstream Rome_C gage and adjacent Rome_E gage had complete data records during the missing period. The difference between the recorded data from these gages was computed and scaled according to the mean flow ratios to fill the missing Rome_O data. The following specific steps were completed:

1. For the Rome_O flow, a bad data value on 1/2/1974 was replaced by interpolating between the two adjacent values.

2. The Rome_E flow was routed downstream and subtracted from the Rome_C flows.

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3. The result from step 2 was scaled according to average discharge ratios computed over the period of record common to the three locations (10/1/1939 – 1/1/1959 and 9/30/1962 – 1/1/1997), defined as:

MeanFlow Rome_O / (MeanFlow Rome_C – MeanFlow Rome_E )

4. The missing data period at Rome_O was filled using the scaled Rome_C minus Rome_E flows.

4.4.7 Rome on the Etowah River (ROME_E)

The Rome_E streamflow record contained missing data for one period (1/1/2002 – 12/31/2007). The missing flow was filled using an upstream gage. The following specific steps were completed:

1. The upstream GA1Loop flow was scaled using the ratio of mean flows between the Rome_E and GA1Loop gages.

2. The missing data period was filled directly with the scaled GA1Loop gage.

4.4.8 Kingston (KINGSTON)

The Kingston streamflow record contained missing data for one period (1/1/2002 – 12/31/2007). Initially, the missing period was filled by routing observed releases from Allatoona downstream to Kingston, filling the local incremental between Allatoona and Kingston using a regression with a nearby tributary gage, and summing the two time series. However, when the resulting time series was used in the local flow calculation at the downstream Rome_E node, there were significant negatives caused by overestimation of the Kingston streamflow. Therefore, an alternate method was identified to fill the Kingston streamflow that would reduce the negatives in the Rome_E local incremental flow.

The Kingston flows were filled by computing the local flow between Allatoona and Rome_E, splitting this local flow between Kingston and Rome_E local incremental flows, and back-routing the resulting Kingston local incremental flow to Kingston. The Kingston local incremental flow was then summed with Allatoona releases routed downstream to Kingston. The following specific steps were completed:

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1. Allatoona dam releases were routed to Kingston, and from Kingston downstream to Rome_E.

2. Routed Allatoona releases were subtracted from the filled Rome_E time series to yield the local flow between Allatoona and Rome_E. Negative flows were removed using the AdjustExtremes command in TSTool.

3. The mean flow at Allatoona, Kingston, and Rome_E was computed over the period of record common to the three locations (1/1/1939 – 10/23/1995). The initial Kingston local incremental flow was computed by scaling the local flow between Allatoona and Rome_E according to:

(MeanFlow Kingston – MeanFlow Allatoona ) / (MeanFlow Rome_E – MeanFlow Allatoona )

4. The resulting initial Kingston local incremental flow was back-routed from Rome_E to Kingston to attempt to better align the local incremental flows during subsequent steps.

The local incremental flow calculation at Rome_E still yielded negative values, yet the negatives appeared primarily as a result of errors of the routing model rather than major volume discrepancies.

4.5 Local Incremental Flow Calculation and Adjustments

After time series for historical stream flows, reservoir effects, and water use data are complete, the next step to derive unimpaired flows is the development of local incremental flows. Local incremental flows are calculated from the filled observed flows by subtraction of routed upstream cumulative flows from downstream cumulative flows. For headwater nodes, local incremental flows are the same as cumulative flows. For downstream nodes, local incremental flows were computed using the following steps:

• Route the upstream cumulative flow time series to the downstream location.

• Subtract the routed upstream cumulative flows from the downstream cumulative filled time series, resulting in local (impaired) incremental flow at the downstream location.

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For reservoirs, the filled reservoir inflow time series was used in the local incremental flow calculation for the reservoir node. The reservoir outflow time series was used in the local incremental flow calculation for the node downstream of the reservoir.

As previously stated, local incremental flows do not yet represent unimpaired flows. Water withdrawals, agricultural diversions, reservoir net evaporation, and other losses or gains are added to the local incremental flows in the final step to produce unimpaired flows.

In some reaches, negative local incremental flows resulted from the subtraction of routed upstream cumulative flows from downstream cumulative flows. These negative values result from a variety of causes, including routing discrepancies (e.g., lag times), errors in observed flow values, small local flows relative to cumulative flows, unaccounted channel storage, erroneous data, unaccounted run-of-river storage, and water use or losses to groundwater. Adjustments to remove negative local incremental flows were limited to refinements to filling and/or routing procedures, with final adjustments to remove all negative local incremental flows performed after final aggregation of local incremental flows, reach net water uses, and remaining reservoir effects in the unimpaired local incremental flows.

Table 4-6 lists TSTool command files and HECDSS macros applied to ACT filling, routing, and local incremental flow calculation.

Table 4-6 TSTool Command and HECDSS Macro File Listing for ACT Basin Local Incremental Flow Determination

ALATNA_R_inflow.TSTool Filling for Allatoona C_REREG-CARTERS_R_fill.TSTool Filling for Carters Main and Rereg GAYLES_fill.TSTool Filling for Gayles KINGSTON_fill.TSTool Filling for Kingston ROME_E_fill.TSTool Filling for Rome on Etowah ROME_O_fill.TSTool Filling for Rome on Oostanaula Populates all observed time series to be used in the InitialPopulate_ACT_dss.TSTool filling for the ACT basin Run_ACT_Filling.TSTool Runs files to fill all nodes in the ACT basin Computes local incremental flows at each node in ComputeLocalIncrementals_ACT.TSTool the ACT basin

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4.6 Local Incremental Unimpaired Flow Calculation

The final stage of local incremental unimpaired flow determination involves aggregation and removal of remaining impairments (human influences) – principally reservoir effects and net water uses – from local incremental flows.

4.6.1 Negative Local Unimpaired Flow Adjustments

In general, negative local unimpaired flows are not realistic, but an indication of inaccuracies or errors in development. Therefore, a no-negative local incremental unimpaired flow procedure was adopted for this study, in consideration of potential application to water availability assessments subject to various minimum flow constraints, including annual or monthly 7Q10 (10-year 7-day low flow). Moreover, many reservoir system operational models do not allow for negative local incremental flows. The utility of unimpaired flows computed in this study is maximized by systematic “intelligent” removal of negative values with minimal alteration to surrounding non-negative values, as opposed to cruder methods employed by operational models.

While negative local incremental flows were removed to the maximum extent possible by refinements to reservoir holdouts, routing and filling procedures, and short-duration (three to five days) smoothing and averaging, some residual negatives remained at the unimpaired flow determination stage. To remove these, three approaches were employed, listed as follows in order of minimum number of adjacent time periods adjusted:

• The AdjustExtreme TSTool procedure, which averages values on either side of the negative value for as many days as necessary to produce a non-negative result. This method works best with intermittent as opposed to continuous periods of negative flows. Where extended periods of negative flows occur, the AdjustExtreme procedure produces multi-month periods of constant low flow.

• Annual adjustment – A DSSMATH procedure that increases all negative flows to zero and reduces all positive values by a factor equal to the ratio of the original (with negatives) annual average flow to the adjusted (no negatives) annual average flow.

• POR adjustment – Same as annual adjustment with the reduction factor computed using 1939 to 2007 POR average flow ratios.

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4.6.2 Selection of Final Local Unimpaired Flow Time Series

Final local unimpaired flow selection is predicated on the basic requirement for no residual negative flows in the following order of preference:

• Unadjusted unimpaired flow (F = UNIMP)

• TSTool AdjustExtreme method, assuming no continuous constant-flow periods greater than the annual or POR adjustment (F = UNIMP–0ADJ LOC)

• DSSMATH annual adjustment (F = UNIMP–0ADJ ANNUAL)

• DSSMATH POR adjustment (F = UNIMP–0ADJ POR)

Final local unimpaired flow time series selection is denoted by an asterisk at the end of the F pathname denoting the adjustment required (e.g., F= UNIMP–0ADJ ANNUAL*).

4.7 Merger of Existing and Extended Unimpaired Flow Time Series

The final step in development of ACT unimpaired flows required the 2002 to 2007 record extension to be merged with the existing 1939 to 2001 record developed for reservoir system operational models used in connection with interstate water allocation negotiations, litigation, and evaluation of USACE ACT water control policies. In reaches where the LDA for existing and extended incremental unimpaired flows corresponded, no further adjustments were necessary and the record extension was simply appended to the existing record. In these cases, the B part pathnames reflect nodes adopted for the current study rather than operational model control points.

In reaches where the LDAs do not correspond, existing local unimpaired flows either had to be aggregated or disaggregated to produce a consistent 1939 to 2007 local unimpaired flow record. Two methods of adjustment for merger of existing and extended local incremental unimpaired flow time series data are described as follows:

• Basic or planning (Georgia EPD) node LDA made up of multiple operational model (USACE) control point LDAs. In this case, the USACE 1939 to 2001 local unimpaired flows are aggregated into the new (Georgia EPD) LDA and appended to the 2002 to 2007 Georgia EPD local unimpaired flow extension – merged B part pathnames designated by node identification followed by “-EPD”.

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• Operational model (USACE) control point LDA made up of multiple (new) Georgia EPD node LDAs. In this case the USACE 1939 to 2001 LDA is larger than the Georgia EPD 2002 to 2007 LDA. As a consequence, USACE local unimpaired flows before 2002 are appended to aggregated Georgia EPD local unimpaired flows afterward, to create a new 1939 to 2007 aggregate unimpaired flow record with the B part pathname identified by “-USACE” to denote its suitability for operational modeling. The constituent LDA Georgia EPD 1939 to 2007 local unimpaired flows are then subtracted from the -USACE local unimpaired flow record to create an “-EPD” 1939 to 2007 local unimpaired flow time series.

Because no adjustments were made to existing ACT 1939 to 2001 local unimpaired flows and all negative values were removed (using previously described procedures) from the 2002 to 2007 unimpaired flow extension, residual negative values in the existing data are carried through to the merged 1939 to 2007 local unimpaired flows. The F part designation for the final merged 1939 to 2007 time series is “UNIMP 1939- 2007”.

4.8 Quality Control

Because primary quality control was performed at each stage of ACT basin unimpaired flow development (water use data, reservoir effects, and filling/routing), final stage quality control relied on (1) visual inspection and comparison of pre- and post-2002 merged local unimpaired flow time series plots, (2) comparison of average local unimpaired flow volumes pre- and post-2002, and (3) consistency plots, in which individual nodes are grouped and differences between accumulated unimpaired flow for individual nodes and average accumulated unimpaired flow for the group are compared. These checks revealed no major discrepancies between the pre- and post- 2002 local unimpaired flow data. Observable differences are (1) absence of negative values in the 2002 to 2007 record extension, and (2) comparatively reduced flashiness of the 1939 to 2001 data as a result of extensive use of five- and seven-day smoothing in their derivation.

4.9 Cumulative Unimpaired Flows

Following Georgia EPD approval of local unimpaired flow data documented in this report, partial and full cumulative unimpaired flow time series data will be developed by aggregation and routing of applicable upstream local, partial cumulative, and cumulative unimpaired flows to downstream nodes.

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4.10 Conclusions

Five- and seven-day CMA smoothing was employed extensively in development of the existing 1939 to 2001 unimpaired flow data. As a consequence, the data appear much less flashy than the 2002 to 2007 record extended in this study, which did not use smoothing. However, CMA may be subsequently applied to the extended period data to produce more visually consistent time series results and to reduce the number of 0- and near-0 flows produced by elimination of negative values.

Adjustments to remove negative local unimpaired flows from the existing 1939 to 2007 data may also be desirable to ensure their suitability for (1) combining and routing to produce various cumulative unimpaired flow time series at planning or multiple basic nodes, and (2) calculating low-flow statistics imposed as constraints on water availability assessments performed using the River Basin Planning Tool. If negative adjustments are required, the same approaches adopted for the ACT unimpaired flow extension (AdjustExtreme, annual, and POR adjustments) are recommended.

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5. Ocmulgee-Oconee-Altamaha (OOA) Study Basin

5.1 OOA Basin Description

The OOA basin, located entirely within the state of Georgia, drains an area of about 14,265 square miles in central-southeastern Georgia. The Ocmulgee River basin is the westernmost river basin within the OOA basin and is located in the Piedmont and Coastal Plain physiographic provinces of central Georgia. The South, Yellow, and Alcovy rivers join at Lake Jackson south of the Atlanta metropolitan area to form the Ocmulgee River. The Oconee River basin is located just east of the Ocmulgee River basin and is formed by the confluence of the Middle and North Oconee rivers south of Athens, Georgia. About 20 miles south of the confluence of the Middle and North Oconee rivers, the Oconee River flows into Lake Oconee and then into Lake Sinclair. The Altamaha River begins at the confluence of the Ocmulgee and Oconee rivers and flows eastward, where it is joined by the Ohoopee River. The Altamaha River flows southeasterly from its confluence with the Ohoopee River to the Atlantic Ocean, south of Savannah Georgia (Georgia Department of Natural Resources, 1998, 2004).

Ocmulgee River and Oconee River flows are regulated by hydropower reservoirs operated by Georgia Power. The Altamaha River is unregulated, having no federal or private power storage reservoirs in its drainage basin. The most downstream OOA planning node for purposes of this study is the Doctortown node, which is located northeast of Jesup, Georgia. Three Georgia Power reservoirs exist within the OOA basin. Lake Jackson is located within the Ocmulgee River, southeast of Atlanta, Georgia. Lake Oconee and Lake Sinclair are located within the Oconee River basin, south of Greensboro, Georgia and north of Milledgeville, Georgia. Lake Oconee is a 21,000-acre reservoir formed by Wallace Dam, and immediately downstream is Lake Sinclair, a 15,330-acre reservoir formed by Sinclair Dam. Lake Oconee drains about 1,830 square miles and began commercial operation in 1979, upon completion of Wallace Dam. Lake Sinclair drains an area of about 2,910 square miles and its construction was completed in 1953 (Georgia Department of Natural Resources, 2004). Streamflow gages south of Lake Jackson (JACKSON) and Lake Sinclair (MILLEDGE) are planning nodes for surface water availability assessment purposes. The OOA study basin map showing node locations and LDAs for each is shown on Figure 5-1.

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Figure 5-1 OOA Study Basin Basic and Planning Nodes

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5.2 Hydrological Data

5.2.1 Existing Unimpaired Flows

No unimpaired flow data exist for the OOA basin.

5.2.2 Streamflow Records

Approximately 81 stream gage stations are located within the OOA basin, of which eight have continuous data covering 100 percent of the period for which unimpaired flows are to be extended; 17 of these cover at least half of the entire period. Streamflow data availability was used as a factor in selecting basic and planning nodes for the study basin. A total of 11 nodes were selected for the OOA basin, of which six are planning nodes and five are basic nodes. Out of the 11 total nodes selected for the basin, seven have continuous streamflow data covering 100 percent of the study period of record and nine have data covering 50 percent or more of the study period.

Because complete time series for 1939 to 2007 were needed for all nodes, four of the 11 nodes in the OOA basin required some filling. The nodes requiring filling included JACKSON, PENFIELD, VERNON, and BAXLEY. The locations of gages used in streamflow filling are shown on Figure 5-2. Yellow circles represent gages at nodes and red circles represent gages not located at nodes. The periods of record for the gages used in streamflow filling are shown on Figure 5-3.

5.2.3 Reservoir Data

Georgia Power provided pool elevation time series for Lake Jackson, Lake Oconee, and Lake Sinclair. Daily elevation time series data existed for these reservoirs from 1997 to 2007, and monthly elevation time series data from Georgia Power also provided storage-area-elevation curves for each reservoir. The time series and reservoir characteristics were used in subsequent local incremental flow and net evaporation computations.

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Figure 5-2 Nodes and Gages Associated with OOA Study Basin Streamflow Filling

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Figure 5-3 Periods of Record for Gages Associated with OOA Study Basin Streamflow Filling

5.2.4 Climatological Data

Precipitation: Required for determination of reservoir net evaporation effects are NWS SERFC and LMRFC MAP time series for sub-basins throughout the state of Georgia. For the majority of the reservoirs included in the study, MAP time series were available for LDAs upstream of the reservoir. The MAP sub-basins cover an area equal to or smaller than the LDAs. The MAP time series were originally derived using hourly and daily station data downloaded from NCDC, and quality controlled to remove outliers and long-term bias from the stations. The NWSRFS MAP processor was used to compute the MAP time series. The processor includes missing data estimation techniques to fill missing precipitation observations, prior to MAP computation using the Thiessen polygon weighting scheme. The resulting MAP time series were generated on six-hour time intervals, and subsequently aggregated to daily values. Table 5-1 summarizes the MAP time series assigned to each OOA reservoir, along with the original period of record for each.

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Table 5-1 OOA Reservoirs Included in the Analysis and Corresponding MAP Time Series

Operated Prior to MAP MAP Period A_PART B_PART Reservoir 1950? Identifier of Record OOA- JACKSON- 1/1950 – OCMULG JACKSN_R Lake Jackson Y JACG1 12/1999 OOA- MILLEDGE- 1/1950 – OCONEE OCONEE_R Lake Oconee N WDMG1 12/1999 OOA- MILLEDGE- 1/1950 – OCONEE SNCLAIR_R Lake Sinclair N SNCG1 12/1999

Evaporation: Free water surface evaporation estimation can be problematic because of data quality problems in measured evaporation data. Using quality-controlled pan evaporation and meteorological data, NOAA developed annual and seasonal free water surface evaporation maps for the contiguous United States (NOAA Technical Reports NWS 33 and 34, 1982). NWS later digitized these maps and developed monthly free water surface evaporation grids. The monthly evaporation grids present a consistent method to derive average monthly free water surface evaporation at every reservoir. Monthly free water surface evaporation estimates from these grids were compared with free water surface evaporation estimates using long-term, monthly pan evaporation data downloaded from NCDC and an assumed pan coefficient (reported in pan coefficient maps from NOAA Technical Report NWS 34). The distributions of the two free water surface estimates generally agree well for stations with better quality data. Only slight spatial variation in evaporation estimates was observed between the upper, middle, and lower OOA basin reservoirs (north to south).

