Document of The World Bank Report No: 87328-MZ PROJECT PAPER FOR A PROPOSED SMALL RETF GRANT FROM THE GLOBAL FACILITY ON DISASTER RISK REDUCTION AND RECOVERY IN THE AMOUNT OF EUR3.58 MILLION (US$4.90 MILLION EQUIVALENT) TO THE MOZAMBIQUE REGIONAL WATER AUTHORITY FOR THE SOUTH AND FOR A PROPOSED SMALL RETF GRANT FROM THE GLOBAL FACILITY ON DISASTER RISK REDUCTION AND RECOVERY IN THE AMOUNT OF EUR2.96 MILLION (US$4.05 MILLION EQUIVALENT) TO THE MOZAMBIQUE REGIONAL WATER AUTHORITY FOR THE ZAMBEZI FOR AN ENHANCING SPATIAL DATA FOR FLOOD RISK MANAGEMENT PROJECT Environment, Natural Resources, Water Resources Management and Disaster Risk Management, Practice 3 Africa Region CURRENCY EQUIVALENTS FISCAL YEAR January 1 – December 31 ABBREVIATIONS AND ACRONYMS ANE National Roads Administration (Administração Nacional de Estradas) ARA Regional Water Authority (Administração Regional de Águas) ARA-Sul Southern Regional Water Authority (Administração Regional do Águas de Sul) ARA-Zambezi Zambezi Regional Water Authority (Administração Regional do Águas de Zambezi) BCA Benefits Costs Analysis CENACARTA National Center for Cartography (Centro Nacional de Cartografia) CENOE National Operational Emergency Center (Centro Nacional Operativo de Emergência) CNA National Water Council (Conselho Nacional de Águas) CPS Country Partnership Strategy CRA The Council for the Regulation of Water Supply (Conselho de Regulação do Abastecimento de Água) CUT Single Treasury Account (Conta Única do Tesouro) CWRAS Country Water Resources Assistance Strategy DA Designated Account DRH Department of Water Resources (Departmento de Recursos Hídricos) DNA National Directorate of Water (Direcção Nacional de Águas) EIRR Economic Internal Rate of Return ENGRH National Water Resources Management Strategy (Estratégia Nacional de Gestão de Recursos Hídricos) FEWS NET Famine and Early Warning System Network GFDRR Global Facility on Disaster Reduction and Recovery GRDC Global Run-off Data Center GoM Government of Mozambique HCB Cahora Bassa Hydropower Plant (Hidroeléctrica de Cahora Bassa) IACM National Institute for Civil Aviation (Instituto de Aviação Civil de Moçambique) IDA International Development Association IFRs Interim Unaudited Financial Reports IIAM Mozambique Institute for Agrarian Research (Instituto de Investigação Agrária) INAHINA National Institute for Hydrography and Navigation (Instituto Nacional de Hidrografia e Navegação) INAM National Meteorological Institute (Instituto Nacional de Meteorologia) INAMAR National Maritime Authority (Instituto Nacional da Marinha) INE National Institute for Statistics (Instituto Nacional de Estatistica) INGC National Institute for Disaster Management (Instituto Nacional de Gestão de Calamidades) JTOC Joint Technical Operational Committee (Mozambique, Zambia and Zimbabwe) Lidar Light Detection and Ranging LIMCOM Limpopo Watercourse Commission M&E Monitoring and Evaluation MAR Mean Annual Runoff MICOA Ministry for Coordination of Environmental Affairs (Ministério para a Coordenação da Acção Ambiental) MOPH Ministry of Public Workings and Housing (Ministério das Obras Públicas e Habitação) MPD Ministry of Planning and Development (Ministério da Planificação e Desenvolvimento) MTC Ministry of Transport and Communication (Ministério dos Transportes e Comunicações) NPV Net Present Value O&M Operation and Maintenance PAMT Project Administration and Monitoring Team PARP Poverty Reduction Action Plan (Plano de Acção para a Redução da Pobreza) PDO Project Development Objective PIM Project Implementation Manual PA Water Policy (Política de Águas) PNDA National Water Development Program (Programa Nacional de Desenvolvimento de Águas) PPCR Pilot Program for Climate Resilience SADC Southern African Development Community SADCHYCOS SADC Hydrological Cycle Observation System SARCOF Southern Africa Climate Outlook Forum UGEA Procurement Unit (Unidade Gestora e Executora de Aquisições) ZAMCOM Zambezi Watercourse Commission ZRA Zambezi River Authority WMO World Meteorological Organisation Vice President: Makhtar Diop Country Directors: Mark Lundell Sector Director: Jamal Saghir Sector Manager: Magda Lovei Task Team Leader: Louise E.M. Croneborg MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project TABLE OF CONTENTS Contents I. STRATEGIC CONTEXT ......................................................................................................... 1 A. Country Context .............................................................................................................. 1 B. Sectoral and Institutional Context................................................................................... 1 II. PROJECT DEVELOPMENT OBJECTIVES........................................................................... 4 A. PDO................................................................................................................................. 4 B. Project Beneficiaries ....................................................................................................... 