Extract of Amaila Falls Hydrology Review Draft Report 23June2011

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© Halcrow Group Limited 2011

PPA Energy

Amaila Falls Hydropower Project

Hydrology Review

Draft Report

June 2011

Halcrow Group Limited

PPA Energy

Amaila Falls Hydropower Project Hydrology Review

Draft Report

Contents Amendment Record This report has been issued and amended as follows: Issue Revision Description Date Approved by

1 0 Draft Report 23/06/11 ZR

Amaila Falls Hydropower Project Hydrology Review Draft Report

Draft Report 23 June 2011 as submitted.doc

Contents

Executive Summary 1

1 Introduction 4

2 Project Summary 6 2.1 The Project Location and Components 6 2.2 Hydropower Facility 7

3 Hydrology Review 8 3.1 Introduction 8 3.2 Review of Amaila Falls Hydroelectric Project Feasibility Study

Report, Kaehne Consulting Ltd., June 2002 8 3.3 Amaila Falls Hydroelectric Project Guyana Feasibility Study

Report Hydrology, Montgomery Watson Harza, December 2001 9

3.4 Hydroelectric Power Survey of Guyana Final Report, Montreal Engineering Company Limited, April 1976 28

4 Review of Relevant Studies 35 4.1 Review of Hydraulic Headloss 35 4.2 Other Factors that Affect Energy Yield Estimation 36 4.3 Power Plant Output 38 4.4 Review of Sedimentation Control Plan and Management

Strategy 38

5 Energy Yield and Power Output Assessments 41 5.1 Basic Data and Assumptions 41 5.2 Energy Yields and Plant Output Assessments 42 5.3 Energy Yield Assessments for a “Dry” Year 44 5.4 Sensitivity Analysis 46 5.5 Uncertainty Analysis 47 5.6 Assessment of climate impacts on hydropower production 49

6 Summary and Conclusions 54 6.1 Review of Hydrology Studies 54 6.2 Review of Relevant Studies 55 6.3 Energy Yield and Power Output Assessments 55

References 57

Annex 1 Amaila Falls Hydropower Project Salient Feature 58

Annex 2 Main Data Used in Energy Yield Assessments 61

Annex C Site Visit Report 64


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Doc No 0 Rev: 1 Date: June 2011 1 C:\RAFHHR\Reports\Draft Report 23 June 2011 as submitted.doc

Executive Summary

Halcrow Group Limited (Halcrow) was commissioned by Power Planning Associates Ltd (PPA Energy) to undertake Hydrology Review of the Amaila Falls Hydropower Project (the Project) in Guyana.

The Halcrow team carried out an initial review of the feasibility study reports together with the recent environmental and social impact assessment report and other documents related the Project. Subsequently, an inspection was undertaken on the two hydrometric gauging stations located located on the Kuribrong River downstream of Amaila Falls and on Potaro River upstream Kaieteur Falls. Further analysis was focused on the uncertainties of streamflows which were derived for the design of the Project and its impact on the capability of the Project to produce the energy. We have also undertaken review on other factors related to the prediction of the power generated from the Project, including hydraulic head losses, turbine and generator efficiencies and other power losses at the power station and along the transmission line, together with impact of climate changes, sedimentation management plan, etc.

This draft report describes our preliminary findings which are summarised as follows:

(1) We have reviewed hydrology study reports produced during pre-feasibility (1976) and feasibility (2001) stages of the Project and undertaken further analysis based on data contained therein and data obtained from visits at the Hydro-meteorological Service of the Ministry of Agriculture in Guyana; Various sources of uncertainty in the use of a monthly flow series from an adjacent catchment (Potage River at Kaieteur Falls) and a simple transposition factor for deriving monthly flows upstream of Amaila Falls have been assessed. These include uncertainties in both hydrometric measurements taken downstream of the Amaila Falls site in 1975 and 2001, and uncertainties in the development of stage-discharge relationships at both Kaieteur Falls and Amaila Falls.

(2) Notwithstanding the identified uncertainties, we concluded that, given the available hydro-meteorological data, a transposition factor of 0.3 applied to the monthly flow data at Kaieteur Falls is suitable for estimating baseline monthly flows upstream of Amaila Falls.

(3) We have reviewed other factors/coefficients that affect power output estimate of the power plant and our judgements are as follows:

• for hydraulic headloss in the water conduits, a constant value of 15 m is not adequate and could result in an overestimate of power output by up to 2% when all turbine-generator units run at full design capacity;


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• other factors, such as the turbine-generator efficiency, rate for scheduled and unscheduled outages of the plant, are considered to be reasonable;

• the power loss rates are considered low for such a long distance transmission line.

(4) We have undertaken review on available sediment data and current estimate of siltation rate, sediment management plan, and its impact on both reservoir storage and turbine efficiency/deterioration, our assessments are:

• there is no reservoir sedimentation mitigation plan besides a broad proposal that effort should be made to minimise erosion from overland flows in the watershed area;

• there is no provision for flushing outlets at the dam and the low level outlet which is designed to meet compensatory flow is inadequate for reservoir flushing or density current venting operations;

• the long term distribution of sediment in the reservoir is unclear, which may affect power generation if coarse sediment settles in the upper backwater region which may be part of the live storage of the reservoir;

• sedimentation is not expected to affect power generation in the early life of the turbines; however for a long term if sedimentation reaches the deeper region of the dam, bed level at the dam is anticipated to reach drawoff intake level and therefore may affect drawoff requirements to the powerhouse.

(5) We have estimated the power output from the turbine-generator unit by taking account of the hydraulic headlosses using typical turbine and generator efficiencies; our estimate indicates that at the rated design flow of 50.2 m3/s the unit achieves approximately 153.5 MW output while the reservoir is at full supply level, which is about 7% lower than the quoted value of 165MW.

(6) We have estimated the energy yield based on the baseline flows of 41 years and obtained that:

• an average annul energy yield at the generator terminals is estimated as 1141 GWh, with the minimum and maximum yields being 884 GWh and 1343 GWh, respectively;

• an average annual energy output from the power plant (at the transformer terminals taking account of machine outages and transformer loss) is estimated as 1090GWh;

• an average annual power available at the distribution point (at Linda and Georgetown) is estimated from 1017 GWh to 1047 GWh taking account of transmission line losses;

• for a dry year (90% dependable annual flows), the annual energy yield is estimated at 994.8 GWh when the monthly average flows are used for simulation. However, when daily flows are used for simulation the annual energy yield estimate reduces to 952.8


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GWh, indicating that using monthly flows could overestimate the energy yield by up to 4.2%.

(8) We have assessed the energy yield with different reservoir full storage levels (FSL) and simulation results indicate that as compared to the existing designed FSL at 431.55 m the average annual energy yield would increase by up to 3.75% and 6.7% if the FSL was increased to 434 m and 435.5 m, respectively.

(9) We have undertaken uncertainty analysis of the energy yields with regard to the transposition factor varying from 0.276 to 0.437. We can have a high level of confidence that the average energy output is between 1046 GWh and 1129 GWh considering machine outages and transformer losses.

(10) A preliminary climate change impact analysis of relevant General Circulation Model (GCM) and Regional Circulation Model (RCM) results for the Project indicates that there is a wide variety of predictions of how rainfall patterns may change in the future but suggests that there is a tendency for models to predict a general decrease in rainfall in the area which would typically cause a resultant reduction in river flows at the project site. Based on indicative climate change related decreases in rainfalls, and assuming a linear response between modelled rainfall and flows in the Amaila Falls catchment, the predicted river flows are used to model possible likely impact on future energy yields. The simulated energy yields indicate that the impact of climate could result in reduction in annual energy yield from 1.3 to 2% for different scenarios when reductions in rainfall range from -0.6 to -2.9%..

It should be noted that the analysis and assessments presented in this report are subject to the accuracy and completeness of the background information and data provided.


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1 Introduction

Halcrow Group Limited (Halcrow) was commissioned by Power Planning Associates Ltd (PPA Energy) to undertake a Hydrology Review of the Amaila Falls Hydropower Project in Guyana.

The purpose of the Hydrology Review is to assess the capability of the Project to produce the energy that will be purchased by Guyana Power and Light (GPL) under the long-term Power Purchase Agreement (PPA). The hydrology review will be a key element of the overall analysis and design of the Project as hydrology will have a direct impact on the financial obligations of GPL.

The main tasks can be summarised as follows:

(1) Reviewing the existing results, and any relevant studies, including sedimentation control plans, as well as the quality of hydrologic data gathered to assess the overall validity of the data and ultimately confirm whether these studies are consistent with best industry practices.

(2) Advising on whether the quality of the data obtained and methodology applied, taken into account the characteristics of the project site, could be used to adequately extrapolate the hydrology for the project or if not, what would be necessary to do so.

(3) Providing input to the Inter-American Development Bank regarding any modifications to the Project’s generation/ dispatching figures that will serve as an input for the Project’s pro-forma financial projections.

(4) Providing an opinion indicating if the currently available information/models for climate change could be incorporated into the hydrology scenarios and provide a preliminary opinion on how the potential changes in rainfall patterns expected due to climate change could affect, in the long term, the project’s hydrological projections and the level of confidence with which such an impact can be assessed.

(5) Based on (1) through (4) above and taking into account the characteristics of the project and available information, assess if an alternative estimate of the project’s basin hydrology and dispatching scenarios should be developed and/or what additional considerations, measurements, studies, if any, might be necessary to help assess the Project´s basin hydrology within acceptable standards for projects of this nature.

The following principal activities were therefore necessary:

• Examining the available data and assessing the suitability and applicability of the studies undertaken to assess the water available to produce energy.


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• Providing a high level assessment of the energy yields from the project and whether the project is likely to generate the power rating and the energy yield as per the documentation.

• Identifying the degree of sedimentation risks to the Project and how this would affect the operation and energy yield.

• Building a bespoke energy yield model and carrying out energy yield uncertainty analysis by explicitly considering the uncertainty in the transposing of the flow record in order to ascertain confidence levels to the hydrologic parameters used for the design of the Project.

• Undertaking review on climate change impact on rainfalls in the area which could potentially cause reduction in river flows at the Project site in the long term.

The above were undertaken as an initial review on the documents immediately available, followed by an on site visit to the two hydrometric gauging stations and meetings with members of the Hydro-meteorological Service of the Ministry of Agriculture, detailed desk study and reporting.

This draft report describes our preliminary findings of the Hydrology Review. It is organised as follows:

The Executive Summary highlights key contents of the report;

Section 1 summarises the main tasks and activities of the Hydrology Review study;

Section 2 contains a brief description of the Project;

Section 3 describes the detailed hydrology review;

Section 4 describes the review on other relevant studies, including review on sedimentation management plant, main factors which affect the power outputs of the Project;

Section 5 presents the energy yields assessments, including uncertainty and sensitivity analysis and climate impact on energy yields,.

Section 6 is a brief summary of the preliminary findings.

Annex A contains the principal features of the Amaila Falls Hydropower Project.

Annex B contains all data used for the energy yield and power output assessments.

Annex C is a short site visit report summarising Halcrow Hydrology Team’s main activities during their visit to Guyana from 18 to 22 May 2011, including some site visit photos.


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2 Project Summary

2.1 The Project Location and Components

The proposed Project is located at Amaila Falls in west central Guyana, approximately 250 km southwest of Georgetown as shown in Figure 1.

Figure 1 Site location and main project components

The Project includes a storage reservoir with a surface area of approximately 23.3 km2 (at full supply level) created by a 2.5 km long and 18.25 m high dam at the head of Amaila Falls at the confluence of the Kuribrong and Amaila rivers, crossing both rivers. Electricity produced at the plant will be delivered to Guyana’s capital, Georgetown, and its second largest town, Linden, by a 230kV electric transmission line and two new substations. To provide access to the Hydropower Facility, new roads will be constructed, and some existing roads will be upgraded.

The Project consists of the following three components:

• Hydropower Facility: dam, reservoir, water tunnel, powerhouse, onsite substation and switchyard and other ancillary systems.

• Electrical Interconnection: approximately 270 km of high-voltage, 230 k transmission line and two remote substations (one at Linden, the other at Georgetown).

• Access Road: 85 km of new roads, and upgrading approximately 122 km of existing roads.

The Hydrology Review is directly linked to the hydropower facility component.


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2.2 Hydropower Facility

The primary components of the hydropower facility are the dam, reservoir, and powerhouse as shown schematically in Figure 2.

The dam will be a concrete-faced rockfill structure about 2.5 km long, crossing the Kuribrong and Amaila rivers, with a ridge dam between them. The dam will create a primarily contiguous reservoir of approximately 23.3 km2 in area at full supply level which is 431.55 m (amsl), providing an active storage volume of about 101 million m3.

The spillway will be located on the Amaila section of the dam and, when operating, water flowing over the spillway will continue over the Amaila Falls and down the reduced-flow segment of the river to join with water flowing from the powerhouse tailrace and into the Kuribrong River. The spillway will also incorporate a Minimum Environmental Flow (MEF) feature to pass water to part of the reduced-flow section and down the falls during periods when there is no water otherwise flowing over the spillway. Water from the reservoir will be delivered to the turbine generators via a water intake structure and conduit system, consisting of a headrace tunnel, vertical shaft, and power tunnel.

Figure 2 Schematic of the power plant

The powerhouse will house 4 Francis-type hydro-turbine generators, each of equal capacity of 41.25 MW. The powerhouse will be located at the bottom of the Amaila Falls escarpment, approximately 3 km from the water intake. The main electrical substation and switchyard will be located adjacent to the powerhouse. The Plant will also include a Pelton-type hydro-turbine auxiliary generator, emergency diesel generators and other support, backup and ancillary systems.

The details of the project salient features are listed in Annex 1.


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3 Hydrology Review

3.1 Introduction

The review of the existing hydrological results is based on an analysis of three key hydrological reports and information obtained during the project team’s visit to Guyana from 18 to 22 May 2011, including site visits to the hydrometric gauging stations located on the Kuribrong River downstream of Amaila Falls and on Potaro River upstream Kaieteur Falls and meetings at the Hydro-meteorological Service of the Ministry of Agriculture.

The key reports reviewed are:

• Review of Amaila Falls Hydroelectric Project Feasibility Study Report, Kaehne Consulting Ltd. June 2002 (Ref 1)

• Amaila Falls Hydroelectric Project Guyana Feasibility Study Report Hydrology, Montgomery Watson Harza , December 2001 (Ref 2)

• Hydroelectric Power Survey of Guyana Final Report, Montreal Engineering Company Limited , April 1976 (Ref 3 )

The review of these reports, supplemented by additional data analysis, has sought to establish the uncertainty in various components of the hydrological analysis undertaken to date in identifying the available water for use in Amaila Falls power generation studies.