Georgia EPD staff generated daily PET time series for every reservoir using the Hamon PET option of the WDMUtil program, a utility program associated with the U.S. EPA HSPF. The Hamon PET calculation requires time series of daily maximum and minimum temperatures, and latitude as inputs. For each reservoir, the daily maximum and minimum temperature time series were estimated from surrounding stations. Daily PET estimates were generated for 11 different locations, with some reservoirs grouped together because of their proximity. Precipitation and evaporation time series data used in development of OOA basin unimpaired flows are applicable only to reservoirs, and contained in OOARE.DSS , sample pathname listings for which are shown in Table 5-2.

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Table 5-2 Sample OOA Precipitation and Evaporation Time Series Data HECDSS Condensed Catalog Listing (from OOARE.DSS , 2009-06-13 version) Tag A Part B Part C Part F Part E Part D Part T1 OOA-OCMULG JACKSON-JACKSN_R EVAP ADJ HAMON 1DAY 01JAN1960 - 01JAN2007 T855 ------PRECIP SERFC MAP 1DAY 01JAN1960 - 01JAN2007 T1000 OOA-OCONEE MILLEDGE-OCONEE_R EVAP ADJ HAMON 1DAY 01JAN1979 - 01JAN2007 T1613 ------PRECIP SERFC MAP 1DAY 01JAN1979 - 01JAN2007 T1701 - - - - - MILLEDGE-SNCLR_R EVAP ADJ HAMON 1DAY 01JAN1953 - 01JAN2007 T2619 ------PRECIP SERFC MAP 1DAY 01JAN1953 - 01JAN2007

5.3 Water Use Data

The Water Use Data Inventory Report documents present and hindcasted municipal and industrial withdrawals and returns, thermal power water use (withdrawals, discharges/returns, and net consumption), and agricultural withdrawals within the OOA basin. Note that no groundwater use with effects on surface water stream flows was assumed for reaches within the OOA basin.

Net water uses of each type are aggregated by reach and summed to produce an aggregate water demand for each reach. The aggregate water demand is used in subsequent local incremental unimpaired flow calculations. HECDSS pathnames for OOA net water uses by reach and type are shown in Table 5-3 for each node.

Table 5-3 OOA Aggregate Reach Water Use HECDSS Condensed Catalog Listings (from OOA-unimpaired flow.DSS , 2009-06-30 version) A Part B Part C Part F Part E Part D Part

OOA-ALTAMA BAXLEY FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 - - - - - DOCTOWN FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-T 1DAY 01JAN1939 - 01JAN2007 OOA-MOCNEE ATHENS FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 OOA-OCMULG JACKSON FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 - - - - - LUMBER FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 - - - - - MACON FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007

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Table 5-3 OOA Aggregate Reach Water Use HECDSS Condensed Catalog Listings (from OOA-unimpaired flow.DSS , 2009-06-30 version) ------COMP-REACH-T 1DAY 01JAN1939 - 01JAN2007 OOA-OCONEE DUBLIN FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 - - - - - MILLEDGE FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-T 1DAY 01JAN1939 - 01JAN2007 - - - - - PENFIELD FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 - - - - - VERNON FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 OOA-OHOOP REIDS FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007

5.4 Reservoir Effects

For purposes of OOA basin unimpaired flow development, reservoir effects were computed for storage reservoirs (i.e., Georgia Power reservoirs). Figure 5-4 shows OOA reservoirs for which reservoir effects were calculated.

5.4.1 Holdouts

Various smoothing adjustments were applied to reservoir holdouts, but only the time series with F=COMP 1DAY or, where applicable, F=COMP 1DAY-REV holdout flow time series were applied to derivation of unregulated inflows. The -REV reflects manual adjustments made to observed reservoir elevation time series based on visual screening of anomalous data. These adjustments significantly reduced outlier holdouts (i.e., one-day changes from large negative to large positive values inconsistent with reservoir operational policy).

5.4.2 Net Evaporation

Calculation of net evaporation in the OOA basin applied evaporation and precipitation time series data previously described (Section 5.2.4) to post- and pre-reservoir runoff coefficients (ROCs), computed for the OOA basin as ratios of annual precipitation to runoff at representative unregulated stream gages at various locations in Georgia, shown on Figure 5-5.

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Figure 5-4 OOA Reservoir Location Map

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Figure 5-5 Georgia Representative Unregulated Flow Gaging Stations and Average Annual Runoff Coefficients

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Pre-development runoff coefficients applied to OOA reservoirs are listed in Table 5-4. For the post-reservoir condition, runoff coefficients are assumed to be unity (i.e., 100 percent runoff), and the resulting net evaporation relationship embodied in the reservoir effects DSS macros is as follows:

NEVAP (cfs) = [(EV(ft/day) – P(ft/day))*A(ac) + ROC*P(ft/day)*A(ac)] * 0.504 (dsf/ac-ft)

Table 5-4 ACF Reservoir Pre-Development Runoff Coefficients

A_Part B_Part Reservoir Name Runoff Coefficient Lake Jackson OOA-OCMULG JACKSON-JACKSN_R 0.30 Lake Oconee OOA-OCONEE MILLEDGE-OCONEE_R 0.25 Lake Sinclair OOA-OCONEE MILLEDGE-SNCLAIR_R 0.25

5.4.3 Net Reservoir Effects

Net reservoir effects are aggregate holdouts and net evaporation as previously described. However, these are applied at separate stages in development of unimpaired flows, as follows:

• Holdouts are applied during filling and routing for determination of local incremental flows.

• Net evaporation is applied as the remaining reservoir effect, in conjunction with net water use, in the determination of local incremental unimpaired flows.

A sample reservoir effects condensed catalog listing for Lake Sinclair net reservoir effects is provided in Table 5-5.

Table 5-5 Sample Lake Sinclair (MILLEDGE-SNCLR_R) Reservoir Effects HECDSS Condensed Catalog Listing (from OOARE.DSS , 2009-06-13 version) Tag A Part B Part C Part F Part E Part D Part T1701 OOA-OCONEE MILLEDGE-SNCLR_R AREA-ELEV OBS-GPC (null) TABLE T1702 ------AREA-RES EOP COMP 1DAY 01JAN1953 - 01JAN2007 T1757 ------ELEV-RES OBS-GPC 1DAY 01JAN1939 - 01JAN2008 T1827 ------OBS-GPC-CORR 1DAY 01JAN1939 - 01JAN2008 T1897 ------OBS-GPC-CORR-EOM 1DAY 01JAN1953 - 01JAN2007 T1952 ------EVAP ADJ HAMON 1DAY 01JAN1953 - 01JAN2007 T2007 ------NOAA EVAP ATLAS 1DAY 01JAN1953 - 01JAN2007 T2062 ------FLOW-EVAPNET POST RES 1DAY 01JAN1953 - 01JAN2007 T2117 ------POST-PRE RES 1DAY 01JAN1953 - 01JAN2007 T2172 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1953 - 01JAN2007 T2227 ------COMP DAY-INTWK 1DAY 01JAN1953 - 01JAN2007 T2282 ------COMP FMA7 1DAY 01JAN1953 - 01JAN2007

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Table 5-5 Sample Lake Sinclair (MILLEDGE-SNCLR_R) Reservoir Effects HECDSS Condensed Catalog Listing (from OOARE.DSS , 2009-06-13 version) T2337 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T2407 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T2477 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T2547 ------PRE-RES 1DAY 01JAN1938 - 01JAN1954 T2564 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1953 - 01JAN2007 T2619 ------PRECIP SERFC MAP 1DAY 01JAN1953 - 01JAN2007 T2674 ------STOR-ELEV OBS-GPC (null) TABLE T2675 ------STOR-RES EOP COMP 1DAY 01JAN1953 - 01JAN2007 T2730 ------COMP DAY-INTWK 1DAY 01JAN1953 - 01JAN2007

5.4.4 Minimum Reservoir Releases

Minimum reservoir releases prior to reservoir elevation time series data for Lake Jackson and Lake Sinclair were calculated using reference streamflow gages located upstream of reservoirs in relation to streamflow gages located downstream of the reservoirs. OOARGage.TSTOOL runs OOARGage.MCO in DSSMATH, which calculates Lake Jackson (JACKSN_R) minimum release effects from unregulated filled cumulative flows at JACKSON-02210500 using MCDONOUGH-02204500 as a reference gage from 10/1/39 – 10/1/60 and calculates Lake Sinclair (SNCLR_R) minimum release effects from observed cumulative flows at MILLEDGE-02223000 using BUCKHEAD-02219500 as a reference gage from 1/1/39 – 1/1/54. Both of these periods for each reservoir occur after reservoir construction but prior to the availability of elevation time series data for the reservoir. The OOARGage.MCO macro, a small computer program, calculates and removes the effects of regulation present in the portion of the period of record prior to the time for which reservoir elevation time series data are available. This removal of the said effects is accomplished by using observed cumulative flows at the next downstream gage from the reservoir and at a nearby upstream or tributary reference gage not affected by reservoir releases. Cumulative inflows at the gage downstream of the reservoir are determined by multiplying the ratio of annual downstream gage flow volume to annual reference gage flow volume times daily observed flows at the reference gage, for each year from 1939 to 1960 (for Lake Jackson) and from 1939 to 1954 (for Lake Sinclair).

5.5 Streamflow Filling, Routing, and Reservoir Inflows

Unimpaired flow development removes human impacts – net water uses and reservoir regulation (holdouts and net evaporation) – from observed streamflows or computed gross reservoir inflows. All 11 nodes in the OOA basin required complete streamflow time series for 1939 through 2007. Four of these nodes required some filling of their streamflow records.

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5.5.1 Methods Summary

Table 5-6 summarizes streamflow filling periods and methods for the four nodes in the OOA basin that required filling. The streamflow records of seven nodes in the study basin were complete over the required periods of analysis and consequently required no filling.

Table 5-6 OOA Streamflow Filling and Routing Summary

Filled Streamflow or Reservoir Node Inflow Period Filling Method/Gage(s) Used for Filling JACKSON 1/1/39 – 7/31/39 Remove Lake Jackson reservoir effects from Jackson to create Jackson unregulated. 10/1/60 – 9/30/75 Remove Lake Jackson reservoir effects from 10/1/82 – 2/28/87 Macon to create Macon unregulated. Fill Jackson unregulated with Macon unregulated back-routed and Griffin (ACF-Flint) using multiple linear regression (annual equation). PENFIELD 1//1/39 – 7/31/77 Fill with Greensboro shifted in time using MOVE2 regression (annual equation). VERNON 1/1/56 – 12/31/07 Compute local Vernon flow by subtracting routed Dublin from Vernon cumulative flow. Fill local Vernon flow using Reids shifted in time. Using MOVE2 regression (annual equation), sum filled local Vernon flow and routed Dublin to get Vernon cumulative flow.

BAXLEY 1/1/39 – 8/13/49 Fill with routed Lumber and back-routed 7/1/51 – 9/30/70 Doctown using multiple linear regression (annual equation).

Specific streamflow filling calculations employed for each of the four nodes that required filling are subsequently described.

5.5.2 Jackson (JACKSON)

The missing streamflow periods for Jackson noted in Table 5-6 were filled by using observed streamflows at Macon and Griffin (ACF-Flint). First, net reservoir effects were removed from cumulative observed streamflows at both Jackson and Macon. Next, Macon unregulated streamflow was back-routed to Jackson using the Lag-K routing model and negative calibrated lag parameters. A multiple linear regression was then developed between Jackson unregulated, Macon unregulated back-routed to Jackson, and observed Griffin. Finally, the multiple linear regression was applied to fill the

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Table 5-7 Annual Multiple Linear Regression Results: Jackson (Y), Macon (X1), and Griffin (X2)

Y = A + BX1 + CX2 Period A B C R2 Annual 201.08 0.5151 0.8789 0.8886

5.5.3 Penfield (PENFIELD)

The missing streamflow period for Penfield noted in Table 5-6 was filled using observed streamflow from Greensboro, which is located downstream of Penfield as shown on Figure 5-2. Greensboro flows were shifted back in time so that the timing of hydrograph peaks in the observed streamflow records for Greensboro and Penfield matched. Greensboro flows were shifted in time so that 70 percent of the flow occurred at time step 1 (t=0) and 30 percent of the flow occurred at time step 2 (t=1). This time shift of Greensboro flows in the TSTool command file was expressed as ShiftData=0,0.7,1,0.3. After the Greensboro streamflow record was shifted back in time, a MOVE2 regression between observed Penfield streamflow and Greensboro shifted streamflow was established and applied to fill the missing data period in the Penfield record. Table 5-8 lists the statistics of the annual MOVE2 regression equation used to fill Penfield using Greensboro streamflow shifted back in time.

Table 5-8 Annual MOVE2 Regression Statistical Results: Penfield (Y) and Greensboro (X)

Y = A + BX Period A B R2 Annual –65.3 0.97 0.968

Although less than one year of observed data overlapped for the Penfield and Greensboro gages, the correlation statistics showed the Greensboro gage to be highly correlated with Penfield flows. To further investigate whether Greensboro flows were appropriate to use to fill Penfield flows, Penfield flows were filled using a MOVE2 monthly regression with Athens, which had a complete period of record for the study period. The filled Penfield streamflow time series using the regression with Athens was then compared to the filled Penfield streamflow time series using an annual MOVE2

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5.5.4 Vernon (VERNON)

The missing streamflow period for Vernon noted in Table 5-6 was filled by computing the local Vernon streamflow by routing observed Dublin streamflow downstream to Vernon and subtracting the routed Dublin streamflow from the observed Vernon streamflow. Negative streamflow values in the resulting Vernon local flow were then eliminated by setting all negative values to zero so that a linear regression could be established with Reids (Figure 5-2). Observed streamflow at Reids was shifted earlier in time by 1.6 days (lag time = –1.6 days) to align its streamflow peaks with those observed at Vernon. Next, an annual MOVE2 regression between observed local Vernon streamflow and shifted Reids was established and applied to fill the missing local Vernon streamflow data. Finally, the filled local Vernon streamflow was summed with the routed Dublin to determine the cumulative Vernon streamflow for the missing period.

Table 5-9 Annual MOVE2 Regression Statistical Results: Vernon Local (Y) and Reids (X)

Y = A + BX Period A B R2 Annual 80.88 0.59 0.6554

5.5.5 Baxley (BAXLEY)

The missing streamflow periods for Baxley noted in Table 5-6 were filled by using observed streamflows at Lumber and Doctown. Lumber observed streamflow was routed downstream to Baxley using the Lag-K routing model and calibrated variable lag k parameters. Next, Doctown observed streamflow was back-routed to Baxley using the Lag-K routing model and negative calibrated lag parameters. A multiple linear regression was then developed between Baxley, Lumber streamflow routed downstream to Baxley, and Doctown streamflow back-routed to Baxley. Finally, the multiple linear regression was applied to fill the missing periods of the Baxley

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Table 5-10 Annual Multiple Linear Regression Results: Baxley (Y), Lumber (X1), and Doctown (X2)

Y = A + BX1 + CX2 Period A B C R2 Annual –51.58 0.488 0.6469 0.9757

5.6 Local Incremental Flow Calculation and Adjustments

Calculations described above produced complete time series (no missing data) of cumulative “semi-impaired” flows (i.e., reservoir holdouts removed but net evaporation and water use remaining included) and reservoir inflows and outflows over the required PORs. The Jackson node is an exception to this, however, because net reservoir effects were removed during the Jackson streamflow filling as described in the methodology in Section 5.5.2. Local incremental flows were next calculated by subtraction of routed upstream cumulative flows from downstream cumulative flows. For headwater nodes, local incremental flows are the same as cumulative flows. For downstream nodes, local incremental flows were computed using TSTool commands executing the following steps:

• Read upstream filled (as needed) cumulative flow time series.

• Route the upstream cumulative flow time series to the downstream location.

• Subtract the routed upstream cumulative flows from the downstream cumulative filled time series, resulting in local (impaired) incremental flow at the downstream location.

For reservoirs, the filled reservoir inflow time series was used in the local incremental flow calculation for the reservoir node. The reservoir outflow time series was used in the local incremental flow calculation for the node downstream of the reservoir.

As previously stated, local incremental flows do not yet represent unimpaired flows. Water withdrawals, agricultural diversions, return flows, reservoir net evaporation (except for the Jackson node as explained in the filling methodology in Section 5.5.2),

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In some reaches, negative local incremental flows resulted from the subtraction of routed upstream cumulative flows from downstream cumulative flows. These negative values result from a variety of causes, including routing discrepancies (e.g., lag times), errors in observed flow values, and water use or losses to groundwater. Adjustments to remove negative local incremental flows were limited to refinements to filling and/or routing procedures, with final adjustments to remove all negative local incremental flows performed after final aggregation of local incremental flows, reach net water uses, and remaining reservoir effects in the unimpaired local incremental flows.

Table 5-11 lists TSTool command files and HECDSS macros applied to OOA filling, routing, and local incremental flow calculation.

Table 5-11 TSTool Command and HECDSS Macro File Listing for OOA Basin Local Incremental Flow Determination

Runs all commands for OOA filling and local incremental flow computations in Run_OOA_Filling.TSTool necessary order. The order of the commands is represented in this table. Populates OOAFill.dss with observed InitialPopulate_OOA_dss.TSTool streamflows used in all calculations. JACKSON_fill-MLR.TSTool Streamflow filling for Jackson node. PENFIELD_fill.TSTool Streamflow filling for Penfield node. Vernon_fill_rev.TSTool Streamflow filling for Vernon node. BAXLEY_fill-MLR.TSTool Streamflow filling for Baxley node. Runs OOARGage.MCO as DSSMATH, which calculates minimum reservoir releases from Lake Jackson prior to 1960 OOARGage.TSTOOL (when reservoir data begins) and from Lake Sinclair prior to 1954 (when reservoir data begins). Computes local incremental flows at ComputeLocalIncrementals_OOA.TSTool non-headwater nodes in the OOA basin.