4 C. PDO Level Results Indicators ......................................................................................... 5 III. PROJECT DESCRIPTION....................................................................................................... 5 A. Project Components ........................................................................................................ 5 B. Project Financing ............................................................................................................ 6 C. Project Cost ..................................................................................................................... 7 IV. IMPLEMENTATION ............................................................................................................... 7 A. Institutional and Implementation Arrangements ............................................................ 7 B. Results Monitoring and Evaluation ................................................................................ 8 C. Sustainability................................................................................................................... 9 V. KEY RISKS AND MITIGATION MEASURES ................................................................... 10 A. Risk Ratings Summary Table ....................................................................................... 11 B. Overall Risk Rating Explanation .................................................................................. 11 VI. APPRAISAL SUMMARY ..................................................................................................... 11 A. Economic benefits and costs ......................................................................................... 11 B. Key financial management, procurement and safeguards issues .................................. 13 Annex 1: Results Framework and Monitoring .........................................................................15 Annex 2: Detailed Project Description .......................................................................................19 Annex 3: Implementation Arrangements ..................................................................................33 Annex 4: Simplified Operational Risk Assessment Framework .............................................40 Annex 5: Maps..............................................................................................................................43 DATA SHEET Mozambique Enhancing Spatial Data for Flood Risk Management Project Small RETF Grants Project Paper Africa AFTN3 . Basic Information Date: June 05, 2014 Sectors: General water, sanitation and flood protection Country Director: Mark Lundell Themes: Natural disaster management 30%, Water resources management 30%, and climate change 40% Sector Manager/Director: Magda Lovei/Jamal Saghir EA Category: C Project ID: P149629 Instrument: Small Recipient Executed Grants Team Leader(s): Louise E.M. Croneborg . Recipient Executing Agency: Southern Regional Water Authority (Administração Regional do Águas de Sul) Contact: Mr. Belarmino Chivambo Title: Director Geral Telephone No.: n/a Email: bchivambo@gmail.com Recipient Executing Agency: Zambezi Regional Water Authority (Administração Regional do Águas de Zambezi) Contact: Mr. Custodio Vicente Title: Director Geral Telephone No.: n/a Email: cvicentedna@yahoo.com . Project Implementation Period: Start Date: June 16, 2014 End Date: June 30, 2016 Expected Effectiveness Date: June 16, 2014 Expected Closing Date: June 30, 2016 . Project Financing Data(EUR M) [ ] Loan [ x ] Grant [ ] Other [ ] Credit [ ] Guarantee For Loans/Credits/Others (EUR M) Total Project Cost : 6.54 Total Bank Financing : 6.54 Total Cofinancing : 0.00 Financing Gap : 0.00 . Financing Source Amount(EUR M) BORROWER/RECIPIENT Global Facility for Disaster Risk Reduction & Recovery 3.58 Global Facility for Disaster Risk Reduction & Recovery 2.96 Financing Gap 0.00 Total 6.54 . Expected Disbursements (in EUR Million) Fiscal Year 2014 2015 2016 Annual 0 3.50 3.04 Cumulative 0 3.50 6.54 . Project Development Objective(s) To increase the capacity of Mozambique to prepare for and manage flood events in the Limpopo and Zambezi River basins. . Components Component Name Cost (EUR Millions) A. Limpopo River basin high-resolution Lidar survey 3.58 B. Zambezi River basin high-resolution Lidar survey 2.96 . Compliance Policy Does the project depart from the CAS in content or in other significant respects? Yes [ ] No [ x ] . Does the project require any exceptions from Bank policies? Yes [ ] No [ x ] Have these been approved by Bank management? Yes [ ] No [ ] Is approval for any policy exception sought from the Board? Yes [ ] No [ x ] Does the project meet the Regional criteria for readiness for implementation? Yes [ x ] No [ ] . Safeguard Policies Triggered by the Project Yes No Environmental Assessment OP/BP 4.01 x Natural Habitats OP/BP 4.04 x Forests OP/BP 4.36 x Pest Management OP 4.09 x Physical Cultural Resources OP/BP 4.11 x Indigenous Peoples OP/BP 4.10 