3.2 Review of Amaila Falls Hydroelectric Project Feasibility Study Report, Kaehne Consulting Ltd., June 2002

The Kaehne feasibility study report review was provided to Halcrow for review prior to the site visit. It provides a review of the feasibility study report produced by Montgomery Watson Harza in December 2001 (see § 3.3) and the relationship between the Kaieteur Falls and Amaila Falls catchments. It suggests that “at no stage have concurrent hydrological data been collected to verify the relationship between the two water basins” and recommends that “additional stream flow data be collected at the base of the Amaila Falls for at least a sufficient period to confirm the relationship with Kaieteur [Falls]”. A brief reference is made to the flow records available at Kaieteur Falls (1950 to 1991) and flow transposition based on an average flow ration of 0.30 (with arrange of 0.24 to 0.40) but no details of this transposition are reported.

It is suggested that recent rainfall in the region has become “more spread out across the seasons” and accordingly the “effect of the dry season should be less”.

Kaehne also suggest that uncertainty in reservoir storage is a “critical design prerequisite” in determining the amount of available water in the dry season.


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3.3 Amaila Falls Hydroelectric Project Guyana Feasibility Study Report Hydrology, Montgomery Watson Harza, December 2001

The MWH feasibility study report was provided to Halcrow for review prior to the site visit. It contains, inter alia, documentation on regional hydro-meteorological data, Kuribrong river field measurements undertaken in 2001, streamflow analysis and reservoir evaporation.

3.3.1 Hydro-meteorological Data

MWH present a summary of hydro-meteorological data collated from the Hydro-meteorological Service and considered by the feasibility study. This is reproduced in Table 1.

Table 1: List of hydro-meteorological data (after MWH, 2001)

It is stated that rainfall and pan evaporation at the Kaieteur Falls meteorological station is “representative for the project site”. No further consideration is given to placing these observed data in the context of regional records.

All datasets are characterised by periods of extensive missing data. The HEC-4 monthly streamflow simulation model was used to infill missing


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data (72 months in a 492 month period)1 in the monthly record for Kaieteur Falls. The infilled flow record is shown in Figure 1.

Figure 1: Kaieteur Falls monthly flow record – infilled (after data reproduced from MWH, 2001)

Kaieteur Falls, Potaro River (1950-1990)

0

100

200

300

400

500

600

700

800

1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990

Date

Flow (m

3/s)

NB: Infilled data shown in red

The annual (infilled) streamflow series was checked for consistency visually through plotting annual totals, a 5-year running average and a single mass curve (as presented in Figures 2 and 3, pg. 16). These figures are repeated in Figure 2.

1 Erroneously, Table 1 suggests that 79 months of data were infilled for Kaieteur Falls.


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Figure 2: Kaieteur Falls annual flow record and single mass curve (after MWH, 2001)

(a) Annual Flows

(b) Single Mass Curve

A “cyclic trend” is observed and tentatively related with El Nino episodes, although it is noted that “there is no one-to-one correspondence between the incidence of El Nino and dry streamflow years at Kaieteur Falls”. Figure 2(a) shows that only a single cycle of approximately 20 years is identifiable from the observed data and as such confidence in the persistence of this cycle is low.

Further tests to check the consistency of the annual streamflow have been undertaken using both a linear trend model and classical decomposition. Figure 3 shows the identified trends suggesting that with a simple linear model (a) there is a reducing trend of 0.36 m3/s per year whereas with a decomposition model that includes a 20 year seasonal cycle (b) there is an


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increasing trend of 0.86 m3/s per year. The reported accuracy measures suggest that the decomposition model is the preferred model.

Figure 3: Kaieteur Falls streamflow 1950-1990 consistency checks (after data reproduced from MWH,

2001)

(a) Linear trend model

(b) Decomposition model (20 year cycle)

The relative importance of the uncertainty associated with the infilling of missing data is informed through a comparison of the magnitude of the infilled data with the observed daily data flow duration curve (as presented by MWH in Table 14, pg. 17). Table 2 and Figure 4 reproduce the monthly / annual flow duration data, indicating that higher than average flows are typically constrained to the May to August period. Table 2 indicates that the infilled missing data tends to be associated with


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moderate flows (i.e., the 35 to 65 %’ile range). As such, uncertainty with the infilling process is considered to have a negligible impact on the overall uncertainty associated with the derived inflow series for Amaila Falls site.

Table 2: Kaieteur Falls Flow Duration Table (after MWH, 2001)

Flow Duration Table Based on Daily Discharge Measurements (m3/s) at Kaieteur Falls, Potaro River (after MWH, 2001)

Probability of

exceedence (%)Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual

0.5 668.4 750.5 563.6 909.1 909.1 1076.2 807.1 756.1 606 430.5 456 591.9 835.4

1 645.7 591.9 535.2 807.1 855.3 991.2 778.8 679.7 529.6 305.9 393.6 535.2 776

2 594.7 509.8 472.9 722.2 798.6 911.9 759 628.7 450.3 266.8 328.5 478.6 708

3 574.9 475.8 436.1 676.8 770.3 858.1 727.8 574.9 396.5 220 305.9 458.8 662.7

4 532.4 441.8 407.8 640 744.8 826.9 708 546.6 348.3 207.3 276.1 436.1 634.4

5 509.8 422 390.8 597.6 730.7 807.1 682.5 509.8 334.2 191.2 247 413.5 606

10 427.6 345.5 308.7 467.3 674 699.5 603.2 433.3 259.1 132 181.5 337 495.6

15 371 294.5 235.1 393.6 631.5 640 540.9 388 216.6 106.2 143.6 300.2 427.6

20 339.8 253.7 200.2 320 591.9 606 498.4 348.3 183.5 90.6 120.1 269.6 371

25 294.5 214.7 166.8 257.4 543.7 572.1 467.3 317.2 164.3 76.5 102.5 236.8 317.2

30 264.8 180.7 141.3 218.3 504.1 546.6 430.5 300.2 143 67.1 89.2 208.4 277.5

35 238.7 161.7 124.6 178.1 467.3 526.8 399.3 281.8 126 59.5 73.3 182.4 243.6

40 203.9 140.5 106.8 150.1 430.5 506.9 373.8 263.9 111.6 54.4 63.4 166 209.6

45 179.8 122.3 95.4 128.3 390.8 492.8 356.8 244.4 101.4 50.7 57.5 147 178.4

50 161.7 106.2 85.5 108.2 348.3 467.3 334.2 233.9 92.9 47.3 52.4 135.9 152.9

55 139.1 91.2 75.9 91.2 303 444.6 317.2 218.3 83.8 44.7 48.4 118.1 124.6

60 121.8 78.7 67.1 77 272.4 427.6 297.4 202.2 74.8 42.8 45.3 104.8 107.6

65 105.6 70 60.9 66.3 244.4 399.3 277.3 183.5 68 40.8 41.3 91.2 87.8

70 91.8 61.5 55.8 57.2 199.4 373.8 253.7 171.1 62.3 38.8 39.1 77.6 73.1

75 80.4 54.9 51.3 51 161.7 348.3 236.8 158.3 57.2 36.8 36.8 63.2 60.9

80 68.5 49.3 46.7 45 120.9 317.2 214.7 145.3 52.4 35.1 33.7 55.5 52.4

85 58.3 43.9 43.3 40.2 83.8 288.9 194.8 129.7 47 32.9 30.3 49.3 45.6

90 51 37.4 39.6 36 57.5 251.8 173.6 114.7 43 30.9 27.8 44.7 39.9

95 43.9 28.2 30 29.5 41.1 210.1 133.7 97.4 38.2 28 23.9 36.8 31.7

96 41.9 27.4 26.8 26.2 36.8 191.4 126.9 90.6 37.4 26.7 23 32.3 29.7

97 37.7 25.9 25 21.2 33.7 181.5 115.3 77.6 36.5 25.8 22.2 30 27.5

98 29.5 22.9 23 15.7 31.7 165.1 102.8 69.4 35.1 24.8 21.3 27.9 24.6

99 24.1 20.3 20.9 14.1 26.4 144.4 90.6 54.1 32.9 23.3 19.4 26.4 22.1

99.5 21.6 17 15.2 12.6 23.9 129.1 83.3 49.6 31.4 22.4 18.4 24.9 19.8

100 18.9 14.2 13.2 11.2 11.2 80.4 21 21.2 29.5 20.9 17.3 21.6 11.2

Key: Data highlighted in an italic, bold red font indicates the range over which mising data has been estimated.


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Figure 4: Kaieteur Falls Flow Duration Curves (after data reproduced from MWH, 2001)

Kaieteur Falls Flow Duration Curves

0

200

400

600

800

1,000

1,200

0 10 20 30 40 50 60 70 80 90 100

Probabilioty of Exceedence (%)

Flow (m

3/s)

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Annual

3.3.2 Kuribrong river field measurements

Stage and velocity measurements at a location near the anticipated location of the powerhouse are reported.

Water levels were recorded at 15-minute intervals using a pressure transducer and data logger from December 2000. No details are provided relating to whether the pressure transducer was calibrated and periodically checked against a manual staff gauge.

A series of 38 velocity measurements were undertaken by boat using a weighted current meter and velocity counter during the period of 27th June to 11th of August 2001 (i.e., during the wet season). Measurements were taken at 1 metre intervals across the river (approximately 50 intervals) and at depths of 0.2, 0.6 and 0.8 total depth. River levels were identified referencing a temporary benchmark and the pressure transducer datum. Streamflow was calculated by averaging velocities from the 3 depths using the mid-section method. Full details of the estimation of each of the spot flow measurements are given in Attachment 2 of the MWH report, including a summary record which is reproduced herein as Table 3.


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Table 3: Kuribrong River spot flow measurements 2001 (after MWH, 2001)

From the resultant estimates of streamflow, a stage-discharge relationship for the Kuribrong River was established by estimating the stage of zero flow by trial and error and estimating constants C and n through fitting a single segment best fit linear trend line. This rating is shown in the feasibility study report in Figure 4, pg. 20 and is reproduced herein as Figure 5.


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Figure 5: Kuribrong River stage-discharge relationship (after MWH, 2001)

It is notable that the reported rating equation on pg. 19 of the feasibility report records a different stage of zero flow (1.7 m) to that recorded by the linear trend fitting (0.52 m). These different values for the stage of zero flow have been checked using the stated constant values and a least squares approach to identify that the stage of zero flow is mis-recorded in the reported rating equation.

It is also apparent that some of the spot flow measurements were discarded from the generation of the stage-discharge relationship due to large discrepancies with an initial rating. This includes most notably a spot flow measurement on July 24th which appears to have the datum mis-recorded and more importantly two spot flow measurements estimating streamflow less than 27 m3/s.

Stage-discharge relationships have been rederived using a least (log) squares approach, using both a fixed value for the stage of zero flow (0.52 m as per MWH, 2001) and an optimised value of the stage of zero flow (2.25 m). It is assumed that the ‘Adjusted Approximately to Transducer Datum’ recorded water level provides the best estimate of stage for each spot flow measurement. All spot flow measurements except the measurement of July 24th (assumed mis-recorded datum) have been included in this analysis.

Figure 6 shows a summary of this analysis. The spot flow measurements are plotted in (a), clearly indicating the anomalous gauging of July 24th. Stage-discharge relationships, with both a fixed and optimised value of the stage of zero flow, are plotted on a logarithmic scale in (b). The optimised value of the stage of zero flow plots the spot flow measurements in a straight line. Best fit trend lines fitted to the data provide estimates of the constants C and n of 77.5532 and 1.1683 (optimised stage of zero flow) and 2.2967 and 3.4404 (0.52 fixed value for stage of zero flow). Model


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residuals are shown in (c), suggesting that a multiple segment rating may outperform a single segment rating (a break in the trend of model residuals can be identified at a stage of approximately 3.00 m).

Figure 6: Kuribrong River Spot Flow Measurements and Stage-discharge Relationship

(a) Spot flow measurements

Kuribrong River Spot Flow Measurements (June - August 2001)

0

20

40

60

80

100

120

140

160

180

200

2 2.5 3 3.5 4 4.5 5

Stage (m)

Flow (m

3/s)

adj. levels

(b) Stage-discharge relationships


y = 3.4404x + 0.3611

R2 = 0.9578

y = 1.1683x + 1.8896

R2 = 0.975

0

0.5

1

1.5

2

2.5

-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8

log (Stage (m))

log (Flow (m

3/s))

log(stage-0.52) log(stage-2.25)


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(c) Stage-discharge relationship residuals


-40

-30

-20

-10

0

10

20

30

2.5 3 3.5 4 4.5

Stage (m)

Residual Flow (m

3/s)

Residual (a=0.52) Residual (a=2.25)

Comparing Figure 5 and Figure 6, it is apparent that there are minor inconsistencies (and uncertainty) in the stage-discharge ratings derived using a fixed stage of zero flow. However, more importantly, Figure 6 suggests that a preferred single segment stage-discharge relationship may be identified by optimising the stage of zero flow. Importantly, the optimised stage-discharge rating results in lower estimates of flow at low stages.

With particular reference to the study requirements of assessing uncertainty in the Amaila Falls inflow record, uncertainty in the Amaila Falls stage-discharge relationship (2001) has been calculated based on the data presented in Figure 6. This is shown in Table 4.

Table 4: Amaila Falls stage-discharge relationship (2001) uncertainty

Percentile 5% 10% 20% 30% 40% 50% 60% 70% 80% 90% 95%

Ratio -12.6% -10.4% -8.3% -4.3% -1.2% 1.0% 2.8% 5.4% 7.6% 9.7% 11.1%

Further inspection of the spot flow measurements suggest additional uncertainty in the estimation of stage. It is notable that automated level readings from the pressure transducer and logger tend to provide a lower estimate of stage than the manually observed adjusted levels, as illustrated in Figure 7. There does not appear to be any direct relationship between stage uncertainty and magnitude of the spot flow measurement. The average discrepancy between the transducer logged water levels (08:00; 12:00; and 24 hour average) and the manually observed adjusted levels are: 0.08 m (+/- s.d. 0.13 m); 0.05 m (+/- s.d. 0.08 m); and 0.06 m (+/- s.d. 0.09 m) respectively.


Draft Report


Figure 7: Kuribrong River Spot Flow Measurement Stage Uncertainty (after MWH 2001)

Kuribrong River Spot Flow Measurements Stage Uncertainty (June - August 2001)

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 20 40 60 80 100 120 140 160 180 200

Spot Flow Measurement (m3/s)

Stage Uncertainty (m)

adj. levels - 08:00 water level adj. levels - 12:00 water level adj. levels - 24hr average water level

Assuming approximately 7-9 minutes per panel, each 50 panel measurement would take approximately 6–7.5 hours to complete. Given an early morning start time, it can be assumed that the 12:00 water level would provide a suitable reference for the ‘average water level’ during the period of measurement.