5.7 Local Incremental Unimpaired Flow Calculation

The final stage of local incremental unimpaired flow determination involves aggregation and removal of remaining impairments (human influences) – principally reservoir

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5.7.1 Negative Local Unimpaired Flow Adjustments

A no-negative local incremental unimpaired flow approach was adopted for this study, in consideration of potential application to water availability assessments subject to various minimum flow constraints, including annual or monthly 7Q10 (10-year 7-day low flow). Moreover, many reservoir system operational models do not allow for negative local incremental flows. The utility of unimpaired flows computed in this study is maximized by systematic “intelligent” removal of negative values with minimal alteration to surrounding non-negative values, as opposed to cruder methods employed by operational models.

While negative local incremental flows were removed to the maximum extent possible by refinements to reservoir holdouts, routing and filling procedures, and short-duration (six days) smoothing and averaging, some residual negatives remained at the unimpaired flow determination stage. To remove these, three approaches were employed, listed as follows in order of minimum number of adjacent time periods adjusted:

• The AdjustExtreme TSTool procedure, which averages values on either side of the negative value for as many days as necessary to produce a non-negative result. This method works best with intermittent as opposed to continuous periods of negative flows. Where extended periods of negative flows occur, the AdjustExtreme procedure produces multi-month periods of constant low flow.

• Annual adjustment – A DSSMATH procedure that increases all negative flows to zero and reduces all positive values by a factor equal to the ratio of the original (with negatives) annual average flow to the adjusted (no negatives) annual average flow.

• POR adjustment – Same as annual adjustment with the reduction factor computed using 1939 to 2007 POR average flow ratios.

5.7.2 Selection of Final Local Unimpaired Flow Time Series

Final local unimpaired flow selection is predicated on the basic requirement for no residual negative flows in the following order of preference:

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• Unadjusted unimpaired flow (F = UNIMP)

• TSTool AdjustExtreme method, assuming no continuous constant-flow periods greater than the annual or POR adjustment (F = UNIMP–0ADJ LOC)

• DSSMATH annual adjustment (F = UNIMP–0ADJ ANNUAL)

• DSSMATH POR adjustment (F = UNIMP–0ADJ POR)

• DSSMATH adjustment for three-day smoothing (F = UNIMP–0ADJ LOC-3)

Final local unimpaired flow time series selection is denoted by an asterisk at the end of the F pathname denoting the adjustment required, e.g., F= UNIMP-0ADJ ANNUAL*. Example OOA DSS pathnames for unimpaired flows and local inflow, reservoir effects, and water use constituents are provided in Table 5-12.

Table 5-12 Example Condensed Catalog Listing of OOA Unimpaired Flow and Component Time Series Tag A Part B Part C Part F Part E Part D Part

T1 OOA-ALTAMA BAXLEY FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T70 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T139 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T208 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T277 ------FLOW-LOC INC COMP-0ADJ LOC-3 1DAY 01JAN1939 - 01JAN2007 T346 ------UNIMP 1DAY 01JAN1938 - 01JAN2007 T416 ------UNIMP-0ADJ ANNUAL 1DAY 01JAN1938 - 01JAN2007 T486 ------UNIMP-0ADJ LOC 1DAY 01JAN1939 - 01JAN2007 T555 ------UNIMP-0ADJ POR 1DAY 01JAN1938 - 01JAN2007 T625 ------UNIMP-0ADJ POR* 1DAY 01JAN1939 - 01JAN2007

5.8 Quality Control

Because primary quality control was performed at each stage of OOA basin unimpaired flow development (water use data, reservoir effects, and filling/routing), final stage quality control relied on (1) visual inspection of average local unimpaired flow plots and (2) consistency plots, in which individual nodes are grouped and differences between accumulated unimpaired flow for individual nodes and average accumulated unimpaired flow for the group are compared. These checks revealed no major discrepancies in the local unimpaired flow data.

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5.9 Cumulative Unimpaired Flows

Following Georgia EPD approval of local unimpaired flow data documented in this report, partial and full cumulative unimpaired flow time series data will be developed by aggregation and routing of applicable upstream local, partial cumulative, and cumulative unimpaired flows to downstream nodes. Cumulative unimpaired flows will be calculated for all basic and planning nodes. Unimpaired flows computed for each planning node are also termed sub-basin unimpaired flows.

5.10 Conclusions

Adjustments to remove negative local unimpaired flows from the existing 1939 to 2007 data may be desirable to ensure their suitability for (1) combining and routing to produce various cumulative unimpaired flow time series at planning or multiple basic nodes, and (2) calculating low-flow statistics imposed as constraints on water availability assessments performed using the River Basin Planning Tool. If negative adjustments are required, approaches to adjust zeros on a local, annual, and entire period of record basis (e.g., AdjustExtreme, annual, and POR adjustments) are recommended.

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6. Savannah and Ogeechee (SO) River Basins

6.1 SO Basin Description

The Savannah River basin is located in northern and eastern Georgia, originating in the Blue Ridge Mountains at the common border of Georgia, North Carolina, and South Carolina. The basin forms the Georgia–South Carolina border and flows through the Mountain, Piedmont, and Coastal Plains physiographic regions to the Atlantic Ocean. Total drainage area at the Savannah River basin is 10,577 square miles, of which 175 square miles are in southwestern North Carolina and 4,581 square miles lie in western South Carolina. The Savannah River basin is characterized by mild winters and hot summers in the lower portions, and cold winters and mild summers in the mountain area. Mean annual precipitation ranges from 40 inches to 80 inches. Precipitation occurs principally as rainfall, distributed fairly uniformly throughout the year but with a dry season from mid-summer to late fall. Rainfall is usually greatest in March and least in October. Mean annual temperature in the basin is approximately 65 degrees Fahrenheit.

The Savannah River upstream of Augusta is highly regulated by three large multipurpose USACE reservoirs – Hartwell, Richard B. Russell, and Thurmond – and by a number of private power reservoirs, including several small Georgia Power projects (Burton, Nacoochee, Rabun, Tallulah Falls, Tugaloo, and Yonah) and Duke Energy’s Keowee–Jocassee pumped-storage project. Downstream of Augusta are the USACE New Savannah Bluff Lock and Dam and the South Carolina Electric and Gas Stevens Creek projects, both of which are essentially operated as run-of-river projects.

The Ogeechee River basin is located in southeastern Georgia between the Altamaha and Oconee River basins to the west, and the Savannah basin to the north and east. The headwaters are located in the southeastern edge of the Piedmont physiographic region, and the river flows 245 miles in a southeasterly direction to the Atlantic Ocean. The Ogeechee River basin is located entirely within the state of Georgia and drains approximately 5,540 square miles. There are no large storage reservoirs or hydroelectric projects in the Ogeechee River basin, though there are numerous small lakes, reservoirs, and farm ponds.

The SO study basin map showing node locations and LDAs for each is shown on Figure 6-1. General procedures for unimpaired flow development are described in Section 2 of this report.

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Figure 6-1 SO Study Basin Basic and Planning Nodes

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6.2 Hydrological Data

6.2.1 Existing Unimpaired Flows

USGS estimated inflow hydrographs for time series input to HEC-5 reservoir system models being developed and applied by the USACE Savannah District. 4 Local incremental flows were estimated at the following locations:

• Tugaloo River at the Seneca River confluence

• Hartwell Dam (excluding Tugaloo River basin)

• Richard B. Russell Dam

• Thurmond Dam

• Savannah River at Augusta, Georgia

• Savannah River near Jackson, Georgia

• Savannah River at Burtons Ferry, Georgia

• Savannah River near Clyo, Georgia

• Savannah River at Savannah, Georgia

USGS data were determined not to be suited to the purposes of this study for the following reasons:

• Only LDAs for Russell, Thurmond, Augusta, and Savannah match basic and planning node LDAs shown on Figure 6-1.

4Sanders, Curtis L. and Stamey, Timothy C., July 2, 2002. Estimated Inflows to the Savannah River, Georgia and South Carolina for the 1940 – 2000 Water Years. Report prepared for USGS and USACE Savannah District.

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• USGS flow data appear to have been estimated using gage relationships without consideration of reservoir operational data (elevations, computed inflows, and outflows) applied to calculation of reservoir effects (holdouts and net evaporation) and unregulated flows.

• Effects of water withdrawals and discharges do not appear to have been removed from USGS-computed flows.

• The 1940 to 2000 USGS period of calculated daily flows data does not span the complete 1939 to 2007 period of analysis for this study.

In summary, because the USGS data reflect statistical relationships between gaged and ungaged and regulated and unregulated streams, as opposed to observed streamflow, reservoir operational, and water use data, they are better estimators of unregulated than unimpaired flows.

6.2.2 Streamflow Records

Stream gages applied to derivation of local incremental flows in the SO basin are located as shown on Figure 6-2, with applicable periods of record shown on Figure 6-3.

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Figure 6-2 Nodes and Gages Associated with SO Study Basin Streamflow Filling

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Figure 6-3 Periods of Record for Gages Associated with SO Study Basin Streamflow Filling

6.3 Water Use Data

The Water Use Data Inventory Report documents measured and hindcasted (1939 to present) surface water consumptive water uses within the SO basin of the following types:

• Municipal (M) and industrial (I) water use (withdrawals and returns) in Georgia and South Carolina

• Thermal power (T) water use (withdrawals, discharges/returns, and net consumption) in Georgia and South Carolina

• Agricultural irrigation (A) water use in Georgia

Net uses of each type are aggregated by reach and summed to produce an aggregate water demand for each reach. Reach aggregate water use is added to local incremental flows and combined with reservoir effects as applicable (both subsequently described) to produce local incremental unimpaired flows. HECDSS pathnames for SO water uses are listed in Table 6-1.

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Table 6-1 HECDSS Condensed Catalog Listing of SO Study Basin Water Use Data (SO-WU.DSS, 2009-06-29 version)

HECDSS Condensed Catalog of Record Pathnames in File f:\zzd\SO-WU.dss

Catalog Created on Jun 20, 2009 at 20:05 File Created on May 2, 2009 Number of Records: 1888 DSS Version 6-MY, File 6-MY Sort Order: ABCFED

Tag A Part B Part C Part F Part E Part D Part

T1 SO-BRIRCR MILLHAVN FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T71 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T141 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T145 SO-BROAD BELL FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T215 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T285 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T289 SO-CNOOCH CLAXTON FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T359 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T429 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T433 SO-OGCHEE EDEN FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T503 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T573 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T577 - - - - KINGSFY FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T647 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T717 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T721 SO-SAVNAH AUGUSTA FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T791 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T861 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T865 - - - - BURTONS FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T935 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T1005 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T1009 - - - - BURTONS-VOGTLE-C FLOW-DIV NET MGD OBS-GA POWER 1MON 01JAN1970 - 01JAN2000 T1013 ------OBS-GA POWER REV 1MON 01JAN1970 - 01JAN2000 T1017 - - - - CLYO FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T1087 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T1157 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T1161 - - - - HARTWL_R FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T1231 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T1301 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T1305 - - - - RBR_R FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T1375 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T1445 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T1449 - - - - SAVANNAH FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T1519 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T1589 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T1593 - - - - SAVANNAH-MCINTSH-C FLOW-DIV NET MGD OBS-GA POWER 1MON 01JAN1970 - 01JAN2000 T1597 ------OBS-GA POWER REV 1MON 01JAN1970 - 01JAN2000 T1601 - - - - THRMND_R FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T1671 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T1741 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000 T1745 SO-SENECA KEOWEE_R FLOW-DIV NET COMP-REACH-I 1DAY 01JAN1938 - 01JAN2007 T1815 ------COMP-REACH-M 1DAY 01JAN1938 - 01JAN2007 T1885 ------FLOW-DIV WD SW COMP-EPD AVG DEPTH 1MON 01JAN1970 - 01JAN2000

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6.4 Reservoir Effects

For purposes of SO basin unimpaired flow development, reservoir effects were computed for 10 federal and private power storage reservoirs, but ignored for small run-of-river projects downstream of Augusta, where evaporation losses are small and holdouts negligible. Figure 6-4 shows the locations of SO reservoirs for which reservoir effects were calculated.

6.4.1 Reservoir Operational Data

Daily operational data (pool elevations, releases, and computed inflows) were obtained in electronic form for the three SO basin multipurpose federal reservoirs from the time each project was placed in service through 2007 (Hartwell – 1962, Russell – 1984, and Thurmond – 1952). Daily elevation data were also available for a few of the Georgia Power reservoirs in the basin dating back to the early 1960s, although most of these reservoirs have been in operation since 1939. Operational data for Duke Energy’s Keowee and Jocassee reservoirs were not available at the time of SO unimpaired flow development, but are currently being developed and applied to determination of unimpaired flows at the KEOWEE_R planning node. Smaller locks/dams, mill ponds, and hydro projects located downstream of Augusta were not considered in this study because of their small surface areas and run-of-river operations.

6.4.2 Holdouts

For the three large federal SO reservoirs (Hartwell, Russell, and Thurmond), holdout flows were highly sensitive to slight misreadings or erroneous reservoir elevation time series. The Savannah District indicated that computed inflows and outflows were corrected for erroneous pool elevations, but that pool elevation data posted on its web site were uncorrected. Because the uncorrected elevation data produced extremely noisy holdout flows (example shown on Figure 6-5), with project releases from storage frequently greater than power plant capacity, it was elected to use USACE-computed reservoir inflows and outflows as the basis for local incremental flows.

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Figure 6-4 SO Study Basin Reservoir Location Map

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Figure 6-5 THRMND_R Computed One-Day Holdout Flows

Monthly elevation time series data for the Georgia Power reservoirs (Burton, Nacoochee, Rabun, Tallulah Falls, Tugaloo, and Yonah) were converted to daily interpolated values, resulting in computed holdout flows with significantly less variability than would be expected with daily elevation readings. Constant normal pool elevations were assumed for Georgia Power reservoirs from the times the reservoirs were placed into service to the date of the first available monthly recorded elevation data. Daily pool elevations were interpolated from the monthly pool elevation data prior to the start of daily pool elevation records. As a consequence, Georgia Power reservoir holdout flow time series exhibit progressively increasing variability, an example of which is shown on Figure 6-6.

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Figure 6-6 Burton Reservoir Computed One-Day Holdout Flows

6.4.3 Net Evaporation

Calculation of net evaporation in the SO basin applied evaporation and precipitation time series to the post- and pre-reservoir ROC, computed for the SO basin as described in Section 2 of this report.

6.4.4 Net Reservoir Effects

Net reservoir effects are the sum of holdout and net evaporation flows. The adopted sign convention – positive holdouts, negative releases from storage, positive evaporation, negative precipitation, and pre-reservoir runoff – allow reservoir effects to be added to calculated local incremental flows to produce unregulated local incremental flows. For net water uses following the same sign convention, i.e., positive withdrawals, negative returns are added to local incremental flows to produce unimpaired local incremental flows. The HECDSS condensed catalog SO basin reservoir effects data are listed in Table 6-2.

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Table 6-2 SO Study Basin Reservoir Effects HECDSS Condensed Catalog Listing (from SORE.DSS, 2009-06-21 version) HECDSS Condensed Catalog of Record Pathnames in File f:\zzd\SORE.dss

Catalog Created on Jun 21, 2009 at 2:56 File Created on May 23, 2009 Number of Records: 11388 DSS Version 6-MY, File 6-MY Sort Order: ABCFED

Tag A Part B Part C Part F Part E Part D Part

T1 SO-SAVNAH HARTWL_R AREA-ELEV OBS-USACE (null) TABLE T2 ------AREA-RES OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T72 ------AREA-RES EOP COMP 1DAY 01JAN1961 - 01JAN2007 T119 ------ELEV-RES OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T189 ------EVAP ADJ HAMON 1DAY 01JAN1961 - 01JAN2007 T236 ------NOAA EVAP ATLAS 1DAY 01JAN1961 - 01JAN2007 T283 ------FLOW-EVAPNET POST RES 1DAY 01JAN1961 - 01JAN2007 T330 ------POST-PRE RES 1DAY 01JAN1961 - 01JAN2007 T377 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1961 - 01JAN2007 T424 ------COMP DAY-INTWK 1DAY 01JAN1961 - 01JAN2007 T471 ------COMP FMA7 1DAY 01JAN1961 - 01JAN2007 T518 ------OBS-RECON 1DAY 1DAY 01JAN1961 - 01JAN2007 T565 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T634 ------COMP DAY-INTWK 1DAY 01JAN1939 - 01JAN2007 T703 ------COMP FMA7 1DAY 01JAN1939 - 01JAN2007 T772 ------PRE-RES 1DAY 01JAN1939 - 01JAN1962 T796 ------FLOW-RES IN COMP+NEVAP 1DAY 1DAY 01JAN1961 - 01JAN2007 T843 ------COMP+NEVAP 1DAY NONEG 1DAY 01JAN1962 - 01JAN2007 T889 ------COMP-RECON 1DAY 1DAY 01JAN1961 - 01JAN2007 T936 ------OBS-RECON 1DAY 1DAY 01JAN1961 - 01JAN2007 T983 ------FLOW-RES OUT OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T1053 ------FLOW-RES TOT INFLOW OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T1123 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1961 - 01JAN2007 T1170 ------PRECIP SERFC MAP 1DAY 01JAN1961 - 01JAN2007 T1217 ------STOR-CHANGE COMP 1DAY 01JAN1962 - 01JAN2007 T1263 ------OBS-RECON 1DAY 01JAN1962 - 01JAN2007 T1309 ------STOR-ELEV OBS-USACE (null) TABLE T1310 ------STOR-RES OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T1380 ------STOR-RES EOP COMP 1DAY 01JAN1961 - 01JAN2007 T1427 ------COMP DAY-INTWK 1DAY 01JAN1961 - 01JAN2007 T1474 - - - - HARTWL_R-BURTON_R AREA-ELEV OBS-GPC (null) TABLE T1475 ------AREA-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T1545 ------ELEV-RES OBS-GPC 1DAY 01JAN1939 - 01JAN2009 T1616 ------OBS-GPC-REV 1DAY 01JAN1939 - 01JAN2009 T1687 ------EVAP ADJ HAMON 1DAY 01JAN1938 - 01JAN2007 T1757 ------NOAA EVAP ATLAS 1DAY 01JAN1938 - 01JAN2007 T1827 ------FLOW-EVAPNET POST RES 1DAY 01JAN1938 - 01JAN2007 T1897 ------POST-PRE RES 1DAY 01JAN1938 - 01JAN2007 T1967 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T2037 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T2107 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T2177 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T2247 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T2317 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T2387 ------PRE-RES 1DAY 01JAN1938 - 01JAN1939 T2389 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1938 - 01JAN2007 T2459 ------PRECIP SERFC MAP 1DAY 01JAN1938 - 01JAN2007 T2529 ------STOR-ELEV OBS-GPC (null) TABLE T2530 ------STOR-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T2600 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T2670 - - - - HARTWL_R-NACOCH_R AREA-ELEV OBS-GPC (null) TABLE T2671 ------AREA-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T2741 ------ELEV-RES OBS-GPC 1DAY 01JAN1939 - 01JAN2009