x Involuntary Resettlement OP/BP 4.12 x Safety of Dams OP/BP 4.37 x Projects on International Waters OP/BP 7.50 x Projects in Disputed Areas OP/BP 7.60 x . Legal Covenants Name Recurrent Due Date Frequency Description of Covenant . Team Composition Bank Staff Name Title Specialisation Unit UPI Antonio Chamuco Sr Procurement Specialist Procurement AFTPC 222820 Celia dos Santos Faias Team Assistant Administration Management AFCS2 368252 Elvis Langa Financial Management Specialist Financial Management AFTFM 206490 Eric Foster-Moore Operations Analyst Water Resources AFTN2 407093 Esther Bea Team Assistant Administration Management AFTN3 435506 Francis S. Nkoka Disaster Risk & Climate Change DRM, Climate Change AFTN2 382675 Specialist George Ledec Lead Environment Specialist Environment AFTN3 014216 Hrishikesh Patel GIS Specialist GIS AFTN1 347802 José Janerio Sr Finance Officer Financial Management CTRLA 194575 Kristine Schwebach Sr Social Specialist Social development AFTCS 160145 Louise E.M. Croneborg Water Resources Management Hydro-Meteorological Services, AFTN2 351606 Specialist, Task Team Leader Water Resources Luz Meza-Bartrina Senior Counsel Legal LEGAM 174951 Marcus Wishart Sr Water Resources Specialist Water Resources AFTN2 279732 Rafael Saute Communication Specialist Communication AFRSC 249187 Roberto White Sr DRM Specialist GFDRR Coord. Mozambique GFDRR 345120 Sofia Bettencourt Lead DRM Specialist DRM GFDRR 023022 Non Bank Staff Name Title Office Phone City Guy Schumann Flood Hydraulics Specialist - Pasadena (USA) Kostas Andreadis Hydrologist/GIS Specialist - Pasadena (USA) Delwyn Moller Remote Sensing Specialist - Pasadena (USA) Donald McKeown Sr Researcher, Lidar - Rochester (USA) Jan van Ardt Associate Professor/Director - Rochester (USA) Jeff Lazo Sr Hydro-Met Economist - Denver (USA) . Locations Country First Administrative Division Location Planned Actual Comments Mozambique Southern Region Limpopo River Basin Mozambique Zambezi Region Zambezi River Basin . I. STRATEGIC CONTEXT A. Country Context 1. Mozambique is one of Africa’s fastest growing economies. In the decade leading up to 2012, annual economic growth consistently ranged between 6% and 8% per year 1 and in 2014, GDP is forecast to grow by 8%. Growth is driven largely by expanding extractive industries, such as coal and natural gas (38.2% real GDP growth in 2013) along with the transport and communications sector and financial services sector (16.1% and 15.2% real GDP growth 2013 respectively) 2. 2. The benefits of an expanding economy have not been equally shared and extreme poverty in Mozambique remains prevalent. Although per capita GDP grew by 4.7% in 2012 to US$565, it is still well below the average of developing countries in Sub-Saharan (US$1,417). Mozambique has a GINI index of 45.7, indicating substantial income inequality. Agriculture generates nearly 30% of economic output and employs 77% of the labor force, yet growth in the agricultural sector was 5.8% in 2013. Best estimates place unemployment between 17% and 20% of the population. The sub-5 child mortality rate is 89.7 per thousand, nearly 40% of the population is malnourished, and 55% of the population lives below the national poverty line. Life expectancy at birth is 49 years and Mozambique now ranks 185 out of 187 countries on the UNDP’s Human Development Index. 3. In scenarios developed through the Intergovernmental Panel on Climate Change (IPCC) and the Global Circulation Models, significant changes in climate patterns are predicted for Mozambique. Rainfall may decrease by 31% to 16%, sea level rise could reach 2.17mm per year in southern populated areas of Maputo (±0.76mm/year) 3 and average temperature could increase by 1-2°C by the 2050. It’s estimated that climate change could result in 4% to 14% GDP losses relative to 2050 projections. B. Sectoral and Institutional Context 4. Mozambique is vulnerable to the impacts of natural hazards such as floods, cyclones and droughts. With 2,740km of coastline, where roughly 60% of the population lives, and located downstream of nine internationally shared rivers, Mozambique is exposed to cyclones and floods resulting from extreme weather events in the region. In more arid regions, droughts are prevalent and reoccurring. In recent years, major floods have hit Mozambique in the years 2000, 2001, 2007 and 2013 (collectively resulting in over 1,200 deaths, displacement of 1.5 million and destruction of US$1.5 billion in physical infrastructure). Best estimates suggest that as much as 58% of the population is vulnerable to natural disasters and that annual economic growth is 1.1 percentage points lower than it otherwise would be, as a result of weather and water shocks. 