Nile Basin Initiative (NBI) Eastern Nile Subsidiary Action Program (ENSAP) Eastern Nile Technical and Regional Office (ENTRO) Eastern Nile Planning Model (ENPM) Project

–

Kevin Wheeler P.E. and Steve Setzer P.E.

October 20 th , 2012

Eastern Nile RiverWare Planning Model – Final Report

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Eastern Nile RiverWare Planning Model – Final Report

Contents 1 Executive Summary ...... 8 2 Introduction ...... 8 3 RiverWare Model Development Tool ...... 9 3.1 Object-Oriented Approach ...... 9 3.2 Rule-Based Model Solutions ...... 9 3.3 Data Management ...... 10 4 Three-Phase Approach ...... 11 4.1 Calibration Model ...... 11 4.2 Baseline Model ...... 12 4.3 Scenario Model ...... 13 5 General Model Design...... 14 5.1 Overall Network Layout ...... 14 5.2 Data Sources ...... 15 5.2.1 Hydrologic Inflow Data Sources ...... 15 5.2.2 Demand Data Sources ...... 16 5.2.3 Reservoir Characteristic Data Sources ...... 16 5.3 Model Run Period ...... 18 6 Model Schematic and Network ...... 18 6.1 Blue Nile ...... 18 6.1.1 Hydrologic Inflows...... 19 6.1.2 Demands ...... 19 6.1.3 Reservoir Data ...... 20 6.1.4 Stream Gage Data ...... 23 6.1.5 Blue Nile Environmental Requirements ...... 23 6.2 Baro-Akobo-Sobat ...... 24 6.2.1 Hydrologic Inflows...... 25 6.2.2 Demands ...... 25 6.2.3 Reservoir Data ...... 25 6.2.4 Stream Gage Data ...... 25 6.3 Tekeze-Setit-Atbara ...... 26 6.3.1 Hydrologic Inflows...... 26

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6.3.2 Demands ...... 27 6.3.3 Reservoir Data ...... 27 6.3.4 Stream Gage Data ...... 29 6.3.5 Tekeze-Setit-Atbara Environmental Requirements ...... 29 6.4 White Nile from Malakal to Khartoum ...... 29 6.4.1 Hydrologic Inflows...... 30 6.4.2 Demands ...... 31 6.4.3 Reservoir Data ...... 31 6.4.4 Stream Gage Data ...... 32 6.5 Main Nile ...... 32 6.5.1 Hydrologic Inflows...... 33 6.5.2 Demands ...... 33 6.5.3 Reservoir Data ...... 35 6.5.4 Stream Gage Data ...... 37 7 Model Calibration ...... 37 7.1 Blue Nile Calibration ...... 37 7.2 Baro-Akobo-Sobat Calibration ...... 42 7.3 Tekeze-Setit-Atbara Calibration ...... 46 7.4 White Nile from Malakal to Khartoum Calibration ...... 47 7.5 Main Nile Calibration ...... 52 7.6 Calibration Summary ...... 55 8 Baseline Model ...... 56 8.1 General Model Design...... 56 8.2 Blue Nile Baseline Model ...... 57 8.2.1 Modeling Method ...... 57 8.2.2 Modeling Results ...... 58 8.2.3 Results Discussion ...... 61 8.3 Baro-Akobo-Sobat ...... 61 8.3.1 Modeling Method ...... 61 8.3.2 Results Discussion ...... 62 8.4 Tekeze-Setit-Atbara ...... 62

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8.4.1 Modeling Method ...... 62 8.4.2 Results Discussion ...... 65 8.5 White Nile from Malakal to Khartoum ...... 65 8.5.1 Modeling Method ...... 65 8.5.2 Results Discussion ...... 66 8.6 Main Nile ...... 67 8.6.1 Results Discussion ...... 69 8.7 Shortages to Water Demands ...... 69 8.8 Summary of Reservoir Operations ...... 70 9 Proposed Infrastructure ...... 70 9.1 General Approach ...... 70 9.2 Proposed Infrastructure ...... 70 9.3 Modeled Representation ...... 71 10 Alternative Scenario Development ...... 74 10.1 Representative Scenarios ...... 74 10.2 Model Results ...... 75 10.2.1 Pool Elevations ...... 75 10.2.2 Power/Energy Generation and Spills ...... 81 10.2.3 Reservoir Evaporation ...... 91 10.2.4 Demands ...... 93 10.3 Mass Balance Analysis...... 94 11 Conclusion ...... 95 12 Bibliography ...... 96

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Figure 3-1. RiverWare Model Data Management ...... 11 Figure 6-1. Model Schematic of the Blue Nile Sub-Basin ...... 19 Figure 6-2. Model Schematic of the Baro-Akobo-Sobat Sub-Basin ...... 25 Figure 6-3. Model Schematic of the Tekeze-Setit-Atbara Sub-Basin ...... 26 Figure 6-4. Model Schematic of the White Nile ...... 30 Figure 6-5. Model Schematic Main Nile ...... 33 Figure 6-6. High Aswan Dam Operation Zones ...... 36 Figure 7-1. Model Schematic of the Upper Blue Nile ...... 37 Figure 7-2. Model Schematic of the Middle Blue Nile ...... 38 Figure 7-3. Time Series Calibration of the Blue Nile at El Diem Gage ...... 38 Figure 7-4. Modeled vs. Historical Calibration of the Blue Nile at El Diem ...... 39 Figure 7-5. Model Schematic of the Lower Blue Nile ...... 39 Figure 7-6.Time Series Calibration of the Blue Nile for Roseries Dam Elevation ...... 40 Figure 7-7. Time Series Calibration of the Blue Nile Khartoum and Soba Gage ...... 41 Figure 7-8. Modeled vs. Historical Calibration of the Blue Nile Khartoum and Soba Gage ...... 42 Figure 7-9. Model Representation of the Lower Baro and Sobat Reaches ...... 43 Figure 7-10. Baro at Gambella and Adura Flows (1947-1956) ...... 43 Figure 7-11. Relationship between Baro River Flows at Gambella and Adura Flows...... 44 Figure 7-12. Attenuation of Flows in the Sobat ...... 44 Figure 7-13. Time Series Calibration of the Sobat River at Hillel Doleib ...... 45 Figure 7-14. Modeled vs. Historical Calibration of the Sobat River at Hillel Doleib ...... 45 Figure 7-15. Time Series Calibration of the Atbara River at Kilometer 3 ...... 46 Figure 7-16. Modeled vs. Historical Calibration at the Atbara at Kilometer 3 ...... 47 Figure 7-17. Time Series Calibration on the White Nile at Melut ...... 48 Figure 7-18. Modeled vs. Historical Calibration on the White Nile at Melut ...... 48 Figure 7-19. Time Series Jebel Aulia Calibration using Historical Monthly Elevations ...... 49 Figure 7-20. Jebel Aulia Calibration by Average Historical Pool Elevation ...... 50 Figure 7-21. Time Series Calibration of the White Nile at Mogren ...... 51 Figure 7-22. Modeled vs. Historical Calibration of the White Nile at Mogren ...... 51 Figure 7-23. Time Series Calibration of the Main Nile at Dongola...... 52 Figure 7-24. Modeled vs. Historical Calibration of the Main Nile at Dongola ...... 53 Figure 7-25. Lake Nassar Evaporation Rates ...... 53 Figure 7-26. Time Series Calibration of the Pool Elevations of Lake Nassar ...... 54 Figure 7-27. Time Series Calibration of the Main Nile at El Akhsas ...... 54 Figure 7-28. Modeled vs. Historical Calibration of the Main Nile at El Akhsas ...... 55 Figure 7-29. Evaporation Rates of East Nile Reservoirs ...... 55 Figure 7-30. Calibration Summary ...... 56 Figure 8-1. Lake Tana Modeled Baseline Pool Elevation ...... 58 Figure 8-2. Tana-Beles Modeled Baseline Power Generation ...... 59 Figure 8-3. Roseries Dam Modeled Pool Elevation ...... 59

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Figure 8-4. Roseries Dam Modeled Power Generation ...... 60 Figure 8-5. Sennar Dam Modeled Pool Elevation ...... 60 Figure 8-6. Sennar Dam Modeled Power Generation ...... 61 Figure 8-7. Tekeze Dam Modeled Pool Elevation ...... 62 Figure 8-8. Tekeze Dam Modeled Power Generation ...... 63 Figure 8-9. Khashm El Girba Dam Modeled Pool Elevation ...... 63 Figure 8-10. Khashm El Girba Dam Modeled Power Generation ...... 64 Figure 8-11. Khashm El Girba Diversion Power Production ...... 64 Figure 8-12. Jebel Aulia Dam Modeled Pool Elevation ...... 66 Figure 8-13. Jebel Aulia Dam Modeled Power Generation...... 66 Figure 8-14.Merowe Dam Modeled Pool Elevation...... 67 Figure 8-15. Merowe Dam Modeled Power Generation ...... 68 Figure 8-16. High Aswan Dam Modeled Pool Elevation ...... 68 Figure 8-17. High Aswan Dam Modeled Power Generation ...... 69 Figure 9-1. Proposed Reservoir Control Panel ...... 71 Figure 9-2. Model Schematic of the Proposed Karadobi Dam Location ...... 72 Figure 9-3. Model Schematic of the Proposed Renaissance Dam Location ...... 72 Figure 9-4. Evaporation Rates of Proposed Reservoirs ...... 74 Figure 10-1. Scenario Results for Merowe Pool Elevation ...... 75 Figure 10-2. Exceedance Plot for Merowe Pool Elevations ...... 76 Figure 10-3. Inflows to High Aswan Dam ...... 77 Figure 10-4. Exceedance Plot of Total Inflows to High Aswan Dam ...... 77 Figure 10-5. Outflows from High Aswan Dam ...... 78 Figure 10-6. Exceedance Plot of Total Outflows from High Aswan Dam ...... 78 Figure 10-7. Scenario Results for High Aswan Pool Elevation ...... 79 Figure 10-8. Exceedance Plot for High Aswan Pool Elevations ...... 80 Figure 10-9. Blue Nile Dependent Operation of Jebel Aulia Dam ...... 81 Figure 10-10. Total Power Generation by Facilities in Ethiopia ...... 82 Figure 10-11. Exceedance Plot of Total Power Generated in Ethiopia ...... 82 Figure 10-12. Annual Energy Generation by Facilities in Ethiopia ...... 83 Figure 10-13. Exceedance Plot of Annual Energy Generation by Facilities in Ethiopia ...... 83 Figure 10-14. Total Power Generation by Facilities in Sudan ...... 84 Figure 10-15. Exceedance Plot of Total Power Generated in Sudan ...... 84 Figure 10-16. Annual Energy Generation by Facilities in Sudan ...... 85 Figure 10-17. Exceedance Plot of Annual Energy Generation by Facilities in Sudan ...... 85 Figure 10-18. Total Power Generation by Facilities in Egypt ...... 86 Figure 10-19.Exceedance Plot of Total Power Generated in Egypt ...... 86 Figure 10-20. Annual Energy Generation by Facilities in Egypt ...... 87 Figure 10-21. Exceedance Plot of Annual Energy Generation by Facilities in Egypt ...... 87 Figure 10-22. Total System Power Generation ...... 88 Figure 10-23. Exceedance Plot of Total System Power Generated ...... 88

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Figure 10-24. Total System Annual Energy Generation ...... 89 Figure 10-25. Exceedance Plot of Total System Annual Energy Generation ...... 89 Figure 10-26. Percentage of Outflows Spilled from Roseries Dam ...... 90 Figure 10-27. Percentage of Outflows Spilled from Merowe Dam ...... 91 Figure 10-28. Combined Annual Evaporation of Ethiopian and Sudanese Reservoirs ...... 92 Figure 10-29. Annual Evaporation for High Aswan Dam ...... 92 Figure 10-30. Average Annual Changes in Reservoir Evaporation...... 93 Figure 10-31. Total Shortages to Water Users During the Filling Period of Scenarios ...... 93 Figure 10-32. Mass Balance Across Entire Modeled Period ...... 94

Table 5-1 Infrastructure Included in Phased Model Development ...... 15 Table 5-2. Operational Rules Provided by ENTRO ...... 17 Table 6-1. Demands on the Blue Nile...... 20 Table 6-2. Elevation-Discharge Relationship for Lake Tana ...... 20 Table 6-3. Tana-Beles Hydropower Generation ...... 21 Table 6-4. Roseries Dam Target Elevation ...... 22 Table 6-5. Sennar Dam Target Elevation ...... 23 Table 6-6. Environmental Demands in the Blue Nile ...... 24 Table 6-7. Demands on the Tekeze-Setit-Atbara ...... 27 Table 6-8. Khashm El Girba Dam Target Elevation ...... 28 Table 6-9. Environmental Demands in the Tekeze-Setit-Atbara ...... 29 Table 6-10. Demands on the White Nile Between Malakal and Khartoum ...... 31 Table 6-11. Jebel Aulia Dam Target Elevation...... 32 Table 6-12. Demands on the Main Nile ...... 34 Table 6-13. Elevation-Based Diversion to the Toshka Project ...... 34 Table 6-14. High Aswan Inflow States ...... 36 Table 8-1. Operation Summary of Baseline Reservoirs ...... 70 Table 9-1. Reservoir and Turbine Characteristics of Proposed Reservoirs ...... 73

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1 Executive Summary

This report describes the development of the Eastern Nile RiverWare model for the Eastern Nile Technical Regional Office (ENTRO) of the Nile Basin Initiative (NBI). The process of model development was a collaborative effort between the consultants and ENTRO with the explicit objective of both providing a tool capable of simulating potential alternative management practices in the basin, and offering the training required to operate, modify and enhance the model. As part of successfully meeting this objective, the model was calibrated to historical conditions, developed into a baseline condition representing current infrastructure and known management practices, and then configured to represent twelve potential proposed infrastructure development projects. To demonstrate the utility of the RiverWare model, an analysis was conducted on the simulated outputs of five selected configurations of development in the Blue Nile, each using a different variety of proposed reservoirs. Inputs to the model reflected the best available information at the time of model development and future refinement and development of the model is encouraged to meet the evolving needs of ENTRO and the stakeholders of the Eastern Nile Region.

2 Introduction

In April 2012, the Eastern Nile Technical Regional Office (ENTRO) of the Nile Basin Initiative (NBI) coordinated with Mr. Kevin Wheeler and Mr. Steve Setzer to build a RiverWare model of the Eastern Nile Region. The purpose of the model is to enhance the analytical capacity of ENTRO staff and the participating stakeholders in the basin to allow the simulation and evaluation of alternative multi- objective management and development strategies for the principal Eastern Nile sub-basins including the Blue Nile, Baro-Akobo-Sobat, Tekeze-Setit-Atbara, and portions of the White Nile and the Main Nile. The objective of this report is to document the RiverWare model that was developed to meet these requirements including the input data, modeling assumptions, functional requirements of the model and the model output and results. Furthermore, this report describes the configuration of the model representing both the current conditions and proposed scenarios. Section 3 describes the RiverWare generalized modeling tool used in this project and Section 4 describes the three-phased approach used in this development process. Section 5 describes the general model design and data sources used for the model development. Section 6 describes the modeled representation of each sub-basin in detail including input data and reservoir operations. Section 7 describes the calibration of the model using historical conditions and Section 8 describes the baseline model configuration and results. Section 9 describes the proposed infrastructure developed for the model and Section 10 describes the alternative scenarios modeled for this study.

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3 RiverWare Model Development Tool

The model developed for this project utilizes RiverWare, a general river basin modeling tool developed at the Center for Advanced Decision Support for Water and Environmental Systems (CADSWES) at the University of Colorado in Boulder (Zagona et al., 2001). RiverWare contains a flexible modeling environment that uses both an object-oriented workspace environment and rule-based policy language that allows a robust simulation of complex operational decisions and policies that govern the management of reservoir systems. RiverWare development has been sponsored and primarily funded by the United States Bureau of Reclamation, the U.S. Army Corps of Engineers and the Tennessee Valley Authority. RiverWare is used extensively by those organizations as well as numerous other licensees world-wide. National governments, individual states or provinces, municipalities, water management districts and authorities, water-related non-governmental organizations and consultants such as the authors of this report maintain active RiverWare licenses. The software is actively used to study, manage and operate the past and future of river basins around the world.

3.1 Object-Oriented Approach RiverWare contains an object-oriented workspace environment that represents the physical layout of a river basin and all major types of entities that are involved in water resource management. Examples of objects types used in RiverWare include storage reservoirs, level power reservoirs, slope power reservoirs, pumped storage reservoirs, river reaches, gaging stations, river confluences, river bifurcations, diversion objects, pipelines, pipe junctions, pump stations, in-line power plants, water users, canals, and groundwater storage objects. A graphical user interface (GUI) allows the user to select objects from a pallet that represent those entities, arrange and configure them according the physical characteristic of the model, and interconnect them with links that represent the physical topology and management relationships to each other.

Each object contains a number of “slots” that represent data that describes the object including the physical characteristics of the entity represented (i.e. elevation-volume curves), data used as inputs to the simulation object (i.e. inflow time series) and outputs that describe the modeled characteristics of the object (i.e. outflow and power generation time series). Furthermore, each object can be configured and customized using a wide variety of available engineering “methods” that define the desired relationships between the data slots in the model and how internal computations are used to simulate the solution of objects.

3.2 Rule-Based Model Solutions RiverWare operates with three basic modes to determine modeled solutions that include Simulation, Rule-based Simulation and Optimization. The first two modes can be generally considered “descriptive” solutions that provide an output that describes the result of a set of given physical or operational inputs. The latter provides a solution that can generally be considered “prescriptive” of what an optimal operation should be. The rule-based solution method is the most commonly used solution method for planning models and is used in the RiverWare Eastern Nile Planning Model described in this report.

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Rule-based simulation generally begins with a network model that contains some input information but is not sufficiently defined though these data inputs to determine modeled solutions. To determine a solution for such a system, a hierarchy of “rules” is written through logical expressions and executed using existing known data and parameters to calculate unknown data and parameters. This solution method provides the flexibility of a programming language providing an assembly of commonly used logic that simulates the operational management decisions that are often made in multi-objective river basin systems.

Providing an example of rule-based operations can be useful. The operation of a reservoir is often a complex decision that consists of many factors. While current pool elevations and volumetric inflow rates to a reservoir may be known, the outflows and resulting pool elevations are unknown, interrelated and a result of a particular decision process. The outflows may be set based on a number of criteria or objectives such as meeting downstream demands, achieving a particular pool elevation for flood control or recreational purposes, providing minimum or maximum releases for downstream environmental considerations, releasing water to generate a specified power demand through hydropower turbines, etc. The relationships between these objectives must often be prioritized, especially if the criteria to meet these objectives result in competing or conflicting operational decisions. The robust programming language of RiverWare allows the modeler to organize the operational management criteria in a way that reflects the actual desired decision making process and determine a specified release from the reservoir.