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Table 6-2 SO Study Basin Reservoir Effects HECDSS Condensed Catalog Listing (from SORE.DSS, 2009-06-21 version) T2812 ------EVAP ADJ HAMON 1DAY 01JAN1938 - 01JAN2007 T2882 ------NOAA EVAP ATLAS 1DAY 01JAN1938 - 01JAN2007 T2952 ------FLOW-EVAPNET POST RES 1DAY 01JAN1938 - 01JAN2007 T3022 ------POST-PRE RES 1DAY 01JAN1938 - 01JAN2007 T3092 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T3162 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T3232 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T3302 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T3372 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T3442 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T3512 ------PRE-RES 1DAY 01JAN1938 - 01JAN1939 T3514 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1938 - 01JAN2007 T3584 ------PRECIP SERFC MAP 1DAY 01JAN1938 - 01JAN2007 T3654 ------STOR-ELEV OBS-GPC (null) TABLE T3655 ------STOR-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T3725 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T3795 - - - - HARTWL_R-RABUN_R AREA-ELEV OBS-GPC (null) TABLE T3796 ------AREA-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T3866 ------ELEV-RES OBS-GPC 1DAY 01JAN1939 - 01JAN2009 T3937 ------EVAP ADJ HAMON 1DAY 01JAN1938 - 01JAN2007 T4007 ------NOAA EVAP ATLAS 1DAY 01JAN1938 - 01JAN2007 T4077 ------FLOW-EVAPNET POST RES 1DAY 01JAN1938 - 01JAN2007 T4147 ------POST-PRE RES 1DAY 01JAN1938 - 01JAN2007 T4217 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T4287 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T4357 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T4427 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T4497 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T4567 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T4637 ------PRE-RES 1DAY 01JAN1938 - 01JAN1939 T4639 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1938 - 01JAN2007 T4709 ------PRECIP SERFC MAP 1DAY 01JAN1938 - 01JAN2007 T4779 ------STOR-ELEV OBS-GPC (null) TABLE T4780 ------STOR-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T4850 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T4920 - - - - HARTWL_R-TALLUL_R AREA-ELEV OBS-GPC (null) TABLE T4921 ------AREA-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T4991 ------ELEV-RES OBS-GPC 1DAY 01JAN1939 - 01JAN2009 T5062 ------EVAP ADJ HAMON 1DAY 01JAN1938 - 01JAN2007 T5132 ------NOAA EVAP ATLAS 1DAY 01JAN1938 - 01JAN2007 T5202 ------FLOW-EVAPNET POST RES 1DAY 01JAN1938 - 01JAN2007 T5272 ------POST-PRE RES 1DAY 01JAN1938 - 01JAN2007 T5342 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T5412 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T5482 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T5552 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T5622 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T5692 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T5762 ------PRE-RES 1DAY 01JAN1938 - 01JAN1939 T5764 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1938 - 01JAN2007 T5834 ------PRECIP SERFC MAP 1DAY 01JAN1938 - 01JAN2007 T5904 ------STOR-ELEV OBS-GPC (null) TABLE T5905 ------STOR-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T5975 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T6045 - - - - HARTWL_R-TUGALO_R AREA-ELEV OBS-GPC (null) TABLE T6046 ------AREA-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T6116 ------ELEV-RES OBS-GPC 1DAY 01JAN1939 - 01JAN2009 T6187 ------EVAP ADJ HAM 1DAY 01JAN1938 - 01JAN2007 T6257 ------NOAA EVAP ATLAS 1DAY 01JAN1938 - 01JAN2007 T6327 ------FLOW-EVAPNET POST RES 1DAY 01JAN1938 - 01JAN2007 T6397 ------POST-PRE RES 1DAY 01JAN1938 - 01JAN2007

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Table 6-2 SO Study Basin Reservoir Effects HECDSS Condensed Catalog Listing (from SORE.DSS, 2009-06-21 version) T6467 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T6537 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T6607 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T6677 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T6747 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T6817 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T6887 ------PRE-RES 1DAY 01JAN1938 - 01JAN1939 T6889 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1938 - 01JAN2007 T6959 ------PRECIP SERFC MAP 1DAY 01JAN1938 - 01JAN2007 T7029 ------STOR-ELEV OBS-GPC (null) TABLE T7030 ------STOR-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T7100 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T7170 - - - - HARTWL_R-YONAH_R AREA-ELEV OBS-GPC (null) TABLE T7171 ------AREA-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T7241 ------ELEV-RES OBS-GPC 1DAY 01JAN1939 - 01JAN2009 T7312 ------EVAP ADJ HAM 1DAY 01JAN1938 - 01JAN2007 T7382 ------NOAA EVAP ATLAS 1DAY 01JAN1938 - 01JAN2007 T7452 ------FLOW-EVAPNET POST RES 1DAY 01JAN1938 - 01JAN2007 T7522 ------POST-PRE RES 1DAY 01JAN1938 - 01JAN2007 T7592 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T7662 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T7732 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T7802 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1938 - 01JAN2007 T7872 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T7942 ------COMP FMA7 1DAY 01JAN1938 - 01JAN2007 T8012 ------PRE-RES 1DAY 01JAN1938 - 01JAN1939 T8014 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1938 - 01JAN2007 T8084 ------PRECIP SERFC MAP 1DAY 01JAN1938 - 01JAN2007 T8154 ------STOR-ELEV OBS-GPC (null) TABLE T8155 ------STOR-RES EOP COMP 1DAY 01JAN1938 - 01JAN2007 T8225 ------COMP DAY-INTWK 1DAY 01JAN1938 - 01JAN2007 T8295 - - - - RBR_R AREA-ELEV OBS-USACE (null) TABLE T8296 ------AREA-RES OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T8366 ------AREA-RES EOP COMP 1DAY 01JAN1984 - 01JAN2007 T8390 ------ELEV-RES OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T8460 ------EVAP ADJ HAMON 1DAY 01JAN1984 - 01JAN2007 T8484 ------NOAA EVAP ATLAS 1DAY 01JAN1984 - 01JAN2007 T8508 ------FLOW-EVAPNET POST RES 1DAY 01JAN1984 - 01JAN2007 T8532 ------POST-PRE RES 1DAY 01JAN1984 - 01JAN2007 T8556 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1984 - 01JAN2007 T8580 ------COMP DAY-INTWK 1DAY 01JAN1984 - 01JAN2007 T8604 ------COMP FMA7 1DAY 01JAN1984 - 01JAN2007 T8628 ------OBS-RECON 1DAY 1DAY 01JAN1984 - 01JAN2007 T8652 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T8721 ------COMP DAY-INTWK 1DAY 01JAN1939 - 01JAN2007 T8790 ------COMP FMA7 1DAY 01JAN1939 - 01JAN2007 T8859 ------PRE-RES 1DAY 01JAN1939 - 01JAN1985 T8906 ------FLOW-RES IN COMP+NEVAP 1DAY 1DAY 01JAN1984 - 01JAN2007 T8930 ------COMP+NEVAP 1DAY NONEG 1DAY 01JAN1985 - 01JAN2007 T8953 ------COMP-RECON 1DAY 1DAY 01JAN1984 - 01JAN2007 T8977 ------OBS-RECON 1DAY 1DAY 01JAN1984 - 01JAN2007 T9001 ------FLOW-RES OUT OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T9071 ------FLOW-RES TOT INFLOW OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T9141 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1984 - 01JAN2007 T9165 ------PRECIP SERFC MAP 1DAY 01JAN1984 - 01JAN2007 T9189 ------STOR-CHANGE COMP 1DAY 01JAN1984 - 01JAN2007 T9213 ------OBS-RECON 1DAY 01JAN1984 - 01JAN2007 T9237 ------STOR-ELEV OBS-USACE (null) TABLE T9238 ------STOR-RES OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T9308 ------STOR-RES EOP COMP 1DAY 01JAN1984 - 01JAN2007 T9332 ------COMP DAY-INTWK 1DAY 01JAN1984 - 01JAN2007

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Table 6-2 SO Study Basin Reservoir Effects HECDSS Condensed Catalog Listing (from SORE.DSS, 2009-06-21 version) T9356 - - - - THRMND_R AREA-ELEV OBS-USACE (null) TABLE T9357 ------AREA-RES OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T9427 ------AREA-RES EOP COMP 1DAY 01JAN1953 - 01JAN2007 T9482 ------ELEV-RES OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T9552 ------EVAP ADJ HAMON 1DAY 01JAN1953 - 01JAN2007 T9607 ------NOAA EVAP ATLAS 1DAY 01JAN1953 - 01JAN2007 T9662 ------FLOW-EVAPNET POST RES 1DAY 01JAN1953 - 01JAN2007 T9717 ------POST-PRE RES 1DAY 01JAN1953 - 01JAN2007 T9772 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1953 - 01JAN2007 T9827 ------COMP DAY-INTWK 1DAY 01JAN1953 - 01JAN2007 T9882 ------COMP FMA7 1DAY 01JAN1953 - 01JAN2007 T9937 ------OBS-RECON 1DAY 1DAY 01JAN1953 - 01JAN2007 T9992 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T10061 ------COMP DAY-INTWK 1DAY 01JAN1939 - 01JAN2007 T10130 ------COMP FMA7 1DAY 01JAN1939 - 01JAN2007 T10199 ------PRE-RES 1DAY 01JAN1939 - 01JAN1954 T10215 ------FLOW-RES IN COMP+NEVAP 1DAY 1DAY 01JAN1953 - 01JAN2007 T10270 ------COMP+NEVAP 1DAY NONEG 1DAY 01JAN1954 - 01JAN2007 T10324 ------COMP-RECON 1DAY 1DAY 01JAN1953 - 01JAN2007 T10379 ------OBS-RECON 1DAY 1DAY 01JAN1953 - 01JAN2007 T10434 ------FLOW-RES OUT OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T10504 ------FLOW-RES TOT INFLOW OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T10574 ------FLOW-RUNOFF PRE RES 1DAY 01JAN1953 - 01JAN2007 T10629 ------PRECIP SERFC MAP 1DAY 01JAN1953 - 01JAN2007 T10684 ------STOR-CHANGE COMP 1DAY 01JAN1953 - 01JAN2007 T10739 ------OBS-RECON 1DAY 01JAN1953 - 01JAN2007 T10794 ------STOR-ELEV OBS-USACE (null) TABLE T10795 ------STOR-RES OBS-USACE 1DAY 01JAN1939 - 01JAN2008 T10865 ------STOR-RES EOP COMP 1DAY 01JAN1953 - 01JAN2007 T10920 ------COMP DAY-INTWK 1DAY 01JAN1953 - 01JAN2007 T10975 SO-SENECA KEOWEE_R EVAP ADJ HAMON 1DAY 01JAN1939 - 01JAN2007 T11044 ------NOAA EVAP ATLAS 1DAY 01JAN1939 - 01JAN2007 T11113 ------PRECIP SERFC MAP 1DAY 01JAN1939 - 01JAN2007 T11182 - - - - KEOWEE_R-JOCASS_R EVAP ADJ HAMON 1DAY 01JAN1939 - 01JAN2007 T11251 ------NOAA EVAP ATLAS 1DAY 01JAN1939 - 01JAN2007 T11320 ------PRECIP SERFC MAP 1DAY 01JAN1939 - 01JAN2007

6.5 Streamflow Filling, Routing, and Reservoir Inflows

All nodes in the SO basin required complete local incremental flow time series to be developed from 1939 through 2007.

6.5.1 Methods Summary

Table 6-3 summarizes streamflow filling completed for the SO basin. The BELL, MILLHAVN, EDEN, and CLAXTON streamflow time series were complete over the analysis period and required no filling. Because KEOWEE_R inflows, outflows, and upstream Duke Energy reservoir effects were unavailable at the time of writing, computed HARTWL_R inflows were cumulative flows for both the Hartwell and Keowee local drainage areas.

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Table 6-3 SO Study Basin Streamflow Filling and Routing Summary

Filled Streamflow or Node Reservoir Inflow Period Filling Method/Gage(s) Used for Filling AUGUSTA and Varies Linear interpolation CLYO BURTONS 1/39 – 9/39 Routed Augusta/Annual MOVE2 using Millhaven 10/75 – 9/82 Routed Augusta/multiple linear regression (Millhaven, Salkehatchie) 10/15/03 – 9/30/04 Routed Augusta/multiple linear regression (Millhaven, Salkehatchie) KINGSFY 1/1/39 – 12/31/07 Filled using data from Claxton and Eden HARTWL_R 1/39 – 12/49 Outflow: Monthly MOVE2/back-routed Calhoun Falls – Bell 1/50 – 4/23/62 Outflow: Monthly MOVE2/back-routed Iva – Beaverdam Creek RBR_R 1/39 – 9/79 Outflow: Calhoun Falls 10/79 – 11/84 Outflow: Hartwell releases/monthly MOVE2/back- routed Calhoun Falls – Bell SAVANNAH 1/1/39 – 12/31/07 Filled using data from Eden, Millhaven, and Clyo THRMND_R 1/1/39 – 5/13/40 Back-routed Augusta – filled local Augusta with Millhaven and SF_Edisto multiple linear regression 5/14/40 – 1/1/54 Clarks Hill

Specific filling and holdout calculations are subsequently described.

6.5.2 Reservoir Time Series Adjustments

Recorded reservoir time series required various adjustments for the Hartwell, Russell, and Thurmond USACE reservoirs located on the Savannah River.

Initial investigations revealed that net inflows computed from recorded project outflows plus holdouts were inconsistent with USACE-computed net inflows. The USACE Savannah District indicated that calculated inflows were quality controlled, whereas reported pool elevations were not. Consequently, it was decided to use USACE- computed inflow time series rather than holdout-adjusted outflows for computation of reservoir inflows.

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Computed reservoir inflows required subsequent adjustment to remove continuity bias with the potential for accumulated differences in computed and observed reservoir elevations. Using recorded inflow and outflow time series, resulting reservoir storage was reconstructed from the daily change in storage. Plots of the reconstructed reservoir storage and observed reservoir storage revealed a gradual accumulation or loss of volume over time at each of the three reservoirs. Reservoir inflows were adjusted on an annual basis to remove this bias. The annual change in storage was determined for the observed and reconstructed storage time series, and the difference in the annual change in storage was distributed evenly over the year and added to the inflow time series. Daily corrections ranged from –329 to 81 cfs for Hartwell inflows, from –66 to 509 cfs for Russell, and from –354 to 586 cfs for Thurmond. Plots of the reconstructed storage at each reservoir are shown on Figures 6-7 through 6-9, demonstrating the effects of inflow adjustment.

Figure 6-7 Hartwell Observed and Reconstructed Storage Time Series

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Figure 6-8 Russell Observed and Reconstructed Storage Time Series

Figure 6-9 Hartwell Observed and Reconstructed Storage Time Series

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6.5.3 Data Time Shifts

Comparison of Hartwell releases and Iva gaged flows downstream of Hartwell revealed that recorded releases from Hartwell were shifted one day forward in time for the period 10/1/1978 – 12/31/1978, and one day back in time for the period 5/3/1979 – 11/24/1979. These periods were corrected and the resulting time series was used in subsequent calculations. The Russell inflow time series exhibited similar shifts during multiple periods relative to Hartwell releases. Periods listed in Table 6-4 were corrected by shifting the time series forward or backward the number of days specified in the table.

Table 6-4 Russell Inflow Time Shift Summary

Adjusted Period Shift Adjustment 3/3/1985 – 9/2/1985 Shifted inflow forward 2 days 10/5/1985 – 1/2/1986 Shifted inflow forward 2 days 2/20/1986 – 7/19/1986 Shifted inflow forward 1 day 7/20/1986 – 12/1/1986 Shifted inflow forward 2 days 12/7/1989 – 12/27/1989 Shifted inflow back 2 days 5/21/1990 – 5/24/1990 Shifted inflow back 2 days

6.5.4 Russell-Thurmond Pumpback Operation

The Russell project has both conventional and pumped-storage power turbines and generators, discharging into and pumping from the Thurmond pool. Russell inflows reported by the Savannah District are net inflows, computed as project outflow minus net change in reservoir storage. The District additionally provides separate pumping time series data, representing average daily pumpback flow transferred from Thurmond to Russell. Russell total inflow from upstream sources was computed by subtracting pumpback from net inflow time series. Pumping time series data were also accounted for in the calculation of local incremental flows to Thurmond Reservoir.

6.5.5 Hartwell Reservoir (HARTWL_R)

Inflow and outflow quality control adjustments previously described resulted in complete time series from 4/24/1962 – 12/31/2007 at Hartwell Reservoir. From 1939 to reservoir startup, filled inflow and outflow time series are identical.