5. In 2013, extreme floods hit Mozambique in the lower stretches of the Limpopo, Incomati, and Zambezi River basins. The impacts were felt in urban centers and rural communities in the provinces of Gaza, Maputo, Zambezia, and Sofala. Over 170,000 people were evacuated, 113 lives were lost, and 89,000 hectares of crops were destroyed, making this the worst disaster to hit Mozambique since the floods of 2000. Other damages include destruction of 47,000 hectares of the most productive cropland, significant damage to the country’s largest irrigation scheme, 1 World Bank Mozambique Economic Update (April 2014) 2 Ibid. 3 IPCC Climate Change 2007: impacts, adaptation and vulnerability (Cambridge University Press, 2007) 1 severe damage to the health and education systems, transport infrastructure, municipal water supply systems, urban drainage and sanitation systems, and flood protection dykes. Flooding forced the closure of the Chokwé hospital and eight additional health centers, destroyed 238 classrooms and damaged 450 more, and stagnant flood water increased the risk of diseases such as malaria and schistosomiasis. Substantial damage was also inflicted to the railway line linking the Maputo port to Zimbabwe, major bridges, major national roads, and the unpaved road system across the Limpopo valley. As a result, the food security and livelihoods of the entire population, and especially of more than 48,000 smallholder and subsistence farmers, remain threatened. An assessment carried out by the World Bank in response to the disaster estimated that short-term physical damages alone were in the order of US$403 million, of which immediate physical restoration costs are estimated at US$127 million, primarily in roads, water infrastructure (dykes, weirs and levees) and agriculture-related infrastructure. 6. High-resolution spatial/topographic data, also called digital elevation models (DEMs) is required for estimating potential extent and impacts of floods. At present, the resolution of spatial data and DEMs available for modeling in the Limpopo and Zambezi River basins are limited to 90m-by-90m grid-pixel data that is sourced through the SRTM satellite (Shuttle Radar Topography Mission) and made available freely through NASA 4. In the low-lying areas of the lower stretches of the two flood-prone basins, this resolution is inadequate for hydrological and hydraulic modeling and risk analysis or risk management. 7. The institutional mandate for water resources management lies with the Ministry of Public Works and Housing (MOPH, Ministério das Obras Públicas e Habitação), the National Directorate of Water (DNA, Direcção Nacional de Águas – Ministerial Decree 142/2012) and the five Regional Water Authorities (ARAs, Administrações Regionais de Águas – Water Law 16/1991 addendum). The DNA combines the responsibility for policy making, implementation, planning and management of water resources, and of water supply and sanitation services. The strategic activities undertaken by DNA are operationalised by the five ARAs. 8. The ARAs are public institutions reporting to the MOPH tasked with the operational management, allocation and licensing of water resources. They are also responsible for hydrological monitoring and modeling and operating water infrastructures. Strategic guidance and technical support for water resources management is provided by DNA to the ARAs. The ARAs coordinate directly with agencies such as: the national meteorological services (INAM, Instituto Nacional de Meteorologia), the disaster risk management agency (INGC, Instituto Nacional de Gestão de Calamidades), the national roads agency (ANE, Administração Nacional de Estradas), amongst others. There are five ARAs for the southern, central, Zambezi, central- north and northern region (ARA-Sul, ARA-Centro, ARA-Zambezi, ARA-Centro Norte and ARA-Norte). The first, ARA-Sul, was established in 1992. 9. The institutional and operational mandate for disaster and crisis management lies with the INGC. The INGC is an autonomous institution under the Ministry of State Administration (Ministério da Administração Estatal) with a strong coordinating and crisis-response function. INGC also manages day-to-day matters related to disaster preparedness and response, including coordination and communication (e.g., issuing of alerts at national, provincial and district levels). 10. Mozambique’s FY12-15 Country Partnership Strategy is based on two pillars, the second of which is decreasing vulnerability and increasing resilience. Specifically, the second of Pillar II’s 4 The models available in the two ARAs, but in limited use, are HECRAS, MIKE11, Waflex WEAP and FloodWatch. 2 three objectives is to improve resilience to natural disasters and the impacts of climate change. The CPS acknowledges that Mozambique’s extreme exposure to weather-related hazards, highlights the significant destructive impact of floods, cyclones, and droughts, and identifies climate change mitigation and adaptation activities as a new and important business line. The CPS is aligned with Mozambique’s own poverty reduction strategy, the Plano de Acção de Redução de Pobreza (PARP), which calls for broad-based and inclusive growth through reduction of vulnerability to natural disasters and the threat of climate change. 