Overview of Models. Brian Joyce, SEI Ken Strzepek, IEc

Overview of Models Brian Joyce, SEI Ken Strzepek, IEc 1

Outline Brian describes: WEAP model of Volta How WEAP model is consistent with other modeling in the region Initial results showing climate change impacts Ken describes: OSeMOSYS model of West African power pool Initial results showing climate change impacts 2

Water Modeling 3

The Water Evaluation and Planning (WEAP) System Generic, object-oriented, programmable, integrated water resources management modeling platform 4

In developing WEAP, SEI is seeking to create a truly integrated water modeling platform 5

WEAP is a globally renowned water modeling platform (as of 27/10/13) Top 10 Forum Members by Country 171 Countries USA Iran India Peru Colombia China Mexico Chile Vietnam Germany 11387 Members 1138 1030 790 632 539 535 498 291 287 252 WEAP Downloads: In last day: 10 In last week: 66 In last month: 279 In last 12 months: 6 3304

WEAP Model of Volta River 7

Origins of the Volta WEAP Model GLOWA: German Ministry of Education and Research funded project from 2001-2009, which produced the first climate-driven, basinlevel water planning tool of Volta using WEAP and MIKE BASIN IWMI & CSIR extended WEAP model to consider proposed projects with limited range of climate change and adaptation scenarios Current World Bank funded effort extends the 8 model to evaluate full range of climate and

WEAP as an Integrated Water Basin Analysis Tool Ø WEAP advantage: seamlessly integrates watershed hydrologic processes with water resources management Ø Water supplies and demands can be climatically driven 9

Two-Step Process for Developing a WEAP Model from Juizo & Liden, Hydrologic Earth System Sciences (2010) 10

Integrating Hydrology into Water Planning Full accounting of water flows throughout watershed: q Rainfall-runoff modeling q Climate-driven evapotranspiration q Snow accumulation/melt q Groundwater-surface water interaction 11

Black Volta Wayen White Volta Lerinord Oti Pendjari Kanazoe Loumbila Dapola Nangodi Kompienga Mango Nouaho Ziga Yakala Bagre Kompienga Noumbiel Arly Nwokuy Simplified Schematic of Bamboi Volta River Subijna System (Pre-Development) Nawuni Koumangou Daka Sabari Bui Subcatchment Irrigation Scheme Domestic/Municipal Reservoir River Flow Flow Records Tanoso Tanoso Senchi Akosombo Kpong

WEAP s Soil Moisture Hydrology Model Ø Hydrology module covers the entire extent of the river basin Ø Study area configured as a contiguous set of catchments Ø Lumped-parameter approach calculates water balance for each catchment Pobs ET= f(zfa, kcfa, PET) Pe = f(pobs, Snow Accum, Melt rate, Tl, Ts) surface runoff = f(zfa, RRFfa, Pe) Ufa zfa Lfa Wcfa Percolation = f( zfa, Hc fa, f) interflow = f(zfa, Hcfa, 1-f) WC Z Baseflow = f(z, HC) 13

Black Volta Headwaters 12 10 8 6 4 2 0 CMS 12 Monthly Flow Duration 12 10 10 8 8 6 4 2 0 CMS CMS Black Volta at Nwokuy Monthly Average Flow 6 4 2 0 14

Black Volta Middle Reaches 12 10 8 6 4 2 0 CMS 12 Monthly Flow Duration 12 10 10 8 8 6 4 2 0 CMS CMS Black Volta at Dapola Monthly Average Flow 6 4 2 0 15

Black Volta Lower Reaches 12 10 8 6 4 2 0 CMS 12 Monthly Flow Duration 12 10 10 8 8 6 4 2 0 CMS CMS Black Volta at Bamboi Monthly Average Flow 6 4 2 0 16

White Volta Middle Reaches 12 10 8 6 4 2 0 CMS 12 Monthly Flow Duration 12 10 10 8 8 6 4 2 0 CMS CMS White Volta at Pwalugu Monthly Average Flow 6 4 2 0 17