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To avoid development of regression relationships based on regulated flow, the Hartwell releases were filled by back-routing downstream observed flows and developing regression relationships for the local area between the downstream gage and Hartwell. This was accomplished by back-routing downstream observed flows to Hartwell and computing observed local incremental flows from the back-routed downstream flows and Hartwell releases. The missing periods of local incremental flow were then filled using regression with nearby tributary gage records. Finally, the resulting local incremental flow was subtracted from back-routed downstream flow to yield filled cumulative flow time series at Hartwell.

The following specific steps were completed to fill the reservoir outflow time series:

• The 10/1/1950 – 4/23/1962 period was filled using the downstream Iva gage, as follows:

- Iva observed flows were back-routed using negative lag values in the variable Lag-K model with no attenuation. After back-routing, the local incremental flow between Hartwell and Iva was computed for the overlapping period.

- The Iva local incremental flow calculation resulted in many negative flow values due to limitations of the routing model. To develop the best estimate of the regression relationships, negative flows were removed using the AdjustExtremes command in TSTool prior to computing the regression relationship. The Iva local incremental flow showed an apparent shift in October 1971; therefore, only the period prior to 9/30/1971 was considered in developing the regression relationship.

- The missing data period for the Iva local flow was filled using an annual MOVE2 relationship with the Beaverdam Creek gage. Table 6-5 presents the resulting regression equation and filling statistics.

- Filled Iva local incremental flows were subtracted from the back-routed Iva flows to fill 10/1/1950 – 4/23/1962. This resulted in negative flows during the period when the reservoir was filling and releases were minimal; all negative values between 1/1/1961 – 5/1/1962 were set to zero and volume-corrected accordingly.

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Table 6-5 Annual MOVE2 Results: Iva Local (Dependent) and Beaverdam Creek (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg Annual 113.72 5.02 0.3431 480.58 379.04 1.27

• The remaining missing period (1/1/1939 – 12/31/1949) was filled in a similar manner using Calhoun Falls observed flow data, as follows:

- Calhoun Falls observed flows were back-routed to Hartwell using negative variable lag in the Lag-K model. Local incremental flows were computed, setting negative flows to zero using the AdjustExtremes command in TSTool prior to developing regression relationships.

- The local incremental Calhoun Falls time series was filled for 1/1/1940 – 12/31/1949 using an annual MOVE2 relationship with the Mt. Carmel gage time series, which was first shifted back 12 hours prior to completing the filling to better align with the computed local incremental Calhoun Falls time series. Table 6-6 displays the resulting regression equation and statistics from the filling.

- The remaining missing period (1/1/1939 – 1/1/1940) was filled using an annual MOVE2 relationship with Bell, after back-routing Bell using negative variable lag in the Lag-K model. No filled data were included when developing the second regression relationship. Table 6-7 presents the resulting regression equation and statistics from the filling.

- The filled Calhoun Falls local incremental flow was subtracted from the back-routed Calhoun Falls flow to fill 1/1/1939 – 9/30/1950 in the Hartwell release time series. This resulted in minor negative flows as a result of limitations of the routing model, which were removed using the TSTool AdjustExtremes command.

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Table 6-6 Annual MOVE2 Results: Calhoun Falls Local (Dependent) and Mt. Carmel Shifted (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg Annual 637.86 4.19 0.6634 1,087.07 1,621.55 0.67

Table 6-7 Annual MOVE2 Results: Calhoun Falls Local (Dependent) and Bell Back-Routed (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg Annual 357.32 0.7 0.5599 1,298.31 1,700.79 0.76

• The reservoir inflow time series were filled as follows:

- The filled reservoir release time series was copied to the reservoir inflow time series prior to 4/24/1962.

- Reservoir holdout flows were computed using observed reservoir elevations prior to the start of the observed release time series (beginning in 1/1/1962). Holdouts were added to the filled release time series for the interim period (1/1/1962 – 4/23/1962), resulting in reservoir outflows for this period.

6.5.6 Richard B. Russell Reservoir (RBR_R)

The reservoir effects quality control adjustments of inflow and outflow, as previously described, resulted in complete time series following the 12/1/1984 power online date of the Russell project. Filling of reservoir inflows was necessary for the period 1/1/1939 – 11/30/1984.

The Calhoun Falls historical stream gage was located just upstream of the Russell Dam site. Observed gage data were used directly to fill the period 1/1/1939 – 9/30/1979. The period from 10/1/1979 – 11/30/1984 was then filled by routing Hartwell releases downstream, filling the missing local incremental flow using regression with nearby tributary gage records, and summing the filled local incremental flow and routed Hartwell releases.

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The following specific steps were completed to fill the reservoir outflow time series:

• The period 1/1/1939 – 9/30/1979 was filled directly by Calhoun Falls observed flows.

• The remaining 10/1/1979 – 12/1/1984 missing period was filled using routed Hartwell releases and filled Calhoun Falls (Russell) local flows, as follows:

- Observed local incremental flow between Hartwell and Russell was computed by routing upstream Hartwell releases to Russell and subtracting this from the observed Calhoun Falls flow. Routing parameters for the pre-reservoir conditions were applied to the routing.

- Local incremental flow calculation resulted in many negative flow values due to limitations of the routing model. To develop the best estimate of the regression relationships, negative flows were removed using the AdjustExtremes command in TSTool prior to computing the regression relationship.

- The local incremental Calhoun Falls time series was filled using an annual MOVE2 relationship with the Bell time series, after back-routing Bell using negative variable lag in the Lag-K model. Table 6-8 displays the resulting regression equation and statistics from the filling.

- The resulting filled local incremental flow was added to the routed Hartwell releases.

Table 6-8 Annual MOVE2 Results: Calhoun Falls Local (Dependent) and Bell Back-Routed (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg Annual 195.55 0.8 0.3994 1,785.59 1,707.18 1.05

• Observed reservoir elevations enabled calculation of holdout flows prior to the start of the observed release time series at Russell (8/2/1984 – 11/30/1984). Because the filling relied on routing upstream releases downstream to Russell, the change in storage needed to be accounted for to compute the reservoir releases during this period. Initially, the change in storage was computed and subtracted from the

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filled time series for the interim period between the start of reservoir storage observations and the start of reservoir release observations to produce a filled release time series. However, even with this change, the local incremental flow calculation for the downstream Thurmond sub-basin resulted in many large negative flow values for the period when Russell began storing flows; the Thurmond local incremental flows required additional adjustments during this period as subsequently described in Section 6.6.

The reservoir inflow time series were filled using the same methods as above, excluding the adjustment for holdouts.

6.5.7 Thurmond Reservoir (THRMND_R)

The reservoir effects quality control adjustments of inflow and outflow, as previously described, resulted in complete time series after the 1/2/1954 startup of Thurmond Reservoir. Complete time series for the full study period are required for both inflows and outflows. Prior to the start of reservoir storage, the filled inflows and outflows are identical.

The Clarks Hill stream gage was located just downstream of the Thurmond Dam site. Observed gage data were used directly to fill the period 5/14/1940 – 1/1/1954. Filling prior to this period was accomplished by back-routing Augusta flows to Thurmond, filling the missing local incremental flow using regression with nearby tributary gage records, and subtracting the filled local incremental flow from the back-routed Augusta flow.

The following specific steps were completed to fill the reservoir outflow time series:

• The period 5/14/1940 – 1/1/1954 was filled directly from the Clarks Hill gage record.

• The period 1/1/1939 – 5/13/1940 was filled using the downstream Augusta gage, as follows:

- Augusta flows were back-routed using negative lag values in the variable Lag-K model with no attenuation. After back-routing, the local incremental flow between Thurmond and Augusta was computed for the overlapping period.

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- The Augusta local incremental flow calculation resulted in negative flow values due to limitations of the routing model. To develop the best estimate of the regression relationships, negative flows were removed using the AdjustExtremes command in TSTool prior to computing the regression relationship.

- Millhaven and SF_Edisto gage records were used to fill the Augusta local flow using multiple linear regression. The Millhaven and SF_Edisto time series were shifted back in time to better align with the observed Augusta local flow prior to computing the regression relationship. Table 6-9 presents the resulting regression equation and correlation from the filling.

- The filled Augusta local incremental flow was subtracted from the back- routed Augusta flows to fill the missing period.

Table 6-9 Annual Multiple Linear Regression Results: Augusta Local (Y), Millhaven (X1), and SF_Edisto (X2)

Y = A + BX1 + CX2 Period A B C R2 Annual –477.6 1.76 0.84 0.433

The Thurmond reservoir inflow time series was filled using these same relationships. The local incremental flow calculation for Thurmond resulted in major negative flows just prior to the start of observed reservoir data, when the reservoir apparently was filling. These negatives were adjusted following the local incremental flow calculation as subsequently described in Section 6.6.

6.5.8 Burtons Ferry (BURTONS)

The Burtons Ferry streamflow record was missing data for 1/1/1939 – 9/30/1939, 10/1/1979 – 9/30/1982, and 10/15/2003 – 9/30/2004. To avoid filling the missing periods based on regression relationships with flows affected by the upstream reservoirs, local observed flows were computed with missing local flows filled using nearby tributary gages, and the resulting filled local flows were added to the routed upstream flow from Augusta to produce a complete total flow time series at Burtons. The following specific steps were completed:

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• Observed local incremental flow was computed by routing upstream Augusta flow to Burtons and subtracting this from the observed flow at Burtons. A single missing daily flow value at Augusta was filled prior to the routing.

• The local incremental flow calculation resulted in many negative flow values due to limitations of the routing model. To develop the best estimate of the regression relationships, negative flows were removed using the AdjustExtremes command in TSTool prior to computing the regression relationship.

• The Millhaven and Salkehatchie gage records were used to fill the Burtons local flow using multiple linear regression. The time series were both shifted back 12 hours in time to better align with the Burtons local flow prior to computing the regression relationship. This relationship was used to fill all missing data at Burtons except the missing period in 1939. Table 6-10 presents the resulting regression equation and correlation from the filling.

• The remaining missing local flow data were filled using an annual MOVE2 relationship with the shifted Millhaven gage. No filled data were included when developing the second regression relationship. Table 6-11 displays the resulting regression equation and statistics from the filling.

• Filled local incremental flow at Burtons was added to the routed Augusta flow to produce a complete total flow time series at Burtons.

Table 6-10 Annual Multiple Linear Regression Results: Burtons Local (Y), Millhaven (X1), and Salkehatchie (X2)

Y = A + BX1 + CX2 Period A B C R2 Annual 185.7 0.66 1.98 0.544

Table 6-11 Annual MOVE2 Results: Burtons Local (Dependent) and Shifted Millhaven (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg Annual –22.8 1.99 0.3651 1,060.47 1,175.29 0.90

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6.5.9 Kings Ferry (KINGSFY)

The Kings Ferry node is a synthetic node with no streamflow data available over the period of record. The flow at Kings Ferry was estimated by routing Claxton and Eden flows downstream to Kings Ferry, summing the routed flows, and scaling up by the ratio of drainage areas, as follows:

DA Kings Ferry / (DA Claxton + DA Eden )

Routing parameters were estimated based on average parameters from the Burtons to Clyo reach, adjusted for differences in reach lengths.

6.5.10 Augusta and Clyo (AUGUSTA, CLYO)

Both the Augusta and the Clyo gage records are complete over the entire 1939 to 2007 period of analysis, with the exception of a few individual streamflow values. These were filled using linear interpolation between adjacent observations.

6.5.11 Savannah (SAVANNAH)

The Savannah node is a tidally influenced synthetic node with no streamflow data available over the period of record. The gage was filled by routing observed flows from Clyo downstream to Savannah, estimating the local flow between Clyo and Savannah, and summing the two components to give the total flow at Savannah. Because of a lack of data to calibrate a routing model, routing parameters were estimated using approximate average routing parameters based on the upstream Burtons to Clyo reach, which is of a similar length.

The Savannah local incremental flow was estimated following preliminary analysis of filling options. The Clyo local incremental flow was computed after routing the Millhaven and Burtons filled flows downstream to Clyo. The Millhaven, Eden, and Claxton streamflow records present additional filling options, since they are located on nearby tributaries and are of similar sizes.

For evaluation purposes, the streamflow at each location was scaled to the local Savannah drainage area. Local drainage areas and associated scaling ratios are shown in Table 6-12.

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Table 6-12 LDAs and Scaling Ratios for Savannah Local Flow Filling

Node LDA (mi 2) Drainage Area Ratio SAVANNAH 1500 -- CLYO 1650 0.91 MILLHAVN 1672 0.90 CLAXTON 1452 1.03 EDEN 6903 0.22

The Clyo local flows are relatively noisy, and because the flow characteristics appear similar to each of the other three scaled options, this option was excluded.

The scaled Claxton flows demonstrate flashier characteristics than the other two sub- basins, and Claxton is located farthest from the Savannah local area. This option was also consequently excluded.

The scaled Eden and Millhaven flows demonstrate similar characteristics. The peaks are shifted in time approximately six days from each other. The flows at Eden were shifted back in time three days and the flows at Millhaven were shifted forward in time three days. The shifted, scaled flows at each location were then averaged to estimate the Savannah local flow.

The total flow at Savannah was computed as the sum of the routed Clyo flow and the estimated Savannah local flow.

6.6 Local Incremental Flow Calculation and Adjustments

Following computation of the local incremental flows, adjustments were made to the resulting time series for the SO basin as subsequently described.

6.6.1 Richard B. Russell Reservoir (RBR_R)

The initial local incremental flow for Russell had distinct characteristics during different time periods, with extensive negatives and noisy low flows during the period with observed data at RBR_R (or the co-located historical Calhoun Falls gage), but smooth low flows with minimal negatives during the filled period (10/1/1979 – 11/30/1984). Two steps were performed to adjust the initial local incremental flows at Russell:

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• Low flows (less than 3,000 cfs) were smoothed by replacing the calculated local flow with a seven-day centered moving average (CMA7). The smoothing was not applied from 10/1/1979 – 11/30/1984.

• The AdjustExtremes TSTool command was applied with a maximum interval of three days (maximum seven-day averaging) to the resulting time series.

6.6.2 Thurmond Reservoir (THRMND_R)

The initial local incremental flow calculations at Thurmond yielded exceptionally large negatives during two periods, just prior to the start of both the Thurmond Reservoir data records and the Russell Reservoir data records. The negatives result from assuming no change in storage in the reservoirs during these periods when the Thurmond inflow and Russell outflow time series were filled. The local incremental flow was filled using an adjacent gage during these periods. In addition, low flows were smoothed after the reservoir began operation, and negatives resulting from routing errors were adjusted for the entire time series. The following specific steps were completed:

• The period 3/1/1951 – 11/30/1954 (when Thurmond was filling but USACE records were unavailable) was set to missing in the local incremental flow time series.

• The AdjustExtremes TSTool command was applied with a maximum interval of three days (maximum seven-day averaging) for the period prior to 3/1/1951.

• The 3/1/1951 – 11/30/1954 period of Thurmond local incremental flows was filled using an annual ordinary least squares (OLS) regression relationship with the Bell gage. Because reservoir evaporation changes the local incremental flow characteristics after 1954, the analysis period was limited to the earlier period. OLS was selected because of major discontinuities resulting from the application of monthly equations. Table 6-13 presents the resulting regression equation and statistics from the filling.

• The period 6/1/1982 – 12/1/1984 (when Russell was filling but USACE records were unavailable) was set to missing in the Thurmond local incremental flow time series.

• Low flows (less than 5,000 cfs) were smoothed by replacing the calculated local flow with a CMA7 for the period after 12/1/1954.

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• The AdjustExtremes TSTool command was applied with a maximum interval of three days (maximum seven-day averaging).

• The 6/1/1982 – 12/1/1984 period of Thurmond local incremental flow was filled using an annual OLS regression relationship with the Bell gage. Only data after 12/1/1954 were considered in the regression because of the change in local flow characteristics after the reservoir began operation. OLS was selected for consistency with filling for the earlier period; an annual equation was selected due to major discontinuities resulting from the application of monthly equations. Table 6-14 presents the resulting regression equation and statistics from the filling.

Table 6-13 Annual OLS Results for the Early Period: Thurmond Local (Dependent) and Bell (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg Annual –523.78 1.4 0.6425 2,591.33 1,942.74 1.33

Table 6-14 Annual OLS Results for the Second Period: Thurmond Local (Dependent) and Bell (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg Annual –507.36 0.97 0.3597 3,200.38 1,172.84 2.73

6.6.3 Other Nodes

Local incremental flow calculations resulted in negative flows at Augusta, Burtons, Clyo, and other locations. The AdjustExtremes command was applied with a maximum interval of three days to adjust negatives resulting from routing errors at Augusta, and with a maximum interval of seven days for the Burtons and Clyo locations. The higher interval was selected for the downstream locations because of longer travel times in these reaches.

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6.7 Local Incremental Unimpaired Flow Calculation

The final stage of local incremental unimpaired flow determination involves aggregation and removal of remaining impairments (human influences) – principally reservoir effects and net water uses – from local incremental flows.

6.7.1 Special Cases – Reservoir Effects

As previously described, time series and paired data for calculation of reservoir effects for Duke Energy’s Keowee and Jocassee reservoirs upstream of Hartwell were in processing at the time of the writing of this report. Consequently, KEOWEE_R inflows were also not available, and as a result HARTWL_R local incremental flows are cumulative for the upstream LDA, including the KEOWEE_R LDA. In addition, Georgia Power reservoir holdouts upstream of Hartwell were not factored into calculation of Hartwell local incremental flows, and as a result net reservoir effects (holdouts plus net evaporation) were added to local incremental flows in the final stage of Hartwell unimpaired flow calculation.

6.7.2 Negative Local Unimpaired Flow Adjustments

A no-negative local incremental unimpaired flow procedure was adopted for this study, in consideration of potential application to water availability assessments subject to various minimum flow constraints, including annual or monthly 7Q10 (10-year 7-day low flow).

While negative local incremental flows were removed to the maximum extent possible by refinements to reservoir holdouts, routing and filling procedures, and short-duration (three- to five-day) smoothing and averaging, some residual negatives remained at the unimpaired flow determination stage. To remove these, three approaches were employed, listed as follows in order of minimum number of adjacent time periods adjusted:

• The AdjustExtreme TSTool procedure, which averages values on either side of the negative value for as many days as necessary to produce a non-negative result. This method works best with intermittent as opposed to continuous periods of negative flows. Where extended periods of negative flows occur, the AdjustExtreme procedure produces multi-month periods of constant low flow.