11. In addition, the Project will build on the World Bank Country Water Resources Assistance Strategy for Mozambique (CWRAS, 2009) by enhancing geomorphological, hydrological and meteorological data for the core operation of water resources planning, infrastructure development, transboundary cooperation with neighboring countries, and disaster risk management. 12. Finally, the proposed small grants are closely aligned with the objectives of the portfolio of World Bank support in Mozambique, with focused efforts in the Limpopo and Zambezi River Basins (see Annex 2). These include the following projects: - Climate Resilience: Transforming Hydro-Meteorological Services Project (P131049, US$15m Pilot Programme for Climate Resilience, PPCR). Objective: to strengthen the national hydro-met services through investments in physical networks of stations monitoring water and weather, technical and human capacity, forecasting and modeling technologies, data sharing and ability to meet user needs (including improved warnings). - National Water Resources Development Project (P107350, US$70m IDA). Objective: to support national water resources management through institutional strengthening and planning, and through augmenting the availability of bulk water to the greater Maputo metropolitan area through investment rehabilitation of the Corumana Dam. - National Water Resources Development Flood Response, Additional Financing (P146098, US$32m IDA Crisis Response Window). Objective: to enable emergency rehabilitation of civil works in the Limpopo River basin (in particular dykes and levees), and longer-term interventions informed through integrated flood management and mitigation studies. - Roads & Bridges Management & Maintenance Programme (P146402, US$186.9m IDA). Objective: to improve road infrastructure and rehabilitation of the national and connected roads and bridges affected by the floods of 2013. - Programmatic Support for Disaster Risk Management (P124755, US$1.4m GFDRR). Objective: to strengthen the early warning systems through rehabilitation of Doppler Radars, and to design and pilot mitigation activities in highly vulnerable areas. 13. At the regional level, the grants will further align and reinforce ongoing and planned Bank support within the Zambezi River basin. The data collected under the proposed project will, in the future, support development and management activities conducted at the transboundary level, such as hydropower feasibility studies, flood risk analyses, and basin-wide hydrologic models. Specifically, this includes the following projects at present: - Zambezi River Management Program (P143546, US$4m CIWA). Objective: to provide support to the Zambezi Watercourse Commission (ZAMCOM) to strengthen cooperative management and development within the basin. In particular, the program will support the continued development of the Zambezi Water Information System (ZAMWIS) which will 3 serve as a platform for collecting, distributing, and visualising relevant hydrologic and environmental data. - Zambezi River Basin Development Project (P133380, US$6m CIWA). Objective: to advance preparation of the Batoka Gorge Hydro-Electric Scheme and strengthen cooperative development within the Zambezi River basin. II. PROJECT DEVELOPMENT OBJECTIVES A. PDO 14. The Project Development Objective (PDO) is to increase the capacity of Mozambique to prepare for and manage flood events in the Limpopo and Zambezi River basins. B. Project Beneficiaries 15. The direct project beneficiaries are the two institutions mandated with water resources management in the Limpopo and Zambezi River basins: the Regional Water Authority for the South (ARA-Sul, Administração Regional de Águas do Sul) and the Regional Water Authority for the Zambezi (ARA-Zambezi, Administração Regional de Águas do Zambezi) respectively. These two institutions will serve as the immediate custodians of the project. The two ARAs will be responsible for managing the acquisition and outputs of the detailed high-resolution spatial and topographical surveys, including the management and processing of resulting data, as well as making the raw data and developed derivative information products available and useable to other agencies. Involvement and close collaboration will be necessary with the National Directorate for Water (DNA, Direcção Nacional de Águas), National Institute for Disaster Management (INGC, Instituto Nacional de Gestão de Calamidades), the National Center for Cartography (CENACARTA, Centro Nacional de Cartografia), the National Institute for Statistics (INE, Instituto Nacional de Estatistica) along with the National Meteorological Institute (INAM, Instituto Nacional de Meteorologia) and the National Roads Administration (ANE, Administração Nacional de Estradas), amongst others. 