3.3 Data Management Managing data in the Eastern Nile RiverWare Planning model is accomplished by using efficient and accessible internal data storage in addition to the ability to import data from and export data to external sources. All data that is required to operate a single execution of the model is contained within a single model file (.mdl) and all output data can also be optionally stored within the same model file or exported to external files. Data can be imported through copying from spreadsheets and pasting directly into the model, or through automated routines that extract data from external sources. To facilitate multiple model runs that may occur in the future, data management interfaces (DMI’s) provide a mechanism to import data into the model from external sources and export data from the model to external sources. The logic that describes the rule-based operation described above is contained in a rule-set file (.rls). A Graphical Policy Analysis Tool (GPAT) is provided by CADSWES that allows the comparative analysis of multiple Excel output files.

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RiverWare

Input Data Input Output DMI Output Data Model File Sources Files

GPAT

Rule Set

Figure 3-1. RiverWare Model Data Management

4 Three-Phase Approach

The RiverWare model development consisted of three distinct phases:

o Phase 1: Calibration o Phase 2: Baseline Development o Phase 3: Alternative Scenario Development A description of the primary objective of each phase is provided below, along with the general methods used to accomplish the objective. Details of the implementation of each phase and the results are provided in subsequent sections. Each phase resulted in a distinct model that achieved the purpose of the particular phase and built the foundation for subsequent models.

4.1 Calibration Model The objective of the calibration phase was to construct a model of the Eastern Nile region that would verify the accuracy of the assumed model configuration and identify the physical characteristics and processes of the basin that must be considered in modeling the future operations and management of the basin. To accomplish this task, a thorough understanding was required of both the natural conditions and human influences over a historical period of time.

A variety of inputs were used in the development of the calibration model including historical hydrologic inflows, demand characteristics, stream gage records, physical reservoir characteristics, and historical topology of the principal components in the basin. In addition, assumptions of historical operations were made when necessary to augment the calibration process.

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The directive in the scope of the current project was to maximize the use of existing datasets, therefore historical naturalized hydrologic inflow data was primarily obtained from an existing MIKE Basins model developed by NBI through Work Package II, Stage I (WP II Stage I) described in a referenced model report (Nile Basin Initiative, 2011). Where this source was inadequate, data was extracted from the ongoing Work Package II, Stage II (WP II Stage II) modeling effort and through previous efforts at ENTRO that estimated intervening and unmeasured flows from historical gage data. These inflow datasets were incorporated into the RiverWare model and used to simulate historical conditions for the calibration phase.

Consumptive use and demand data was obtained from the WP II Stage I model. These demands were only available as average monthly depletions, and no distinction is made with respect to interannual variability. Therefore both the WP II Stage I Model and the RiverWare model assume identical demand patterns for the entire period of record. The lack of actual historical diversion records poses a significant limitation to calibration of the historical conditions and must be acknowledged. Improved estimates of the historical demands throughout the basin, including population growth and expansion of agriculture, would improve the calibration results.

An ideal calibration process utilizes known or reconstructed data of the region including hydrologic inflows, depletions from the river, historical development of infrastructure that affected the natural system, and various physical historical characteristics of the natural and modified system. This information is used to determine unknown physical properties through mass balance comparisons with historical stream gage data. Adjustments are made to the parameters that affect the physical processes such as simulation of gains, seepage and evaporation losses and timing of flows until a suitable comparison is made with available historical data. Although this ideal calibration procedure was used in certain regions of the Eastern Nile RiverWare Planning model, alternative calibration procedures were applied in regions when sufficient data was unavailable to fully describe the system. These alternative procedures combine available known data with assumed historical reservoir operations to allow modeled flows at stream gages to be compared with known historical values. The calibration procedures applied to each sub-region are described in detail in Section 7 of this report.

To perform a proper calibration, data is required over a common period of history for all aspects that describe the known hydrology. The historical period selected in the calibration phase is 1956 to 1990 . This period was selected primarily based on the availability of stream flow data and reconstructed intervening inflows to the system. Using this historical period, a successful calibration model was developed that adequately simulates the historical conditions of the basin and provided a method to estimate the physical gains and losses in the system.

4.2 Baseline Model The primary goal of the baseline development phase is to generate a model that accurately reflects current conditions and potential future conditions using currently established infrastructure. The baseline model is similar to the calibration model by using the general model framework developed in the first phase, but model inputs and structure are modified to simulate future conditions. The primary inputs to the baseline model include assumed future hydrologic inflows, demands, and reservoir

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Eastern Nile RiverWare Planning Model – Final Report conditions. Due to the uncertain nature of these projected inputs, the outputs are naturally subject to a greater degree of uncertainty and any application of a model must recognize these limitations.

The hydrologic inflows used in the current baseline model are historical inflows and therefore identical to the calibration model. Although this provides a sound justification for estimates of future inflows, this method assumes stationarity and does not consider hydrologic conditions that have not been historically recorded. Alternative methods to determine future hydrologic inflows can be used such as rainfall-runoff models combined with downscaled global circulation models. Such methods can be used to allow a larger range of potential conditions. In the development of the Eastern Nile RiverWare Planning Model, historical hydrologic inflows are used for the baseline model and future planning scenarios, however the model is configured to readily accept alternative hydrologic inputs as they are developed in the future.

The demands used in the current baseline model are monthly average consumptive uses available from the WP II Stage I model and are also identical to those used in the calibration model. No increases or decreases in total annual consumptive use are currently assumed, but this can be easily incorporated into the model as improved demand projections are developed.

The fundamental difference between the calibration model and the baseline model is in the solution method. As described above, the calibration model utilizes historical data whenever available to specify reservoir operations. In contrast, the baseline model relies on operating policy to simulate the future operations of the reservoirs. In addition, the major infrastructure projects that were developed in the modeled region since the end of the calibration period (1990) are included in the baseline model. These projects include the Tekeze Dam in on the upper Atbara River, the Merowe Dam on the Main Nile upstream of Dongola, and the Tana-Beles Hydropower project.

Initial conditions of the reservoirs in the Baseline model were assumed. No precise data for current reservoir levels were known, therefore all reservoirs were considered at full capacity or targeted January elevations on the starting time step with the exception of the Aswan Dam, which assumed an initial starting elevation of 165 masl. Due to the nature of the current application of this model for the purpose of long-term comparative studies or proposed infrastructure, this assumption was deemed reasonable.

4.3 Scenario Model The third phase of the RiverWare model development was the addition of numerous proposed reservoirs to the model. Proposed reservoirs were incorporated into the model that could be sufficiently characterized by their physical properties including storage, elevation, evaporation, and hydropower generation characteristics. The twelve proposed reservoirs that met these criteria included:

Blue Nile / Abay • Karadobi • Beko Abo High • Beko Abo Low • Upper Mandaya (relocated) • Lower / Original Mandaya

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• Renaissance 640 Dam • Renaissance 620 Dam • Didessa BAS • Baro 1 • Baro 2 Main Nile • Sherieg • Kajbar

Although future operations of the proposed reservoirs are by definition speculative, the primary goal of operating to maximize hydropower generation was assumed for each location. The scenario model was developed in a format that allows each of the proposed reservoirs to be turned on or off to allow the evaluation of various combinations of storage facilities.

5 General Model Design 5.1 Overall Network Layout The Eastern Nile RiverWare Planning Model consists of the principal Eastern Nile sub-basins including the Blue Nile, Baro-Akobo-Sobat, Tekeze-Setit-Atbara, and portions of the White Nile and the Main Nile. Each sub-basin is modeled with the primary inflow tributaries, reaches, reservoirs, demand locations and stream gages.

Hydrologic inflows are included throughout the model based on datasets generated through previous modeling efforts. The locations of these inflows represent a combination of gaged tributary locations, intervening inflows representing ungaged inflows, and synthetically generated inflows in regions where little historical gaged data exists. Similarly, diversions are aggregated into groups representing cumulative depletions in particular reaches and at generalized locations. The relative location of assumed inflow locations and these aggregate depletion locations may affect the ability of the model to accurately simulate shortages to particular water users. In such cases of unavoidable uncertainty due to spatial resolution, it is important to recognize that the purpose of modeling is not to be predictive, but to allow a comparative analysis between alternatives that affect the mass balance of the overall system.

Infrastructure included in each model reflects the actual infrastructure during the period of simulation. The historical calibration model contains the major infrastructure in operation between 1956 and 1990, the Baseline model contains the infrastructure that is currently operational, and the Scenario Model contains the proposed future infrastructure in addition the current infrastructure that will likely be operational into the modeled future period.

Table 5-1 describes which reservoirs were included or active in each of the three phases of model development.

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Phase 1: Phase 2: Phase 3: Calibration Model Baseline Model Scenario Model Lake Tana XXX Sennar Dam XXX Jebel Aulia Dam XXX Khashm El Girba Dam Start 1964 X X High Aswan Dam Start 1964 X X Roseries Dam Start 1967 X X Merowe Dam XX Tekeze Dam XX Tana-Beles Hydropower XX Baro 1 Dam X Baro 2 Dam X Beko Abo High Dam X Beko Abo Low Dam X Kajbar Dam X Karadobi Dam X Lower Didessa Dam X Mendaya Dam X Mendaya Upper Dam X Renaissance 620 Dam X Renaissance 640 Dam X Sherieg Dam X

Table 5-1 Infrastructure Included in Phased Model Development

5.2 Data Sources This section describes the sources of data used in the RiverWare model development. A wide variety of sources were accessed and incorporated into the model including historical records, previous models, spreadsheets, reports and individual conversations with ENTRO staff. Data provided from ENTRO was checked for consistency by the consultant and further validation was done by ENTRO staff. When sources conflicted with each other, consultations with ENTRO were held to identify the most useful and reliable data source for the objective of the RiverWare model.

5.2.1 Hydrologic Inflow Data Sources The RiverWare model uses hydrologic inflows as direct inputs to the model, as opposed to computing inflows using a rainfall-runoff approach. Historical inflows were used for the calibration, baseline and scenario models whenever available. When gaged data was not available, existing inflows were extracted from previous modeling efforts. Three distinct sources were used to develop this historical inflow dataset.

1. Nile Basin Initiative, Work Product II, Stage I: As described in the scope of work, the primary source of hydrologic data was the WP II Stage I Model of the Eastern Nile Region (NBI 2011). This existing dataset provided a comprehensive suite of headwater locations throughout the area of interest covering the period from 1951 to 1990. 2. Monthly Blue Nile Dataset : An inflow dataset was acquired at ENTRO that focused on monthly inflows in the Blue Nile and covered variable periods of history. This dataset was developed through scoping studies of the alternative Blue Nile reservoir sites and contained a higher spatial

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resolution of incremental inflow locations for the period of 1956 to 2003 and was also used for the development of a HEC ResSim model. The overlap between these two datasets was 1956 to 1990 and formed the basis for the RiverWare models developed in this project. 3. Work Product II, Stage II : As A third source of hydrologic inflow data was used that was also acquired at ENTRO. This dataset was provided through various data extractions including a spreadsheet called BAS_Schematic.xlsx and ENTRO staff manually extracting data from the ongoing WP II Stage II Model of the Eastern Nile region. This source was used to inform inflow locations where the WP II Stage I Model did not provide sufficient spatial resolution to evaluate the proposed infrastructure alternatives. This source was specifically used for the inflows to the headwaters of the Baro-Akobo-Sobat and the Tekeze-Setit-Atbara sub-basins. These headwater flows were developed from a simplified rainfall-runoff model called NAM and represent the only available information for these reaches.

5.2.2 Demand Data Sources The availability of measured historical depletions is incomplete in some regions of the Eastern Nile Basin and non-existent in others. However average monthly demands are available and published in a variety of data sources. The primary source of demand data used in the RiverWare model was the Work Product II, Stage I model of the Eastern Nile region. This existing dataset provided a comprehensive suite of demand locations throughout the area of interest. All available demands are average monthly values and do not indicate any inter-annual variability. These same demands are used in the calibration, baseline and scenario models.

5.2.3 Reservoir Characteristic Data Sources Reservoir characteristics can be divided into physical and operational components. Physical characteristics include descriptive aspects such as elevation-volume-surface area curves, operational elevations, evaporation rates, and power generation characteristics. Operational characteristics describe how the reservoirs are used to meet management objectives. Five general sources of information were used to identify these reservoir characteristics:

1. Nile Basin Initiative, Work Product II, Stage I : Basic reservoir characteristics of elevation-volume- surface area were extracted from the WP II Stage I Model of the Eastern Nile Region , 2. A spreadsheet titled system diagram.xlsm was provided by ENTRO that contained both physical and operational characteristics of many of the existing reservoirs and a limited amount of information on some of the proposed reservoirs. The physical characteristics of elevation- volume-surface area generally matched those extracted from the WP II Stage I Model. This spreadsheet also contained a significant variety of operational characteristics for existing reservoirs. In particular, monthly target elevations, target releases and elevation-discharge relationships were available. Where multiple management objectives were identified for a single reservoir, little information on the governing rules was identifiable.

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Monthly Target Monthly Target Elevation-Discharge Elevation Release Lake Tana X Roseries Dam XX Sennar XX Khashim EL Girba XX Jabel Aulia XX Aswan XX Table 5-2. Operational Rules Provided by ENTRO

This source was essentially a collection of several management schemes. The logic included in the RiverWare model extensively used one or more of these schemes for each reservoir.

3. The Power Toolkit provided by ENTRO provided a variety of physical and operational characteristics for many of the existing and proposed reservoirs in the Eastern Nile Region. Information contained in a spreadsheet describes the elevation-volume-surface area relationships, reservoir characteristics, dam characteristics, power plant and turbine characteristics, and spillway characteristics. In addition, information includes environmental demands, tailwater elevations and a wide variety of descriptions related to the economic and environmental impacts of the reservoirs. It was observed that the Power Toolkit is an extensive repository of many sources of information; however it was also observed that the toolkit was still under development. Furthermore, information contradiction was sometimes observed from the different sources which asked for further investigation and validation. The primary use of this data source was to inform where other sources were inadequate, or insufficient, especially describing the proposed reservoirs and the power generation objectives of these future projects.

4. A key report to understanding the operation of the Dams within Sudan was the National Electricity Corporation Long-Term Power System Planning Study for the Reservoirs of Sudan (NEC 2003). This report supported the descriptions provided in the other sources describing the reservoir operations.

5. Personal communications with ENTRO staff provided valuable insight to the multiple objectives of the reservoirs. A specific example of this included understanding the operations of the Jebal Aulia dam and its relationship to the timing of the Blue Nile flow.

The availability of information describing the physical and operational characteristics of dam structures varied significantly between dam sites. In compiling the multiple sources of reservoir operation data, it became clear that some reservoirs are well defined and operational rules could be validated from multiple sources, while other sites had limited physical information available. RiverWare offers a variety of engineering methods that can be used to simulate characteristics such a power generation and spillways, depending on the reservoir characteristics and information available. Methods were selected and customized for each reservoir depending on the availability of data.

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It also became clear that the operation of some reservoirs are well described compared to other reservoirs. Rules were developed in RiverWare that operate reservoirs to meet the objectives of the reservoirs as specified in the above sources. For existing or proposed reservoirs for which no operational guidelines could be identified, rules were developed that operate reservoirs to meet target power demands. Like all rules in RiverWare, these are user configurable and the model user is able to change targets as needed. Specific details of each reservoir’s operations are described in subsequent sections.

5.3 Model Run Period As stated previously, the period of overlapping historical hydrologic data is from 1956 to 1990, therefore, this period was used to calibrate the model. The model simulates historical conditions such that reservoirs are disabled/inactive for dates before they began operating (historically) and reservoirs become operational, in the model, on the same year that they historically began operating.

The baseline model and the scenario model are used to model future conditions. The RiverWare model was configured to simulate the period from 2018 to 2052, using the same 35 years of historical hydrologic data from 1956 to 1990. In other words, historical inflow data from 1956 to 1990 was used for the 2018 to 2052 time period in the baseline and scenario models. The selected model start date of January 2018 was somewhat arbitrary, but was selected to begin after the projected completion of infrastructure currently under construction, thus avoiding arbitrary assumptions of filling criteria. All reservoirs are considered to be operational throughout the modeled period. By shifting the analysis to the future period, it also becomes clear that only future operations apply and historical operations cease to apply. Cases were observed in existing models where historical operations were mistakenly enabled for future development scenarios. Shifting the simulation period as described above prevents model users from making this critical modeling error in the future.

A monthly time step was selected for the RiverWare model due to the nature of its current and projected application. With the focus of the Eastern Nile Planning Model (ENPM) being long-term strategic planning and management of the Eastern Nile River Basin, this balances the objectives with the high degree of seasonal variability and data availability

6 Model Schematic and Network 6.1 Blue Nile The Blue Nile sub-basin is modeled from Lake Tana to the confluence with the White Nile at Khartoum. The historical and existing modeled network consists of fourteen inflow locations, three diversion locations and three reservoir sites.

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Figure 6-1. Model Schematic of the Blue Nile Sub-Basin

6.1.1 Hydrologic Inflows Historical hydrologic inflows were acquired from the WP II Stage I model. The five inflow locations into Lake Tana include: Gilg Abay, Megech, Ribb, Gumara, and Tana Ungaged Inflow

Time series data from five tributary locations include: Didessa, Dabus, Beles, Dinder, and Rahad

Incremental flows along the mainstem of the Blue Nile were extracted from a monthly flow spreadsheet at ENTRO which was used for the development of the HEC ResSim model. These monthly flows were developed through the scoping of the proposed reservoirs. These sites include: Bahar Dar to Kessie_Incremental, Kessie to Karadobi_Incremental, Karadobi to Mandaya_Incremental, and Mandaya to Border/Renaissance_Incremental

These incremental flows were available for these four sites for the period from 1956 to 2003 and were developed from simple subtractions of mainstem gages, therefore incorporating flows from tributaries already known from gaged data. To maintain the maximum resolution of hydrologic inflows in the Blue Nile, flows from the first dataset for the Didessa, Dabus and Beles were subtracted from the corresponding incremental flows in the second dataset and these tributaries were included in the model.

6.1.2 Demands Data from three demand locations were extracted from the WP II Stage I model including: Upstream Sennar Demand, Gezira Managil Demand, and Downstream Sennar Demand. These demands were simple repeating patterns. No data on historical inter-annual variability was available.