Accordingly, an alternative optimised stage-discharge rating was sought using the 12:00 water levels as the reference stage, providing a stage of zero flow of 2.34 m and estimates of the constants C and n of 91.1575 and 1.1715. However, model performance criterion suggests a poorer model (R2=0.9275 vis-à-vis 0.975).

It is also recognised that additional uncertainty in the estimation of streamflow from velocity measurements can be assessed by comparing velocities at 0.2, 0.6 and 0.8 total depth. An example of indicative uncertainty in the estimation of velocity is given with reference to low flow measurements taken on the 31st July – 3rd August.

This comparison has illustrated potential systematic bias in the estimation of average panel velocity, and subsequent overestimation of flow, for those panels where no readings were recorded at the 0.6 depth and / or 0.8 depth. Table 5 shows the results of uncertainty in discharge estimation based on assuming a minimum velocity for depth soundings where no revolutions are reported, vis-à-vis the reported discharge and a calculated discharge based on using a single point method (0.6 depth) of estimating average velocity.


Draft Report


Table 5: Selected Kuribrong River Velocity Measurement and Discharge Computation – Uncertainty

(after MWH, 2001)

Discharge (m3/s) Method 31st July 1st August 2nd August 3rd August

Reported Discharge 30.58 27.63 22.99 26.64 Discharge Check – Assumed 0 revs. 26.25 24.41 20.76 23.37 Discharge Check – Assumed 1 revs. 26.70 24.80 21.08 23.96 Discharge Check – Assumed 2 revs. 27.15 25.18 21.40 24.35 Discharge Check – 1 pt (0.6d) reading 29.49 28.07 23.09 26.69

This suggests that a further important source of uncertainty can be also attributed to estimating low flows based on a plausible bias in the estimation of discharge (overestimation of approximately 10%) during low flows.

3.3.3 Streamflow analysis

Streamflow analysis reported by MWH sought to relate flow in the Kuribrong River (at Amaila Falls) to flow in the Potaro River (at Kaieteur Falls).

Reference is made to an aerial reconnaissance observation that “it was realized from the vegetation cover that the rainfall over the Kuribrong River basin could be somewhat higher than that over the Potaro River basin”.

A summary of 22 spot flow measurements undertaken in 1975 as part of pre-feasibility studies is presented to suggest an average ratio of flow between Kaieteur Falls and Amaila Falls of 0.3, with a range of ratios between 0.24 to 0.40 (Table 15, pg. 22). No further consideration of possible reasons for the observed range of ratios is reported. The pre-feasibility spot flow measurements are further considered herein in § 3.4.3.

A comparison of ratios between additional spot flow measurements on the Kuribrong River (as described in § 3.3.2) and estimated flow on the Potaro River suggests:

• A median ratio of 0.352

• A mean ratio of 0.413

• A minimum ratio of 0.182

• A maximum ratio of 1.825

This is summarised in Attachment 2 (pgs. 48–52) and Figure 6 of the MWH report. No further consideration of possible reasons for the observed range of ratios is reported.

The stream flow analysis is summarised thus: “The 1975 prefeasibility hydrology report suggested a factor of 0.26 to convert the Potaro flows to the Kuribrong flows. For this study, a factor of 0.30 was considered more appropriate.”


Draft Report


Figure 8 shows a comparison of flows at Amaila Falls and Kaieteur Falls for the period 14th February to 13th August 2001. Derived from the MWH 201 report Figure 6 (pg. 21), it shows multiple ratings for the Amaila Falls site, as follows:

• Fixed rating (adj. levels) – rating as developed by MWH (2001) where the stage of zero flow was identified prior to estimation of rating C and n constants; reference level taken as ‘[river levels] adjusted approximately to transducer datum’.

• Optimised rating 1 (adj. levels) – a preferred revised rating undertaken as part of this review where all rating parameters were identified through least squares optimisation; reference level taken as ‘[river levels] adjusted approximately to transducer datum’.

• Optimised rating 2 (12:00 level) – an alternative revised rating undertaken as part of this review where all rating parameters were identified through least squares optimisation; reference level taken as transducer level recorded at 12:00.

Figure 8: Comparison of concurrent measurements of Potaro River and Kuribrong River Flows (2001)

Estimated Kuribrong River Daily Flows (February - August 2001)

0

200

400

600

800

1000

1200

14/02/2001

21/02/2001

28/02/2001

07/03/2001

14/03/2001

21/03/2001

28/03/2001

04/04/2001

11/04/2001

18/04/2001

25/04/2001

02/05/2001

09/05/2001

16/05/2001

23/05/2001

30/05/2001

06/06/2001

13/06/2001

20/06/2001

27/06/2001

04/07/2001

11/07/2001

18/07/2001

25/07/2001

01/08/2001

08/08/2001

Date

Flow (m

3/s)

Fixed Rating (adj. levels) Optimised Rating 1 (adj. levels) Optimised Rating 2 (12:00 levels) Estimated Potaro River Daily Flows (m3/s)

It is notable that at high stages the MWH rating suggests that the flow at Amaila Falls may exceed that at Kaieteur Falls and at low stages the revised optimised rating suggest no flow at Amaila Falls. Given the characteristics of the respective catchments, it is likely that these features are attributable to uncertainty in extrapolation of the derived ratings for Amaila Falls.


Draft Report


Accordingly, putting to one side uncertainty in the Kaieteur Falls rating, it is considered more instructive to compare flow ratios within the gauged range of stage at Amaila Falls (2.64 m to 4.2 m). A revised estimate of ratios between estimated flows on the Kuribrong River and Potaro River, taking a 3 day moving average to account for variation in timing of flow, is given in Table 6 and Figure 9. It is suggested that there is a tendency for the ratio to increase as a function of stage.

Table 6: Summary of estimates of flow ratios between Kaieteur Falls and Amaila Falls

Ratio Method Median Mean Min Max s.d.

Fixed Rating (adj. levels) 0.312 0.337 0.206 0.607 0.096 Optimised Rating 1 (adj. levels) 0.299 0.319 0.178 0.604 0.087

Optimised Rating 2 (12:00 levels) 0.319 0.339 0.192 0.646 0.091

Figure 9: Estimates of flow ratios between Kaieteur Falls and Amaila Falls by stage

Estimated ratios between Kaieteur Falls and Amaila Falls (2001)

Fixed: y = 0.1182x - 0.047 (R2 = 0.1999)

Opt 1: y = 0.0864x + 0.0379 (R2 = 0.13)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

2.64 2.84 3.04 3.24 3.44 3.64 3.84 4.04

Kuribrong River Stage (m)

Ratio

Fixed Rating (adj. levels) Optimised Rating 1 (adj. levels) Optimised Rating 2 (12:00 levels)

Linear (Fixed Rating (adj. levels)) Linear (Optimised Rating 1 (adj. levels))

With particular reference to the study requirements of assessing uncertainty in the Amaila Falls inflow record, flow ratios have been calculated for each decile based on the preferred data (optimised rating 1) presented in Figure 9. This is shown in Table 7.


Draft Report


Table 7: Kaieteur Falls – Amaila Falls 3 day M.A. flow ratio uncertainty (hydrometric data, 2001)

Percentile 10% 20% 30% 40% 50% 60% 70% 80% 90%

Ratio 0.230 0.243 0.263 0.287 0.299 0.316 0.347 0.383 0.454

Furthermore, it is instructive to consider the variation in flow ratios both on a 31 day moving average basis to account for uncertainty in the flow ratio estimation over a monthly duration and also on a calendar month basis to assess if any seasonality in flow ratio can be identified. Estimates of 31 day moving average ratios between estimated flows on the Kuribrong River and Potaro River are given in Table 8.

Table 8: Summary of estimates of 31 day M.A. flow ratios between Kaieteur Falls and Amaila Falls

Ratio Method Median Mean Min Max s.d.

Fixed Rating (adj. levels) 0.409 0.423 0.276 0.707 0.131 Optimised Rating 1 (adj. levels) 0.383 0.359 0.264 0.486 0.069

Optimised Rating 2 (12:00 levels) 0.379 0.373 0.279 0.513 0.066

With particular reference to the study requirements of assessing uncertainty in the Amaila Falls inflow record, flow ratios have been calculated for each decile based on the preferred data (optimised rating 1) summarised in Table 8. This is shown in Table 9.

Table 9: Kaieteur Falls – Amaila Falls 3 day M.A. flow ratio uncertainty (hydrometric data, 2001)

Percentile 10% 20% 30% 40% 50% 60% 70% 80% 90%

Ratio 0.276 0.292 0.297 0.303 0.383 0.396 0.421 0.423 0.439

Table 10 shows a summary of the monthly flow ratios. This tentatively suggests that the flow ratio is notably different in May (0.43-0.46) than it is in June through to August (0.27-0.32). Flow ratios for other months are not presented due to increased uncertainties related to the extrapolation of the stage-discharge relationship.


Draft Report


Table 10: Summary of monthly flow ratios between Kaieteur Falls and Amaila Falls

Ratio Method

Count Mean Min Max May 24 0.45 0.19 0.69 Jun 22 0.29 0.20 0.47 Jul 30 0.32 0.19 0.59

Fixed Rating (adj. levels)

Aug 11 0.27 0.18 0.46 May 24 0.43 0.19 0.69

Jun 22 0.28 0.19 0.43

Jul 30 0.30 0.19 0.58

Optimised Rating 1 (adj. levels)

Aug 11 0.27 0.17 0.46

May 24 0.46 0.21 0.74 Jun 22 0.30 0.20 0.44 Jul 30 0.32 0.21 0.62

Optimised Rating 2 (12:00 levels)

Aug 11 0.29 0.19 0.49

Further analysis on the estimation of the stage-discharge relationship at Kaieteur Falls shows that spot flow measurements have been taken at Kaieteur Falls during the period June 1949 to May 1989 and over a range of flows of 10.2 m3/s to 778.3 m3/s. The station history held at the Hydro-meteorological Service suggests that a stage-discharge relationship was prepared in May 1956 and again in June 1963. Documented analysis presented in the station files (undated) suggests a possible change in rating in approximately 1966 (see Figure 10).

Figure 10: Kaieteur Falls stage-discharge relationship analysis (undated)

The station history records also note that large departures from the rating in 1966 could be attributable to a shifting control at Kaieteur Falls due to clandestine diamond operations diving in the river and / or uncertainty in the gauge datum.


Draft Report


Figure 11 shows the variation in channel cross-section associated with three spot flow measurements taken in February 1971, August 1973 and March 1975, indicating in particular a difference in bed level between 1971 and 1973.

Figure 11: Kaieteur Falls river cross-section (selected spot flow measurements)

A summary of the station rating and spot flow measurement history is presented in Figure 12. Of particular note:

• (a) shows that spot flow measurements are typically closely distributed

around the rating, with few visible significant deviations.

• (b) shows that a significant cluster of spot flow measurements were

undertaken prior to 1957, over a range of flows of 30 to 800 m3/s. A

secondary cluster of measurements are evident during the period 1966 to

1975, although the flow range gauged is somewhat narrower.

• (c) shows the deviations from the rating for each spot flow measurement

are typically within +/- 20% across all stages, although a group of notable

outliers (~ + 70%) exist at a stage of approximately 2.7 m.

• (d) shows how the deviations change with date, indicating increased

deviations post 1963 and in particular in 1986.


Draft Report


Figure 12: Summary of Kaieteur Falls rating and spot flow measurement history

(a) Rating and Spot Flow Measurements (b) Spot Flow Measurements by Date

Kaieteur Falls Stage-Discharge Rating and Spot Flow Measurements

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Flow (m3/s)

Stage (m)

Rating Spot Flow Measurement

Kaieteur Falls - Spot Flow Measurements by Date

0

100

200

300

400

500

600

700

800

900

01-Jan

-49

01-Jan

-51

01-Jan

-53

01-Jan

-55

01-Jan

-57

01-Jan

-59

01-Jan

-61

01-Jan

-63

01-Jan

-65

01-Jan

-67

01-Jan

-69

01-Jan

-71

01-Jan

-73

01-Jan

-75

01-Jan

-77

01-Jan

-79

01-Jan

-81

01-Jan

-83

01-Jan

-85

01-Jan

-87

01-Jan

-89

Date

Flow (m

3/s)

Spot Flow Measurements

(c) Spot Flow Measurements Deviations from Rating by Stage (d) Spot Flow Measurements Deviations from Rating by Date

Kaieteur Falls - Spot Flow Measurements by Stage

-40%

-20%

0%

20%

40%

60%

80%

1.6

1.8 2

2.2

2.4

2.6

2.8 3

3.2

3.4

3.6

3.8 4

4.2

4.4

4.6

4.8 5

5.2

Stage (m)

Deviation from Rating (%)


Kaieteur Falls - Spot Flow Measurements by Date

-40%

-20%

0%

20%

40%

60%

80%

01-Jan

-49

01-Jan

-51

01-Jan

-53

01-Jan

-55

01-Jan

-57

01-Jan

-59

01-Jan

-61

01-Jan

-63

01-Jan

-65

01-Jan

-67

01-Jan

-69

01-Jan

-71

01-Jan

-73

01-Jan

-75

01-Jan

-77

01-Jan

-79

01-Jan

-81

01-Jan

-83

01-Jan

-85

01-Jan

-87

01-Jan

-89

Date

Deviation from Rating (%)



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Doc No RAFHHR Rev: 1.0 Date: June 2011 27

This preliminary review of the Kaieteur Falls rating and spot flow measurement history suggests that the rating may not be consistent and that further consideration of temporal changes may be warranted (for example, to identify whether a significant and persistent change in the low flow rating has occurred post early 1970s).

Notwithstanding possible inconsistency in the stage-discharge rating, and with particular reference to the study requirements of assessing uncertainty in the Amaila Falls inflow record, uncertainty in the Kaieteur Falls stage-discharge relationship has been calculated based on the data presented in Figure 12. This is shown in Table 11.