White Volta Lower Reaches 12 10 8 6 4 2 0 CMS 12 Monthly Flow Duration 12 10 10 8 8 6 4 2 0 CMS CMS White Volta at Nawuni Monthly Average Flow 6 4 2 0 18

Oti Pendjari Middle Reaches 12 10 8 6 4 2 0 CMS 12 Monthly Flow Duration 12 10 10 8 8 6 4 2 0 CMS CMS Oti Pendjari at Mango Monthly Average Flow 6 4 2 0 19

Oti Pendjari Lower Reaches 12 10 8 6 4 2 0 CMS 12 Monthly Flow Duration 12 10 10 8 8 6 4 2 0 CMS CMS Oti Pendjari at Sabari Monthly Average Flow 6 4 2 0 20

Natural simulations The project team are confident about most of the simulations. WEAP simulations are more than adequate simulations compared to accepted information. WEAP produces reasonable frequency distributions of monthly flow volumes and the seasonal distributions of inflow. However, there are some parts of the basin where refinements are possible: Some of these could follow a comparison of 21

Integrating Hydrology into Water Planning Water infrastructure and demands are nested within the underlying hydrological processes: q Programmable operating rules for infrastructure q Represent water demands from all sectors 22

Planned Water Resources Development in the Volta Basin Catchment Black Volta Nwokuy Dapola Noumbiel Bamboi White Volta Nawuni Pwalugu Yakala Nangodi Oti River Sabari Mango Lower Volta Senchi Name of Dam/Scheme Country Total Reservoir Volume (Mm3) Irrigated Area (ha) Installed Hydropower Capacity (MW) Projected Date of Completion Samendeni Bonvale Bagri Bontioli Bon Duuli Gbari Noumbiel Gongourou Bui Koulbi Ntereso Lanka Jambito Burkina Faso Burkina Faso Ghana Burkina Faso Burkina Faso Ghana Ghana Burkina Faso Burkina Faso Ghana Ghana Ghana Ghana Ghana 610 130 320 2,000 11,300 1,000 12,570 29,501 13,701 7601 5,000 100 150 100 7,800 30,000-2.4 0.3 5.1 7.8 48 5 400 68 64 95 55 2027 2024 2024 2024 2024 2012 - Daboya Pwalugu Kulpawn Dipala Sogo Daboya Tiego Yarugu Sambolekuliga Bagre Aval Bandongo Ghana Ghana Ghana Ghana Ghana Ghana Ghana Ghana Burkina Faso Burkina Faso 3,430 3,260 7,200 107 480 100 100 50 200 200-43 50 40 14 3 2020 2024 2024 Juale Namiele Wakuti Arli Ghana Togo Togo Burkina Faso 1,200-1,250 1,350-87 0.92 2012 - Asantekwaa New Longoro Buipe Yapei Ghana Ghana Ghana Ghana - 200 200 200 200 - -

Ghana Formal Irrigation Projects Projected irrigated area for existing and planned irrigation projects 12 10 8 6 I r rig a te d A re a ( h a ) 4 2 0 24

Burkina Faso Formal Irrigation Projects Projected irrigated area for existing and planned irrigation projects 12 10 8 6 I rrig a te d A re a ( h a ) 4 2 0 25

Black Volta Wayen White Volta Lerinord Sourou Bonvale Kanazoe Loumbila Dapola Nangodi Nwokuy Gongorou Simplified Schematic of Volta River System Bamboi Subijna Subcatchment Irrigation Scheme Domestic/Municipal Reservoir River Flow Water Outtake Mango Yakala Kompienga Bagre Bontioli Noumbiel Kompienga Nouaho Ziga Bon Samendeni Oti Pendjari Badongo Koulbi Noumbiel Bagre Aval Arly Pwalugu Koumangou Nawuni Ntereso Kulpawn Lanka Bui Daka Daboya Sabari Juale Jambito Tanoso Tanoso Senchi Akosombo Kpong