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Upstream Sennar Downstream Gezira Managil Demand Sennar Demand Demand cms cms cms January 82.78 7.25 185.58 February 67.46 7.51 202.34 March 66.33 8.1 190.86 April 44.69 10.42 118.13 May 34.87 11.72 30.78 June 35.09 12.39 44.49 July 77.06 12.54 180.89 August 97.39 9.04 268.64 September 93.75 7.22 258.55 October 132.38 10.28 337.76 November 148.2 11.35 321.77 December 141.85 10.11 249.6

Table 6-1. Demands on the Blue Nile

6.1.3 Reservoir Data Reservoirs on the Blue Nile include Lake Tana, Roseries Reservoir and Sennar Reservoir. Elevation- Volume-Surface Area relationships, evaporation rates and power generation characteristics were extracted from the WP II Stage I model and information provided by ENTRO.

6.1.3.1 Lake Tana Operations Operational rules for Lake Tana were based on the Elevation-Discharge relationships from information provided by ENTRO.

Elevation (m) Discharge (cms) 1783.5 0 1784.5 40 1785.0 56 1785.5 80 1786.0 107 1786.5 132 1787.0 165 1787.5 204 1788.0 260 1788.5 397

Table 6-2. Elevation-Discharge Relationship for Lake Tana

The Tana-Beles hydropower project was completed in May 2010 and is represented in the baseline and scenario models, but not included in the historical calibration model. The project diverts water directly from Lake Tana and is represented as such in the models. The relationship between the diverted flow

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Eastern Nile RiverWare Planning Model – Final Report and intake elevation for the diversion is defined in the Beles Multipurpose Level 1 Design Report from the Ethiopian Electric Power Corporation (EEPCO 2006).

If the elevation of Lake Tana is above 1787.0 masl or the elevation is above 1786.3 masl and it is still rising, then the flow to the Tana-Beles hydropower diversion is 160 cms. If the elevation of Lake Tana is below 1784.0 masl or is below 1784.3 and the elevation is decreasing, then the flow to the hydropower diversion is turned off. If the reservoir is between these two dynamic ranges, then the flow to the hydropower diversion is set to 77 cms.

The hydropower generation is modeled in RiverWare as an in-line power plant. The head variation is essentially fixed and therefore a unique relationship exists between flow and energy generated through the turbines.

Flow (cms) Power (MW) 0 0.0 77 213.1 160 423.0

Table 6-3. Tana-Beles Hydropower Generation

Water diverted through the Tana-Beles project is returned entirely to the headwaters of the Beles tributary, which flows into the Blue Nile upstream of the border between Sudan and Ethiopia.

6.1.3.2 Roseries Dam Operations Operational rules for Roseries Dam are based on descriptions provided by ENTRO. Due to the large seasonal fluctuation, relatively small storage volume, and high amount of sediment accumulating in Roseries, the operational criteria is specified to draw down the reservoir starting in mid-January and maintain a minimum elevation until the peak flow has passed in September. Therefore, meeting target elevation criteria is the primary guiding principle of the operation of Roseries Dam.

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Month Target Elevation (masl) Jan 478.78 Feb 475.13 Mar 472.39 Apr 469.78 May 467.09 Jun 467.00 Jul 467.00 Aug 467.00 Sep 471.67 Oct 481.00 Nov 481.00 Dec 481.00

Table 6-4. Roseries Dam Target Elevation

An additional rule is placed on Roseries Dam to increase outflows based on any shortages to the water users upstream of the Sennar Dam. Although this rule is essentially never effective given the small demands of this diversion location relative to outflows from the reservoir, it was included for future multi-objective uses and potential growth in agriculture in this region.

The MonthlySpillCalc method in RiverWare was used to calculate spillway releases. This method divides the assigned outflow between turbine releases, regulated spills, and unregulated spills using a maximum controlled release. This method is appropriate for monthly time step models when detailed spillway operations are not considered accurate. Turbine characteristics were obtained from information provided by ENTRO and the plantPowerCalc method in RiverWare was used to determine power generation given the relationship between operating head and power coefficient. The relationship between operating head and maximum turbine capacity for Roseries was also obtained from the information provided by ENTRO.

6.1.3.3 Sennar Dam Operations Operational rules for Roseries Dam are also based on descriptions provided by ENTRO and NEC 2003. Similar to Roseries Dam, a primary operational objective of this reservoir is to achieve drawdown and refill elevations on specified dates. In addition, the Gezira Managil diversion takes water directly from the reservoir for agriculture purposes. The minimum diversion elevation of the Gezira Managil diversion is 417.0 masl and therefore demands can be met when the pool elevation is greater than this level. All water in the reservoir above this elevation is considered available for diversion. After this objective is met, the reservoir operates to meet the monthly target elevations shown below.

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Month Target Elevation (masl) Jan 421.70 Feb 421.70 Mar 421.70 Apr 421.70 May 417.00 Jun 417.00 Jul 417.00 Aug 417.00 Sep 418.65 Oct 421.70 Nov 421.70 Dec 421.70

Table 6-5. Sennar Dam Target Elevation

An additional rule is placed on Sennar Dam to increase outflows based on any shortages to the water users downstream of the Sennar Dam. Although this rule is rarely necessary given the small demands of this diversion location relative to target-driven outflows from the reservoir, it was included for future multi-objective uses and potential growth in agriculture in this region.

Similar to Roseries, the MonthlySpillCalc method in RiverWare was used to calculate spillway releases and the plantPowerCalc method was used to determine power generation. The power coefficients and the maximum turbine releases were provided by ENTRO.

6.1.4 Stream Gage Data A complete set of stream gage data was available at Kessie, El Diem and at the Khartoum Soba gage sites. Historical release data from any of the reservoirs on the Blue Nile is inadequate for calibration purposes.

6.1.5 Blue Nile Environmental Requirements An additional augmentation check is available on the release from each of the reservoirs to meet downstream environmental requirements. These demands are specified in the Power Toolkit and are uniform for the entire Blue Nile.

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Environmental Month Demand (cms) Jan 64.40 Feb 64.40 Mar 64.40 Apr 64.40 May 64.40 Jun 64.40 Jul 128.80 Aug 643.80 Sep 193.20 Oct 128.80 Nov 64.40 Dec 64.40

Table 6-6. Environmental Demands in the Blue Nile

6.2 Baro-Akobo-Sobat The Baro-Akobo-Sobat sub-basin is a complex network of streams originating in the Ethiopian Highlands and draining into the White Nile above Malakal. The only existing hydraulic structures in the river system are the Alwero/Abobo dam, constructed 20 years ago, and the SOR hydropower Plant (5 MW). Several potential reservoir sites exist in the sub-basin. Complete hydrologic data for the period of 1956 to 1990 exists only in isolated stream gages on the Baro at Gambella and the Sobat at Hillel Doleib. The tributaries of the Baro River are described with several time series of headwater data obtained through ENTRO which was developed through the WP II, Stage II described earlier but the Pibor is only defined near the outlet into the Sobat.

The gage on the Sobat at Hillel Doleib provides a calibration point immediately before the confluence with the While Nile. A complicating factor in the Baro-Akobo-Sobat sub-basin is the spills that occur to the Machar Marshes after the Adura River bifurcation during times of high runoff. This water spilled to the marsh is typically removed from the system due to evapotransiration, but some outflow from the marsh can also return to the White Nile below the Malakal Gage and also to the Sobat.

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Figure 6-2. Model Schematic of the Baro-Akobo-Sobat Sub-Basin

6.2.1 Hydrologic Inflows The hydrologic inflows for the Baro-Akobo-Sobat were extracted from a spreadsheet provided by ENTRO. Data in this spreadsheet is a combination of gaged flows found in the Nile Encyclopedia and headwater inflows extracted from the ongoing WP II Stage II Model under development at NBI. The headwater inflows for the tributaries of the Giba, Sore, Birbir, Gumero, Gengi and Baro Rivers were synthesized using a simplified rainfall-runoff model called NAM.

6.2.2 Demands No historical quantified consumptive use data was identified in the Baro-Akobo-Sobat sub-basin and therefore are not included in the current models.

6.2.3 Reservoir Data The only existing dam structure is the Abobo Dam in the Alwero tributary that contributes to the Pibor River. Since there is insufficient data describing the headwaters of the Pibor River, the model does not include this structure in the calibration model or baseline models. Inflows from Pibor are assumed near the confluence with the Sobat.

6.2.4 Stream Gage Data Three principal stream gages are used for calibration of the model. The gage on the Baro at Gambella measures the runoff from several tributaries including the Gumero, Birbir, Sore, Sese, Geba and the Baro and the gage at the mouth of the Baro measures the total contribution of the Baro to the Sobat after various losses have taken place. The gage on the Sobat at Hillet Doleib records flows immediately before the river flows into the White Nile.

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6.3 Tekeze-Setit-Atbara The Tekeze-Setit-Atbara sub-basin is the last significant tributary to the Nile River. This tributary has the highest seasonal variation of the entire basin and had the least amount of data available describing its characteristics. The Atbara River originates just north of Lake Tana. The primary tributary to the Atbara River is the Tekeze/Setit, which forms part of the border between Eritrea and Ethiopia and originates in the high mountains of northern Ethiopia. The principal reservoirs in the sub-basin are the Khashm El Girba Dam just downstream of the confluence of the rivers and the Tekeze Dam on the Tekeze River. The Tekeze Reservoir was not constructed until after the modeled calibration period, therefore is not included in the calibration model but is included in the baseline and scenario models. The primary consumptive use is a direct diversion from the Khashm El Girba Dam.

Figure 6-3. Model Schematic of the Tekeze-Setit-Atbara Sub-Basin

6.3.1 Hydrologic Inflows A continuous historical flow record during the modeled historical period of 1956-1990 exists for the Atbara River upstream of the confluence with the Nile River and allows a point of comparison for calibration. Flow records for upstream reaches and tributaries are unfortunately limited, therefore this study utilized hydrologic inflows developed through previous modeling efforts. The initial WP II Stage I model used to develop the other tributaries was considered as a data source, but deemed inadequate for the purposes of the RiverWare model. Two hydrologic inflow locations were included in this model and labeled Tekeze Catchment and Atbara Inflow. It was observed that flows in the Tekeze Catchment were non-existent and hence the Tekeze Dam was ineffectively modeled in the WP II Stage I Model. Furthermore it appeared that that the inflows from the Atbara were reconstructed to simply meet the historical flows at the gage at kilometer three, hence included the flows from both the Atbara and the Tekeze tributaries. Since neither of these inflows from the WP II Stage I model could be considered reliable, flows in the Tekeze tributary and from the Atbara Wad were obtained from ENTRO staff using the ongoing implementation of WP II Stage II model.

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6.3.2 Demands Data from the Kashim El Girba Demand location were extracted from the WP II Stage I model. These demands were simple repeating patterns and no data on historical inter-annual variability was available.

Khashm El Gibra Month Demand (cms) Jan 42.24 Feb 39.78 Mar 27.43 Apr 16.89 May 19.44 Jun 40.83 Jul 45.56 Aug 51.35 Sep 51.82 Oct 55.41 Nov 46.73 Dec 45.23

Table 6-7. Demands on the Tekeze-Setit-Atbara

6.3.3 Reservoir Data Reservoirs on the Tekeze-Setit-Atbara include of Khashm El Girba Reservoir and Tekeze Reservoir. Although data describing these reservoirs were compiled from a variety of sources including the WP II Stage I model, information provided by ENTRO and the Power Toolkit, significant uncertainty on the operation of these reservoirs remains.

6.3.3.1 Khashm El Girba Operations Physical characteristics of Khashm El Girba Reservoir were extracted obtained through ENTRO, including elevation-storage-surface area curves, reservoir evaporation rates, and turbine characteristics. Operations were assumed to primarily meet the the Khashm El Girba demands and then to achieve the target elevations provided by ENTRO, adjusted to limit the drawdown as specified in the NEC 2003 report.

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Month Target Elevation (masl) Jan 474.00 Feb 474.00 Mar 474.00 Apr 474.00 May 474.00 Jun 463.50 Jul 463.50 Aug 463.50 Sep 474.00 Oct 474.00 Nov 474.00 Dec 474.00

Table 6-8. Khashm El Girba Dam Target Elevation

The MonthlySpillCalc method in RiverWare was used to calculate spillway releases. As described in the Roseries Dam section above, this method divides the assigned outflow between turbine releases, regulated spills, and unregulated spills using a maximum controlled release. The plantPowerCalc method was used to determine power generation using the relationship between operating head, maximum turbine flows and power coefficient. The power coefficients were obtained from the Power Toolkit and the maximum flow was obtained ENTRO.

Power is generated through a low head turbine as water is released to the Khashm El Girba Demand directly from the reservoir. This is modeled in RiverWare as an in-line power plant with a linear turbine release-power relationship ramping up to the maximum discharge of 116 cms and a flow power capacity of 7.6 MW.

6.3.3.2 Tekeze Dam Operations Physical Characteristics describing the elevation-storage-surface area relationships and reservoir evaporation rates for the Tekeze dam were obtained through the WP II Stage I model. Turbine characteristics of target and maximum power generation were extracted from the Power Toolkit provided by ENTRO. No operational guidelines could be located, therefore a method was developed to operate this reservoir to primarily meet a target power generation of 112 MW, with a maximum power capacity of 300 MW. To accomplish this operation, a rule was written that specifies a turbine release to meet the power generation objective, followed by a flood control rule that spills any water in excess of a specified elevation. A maximum pool elevation of 1140 masl and a minimum operation level of 1096 masl was used as the range over which power could be generated. The RiverWare spill method of regulatedSpillCalc was selected to allow rules to explicitly assign the turbine release and the spill volumes to maintain the maximum pool elevation. A RiverWare method of plantPowerEquation was selected to calculate the power given a plant efficiency of 95%.

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6.3.4 Stream Gage Data Stream gage data for the Tekeze-Setit-Atbara sub-basin exists for the Atbara at Kilometer 3. This provides a continuous record for calibration of the historical upstream conditions and assumptions. Records of outflows from of Khashm El Girba dam exist, but were considered too incomplete to be used for calibration purposes.

6.3.5 Tekeze-Setit-Atbara Environmental Requirements An additional augmentation check is available on the release from each of the reservoirs to meet downstream environmental requirements. These demands are specified in the Power Toolkit and are uniform for both the Tekeze and the Khashm El Girba reservoirs.

Environmental Month Demand (cms) Jan 2.47 Feb 1.59 Mar 2.43 Apr 3.72 May 3.57 Jun 9.07 Jul 22.77 Aug 22.77 Sep 22.77 Oct 20.30 Nov 8.58 Dec 4.74

Table 6-9. Environmental Demands in the Tekeze-Setit-Atbara

6.4 White Nile from Malakal to Khartoum The White Nile at Malakal represents the upstream boundary of the modeled region. This gage represents the combined flows from the Sobat and the outflows from the Sudd marshes. The lower extent of this reach is at the confluence with the Blue Nile at Khartoum. The Jebel Aulia Dam is the only dam in this reach along with two diversion locations.

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Figure 6-4. Model Schematic of the White Nile

6.4.1 Hydrologic Inflows Hydrologic inflows to this reach are strictly from catchment areas entering the reach. The gage at Malakal combines the outflows from the Sobat with the outflows from the Sudd. The historical outflows from the Sudd are ungaged, but can be back-calculated by subtracting the flows on the Sobat at Hillel Doleib from the flows at Malakal. For the purposes of calibration, this provides a reconciled flow at Malakal. Additional inflows from the Machar Marshes are possible downstream of the Malakal gage, however the magnitudes of these flows are historically insignificant and not deemed reliable for any planning purposes. These return flows are considered zeros in the current model, but links have been maintained so they can be easily enhanced for future studies. No intervening inflows are assumed on

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Eastern Nile RiverWare Planning Model – Final Report the remainder of the While Nile before reaching the confluence with the Blue Nile, however losses due to evaporation losses and seepage are accounted for upstream of the Mogren Gage. The values assigned to these losses are discussed further in the calibration section of this report.

6.4.2 Demands Two demand locations are included on the While Nile between Malakal and Khartoum. Diversions upstream of Jebel Aulia and diversions directly from Jebel Aulia are quantified as average monthly demands.

u/s of Jebel Jebel Aulia Month Aulia (cms) Demand (cms) Jan 9.05 20.91 Feb 9.83 24.72 Mar 10.73 28.00 Apr 12.01 31.25 May 12.04 32.99 Jun 12.27 35.58 Jul 9.30 69.22 Aug 6.74 71.91 Sep 10.41 135.65 Oct 10.50 155.89 Nov 10.15 135.35 Dec 8.75 36.99

Table 6-10. Demands on the White Nile Between Malakal and Khartoum

6.4.3 Reservoir Data The physical characteristics of the elevation-storage-surface area for the Jebel Aulia Reservoir were obtained from WPII Stage I model and the evaporation coefficients were obtained data provided by ENTRO. The operation of the reservoir was understood through the NEC 2003 study and target elevations were developed to reflect the basic logic.

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Month Target Elevation (masl) Jan 377.40 Feb 377.40 Mar 376.87 Apr 375.43 May 373.94 Jun 372.50 Jul 376.50 Aug 376.50 Sep 377.40 Oct 377.40 Nov 377.40 Dec 377.40

Table 6-11. Jebel Aulia Dam Target Elevation

The NEC 2003 study described how the management of the Jebel Aulia Dam depends on the timing of the peak flood on the Blue Nile. The filling of the reservoir starts at the beginning of July and continues to 376.5 masl at the end of the month. It is then held constant for one month until the peak flood of the Blue Nile has passed. In a monthly time step model, the only real effect of this policy is the target elevation at the end of the month of September. A rule was incorporated to evaluate if the peak flow at the Khartoum Soba gage has passed, and if so, set the outflows from the Jebel Aulia dam immediately to meet the refill volume. If the peak flow at the beginning of September has not passed, then set the September target to the half-way point with the goal of achieving the refill volume by the end of October.

6.4.4 Stream Gage Data Historical stream gage records exist for three locations on the While Nile. The Flows at Malakal, flows at the Melut Gage upstream of Jebel Aulia, and flows the Mogren Gage downstream of Jebel Aulia. As described above, the flows at Malakal are used to determine the presumed outflows from the Sudd. Although both the Melut and the Mogren gages can be used as calibration locations due to the robust flow record, it is important to note that the Melut Gage is potentially affected by the elevation of the Jebel Aulia Reservoir and the Mogren gage is reported to be affected by backwater effects of the flood inflows of the Blue Nile (Hydrology of the Nile) and thus affects calibration results.