Table 11: Kaieteur Falls stage-discharge relationship uncertainty

Percentile 5% 10% 20% 30% 40% 50% 60% 70% 80% 90% 95%

Deviation -13.9% -10.1% -5.4% -2.3% -1.2% -0.1% 1.5% 4.3% 6.3% 10.8% 14.6%

3.3.4 Reservoir evaporation

Net reservoir evaporation for “use in reservoir operation computations” has been calculated (MWH, Table 18, pg. 25) using monthly average data based on:

• Pan evaporation at Kaieteur Falls (1959-1974)

• Rainfall at Kaieteur Falls (1953-1978)

• Estimated flow at Amaila Falls (1950-1990)

A pan coefficient of 0.75 has been assumed to estimate lake evaporation. An estimate of catchment losses has been made using the estimated flow and observed rainfall data (“rainfall minus runoff”) – the losses have been equally apportioned to evapo-transpiration and infiltration. Estimated net evaporation has been calculated by subtracting the estimate of evapo-transpiration from estimated reservoir evaporation (zero bounded). The MWH analysis is repeated in Table 12.

Table 12: Estimated net reservoir evaporation (reproduced after MWH, 2001)

Month

Observed Pan

Evaporation (mm)

Estimated Reservoir

Evaporation (mm)

Observed Rainfall

(mm)

Computed Runoff

(mm)

Rainfall minus

Runoff (mm)

Estimated Net

Evaporation (mm)

Jan 108 81 364 257 107 28

Feb 110 83 228 178 50 58

Mar 132 99 243 158 85 57

Apr 125 94 331 219 112 38

May 133 99 591 453 138 30

Jun 145 109 646 566 80 69

Jul 137 103 505 447 58 74

Aug 144 108 337 314 23 97

Sep 142 106 185 147 38 87

Oct 138 104 148 83 65 72

Nov 126 95 246 97 149 21

Dec 108 81 410 202 208 0

Annual 1,548 1,162 4,234 3,121 1,113 629

In addition to unknown uncertainties in the use of observed rainfall at Kaieteur Falls to represent catchment average rainfall in the Amaila Falls


Draft Report


catchment and in the transposition factor of 0.3 used to estimate Amaila Falls computed runoff, additional uncertainties exist in the use of selected pan coefficient and assumptions on estimation of catchment evapo-transpiration and infiltration. Furthermore, it is not clear that this calculation accurately estimates net evaporation from the reservoir for use in reservoir operation computations.

3.4 Hydroelectric Power Survey of Guyana Final Report, Montreal Engineering Company Limited, April 1976

The Guyana Energy Agency was visited by the Project Team on 20 May 2011 to identify relevant sections of the above named report for the purposes of the Hydrology review. The following sections were identified to contain relevant information:

• Volume 2, Appendix 3, Hydrology Studies (pp. A3-1 – A.3-15)

• Volume 4, Appendix 9, River Basin Inventory (§ 2.4, pp. A9-47 – A9-52)

• Volume 5, Appendix 11, Pre-feasibility site studies, Part 1. Amaila Project (§ 1.5, pp. A11-17 – A11-20)

3.4.1 Volume 2, Appendix 3, Hydrology Studies (pp. A3-1 – A.3-15)

Vol. 2 App. 3 describes the general climate of Guyana. It is noted that “Guyana’s rainfall is produced primarily by the cumulus scale and meso-convective scale weather systems linked with the Inter-Tropical Convergence Zone (ITCZ), and to a lesser extent by the cloud-cluster scale weather system. … The oscillation of the ITCZ between 3° N and 8° N is primarily responsible for the two rainy seasons in northern Guyana.”

An isohyetal map reflecting observed rainfall and known orographic effects is given within App. 3 (Figure A3-3), and is re-produced in part in Figure 13. Isohyets are given in inches and are typically based on the annual rainfall of

1971, as observed at sites identified by a . The Kaieteur Falls and Amaila Falls sites are marked as (KF) and (AF) respectively.


Draft Report


Figure 13: Typical isohyetal map of Guyana (part reproduced after Montreal Engineering Company

Limited, 1976)

Additionally, Vol. 5, App.11 (see 3.4.3) provides the locations of the Amaila Falls site and Kaieteur Falls, together with their respective catchment boundaries (Figure A11-1). This is part reproduced in Figure 14

Figure 14: Location of Amaila and Kaieteur Falls sites (part reproduced after Montreal Engineering

Company Limited, 1976)

AF

KF


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Visual comparison of these two figures suggests that annual rainfall is greater in the Amaila Falls catchment when compared to the Kaieteur Falls catchment. Geo-rectification and subsequent GIS analysis suggests an annual average rainfall of 147 inches and 116 inches respectively.

Interestingly, Figure 14 also suggests the possibility of inter-basin transfer into the Kuribrong basin upstream of Amaila Falls. The feasibility of these transfers is unknown, but if these could be put in place, this could significantly reduce the uncertainty and risk associated with water supply.

A summary of runoff patterns describes the response of streamflow to the rainfall seasons for the main rivers in Guyana. High flows typically occur in May through to early September, with a secondary peak in December and January.

Fifteen (15) years of data from a class ‘A’ evaporation pan at Kaieteur Falls is summarised indicating an annual average evaporation of approximately 60 (59.37) inches. It is reported that comparisons of pan evaporation data with evaporation estimated using the Penman formula were undertaken by the Guyana Hydrometeorological Service to derive a local pan coefficient of 1.06. No details of this comparison have been reviewed.

A ‘water balance’ approach to the estimation of inflow to the proposed Amaila Falls site is presented, accounting for both an increase in effective rainfall falling directly onto the associated reservoir surface and an increase in evaporation from the associated reservoir surface. A ‘net evaporation’ rate from the reservoir surface of 20 inches is estimated reflecting a reduction in the “dependable flow that can be maintained during periods of drought”.

Table 13 shows repeated calculations of the water balance confirming the net evaporation rate of approximately 20 inches (EL – P1) and the (approximately 3 %) reduction in total average flow, given an estimation of catchment average rainfall from GIS analysis as above. Importantly, this estimated reduction in dependable flow can be attributed to both the use of a local pan evaporation coefficient of 1.06 and a maximum reservoir surface area of (estimated) 42 sq. miles.

It is also noted that Figure 13 suggests that average rainfall is typically higher over the reservoir location than over the whole Amaila Falls site basin, although this spatial variation has been calculated to have a negligible impact (< 0.5 %) on estimated total inflow.

It is important to note the difficulties in attempting to measure evaporation using water budget related instruments. Brutsaert (1982) highlights some of the difficulties in relating evaporation in nature to that measured by evaporation pans. Recourse is usually made to the use of ‘pan coefficients’ to relate pan evaporation to lake evaporation. Typical values vary from 0.7 for a Class-A pan (FAO Irrigation and Drainage Paper No. 24) to approaching unity for the 20 m2 basin, yet these coefficients vary greatly according to exposure and climatic conditions.


Draft Report


Table 13: Amaila Falls water balance (calculations after Montreal Engineering Company Limited, 1976)

Kaieteur Falls Amaila Falls Comments

Annual average flow

(cusecs)7,370 1,916 - as given in A9-49 (1950-1975) and derived from transposition factor

Transposition factor 0.26 - as given in A11-18

A, Catchment area

(sq. miles)1,220 250 - as given in A9-49 and A11-17

P1, Annual streamflow

(inches)82 104

P, Annual average rainfall

(inches)116 147

- as derived from A3-3 and A11-1 and geo-rectification and subsequent analysis. (Inferred from transpostion

factor and catchment areas, AF = 1.27.KF. A3-4 suggets 162 at Kaieteur Falls).

r, Runoff coefficient 0.71 0.71 - derived from P1 and P

Ea, Actual

evaporation(inches)34 43 - derived from P and r

EP, Pan evaporation

(inches)60 60 - as given for Kaieteur Falls in A3-9 (1959-1975)

α, Pan evaporation

coefficient1.06 1.06 - as given in A3-11 as per local comparisons

EL, Reservoir evaporation

(inches)64 64 - derived from EP and α

y, Fraction of basin flooded 0.16 - as derived from A11-1 and GIS digitisation

Annual average inflow

(cusecs)1,610 - derived from r, P, 1-y and A

Annual average net direct

rainfall (inches)83 - derived from P and EL

Total inflow to Amaila Falls

site (cusecs)1,855 - drived from inflow and net direct rainfall

3.4.2 Volume 4, Appendix 9, River Basin Inventory (§ 2.4, pp. A9-47 – A9-52)

Vol. 4 App. 9 describes the general topography of the Potaro and Kuribrong Basins, noting “similar characteristics” shared by the two basins. It is noted that in early 1975, gold and diamond porknockers (prospectors) were working alluvial deposits approximately 1.5 miles upstream of Kaieteur Falls. The bedrock of the basin is described as being Proterozoic Roraima group sediments characterised by crevices and surface cracks near the escarpment (upon which Kaieteur Falls and Amaila Falls are located).

A single raingauge in the basin at Kaieteur Falls is identified (averaging 160 inches a year over a recorded 15 year period).

Two river gauging stations in the Potaro Basin are identified – at Kaietuer Falls and further downstream at Tumatumari Falls. Their respective catchment areas , record length and mean annual flow are noted as 1,220 and 2,730 sq. miles, 25 and 22 years, and 6.04 and 6.85 cusecs / sq. mile. It is noted that the flow record at Tumatumari Falls is subject to backwater effects and is therefore not consider as accurate as the flow record at Kaieteur Falls (for use in estimating inflows at the Amaila Falls site).

Unknown uncertainty both in the stage discharge relationship (particularly in 1975 during the period of spot flow measurements at the Amaila Falls site – see 3.4.3) as a result of porknocker activity and in the estimation of catchment area as a result of the presence of crevices and surface cracks should be considered when assessing the overall uncertainty in the estimation of inflows at the Amaila Falls site.


Draft Report


3.4.3 Volume 5, Appendix 11, Pre-feasibility Site Studies, Part 1. Amaila Project (§ 1.5, pp. A11-17 – A11-20)

Vol. 5 App. 11 describes the method used during pre-feasibility for deriving inflows into the Amaila Falls site based on the monthly flow record at Kaieteur Falls, due to the “similarity of terrain and climate of the Kuribrong and Potaro Basins”. The contributing catchment area was planimetered from 1:50,000 scale topographic maps to be 250 sq. miles and the resultant ratio of catchment areas adjusted ‘for average annual precipitation believed (Halcrow emphasis) to be higher on the Kuribrong watershed’ such that a monthly flow transposition factor of 0.26 was estimated.

Unknown uncertainty in both the estimation of catchment area of the Kuribrong and Potaro Basins upstream the respective subject locations and in the estimation of the average annual precipitation adjustment can be associated with this transposition factor.

A comparison of 22 spot flow measurements taken on the Kuribrong River downstream of Amaila Falls (June 25th – July 7th 1975) with flows derived from recorded level on the Potaro River upstream Kaieteur Falls is also presented, providing an average flow ratio of 0.30. The results of the spot flow measurement comparison were used to “give some confidence in the derived flows for the Amaila site”, but it was noted “are no substitute for actual records [at the Amaila Falls site] which should be instituted”.

The results of the spot flow measurement analysis, together with modelled flows using a simple linear regression with zero intercept and model residuals, are shown in Table 14 and Figure 15.

Table 14: Spot flow measurement analysis (June – July 1975 data)

Date TimeDischargeAF

(cusecs)

DischargeKF

(cusecs)

Tabulated Ratio

(AM/KF)

Calculated Ratio

(AM/KF)

Difference in

calculated ratio

Estimated dischargeAF

(cusecs)

Deviation

(%)

25/06/1975 10:00 5,550 16,200 0.34 0.34 0.00 4,758 17%

25/06/1975 14:40 5,260 16,600 0.32 0.32 0.00 4,875 8%

27/06/1975 08:20 4,970 17,000 0.26 0.29 -0.03 4,993 0%

27/06/1975 13:55 5,330 17,200 0.28 0.31 -0.03 5,052 6%

28/06/1975 07:30 5,190 19,500 0.27 0.27 0.00 5,727 -9%

28/06/1975 14:40 4,960 19,600 0.25 0.25 0.00 5,757 -14%

29/06/1975 07:58 4,780 20,100 0.24 0.24 0.00 5,903 -19%

30/06/1975 08:05 4,480 18,700 0.24 0.24 0.00 5,492 -18%

30/06/1975 17:25 4,510 18,400 0.25 0.25 0.00 5,404 -17%

01/07/1975 08:15 7,220 22,100 0.33 0.33 0.00 6,491 11%

01/07/1975 16:30 6,970 23,200 0.30 0.30 0.00 6,814 2%

02/07/1975 08:00 7,160 22,300 0.32 0.32 0.00 6,550 9%

02/07/1975 15:10 7,190 22,100 0.33 0.33 0.00 6,491 11%

03/07/1975 08:05 6,670 21,300 0.31 0.31 0.00 6,256 7%

03/07/1975 17:00 6,350 20,700 0.31 0.31 0.00 6,080 4%

04/07/1975 08:28 5,140 19,700 0.26 0.26 0.00 5,786 -11%

04/07/1975 15:50 4,820 19,100 0.25 0.25 0.00 5,610 -14%

05/07/1975 08:50 4,120 15,900 0.26 0.26 0.00 4,670 -12%

06/07/1975 08:45 4,690 12,100 0.39 0.39 0.00 3,554 32%

06/07/1975 16:45 5,010 12,500 0.40 0.40 0.00 3,671 36%

07/07/1975 08:05 4,330 13,800 0.31 0.31 0.00 4,053 7%

07/07/1975 13:000 4,000 13,800 0.29 0.29 0.00 4,053 -1%

Mean 5,395 18,268 0.30 0.30 0.00 5,365 2%

Median 5,075 18,900 0.30 0.30 0.00 5,551 3%

Min 4,000 12,100 0.24 0.24 -0.03 3,554 -19%

Max 7,220 23,200 0.40 0.40 0.00 6,814 36%


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The simple linear regression shown in Figure 15 (a) illustrates both close agreement with the calculation of the average flow ratio (0.2937 vis-à-vis 0.3) and also the degree of deviation from the average for each spot flow measurement, as a function of flow magnitude. The linear regression model residuals together with the ‘0.26 transposition factor’ model residuals are shown in Figure 15 (b) suggesting a relatively high degree of uncertainty in both models – residuals demonstrate a curvilinear relationship, highly dependent on the two (2) spot flow measurement estimates of July 6th.