WEAP Allocation Logic for Volta River System Ø Water allocation order (highest to lowest) Ø Domestic/Municipal Water Users Ø Livestock Ø In-basin Irrigation Ø Hydropower generation Ø Reservoir Storage 28

Comparison of WEAP to Historical WEAP operational rules lead to similar reservoir storages Lake Akosombo Lake Elevation (meters) 12 10 8 6 4 2 0 29

We can use our models to explore a range of potential future climate conditions. 30

Consider Alternative Climate Projections Historical Wet (from giss_aom-b1) Dry (from ipsl-cm4-a2) 31

Climate change might affect performance of hydro-power and irrigation 32

Energy Modeling 33

An Introduction to OSeMOSYS Open Source energy MOdeling SYStem At present there exists a useful, but limited set of accessible energy systems models. They often require significant investments in terms of human resources, training and software purchases. Leading International Partners OSeMOSYS is a fully fledged energy systems linear optimisation model, with no associated upfront financial requirements. It extends the availability of energy modelling further to researchers, business analysts and government specialists in developing countries. An easily ledgible 500 line long open source code written in GNU Mathprog with an existing translation into GAMS. 34

An Introduction to OSeMOSYS A Straight forward Building Block based structure A large user community using and developing different code blocks for OSeMOSYS Increased tool flexibility with the ability to tailor the code specific modelling requirements Easy version change management: OSeMOSYS to be integrated with a Semantic Media Wiki (SMW) being developed by World Bank-ESMAP Reserve Margin Annual Activity Capital Costs Total Activity Operating Costs (1) Objective Capacity Adequacy B Energy Balance B New Capacity Discounte d Cost Hydro Facilities Capacity Adequacy A Energy Balance A Total Capacity (2) Costs (3) Storage (4) Capacity Adequacy (5) Energy Balance (6) Constraints Plain English Description Multiple Levels of Abstraction Mathematical Analogy Micro Implementation 35 Modular Structure Salvage Value (7) Emissions

An Introduction to OSeMOSYS Useful for: Medium- to long-term capacity expansion/investment planning To inform local, national and multi-regional energy planning May cover all or individual energy sectors, including heat, electricity and transport Main Assumptions Deterministic linear optimisation model - assumes perfect competition on energy markets. Driven by exogenously defined demands for energy services. These can be met through a range of technologies. Technologies consume resources, defined by their potentials and costs. Policy scenarios impose certain technical constraints, economic implications or environmental targets. Temporal resolution: consecutive years, split up into time slices with specific demand or supply characteristics, e.g., weekend evenings in summer. 36

An Introduction to OSeMOSYS A tested ability to Replicate Results Tested on standard model cases against established MARKAL modelling frameworks Derived from standard demonstration application used in MARKAL Region description: Lighting/Heating/Transport demands Multiple generation options Multiple Fuels Multiple time slices over for seasonal demand fluctuation Comparable results between both modelling structures 37

The Western African Power Pool Model Site Specific Hydro power Investments to measure the impact of climate change accurately Potential to investigate optimal mix of fossil, hydro, other RE, nuclear and trade to meet growth Power generation information comparable to the WAPP master plan 38

The link to the water modeling Inputs Outputs e.g. Energy Model T e c h n o l o g y D e Energy fors water processing Energy forcwater pumping Water available for hydropower r Water for ipower plant cooling p t i o n D e t a i l e d o p t i m a l Water Model c o s t 39 s

Model Design Features Common grounds with previous work Latest available IRENA- WAPP Energy model Current World Bank effort Electricity demand divided in 3 categories - heavy industry, urban and rural. Transmission and distribution losses vary for each category. Off-grid power generation examined closely. More than 25 power generating options for each country. Detailed assessment of existing, planned and potential power plants. Detailed assessment of both Fossil and Renewable Resource potentials 40