6.5 Main Nile The Main Nile is considered to be the reach below the confluence of the White and Blue Nile to the Delta and outflow the Mediterranean Sea. The Atbara joins the Nile in this reach and passes through the High Aswan Dam near the Sudan-Egypt border. The recently constructed Merowe Dam and constructed upstream of the High Aswan dam and is therefore included in the Baseline and Scenario models, but not

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Figure 6-5. Model Schematic Main Nile

6.5.1 Hydrologic Inflows Hydrologic inflows into the Main Nile are from three reaches described earlier including the Blue Nile, White Nile and the Tekeze -Setit- Atbara sub-basins. No local inflows are assumed in arid regions and two loss locations are represented in the reach.

6.5.2 Demands Five demand locations are modeled in on the Main Nile that represent aggregate consumptive uses along this reach. Average monthly demands were used from the WPII Stage I model for four of the demand locations. The values for the depletions downstream of El Akhsas were not included in the WPII Stage I model, however a placeholder was maintained in the RiverWare model if this data becomes available. Since the demands in this location have no effect on reservoir operations, this was considered acceptable for the current model development and analysis.

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Hassanab-Dongola Tamaniat-Hassanab Demand u/s of El Akhsas Month Demand (cms) (cms) (cms)

Jan 18.85 28.21 104.41 Feb 12.85 19.33 583.21 Mar 5.34 8.10 531.34 Apr 4.63 6.94 538.84 May 7.17 10.75 745.41 Jun 14.81 22.21 983.59 Jul 13.44 20.15 844.91 Aug 10.75 16.08 713.17 Sep 20.37 30.54 490.38 Oct 25.08 37.61 433.54 Nov 25.92 38.87 436.30 Dec 23.26 34.93 305.84

Table 6-12. Demands on the Main Nile

An additional demand location for the Toshka project is modeled immediately below the High Aswan Dam. The volume of this diversion is a function of the pool elevation in Lake Nasser/Lake Nubia, and therefore could be modeled using an unregulated spillway. The value of the flow resulting from this unregulated spillway is then set as the depletion from the reach immediately below the dam.

Pool Elevation Toshka Diversion (masl) (cms) 178.0 0.0 178.5 6.0 179.0 19.0 179.5 37.3 180.0 60.3 180.5 87.5 181.0 118.6 181.5 153.3 182.0 191.5 182.5 233.0 183.0 277.8 183.5 325.6 184.0 376.4

Table 6-13. Elevation-Based Diversion to the Toshka Project

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6.5.3 Reservoir Data The High Aswan Dam is included in the Main Nile reach in the Calibration, Baseline, and Scenario models and the Merowe Dam is included in the Baseline and Scenario models. The physical characteristics and operation of the High Aswan dam are well described in numerous data sources while the Merowe Dam is currently under construction and limited information was identified that describe its future operations. Data provided by ENTRO was the principle source used to describe both reservoirs.

6.5.3.1 Merowe Dam Operations The Merowe Dam is recently constructed and is currently filling, therefore it is not included in the historical calibration model but is included in the baseline and scenario models. Data describing the elevation-volume-surface area was acquired through ENTRO while the power generation characteristics were obtained from the public web-site of the Sudanese government. http://www.merowedam.gov.sd/en/index.php .

Operational criteria of the Merowe Dam was not identified and therefore assumed to be operated to meet the primary objective of hydropower generation. A method was developed to operate this reservoir to primarily meet a target power generation of 625 MW, with a maximum power capacity of 1250 MW. To accomplish this operation, a rule was written that specifies a turbine release to meet the power generation objective, followed by a flood control rule that spills any water in excess of a specified elevation. A maximum pool elevation of 300 masl and a minimum operation level of 284.90 masl was used as the range over which power could be generated. The RiverWare spill method of regulatedSpillCalc was selected to allow rules to explicitly assign the turbine release and the spill volumes to maintain the maximum pool elevation. A RiverWare method of plantPowerEquation was selected to calculate the power given a plant efficiency of 95%.

6.5.3.2 High Aswan Dam Operations The physical characteristics for the High Aswan Dam and Lake Nasser/Lake Nubia were extracted from information provided by ENTRO. This information contains descriptions of the turbine characteristics including explicit relationships between operating head, turbine releases and power generation. This level of detail allowed the plantEfficiencyCurve method in RiverWare to be applied to calculate the power generation. The spillway characteristics were modeled using the regPlusUnregSpillCalc method to allow the Toshka diversions to be calculated as described above.

The presumed operation of High Aswan is described by logic provided by ENTRO. Inflows to the reservoir are evaluated and an inflow state is assigned based on a specified range.

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Inflow Flow Range Flow Range State (Millard m3/Month) (cms) Above 1 11.50 4364.00 11.50 4364.00 2 9.80 3718.88 9.80 3718.88 3 7.80 2959.93 7.80 2959.93 4 6.00 2276.87 6.00 2276.87 5 0.00 0.00

Table 6-14. High Aswan Inflow States

In addition to the inflow ranges, current reservoir pool elevations are identified and categorized into four elevation zones including an Upper Conservation Storage Zone, Lower Conservation Storage Zone, Buffer Storage Zone and Inactive Storage. Elevations above 178 masl include Toshka releases.

Elevtion 184

Toshka 3/5 Q = 19 h −178 Releases Toshka [ ] Dec

Elevtion 178 Upper Rule Curve Based Upper Conservation Storage on Inflows Elevtion 170

Lower Rule Curve Based on Low Conservation Storage Inflows

Elevtion 150 Minimum Rule Curve Buffer Storage Based on Inflows Elevtion 146 0.0 Inactive Storage Qinactive =

Figure 6-6. High Aswan Dam Operation Zones

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Releases from High Aswan are then determined as a function of both the pool elevation and the inflow state of the reservoir. A table of releases for Aswan is included in Appendix B.

6.5.4 Stream Gage Data Four stream gage locations were identified on the Main Nile and used in the model development for calibration purposes. The Tamaniat Gage represents the flow at the upstream end of the Main Nile, the Dongola Gage below the Merowe Dam site, the outflows below the High Aswan Dam, and the El Akhsas Gage in Egypt.

7 Model Calibration 7.1 Blue Nile Calibration The objective of the calibration simulation is to identify and validate the physical losses in the system. The calibration solution of the Blue Nile utilizes available data to replicate historical conditions and validate the simulation. Historical elevation data was available for Roseries and Sennar Reservoirs, but direct outflow data was not available. For these cases, reservoir elevations were used to estimate the operations of the dams, but independent validation of the operation was not possible. Historical data for Lake Tana was not available and must be inferred from downstream gages. The ramification of this assumption (using operational rules in place of historical data) is that the model cannot be calibrated properly for the reach containing the reservoir in question (i.e. there are too many unknown parameters). In order to properly calibrate a river reach containing a reservoir, historical reservoir data of both outflows and elevations must be known.

The mass balance around Lake Tana was calculated using hydrologic inflows for Lake Tana (Gilg Abay, Megech, Ribb, Gumara, and Tana Ungaged Inflow), the known flows at the Kessie Gage, and the incremental flows between the outflow to Lake Tana and Kessie. This allowed the model to solve storages at Lake Tana, and use the Kessie Gage as inflows into the lower system.

Figure 7-1. Model Schematic of the Upper Blue Nile

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The known outflow from Kessie Gage was combined with the incremental main stem flows and the Didessa, Dabus and Beles tributaries to simulate the flows at the El Diem Gage.

Figure 7-2. Model Schematic of the Middle Blue Nile

Downstream of the El Diem Gage, the calibration model simulates the historical operation of two existing reservoirs, Roseries and Sennar, followed by a gage at Khartoum and Soba before merging with the White Nile.

Figure 7-3. Time Series Calibration of the Blue Nile at El Diem Gage

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Figure 7-4. Modeled vs. Historical Calibration of the Blue Nile at El Diem

Figure 7-5. Model Schematic of the Lower Blue Nile

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The flows at El Diem are considered equivalent to the inflows at Roseries Dam, which became operational in 1967. Prior to the assumed operational start date of 1967, the outflow is assumed to be equal to the inflow in the calibration model. After this date, historical pool elevations are known and were used as inputs to the calibration model. Using modeled inflows and historical pool elevations, the outflows of Roseries could be directly simulated without needing to assume a particular historical reservoir operation. Unexplained anomalies exist in the initial few years of historical elevation data; however the model was configured to adhere to the elevation-volume curve provided by ENTRO.

Figure 7-6.Time Series Calibration of the Blue Nile for Roseries Dam Elevation

Modeled outflows from Roseries are depleted by downstream users and become the modeled inflow to the Sennar Reservoir. Similar to Roseries, historical outflows from Sennar Dam are not known, but historical pool elevations are known. Utilizing this elevation data and assumed depletions from Gezira Managil allows modeled outflows from Sennar to be calculated by the RiverWare model without reconstucting historical reservoir operation logic. Unexplained anomalies exist in the historical elevation data that appear to have the pool elevation fall below the minimum elevation according to the elevation-volume curve provided by ENTRO. The model was configured to limit the minimum elevation to this provided curve.

Outflows from Sennar dam are further depleted by water users downstream and arrive at the gage at Khartoum and Soba. This modeled flow is then compared to the historical gage flow. Losses in the Blue

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Nile are simulated with a reach labeled Blue Nile Losses before the gage at Khartoum and Soba and parameters are adjusted to match the flows at the gage. The interpolated gain-loss method in RiverWare was applied to this reach. This method allows losses to be applied as a function of the time of the year and the flow in the reach. A range of 7% loss to 12% loss resulted in the best match between the modeled flows and the historical data. Given the lack of historical demand data in the entire Blue Nile, the results were deemed acceptable.

Figure 7-7. Time Series Calibration of the Blue Nile Khartoum and Soba Gage

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Figure 7-8. Modeled vs. Historical Calibration of the Blue Nile Khartoum and Soba Gage

7.2 Baro-Akobo-Sobat Calibration Hydrologic inflows were obtained for several locations in the Baro Sub-basin and in the mouth of the Pibor. Flows from the Geba, Sese, Sore, Birbir, Gumero and Baro headwaters combine upstream of the gage at Gambella. Several ungaged tributaries also exist in this region, therefore incorporating incremental flows was necessary. Incremental flows from the Baro-Birbir confluence to the Tams was included in the dataset extracted from data provided by ENTRO and incorporated into the model.

Remaining incremental inflows were estimated through comparing the Baro at Gambella gage with the cumulative known inflows up to that location. An additional hydrologic inflow location was added upstream of the Baro at Gambella gage that adjusted for flow discrepancies. A significant majority of the discrepancies indicated there were missing flows from the synthetically generated headwaters, although various cases existed during the 1960’s when the sum of the synthetically generated headwater tributaries exceeded the flows at the Baro at Gambella. Improving the hydrologic inflows is an area for improvement and the model is designed to readily accept them as they become available.

The flows between the gage on the Baro at Gambella and the Baro at the mouth to the Sobat are known to have substantial losses resulting from overflows to the Adura River and Machar Marshes.

Before reaching the confluence with the Pibor, the Baro River bifurcates during high flows and pours into the Adura River which returns through the Pibor/Akobo River. The overflow flow to this bifurcation

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Figure 7-9. Model Representation of the Lower Baro and Sobat Reaches

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Figure 7-10. Baro at Gambella and Adura Flows (1947-1956)

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Figure 7-11. Relationship between Baro River Flows at Gambella and Adura Flows.

A second substantial loss is known to occur through overflows to the Machar Marshes during periods of high flows. Calculating actual losses to the Machar Marshes is a complex hydrologic process, however The Hydrology of the Nile (Sutcliffe and Parks) suggests that flows above 1.5 km3/month are lost between Gambella and the mouth of the Baro. This study found that using 1.6 km3/month resulted in a slightly improved result and a rule is incorporated in RiverWare to reflect this simplified assumption.

Flows in the Sobat are attenuated substantially before reaching the confluence with the White Nile. Comparing the average monthly flows on the Baro at Gambella to the Sobat at Hillet Doleib, the peak is attenuated one to two months.

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Figure 7-12. Attenuation of Flows in the Sobat

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This attenuation is modeled explicitly by incorporating a reach in the RiverWare model called Sobat Lag Reach . An impulse response routing method was incorporated and lag coefficients were calibrated to allow the peak to align with the historical flows at Hillel Doleib.

Figure 7-13. Time Series Calibration of the Sobat River at Hillel Doleib

Figure 7-14. Modeled vs. Historical Calibration of the Sobat River at Hillel Doleib

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7.3 Tekeze-Setit-Atbara Calibration The calibration solution for the Tekeze-Setit-Atbara sub-basin progresses from upstream to downstream, does not include the Tekeze Reservoir because it was not completed during the historical calibration period, and assumes a perscribed operation for the Khashm El Girba reservoir after its operational start date in 1963. Prior to 1963, the outflow is assumed to be equal to the inflow. After 1963, the reservoir is assumed to operate to meet the demand objectives of the Khashm El Girba demand and operate based on monthly target elevations provided by ENTRO, but modified to limit drawdown to 463.5m and raise to the maximum elevation to 474m based on the National Electricity Corporation Report for Sudan (NEC 2003).

Alignment of the modeled flows at Atbara at Kilometer 3 and the historical flows proved to be a challenge and an area for future improvement. The synthetically generated hydrologic inflows provided by ENTRO for the Atbara and the Tekeze tributaries generally produced significantly larger volumes of water than the historical gage record. To adjust for some of this difference, two gain-loss reaches were implemented into the model. One was placed on the Setit/Tekeze uptream of the confluence with the Atbara while another was upstream above the gage site at Kilometer 3. A RiverWare method of interpolated gain-loss was applied to both reaches that allows the greatest flexibility of modeling losses as a function of both month and flows in the reach. A 30% loss was implemented on the Setit/Tekeze loss reach and a 20% loss was implemented on the reach above the gage at Kilometer 3. No distinct pattern could be identified through the calibration and this general scaling method was the only reasonable approach.

Figure 7-15. Time Series Calibration of the Atbara River at Kilometer 3

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Figure 7-16. Modeled vs. Historical Calibration at the Atbara at Kilometer 3

Given the synthetically generated hydrologic inflows, the lack of historical demand data in the Tekeze- Setit-Atbara sub-basin, and the lack of any alternative, the results were considered acceptable. If improved hydrologic or demand data is generated, the model is configured to readily incorporate it.

7.4 White Nile from Malakal to Khartoum Calibration The calibration of the White Nile begins with the assumption that, at the upstream end of the reach, the Malakal Gage is accurate. Inflows from the Sudd are dynamically assigned based on the difference between the flows at Makakal and the flows on the Sobat at Hillel Doleib. This allows the calibration to focus on evaluating the physical properties of the reach below this location. In the baseline and scenario models however, the inflows from the Sudd are not dynamic but are considered fixed values calculated as the differences between the actual historical flows at Makakal and Sobat as Hillel Doleib gages. When both sets were not available for such a calculation, the modeled differences from the calibration run were applied as fixed inflows. No flows are assumed to return from the Marchar Marshes due to the small volumes and infrequent historical events in which this is recorded.

The first location for calibration on the White Nile is the Melut Gage. A comparison of modeled and historical flows indicates the reach between Makalal and Melut is represented well by the model.

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Figure 7-17. Time Series Calibration on the White Nile at Melut

Figure 7-18. Modeled vs. Historical Calibration on the White Nile at Melut

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Data available for Jebel Aulia appeared to be plentiful, but through the calibration process was identified to be inconsistent. A limited amount of historical pool elevation data was obtained from the Nile Encyclopedia covering the years from 1965-1962, 1973-1978, and 1983-1987. A second set of data labeled White Nile downstream of Jebel Aulia Dam was obtained from ENTRO staff that was extracted from the Monthly Blue Nile Dataset described earlier.

Calibration of the Jebel Aulia Dam was done with two distinct methods, each operating the model with one set of data and comparing the model results with the other set. The first method used the limited amount of historical pool elevation data to govern the operation of the reservoir for the calibration. Average monthly elevations were determined from this data and were used as target elevations for the model. Given the inflows described with the Melut gage and these average monthly pool elevations, outflows from the reservoir could be simulated. These outflows were compared to results from the Monthly Blue Nile Dataset, generally resulting in a poor correlation.

Figure 7-19. Time Series Jebel Aulia Calibration using Historical Monthly Elevations

The second calibration method applied the reservoir outflows from the Monthly Blue Nile Dataset to the calibration model. This method then uses the inflows and the specified outflows to calculate reservoir storage values. These storage values were then plotted along with the limited historical data.

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Figure 7-20. Jebel Aulia Calibration by Average Historical Pool Elevation

The resulting modeled reservoir volumes exceeded the maximum capacity of the reservoir, indicating either the reservoir outflows from the Monthly Blue Nile Dataset were based on vales from downstream gages as opposed to actual measured flows or the physical characteristics of the reservoir were inaccurate.

Although the results of this calibration effort indicated inconsistencies in the data sources, no modifications to the the Jebel Aulia reservoir were made. The limited amount of reservoir elevation data were assumed to have the highest reliability followed by the inflows at Melut . The Jebel Aulia outflows from the Monthly Blue Nile Dataset were presumed to be the least accurate and possibly based on modeled results. Because this dubious dataset is not considered in the baseline or scenario models, it was not justified to modify the physical characteristics in the calibration, baseline or scenario models.

It was necessary to continue the calibration process of the White Nile downstream of the Jebal Aulia dam. This next step of the process begins with outflows from the Monthly Blue Nile Dataset and ends with the gage at Mogren. Modeled flows matched the observed flows at Mogren contained in the Nile Encyclopedia therefore suggesting the Monthly Blue Nile Dataset is indeed accurate or perhaps developed directly from the gaged data at Mogren.

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Figure 7-21. Time Series Calibration of the White Nile at Mogren

Figure 7-22. Modeled vs. Historical Calibration of the White Nile at Mogren

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7.5 Main Nile Calibration The calibration of the Main Nile extends from the confluence of the White Nile and the Blue Nile to the operation of the High Aswan Dam. The calibration of this section was accomplished by isolating this reach and using the historical gaged inflows at on the Nile at Tamaniat and at the Atbara at Kilometer 3 as inputs. Two gain-loss reaches were prepared in this reach above and below the confluence with the Atbara. The gain-loss reach above the Atbara was assigned a 1.6% loss of the total flow according to the Hydrology of the Nile (Sutcliffe and Parks, 1999) which was supported by the finding of this the calibration. The gain-loss reach below the Atbara confluence was not used, but was kept in the model for potential future uses. The Merowe Dam did not exist during the period of record used for the calibration and therefore is not active in the calibration model.

Flows in the reach are diverted at two aggregate locations of Tamaniat-Hassanab Demand and Hassanab-Dongola Demand before passing the Dongola Gage. This gage provides an intermediate calibration point in the river.