Figure 15: Spot flow measurement analysis (June 1975 – July 1975 data)

(a) Simple linear regression; zero intercept

Amaila Falls / Kaieteur Falls spot flow measurement analysis (June - July 1975)

y = 0.2937x

R2 = 0.5181

3,000

3,500

4,000

4,500

5,000

5,500

6,000

6,500

7,000

7,500

10,000 12,000 14,000 16,000 18,000 20,000 22,000 24,000

Kaieteur Falls (cusecs)

Amaila Falls (cusecs)

(b) Simple linear regression model residuals

Amaila Falls / Kaieteur Falls spot flow measurement analysis (June - July 1975)

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

10,000 12,000 14,000 16,000 18,000 20,000 22,000 24,000

Kaieteur Falls (cusecs)

Residuals (%)

Linear regression model residuals 0.26 transposition factor residuals

It should be noted that the spot flow measurements at the Amaila Falls site were undertaken during a period when the flows at Kaieteur Falls were estimated as between 12,100 cusecs and 23,200 cusecs. Given the curvilinear


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nature of model residuals, particular care should be given to extrapolating a simple linear relationship.

Additional uncertainties in the spot flow measurements, recorded stage at Kaieteur Falls and the stage-discharge relationship at Kaieteur Falls notwithstanding, assuming a simple linear regression model transposition factor of 0.2937, a ‘true’ estimate of flow at Amaila Falls may be within approximately +36 / -19 % of the modelled estimate. Given a transposition factor of 0.26, this uncertainty increases to +54 / -9 %, and results in an apparent bias of 15 % to 17 %.

With particular reference to the study requirements of assessing uncertainty in the Amaila Falls inflow record, flow ratios have been calculated for each decile based on the data presented in Table 14. These are shown in Table 15.

Table 15: Kaieteur Falls – Amaila Falls flow ratio uncertainty (hydrometric data, 1975)

Percentile 10% 20% 30% 40% 50% 60% 70% 80% 90%

Ratio 0.246 0.254 0.262 0.291 0.304 0.312 0.316 0.324 0.341


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4 Review of Relevant Studies

The review of relevant studies is carried out to verify whether the whether the following factors/coefficients have been correctly considered in the existing energy yield assessment and generation/dispatching model:

• hydraulic head-losses from intake through penstock to turbine;

• turbine-generator efficiency factors for different operating conditions and unit deterioration due to wear;

• the scheduled and unscheduled outages of the turbine-generator units

• the power losses in the transmission line.

The review on the existing sedimentation control plan is also undertaken to identify the likely impact on both reservoir storage and turbine efficiency and deterioration.

4.1 Review of Hydraulic Headloss

It is understood that a constant of 15 m was used as an estimated headloss in the water conveyance system according to the 2001 Feasibility Study Report (Ref 2).

We have carried out a detailed analysis to estimate the anticipated hydraulic headloss in the water conveyance system starting from the headrace tunnel to power shaft and tunnel based on the MWH drawings dated in March 2011(Ref 14). Losses were calculated up to the main inlet valve only. Losses through the Francis turbine are considered to be included in the turbine efficiencies.

The layout of the conduits comprise an intake structure consisting of twin screened rectangular shaped section tunnels which then combine into a single D shaped tunnel section head race tunnel approximately 1600m long constructed as a drill and blast tunnel which changes to a circular concrete lined vertical power shaft section (approximately 315 m high) which then discharges into the power tunnel (approximately 1200 m long) which is initially concrete lined before changing to a steel lined section. A double bifurcation then brings flows into the powerhouse.

An initial review of the headloss calculation indicated that around 75% of the losses at rated full flow (50.2 m3/s) are due to friction losses in the water conveyance system, with other losses such as bends and transitions making the rest up. The resulted headloss and discharge relationship can be summarised as shown in Figure 16.


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Figure 16: Headloss v’s discharge relationship

Amaila Falls Hydropower Project Headloss vs discharge curve

0.00

5.00

10.00

15.00

20.00

25.00

0 10 20 30 40 50 60

Discharge Q (m3/s)

Headloss (m)

It is evidence that a constant headloss of 15 m is an adequate estimate for the hydraulic headlosse in the water conveyance system and will resulted in over-estimation in power output when the flow is less than 40 m3/s or under-estimation when the flow is less than 40 m3/s as shown in Figure 16. For example, for the design flow at 50.2 m3/s, our estimated headloss is about 22 m which is 7 m higher that the assumed valve of 15 m. This could result in over-estimate of energy yields by up to 2%.

4.2 Other Factors that Affect Energy Yield Estimation

4.2.1 Efficiency of Francis Turbine and Generator

According to the 2001 Feasibility Study Report (Ref 2), it is understood that constant rates of 90% and 97.5% were used for turbine and generator efficiencies, respectively.

Our judgement is that although they are acceptable for the purposes of estimating energy yield, they could result in over-estimation in power output when the turbine is operated below its rated flow. Therefore, we adopted a set of variable efficiency curves for the Francis turbine and generator based on available information for the similar features for our energy yield assessments as shown in Figure 17:


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Figure 17: Turbine and generator efficiency curves

Turbine and Generator Efficiency Curves

50%

55%

60%

65%

70%

75%

80%

85%

90%

95%

100%

10% 30% 50% 70% 90% 110% 130%

Output

Efficiency

Generator

Turbine

Combined

4.2.2 Plant Outages

According to the existing energy assessment reports, it is assumed that the power plant will operate with 96% availability (a level of 4% for planned and forced outages). Our judgement is that this is acceptable.

4.2.3 Auxiliary Power Uses and Transformer Loss

According to the 2001 Feasibility Study Report (Ref 2), it is understood that a power loss rate of 0.5% is used for both transformer and at site use, which are considered reasonable. However, we note that the power plant includes a Pelton-type hydro-turbine generator which should produce enough energy for plant auxiliary uses.

4.2.4 Transmission loss

According to the 2001 Feasibility Study Report (Ref 2), it is understood that a loss rate of 2% was used for transmission loss. However, from the recent MWH written answers to our queries (Ref 12), it is understood that transmission line losses are estimated at 3.9% if two lines are operating and 6.7% if one line is operating.

Our judgement is that these rates are considered as low for such a long distance transmission line bearing in mind the fact that transmission and distribution losses in Guyana were estimated at 44%2 in April 2003.

2 Government of Guyana Strategy for Sustaining the Guyana Power & Light, Inc, March 2007


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4.3 Power Plant Output

We have estimated the plant power outputs from the turbine-generator units taking account of variations in hydraulic headlosses and tailwater levels for varying discharges of 1, 2, 3 and 4 turbines running using typical turbine and generator efficiencies and the results are summarised as shown in Figure 18.

It indicated that at the rated design flow of 50.2 (4x12.6 m3/s) the generator achieves approximately 153.5 MW output which is about 7% lower than the quoted output of 165MW. However it appears that this quoted output is a gross output and that either the turbine-generator efficiency or the headloss is not properly considered. To achieve the required output at 165 MW it would require a discharge at an estimated 56 m3/s while the reservoir is at FSL.

Figure 18: Power output from the turbine-generator unit

Amaila Falls Hydropower

Discharge vs Power Generation

0

20

40

60

80

100

120

140

160

180

0 12.6 25.2 37.8 50.4 63

Discharge Q (m3/s)

Output (MW)

1Turbine

2 Turbines

3 Turbines

4 Turbines

4.4 Review of Sedimentation Control Plan and Management Strategy

4.4.1 Sediment loads and siltation rates

There are no reliable sediment measurements for assessing long term siltation of the proposed reservoir. Inconsistent sediment yield measurements in the Mazaruni and Kamarang rivers in the 1960’s and 1970’s (Ref 2 and Ref 3) are inadmissible for estimating depletion of reservoir storage due to sedimentation.

Assuming a stable and good watershed management plan in place, Ref 2 estimated the sediment yield to be 0.25 mm per year (mm/yr) based on an


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assumption that the physical condition of the catchment here is very similar to the upper part of the Río Caroni basin in Venezuela, the basin adjacent to the Kuribrong River. This is equivalent to a mean annual sediment inflow of about 0.165 million m3.

Recent attempts to calculate sedimentation rates from the Amaila and Kuribong rivers have been based on field measurements from May 2010 (Ref 9). Whilst the sampling methodology appears robust, only spot measurements were obtained. Ideally, continuous sediment sampling over a complete annual hydrological cycle to capture any seasonal changes would provide better estimate of sediment yield. The result presented in Table 4.1.1.7.b (Ref 9) is also questionable as it appears that bed load estimate is significantly more than that of the suspended load. Bedload in rivers is normally only a fraction (typically 15-20%) of the suspended load. It is also unclear if the total load or only the suspended load has been used to estimate the long term siltation in this reservoir.

We consider that the trap efficiency (TE) of 75%used in the estimation of the sedimentation rate is acceptable (Ref 11). The mean annual sedimentation rate for this Project has been estimated to be 0.162 million m3. This coincidentally compares well with the 0.165 million m3 inflows given in Ref 2, based on work entirely from a neighbouring catchment in Venezuela. The total sediment accumulation over 50 years based on annual sedimentation rate of 0.155 million m3/yr has been estimated to be 7.7 million m3, representing storage loss of just under 6% of the overall reservoir capacity.

No further data or sedimentation details are available to validate these estimates and will be taken as the accepted siltation rate of the proposed reservoir for the review of sediment management plan and impact on power generation and silt abrasion on the turbines.

4.4.2 Review of existing sediment plan and management strategy

In general there is no reservoir sedimentation mitigation plan besides a broad proposal that effort should be made to minimise erosion from overland flows in the watershed area. Whilst watershed management can be effective, it is normally difficult to implement especially in the long term unless the watershed is strictly protected and designated as non-development area. In any circumstances watershed management should not be regarded as the only strategy in place to actively manage siltation in a reservoir.

It has been noted that there is no provision for flushing outlets at the dam and the low level outlet is designed to meet compensatory flow estimated at 1m3/s which is inadequate for reservoir flushing or density current venting operations. There is therefore no other means of removing sediment from this reservoir once sediment enters and settles in the reservoir besides dredging which is more than often the least economical way to restore the storage capacity.

It is unclear from the above reports if the current proposed reservoir gross storage includes any provision for long term loss due to siltation. It is assumed here that an allowance for dead storage has been made. Whilst the dead storage approach is a common industry practice to manage sedimentation in reservoir, it has been shown in recent advances that this approach may not be entirely adequate for long term mitigation strategy


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especially in a hydropower scheme. Sediment do not build up evenly along a horizontal plane, therefore some live storage which would be useful for drawoff is usually lost long before the dead storage, located at the deepest region of the reservoir is filled.

It may be likely that sediment will settle in the upper region of the reservoir hence blockage of intake will not be an issue (Ref 2) as coarser and heavier sediment usually deposit in the upper region, forming a backwater delta which gradually advances towards the dam. Only lighter and fine sediment tends to be deposited in the deeper area of the reservoir near the dam. However insufficient information is available to confirm if the silting up of the backwater region would not affect the live storage of the proposed scheme required for drawoff to generate power.

The actual process of sediment deposition is unique to every reservoir, ideally sediment modelling to confirm sediment distribution is required to demonstrate that sedimentation will not affect drawoff requirement for power generation However as there is no sediment data available, sediment distribution exercise in the reservoir cannot be carried out to confirm if this would be a problem at this scheme.

4.4.3 Impact on turbines and power generation

Four Francis type turbines have been proposed to generate power at the power house. As there is no qualitative sediment data available for this review, it is impossible to comment on the potential abrasion of the proposed turbines.

It is noted that there is no provision for desilting basin or chamber at the drawoff inlet but this is not unreasonable given the expectation that operational problem due to blockage of intake is minimal as the estimated sediment yield coming into the reservoir is considered to be low.

The intake structure however is only about 7 m above the river bed level (estimated as 410m asml from design drawing C-9). Assuming that sediment is carried into the deeper region of the reservoir in the long term, the estimated accumulation of 7.7 million m3(over 50 years) would result in a bed level of around 420.5 m asml near the dam ( refer to stage–storage table in Ref 11). This level exceeds the proposed intake invert level of 417 m asml by approximately 3m. The reduction in storage capacity as the reservoir is gradually silted up over time meant there will be some risk of sediment entering the drawoff intake well before sediment build up to this level.

However given the nature that incoming sediment yield is low and that sediment build up is not expected to reach the intake for decades (estimated 50 years) it is likely that only fines would enters the drawoff intake under normal operating conditions thus turbine performance should not be adversely affected in the early years.

In any circumstance it is anticipated that each of the four turbine runners (and associated equipment prone to sediment wear) should be coated to protect against silt damage as per manufacturers recommendation and provision is made for rapid runner removal and repair at the site.


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5 Energy Yield and Power Output Assessments

We have built a bespoke energy yield simulation model for the Amaila Falls hydropower facility, including the reservoir, power plant taking into account the following factors:

• Net evaporation loss on the reservoir surface

• Release of environmental compensation flow at the dam (1 m3/s)

• Variations in hydraulic headloss in the conveyance system and tailwater levels for different discharges

• The combined efficiency of the turbine and generator

Please note that we use “Energy Yield” to describe the power obtained at the generator terminals, which is the net power generated at the power plant by taking account of the hydraulic headloss, turbine and generator efficiencies. The “Power output” is the “energy yield” subtracting power losses due to generating unit availability and transformer losses.

5.1 Basic Data and Assumptions

5.1.1 Baseline Streamflows

As discussed in Section 3, we concluded that, given available data, a transposition factor of 0.3 applied to the monthly flow data at Kaieteur Falls is suitable for estimating baseline monthly flows upstream of Amaila Falls. Therefore, the baseline monthly streamflows used in energy yield assessments are the same streamflow series as used in the Feasibility Study and the period of hydrologic record used is from 1950 to 1990 (41 years of monthly streamflows data) and are subject to the uncertainties as described in Section 3 of this report.

5.1.2 Reservoir Operating Policy

According to the Amaila Falls Hydropower ESIA Report, the Amaila Falls reservoir has a minimum operation level (MOL) at 425.0 m (amsl) and a full supply level (FSL) at 431.55 m (amsl). The corresponding storages are 34.303 million m3 and 135.599 million m3 for MOL and SFL, respectively. Therefore, the live storage for power production is about 101.3 million m3.

For the monthly reservoir operations, the energy generated from the plant is simulated month by month chronologically according to an operating policy as follows:

In wet months, the reservoir is filled or kept full and the rated flow (at 50.4 m3/s) is discharged to generate energy. Any extra flow is either spilled or (if possible) stored in the reservoir subject to the storage limit at FSL.

In dry months, the maximum possible flow will be discharged by taking account of the inflow, environmental compensation flows, net evaporation loss, etc and subject to the ending storage limit at MOL. Therefore the net


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inflow is supplemented by drawing water from storage in order to maximize power generation until the MOL is reach when the plant takes the net inflow only.

The similar operation strategy will also apply to the daily reservoir operation simulations.

5.2 Energy Yields and Plant Output Assessments

5.2.1 Energy Yield Assessments for Baseline Steamflows

We have estimated the energy yields for the entire baseline streamflows series of 41 years

Assuming that all units generate full capacity without any restrictions when possible, the simulated monthly and annual energy yields for the baseline flows of 41 years is show in Figure 19 and Figure 20 respectively.