16. The indirect project beneficiaries are people, communities, and businesses at risk of water and weather related hazards. Improved information about flood-related hazards can both lower the exposure to risks and increase productivity. This includes approximately 450,000 people living in the middle and lower Limpopo River basin and 313,000 in the lower Zambezi River basin in Mozambique. The target area in the Limpopo is one of the more populated areas of Gaza, Inhambane and Maputo Provinces. It comprises around 253 small villages and important settlements such as the provincial capital Xai-Xai (115,752 inhabitants), and district capitals Chibuto (63,184 inhabitants), Chokwé (53,062 inhabitants) and Guijá (28,492 inhabitants). 17. During preparation, preliminary priority survey areas were identified in the two basins. Population estimates for these Lidar survey areas are 164,200 in the Limpopo and 156,600 in the Zambezi 5. The people who live in these areas will benefit through increased information about the immediate and long-run risks of water and weather related hazards. Indirectly, a number of key private sectors will benefit - from commercial farmers and power utilities, to telecommunication and construction companies. These minimum estimates of direct beneficiary may increase as survey areas are refined. 5 Source for population data: NASA SEDAC. 4 18. A gendered dimension exists among beneficiaries, partly because there is increasing ‘feminisation’ of both vulnerability and small-scale farming in Mozambique 6. Analysis of the social impact from climate change conducted in Mozambique emphasises that women and girls will be more affected in drought-prone areas, for example, because of the increase in time spent on activities such as water collection. C. PDO Level Results Indicators 19. The proposed Project Development Objective level indicators are: • Flood preparedness improved through updated & utilised Contingency Plan led by INGC in the Zambezi and Limpopo • Flood risk identification improved through creation of probabilistic flood risk hazard maps for the Limpopo and Zambezi survey areas • Flood risk reduced through use of new geospatial data to ‘build-back-better’ infrastructure • Improved accuracy of areas and populations at risk of 100-year flood in the Limpopo and Zambezi with improvement to Early Warning Systems • Direct Project Beneficiaries (number) – Core indicator • Direct Female Project Beneficiaries (% of total direct project beneficiaries) – Core indicator III. PROJECT DESCRIPTION A. Project Components 20. The project will support: the acquisition of high resolution spatial and topographic data through airborne Lidar 7 (Light Detection and Ranging) and co-registered orthophotography surveys; the subsequent production of digital elevation models (DEMs); derivative information products such as land cover/use classification maps and breaklines; the incorporation of those products into hydrologic models, hydraulic models, and decision support systems; and, the application of those models to flood and natural disaster risk management. 21. Two survey operations will be conducted in parallel, one in the Limpopo River basin and one in the Zambezi River basin. Potential survey sites within each basin will be ranked and prioritised by the degree to which high-resolution elevation models of their terrain will improve modeling accuracy and inform decision making and planning in the basins (for example zoning for disaster risks or key infrastructure). A detailed description of the project, including Lidar technology, the utility of DEMs, and their broader applications is presented in Annex 2. 22. The project will consist of two small recipient-executed grants implemented in parallel by ARA-Sul and ARA-Zambezi, respectively, with each grant constituting one of the project’s two components. The grants will finance: 6 In Chibuto District southern Mozambique, for example, male migration results in women representing 57% of total population. Africa Climate Change Resilience Alliance Understanding adaptive capacity at the local level in Mozambique (2012). 7 Light Detection and Ranging, Lidar, is a remote sensing technology that measures distance by bouncing a laser off a target and analysing the reflected light. When flown in an airborne survey, Lidar can be used to scan large swaths of terrain and create three dimensional models of the terrain surface (see Annex 2, Section E and F for detailed information on Lidar technology). 5 23. Component A. Limpopo River basin high-resolution Lidar survey (ARA-Sul, EUR3.58 million, GFDRR 8). Component A will be implemented by ARA-Sul in close collaboration with DNA and INGC, as well as key stakeholder agencies. 