Figure 7-23. Time Series Calibration of the Main Nile at Dongola

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Figure 7-24. Modeled vs. Historical Calibration of the Main Nile at Dongola

Flows through the Dongola Gage become the inflows to Lake Nassar. Data exists for flows below the High Aswan Dam and are therefore used to simulate the operation of the reservoir in the calibration model. Monthly evaporation rates were the primary calibration parameters that adjusted to match historical conditions. The RiverWare simulations of Lake Nasser/Lake Nubia captured the filling period and seasonal variability well.

Evaporation Rate (cm/month) January 21.1 February 3.1 March 15.5 April 22.3 May 18.0 June 21.7 July 34.1 August 36.6 September 25.4 October 22.9 November 21.7 December 19.8

Figure 7-25. Lake Nassar Evaporation Rates

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Figure 7-26. Time Series Calibration of the Pool Elevations of Lake Nassar

Below Lake Nasser/Lake Nubia flows are diverted through several locations in Egypt. Aggregate diversion locations are included in the model to represent these abstractions, however the complexity of the system is not represented. Calibration at the El Akhsas gage is shown in the figures below.

Figure 7-27. Time Series Calibration of the Main Nile at El Akhsas

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Figure 7-28. Modeled vs. Historical Calibration of the Main Nile at El Akhsas

7.6 Calibration Summary In addition to the descriptions provided above, a summary of evaporation rates is provided in Figure 7-29.

Khashm Jebel High Lake Tana Roseries Sennar Tekeze El Girba Aulia Merowe Aswan January 13.40 17.98 17.98 13.40 17.36 18.91 19.70 21.08 February 14.39 18.48 18.48 14.39 20.44 23.52 22.20 3.10 March 9.90 22.66 22.66 9.90 24.18 23.25 29.50 15.50 April 7.96 22.11 22.11 7.96 24.80 22.20 33.10 22.32 May 7.90 18.91 18.91 7.90 25.78 22.94 36.50 17.98 June 0.21 6.27 6.27 0.21 23.80 22.50 34.00 21.70 July -15.40 -2.79 -2.79 -15.40 12.58 11.78 31.40 34.10 August -18.30 -2.60 -2.60 -18.30 8.09 11.47 30.30 36.58 September -3.82 1.95 1.95 -3.82 16.20 13.50 31.70 25.42 October 11.30 12.49 12.49 11.30 18.25 15.19 30.70 22.94 November 14.67 15.69 15.69 14.67 18.80 17.40 23.10 21.70 December 14.70 16.74 16.74 14.70 18.29 17.05 19.90 19.84 *Units in cm/month

Figure 7-29. Evaporation Rates of East Nile Reservoirs

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A summary of the calibration results is presented in Figure 7-30. The model configuration generally calibrated well at all gage sites, with the exception of the Atbara at Kilometer 3. The lack of historical hydrologic gaged data in the upstream reaches of the Atbara and Tekeze reservoirs required the use of synthetically generated inflows. The inflows used were provided by ENTRO staff and assumed to be the best available representation of reconstructed conditions. The calibration of the Jebel Aulia reservoir highlighted inconsistencies between in the three available datasets including flows at Melut, historical pool elevations and reported flows below the reservoir. These differences were attributed to likely differences in data collection methods or physical characteristics of the reservoir during flooding conditions, but were not clearly discernible in this study and remain an area of potential improvement if more data or detail becomes available.

Calibration Location R2 Value Blue Nile El Diem Gage 0.99 Khartoum and Soba Gage 0.96 Baro-Akobo-Sobat Sobat at Hillel Dolieb 0.85 Tekeze-Setit-Atbara Atbara at Kilo 3 0.67 White Nile Melut 0.94 Mogren 0.92 Main Nile Dongola 0.95 El Akhsas 0.90

Figure 7-30. Calibration Summary

8 Baseline Model The second phase of the RiverWare model development was to adapt the modeling framework and rule set into a baseline model. The purpose of the baseline model is to represent existing conditions in the basin including current major infrastructure and depletion schedules and best known management practices. Inputs to the baseline model were repeating demand patterns and historical hydrology identical to those used in the calibration model. The primary difference between the calibration model and the baseline model is the mechanism by which some of the reservoirs operate. All dams and reservoirs are assumed to operate with operational rules based on logic as opposed to using historical data for pool elevations or outflows.

8.1 General Model Design The physical layout of the baseline model is identical to the calibration model previously described. Three pieces of infrastructure were included and enabled that were not active during the historical

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Although the hydrology used in the baseline model is derived from measured or reconstructed flows during the calibration period, the focus of the baseline model is to assess future conditions. Therefore the model time range was shifted from 1956 through 1990 to 2018 through 2052, thus still using the same 35 year historical record. Although the selected simulation period is not critical for numerical modeling purposes when the same input data is used, this shift has three distinct goals including:

1. Output presentation of a future time range facilitates the understanding of the modeling results by stakeholders 2. Reduction of potential critical modeling errors by avoiding the mixing of historical and future demands and reservoir operations. This is particularly important in a multi-stakeholder context when many modelers are involved. 3. Allow alternative future hydrologic scenarios to be readily imported into the model such as those derived from future climate change projections, with a clear understanding that these are not representative of past conditions.

As mentioned earlier, the selected model start date of January 2018 was somewhat arbitrary, but does begin after the projected completion of infrastructure currently under construction and avoids the need to assume any particular filling criteria. All reservoirs are considered to be operational throughout the modeled period.

8.2 Blue Nile Baseline Model

8.2.1 Modeling Method The solution method for the baseline model simulation of the Blue Nile is similar in some aspects to the calibration model and different in others. Specifically the physical gains and losses identified in the calibration phase are consistent between the models, but the operations of the three reservoirs are guided by operational rules as opposed to historical data.

Lake Tana outflows are not governed by the historical flows at the Kessie Gage, but instead managed according to the elevation-release curve described in Table 6-2. This distinction allows the simulation of the reservoir to respond to the upstream hydrologic conditions as would occur in actual operations. The Tana-Beles Hydropower diversion was enabled according to the criteria described in Section 6.1.3.1. Meeting environmental objectives from Lake Tana was not enabled due to the uncertain source of these criteria and the frequent trade-off these releases had with the Tana-Beles hydropower releases.
Roseries Dam is primarily operated according to the target elevations described in Table 6-4. Additional reservoir objectives are to meet downstream demands above the Sennar Reservoir as specified in Table 6-1, and meeting environmental objectives as specified in Table 6-6.
Sennar Dam is operated to meet the demands at the Gezira Managil diversion in Table 6-1 and to meet the target elevations described in Table 6-5. Additional objectives are to meet downstream demands above the Sennar Reservoir, and meeting environmental objectives as specified in in Table 6-6.

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8.2.2 Modeling Results The following graphs demonstrate the results from the Baseline model. The primary results of interest provided here are reservoir pool elevations and power production at each hydropower generation facility. A complete suite of plots of annual energy produced at the dam sites are included in Appendix A2 and further regional energy analyses are included in Section 10.2.2 of this report.

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Figure 8-1. Lake Tana Modeled Baseline Pool Elevation

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Figure 8-2. Tana-Beles Modeled Baseline Power Generation

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Figure 8-3. Roseries Dam Modeled Pool Elevation

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Figure 8-4. Roseries Dam Modeled Power Generation

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Figure 8-5. Sennar Dam Modeled Pool Elevation

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Figure 8-6. Sennar Dam Modeled Power Generation

8.2.3 Results Discussion The results from the baseline model of the Blue Nile demonstrate the expected reservoir elevations and power generation. Both the Roseries and Sennar dams are operated with the primary objective of achieving target elevations, hence producing a regular annual pattern of pool elevations and a variable power generation as a function of hydraulic head due to variable hydrologic conditions. The one exception is on the Sennar Dam in 2046 when inflows from the sub-basin were minimal and additional releases were made in October-December to attempt to meet environmental release targets. These targets were met in all months except October 2043 when the minimum active pool elevation of 415 masl was reached.

8.3 Baro-Akobo-Sobat

8.3.1 Modeling Method The solution for the baseline model simulation of the Bara-Akobo-Sobat is identical to the simulation used for the calibration model. The simulation begins with flows from the Geba, Sese, Sore, Birbir, Gumero and Baro headwaters reaches which combine and merge with the flows from the Pibor River. Physical characteristics developed in the calibration model are included in the baseline model including incremental flows upstream of the Gage on the Baro at Gambella, logic specifying the volume of bifurcation passing from the Baro to the Adura as shown in Figure 7-11, overflows to the Machar

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Marshes in excess of 1.6 km 3/month and the lag and attenuation of flows on the Lower Sobat. Outflows from the Sobat are used as one of the headwater inflows to the While Nile above Malakal.

8.3.2 Results Discussion There are no modeled reservoirs in the Baseline model, therefore no results are described here.

8.4 Tekeze-Setit-Atbara

8.4.1 Modeling Method The solution for the Baseline simulation of the Tekeze-Setit-Atbara sub-basin uses the same hydrologic inflows and demands as the calibration model, but includes both the Tekeze Dam and the Khashm El Girba Dam.

The Tekeze Dam operates with hydropower generation as the primary objective. The turbines are operated to meet a target power of 112 MW and can generate up to 300 MW during periods of spills or spill avoidance. Meeting environmental objectives as specified in the Power Toolkit is a secondary objective.
The Khashm El Girba Dam is operated to meet the demands of the Khashm El Girba direct diversion and to meet the target elevations described in Table 6-7. Additional objectives are to meet environmental objectives as specified in Table 6-9.

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Figure 8-7. Tekeze Dam Modeled Pool Elevation

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Figure 8-8. Tekeze Dam Modeled Power Generation

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Figure 8-9. Khashm El Girba Dam Modeled Pool Elevation

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Figure 8-10. Khashm El Girba Dam Modeled Power Generation

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Figure 8-11. Khashm El Girba Diversion Power Production

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8.4.2 Results Discussion The baseline results for the reservoirs in the Tekeze-Setit-Atbara are as expected. The Tekeze Reservoir is operated to achieve a target power generation of 112 MW with the ability to reach 300 MW during flood control releases. The highly seasonality of the Tekeze River allows this increased power generation to occur frequently for one to three months. Spills frequently occur when releases are made in excess of that which can pass through the turbines.

The Khashm El Girba reservoir operates primarily to meet demands directly from the reservoir, then to meet target pool elevations. These two goals are achieved throughout the entire modeled period with the exception of 1946 when pool elevations decrease to meet environmental release requirements during the months of September through November. Normal power generation is also decreased during these months due to decreased releases from the reservoir to minimum outflow levels. Power generation through the diversion is consistent as the direct demand are always met.

8.5 White Nile from Malakal to Khartoum

8.5.1 Modeling Method The baseline solution for the While Nile combines outflows from the modeled Baro-Akobo-Sobat sub- basin and outflows from the Sudd, which are calculated as the historical difference between the gage at Malakal and the gage on the Sobat at Hillel Doleib. Gaged data on the Sobat is not available after 1983, therefore modeled data from the calibration model is substituted to complete the historic dataset, which is then transferred to the assumption of future inflows from 2018-2052.

In the baseline model, the Jebal Aulia reservoir is operated to primarily meet the direct Jebel Aulia demands and then to meet target elevations specified in Table 6-11. One caveat to this approach is an adaptive solution for the September outflows to allow the flows from the Blue Nile to pass by evaluating the rising or falling condition at the Khartoum and Soba gage as discussed in Section 6.4.3.

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Figure 8-12. Jebel Aulia Dam Modeled Pool Elevation

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Figure 8-13. Jebel Aulia Dam Modeled Power Generation

8.5.2 Results Discussion The results from the only reservoir on the While Nile, Jebel Aulia, are as expected. The reservoir is primarily driven by target pool elevations with a slight variations occurring in the months of September

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8.6 Main Nile The baseline solution for the Main Nile combines the modeled outflows from the Blue Nile and White Nile sub-basins as the headwater, and combines the modeled outflows from the Tezeze-Setit-Atbara sub-basin. Demands as shown in Table 6-12 remain constant in the baseline model. Both the Merowe and High Aswan reservoirs are actively modeled.

The Merowe Dam operates with hydropower generation as the primary objective. The turbines are operated to meet a target power of 625 MW and can generate up to 1250 MW during periods of spills or spill avoidance.
The High Aswan Dam operates according to the release objectives described in Section 6.5.3.2. These objectives evaluate the inflow state of the reservoir and the current pool elevation to select an appropriate release rate. Additional releases for diversions to the Toshka project are modeled when the reservoir exceeds an elevation of 178 masl.

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Figure 8-14.Merowe Dam Modeled Pool Elevation

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Figure 8-15. Merowe Dam Modeled Power Generation

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Figure 8-16. High Aswan Dam Modeled Pool Elevation

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Figure 8-17. High Aswan Dam Modeled Power Generation

8.6.1 Results Discussion The baseline results for the Main Nile demonstrate the operation of the system with both the Merowe and High Aswan dams in operation. The Merowe Dam is operated to achieve a hydropower production target of 625 MW with a maximum generation capacity of 1250 MW. The high flows of the Main Nile allow the target power to be frequently exceeded as the pool elevation often reaches the assumed maximum of 300 masl. The timing of the inflows to the Lake Nubia/Lake Nasser are affected by existence of the Merowe Dam, as are the volumes due to evaporation behind the Merowe Dam.

8.7 Shortages to Water Demands The baseline model assumes the repeated patterns of future depletions at each node described in earlier sections of this report. The Sennar, Khashm El Girba and Jebel Aulia dams are operated to supply direct diversions from the reservoirs. In addition, the Roseries and Sennar Dams are operated to assure demands are satisfied downstream. In the vast majority of the run, all demands are completely satisfied. The only instance that all demands are not met is due to a single month in October 2046 when the direct diversion from the Sennar Reservoir cannot be fully satisfied. This single occurrence is within the accuracy of the model to represent actual conditions, therefore the conclusion therefore is that all demands assumed in the model are essentially met under the baseline conditions.

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8.8 Summary of Reservoir Operations Reservoir are typically operated to meet multiple objectives, therefore the RiverWare model is designed in a way to include these objectives. Furthermore, the structure of the RiverWare ruleset allows each objective to be described in user-defined logic and prioritized appropriately with other objectives. Table 5-1 summarizes each of the objectives.

Meet Meet Target Elevation- Target Meet Power Meet Direct Downstream Environmental Elevations Discharge Discharge Objectives Diversions Diversions Requirements Lake Tana 1 Roseries Dam 3 1 2 Sennar Dam 4 1 2 3 Tekeze Dam 2 1 Khashm El Girba Dam 3 1 2 Jebel Aulia 2 1 Merowe Dam 1 High Aswan Dam 1

Table 8-1. Operation Summary of Baseline Reservoirs

9 Proposed Infrastructure 9.1 General Approach The third Phase of the Eastern Nile RiverWare Planning model development was to analyze alternative future management scenarios. More specifically, an objective of this phase was to explore a range of proposed infrastructure development options on the Nile and its tributaries. The object-oriented workspace configuration allows RiverWare to be easily modified to incorporate additional infrastructure, while the rule-based solution method used by the RiverWare Planning model allows the flexibility to readily develop and modify alternative operations.

9.2 Proposed Infrastructure Ten different proposed reservoir sites were incorporated into the RiverWare model, two of which have alternative construction heights. Five dam sites are on the mainstem of the Blue Nile, one is on the Didessa Tributary of the Blue Nile, two are on the Baro River in the Baro-Akoba-Sobat sub-basin and two are on the Main Nile.

Blue Nile • Karadobi Dam • Beko Abo High Dam • Beko Abo Low Dam • Mendaya Upper Dam • Mendaya Dam • Renaissance 640 Dam • Renaissance 620 Dam • Lower Didessa Dam

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Baro-Akobo-Sobat • Baro 1 Dam • Baro 2 Dam Main Nile • Sherieg • Kajbar

These locations were selected primarily by the availability of data that sufficiently describes the physical characteristics of the reservoir and power generation objectives. All reservoirs for which ENTRO provided sufficient data were incorporated into the model. Two sources of data were used to characterize the proposed reservoirs. The first was the East Nile Power Toolkit provided by ENTRO. This reservoir database within the toolkit is a spreadsheet record containing information on the elevation- volume-surface are relationships, the monthly evaporation rates, the full surface elevation (FSL), the minimum operating level (MOL), the installed capacity of the turbines and the firm power generation of the reservoirs. The second data source was a Memo titled Alternatives to the Mandaya Project - Cascading Options written for the Ethiopian Ministry of Water (Ministry of Water and Energy 2011). This second source was assumed to be more authoritative when the two sources conflicted.

9.3 Modeled Representation Each alternative reservoir was incorporated into the scenario model with the ability to turn on or off the reservoir at the user’s discretion. A reservoir control panel was incorporated into a table slot called Reservoir Control on a data object called Model Configuration .

Figure 9-1. Proposed Reservoir Control Panel

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When a value of zero is assigned to a row in the control panel, that reservoir is considered disabled in the model. If a value of one is assigned to the row, the reservoir is enabled. Each proposed reservoir was incorporated onto the workspace along the appropriate reach, but also with a bypass route that disables the reservoir in the network solution. Reservoirs that have a single possible configuration are represented on the workspace as shown in the example in Figure 9-2.

Figure 9-2. Model Schematic of the Proposed Karadobi Dam Location

Reservoirs that have multiple potential dam heights or are considered mutually exclusive alternatives were co-located on a reach with a single bypass option. If both options of mutually exclusive locations are selected in the control panel, the RiverWare model will abort with a warning that this configuration is not allowed. Reservoirs that have a two possible configuration are represented on the workspace as shown in the example in Figure 9-3.

Figure 9-3. Model Schematic of the Proposed Renaissance Dam Location

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The operation of each of the potential alternative reservoirs was assumed to primarily meet hydropower objectives. The values describing the firm power were assumed to be the target power criteria and the installed capacity was assume to be the maximum power capacity of each reservoir. Reservoirs were operated to meet target power objectives whenever possible. Any inflows resulting in a volume that exceeded the Full Surface Level (FSL) was immediately discharged through the turbines up to the flow required for the maximum power generation and the remainder was assumed to be discharged through a regulated spillway.

The operational criteria for the proposed reservoirs are outlined in Table 9-1. Additional operating criteria can be easily incorporated into the RiverWare model such as meeting increased demands or target elevations if such values are determined.