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• Annual adjustment – A DSSMATH procedure that increases all negative flows to zero and reduces all positive values by a factor equal to the ratio of the original (with negatives) annual average flow to the adjusted (no negatives) annual average flow.

• POR adjustment – Same as annual adjustment with the reduction factor computed using 1939 to 2007 POR average flow ratios.

6.7.3 Selection of Final Local Unimpaired Flow Time Series

Final local unimpaired flow selection is predicated on the basic requirement for no residual negative flows in the following order of preference:

• Unadjusted unimpaired flow (F = UNIMP)

• TSTool AdjustExtreme method, assuming no continuous constant-flow periods greater than the annual or POR adjustment (F = UNIMP–0ADJ LOC)

• DSSMATH annual adjustment (F = UNIMP–0ADJ ANNUAL)

• DSSMATH POR adjustment (F = UNIMP–0ADJ POR)

Final local unimpaired flow time series selection is denoted by an asterisk at the end of the F pathname denoting the adjustment required (e.g., F= UNIMP-0ADJ ANNUAL*). Example SO DSS pathnames for unimpaired flows and local inflow, reservoir effects, and water use constituents are shown in Table 6-15.

Table 6-15 Sample Condensed Catalog Listing of SO Unimpaired Flow Component Time Series T3466 SO-SAVNAH AUGUSTA FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T3535 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T3604 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T3673 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T3742 ------FLOW-LOC INC 0ADJ LOC 1DAY 01JAN1939 - 01JAN2007 T3811 ------UNIMP 1DAY 01JAN1938 - 01JAN2007 T3881 ------UNIMP-0ADJ ANNUAL 1DAY 01JAN1938 - 01JAN2007 T3951 ------UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T4020 ------UNIMP-0ADJ LOC 1DAY 01JAN1939 - 01JAN2007 T4089 ------UNIMP-0ADJ POR 1DAY 01JAN1938 - 01JAN2007 T4159 - - - - BURTONS FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T4228 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T4297 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T4366 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T4435 ------COMP-REACH-T 1DAY 01JAN1939 - 01JAN2007 T4504 ------FLOW-LOC INC 0ADJ LOC 1DAY 01JAN1939 - 01JAN2007 T4573 ------UNIMP 1DAY 01JAN1938 - 01JAN2007 T4643 ------UNIMP-0ADJ ANNUAL 1DAY 01JAN1938 - 01JAN2007

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Table 6-15 Sample Condensed Catalog Listing of SO Unimpaired Flow Component Time Series T4713 ------UNIMP-0ADJ ANNUAL* 1DAY 01JAN1939 - 01JAN2007 T4782 ------UNIMP-0ADJ LOC 1DAY 01JAN1939 - 01JAN2007 T4851 ------UNIMP-0ADJ POR 1DAY 01JAN1938 - 01JAN2007 T4921 - - - - CLYO FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T4990 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T5059 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T5128 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T5197 ------FLOW-LOC INC 0ADJ LOC 1DAY 01JAN1939 - 01JAN2007 T5266 ------UNIMP 1DAY 01JAN1938 - 01JAN2007 T5336 ------UNIMP-0ADJ ANNUAL 1DAY 01JAN1938 - 01JAN2007 T5406 ------UNIMP-0ADJ LOC 1DAY 01JAN1939 - 01JAN2007 T5475 ------UNIMP-0ADJ POR 1DAY 01JAN1938 - 01JAN2007 T5545 ------UNIMP-0ADJ POR* 1DAY 01JAN1939 - 01JAN2007 T5614 - - - - HARTWL_R FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T5683 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T5752 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T5821 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T5890 ------FLOW-EVAPNET POST RES 1DAY 01JAN1939 - 01JAN2007 T5959 ------POST-PRE RES 1DAY 01JAN1939 - 01JAN2007 T6028 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T6097 ------FLOW-LOC INC FILLED 1DAY 01JAN1939 - 01JAN2007 T6166 ------UNIMP 1DAY 01JAN1938 - 01JAN2007 T6236 ------UNIMP-0ADJ ANNUAL 1DAY 01JAN1938 - 01JAN2007 T6306 ------UNIMP-0ADJ LOC 1DAY 01JAN1939 - 01JAN2007 T6375 ------UNIMP-0ADJ LOC* 1DAY 01JAN1939 - 01JAN2007 T6444 ------UNIMP-0ADJ POR 1DAY 01JAN1938 - 01JAN2007 T6514 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T6583 - - - - HARTWL_R-BURTON_R FLOW-EVAPNET POST RES 1DAY 01JAN1939 - 01JAN2007 T6652 ------POST-PRE RES 1DAY 01JAN1939 - 01JAN2007 T6721 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T6790 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T6859 - - - - HARTWL_R-NACOCH_R FLOW-EVAPNET POST RES 1DAY 01JAN1939 - 01JAN2007 T6928 ------POST-PRE RES 1DAY 01JAN1939 - 01JAN2007 T6997 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T7066 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T7135 - - - - HARTWL_R-RABUN_R FLOW-EVAPNET POST RES 1DAY 01JAN1939 - 01JAN2007 T7204 ------POST-PRE RES 1DAY 01JAN1939 - 01JAN2007 T7273 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T7342 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T7411 - - - - HARTWL_R-TALLUL_R FLOW-EVAPNET POST RES 1DAY 01JAN1939 - 01JAN2007 T7480 ------POST-PRE RES 1DAY 01JAN1939 - 01JAN2007 T7549 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T7618 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T7687 - - - - HARTWL_R-TUGALO_R FLOW-EVAPNET POST RES 1DAY 01JAN1939 - 01JAN2007 T7756 ------POST-PRE RES 1DAY 01JAN1939 - 01JAN2007 T7825 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T7894 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T7963 - - - - HARTWL_R-YONAH_R FLOW-EVAPNET POST RES 1DAY 01JAN1939 - 01JAN2007 T8032 ------POST-PRE RES 1DAY 01JAN1939 - 01JAN2007 T8101 ------FLOW-HOLDOUT COMP 1DAY 1DAY 01JAN1939 - 01JAN2007 T8170 ------FLOW-NET RE COMP 1DAY 1DAY 01JAN1939 - 01JAN2007

6.8 Quality Control

Quality control as previously described was performed at each stage of SO basin unimpaired flow development (water use data, reservoir effects, filling, routing, and local incremental flow calculations). Final unimpaired flow stage quality control relied on consistency plots, in which individual nodes are grouped and differences between

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6.9 Cumulative Unimpaired Flows

Following Georgia EPD approval of local unimpaired flow data documented in this report, partial and full cumulative unimpaired flow time series data will be developed by aggregation and routing of applicable upstream local, partial cumulative, and cumulative unimpaired flows to downstream nodes.

6.10 Conclusions

The SO basin is the most complex and highly regulated basin in Georgia, with one pumped-storage and two conventional federal multipurpose hydropower reservoirs, impounding more conservation and flood storage than all other federal reservoirs in the state combined. The SO basin also has more private power reservoirs than any other study basin. The outlet planning nodes for both the Savannah and Ogeechee basins are tidally influenced and consequently lack gaged streamflow records. The Clyo reach is one of the few in Georgia experiencing multiple continuous months of negative local inflows, and even average annual local inflows for some years are negative, requiring the use of POR average inflow volume adjustment. Despite these complications, the quality of computed unimpaired flows appears to be quite good and well-suited to water availability assessment in the SO basin. Pending distributional corrections to the Russell and Thurmond unimpaired flows, the data appear also to be well-suited to reservoir system operational modeling.

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7. Ochlockonee, Suwannee, Satilla, and St. Mary’s (OSSS) River Basins

7.1 OSSS Basin Description

The OSSS drains an area of 10,450 square miles in southern Georgia. The Ochlockonee River basin is in the southwestern part of the state of Georgia. The Ochlockonee River begins approximately 19 miles southeast of Albany, Georgia and extends southwest through Florida to the Gulf of Mexico. The Suwannee River basin lies between the Ochlockonee and Satilla basins. The Suwannee River begins approximately 9 miles south of Waycross, Georgia in the Okefenokee Swamp, flows southwest through Florida, and empties into the Gulf of Mexico. Major tributaries of the Suwannee River that lie within Georgia are the Alapaha, Withlacoochee, and Aucilla rivers. The Satilla basin is between the Suwannee River basin and the Atlantic Coast. The Satilla River begins approximately 25 miles east of Tifton, Georgia and flows southeast to the Atlantic Ocean. A major tributary of the Satilla River is the Little Satilla River. The St. Mary’s basin is located in the southeast corner of Georgia. The St. Mary’s River begins approximately 14 miles east of Lake City, Florida and flows north into Georgia and then east to the Atlantic Coast.

Ochlockonee, Suwannee, Satilla, and St. Mary’s river flows within Georgia are unregulated, having no federal or private power storage reservoirs. The planning nodes for the OSSS are Quincy, Concord, Pinetta, Jennings, Statenville, Fargo, Atkinson, and Gross. The locations of these planning nodes and the basic nodes in the OSSS are shown on Figure 7-1.

7.2 Hydrological Data

7.2.1 Streamflow Records

Approximately 35 stream gage stations are located within the OSSS basin in Georgia. A total of 15 stream gage stations were selected within the OSSS basin, of which approximately 10 have continuous data covering most of the 1939 to 2007 study period for which unimpaired flows were derived; six of these have data that cover the entire study period. The gage near Gross, Florida is a virtual planning gage subject to tidal influence, for which observed flows will be extrapolated from upland gage records in adjacent watersheds. Gage locations are shown on Figure 7-2, and periods of record for gages used in filling are shown on Figure 7-3.

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Figure 7-1 OSSS Study Basin Basic and Planning Nodes

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Figure 7-2 Nodes and Gages Associated with OSSS Study Basin Streamflow Filling

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Figure 7-3 Periods of Record for Gages Associated with OSSS Study Basin Streamflow Filling

7.3 Water Use Data

The Water Use Data Inventory Report documents present hindcasted (1939 to 2001) consumptive water uses within the OSSS basin of the following types:

• Municipal and industrial water use (withdrawals, discharges/returns) in Georgia, and net consumptive uses by Alabama in the Chattahoochee basin

• Agricultural irrigation water use in Georgia

Net uses of each type are aggregated by reach and summed to produce an aggregate water demand for each reach. Reach aggregate water use is added to local incremental flows and combined with reservoir effects as applicable (both subsequently described) to produce local incremental unimpaired flows. Sample HECDSS pathnames for OSSS water uses are shown in Table 7-1. Note that there are no reaches in the OSSS basin having all five use categories listed above.

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Table 7-1 Sample OSSS Aggregate Reach Water Use HECDSS Condensed Catalog Listings (from OSSS-unimpaired flow.DSS , 2009-06-26 version T1 OSSS-ALAPHA ALAPAHA FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T70 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T139 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T208 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007

T2968 OSSS-OCHLKN CONCORD FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T3037 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T3106 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T3175 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007

T4693 OSSS-SATLA ATKINSON FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T4762 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T4831 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T4900 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007

7.4 Streamflow Filling, Routing, and Reservoir Inflows

Unimpaired flow development removes human impacts – net water uses and reservoir regulation (holdouts and net evaporation) – from observed streamflows or computed gross reservoir inflows. All nodes in the OSSS basin required complete time series for 1939 through 2007 and no reservoirs were present.

7.4.1 Methods Summary

Table 7-2 summarizes streamflow filling periods and methods for the Ochlockonee and Suwannee basins. As noted, some of the streamflow records were complete over the required periods of analysis and consequently required no filling.

Table 7-2 Streamflow Filling and Routing Summary

Node Filled Streamflow Filling Method/Gage(s) Used for Filling ALAPAHA 3/11/1937 – 4/25/1937 Linear regression (Statenville) 10/1/1976 – 9/3/2002 BEMISS 3/11/1937 – 6/10/1988 Linear regression (Pinetta) CONCORD 3/11/1937 – 9/30/1998 Linear regression (Havana) JENNINGS 3/11/1937 – 7/27/1976 Linear regression (Statenville) 10/1/1984 – 9/30/1985 10/6/1987 – 9/30/1999 10/1/2001 – 9/30/2006

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Table 7-2 Streamflow Filling and Routing Summary

QUINCY 3/11/1937 – 3/31/1950 Linear regression (Havana) 3/7/1979 – 7/31/1980 2/12/1992 – 4/2009 QUITMAN 3/11/1937 – 12/20/1979 Linear regression (Pinetta) THOMASVL 3/11/1937 – 8/10/1937 Linear regression (Havana) 7/1/1971 – 10/10/2000 GROSS 1/39 – 12/07 Filled with data from MacClenny OFFMAN 1/39 – 12/50 Fill with back-routed Atkinson using monthly MOVE2

Specific filling and routing calculations are subsequently described.

7.4.2 Alapaha (ALAPAHA)

The TSTool was utilized to fill the Alapaha basic node on the Alapaha River at USGS Gage 02316000 near Alapaha, Georgia. The Alapaha node has a downstream gage on the Alapaha River near Statenville, Georgia (STATVL 02317500). The Alapaha node had data for 63 percent of the period of record, while the Statenville node provided a complete time series for the entire study area of 1939 through 2007.

• The Alapaha record was filled by calibrating and back-routing the Statenville data utilizing the variable Lag-K command using negative variable lag.

• Once the Statenville gage records were routed, linear regression was utilized to develop the statistical relationships and fill the Alapaha gage.

7.4.3 Bemiss (BEMISS)

The TSTool was utilized to fill the Bemiss basic node on the Withlacoochee River at McMillan Road near Bemiss, Georgia (023177483). The Bemiss node has a downstream gage on the Withlacoochee River near Pinetta, Florida (Pinetta 02319000). The Bemiss node had data for only 30 percent of the period of record, while the Pinetta node provided a complete time series for the entire study area of 1939 through 2007.

• The Bemiss record was filled by calibrating and back-routing the Pinetta data utilizing the variable Lag-K command using negative variable lag.

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• Once the Pinetta gage records were routed, a linear regression equation was utilized to develop the statistical relationships and fill the Bemiss gage.

7.4.4 Concord (CONCORD)

The TSTool was utilized to fill the Concord planning node on the Ochlockonee River at USGS Gage 02328522 near Concord, Florida. The Concord node has both an upstream and downstream gage that constitute possible sources of flow data with which to fill the record for the Concord gage. The downstream Havana, Florida gage (USGS 02329000) was selected because it has a full period of record for 1939 to 2007.

• The Concord record was filled by calibrating and back-routing the Havana data using the variable Lag-K command using negative variable lag.

• Once the gage records were routed, a linear regression equation was utilized to develop the statistical relationships and fill the Concord gage.

7.4.5 Fargo (FARGO)

Fargo (02314500) had a complete data record for the study period. Therefore, no data filling was required for this node.

7.4.6 Jennings (JENNINGS)

TSTool was utilized to fill the planning node on the Alapaha River at USGS Gage 02317620 near Jennings, Florida. The node had an upstream gage on the Alapaha River near Statenville, Georgia (STATVL 02317500), which had a full period of record and was used to fill the record for the Jennings gage. The Jennings node had data for only 21 percent of the period of record, while the Statenville node provided a complete time series for the entire study area of 1939 through 2007.

• The Jennings record was filled by calibrating and downstream routing of the Statenville data utilizing the variable Lag-K command.

• Once the Statenville gage records were routed, a linear regression equation was utilized to develop the statistical relationships and fill the Jennings gage.

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7.4.7 Pinetta (PINETTA)

The Pinetta (02319000) station on the Withlacoochee River had 100 percent of the data provided for the period of record. Therefore, no data filling was required for this node.

7.4.8 Quincy (QUINCY)

TSTool was utilized to fill the planning node on the Little River near Quincy, Florida (02329500). The Quincy node had data for only 59 percent of the period of record and no available upstream or downstream gages with a full period of record. Gage 02329900 is a reservoir gage and Gage 2330000 had missing time series so it was determined that the Havana gage from the adjacent watershed was the best fit to be used for the record filling (02329000).

• The Quincy record was filled by calibrating and back-routing the Havana data utilizing the variable Lag-K command using negative variable lag.

• Once the gage records were routed, a linear regression equation was utilized to develop the statistical relationships and fill the Quincy gage.

7.4.9 Quitman (QUITMAN)

TSTool was utilized to fill the basic node on Okapilco Creek at USGS Gage 02318700 near Quitman, Georgia. The Quitman node had a downstream gage on the Withlacoochee River near Pinetta, Florida (Pinetta 02319000). The Quitman node had data for 41 percent of the period of record, while the Pinetta node provided a complete time series for the entire study period of 1939 through 2007.

• The Quitman record was filled by calibrating and back-routing the Pinetta data utilizing the variable Lag-K command with a negative variable lag.

• Once the Pinetta gage records were routed, a linear regression equation was utilized to develop the statistical relationships and fill the Quitman gage.

7.4.10 Statenville (STATVL)

The Statenville (02317500) station on the Alapaha River had a full period of record and therefore no data filling was required for this planning node.

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7.4.11 Thomasville (THOMASVL)

The TSTool was utilized to fill the Thomasville basic node on the Ochlockonee River near Thomasville, Georgia (02327500). The Thomasville node has a downstream gage on the Ochlockonee River near Havana, Florida (Havana 02329000). The Thomasville node had data for only 57 percent of the period of record, while the Havana node provided a complete time series for the entire study area of 1939 through 2007.

• The Thomasville record was filled by calibrating and back-routing the Havana data utilizing the variable Lag-K command using negative variable lag.

• Once the Havana gage records were routed, a linear regression equation was utilized to develop the statistical relationships and fill the Thomasville gage.