24. Component A includes the following activities: A1) Technical Assistance for implementation of Limpopo Lidar assignment, including quality control and strategic guidance; A2) Determination of priority Survey Areas of the Limpopo recognising already surveyed areas in the lower Limpopo and agreed priority areas and assets (including roads, settlements, bridges and areas at risk of flooding); A3) Acquisition and completion of Limpopo Lidar Survey (including all logistics, permits, and aerial and field operation); A4) Processing and quality assurance review of acquired Lidar point data for open access, long-term use and all possible applications; A5) Integration of Lidar data into existing models and decision support systems, and establishment of new ones (including mapping, hydrological and hydraulic modeling, disaster risk tools etc.); A6) Long-term training and capacity building for technical staff in ARA- Sul, DNA, INGC and associated agencies working in the Limpopo River basin; A7) Effective data management systems and solutions to ensure Lidar data and derivative projects from the Limpopo River basin are easily and openly accessible; and, A8) Investments into physical Information Management Systems (IMS) to ensure long-term accessibility and use of Lidar data and derivative products, including reinforcing IT infrastructure and internet access. 25. Component B. Zambezi River basin high-resolution Lidar surveys (ARA-Zambezi, EUR2.96 million, GFDRR). Component B will be implemented by ARA-Zambezi in close collaboration with DNA, INGC and other key stakeholder agencies. 26. Component B includes the following activities: B1) Technical Assistance for implementation of Zambezi Lidar assignment, including quality control and strategic guidance; B2) Determination of priority Survey Areas of the Zambezi recognising surveyed areas in the Shire River basin and agreed priority areas and assets (including roads, settlements, bridges and areas at risk of flooding); B3) Acquisition and completion of Zambezi Lidar Survey (including all logistics, permits, and aerial and field operation); B4) Processing and quality assurance review of acquired Lidar point data for open access, long-term use and all possible applications; B5) Integration of Lidar data into existing models and decision support systems, and establishment of new ones (including mapping, hydrological and hydraulic modeling, disaster risk tools etc.); B6) Long-term training and capacity building for technical staff in ARA-Zambezi, DNA, INGC and associated agencies active in the Zambezi River basin; B7) Effective data management systems and solutions to ensure Lidar data and derivative projects from the Zambezi River basin are easily and openly accessible; and, B8) Investments into physical Information Management Systems (IMS) to ensure long-term accessibility and use of Lidar data and derivative products, including reinforcing IT infrastructure and internet access. B. Project Financing 27. Financing for the two recipient executed small grants comes from contributions from the United Kingdom’s Department for International Development (DfID) to the World Bank managed trustfund, the Global Facility on Disaster Reduction and Recover (GFDRR). Following the floods of January and February 2013, DfID has provided two allocations to the GFDRR Track 3 (Sustainable Recovery) in the order of EUR3.58 million and EUR2.96 million. The two 8 Multidonor trustfund Global Facility on Disaster Reduction and Recovery. 6 allocations will form the two recipient executed small grants for Component A (ARA-Sul) and Component B (ARA-Zambezi) respectively. C. Project Cost Table 1. Project components Project Component Project Cost Grant Financing Financing (EUR millions) (GFDRR, EUR millions) A. Limpopo River basin high-resolution Lidar surveys 3.58 3.58 100% B. Zambezi River basin high-resolution Lidar surveys 2.96 2.96 100% Total Project Costs 6.54 6.54 100% IV. IMPLEMENTATION A. Institutional and Implementation Arrangements 28. The two recipient executed small grants from the GFDRR will be implemented by the two Regional Water Authorities, ARA-Sul and ARA-Zambezi. The ARAs were established in 1992 by an addendum to the Water Law (No. 16/1991). ARA-Sul was the first ARA to be established. The ARAs are semi-autonomous institutions who report to the Ministry for Public Works and Housing (MoPH, Ministério das Obras Públicas e Habitação) and receive strategic and management guidance from the National Directorate for Water (DNA, Direcção Nacional de Águas). 29. Component Coordinators within both ARA-Sul and ARA-Zambezi will be responsible for the technical management and delivery of each component and their respective activities. There is strong alignment of the Lidar surveys with the activities under the National Water Resources Development Project (P107350), the Emergency Flood Response Additional Financing (P146098) and the Transforming Hydro-Meteorological Services Project (P131049), where the outputs will be mutually beneficial. Responsibilities for ongoing activities under the associated projects are already established. Therefore, the new activities under the proposed small grants will be harmonised with existing staff resources to the extent possible (also because the ARAs, DNA and INGC experience constraints in staff capacity and availability). The technical work related to the development of the technical content of the bidding documents for the Lidar surveys and the prioritisation of the areas to be surveyed will be completed by staff within ARA-Sul and ARA-Zambezi, respectively, with support provided by DNA, INGC and other government agencies (Technical Assistance will also provide support during implementation). 