Minimum Full Surface Level Operating Level Maximum Power Target Power (masl) (masl) (MW) (MW) Blue Nile Karadobi Dam 1146 1100 1600 933 Beko Abo High Dam 1062 1010 2423 1329 Beko Abo Low Dam 910 870 935 594 Mendaya Upper Dam 770 800 1700 802 Mendaya Dam 770 800 2750 1423 Renaissance 640 Dam 640 610 5290 1745.7 Renaissance 620 Dam 620 590 4500 1485 Lower Didessa Dam 800 770 550 280 Baro-Akobo-Sobat Baro 1 Dam 1520 1485 180 93.8 Baro 2 Dam 1320 1318 500 254 Main Nile Sherieg 343 340 350 350 Kajbar 213 208 250 250

Table 9-1. Reservoir and Turbine Characteristics of Proposed Reservoirs

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Mendaya Karadobi Beko Abo Beko Abo Upper Mendaya Renaiss. Renaiss. Lower Dam High Dam Low Dam Dam Dam 640 Dam 620 Dam Didessa Baro 1 Baro 2 Sherieg Kajbar January 17.60 16.70 16.70 19.28 19.28 13.50 13.50 19.50 10.80 11.20 17.40 17.40 February 16.90 16.10 16.10 18.37 18.37 13.60 13.60 18.60 11.10 11.50 17.90 17.90 March 14.00 15.40 15.40 14.74 14.74 17.10 17.10 14.90 11.00 11.60 23.30 23.30 April 13.10 12.60 12.60 13.56 13.56 15.70 15.70 13.70 7.90 8.70 25.50 25.50 May 10.10 6.30 6.30 10.52 10.52 10.60 10.60 10.70 1.70 2.80 29.50 29.50 June -1.50 -6.50 -6.50 -2.08 -2.08 4.20 4.20 -2.00 -1.90 -0.80 29.10 29.10 July -20.00 -13.80 -13.80 -21.91 -21.91 -0.40 -0.40 -21.90 -3.70 -2.50 28.80 28.80 August -18.10 -4.60 -4.60 -15.05 -15.05 0.10 0.10 -15.00 -3.30 -2.10 28.50 28.50 September -2.80 0.80 0.80 1.72 1.72 1.40 1.40 1.80 -6.20 -4.70 27.00 27.00 October 8.20 6.60 6.60 11.76 11.76 9.10 9.10 11.90 1.30 2.40 25.10 25.10 November 12.60 11.70 11.70 14.79 14.79 11.40 11.40 14.90 6.00 6.70 19.80 19.80 December 16.10 14.50 14.50 18.01 18.01 11.50 11.50 18.20 9.40 9.80 16.70 16.70 *Units in cm/month

Figure 9-4. Evaporation Rates of Proposed Reservoirs

10 Alternative Scenario Development

The RiverWare model of the Eastern Nile is a tool designed to analyze alternative management scenarios. These scenarios can include any combination of infrastructure as proposed in Section 9 that is physically possible or any additional infrastructure that is proposed in the future. Future alternatives may also include increased consumptive losses due to expansion of agriculture or municipal demands. An additional strength of RiverWare is the ability to change reservoir operations within the model to meet a wide variety of proposed objectives. This ability allows RiverWare to be used to explore the possibility of numerous joint management practices in which multiple reservoirs are operated in a coordinated manner to meet multiple objectives. This can come in the form of sharing or balancing benefits, such as power generation, across political borders or sectors. The flexibility of the RiverWare policy language allows users to simulate essentially any proposed policy for any proposed reservoir or demand.

10.1 Representative Scenarios The scope of work indicated that at least two scenarios would be analyzed to demonstrate the application of the RiverWare modeling tool. To meet this criterion, ENTRO staff identified five alternative scenarios that use a combination of proposed reservoirs on the Blue Nile. These five alternatives are as follows:

Scenario 1. Renaissance 640 Scenario 2. Karadobi + Beko Abo Low + Mendaya + Renaissance 620 Scenario 3. Karadobi + Beko Abo Low + Mendaya Upper + Renaissance 640 Scenario 4. Beko Abo High + Mendaya + Renaissance 620 Scenario 5. Beko Abo High + Mendaya Upper + Renaissance 640

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The alternatives listed above represent a set of potential development options for the Blue Nile. Reservoirs were activated using the control panel shown in Figure 9-1 and rules operated each reservoir according to the objectives shown in Table 9-1. Results for each combination were output into time series data and included in Appendix A. To compare the significant effects of each alternative development options, suite of outputs were generated that include pool elevations, hydropower generation, reservoir spills, reservoir evaporation and demands. A comparison of the significant results is presented here. A complete set of results for each scenario were are included in Appendix A.

10.2 Model Results

10.2.1 Pool Elevations A basic evaluation parameter across the various scenarios is the impact on pool elevations of existing reservoirs. The elevations of the scenarios for Roseries and Sennar reservoirs are essentially identical to the baseline due the primary operational criteria being monthly elevation targets and therefore the results for all scenarios appear identical to Figure 8-3, Figure 8-5, and Figure 8-12. In addition, these reservoirs are minimally subject to shortages due to the high flows relative to the small storage volumes of these reservoirs. The reservoirs in the Tekeze-Setit-Atbara sub-basin are not affected by the scenarios analyzed here. The effects on elevations of the downstream reservoirs of Merowe and Aswan are not negligible and are shown below.

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Figure 10-1. Scenario Results for Merowe Pool Elevation

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Figure 10-2. Exceedance Plot for Merowe Pool Elevations

The primary operational objective assumed for the Merowe Dam is to meet hydropower demands. The flows passing through the Merowe dam will typically be sufficient to meet these target power objectives and typically allow the reservoir to operate at the Full Surface Level of 300 masl, however the variable nature of the inflows demonstrate that large spills occur at certain times and substantial drawdowns in the Baseline condition are common as shown in Figure 10-1. These drawdowns are less common in the scenario models due the proposed upstream reservoirs allowing a more continuous supply to Merowe.

The pool elevations of the High Aswan dam are affected by the upstream development options by both reductions of inflows due to evaporation losses from the proposed reservoirs and reductions in the seasonal fluctuations. As a result of the initial filling of the proposed reservoirs, inflows to Aswan are reduced. As a result, the releases from the High Aswan dam are decreased according to the assumed operational logic, which is a function of both inflows and pool elevations. The resulting pool elevation of the High Aswan Dam reflects this initial period.

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Figure 10-3. Inflows to High Aswan Dam

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Figure 10-4. Exceedance Plot of Total Inflows to High Aswan Dam

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Figure 10-5. Outflows from High Aswan Dam

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Figure 10-6. Exceedance Plot of Total Outflows from High Aswan Dam

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After a period of filling of the proposed reservoirs, the elevations return to slightly below the annual average of the baseline as a new balance is reached between reduced inflows, resulting outflows and lower evaporation losses due to the decreased surface area.

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Figure 10-7. Scenario Results for High Aswan Pool Elevation

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Figure 10-8. Exceedance Plot for High Aswan Pool Elevations

Elevations for Jebel Aulia Lake are slightly modified in the scenario models. Although all the infrastructure in the proposed scenarios are on the Blue Nile, the operation of Jebel Aulia required that the peak flows pass in the Blue Nile before completing the seasonal fill. This logic was captured in the RiverWare model and the implications of the delayed peak flow on the Blue Nile are seen in pool elevations shown in Figure 10-9. In addition to the results described here, all pool elevation results are provided in Appendix A1.

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Figure 10-9. Blue Nile Dependent Operation of Jebel Aulia Dam

10.2.2 Power/Energy Generation and Spills Hydropower Generation is a primary objective of the development of the Blue Nile sub-basin. Since each scenario invokes different reservoirs in the model, the cumulative power generation and annual energy generation across all reservoirs or any sub-set of reservoirs provides statistics that can be compared across the different scenarios. The power and energy generation is shown below by country in addition to the entire modeled system. These plots are shown with both a standard time-series and exceedance probabilities. These statistical plots inform the reader of the percentage of time a value is exceeded given the modeling assumptions. Results for the individual reservoirs are included in Appendix A2.

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Figure 10-10. Total Power Generation by Facilities in Ethiopia

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Figure 10-11. Exceedance Plot of Total Power Generated in Ethiopia

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Figure 10-12. Annual Energy Generation by Facilities in Ethiopia

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Figure 10-13. Exceedance Plot of Annual Energy Generation by Facilities in Ethiopia

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Figure 10-14. Total Power Generation by Facilities in Sudan

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Figure 10-15. Exceedance Plot of Total Power Generated in Sudan

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Figure 10-16. Annual Energy Generation by Facilities in Sudan

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Figure 10-17. Exceedance Plot of Annual Energy Generation by Facilities in Sudan

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Figure 10-18. Total Power Generation by Facilities in Egypt

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Figure 10-19.Exceedance Plot of Total Power Generated in Egypt

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Figure 10-20. Annual Energy Generation by Facilities in Egypt

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Figure 10-21. Exceedance Plot of Annual Energy Generation by Facilities in Egypt

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Figure 10-22. Total System Power Generation

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Figure 10-23. Exceedance Plot of Total System Power Generated

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Figure 10-24. Total System Annual Energy Generation

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Figure 10-25. Exceedance Plot of Total System Annual Energy Generation

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Figure 10-10 through Figure 10-13 demonstrate the obvious benefit of the analyzed scenarios for Ethiopia. Figure 10-14 through Figure 10-17 demonstrates a significant increase in power generation for the reservoirs of Sudan. This benefit is the result of maintaining a higher level of consistency in the pool elevations of the Roseries, and Merowe reservoirs by and reducing the inflows during the flooding period and hence reducing the probability of spills from the reservoirs as shown in Figure 10-26 and Figure 10-27. Effects on the power generation in Egypt are shown in Figure 10-18 to Figure 10-21.

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Figure 10-26. Percentage of Outflows Spilled from Roseries Dam

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Figure 10-27. Percentage of Outflows Spilled from Merowe Dam

10.2.3 Reservoir Evaporation The construction of new reservoirs in the Blue Nile results in two competing effects with respect to evaporation. The first effect is increased evaporation resulting from the proposed reservoirs while the other is reduced evaporation from the Lake Nubia/Nasser as a result of decreased inflows to the reservoir. These primary findings are demonstrated below as total evaporative losses upstream of Egypt (total losses in both Sudan and Ethiopia), and evaporative losses from the High Aswan Dam. Evaporation losses for individual reservoirs are provided in Appendix A4.

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Figure 10-28. Combined Annual Evaporation of Ethiopian and Sudanese Reservoirs

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Figure 10-29. Annual Evaporation for High Aswan Dam

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The average annual evaporation volume from the increased reservoir surface area in Ethiopia and Sudan is compared to the decrease in evaporation losses at Aswan.

Increase in Evaporation Decrease in Annual Net Average Change in Ethiopian and Sudan Evaporation in Egypt in Evaporation Scenario 1 1668 -233 1435 Scenario 2 1962 -311 1651 Scenario 3 2394 -339 2055 Scenario 4 1945 -309 1636 Scenario 5 2381 -329 2053 Units in MCM per Year

Figure 10-30. Average Annual Changes in Reservoir Evaporation

10.2.4 Demands The ability to meet water supply requirements was analyzed in the RiverWare model given the assumed monthly depletions described in Section 6 of this report. In the baseline model, essentially all demands were met with the exception of a one-month shortage in the Gezira-Managil diversion from the Sennar Dam. This is certainly within the accuracy limitations of the model, so it was not considered a significant finding. However in the scenario models, it was clear that the initial period of filling the reservoirs would carry the probability of shortages to water users unless otherwise managed. Each of the three represented water users on the Blue Nile indicated shortages and the cumulative effect is shown in Figure 10-31.

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Figure 10-31. Total Shortages to Water Users During the Filling Period of Scenarios

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The filling criteria used in the model did not attempt to operate the proposed reservoirs to assure these demands would be met, however this would certainly need to occur as these criteria are established, requiring a cooperative agreement between Ethiopia and Sudan.

Demands below the Aswan High Dam are met as specified in the model, however it is clear that these demands require further clarification with actual demand projections. The rules used to specify the outflows from the Aswan dam are described in Section 6.5.

10.3 Mass Balance Analysis A final analysis was performed on the results to verify the mass balance of the scenarios. A closed system was assumed around all the portions of the model affected by the alternative reservoirs included in the scenarios, therefore portions of the Blue Nile, White Nile and Main Nile were included. The mass balance approach begins with the total storage in the closed system at the beginning of the modeled period, add all inflows across the entire modeled time period, deduct all losses and outflows across the entire modeled period, and the result must be equivalent to the ending storage within the closed system.

The initial storage in the system was considered to be all the reservoirs on the Blue Nile below Lake Tana, Jebel Aulia on the White Nile and Merowe on the Main Nile. The primary inflows were assumed to be modeled inflows at the Kessie Gage below Lake Tana, the Melut Gage upstream of Jebel Aulia Dam and the Atbara Gage at Kilo 3. Additional inflows included all headwater and incremental inflows and all demands within this area were considered. Losses include evaporation to each of the reservoirs and reach losses within the closed system. The outflows are the inflows into High Aswan. The results of the mass balance are shown in

Baseline Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Mass Balance Start Storage 17,964 17,964 17,964 17,964 17,964 17,964 Total Mass Balance Inflows 3,305,454 3,305,454 3,305,454 3,305,454 3,305,454 3,305,454 Mass Balance Depletions 430,136 428,319 428,319 425,945 428,319 425,945 Mass Balance Reach Gain/Losses -187,477 -155,507 -152,138 -150,122 -151,954 -149,419 Mass Balance Evaporation 178,414 236,806 247,077 262,193 246,492 261,754 Mass Balance Outflows 2,509,366 2,431,801 2,394,734 2,375,852 2,393,120 2,369,868 Mass Balance Final Calculated Storage 18,026 70,985 101,150 109,306 103,533 116,431

Mass Balance Final Storage 18,026 70,985 101,150 109,306 103,533 116,431

Difference 0 0 0 0 0 0 Units in Mm 3

Figure 10-32. Mass Balance Across Entire Modeled Period

The mass balance provides a global perspective of how water is distributed within a single model configuration and how the operations change with respect to each scenario. Total depletions decrease due to the shortages at filling, losses due to evaporation increases, while gain/losses decrease (less losses) due to less water passing through the loss reaches. This type of analysis confirms that all sources and sinks are accounted for and can be classified for a complete conceptual understanding of the modeled representation of the system.

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Eastern Nile RiverWare Planning Model – Final Report

11 Conclusion

The purpose of developing a RiverWare model was to provide a tool for ENTRO and the stakeholders of the Eastern Nile Region that would allow a basin-wide perspective of the future management of the basin. This objective was achieved during a five month period through a collaborative effort between the consultants and ENTRO.

An effort was made to collect and utilize all available public data sources describing the physical characteristics of the basin and the current and proposed reservoir operations. Datasets of hydrologic inflows and consumptive uses were extracted from existing models and incorporated into the RiverWare model. Applying the products of these previous efforts allowed the development of the RiverWare model to focus on the developing operational rules of the reservoirs to simulate actual management practices. These practices are presumed to achieve multiple objectives such as meeting direct and downstream demands, providing a reliable source of power generation, achieving target elevations, making target releases, and meeting environmental criteria. The flexibility of the RiverWare allowed these objectives to be successfully simulated for every location where sufficient information was provided. When a lack of data or knowledge of operational practices were encountered, ENTRO provided guidance to direct the assumed management operations and objectives of the reservoirs.

The calibration of the model was considered successful, although the lack of historical depletion data posed a significant limitation. Losses in reaches, lags in reaches and evaporation rates were adjusted to allow the model to match historical data. The calibration period of 1956-1990 was selected based on the availability of a complete dataset, however it is acknowledged that further calibration should be conducted if data up to the present date are made available.

The proposed infrastructure incorporated into the model represents some of the major developments under consideration. The model was configured to allow the user to invoke essentially any combination proposed reservoirs. More importantly, the model was developed in a manner that would allow modifications to be readily made to the model including the addition of new infrastructure, modifying operational rules, or improving input data. The model was developed in close coordination with ENTRO and a two training sessions were provided to staff and interns that provide the in-house capacity to apply, modify and further develop the model to achieve the evolving needs of ENTRO and stakeholders.

The developers of the Eastern Nile RiverWare model acknowledge that limitations exist in its ability to accurately simulate actual conditions. The resolution of hydrologic inflows and demands can always be improved upon, and updated descriptions of the physical characteristics of the basin can be readily incorporated. During the development period, the vast majority of data was acquired from ENTRO which relied on their previous efforts of compiling multiple data sources. As the application of the model expands to stakeholders, additional data and information about the basin is likely to available through new sources and perspectives. The developers of this model encourage its ongoing improvement through access and use by multiple parties, and sincerely hope that it provides a foundation from which to build upon.

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Eastern Nile RiverWare Planning Model – Final Report

12 Bibliography

EEPCO, 2006. Beles Multipurpose Level 1 Design Report. Ethiopian Electric Power Corporation.

MINISTRY OF WATER AND ENERGY, 2011. MEMO: Alternatives to the Mandaya Project, Cascading Options. Federal Democratic Republic of Ethiopia, Ministry of Water and Energy.

MINISTRY OF WATER RESOURCES AND ELECTRICITY, 9/6/2012, 2012-last update, Merowe Dam Project [Homepage of Republic of Sudan, Dams Implementation Unit], [Online]. Available: http://www.merowedam.gov.sd/en/index.php [10/21, 2012].

NATIONAL ELECTRICITY CORPORATION, 2003. Building of Electricity Sector Database and Long-Term Power System Planning Study, Interim Report No. 3, The Data book, Republic of Sudan. PB Power.

NILE BASIN INITIATIVE, 2011. Nile Basin Decision Support System (DSS), Data Processing and Quality Assurance, Pilot Application of the Nile Basin Decision Support System: Stage 1, Report on Development of Nile Baseline Model. Nile Basin Initiative.

SUTCLIFFE, J.V. and PARKS, Y.P., 1999. Hydrology of the Nile. Wallingford : International Association of Hydrological Sciences.

ZAGONA, E., FULP, T., SHANE, R., MAGEE, T. and GORANFLO, H., 2001. RiverWare: A Generalized Tool for Complex Reservoir Systems Modeling. Journal of the American Water Resources Association, 37 (4), pp. 913.