7.4.12 Offman (OFFMAN)

The Offman streamflow record contained missing data for one period (1/1/1939 – 12/31/1950). The missing local flow was filled using nearby tributary gages. The following specific steps were completed:

1. The downstream Atkinson flow was back-routed upstream to the Offman gage.

2. The missing local flow at Offman was filled using a monthly MOVE2 relationship with the back-routed Atkinson gage. Table 7-3 presents the resulting monthly regression equations and statistics from the filling.

Table 7-3 Monthly MOVE2 Results: Offman (Dependent) and Back-Routed Atkinson (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg January –138.04 0.29 0.8685 454.14 827.54 0.55 February –183.04 0.27 0.8908 432.29 1,043.8 0.41 March –256.84 0.28 0.8699 543.59 1,069.62 0.51 April –130.13 0.25 0.856 405.73 635.6 0.64 May –156.92 0.32 0.6362 405.47 214 1.89 June –85.01 0.3 0.6371 378.48 278.57 1.36 July –129.83 0.31 0.7014 336.06 297.59 1.13

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Table 7-3 Monthly MOVE2 Results: Offman (Dependent) and Back-Routed Atkinson (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg August –147.19 0.31 0.6744 425.3 412.87 1.03 September –202.66 0.34 0.7489 554.54 388.36 1.43 October –55.02 0.25 0.8193 293.91 251.58 1.17 November –41.50 0.3 0.8106 195.12 188.37 1.04 December –64.42 0.29 0.8687 328.3 474.91 0.69

7.4.13 Gross (GROSS)

The Gross node is a synthetic node because the quality of its gage record is not sufficient to be utilized to support unimpaired flow calculations as in a typical node. The period of record is relatively short, beginning March 1, 1966 and ending August 30, 1990. This gage is tidally influenced, so many of the recorded flows are negative. In addition, there are many gaps in the flow record. The existing USGS flow records for Gross were not used to calculate unimpaired flows because of the large number of gaps and negative flows. Instead, a synthetic record was estimated by routing MacClenny downstream to Gross and scaling the routed flows up by the drainage area ratio of Gross to MacClenny.

Because of the lack of data to calibrate a routing model, routing parameters were estimated by comparing routing parameters for Offerman to Atkinson and Waycross to Atkinson, and adjusting these for differences in reach lengths.

7.5 Local Incremental Flow Calculation and Adjustments

Calculations described above produced complete time series (no missing data) over the required periods of record. Local incremental flows were next calculated by subtraction of routed upstream cumulative flows from downstream cumulative flows. For headwater nodes, local incremental flows are the same as cumulative flows. For downstream nodes, local incremental flows were computed using TSTool commands executing the following steps:

• Read upstream filled cumulative flow time series.

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• Route the upstream cumulative flow time series to the downstream location.

• Subtract the routed upstream cumulative flows from the downstream cumulative filled time series, resulting in local (impaired) incremental flow at the downstream location.

As previously stated, local incremental flows do not yet represent unimpaired flows. Water withdrawals, agricultural diversions, return flows, and other losses or gains are added to the local incremental flows in the final step to produce unimpaired flows.

In some reaches, negative local incremental flows resulted from the subtraction of routed upstream cumulative flows from downstream cumulative flows. These negative values result from a variety of causes, including routing discrepancies (e.g., lag times), errors in observed flow values, small local flows relative to cumulative flows, and water use or losses to groundwater. Adjustments to remove negative local incremental flows were limited to refinements to filling and/or routing procedures and manual routing adjustments in certain circumstances where global parameters were not sufficient in eliminating large negative flows. Adjustments were made to the resulting time series as described in the following sections for the OSSS study basin.

7.5.1 Concord (CONCORD)

The initial local incremental flow for Concord had eight distinct periods with large negatives that could not be corrected with the three-day AdjustExtremes method and were manually adjusted: July 11, 1945 – July 15, 1945; June 26, 1958 – June 28, 1958; July 2, 1967 – July 14, 1967; May 3, 1971 – May 13, 1971; March 7, 2001 – March 11, 2001; September 19, 2002 – September 25, 2002; November 15, 2002 – November 17, 2002; and July 21, 2004 – July 24, 2004.

1. Global routing parameters did not attenuate and lag the Thomasville flow properly and therefore created large negative peaks in the initial local incremental flow. Routed flows were manually adjusted for attenuation and lag, maintaining mass balance, and matching the flow curve of Concord.

2. After manual adjustment of routed flows, local incremental flows were calculated.

3. The AdjustExtremes TSTool command was applied with a maximum interval of three days (maximum seven-day averaging) to the resulting local incremental time series to remove any remaining negatives.

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7.5.2 Jennings (JENNINGS)

The initial local incremental flow for Jennings had two distinct periods with large negatives that could not be corrected with the three-day AdjustExtremes method and were manually adjusted: April 12, 2000 – April 23, 2000 and March 26, 2001 – April 5, 2001.

1. Global routing parameters did not attenuate and lag the Statenville flow properly and therefore created large negative peaks in the initial local incremental flow. Routed flows were manually adjusted for attenuation and lag, maintaining mass balance, and matching the flow curve of Jennings.

2. After manual adjustment of routed flows, local incremental flows were calculated.

3. The AdjustExtremes TSTool command was applied with a maximum interval of three days (maximum seven-day averaging) to the resulting local incremental time series to remove any remaining negatives.

7.5.3 Pinetta (PINETTA)

The initial local incremental flow for Pinetta had just one period with large negatives that could not be corrected with the three-day AdjustExtremes method and were manually adjusted: September 13, 2000 – September 17, 2000.

1. Global routing parameters did not attenuate and lag the summed Bemiss and Quitman flows properly and therefore created a large negative peak in the initial local incremental flow. Routed flows were manually adjusted for attenuation and lag, maintaining mass balance, and matching the flow curve of Pinetta.

2. After manual adjustment of routed flows, local incremental flows were calculated.

3. The AdjustExtremes TSTool command was applied with a maximum interval of three days (maximum seven-day averaging) to the resulting local incremental time series to remove any remaining negatives.

7.5.4 Statenville (STATVL)

The initial local incremental flow for Statenville had four distinct periods with large negatives that could not be corrected with the three-day AdjustExtremes method and

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1. Global routing parameters did not attenuate and lag the Alapaha flow properly and therefore created large negative peaks in the initial local incremental flow. Routed flows were manually adjusted for attenuation and lag, maintaining mass balance, and matching the flow curve of Statenville.

2. After manual adjustment of routed flows, local incremental flows were calculated.

3. The AdjustExtremes TSTool command was applied with a maximum interval of three days (maximum seven-day averaging) to the resulting local incremental time series to remove any remaining negatives.

7.5.5 Final Adjustments to Unimpaired Local Incrementals

Some small negatives remained in the adjusted local incremental flows. Final adjustments to remove all negative local incremental flows were performed after final aggregation of local incremental flows and reach net water uses in the unimpaired local incremental flows.

Table 7-4 lists TSTool command files used for OSSS filling, routing, and local incremental flow calculation.

Table 7-4 TSTool Command for OSSS Basin Local Incremental Flow Determination

ALAPAHA_fill.TSTool Filling for Alapaha BEMISS_fill.TSTool Filling for Bemiss CONCORD_fill.TSTool Filling for Concord JENNINGS_fill.TSTool Filling for Jennings QUINCY_fill.TSTool Filling for Quincy QUITMAN_fill.TSTool Filling for Quitman THOMASVL_fill.TSTool Filling for Thomasville OFFMAN_fill.TSTool Filling for Offman GROSS_fill.TSTool Filling for Gross Computes local incremental flows in the OSSS ComputeLocalIncrementals_OSSS.TSTool basin

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Table 7-4 TSTool Command for OSSS Basin Local Incremental Flow Determination

Corrects negative local incremental flow values AdjustExtremesLocInc_OSSS.TSTool with a three-day interval (maximum seven-day averaging) Populates the initial HECDSS file with observed InitialPopulate_OSSS_dss.TSTool gage data Populates the INT DSS file with manually Populate_ManAdj_INT_dss.TSTool adjusted routed flows prior to local incremental flow calculations Runs files to fill all nodes in the OSSS basin Run_OSSS_Filling.TSTool (Satilla and Saint Mary’s)

7.6 Local Incremental Unimpaired Flow Calculation

The final stage of local incremental unimpaired flow determination involves aggregation and removal of remaining impairments (human influences) – principally reservoir effects and net water uses – from local incremental flows. With no reservoirs in this basin, the focus of this section is net water uses.

7.6.1 Negative Local Unimpaired Flow Adjustments

A no-negative local incremental unimpaired flow policy was adopted for this study, in consideration of potential application to water availability assessments subject to various minimum flow constraints, including annual or monthly 7Q10 (10-year 7-day low flow). Moreover, many operational models do not allow for negative local incremental flows. The utility of unimpaired flows computed in this study is maximized by systematic “intelligent” removal of negative values with minimal alteration to surrounding non-negative values, as opposed to cruder methods employed by operational models.

While negative local incremental flows were removed to the maximum extent possible by refinements, routing and filling procedures, and short-duration (three to seven days) smoothing and averaging, some residual negatives remained at the unimpaired flow determination stage. To remove these, three approaches were employed, listed as follows in order of minimum number of adjacent time periods adjusted:

• The AdjustExtreme TSTool procedure, which averages values on either side of the negative value for as many days as necessary to produce a non-negative result. This method works best with intermittent as opposed to continuous periods of

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negative flows. Where extended periods of negative flows occur, the AdjustExtreme procedure produces multi-month periods of constant low flow.

• Annual adjustment – A DSSMATH procedure that increases all negative flows to zero and reduces all positive values by a factor equal to the ratio of the original (with negatives) annual average flow to the adjusted (no negatives) annual average flow.

• POR adjustment – Same as annual adjustment with the reduction factor computed using 1939 to 2007 POR average flow ratios.

7.6.2 Selection of Final Local Unimpaired Flow Time Series

Final local unimpaired flow selection is predicated on the basic requirement for no residual negative flows in the following order of preference:

• Unadjusted unimpaired flow (F = UNIMP)

• TSTool AdjustExtreme method, assuming no continuous constant-flow periods greater than the annual or POR adjustment (F = UNIMP–0ADJ LOC)

• DSSMATH annual adjustment (F = UNIMP–0ADJ ANNUAL)

• DSSMATH POR adjustment (F = UNIMP–0ADJ POR)

7.7 Quality Control

Because primary quality control was performed at each stage of OSSS basin unimpaired flow development (water use data and filling/routing), final stage quality control relied on (1) visual inspection of local unimpaired flow time series plots, (2) comparison of average local unimpaired flow volume, and (3) consistency plots, in which individual nodes are grouped and differences between accumulated unimpaired flow for individual nodes and average accumulated unimpaired flow for the group are compared. These checks revealed no significant problems with the unimpaired flow data.

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7.8 Cumulative Unimpaired Flows

Following Georgia EPD approval of local unimpaired flow data documented in this report, partial and full cumulative unimpaired flow time series data will be developed by aggregation and routing of applicable upstream local, partial cumulative, and cumulative unimpaired flows to downstream nodes.

7.9 Conclusions

Adjustments to remove negative local unimpaired flows from the existing 1939 to 2007 data may also be desirable to ensure their suitability for (1) combining and routing to produce various cumulative unimpaired flow time series at planning or multiple basic nodes, and (2) calculating low-flow statistics imposed as constraints on water availability assessments performed using the River Basin Planning Tool. If negative adjustments are required, approaches to adjust zeros on a local, annual, and entire period of record basis (AdjustExtreme, annual, and POR adjustments) are recommended.

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8. Tennessee (TN) River Basin

8.1 TN Basin Description

The TN basin drains an area of 2,100 square miles in northern Georgia and small portions of southwestern North Carolina, southeastern Tennessee, and northeastern Alabama. The Georgia portion of the TN basin is split between three tributaries along the northern border of Georgia. The Little Tennessee River basin drains an area of 85 square miles and begins in the state of Georgia and drains north into North Carolina. The Toccoa-Nottely-Hiwassee River basin drains an area of 1,030 square miles and begins in the state of Georgia and drains northwest into Tennessee and North Carolina. The South Chickamauga-Lookout Creek basin drains an area of 970 square miles and begins in the states of Georgia and Alabama and drains north into Tennessee.

Toccoa-Nottely-Hiwassee River basin flows are regulated by TVA reservoirs on each of the three major rivers. The TVA reservoirs are operated primarily as flood control and hydropower facilities. The three reservoirs – Blue Ridge (BLRIDG_R), Nottely (NOTLY_R), and Chatuge (CHATUG_R) – all comprise basic or planning nodes for surface water availability assessment purposes. The Little Tennessee River and the South Chickamauga-Lookout Creek basins are largely unregulated. The TN study basin map showing node locations and local drainage areas for each is shown on Figure 8-1.

8.2 Hydrological Data

8.2.1 Streamflow Records

Approximately 26 stream gage stations are located within the TN basin, of which only 12 have continuous data covering at least 20 percent of the period for which unimpaired flows are to be extended; three of these cover at least half of the entire period. All nodes in the TN basin required complete time series for 1939 through 2007. The LITLE_TN node required filling for the entire period. Gage locations are shown on Figure 8-2, and PORs for gages used in filling are shown on Figure 8-3.

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Figure 8-1 TN Study Basin Basic and Planning Nodes

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Figure 8-2 Nodes and Gages Associated with TN Study Basin Streamflow Filling

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Figure 8-3 Periods of Record for Gages Associated with TN Study Basin Streamflow Filling

8.3 Reservoir Data

TVA provided pool elevation, release, and computed inflow time series for Blue Ridge, Nottely Dam, and Chatuge Dam. TVA also provided storage-area-elevation relationships for each reservoir. The time series and reservoir characteristics were used in subsequent local incremental flow and net evaporation computations.

8.4 Climatological Data

Precipitation and evaporation data were required for each reservoir to remove the effects of net evaporation in the unimpaired flow calculations. The data used and the subsequent net evaporation calculations were applied consistently across the state, as described in Section 6.4.3.

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8.5 Water Use Data

The Water Use Data Inventory Report documents present and hindcasted municipal and industrial withdrawals and returns and agricultural withdrawals within the TN basin. Net uses of each type are aggregated by reach and summed to produce an aggregate water demand for each reach. The aggregate water demand is used in subsequent local incremental unimpaired flow calculations. HECDSS pathnames for TN water uses are shown in Table 8-1 for each node. Note that agricultural water use is limited to the CHICKMGA reach.

Table 8-1 HECDSS Catalog Listing for Aggregated Water Use in the TN Basin T1 TN-HIAWAS CHATUG_R FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T70 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T139 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T694 TN-LOOKCR ENGLAND FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T763 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T832 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T1318 TN-LTENN LITLE_TN FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T1387 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T1456 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T1942 TN-NOTTLY NOTLY_R FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T2011 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T2080 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T2635 TN-OCOEE COPRHILL FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T2704 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T2773 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T3259 TN-SCHKCR CHICKMGA FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T3328 ------COMP-REACH-A 1DAY 01JAN1939 - 01JAN2007 T3397 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T3466 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T3952 TN-TOCCOA BLRIDG_R FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T4021 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T4090 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007

8.6 Reservoir Effects

Reservoirs impact the natural streamflow by (1) storing and releasing water from storage and by (2) changing the runoff characteristics over the reservoir surface area, resulting in evaporation losses from the reservoir surface area and increased runoff from precipitation falling on the reservoir surface rather than the land. Both factors were accounted for in the unimpaired flow calculations for the Blue Ridge, Nottely, and Chatuge reservoirs in the TN basin.

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8.6.1 Reservoir Holdouts and Inflow Calculations

For each of the three TVA reservoirs, net reservoir inflow was computed as:

I = O + ∆S

Where:

I = Net reservoir inflow O = Reservoir outflow (release) ∆S = Change in storage (reservoir holdout)

The change in storage was computed from the observed pool elevation data and the storage-elevation curve provided by TVA for the reservoirs.

The resulting calculated inflow time series were reviewed to identify any periods resulting in negative values. The corresponding pool elevations were checked to determine if clearly erroneous pool elevation data caused the negative values. No corrections were made to the TVA reservoir elevation time series as a result of this review.

8.6.2 Net Evaporation

Calculations of net evaporation require estimates of reservoir evaporation, precipitation, and a representative runoff coefficient for the reservoir area prior to the construction of the reservoir. The calculations of these factors were consistently applied across the state, as described in Section 2.3.2, resulting in a net evaporation time series for each reservoir.

8.6.3 Net Reservoir Effects

The net reservoir effect is computed as the sum of reservoir holdouts and net evaporation. However, these are applied at separate stages in development of unimpaired flows, as follows:

• Holdouts are applied to compute reservoir inflows for each reservoir, which are subsequently used during filling and routing for determination of unimpaired flows.

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• Net evaporation is applied as the remaining reservoir effect, in conjunction with net water use, in the determination of local incremental unimpaired flows.

8.7 Streamflow Filling, Routing, and Reservoir Inflows

Unimpaired flow development removes human impacts – net water uses and reservoir regulation (holdouts and net evaporation) – from observed streamflow or computed net reservoir inflow.

8.7.1 Methods Summary

Table 8-2 lists streamflow filling periods and methods for the TN basin.

Table 8-2 TN Streamflow Filling and Routing Summary

Filled Streamflow or Node Reservoir Inflow Period Filling Method/Gage(s) Used for Filling ENGLAND 1/1/39 – 9/30/78 Multiple linear regression (Summerville, Chickmga) 10/31/78 – 8/29/79 Fill with Summerville using MOVE2

CHICKMGA 10/31/78 – 9/30/80 Multiple linear regression (Sequatchie, Summerville) 6/23/97 – 11/10/01 Multiple linear regression (Sequatchie, Summerville)/Fill with Summerville – MOVE2 BLRIDG_R 1/1/39 – 12/31/41 Inflow: Fill with Dial using MOVE2 Outflow: Fill using daily average change in storage and filled Inflows COPRHILL 1/1/39 – 9/1/42 Fill with Ellijay using MOVE2

7/16/71 – 12/31/07 Fill with Ellijay using MOVE2

NOTLY_R 1/1/39 – 1/22/42 Inflow: Fill with Dial using MOVE2 CHATUG_R 1/1/39 – 2/11/42 Inflow: Multiple linear regression (Dial, Judson) LITLE_TN 1/1/39 – 12/31/07 Filled using data from Prentiss ad Iotla

Specific filling calculations are subsequently described.