Figure 19: Monthly energy yields

Monthly Energy Yields

0

20

40

60

80

100

120

50

52

54

56

58

60

62

64

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76

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90

GWh


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Figure 20: Annual energy yields

Annual Energy Yields

0

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1952

1954

1956

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1962

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1980

1982

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1990

Year

GWh

It is noted that the monthly powers generated exhibit variations as shown in Figure 21.

Figure 21: Monthly min, average and max power generated at the power plant

Monthly Minimum, average and maximum energy yields

0

20

40

60

80

100

120

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months

GWh

Minimum

Average

Maximum


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5.2.2 Power Output Assessment for Baseline Streamflows

If a combined loss rate of 4.5% is assumed for both the machine outages and transformer loss, the energy outputs for the power plant are listed in Table 16.

Table 16: Estimated plant energy outputs for baseline flows

Energy Yield

Energy losses (Machine outage and transformer loss 4.5%)

Energy Output at station

Minimum (GWh) 884 40 844 Average (GWh) 1141 51 1090 Maximum(GWh) 1343 60 1283

The average annual energy output from the plant is estimated as 1090GWh.

5.3 Energy Yield Assessments for a “Dry” Year

In order to assess the impact of the monthly and daily streamflows on the energy yield of the project, we have carried out the energy yield simulations based on both monthly and daily streamflows for a “dry” year which is defined in this study as the year with 90% dependable flow. On the basis of annual flow-duration curve, 1962 is selected as a “dry” year (90% dependable).

The estimated annual energy yields for the monthly and daily simulation are 994.8 GWh and 952.8 GWh, respectively as shown in Figure 22. This indicated that using monthly average flows for energy yield assessment could result in an over estimate of energy yield by up to 4.2% as compared with that using daily flows.

Figure 23 depicts the available discharges for power generation under daily and monthly operation scenarios as compared with daily inflow to reservoir. The main reason behind is that the reservoir has a relatively small live storage (which is 101.3 million m3) which could only store enough water for supplying 3 units for up to one month and 4 units for up 23 days.


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Figure 22: Estimated Energy Yield (90% dependable flows)

Energy Yields for Monthly and Daily Simulated Operations

0

1000

2000

3000

4000

5000

01/01/1962 01/02/196 01/03/196 01/04/196 01/05/1962 01/06/196 01/07/1962 01/08/196 01/09/196 01/10/1962 01/11/1962 01/12/1962

KWh

Energy Yields based on monthly flows

Energy Yields based on daily flows

Figure 23: Available discharge (90% dependable flows)

Inflows, Monthly and Daily Discharges for Power Production

0

50

100

150

200

250

1/1/62 1/2/62 1/3/62 1/4/62 1/5/62 1/6/62 1/7/62 1/8/62 1/9/62 1/10/62 1/11/62 1/12/62

m3/s

Inflows to Reservoir

Monthly Discharges for Power Generation

Daily Discharges for Power Generation


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5.4 Sensitivity Analysis

A sensitivity analysis has been carried out to assess the impact of reservoir size on energy generated from the power plant. The analysis is based on the baseline monthly streamflows of 42 years and the energy yield simulations were run for two further reservoir sizes assuming the FSL at 434.0 m and 435.5, respectively.

The simulated average annual energy yields are listed in Table 17 and the annual energy yields for the 41 years are shown in Figure 24.

Table 17: Estimated average annual energy yields for different reservoir sizes

Full Supply Level FSL (m)

Live Storage Volume (million m3)

Energy Yields (GWh)

Changes in GWh (%)

431.55 101.3 1141 434.0 169.3 1183 +3.7% 435.0 220.8 1218 +6.7%

Figure 24: Estimated annual energy yields for different reservoir sizes

Annaual Energy Yields for Different FSLs

800.00

900.00

1000.00

1100.00

1200.00

1300.00

1400.00

1950

1951

1952

1953

1954

1955

1956

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1987

1988

1989

1990

Month

GWh

FSL=431.55m

FSL=434.0m

FSL=435.5m

The simulation results indicate that as compared with the existing design of FSL at 431.55m the average annual energy yield would increase by up to 3.75% and 6.7% if the FSL was increased to 434 m and 435.5 m, respectively, representing an increase of storage volume by some 67% and 118%, respectively. The reason is that the energy yield of the power plant is constrained by both the design flow rate (12.6 m3/s) and the regulation capacity of the reservoir.


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5.5 Uncertainty Analysis

5.5.1 Uncertainties in Derived Streamflows

The review of existing hydrological results and studies has highlighted uncertainty in various components of the hydrological analysis undertaken to date in identifying the available water for use in Amaila Falls power generation studies. Uncertainties in the following areas have been identified:

• Uncertainty in establishing a transposition factor derived from catchment areas and catchment rainfall due to: uncertainty in the estimation of catchment areas (watershed definition, possible inter-basin transfers and the presence of crevices and surface cracks), and; uncertainty in the estimation of average rainfall in the two catchments (based on observations in 1971 from a sparse hydrometric network, supplemented by the effect of “known orographic features”).

• Uncertainty in establishing a transposition factor based on estimated flow at Kaieteur Falls and spot flow measurements downstream of Amaila Falls undertaken in June-July 1975.

• Uncertainty in establishing a transposition factor based on estimated flow at Kaieteur Falls and spot flow measurements downstream of Amaila Falls undertaken in June-August 2001, including; uncertainty in establishing a temporary stage-discharge relationship downstream of Amaila Falls due to uncertainty in velocity measurements and uncertainty in measuring stage, and; uncertainty in deriving a flow record downstream of Amaila Falls due to rating extrapolation at low and high flows.

• Uncertainty in the consistency of the stage-discharge relationship at Kaieteur Falls, including possible shifts in rating control and frequency of recent spot flow measurements.

• Uncertainty in the estimation of a 41-year flow record due to missing data.

• Uncertainty in the estimation of a consistent 41-year flow record (trend and cyclic features).

• Uncertainty in net evaporation from an Amaila Falls reservoir due to uncertainty in both direct rainfall and evaporation.

• Uncertainty in the temporal and seasonal stability of rainfall patterns in the Amaila Falls catchment.

It is recognised that the overall uncertainty in the use of a transposition factor is a complex function of many contributing factors. From the perspective of the current study requirements, the overall uncertainty has been reduced to what are considered the primary components of:

• Uncertainty in the daily flow ratios between Kaieteur Falls and Amaila Falls based on hydrometric measurements undertaken in 1975.

• Uncertainty in the 3 day M.A. and 31 day M.A. flow ratios between Kaieteur Falls and Amaila Falls based on hydrometric measurements undertaken in 2001.


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• Uncertainty in the Kaieteur Falls rating based on the recorded rating table and spot flow measurements undertaken between June 1949 and May 1989.

• Uncertainty in the Amaila Falls rating based on an updated logarithmic rating curve and spot flow measurements undertaken in June – July 1975.

A simplified assessment of uncertainty in the derivation of a simple constant transposition factor applied to a monthly flow record has been undertaken based on the application of a dominant factor of uncertainty in Kaieteur Falls / Amaila Falls flow ratios derived from hydrometric measurements undertaken in 2001. This effectively assumes that all other sources of uncertainty are subsumed in the quantification of uncertainty of a 31 day moving average flow ratio.

This simplified assessment does not take into account any possible variations in flow ratio between the two sites that may be associated with the magnitude of flow, seasons or longer term consistency. Although the analysis undertaken suggests that such factors may be important, it is considered that insufficient data is available to make quantified assessments in these areas.

As such, derived from use of a cumulative distribution function, the resultant uncertainty in a simple transposition factor is summarised in Table 18.

Table 18: Summary of uncertainty in key hydrological components

Percentile (%) 31 day M.A. flow ratios (2001) 10 0.276 20 0.292 30 0.297 40 0.303 50 0.383 60 0.396 70 0.421 80 0.423 90 0.439

It is notable that the median transposition factor estimate of 0.383 is somewhat higher than the accepted baseline transposition factor estimate of 0.300 suggesting that the baseline estimate is a precautionary estimate.

5.5.2 Uncertainties of energy yield

The uncertainty analysis of energy yield is carried out by deriving the Amaila Falls monthly streamflows using different transposition factors as identified in Table 18. The energy yields can be summarised in Table 19.


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Table 19: Energy yield uncertainty

Percentile Transposition

factors Energy Yield (GWh/year)

Energy Output at Station (GWh/year)

10% 0.276 1095 1046

20% 0.292 1118 1068

30% 0.297 1125 1074

40% 0.303 1133 1082

50% 0.383 1174 1121

60% 0.396 1176 1123

70% 0.421 1180 1127

80% 0.423 1180 1127

90% 0.439 1182 1129

Table 19 suggests an average energy yield of 1174 GWh. This compares with the baseline assessment of average energy yield of 1141 GWh (see Table 16).

Considering the estimated energy output at the station and assuming a 4.5% energy loss due to machine outage and transformer losses, adopting an Intergovernmental Panel on Climate Change (IPCC) approach to communicating levels of confidence in model results, we can have a high level of confidence that the average energy output is between 1046 GWh and 1129 GWh..

5.6 Assessment of climate impacts on hydropower production

A review of the potential impacts of climate change has been undertaken in order to identify whether any potential climate change impact can be quantified and used for developing an alternative estimate of basin hydrology and of the associated dispatching scenarios. As such, a review of the following studies has been undertaken:

• The ‘Assessment of the Risk of Amazon Dieback’ report (World Bank, February 2010).

• National Climate Committee and National Resources and Environment Advisory Committee (Guyana: Initial National Communication in response to its commitments to the UNFCCC, 2002).

• Effects of 21st century climate change on the Amazon Rain Forest (Cook, K and Vizy. E, 2007), Journal of Climate, Vol. 21 pp.542-560.

• UNDP Climate Change Country Profiles, University of Oxford.

• Future of climate in South America in the late 21st century: Intercomparison of scenarios from three regional climate models (Marengo, J et al, 2009), Climate Dynamics.

Most of the climate change studies have been undertaken using GCM’s as there has been little research done with downscaling techniques, particularly for Guyana and the Amaila Falls region. However, it is notable that the majority of studies predict a general decrease in both annual and seasonal mean precipitation.


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With reference to IPCC emissions scenarios, indicative results, presented by the UNDP country profile study, with reference to a 1971-2000 baseline, rainfall may on average decrease for all modelled scenarios as per the values shown in Table 20.

Table 20: Indicative climate change related decreases in rainfall – median values

SRES scenario

Period Annual Nov-Jan

Feb-Apr

May-Jul

Aug-Oct

A2 -1.5% -1.6% -0.7% -0.6% -1.8% A1B -1.4% -1.7% -0.1% -0.3% -2.1% B1

2021-2050

-0.6% -0.8% -0.6% -0.6% -1.0% A2 -2.9% -2.4% -0.9% -2.2% -3.0% A1B -2.9% -2.8% -1.1% -2.4% -3.6% B1

2051-2080

-1.8% -1.4% -0.7% -0.8% -1.4%

It is notable that the SRES scenario A2 is at the higher end of modelled emission scenarios, A1B is a mid-line scenario and B1 is a low emissions scenario. Both the scenarios A2 and A1B predict similar decreases in rainfall both for the period 2021-2050 (-1.4% to -1.5%) and 2051-2080 (-2.9%), whereas scenario B1 predicts less of a decrease in rainfall (-0.6% and -1.8% for 2021-2050 and 2051-2080 respectively).

Further details of each of the reviewed studies is summarised in the following sections.

5.6.1 The ‘Assessment of the Risk of Amazon Dieback’ report (World Bank, February 2010).

The World Bank report presents the difficulties of predicting future rainfall over the region, and reviews the outputs of 24 Global Circulation Models (GCM) used by the IPCC (International Panel for Climate Change) from the perspective of the ability to simulate current rainfall. 24 climate models results were available for the study. These models were included in the Couple Model Intercomparison Project 3 carried out by the IPCC Fourth Assessment Report (4-AR). It is notable that some of the 24 GCMs predict an increase in rainfall over the region and others predict a decrease.

The report presents five study objectives of which modelling future climate and assessing the impact of climate on rainfall are of direct relevance to the Amaila Falls hydrology review.

The 4-AR used 24 GCMs to predict future climate under various scenarios. Many of these models use a very coarse resolution (100-400 km) and as such provide only a broad scale assessment of climate. The study presents the results of a 20km – 180km GCM developed by Japan which makes use of a supercomputer called the ‘Earth Simulator’. Modelled seasonal mean precipitation is compared to observed precipitation and is reported as being able to reproduce baseline (1979 to 2003) precipitation distributions quite well. Predicted changes in precipitation show an increase in rainfall in Northwest Amazonia and a decrease elsewhere in the region. However, the reported changes in precipitation are not quantified.


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5.6.2 National Climate Committee and National Resources and Environment Advisory Committee (Guyana: Initial National Communication in response to its commitments to the UNFCCC, 2002).

In the Initial National Communication of Guyana two GCMs were applied to forecast the future changes in the country’s climate: the Canadian Climate Centre (CGCM-1), and the Hadley Centre (HadCM2Gsal) from the SCENGEN scenario within the MAGIC (Model for the Assessment of Greenhouse Gas Induced Climate Change) model.

The CGCM-1 model results were available for three time slices: 1945 – 1995 (present); 2020 – 2040 (2 x CO2); and 2080 – 2100 (3 x CO2). These predict a decrease of 10 mm per month for the 2020 – 2040 scenario. The decrease is greatest in the country’s First Wet Season (May to July - 17 mm per month) and in the Second Dry Season (August to October – 12 mm per month). For the 2080 – 2100 scenario, the predicted decrease in rainfall is even higher. These anomalies represent a decrease between a 2.2% to a 6.8% with respect to the mean annual rainfall values.

The Hadley Centre Model results are available for two future time periods corresponding to 2016 – 2045 (2 x CO2) and 2076 – 2105 (3 x CO2). The changes in rainfall are expressed by %. The predictions of future rainfall patterns are similar between the two models. Country average results show a consistent decrease in rainfall although the Hadley projections show a more severe decrease in rainfall especially for the May to July period and a slight increases in rainfall in the February to April and the August to October periods.

5.6.3 Effects of 21st century climate change on the Amazon Rain Forest (Cook, K and Vizy. E, 2007), Journal of Climate, Vol. 21 pp.542-560.