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Appendix A1 – Elevation Model Results

A1-1 | P a g e

485

480

475

470

Baseline Pool Elevation (masl) Elevation Pool 465 Scenario 1 Scenario 2 460 Scenario 3 Scenario 4 Scenario 5 455 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Roseries Dam Pool Elevation

424

422

420

418

416

Baseline Pool Elevation (masl) Elevation Pool 414 Scenario 1 Scenario 2 Scenario 3 412 Scenario 4 Scenario 5 410 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Sennar Dam Pool Elevation

A1-2 | P a g e

1145

1140

1135

1130

Baseline Pool Elevation (masl) Elevation Pool 1125 Scenario 1 Scenario 2 1120 Scenario 3 Scenario 4 Scenario 5 1115 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Tekeze Dam Pool Elevation

476

474

472

470

468

466

464

Pool Elevation (masl) Elevation Pool Baseline 462 Scenario 1

460 Scenario 2 Scenario 3 458 Scenario 4 Scenario 5 456 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Khashm El Girba Pool Elevation

A1-3 | P a g e

378

377

376

375

374

373 Pool Elevation (masl) Elevation Pool Baseline 372 Scenario 1 Scenario 2 371 Scenario 3 Scenario 4 Scenario 5 370 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Jebel Aulia Dam Pool Elevation

305

300

295

290

Baseline Pool Elevation (masl) Elevation Pool 285 Scenario 1 Scenario 2 280 Scenario 3 Scenario 4 Scenario 5 275 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Merowe Dam Pool Elevation

A1-4 | P a g e

175

170

165

160 Baseline Pool Elevation (masl) Elevation Pool Scenario 1 Scenario 2 155 Scenario 3 Scenario 4 Scenario 5 150 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

High Aswan Dam Pool Elevation

1200

1150

1100

1050

1000 Pool Elevation (masl) Elevation Pool 950 Scenario 2

900 Scenario 3

850 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Karadobi Dam Pool Elevation

A1-5 | P a g e

1100

1050

1000

950

Pool Elevation (masl) Elevation Pool 900 Scenario 4

850 Scenario 5

800 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Beko Abo High Dam Pool Elevation

920

910

900

890

880

870

Pool Elevation (masl) Elevation Pool 860 Scenario 2 850

Scenario 3 840

830 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Beko Abo Low Dam Pool Elevation

A1-6 | P a g e

850

800

750

700 Pool Elevation (masl) Elevation Pool Scenario 3

650 Scenario 5

600 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Mendaya Upper Dam Pool Elevation

850

800

750

700 Scenario 2 Pool Elevation (masl) Elevation Pool Scenario 4 650

600 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Mendaya Dam Pool Elevation

A1-7 | P a g e

660

640

620

600

580

560

Pool Elevation (masl) Elevation Pool 540 Scenario 1

520 Scenario 3

500 Scenario 5

480 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Renaissance 640 Dam Pool Elevation

640

620

600

580

560

Pool Elevation (masl) Elevation Pool Scenario 2 540 Scenario 4 520

500 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Renaissance 620 Dam Pool Elevation

A1-8 | P a g e

Appendix A2 – Power and Energy Generation Model Results

A2-1 | P a g e

350 Baseline Scenario 1 Scenario 2 300 Scenario 3 Scenario 4 Scenario 5 250

200

150

Power Generation (MW) Generation Power 100

50

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Roseries Dam Power Generation

18

16

14

12

10 Baseline Scenario 1 8 Scenario 2 Scenario 3 6

Power Generation (MW) Generation Power Scenario 4

4 Scenario 5

2

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Sennar Dam Power Generation

A2-2 | P a g e

350

300

250

200

150 Power Generation (MW) Generation Power 100 Baseline Scenario 1 Scenario 2 50 Scenario 3 Scenario 4 Scenario 5 0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Tekeze Dam Power Generation

14

12

10

8

Baseline 6 Scenario 1 Scenario 2

Power Generation (MW) Generation Power 4 Scenario 3 Scenario 4 Scenario 5 2

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Khashm El Girba Power Generation

A2-3 | P a g e

40 Baseline Scenario 1 35 Scenario 2 Scenario 3 Scenario 4 30 Scenario 5

25

20

15 Power Generation (MW) Generation Power 10

5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Jebel Aulia Dam Power Generation

1400

1200

1000

800

600 Baseline

Power Generation (MW) Generation Power 400 Scenario 1 Scenario 2 Scenario 3 200 Scenario 4 Scenario 5 0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Merowe Dam Power Generation

A2-4 | P a g e

1600

1400

1200

1000

800

600 Baseline Power Generation (MW) Generation Power Scenario 1 400 Scenario 2 Scenario 3 200 Scenario 4 Scenario 5 0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

High Aswan Dam Power Generation

1800

1600

1400

1200

1000

800

600 Power Generation (MW) Generation Power

400 Scenario 2

200 Scenario 3

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Karadobi Dam Power Generation

A2-5 | P a g e

3000

2500

2000

1500

1000 Power Generation (MW) Generation Power Scenario 4

500 Scenario 5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Beko Abo High Power Generation

1000

900

800

700

600

500

400

Power Generation (MW) Generation Power 300 Scenario 2 200

100 Scenario 3

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Beko Abo Low Power Generation

A2-6 | P a g e

1800

1600

1400

1200

1000

800

600 Power Generation (MW) Generation Power

400 Scenario 3

200 Scenario 5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Mendaya Upper Power Generation

3000

2500

2000

1500

1000 Power Generation (MW) Generation Power Scenario 2

500 Scenario 4

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Mendaya Power Generation

A2-7 | P a g e

6000

Scenario 1 5000 Scenario 3

4000 Scenario 5

3000

2000 Power Generation (MW) Generation Power

1000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Renaissance 640 Power Generation

4500

4000 Scenario 2

3500

3000 Scenario 4

2500

2000

1500 Power Generation (MW) Generation Power

1000

500

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 YEAR

Renaissance 620 Power Generation

A2-8 | P a g e

300

Baseline 250 Scenario 1 Scenario 2 Scenario 3 Scenario 4 200 Scenario 5

150

100 Power Generation (MW) Generation Power

50

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Roseries Dam Power Generation Exceedance

18

16

14 Baseline 12 Scenario 1 Scenario 2 10 Scenario 3 Scenario 4 Scenario 5 8

6 Power Generation (MW) Generation Power

4

2

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Sennar Dam Power Generation Exceedance

A2-9 | P a g e

350

Baseline 300 Scenario 1 Scenario 2 Scenario 3 250 Scenario 4 Scenario 5

200

150

Power Generation (MW) Generation Power 100

50

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Tekeze Dam Power Generation Exceedance

14

12

10

Baseline 8 Scenario 1 Scenario 2 Scenario 3 6 Scenario 4 Scenario 5

Power Generation (MW) Generation Power 4

2

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Khashm El Girba Power Generation Exceedance

A2-10 | P a g e

35 Baseline Scenario 1 30 Scenario 2 Scenario 3 Scenario 4 25 Scenario 5

20

15

Power Generation (MW) Generation Power 10

5

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Jebel Aulia Dam Power Generation Exceedance

1400 Baseline Scenario 1 1200 Scenario 2 Scenario 3 Scenario 4 1000 Scenario 5

800

600

Power Generation (MW) Generation Power 400

200

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Merowe Dam Power Generation Exceedance

A2-11 | P a g e

1600

Baseline 1400 Scenario 1 Scenario 2 1200 Scenario 3 Scenario 4 Scenario 5 1000

800

600 Power Generation (MW) Generation Power 400

200

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

High Aswan Dam Power Generation Exceedance

1800

1600 Scenario 2 1400 Scenario 3 1200

1000

800

600 Power Generation (MW) Generation Power

400

200

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Karadobi Dam Power Generation Exceedance

A2-12 | P a g e

3000

2500 Scenario 4

Scenario 5 2000

1500

1000 Power Generation (MW) Generation Power

500

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Beko Abo High Dam Power Generation Exceedance

1000

900 Scenario 2 800

700 Scenario 3

600

500

400

Power Generation (MW) Generation Power 300

200

100

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Beko Abo Low Dam Power Generation Exceedance

A2-13 | P a g e

1800

1600 Scenario 3 1400

1200 Scenario 5

1000

800

600 Power Generation (MW) Generation Power

400

200

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Mendaya Upper Power Generation Exceedance

3000

2500 Scenario 2

Scenario 4 2000

1500

1000 Power Generation (MW) Generation Power

500

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Mendaya Dam Power Generation Exceedance

A2-14 | P a g e

6000

Scenario 1 5000 Scenario 3

4000 Scenario 5

3000

2000 Power Generation (MW) Generation Power

1000

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Renaissance 640 Power Generation Exceedance

4500

4000 Scenario 2 3500

3000 Scenario 4

2500

2000

1500 Power Generation (MW) Generation Power

1000

500

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Renaissance 620 Power Generation Exceedance

A2-15 | P a g e

2000

1800

1600

1400

1200

1000

800 Baseline Scenario 1 600

Energy Generation (GWH/year) Generation Energy Scenario 2 Scenario 3 400 Scenario 4 200 Scenario 5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Roseries Annual Energy Generation

140

120

100

80

60 Baseline Scenario 1

Energy Generation (GWH/year) Energy Generation 40 Scenario 2 Scenario 3 Scenario 4 20 Scenario 5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Sennar Dam Annual Energy Generation

A2-16 | P a g e

1600

1400

1200

1000

800

Baseline 600 Scenario 1

Energy Generation (GWH/year) Generation Energy Scenario 2 400 Scenario 3 Scenario 4 200 Scenario 5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Tekeze Annual Energy Generation

120

100

80

60

Baseline

40 Scenario 1

Energy Generation (GWH/year) Generation Energy Scenario 2 Scenario 3 20 Scenario 4 Scenario 5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Khashm El Girba Annual Energy Generation

A2-17 | P a g e

195

190

185

180

175

170

165 Baseline 160 Scenario 1

Energy Generation (GWH/year) Generation Energy 155 Scenario 2 Scenario 3 150 Scenario 4

145 Scenario 5

140 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Jebel Aulia Annual Energy Generation

12,000

10,000

8,000

6,000

Baseline

4,000 Scenario 1

Energy Generation (GWH/year) Generation Energy Scenario 2 Scenario 3 2,000 Scenario 4 Scenario 5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Merowe Annual Energy Generation

A2-18 | P a g e

14,000

12,000

10,000

8,000

6,000 Baseline Scenario 1

Energy Generation (GWH/year) Generation Energy 4,000 Scenario 2 Scenario 3 Scenario 4 2,000 Scenario 5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

High Aswan Annual Energy Generation

12,000

10,000

8,000

6,000

Scenario 2 4,000

Energy Generation (GWH/year) Generation Energy Scenario 3

2,000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Karadobi Annual Energy Generation

A2-19 | P a g e

16,000

14,000

12,000

10,000

8,000

6,000 Scenario 4

Scenario 5 Energy Generation (GWH/year) Generation Energy 4,000

2,000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Beko Abo High Annual Energy Generation

7000

6000

5000

4000

3000 Scenario 2

Energy Generation (GWH/year) Generation Energy 2000 Scenario 3

1000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Beko Abo Low Annual Energy Generation

A2-20 | P a g e

12,000

10,000

8,000

6,000

Scenario 3 4,000

Energy Generation (GWH/year) Generation Energy Scenario 5

2,000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Upper Manadaya Annual Energy Generation

18,000

16,000

14,000

12,000

10,000

8,000

6,000 Scenario 2 Energy Generation (GWH/year) Generation Energy 4,000 Scenario 4 2,000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Mendaya Annual Energy Generation

A2-21 | P a g e

25,000

20,000

15,000

Scenario 1 10,000

Scenario 3 Energy Generation (GWH/year) Generation Energy

5,000 Scenario 5

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Renaissance 640 Annual Energy Generation

20,000

18,000

16,000

14,000

12,000

10,000

8,000 Scenario 2

6,000 Scenario 4 Energy Generation (GWH/year) Generation Energy

4,000

2,000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Renaissance 620 Annual Energy Generation

A2-22 | P a g e

2000

1800

1600

1400

1200

1000 Baseline 800 Scenario 1 600 Scenario 2 Scenario 3 Energy Generation (GWH/year) Generation Energy 400 Scenario 4 200 Scenario 5

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Annual Roseries Energy Generation

140

120

100

80

60 Baseline Scenario 1 40 Scenario 2 Scenario 3 Energy Generation (GWH/year) Generation Energy Scenario 4 20 Scenario 5

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Annual Sennar Energy Generation

A2-23 | P a g e

1600

1400

1200

1000

800 Baseline 600 Scenario 1 Scenario 2 400 Scenario 3 Energy Generation (GWH/year) Generation Energy Scenario 4 200 Scenario 5

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Annual Tekeze Energy Generation

120

100

80

60 Baseline Scenario 1 40 Scenario 2 Scenario 3 Energy Generation (GWH/year) Generation Energy 20 Scenario 4 Scenario 5

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Khashm El Girba Energy Generation

A2-24 | P a g e

195

190

185

180

175 Baseline 170 Scenario 1 Scenario 2 165 Scenario 3 Energy Generation (GWH/year) Generation Energy Scenario 4 160 Scenario 5

155 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Jebel Aulia Energy Generation

12,000

10,000

8,000

6,000 Baseline Scenario 1 4,000 Scenario 2 Scenario 3 Energy Generation (GWH/year) Generation Energy 2,000 Scenario 4 Scenario 5

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Merowe Energy Generation

A2-25 | P a g e

14,000

12,000

10,000

8,000

6,000 Baseline Scenario 1 4,000 Scenario 2 Scenario 3 Energy Generation (GWH/year) Generation Energy Scenario 4 2,000 Scenario 5

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of High Aswan Energy Generation

12,000

10,000

8,000

6,000

Scenario 2 4,000 Scenario 3 Energy Generation (GWH/year) Generation Energy 2,000

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Karadobi Energy Generation

A2-26 | P a g e

16,000

14,000

12,000

10,000

8,000

6,000 Scenario 4

4,000 Scenario 5 Energy Generation (GWH/year) Generation Energy

2,000

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Beko Abo High Energy Generation

7000

6000

5000

4000

3000 Scenario 2

2000 Scenario 3 Energy Generation (GWH/year) Generation Energy 1000

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Beko Abo Low Energy Generation

A2-27 | P a g e

12,000

10,000

8,000

6,000

Scenario 3 4,000 Scenario 5 Energy Generation (GWH/year) Generation Energy 2,000

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Mendaya Upper Energy Generation

18,000

16,000

14,000

12,000

10,000

8,000 Scenario 2 6,000 Scenario 4

Energy Generation (GWH/year) Generation Energy 4,000

2,000

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Mendaya Energy Generation

A2-28 | P a g e

25,000

20,000

15,000

10,000 Scenario 1 Scenario 3 Scenario 5

Energy Generation (GWH/year) Generation Energy 5,000

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Renaissance 640 Energy Generation

20,000

18,000

16,000

14,000

12,000

10,000

8,000 Scenario 2

6,000 Scenario 4

Energy Generation (GWH/year) Generation Energy 4,000

2,000

0 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Exceedance

Exceedance Plot of Renaissance 620 Energy Generation

A2-29 | P a g e

Appendix A3 – Reservoir Spill Modeled Results

A3-1 | P a g e

50,000 Baseline 45,000 Scenario 1 Scenario 2 40,000 Scenario 3 Scenario 4 35,000 Scenario 5

30,000

25,000

20,000 Volume (MCM) Volume

15,000

10,000

5,000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Roseries Dam Spill

60,000 Baseline Scenario 1 50,000 Scenario 2 Scenario 3 Scenario 4 Scenario 5 40,000

30,000 Volume (MCM) Volume 20,000

10,000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Sennar Dam Spill

A3-2 | P a g e

70%

60%

50%

40%

30%

Baseline Percent ofOutflow Spilled Percent 20% Scenario 1 Scenario 2 Scenario 3 10% Scenario 4 Scenario 5 0% 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Roseries Dam Spill as Percent of Outflow

100%

90%

80%

70%

60% Baseline

50% Scenario 1 Scenario 2 40% Scenario 3

30% Scenario 4 Percent Outflow of Spilled Percent Scenario 5 20%

10%

0% 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Sennar Dam Spill as a Percent of Outflow

A3-3 | P a g e

50% Baseline 45% Scenario 1 Scenario 2 40% Scenario 3 Scenario 4 35% Scenario 5

30%

25%

20%

15% Percent Outflow of Spilled Percent

10%

5%

0% 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Merowe Dam Spill as a Percent of Outflow

45,000 Baseline 40,000 Scenario 1 Scenario 2 35,000 Scenario 3 Scenario 4 Scenario 5 30,000

25,000

20,000 Volume (MCM) Volume 15,000

10,000

5,000

0 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054

Merowe Dam Spill

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Appendix B – Model Inputs

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Initial Pool Elevations

Reservoir Pool Elevation (m) High Aswan Dam 165 Jebel Aulia Dam 377 Khashm El Girba Dam 474 Lake Tana 1787 Machar Marshes 1003 Merowe Dam 300 Roseries Dam 481 Sennar Dam 421.7 Tekeze Dam 1140

Elevation-Volume Tables

Power Toolkit Power Toolkit Power Toolkit Power Toolkit

Baro 1 Baro 2 Beko Abo High Beko Abo Low Dam.Elevation Dam.Elevation Dam.Elevation Dam.Elevation Volume Table Volume Table Volume Table Volume Table masl MCM masl MCM masl MCM masl MCM 1470 0 1304 0 800 0 800 0 1477.5 231.32 1311 18.43 905 1511.69 835 70.14 1481.04 284.38 1311.75 21.17 918 2193.55 841 104.91 1484.58 343.83 1312.5 24.18 931 3077.41 848 150.87 1488.13 409.83 1313.25 27.49 944 4197.69 854 210.11 1491.67 482.56 1314 31.11 957 5591.08 860 284.82 1495.21 562.19 1314.75 35.05 970 7296.53 866 377.36 1498.75 648.88 1315.5 39.33 984 9355.15 873 490.22 1502.29 742.77 1316.25 43.96 997 11810.2 879 626.02 1505.83 844.01 1317 48.97 1010 14707.07 885 787.53 1509.38 952.74 1317.75 54.37 1023 18093.2 891 977.65 1512.92 1069.1 1318.5 60.18 1036 22018.08 898 1199.39 1516.46 1193.21 1319.25 66.41 1049 26533.22 904 1455.92 1520 1325.21 1320 73.08 1062 31692.13 910 1750.52

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High Aswan Sheet, MIKE basins MIKE Basins Power Toolkit High Asw an Sheet, Lahmeyer

High Aswan Jebel Aulia Kajbar Karadobi Dam.Elevation Dam.Elevation Dam.Elevation Dam.Elevation Volume Volume Table Volume Table Volume Table Table masl MCM masl MCM masl MCM masl MCM 107 0 360 0 207.9 0 900 0 120 5200 366 75 207.95 237.96 920 4 125 7800 370 100 208.37 258.43 940 93 130 11300 373.29 305 208.79 266.2 960 466 135 15600 373.7 501 209.21 271.16 980 1383 140 21200 374.68 803 209.63 274.84 1000 3117 145 28300 375.41 1424 210.05 277.76 1020 5605 147 31860 376 1925 210.48 280.2 1040 8703 150 37200 376.27 2125 210.9 282.29 1060 12520 155 48100 376.75 2702 211.32 284.12 1080 17189 160 61500 377.25 3125 211.74 285.76 1100 22799 165 77900 377.27 3178 212.16 287.23 1120 29479 170 97600 377.5 3377.01 212.58 288.57 1140 37338 175 121300 378 3903.51 213 289.8 1146 40094 180 149500 378.5 4430.01 1147 40553 183 169420 379 4956.51 1148 41012 1150 41931 1151 42390 1153 43309 1153.81 43681