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8.7.2 England (ENGLAND)

The England streamflow record contained missing data for one period (1/1/1939 – 8/29/1979). The missing local flow was filled using nearby tributary gages. The following specific steps were completed:

• The Summerville and Chickmga gage records were used to determine a multiple linear regression relationship with England. Table 8-3 presents the resulting regression equation and correlation from the filling.

• This multiple linear regression relationship was used to fill all missing data at England except the missing period in 1978.

• The 1978 missing local flow data were filled using a monthly MOVE2 relationship with the Summerville gage. No filled data were included when developing the second regression relationship. Table 8-4 presents the resulting monthly regression equations and statistics from the filling.

• The fill using the multiple linear regression relationship resulted in negative flows with a maximum value of –35 cfs in a single month (October 1978). The negative flows were set to zero for this month.

Table 8-3 Annual Multiple Linear Regression Results: England (Y), Chickmga (X1), and Summerville (X2)

Y = A + BX1 + CX2 Period A B C R2 Annual –15.9 0.14 0.49 0.736

Table 8-4 Monthly MOVE2 Results: England (Dependent) and Summerville (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg January 44.55 0.73 0.6512 356.08 424.88 0.84 February –3.57 0.84 0.7422 452.06 531.79 0.85 March –30.05 0.83 0.8055 349.9 518.25 0.68 April –74.43 0.94 0.7639 237.78 349.59 0.68 May –140.91 1.11 0.7515 353.64 247.74 1.43

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Table 8-4 Monthly MOVE2 Results: England (Dependent) and Summerville (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg June –83.36 0.99 0.6333 125.85 99.53 1.26 July –14.87 0.53 0.7329 73.85 76.78 0.96 August –280.16 2.63 0.0555 484.69 64.86 7.47 September –134.96 1.6 0.7698 254.69 92.51 2.75 October –127.43 1.42 0.5549 338.26 83.44 4.05 November –48.81 0.87 0.7441 207.06 176.5 1.17 December –67.23 0.95 0.6926 311.98 293.73 1.06

8.7.3 Chickamauga (CHICKMGA)

The Chickamauga streamflow record contained missing data for two periods (10/1/1978 – 9/30/1980 and 6/23/1997 – 11/10/2001). The missing local flow was filled using nearby tributary gages. The following specific steps were completed:

• The Sequatchie and Summerville gage records were used to determine a multiple linear regression relationship with Chickmga.

• This multiple linear regression relationship was used to fill all missing data at Chickmga except the missing period between June 1997 and September 2001 as well as smaller time periods between 1994 and 1997. Table 8-5 presents the resulting regression equation and correlation from the filling.

• The remaining missing local flow data were filled using a monthly MOVE2 relationship with the Summerville gage. No filled data were included when developing the second regression relationship. Table 8-6 presents the resulting monthly regression equations and statistics from the filling.

Table 8-5 Annual Multiple Linear Regression Results: Chickmga (Y), Sequatchie (X1), and Summerville (X2)

Y = A + BX1 + CX2 Period A B C R2 Annual –7.3 0.36 1.22 0.801

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Table 8-6 Monthly MOVE2 Results: Chickmga (Dependent) and Summerville (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg January 90.73 1.98 0.7334 937.82 1,231.09 0.76 February 12.57 2.13 0.687 1,234.33 1,503.25 0.82 March 50.50 1.93 0.6575 1,253.36 1,417.3 0.88 April –33.42 1.88 0.6644 599.43 864.58 0.69 May –149.66 2.3 0.5793 901.94 625.52 1.44 June –99.42 2.29 0.655 275.21 344.93 0.80 July –83.65 2.38 0.554 444.1 360.74 1.23 August 13.50 1.57 0.4541 178.25 226.63 0.79 September –110.87 2.8 0.7211 561.37 323.33 1.74 October –155.81 2.75 0.7676 396.99 296.63 1.34 November 8.25 2.04 0.7304 640.03 524.53 1.22 December –34.41 2.28 0.7893 691.66 891.3 0.78

8.7.4 Blue Ridge Reservoir (BLRIDG_R)

For Blue Ridge Reservoir, filled inflow time series were required for calculation of the unimpaired flows at the BLRIDG_R node. Reservoir time series were unavailable prior to 1/1/1940. Filled reservoir release time series were required to compute a complete local incremental flow time series between the COPRHILL and BLRIDG_R nodes.

Blue Ridge Reservoir inflows were computed by mass balance of observed outflows and changes in reservoir storage (holdouts), as described in Section 8.6.1. The resulting inflow time series were extended using a monthly MOVE2 relationship with the Dial No. 03558000 gage located upstream of the reservoir.

Table 8-7 Monthly MOVE2 Results: Blridg_R Inflows (Dependent) and Dial (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg January –64.74 1.32 0.9559 120 707.21 0.17 February –101.76 1.37 0.9062 195.18 860.22 0.23 March –66.55 1.3 0.9576 143.63 963.57 0.15

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Table 8-7 Monthly MOVE2 Results: Blridg_R Inflows (Dependent) and Dial (Independent)

Y = A + BX RMSE Dependent Average 2 Period A B R (cfs) Flow, Obs. Period (cfs) RMSE/Q avg April –76.59 1.29 0.9483 109.3 885.37 0.12 May –55.44 1.28 0.9506 88 701.04 0.13 June –40.79 1.28 0.9125 86.05 539.33 0.16 July –22.83 1.27 0.8841 89.84 456.23 0.20 August –18.41 1.26 0.9575 78.54 397.93 0.20 September –43.11 1.35 0.8101 86.51 317.83 0.27 October –44.50 1.35 0.9125 113.82 332.69 0.34 November –20.45 1.26 0.9424 81.72 402.73 0.20 December –23.56 1.26 0.9452 104.26 549.04 0.19

The Blue Ridge Reservoir began operation prior to the start of release records. To fill the first year of reservoir release data (1939), assumptions related to the reservoir holdouts were required. The missing year of reservoir holdouts was estimated by averaging the historical holdouts each day of the year to produce a continuous annual time series. The reservoir release was filled by adding the average holdout time series to the filled reservoir inflow time series for the missing year.

8.7.5 Copperhill (COPRHILL)

The Copperhill streamflow record contained missing data for two periods (1/1/1939 – 9/30/1942 and 7/16/1971 – 12/31/2007). To avoid filling the missing periods based on regression relationships with flows affected by the upstream reservoir, the local observed flow was computed, the missing local flow was filled using a tributary gage, and the resulting filled local flow was added to the routed upstream flow from Blue Ridge Reservoir releases to produce a complete total flow time series at Copperhill. The following specific steps were completed:

• Local incremental flows at Copperhill were computed by routing upstream Blue Ridge Reservoir releases to Copperhill and subtracting this from the observed flow at Copperhill.

• The local incremental flow calculation resulted in many negative flow values because of limitations of the routing model. To develop the best estimate of the

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regression relationships, negative flows were removed using the AdjustExtremes command in TSTool prior to computing the regression.

• Low flows (less than 600 cfs) were smoothed by replacing the calculated local flow with a centered running average over seven days (three days before and three days after).

• The missing local flow data were filled using a monthly MOVE2 relationship with the Ellijay gage. Table 8-8 presents the resulting monthly regression equations and statistics from the filling.

• The fill using the MOVE2 relationship resulted in a few periods of negative flows. The negative values were set to zero.

• The filled local incremental flow for Copperhill was added to the routed Blue Ridge Reservoir releases to produce a complete total flow time series at Copperhill.

Table 8-8 Monthly MOVE2 Results: Coprhill_Local (Dependent) and Ellijay (Independent)

Y = A + BX RMSE Dependent Average Period A B R2 (cfs) Flow, Obs. Period (cfs) RMSE/Q avg January –12.45 0.52 0.864 123.67 326.08 0.38 February –34.83 0.52 0.8542 138.53 383.45 0.36 March –3.65 0.48 0.7562 163.87 393.81 0.42 April –49.49 0.54 0.5928 143.23 364.79 0.39 May –20.20 0.51 0.4161 161.73 305.42 0.43 June -36.96 0.55 0.3379 115.995 224.54 0.52 July 15.65 0.44 0.257 95.77 189.88 0.50 August –41.67 0.65 0.6888 116.27 178.32 0.65 September 13.94 0.5 0.2871 88.32 143.38 0.62 October 5.61 0.64 0.4043 214.76 177.56 1.21 November –6.12 0.61 0.8574 81.91 193.01 0.42 December –7.45 0.53 0.7334 114.59 228.41 0.50

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8.7.6 Nottely Dam (NOTLY_R)

Nottely Dam inflows were computed by mass balance of observed outflows and changes in reservoir storage (holdouts), as described in Section 8.6.1. The inflow contained missing data for one period (1/1/1939 – 1/22/1942). The computed Chatuge Dam inflows were extended using a monthly MOVE2 regression with Dial gage 03558000. Table 8-9 presents the resulting monthly regression equations and statistics from the filling. The filling resulted in some short periods with negative values, with a maximum negative value of –105 cfs. The negative values were set to zero.

Table 8-9 Monthly MOVE2 Results: Notly_R (Dependent) and Dial (Independent)

Y = A + BX RMSE Dependent Average Period A B R2 (cfs) Flow, Obs. Period (cfs) RMSE/Q avg January –178.06 1.14 0.8245 211.5 503.49 0.42 February –317.20 1.26 0.8284 246.81 584.71 0.42 March –301.82 1.18 0.8405 257.69 645.62 0.40 April –293.12 1.13 0.7597 213.18 561.7 0.38 May –310.70 1.26 0.7403 204.7 446.56 0.46 June –146.85 1.07 0.6801 141.79 341.85 0.41 July –98.66 1.06 0.622 147.11 298.76 0.49 August –155.81 1.32 0.7937 184.87 278.93 0.66 September –85.73 1.17 0.6623 104.62 229 0.46 October –163.88 1.45 0.7979 190.3 245.12 0.78 November –61.65 1.05 0.8594 109.17 295.27 0.37 December –84.24 1.04 0.8509 147.05 394.88 0.37

8.7.7 Chatuge Dam (CHATUG_R)

Chatuge Dam inflows were computed by mass balance of observed outflows and changes in reservoir storage (holdouts), as described in Section 8.6.1. The inflow contained missing data for one period (1/1/1939 – 9/30/1942). The computed Chatuge Dam inflows were extended using a multiple linear regression relationship with the Dial No. 03558000 and Judson No. 03507000 gages. Table 8-10 presents the resulting multiple linear regression coefficients.

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Table 8-10 Annual Multiple Linear Regression Results: Chatug_R (Y), Dial (X1), and Judson (X2)

Y = A + BX1 + CX2 Period A B C R2 Annual –83.6 0.82 0.08 0.814

8.7.8 Little Tennessee (LITLE_TN)

The Little Tennessee node is a synthetic node with no streamflow data available over the period of record. The gage was filled by routing observed flows from Prentiss upstream to Little Tennessee, scaling the routed flows by the ratio of drainage areas between Prentiss and Little Tennessee, and directly filling the period after 6/1/1944. The remaining time period was filled by routing observed flows from Iotla upstream to Little Tennessee, scaling the routed flows by the ratio of drainage areas between Iotla and Little Tennessee, and directly filling the remaining period.

Because of a lack of data to calibrate a routing model, routing parameters were estimated using reach lengths between the Little Tennessee node and the downstream gages and routing characteristics from nearby reaches.

Drainage areas and associated scaling ratios are presented in Table 8-11.

Table 8-11 LDAs and Scaling Ratios for the Little Tennessee Flow Filling

Node Total Drainage Area (mi 2) Drainage Area Ratio LITLE_TN 44.5 -- PRENTISS 140 0.40 IOTLA 323 0.17

8.8 Local Incremental Flow Calculation and Adjustments

The TN study basin was unique in that there was only one node (COPRHILL) located downstream of other nodes; the remainder were headwater nodes. The local incremental flow for the COPRHILL node was computed as a part of the streamflow filling process described in Section 8.7.5.

Table 8-12 lists TSTool command files and HECDSS macros applied to TN filling, routing, and local incremental flow calculation.

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Table 8-12 TSTool Command and HECDSS Macro File Listing for TN Basin Local Incremental Flow Determination

Run_TN_Filling.TSTool Runs files to fill all nodes in the TN basin Populates all observed time series to be used InitialPopulate_TN_dss.TSTool in the filling for the TN basin ENGLAND_fill.TSTool Filling for England EnglandMLR.MCO Computes MLR for England CHICKMGA_fill.TSTool Filling for Chickmga ChickmgaMLR.MCO Computes MLR for Chickmga BLRIDG_R_fill.TSTool Filling for Blridg_R COPRHILL_fill.TSTool Filling for Coprhill NOTLY_R_fill.TSTool Filling for Notly_R CHATUG_R_fill.TSTool Filling for Chatug_R ChatugMLR.MCO Computes MLR for Chatug_R LITLE_TN_fill.TSTool Filling for Litle_TN

8.9 Local Incremental Unimpaired Flow Calculation

The final stage of local incremental unimpaired flow determination involves aggregation and removal of remaining impairments (reservoir net evaporation and net water use) from local incremental flows.

8.9.1 Negative Local Unimpaired Flow Adjustments

A no-negative local incremental unimpaired flow policy was adopted for this study, in consideration of potential application to water availability assessments subject to various minimum flow constraints, including annual or monthly 7Q10 (10-year 7-day low flow). Moreover, many reservoir system operational models do not allow for negative local incremental flows. The utility of unimpaired flows computed in this study is maximized by systematic “intelligent” removal of negative values with minimal alteration to surrounding non-negative values, as opposed to cruder methods employed by operational models.

While negative local incremental flows were removed to the maximum extent possible by refinements to reservoir holdouts, routing and filling procedures, and short-duration (three- to five-day) smoothing and averaging, some residual negatives remained at the unimpaired flow determination stage. To remove these, three approaches were

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan employed, listed as follows in order of minimum number of adjacent time periods adjusted:

• The AdjustExtreme TSTool procedure, which averages values on either side of the negative value for as many days as necessary to produce a non-negative result. This method works best with intermittent as opposed to continuous periods of negative flows. Where extended periods of negative flows occur, the AdjustExtreme procedure produces multi-month periods of constant low flow.

• Annual adjustment – A DSSMATH procedure that increases all negative flows to zero and reduces all positive values by a factor equal to the ratio of the original (with negatives) annual average flow to the adjusted (no negatives) annual average flow.

• POR adjustment – Same as annual adjustment with the reduction factor computed using 1939 to 2007 POR average flow ratios.

8.9.2 Selection of Final Local Unimpaired Flow Time Series

For the TN basin, adjustments were made for negative flow values during the streamflow filling stage. However, the addition of net evaporation results in negative flow values in the unimpaired flow time series as a result of overestimation of precipitation for particular events. The AdjustExtremes TSTool procedure effectively removed these negative flow values for each of the three reservoir nodes. No negative flow adjustments were necessary for the locations without reservoirs.

Final local unimpaired flow time series selection is denoted by an asterisk at the end of the F pathname denoting the adjustment required (e.g., F= UNIMP-0ADJ LOC*). Example TN DSS pathnames for unimpaired flows and local inflow, reservoir effects, and water use constituents are shown in Table 8-13.

Table 8-13 Sample Condensed Catalog Listing of TN Unimpaired Flow and Component Time Series T694 TN-LOOKCR ENGLAND FLOW-DIV NET COMP-REACH TOTAL 1DAY 01JAN1939 - 01JAN2007 T763 ------COMP-REACH-I 1DAY 01JAN1939 - 01JAN2007 T832 ------COMP-REACH-M 1DAY 01JAN1939 - 01JAN2007 T901 ------FLOW-LOC INC FILLED 1DAY 01JAN1939 - 01JAN2007 T970 ------UNIMP 1DAY 01JAN1938 - 01JAN2007 T1040 ------UNIMP* 1DAY 01JAN1939 - 01JAN2007 T1109 ------UNIMP-0ADJ ANNUAL 1DAY 01JAN1938 - 01JAN2007 T1179 ------UNIMP-0ADJ LOC 1DAY 01JAN1939 - 01JAN2007 T1248 ------UNIMP-0ADJ POR 1DAY 01JAN1938 - 01JAN2007

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8.10 Quality Control

Because primary quality control was performed at each stage of TN basin unimpaired flow development (water use data, reservoir effects, and filling/routing), final stage quality control relied on (1) comparison of average local unimpaired flow volumes pre- and post-2002, and (2) consistency plots, in which individual nodes are grouped and differences between accumulated unimpaired flow for individual nodes and average accumulated unimpaired flow for the group are compared. These checks revealed no major discrepancies in the local unimpaired flow data.

8.11 Cumulative Unimpaired Flows

Six of the seven TN nodes are headwater nodes, where the local unimpaired flow equals the cumulative unimpaired flow. For the remaining node (COPRHILL), the cumulative unimpaired flow was computed by routing the unimpaired flow from BLRIDG_R downstream to COPRHILL and summing this with the local COPRHILL unimpaired flow time series.

Final local incremental unimpaired flows at each node for each study basin will be presented in a written summary and graphical manner.

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Unimpaired Flow Data Report Surface Water Availability Modeling and Technical Analysis for Statewide Water Management Plan

9. References

Georgia Environmental Protection Division (EPD). 1997a. Chattahoochee River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 1997b. Flint River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 1998a. Coosa River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 1998b. Oconee River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 2001a. Savannah River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 2001b. Ogeechee River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 2002a. Ochlockonee River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 2002b. Suwannee River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 2002c. Satilla River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 2002d. St. Marys River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 2004a. Altamaha River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

Georgia Environmental Protection Division (EPD). 2004b. Ocmulgee River Basin Management Plan. Georgia Department of Natural Resources (DNR). Atlanta, GA.

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