Cook and Vizy present the result of a Regional Circulation Model (RCM) constrained by a GCM. The RCM produces a more accurate representation of the present South American climate, and provides regional information needed for assessing the impacts. The paper states that most of the GCMs produce rainfall rates for the Amazon Basin that are inaccurate and make the results of such models inadequate for hydrological studies. The RCM model (5th generation Pennsylvania State University – National Centre for Atmospheric Research Mesoscale Model) results were compared with ‘baseline’ values3 in order to observe which simulation (different emission scenario) provides a better representation of the annual mean precipitation. The model predicts a future precipitation decrease (2081-2100) of 4 mm per day over a large portion of the Amazon Rainforest with decreases greater than 10 mm per day in southeastern Brazil. Close to the equator, annual mean rainfall is predicted to increase by more than 2 mm per day in the central and eastern parts of the continent and along the eastern slopes of the Andes. From the figures of the publication it is possible to observe that around the study area there is a predicted decrease in future mean annual precipitation. Detailed analysis of two regions east of the Amaila Falls catchment suggests a 70 % reduction in rainfall (2081 - 2100) for the entire second half of the calendar year.

3 From the CRU 1961 – 1990 and CCCMA twentieth-century GCM integration (1981 – 2000)


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5.6.4 UNDP Climate Change Country Profiles, University of Oxford.

The UNDP climate change country profiles were constructed by a joint effort between the National Communications Support Programs (NCSP) and the UK Department for International Development and were developed to address the climate change information gap in many developing countries by making use of existing climate data. Data from the Couple Model Intercomparison Project 3 (CMIP3) was collated by this initiative and is presented in a synthesized way by making use of graphs and maps with the most up-to-date multimodel projections. In itself, the initiative does not present new results but rather provides a compilation of existing model predictions. It only contains data from the GCMs in which the IPCC 4th assessment report.

The report summarizes that mean annual rainfall from different models show a wide range of predicted variation. Predictions vary between -34 % to +20 % by 2090, although the median estimate of change for the 2060’s is negative. The largest change in total rainfall is predicted for May – July (-68 mm to +21mm per month). Relative changes show the largest variation in August – October and November – January periods (-82 % to +68 %).

The country profile also concludes that model simulations show a wide disagreement in predicted rainfall variation in the amplitude or frequency of future El Niño events, contributing to uncertainty in climate predictions for the region.

5.6.5 Future of climate in South America in the late 21st century: Intercomparison of scenarios from three regional climate models (Marengo, J et al, 2009), Climate Dynamics.

As part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project, different regional climate change projections have been made. This paper cover three RCMs nested within one GCM to simulate climate for the present (1961-1990) and predictions for 2071-2100 under the A2 IPCC emissions scenario. The results of the study are focused on the intercomparison between models using the same boundary conditions, allowing for an exploration of the uncertainty in regional models.

Two of the three models show rainfall reductions in the future for most of tropical South America east of the Andes. In contrast, the third model shows a regional pattern with increased rainfall in the future over the western Amazon extending to southern Brazil. According to the study, the projected differences in precipitation among the three models could be a partial consequence of an El Niño response of each model. The paper analyses the annual cycle for Northern Brazil (closest analysis area to the Amaila Falls catchment) showing that for the baseline scenario the three models agree reasonably well with the observations but that intensity is in general under estimated.


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5.6.6 Climate impact on hydropower production

Based on the indicative decreases in rainfalls related to different climate change scenarios as shown in Table 20 and assuming a linear response between rainfalls and modelled flows in the Amaila Falls catchment, the predicted reductions in river flows are used to model possible likely impact on future energy yields.

The simulated energy yields as shown in Table 21 indicate that the impact of climate could result in reduction in annual energy yield from 1.3 to 2% for different scenarios when reductions in rainfall range from -0.6 to -2.9%.

Table 21: Climate impact on future energy yields

SRES Scenario

Period Changes in River flows

Annual Energy Yield (GWh)

Change in GWh (%)

Baseline 1141

A2 av. -1.5% 1124 -1.50%

A1B av. -2.9% 1121 -1.78%

B1

2021-2050

av. -1.4% 1124 -1.48%

A2 av. -2.9% 1119 -1.93%

A1B av. -0.6% 1126 -1.29%

B1

2051-2080

av. -1.8% 1125 -1.44%


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6 Summary and Conclusions

6.1 Review of Hydrology Studies

We have reviewed hydrology reports produced during pre-feasibility (1976) and feasibility (2001) stages of the Project and undertaken further analysis based on data contained therein and data obtained from visits at the Hydro-meteorological Service of the Ministry of Agriculture in Guyana (2011).

Various sources of uncertainty in the use of a monthly flow series from an adjacent catchment (Potage River at Kaieteur Falls) and a simple transposition factor for deriving monthly flows upstream of Amaila Falls have been assessed. These include uncertainties in both hydrometric measurements taken downstream of the Amaila Falls site in 1975 and 2001, and uncertainties in the development of stage-discharge relationships at both Kaieteur Falls and Amaila Falls.

We concluded that, given the available hydro-meteorological data, a transposition factor of 0.3 applied to the monthly flow data at Kaieteur Falls is suitable for estimating baseline monthly flows upstream of Amaila Falls, subject to the following identified uncertainties:

• Uncertainty in the daily flow ratios between Kaieteur Falls and Amaila Falls based on hydrometric measurements undertaken in 1975.

• Uncertainty in the 3 day M.A. and 31 day M.A. flow ratios between Kaieteur Falls and Amaila Falls based on hydrometric measurements undertaken in 2001.

• Uncertainty in the Kaieteur Falls rating based on the recorded rating table and spot flow measurements undertaken between June 1949 and May 1989.

• Uncertainty in the Amaila Falls rating based on an updated logarithmic rating curve and spot flow measurements undertaken in June – July 1975.

A simplified assessment of uncertainty in the derivation of a simple constant transposition factor applied to a monthly flow record has been undertaken based on the application of a dominant factor of uncertainty in Kaieteur Falls / Amaila Falls flow ratios derived from hydrometric measurements undertaken in 2001. This effectively assumes that all other sources of uncertainty are subsumed in the quantification of uncertainty of a 31 day moving average flow ratio.

This simplified assessment does not take into account any possible variations in flow ratio between the two sites that may be associated with the magnitude of flow, seasons or longer term consistency. Although the analysis undertaken suggests that such factors may be important, it is considered that insufficient data is available to make quantified assessments in these areas.


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6.2 Review of Relevant Studies

We have reviewed other factors/coefficients that affect power output estimate of the plant and our judgements are as follows:

• For hydraulic headloss in the water conduits, a constant value of 15 m is not adequate and could result in an overestimate of power output by up to 2% when all units run at full capacity;

• Other factors, such as the turbine-generator efficiency, rate for scheduled and unscheduled outages of the plant, are considered to be reasonable;

• The power loss rates are probably low for such a long distance transmission line.

We have also undertake review on the estimate of siltation rate and existing sediment plan and management strategy and assessed the sedimentation impact on both reservoir storage and turbine. We concluded that

• The most up to date estimate of incoming sediment yield is based on field measurements from May 2010. Although the measurements are spot samplings which are not ideal for estimating sediment yield, the estimated yield of 0.162 million m3 is in general comparable with an independent estimate of the sediment yield in an adjacent basin of similar characteristics.

• The estimated sediment yield cannot be checked as there is no sediment data made provided for this review exercise. The values have been accepted as accurate in order to review the management strategy and impact on turbines affecting power generation for this scheme.

• Whilst the overall sedimentation in the reservoir is considered low, the long term distribution of sediment in the reservoir is unclear and this may affect power generation if coarse sediment settles in the upper backwater region which may be part of the live storage of the reservoir.

• Sedimentation is not expected to affect power generation in the early life of this reservoir, however long term sedimentation if reaches the deeper region of the dam, bed level at the dam is anticipated to reach drawoff intake level and therefore may affect drawoff requirement to the powerhouse.

6.3 Energy Yield and Power Output Assessments

We have estimated the power output from the turbine-generator unit by taking account of the hydraulic headlosses using typical turbine and generator efficiencies; our estimate indicates that at the rated design flow of 50.2 m3/s the unit achieves approximately 153.5 MW output while the reservoir is at full supply level, which is about 7% lower than the quoted value of 165MW.

We have estimated the energy yield based on the baseline flows of 41 years and obtained that:

• an average annul energy yield at the generator terminals is estimated as 1141 GWh, with the minimum and maximum yields being 884 GWh and 1343 GWh, respectively;


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• an average annual energy output from the power plant (at the transformer terminals taking account of machine outages and transformer loss) is estimated as 1090GWh;

• an average annual power available at the distribution point (at Linda and Georgetown) is estimated from 1017 GWh to 1047 GWh taking account of transmission line losses;

• for a dry year (90% dependable annual flows), the annual energy yield is estimated at 994.8 GWh when the monthly average flows are used for simulation. However, when daily flows are used for simulation the annual energy yield estimate reduces to 952.8 GWh, indicating that using monthly flows could overestimate the energy yield by up to 4.2%.

We have assessed the energy yield with different reservoir full storage levels (FSL) and simulation results indicate that as compared to the existing designed FSL at 431.55 m the average annual energy yield would increase by up to 3.75% and 6.7% if the FSL was increased to 434 m and 435.5 m, respectively.

We have undertaken uncertainty analysis of the energy yields with regard to the transposition factor varying from 0.276 to 0.437. We can have a high level of confidence that the average energy output is between 1046 GWh and 1129 GWh considering machine outages and transformer losses.

A preliminary climate change impact analysis of relevant General Circulation Model (GCM) and Regional Circulation Model (RCM) results for the Project indicates that there is a wide variety of predictions of how rainfall patterns may change in the future but suggests that there is a tendency for models to predict a general decrease in rainfall in the area which would typically cause a resultant reduction in river flows at the project site. Based on indicative climate change related decreases in rainfalls, and assuming a linear response between modelled rainfall and flows in the Amaila Falls catchment, the predicted river flows are used to model possible likely impact on future energy yields. The simulated energy yields indicate that the impact of climate could result in reduction in annual energy yield from 1.3 to 2% for different scenarios when reductions in rainfall range from -0.6 to -2.9%.

It should be noted that the analysis and assessments presented in this report are subject to the accuracy and completeness of the background information and data provided.


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References

Ref 1. Kaehne Consulting Ltd, Review of Amaila Falls Hydroelectric Project Feasibility Study Report, June 2002.

Ref 2. Montgomery Watson Harza, Amaila Falls Hydroelectric Project Guyana Feasibility Study Report Hydrology, December 2001

Ref 3. Montreal Engineering Company Limited, Hydroelectric Power Survey of Guyana Final Report, April 1976.

Ref 4. Montgomery Watson Harza, Amaila Falls Hydro - Estimated Monthly Energy and Average Power for a Range of Load Factors, 14 August 2009

Ref 5. Montgomery Watson Harza, Amaila Falls Hydro - Estimated Monthly Energy and Average Power for a Range of Load Factors, 19 October 2009

Ref 6. Engenuity, Amaila Falls Survey Data Interpretation, October 2009

Ref 7. Montgomery Watson Harza, Amaila Falls Hydroelectric Project Generating Facilities Owner’s Requirement – Drawings, 4 March 2011

Ref 8. The World Bank, Assessment of the Risk of Amazon Dieback, Main Report, February 4, 2010

Ref 9. Amaila Falls Hydro Inc, Amaila Falls Hydropower ESIA Report (accessible at http://amailahydropower.com )

Ref 10. Mercados Energeticos Consultores, Economics and Financial Evaluation Study: Guyana Amaila Falls Hydro Project, March 2010

Ref 11. Amaila Falls Reservoir Sediment Assessment and Intake Setting _R2_.pdf – undated (received from Sithe as an email attachment on 16 June 2011 )

Ref 12. MWH’s written answers to Halcrow’s queries (received from Sithe as an email attachment on 16 June 2011 )

Ref 13. Government of Guyana Strategy for Sustaining the Guyana Power & Light, Inc, March 2007

Ref 14. Amaila Falls Hydro, Inc., Amaila Hydropower Project Generating Facilities, Section 8, Owner's Requirements - Revised Drawings, March 2011


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Annex 1 Amaila Falls Hydropower Project Salient Feature

General Project Location The confluence of Amaila and

Kuribrong Rivers Coordinates

(at Powerhouse location) Lat/Long: 5º23’42” N 59º33’58” W UTM: 21 Northing - 596912 Easting - 219300

Site Elevation Powerhouse – 77.5 m, above mean sea level (amsl) Reservoir Full Supply Level (FSL) 431.55 m, amsl

Hydrology Watershed Area (Drainage Area) upstream of dam 623 km2 Combined Amaila + Kuribrong River Flows Mean Monthly Flow 64 m3/s Average Monthly Maximum for a Given Year 151.25 m3/s Average Monthly Minimum in a Given Year 14.84 m3/s Record Monthly Maximum Flow 210.13 m3/s Record Monthly Minimum Flow 4.48 m3/s (for entire 41-year period of record) Maximum Flood (Amaila and Kuribrong basins) 25-yr 1,339 m3/s 50-yr 1,486 m3/s Probable Maximum Flood Peak Flow 5,010 m3/s Volume 314 mcm Routed Outflow 2,034 m3/s Estimated Annual Sediment Inflow 0.165 mcm Estimated Annual Net Evaporation 630 mm Hydropower Facility Reservoir Minimum operating level (MOL) 425.0 m, amsl Full supply level (FSL) 431.55 m, amsl Maximum flood surcharge level 434.35 m, amsl Reservoir volume at FSL (gross storage) 135.6 mcm Reservoir perimeter at FSL 59.6 km


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Reservoir area at FSL 23.3 km2 Existing river channel area (already inundated) 1.5 km2 Net increase in flooded area at FSL 21.8 km2 Length as measured by Amaila channel 12 km Length as measured by Kuribrong channel 7 km Net active storage (FSL – MOL) 101.3 mcm Average depth 5.8 m Maximum depth 25.3 m Filling time to FSL (mean monthly inflow of 64 24 days m3/s, assuming reservoir is empty at the start) Filling time to MOL (mean monthly inflow of 64 6 days m3/s, assuming reservoir is empty at the start) Net Storage Time At nominal 50 cms full output (assuming rated 80 days flow, no inflow, no evaporation) Dams Construction Type Concrete–faced, rock filled Crest Elevation 435.05 m, amsl Max Dam Height (above original ground surface) 18.25 m Dam Crest Width 8 m Main Dam Centerline Length (Amaila & Kuribrong) 2,460 m Spillway Type Ungated overflow Spillway Crest Level 431.55 m, amsl Spillway Capacity 2,034 m3/s Spillway Length 236 m Intake & Headrace Tunnel Construction Type Concrete for intake, concrete or

shotcrete for headrace tunnel depending on rock conditions

Intake Invert - Elevation 418 m, amsl Length & Height of Intake 11 m width by 8 m high Effective Face Area 66 m2 Design Flow at 165 MW at FSL 50.4 m3/s Headrace Tunnel Diameter and Length 4.0 or 4.6 m diameter depending on

rock conditions, 1,603 m length Headrace Tunnel Max velocity at 165 MW 3.6 m/s Surge and Power Shaft Lining Concrete Inside Diameter 3.4 m Height 314.4 m Power Tunnel Construction Type Concrete, steel-lined concrete Inside Diameter 3.40 m for concrete, 3.10 m for steellined

concrete Top Invert (Elevation at Exit from Shaft) 81.25 m, amsl Bottom Invert (at Entry to Powerhouse) 63.40 m, amsl Length 1,231 m