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Power Toolkit Power Toolkit Power Toolkit Power Toolkit

Mendaya Upper Merowe Renaissance 620 Renaissance 640 Dam.Elevation Dam.Elevation Dam.Elevation Dam.Elevation Volume Table Volume Table Volume Table Volume Table masl MCM masl MCM masl MCM masl MCM 640 0 240 0 505 0 505 0 705 2979.64 249.9 0 547.5 469.56 557.5 994.7184 713 3828.64 250 3 554 819.37 564.38 1681.821 721 4836.65 260 143 560 1347.07 571.25 2695.841 729 6020.05 265 389 566 2110.73 578.12 4137.312 737 7395.75 270 817 572 3178.97 585 6124.106 745 8981.11 275 1520 578 4631.65 591.88 8792.5 753 10793.94 280 2570 584 6560.56 598.75 12298.22 760 12852.5 284.9 4119 590 9070.03 605.62 16817.44 768 15175.5 285 4120 596 12277.6 612.5 22547.79 776 17782.04 290 6170 602 16314.57 619.38 29709.26 784 20691.64 295 8900 608 21326.66 626.25 38545.23 792 23924.24 298 11050 614 27474.55 633.12 49323.27 800 27500.12 300 12450 620 34934.46 640 62336.16 630 50687.15 700 175820.6 640 62336.16

High Asw an Sheet, Acres(1993) MIKE Basins Power Toolkit High Aswan, Scott Wilson 2006

Khashm El Girba Lower Didessa Mendaya Dam.Elevation Volume Lake Tana.Elevation Dam.Elevation Dam.Elevation Volume Table Volume Table Volume Table Table masl MCM masl MCM masl MCM masl MCM 440 0 1772 0 640 0 610 0 445 5 1773 250 705 583.86 620 30 450 12.5 1774 1000 713 818.56 630 140 455 22.5 1775 2000 721 1108.3 640 358 460 37.5 1776 4000 729 1458.67 650 716 461 42.5 1777 5500 737 1875.23 660 1256 462 50 1778 7500 745 2363.53 670 2011 463 60 1779 10000 753 2929.07 680 3006 463.5 65 1780 12000 760 3577.34 690 4286 464 70 1781 15000 768 4313.79 700 5881 465 90 1782 17000 776 5143.88 710 7771 467.5 165 1783 20000 784 6073.01 720 9946 470 308 1784 23147 792 7106.59 730 12486 473.6 580 1785 26096 800 8250 740 15781 474 657 1786 29097 741 16223 1787 32098 760 24614 1788 35099 780 35727 800 49201 820 65318 840 84303 860 106728

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Aw asn Sheet - HLC(MoI) 2002 MIKE Basins Power Toolkit Power Toolkit

Roseries Sennar Sherieg Tekeze Dam.Elevation Dam.Elevation Dam.Elevation Dam.Elevation Volume Table Volume Table Volume Table Volume Table masl MCM masl MCM masl MCM masl MCM 465 0 411 0 330 0 974 0 466 13 411.9 0.84 335 731.47 975 1 467 30.1 412 0.85 336 830.74 1000 69 467.7 50.7 412.3 1.07 336 934.63 1010 134 468 61.8 412.6 1.45 337 1042.99 1020 245 468.5 83.2 413 2.3 338 1155.7 1030 423 469 108.8 413.3 3.3 338 1272.65 1040 678 470 172.4 413.6 4.6 339 1393.73 1050 1023 471 253.2 414 7 340 1518.85 1060 1474 472 351.9 414.3 9.5 340 1647.91 1070 2036 473 469 414.6 12.6 341 1780.84 1080 2707 474 605 415 17.6 342 1917.55 1090 3480 475 760.4 415.3 22.4 342 2057.99 1100 4354 476 935.5 415.6 27.9 343 2202.07 1110 5353 477 1130.8 416 36.9 1120 6499 478 1346.5 416.3 44.8 1130 7810 478.5 1462.1 416.6 53.9 1140 9293 479 1583 417 67.9 1150 10958 479.5 1709.2 417.3 80.1 480 1840.6 417.6 93.7 480.5 1877.5 418 114.2 481 2119.7 418.3 131.7 481.02 2200 418.6 150.9 419 179.5 419.3 203.3 419.6 229.3

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Elevation-Area Tables

Power Toolkit Power Toolkit Power Toolkit Power Toolkit Baro 1 Baro 2 Beko Abo High Beko Abo Low Dam.Elevation Area Dam.Elevation Area Dam.Elevation Area Dam.Elevation Area Table Table Table Table masl ha masl ha masl ha masl ha 1470 0 1304 0 800 0 800 0 1477.5 1399.978 1311 327.2508 905 4885.049 835 579.7918 1481.04 1564.889 1311.75 361.2304 918 6325.535 841 766.6867 1484.58 1733.534 1312.5 397.1961 931 8001.26 848 986.65 1488.13 1905.695 1313.25 435.1809 944 9925.274 854 1241.654 1491.67 2081.184 1314 475.217 957 12110.17 860 1533.6 1495.21 2259.836 1314.75 517.336 970 14568.16 866 1864.323 1498.75 2441.502 1315.5 561.5688 984 17311.06 873 2235.602 1502.29 2626.05 1316.25 607.9457 997 20350.41 879 2649.164 1505.83 2813.36 1317 656.4966 1010 23697.41 885 3106.69 1509.38 3003.325 1317.75 707.2505 1023 27363.01 891 3609.819 1512.92 3195.845 1318.5 760.2361 1036 31357.92 898 4160.148 1516.46 3390.829 1319.25 815.4816 1049 35692.6 904 4759.243 1520 3588.195 1320 873.0147 1062 40377.29 910 5408.632

High Aswan Sheet, MIKE basins MIKE Basins Power Toolkit High Asw an Sheet, Lahmeyer High Aswan Jebel Aulia Kajbar Karadobi Dam.Elevation Area Dam.Elevation Area Dam.Elevation Area Dam.Elevation Area Table Table Table Table masl ha masl ha masl ha masl ha 107 0 360 0 207.9 0 900 0 120 45000 366 5000 207.95 650.4414 920 65 125 60000 370 8000 208.37 1373.639 940 1020 130 74900 373.29 13100 208.79 1796.32 960 2860 135 98800 373.7 21600 209.21 2123.551 980 6570 140 124200 374.68 31900 209.63 2398.924 1000 11000 145 158900 375.41 56000 210.05 2640.571 1020 14000 147 173800 376 82000 210.48 2858.076 1040 17000 150 196200 376.27 88800 210.9 3057.223 1060 21200 155 241400 376.75 106000 211.32 3241.816 1080 25600 160 295000 377.25 122000 211.74 3414.514 1100 30600 165 358100 377.27 122500 212.16 3577.258 1120 36300 170 430800 377.5 132629 212.58 3731.519 1140 42400 175 516800 378 149479 213 3878.438 1146 44500 180 611800 378.5 166329 183 675200 379 183179

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High Asw an Sheet, Acres(1993) MIKE Basins Power Toolkit High Aswan, Scott Wilson 2006 Khashm El Girba Lower Didessa Mendaya Dam.Elevation Area Lake Tana.Elevation Dam.Elevation Area Dam.Elevation Area Table Area Table Table Table masl ha masl ha masl ha masl ha 440 0 1772 0 640 0 610 0 445 150 1773 30000 705 2978.137 620 600 450 200 1774 90000 713 3634.918 630 1600 455 300 1775 140000 721 4346.251 640 2760 460 400 1776 170000 729 5110.658 650 4400 461 600 1777 200000 737 5926.834 660 6400 462 700 1778 225000 745 6793.613 670 8700 463 800 1779 250000 753 7709.946 680 11200 463.5 940 1780 255000 760 8674.88 690 14400 464 1080 1781 265000 768 9687.541 700 17500 465 1900 1782 275000 776 10747.13 710 20300 467.5 3500 1783 287500 784 11852.9 720 23200 470 6300 1784 293197 792 13004.16 730 27600 473.6 9500 1785 297800 800 14200.28 740 38300 474 10000 1786 302403 741 38900 1787 307005 760 50000 1788 311608 780 61100 800 73600 820 87500 840 102300 860 121900

Power Toolkit Power Toolkit Power Toolkit Power Toolkit Mendaya Upper Merowe Renaissance 620 Renaissance 640 Dam.Elevation Area Dam.Elevation Area Dam.Elevation Area Dam.Elevation Area Table Table Table Table masl ha masl ha masl ha masl ha 640 0 240 0 505 0 505 0 705 13071.9 249.9 0 547.5 8307.4 557.5 13828.81 713 15509.16 250 100 554 11625.84 564.38 18987.44 721 18188.82 260 3500 560 15695.01 571.25 25244.35 729 21116.74 265 6500 566 20582.58 578.12 32693.3 737 24298.52 270 10800 572 26354.91 585 41426.29 745 27739.55 275 17400 578 33077.2 591.88 51533.79 753 31445.03 280 25600 584 40813.57 598.75 63104.86 760 35419.96 284.9 35300 590 49627.19 605.62 76227.26 768 39669.2 285 35400 596 59580.38 612.5 90987.61 776 44197.43 290 47600 602 70734.62 619.38 107471.4 784 49009.21 295 62000 608 83150.65 626.25 125763.2 792 54108.94 298 72400 614 96888.55 633.12 145946.6 800 59500.95 300 80300 620 112007.7 640 168104.2 630 140224.9 640 168104.2

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Asw an Sheet - HLC(MoI) 2002 MIKE Basins Power Toolkit Power Toolkit Roseries Sennar Sherieg Tekeze Dam.Elevation Area Dam.Elevation Area Dam.Elevation Area Dam.Elevation Area Table Table Table Table masl ha masl ha masl ha masl ha 465 0 411 0 330 0 974 0 466 1050 411.9 89 335 11842.14 975 39 467 1440 412 90 336 13078.86 1000 503.4 467.7 1850 412.3 140 336 14338.75 1010 807.4 468 2060 412.6 210 337 15620.52 1020 1401.5 468.5 2450 413 320 338 16923.07 1030 2156.1 469 2900 413.3 430 338 18245.4 1040 2946.3 470 3970 413.6 570 339 19586.62 1050 3960.1 471 5230 414 780 340 20945.93 1060 5055.1 472 6740 414.3 960 340 22322.59 1070 6179.8 473 8430 414.6 1170 341 23715.95 1080 7256 474 10340 415 1560 342 25125.39 1090 8193.4 475 12450 415.3 1780 342 26550.37 1100 9285.1 476 14760 415.6 2080 343 27990.36 1110 10692.2 477 17270 416 2530 1120 12272 478 19980 416.3 2890 1130 13970.2 478.5 21410 416.6 3300 1140 15687.6 479 22890 417 3880 1150 17612.6 479.5 24420 417.3 4350 480 26000 417.6 4860 480.5 27630 418 5580 481 29300 418.3 6170 481.02 29300 418.6 6780 419 7660 419.3 8350 419.6 9690 420 10130 420.3 10940 420.6 11790 421 12990 421.3 13940 421.7 15260 422.4 17530

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Power Generation Coefficients

Aswan Sheet - Voith Riva 99 Aswan Sheet - NEC Aswan Sheet - NEC Aswan Sheet - NEC Jebel Aulia Sennar Roseries Khashm El Girba

Power Power Power Power Coeff Coeff Coeff Coeff Head (MW/cms) Head (MW/cms) Head (MW/cms) Head (MW/cms) 4.24 0.0000 5.99 0.1064 14.99 0.0000 18.45 0.1445 4.25 0.0090 6.00 0.1064 15.00 0.1050 20.26 0.1639 4.70 0.0156 7.00 0.1141 25.00 0.1700 22.08 0.1831 5.15 0.0210 8.00 0.1217 27.00 0.1800 23.89 0.2021 5.60 0.0257 9.00 0.1293 29.00 0.2000 25.70 0.2209 6.05 0.0301 10.00 0.1369 31.00 0.2100 27.51 0.2395 6.50 0.0341 11.00 0.1369 33.00 0.2300 29.33 0.2581 6.95 0.0380 35.00 0.2400 31.14 0.2765 7.40 0.0416 37.00 0.2600 32.95 0.2947 39.00 0.2700 34.76 0.3129 40.00 0.2800 36.58 0.3310 38.39 0.3489 40.20 0.3668

Reservoir Parameters

Bottom of Minimum Reservoir or Minimum Minimum Direct Top of Dead Active Pool Minimum Operating Diversion Maximum Pool Pool Elevation Power Level Level (MOL) Elevation Elevation (FSL) High Aswan Dam 107 110 147 147 -- 183 Jebel Aulia Dam 370 370 370 372 372 377.4 Khashm El Girba Dam 440 463 452 463.5 463.5 474 Lake Tana 1772 1783.5 -- 1784 -- 1787 Merowe Dam 250 285 263 285 -- 300 Roseries Dam 463.7 467 467 467 -- 481 Sennar Dam 411 415 415 417 417 421.7 Tekeze Dam 975 1096 975 1096 -- 1140

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Roseries Target Khashm El Girba Tana Releases Elev Sennar Target Elev Jebel Aulia Target Elev Target Elev Elev (masl) MCM/month masl masl masl masl 0 0 Jan 478.78 Jan 421.7 Jan 377.4 Jan 474 1783.5 0 Feb 475.13 Feb 421.7 Feb 377.4 Feb 474 1784.5 107.136 Mar 472.39 Mar 421.7 Mar 376.8715686 Mar 474 1785 149.9904 Apr 469.78 Apr 421.7 Apr 375.4303922 Apr 474 1785.5 214.272 May 467.09 May 417 May 373.9411765 May 474 1786 286.5888 Jun 467 Jun 417 Jun 372.5 Jun 463.5 1786.5 353.5488 Jul 467 Jul 417 Jul 376.5 Jul 463.5 1787 441.936 Aug 467 Aug 417 Aug 376.5 Aug 463.5 1787.5 546.3936 Sep 471.67 Sep 418.65 Sep 377.4 Sep 474 1788 696.384 Oct 481 Oct 421.7 Oct 377.4 Oct 474 1788.5 1063.3248 Nov 481 Nov 421.7 Nov 377.4 Nov 474 Dec 481 Dec 421.7 Dec 377.4 Dec 474

High Aswan Inflow States Flow Inflow Flow Range Range State (MCM/Month) (cms) Above 1 11,500 4364.00 11,500 4364.00 2 9,800 3718.88 9,800 3718.88 3 7,800 2959.93 7,800 2959.93 4 6,000 2276.87 6,000 2276.87 5 0 0.00

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Full Surface Minimum Maximum Target Level Operating Power Power (masl) Level (masl) (MW) (MW) Blue Nile Karadobi Dam 1146 1100 1600 933 Beko Abo High Dam 1062 1010 2423 1329 Beko Abo Low Dam 910 870 935 594 Mendaya Upper Dam 770 800 1700 802 Mendaya Dam 770 800 2750 1423 Renaissance 640 Dam 640 610 5290 1745.7 Renaissance 620 Dam 620 590 4500 1485 Lower Didessa Dam 800 770 550 280 Baro-Akobo-Sobat Baro 1 Dam 1520 1485 180 93.8 Baro 2 Dam 1320 1318 500 254 Main Nile Sherieg 343 340 350 350 Kajbar 213 208 250 250

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Releases from High Aswan Dam Inflow State 1 Inflow State 2 Inflow State 3 Inflow State 4 Inflow State 5 Elev (masl) MCM/month MCM/month MCM/month MCM/month MCM/month 145 0.00 0.00 0.00 0.00 0.00 146 1239.99 0.00 0.00 0.00 0.00 147 1689.88 0.00 0.00 0.00 0.00 148 2135.46 387.24 46.17 40.98 0.00 149 2581.01 899.60 466.25 321.41 0.00 150 3026.59 1411.95 886.34 749.95 0.00 151 3435.41 1855.12 1580.29 412.25 137.42 152 3985.08 2198.66 1717.70 755.79 343.54 153 4259.91 3160.58 1992.54 1442.87 549.67 154 4878.28 3366.70 2198.66 1717.70 755.79 155 5427.95 3985.08 2885.74 2129.95 1305.46 156 5565.36 4328.62 3778.95 2336.08 1855.12 157 5702.78 4809.57 4191.20 2885.74 2129.95 158 6046.32 5221.82 4603.45 3572.83 2336.08 159 6183.74 5496.66 4809.57 4122.49 3504.12 160 6252.45 5771.49 5221.82 4672.16 3847.66 161 6321.15 5908.90 5496.66 5221.82 4397.32 162 6355.51 6011.97 5702.78 5496.66 5221.82 163 6389.86 6046.32 5840.20 5908.90 5565.36 164 6424.22 6183.74 6046.32 6115.03 5977.61 165 6458.57 6321.15 6321.15 6183.74 6183.74 166 6458.57 6458.57 6458.57 6444.83 6389.86 167 6458.57 6458.57 6458.57 6458.57 6424.22 168 6458.57 6458.57 6458.57 6458.57 6458.57 169 6458.57 6458.57 6458.57 6458.57 6458.57 170 6458.57 6458.57 6458.57 6458.57 6458.57 171 6595.99 6595.99 6595.99 6595.99 6595.99 172 6733.40 6733.40 6733.40 6733.40 6733.40 173 6802.11 6802.11 6802.11 6802.11 6802.11 174 6870.82 6870.82 6870.82 6870.82 6870.82 175 6870.82 6870.82 6870.82 6870.82 6870.82 176 6870.82 6870.82 6870.82 6870.82 6870.82 177 6870.82 6870.82 6870.82 6870.82 6870.82 178 6870.82 6870.82 6870.82 6870.82 6870.82 179 7557.90 7283.07 6870.82 6870.82 6870.82 180 8657.23 8107.57 7420.49 7283.07 7214.36 181 9481.73 8657.23 8038.86 7695.32 7557.90 182 10443.65 9481.73 8725.94 8657.23 8313.69 183 10855.90 10374.94 9825.27 9550.44 9275.61 184 11130.73 10993.31 10168.81 9756.56 9550.44 185 11199.44 11062.02 10237.52 9825.27 9619.15

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