Model Design Features Some noteworthy improvements Latest available IRENA- WAPP Energy model Current World Bank effort Year split in 3 seasons with 3-4 day parts Year split in 12 months with 4 day parts for each season. for each month; greater detail Existing hydroelectric plants aggregated together for each country. Existing and potential hydroelectric plants modelled individually; increased flexibility Model horizon to 2030 with two tenyear steps to 2050 Year based study with modelling horizon to 2070 41

Analysis of Hydropower generation (Capacity Factor representation) Previous modelling efforts Capacity Factor 1 0.8 0.6 0.4 0.2 0 This project Capacity Factor 1 0.8 0.6 0.4 0.2 0 42

Regional Generation Mix Current OSeMOSYS results in regard to existing WAPP-Master Plan reference scenario Region 1200% 100% 90% 1000% 80% 70% 800% GW 60% 600% 50% 40% 400% 30% 20% 200% 10% 0% 0% This Project Baseline Including Total Regional Capacity And Volta generating capacity (13% of total in 2025) WAPP Master Plan 43

Reported Energy Model Runs Historical Wet (from giss_aom-b1) Dry (from ipsl-cm4-a2) NB: These runs include: - - Baseline model run against historic climate Investigation of wetter/dryer futures Investigation of higher/lower hydro capacities The runs are set up considering Full optimisation and therefore Perfect foresight from 2018 on. Corresponding consequences include less noticeable impacts on costs and hydro power Final work will include three levels of infrastructure constraint: Fixed infrastructure: Higher costs/harsher consequences Myopic investments: Some level of adaptation Full optimisation: best case/minimum impacts 44

Ghana Historic vs. Dry futures Generation mix comparison between historic and dry scenarios for the future climate Dry climate PJ Historical climate As compared to a historic case, the dry scenario sees a decrease of hydro generation by 46% replaced by 96 TWh of gas based generation 45

Ghana Historic vs. Wet futures Generation mix comparison between historic and wet scenarios for the future climate Wet climate PJ Historical climate The 23% increase in generation from Hydro displaces 44 TWh of Gas based generation. 46

Ghana Scenario deviations System operation changes as compared to historic climate Historical climate Wet climate The share of generation from Hydro increases by 2.6% under a wet future but decreases by 5.2% under a dry case. 47

Burkina Faso Historic vs. Dry futures Generation mix comparison between historic and dry scenarios for the future climate Dry climate PJ Historical climate 2.36 TWh and 1.03 TWh of repsectively Gas and Coal based generation replace 23% of historic case hydro generation. 48

Burkina Faso Historic vs. Wet futures Generation mix comparison between historic and wet scenarios for the future climate Wet climate PJ Historical climate The generation from Hydro increases by 17.6% under a wet future displacing coal and gas based generation. 49

Burkina Faso Scenario deviations System operation changes as compared to historic climate Historical climate Wet climate The share of generation from Hydro increases by 1.4% under a wet future but decreases by 1.9% under a dry case. 50

WAPP- Regional Unit cost of Electricity Baseline Scenario 100% 1200% 90% 70% 60% 50% 40% 30% 20% 1000% 800% USD/kWh 80% 600% 400% 200% 10% 0% 0% 51

Annex Volta Slides 52

Introducing Climate Projections 53

GOAL FOR FUTURE CLIMATE CHANGE SCENARIOS Provide the set of GCM scenarios that span a wide range of plausible Climate Change Possibilities No attempt to provide : Probability density Frequency analysis Extreme event focus

Within Latest IPCC AR5 Assessment

THE WORLD BANK PROJECT BASINS

Mean Annual Precipitation 2041 to 2050

VOLTA Mean Annual Precipitation 2001 to 2050

VOLTA Mean Monthly Precip & Temp2041 to 2050

VOLTA Mean Annual Precipitation 2041 to 2050