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Powerhouse (165 MW at FSL) Number & Type of Units 4 Gross MW per Unit 41.25 MW Total Gross Output at Generator Bus Bar 165 MW Design Flow per Unit 12.6 m3/s Tailrace Gross Head at FSL 364.4 m Nominal operating tailrace level (full load) (typically vary less than 1 m) 67.2 m, amsl Minimum downstream tailrace level (at 0 m3/s assumed flow) 66.4 m, amsl Extreme maximum operating downstream tailrace level (based on spill flow of 2,034 m3/s during Probable Maximum Flood) 75.6 m, amsl Electrical Interconnect Substations Linden, Sophia (Georgetown) Voltage 230 kV / 69kV Length 170 km, Amaila to Linden

100 km, Linden to Sophia Corridor width

Amaila - Linden: 100 m +25m each side selective clearing Linden - Sophia: varies, typically 100 m

Tower construction type Steel lattice Number of Circuits Two (i.e., dual circuits on single tower) Conductor type 853.7 KCMIL 18/19 Tower height 36 m Tower arm width 23 m Conductor minimum height above ground 9 m Access Roads Length of two new roads 85 km (67 km and 18 km) Length of upgrade roads 122 km Road Width 5-7 m Road Corridor width 20-30 m (portion of which will be within the

transmission line corridor) Alignment As shown on mapping Design vehicle loading 100 tonnes Design Speed 50 km/hr Sight distance 60 m Preferred max slope 10% Two (2) Kuribrong Bridges Steel framed


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Annex 2 Main Data Used in Energy Yield Assessments

A2.1 Reservoir Elevation, Area and Volume Relationships (received from MWH 22/06/2011)

Elevation

(m)

Area

(sq. m)

Volume

(cu.m)

440.0 439.0 438.3 438.0 437.6 437.0 436.0 435.5 435.0 434.0 433.0 432.0 431.55 431.0 430.0 429.0 428.0 427.0 426.0 425.0 424.0 423.0 422.0 421.0 420.0

62,439,059 58,060,450 54,061,308

53,541,636 51,602,229 46,669,206 41,470,211 38,694,577

36,635,315 32,259,642 27,169,210 24,259,630 23,286,514

22,014,873 19,489,793 16,897,065 14,474,359 12,309,602 9,939,376 8,388,726

7,189,034 6,147,785 5,069,662 3,896,700 2,661,101

486,190,218 426,278,652 387,311,016

371,186,576 347,609,782 320,683,236 276,633,490 255,058,762

237,792,552 203,462,963 173,278,752 146,582,792 135,598,561

122,964,571 102,048,342 83,850,491 68,183,731 54,832,155 43,411,578 34,302,919

26,515,609 19,857,297 14,243,286 9,757,648 6,491,547

A2.2 Tailwater Rating Table (received from Sithe 20/05/2011)

Elevation (m)

Discharge (m3/s)

66.35 66.6 66.8 67

67.2 67.21 71.29 71.59 71.89 75.59 76.71 79.3 80.69

0 16 24 32 48 64 655 728 800 2000 2500 4000 5000


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A2.3 Baseline Monthly Steamflows

(Derived from Kaieteur Falls Monthly Flows by a transposition factor of 0.3)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual

1950 104.07 81.03 42.42 32.31 134.61 171.39 100.62 101.55 49.50 16.83 14.73 60.84 75.83

1951 63.66 110.58 58.11 86.82 136.14 171.72 132.36 79.74 26.01 18.12 9.81 15.78 75.74

1952 28.77 42.33 14.67 37.86 98.19 134.67 91.95 102.36 23.13 13.50 16.35 31.56 52.95

1953 89.31 148.20 108.63 60.78 166.11 154.89 104.43 50.25 25.92 14.28 10.98 79.59 84.45

1954 103.62 46.83 36.72 117.78 145.92 163.59 101.91 103.92 41.67 27.27 36.57 66.03 82.65

1955 45.21 39.75 80.40 64.17 125.04 101.91 111.99 55.62 35.13 16.29 17.22 85.02 64.81

1956 116.67 66.12 66.72 38.40 120.33 210.12 140.76 81.24 61.35 32.91 22.71 73.17 85.88

1957 71.82 67.14 20.10 15.66 106.02 163.17 134.64 68.40 34.44 10.56 14.31 48.39 62.89

1958 33.99 38.91 37.20 122.25 142.92 81.87 78.15 86.28 20.16 13.50 11.73 36.84 58.65

1959 27.72 32.76 22.17 46.17 49.53 149.49 161.46 61.17 47.10 17.52 38.01 56.88 59.17

1960 47.58 51.15 17.91 44.01 157.29 132.72 90.99 64.41 18.21 11.70 27.63 32.13 57.98

1961 39.75 16.86 10.56 4.47 25.05 146.49 105.33 70.92 34.05 15.96 18.60 38.16 43.85

1962 38.28 30.96 25.74 16.11 69.09 141.00 89.97 72.54 21.12 10.89 16.74 16.44 45.74

1963 70.29 60.72 42.48 42.90 136.29 156.45 89.55 64.41 23.40 8.52 9.06 27.18 60.94

1964 8.04 7.83 13.71 37.08 46.20 95.28 73.83 41.97 17.13 12.96 15.75 39.78 34.13

1965 40.23 29.40 22.32 15.24 94.17 139.17 79.83 64.83 19.71 9.66 26.10 20.85 46.79

1966 27.27 9.33 25.41 22.74 39.99 121.32 103.71 83.13 45.93 14.85 12.81 39.45 45.50

1967 69.48 27.81 21.54 49.71 133.05 144.60 118.35 79.59 30.90 12.78 17.64 35.94 61.78

1968 64.74 21.57 22.68 86.58 74.70 196.56 116.07 45.66 32.13 16.26 44.67 57.30 64.91

1969 75.27 54.48 24.09 26.07 87.24 109.20 59.64 68.97 19.02 16.74 10.02 16.59 47.28

1970 67.53 59.16 41.82 72.18 105.00 98.25 111.72 104.61 47.52 13.50 17.85 42.69 65.15

1971 64.89 45.78 35.46 50.07 157.50 166.02 155.37 74.10 43.47 24.78 33.03 39.24 74.14

1972 89.52 51.00 85.77 89.31 169.53 157.80 117.06 56.85 51.18 15.00 55.35 54.24 82.72

1973 22.86 17.73 19.38 26.13 61.32 133.14 126.99 68.43 99.66 62.94 64.05 92.70 66.28

1974 144.87 60.57 52.95 103.47 24.06 77.40 146.10 113.88 93.27 48.66 54.69 50.58 80.88

1975 102.96 70.41 34.08 21.78 54.48 184.59 110.82 138.57 90.99 28.05 27.75 69.15 77.80

1976 96.00 86.01 99.99 159.33 206.70 171.96 164.79 98.22 23.31 13.59 15.12 65.40 100.04

1977 48.18 32.97 45.27 30.57 108.42 142.44 164.55 134.37 54.15 28.65 18.87 50.07 71.54

1978 32.01 36.45 19.77 45.54 158.61 141.93 110.67 122.49 58.23 36.69 46.20 82.23 74.24

1979 68.43 23.28 73.68 81.60 132.36 145.50 107.88 75.60 32.79 46.50 30.24 57.45 72.94

1980 42.24 15.33 25.02 131.67 144.93 146.70 108.69 71.88 31.92 17.46 21.24 47.43 67.04

1981 58.38 42.90 31.26 43.95 103.47 140.82 106.80 84.33 59.37 36.42 23.58 59.64 65.91

1982 66.03 45.72 34.20 48.72 192.87 151.98 128.01 57.21 15.63 11.49 15.00 43.08 67.50

1983 60.03 25.47 40.14 108.93 123.48 91.59 70.26 59.49 23.01 14.64 19.29 44.46 56.73

1984 57.81 42.15 31.77 9.36 66.06 124.89 89.82 70.83 30.75 16.50 21.09 48.78 50.82

1985 59.04 43.11 16.41 12.51 72.96 124.65 48.63 56.49 23.97 15.66 20.10 40.59 44.51

1986 26.28 48.15 27.27 14.10 60.51 145.89 80.73 41.73 12.12 13.56 28.11 70.59 47.42

1987 76.77 53.58 36.78 45.39 107.85 142.17 105.15 71.73 32.49 18.36 22.02 49.20 63.46

1988 60.21 43.41 32.16 43.80 104.82 137.58 105.42 73.14 31.44 17.01 21.21 44.73 59.58

1989 57.03 38.55 29.61 41.61 100.98 168.33 111.93 34.83 15.09 21.96 39.51 37.83 58.11

1990 84.00 73.05 37.29 98.40 149.70 126.63 76.02 55.44 13.17 10.71 9.87 39.30 64.47

Minimum 8.04 7.83 10.56 4.47 24.06 77.40 48.63 34.83 12.12 8.52 9.06 15.78 34.13

Average 62.22 47.28 38.14 54.77 109.60 141.61 108.12 75.88 36.82 20.08 24.28 48.96 63.98

Maximum 144.87 148.20 108.63 159.33 206.70 210.12 164.79 138.57 99.66 62.94 64.05 92.70 100.04


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A2.4 Estimated Monthly Net Reservoir Evaporation

(Adopted from MWH 2001 Report)


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Annex C Site Visit Report

C1. Introduction

This short report summarises the Halcrow Hydrology Team’s main activities during their visit to Guyana from 18 to 22 May 2011, including site visits to two of the hydrometric gauging stations located on Kuribrong River downstream of Amaila Falls and on Potaro River upstream Kaieteur Falls, respectively and meetings at Hydro-meteorological Service of the Ministry of Agriculture and at the Guyana Energy Agency. The Halcrow Hydrology team visiting the sites comprised Zhengfu Rao (PM, Principal Consultant) and Matthew Scott (Principal Hydrologist). They believe that most of the required information and data have been collected pending further review and would like to thank Sithe for organising the meetings and arranging the logistics to the gauging stations. They also appreciated the support provided by the Hydro-meteorological Service of the Ministry of Agriculture and by the Guyana Energy Agency. The Halcrow Project Team will analyse the information and data gathered on site and at the meetings and report the findings at a later stage in the Draft Final Report. C2. Site Visit Report

Tuesday 17th: pm: Left London Heathrow. Wednesday 18th: Arrival and Meetings in Georgetown 08:00: Arrived Georgetown. 12:00: Met with Sithe Global representative Chris Kelly (Engineer) to discuss programme for site visit and confirm scope of Hydrology Review. 14:00: Meeting at Hydro-meteorological Service of Ministry of Agriculture with Mr. Zainool Rahaman (Specialist Hydrologist), Lydon Alves (Team Leader) and Kelvin Samaroo (Technician), joined by Chris Kelly (Sithe) and John Cush (PPA), to discuss:

• Availability of hydro-meteorological data post 1991, with particular reference to flow and level data at Kaieteur Falls and Amaila Falls, and rainfall data at Kaieteur Falls.

• Data collection procedures, with particular emphasis to hydro-meteorological data at Kaieteur Falls.

• Availability of additional rainfall data, with particular reference to Kaieteur Falls.

• Availability of 1975 pre-feasibility report for review.

• Regional variation in precipitation, with particular reference to ‘The Classification of the Rainfall Regions of Guyana’ Climate related science series no. 4 report (May 1995).

16:00: Met with Sithe Global Senior Vice President Development (James McGowan) to confirm programme for site visit and scope of Hydrology Review. Thursday 19th: Site visit accompanied by Chris Kelly and Mr. Zainool Rahaman. 07:00: Arrive at airport for transfer to Kaieteur Falls landing strip. 10:30: Helicopter / boat transfer to hydrometric station on Kuribring River downstream of Amaila Falls. 11:00 – 14:00: Inspection of level recording equipment – Sutron Constant Flow Bubbler pressure transducer and Sutron 9210 XLite automatic data logger and manually-read staff gauge (see Figure). Assisted in calibration of pressure transducer and staff gauge and discussion of operational maintenance procedures. 14:00: Transfer by boat / helicopter to Kaieteur Falls landing strip.


Draft Report


14:30 – 16:00: Hike to hydrometric station on Potaro River upstream Kaieteur Falls. Site inspection – manual reading of staff gauge and spot check of level chart. Replacement of level; chart (see Figure). 16:30: Transfer to Georgetown. Friday 20th: Meetings in Georgetown 09:30 – 12:00: Follow-up visit to Hydro-meteorological Service of Ministry of Agriculture to review data management procedures and collect additional hydrometric data. Copies of Kaieteur Falls spot flow measurements summary, stage-discharge ratings and cross sections, and Amaila Falls spot flow measurements (1975) obtained (see Figure C). Additional data for Kaieteur Falls and Portage Falls (Kuribrong River) provided. 14:30 – 15:30: Meeting at Guyana Energy Agency to review ‘Hydroelectric Power Survey of Guyana Final Report’ (Montreal Engineering Company Limited, April 1976). Copies of relevant sections of Volumes 2, 4 and 5 obtained re: hydrology and sedimentation studies. Saturday 21st: Free day Sunday 22nd- Monday 23rd : Travel Back To UK Sunday 22nd : 08:00: Left Georgetown. Monday 23rd: 07:00: Arrived London Heathrow.

Photos Taken During the Site Visits

Figure C1: Proposed powerhouse is located on the left bank of the river (right on the photo).


Draft Report


Figure C2: Hydrometric station downstream Amaila Falls

Figure C3 Rainfall gauging station upstream Kaieteur Falls


Draft Report


Figure C4 Hydrometric station upstream Kaieteur Falls

Figure C5 Kaieteur Falls stage-discharge curve and spot flow measurements

Extract of Amaila Falls Hydrology Review Draft Report 23June2011

Documents

Transcript of Extract of Amaila Falls Hydrology Review Draft Report 23June2011