30. The Project Administration and Monitoring Team (PAMT) in DNA will be responsible for procurement, financial management and coordinating progress reporting. In 2012, the PAMT was set up with funds from the National Water Resources Development Project within DNA. The PAMT includes a Project Manager, Procurement Specialist, Financial Management Specialist, a Monitoring & Evaluation Officer, and administrative support staff. The PAMT will extend its support to provide the same services and functions for the new proposed grants. Their core tasks will include: supervising and managing procurements, financial management and reporting, and coordinating reporting on progress of implementation and results. 31. The airborne Lidar surveys will be flown by a specialised contractor(s). The firms providing the non-consultancy service of Lidar surveys will be contracted through a competitive 7 bidding process in adherence with the World Bank’s Procurement Policies and Guidelines of January 2011. 32. Inter-agency coordination is critical for successful results, and will build on existing platforms for coordination on water resources and floods in Mozambique. During preparation, focal points have been identified and mandated to support coordination amongst the key agencies of the ARAs, DNA and INGC. This group will continue to collaborate during implementation and extend the engagement to other key agencies by engagement through existing platforms for coordination. These include the Technical Council for Disaster Management, the inter-agency working group on hydro-meteorological services and the collaborative groups of previous Lidar survey of the lower Limpopo in 2012 (P124755 GFDRR). 33. Access to Lidar survey data and maps can strengthen basin-level cooperation in the Limpopo and Zambezi River basins. Mozambique is the last downstream riparian of both river basins. The country is active in the two basin organisations, namely the Limpopo Watercourse Commission (LIMCOM) and the Zambezi Watercourse Commission (ZAMCOM). Both the 2003 Agreement on the Establishment of the Limpopo Watercourse Commission9 (ratified in 2010) and the 2004 Agreement on the Establishment of the Zambezi Watercourse Commission10 (ratified in 2011) emphasise and provide for the sharing of information required for early flood warnings and protection of lives and assets. Under LIMCOM and ZAMCOM there are also ongoing efforts to strengthen information sharing systems, including harmonisation of hydrological modeling and data. In addition, there are topographical surveys in neighbouring riparian countries, which will facilitate hydrological modeling of floods across the basin once the Digital Elevation Models are merged and harmonised (so called hydrological conditioning). Early engagement with the riparian neighbors will facilitate successful project implementation. Figure 1. Implementation Arrangements National Directorate for Water (DNA) Cooperation and involvement of key Project Administration & Monitoring Team (PAMT) Government agencies and stakeholders Department for Water Resources (coordin.) INGC - National Institute for Disaster Management INAM - National Institute for Meteorology CENACARTA - National Center for Cartography Regional Water Authority of Regional Water Authority of INE - National Institute for Statistics the South (ARA-Sul) the Zambezi (ARA-Zambezi) CENOE - National Operational Emergency Center ANE - Roads Administration Component A Coordinator Component B Coordinator MINAG - Ministry for Agriculture DNSA - National Directorate for Agriculture UEM - University of Eduardo Modlane Others. Specialist firms / Technical Assistance B. Results Monitoring and Evaluation 34. The ‘results-chain’ of project outputs through to outcomes follows a set of interventions funded by the Project. To begin, the project will enable the collection, creation, and analysis of digital elevation and land cover data as a project output to strengthen the work of water resources and disaster risk management sector agencies (i.e., in particular DNA, ARAs and INGC). An airborne survey, to collect Lidar data and aerial photographs, will be flown over priority sections 9 http://www.icp-confluence-sadc.org/riverbasin/96 10 http://www.zambezicommission.org/index.php 8 of the Limpopo and Zambezi River basins. The raw data will then be processed by the survey contractor and turned over to the implementing agencies as raw data and in the form of digital elevation models (DEMs) and other derivative data products such as breaklines and land cover classification maps. Once this transfer has been made, the implementing agencies will begin incorporating the output data into hydrologic and hydraulic models to generate project outcomes such as emergency planning, risk identification, and risk reduction. 35. For example, one of the several outcomes of this process will be flood hazard maps, which delineate flood plains across a range of return periods. When combined with other spatial data layers, these maps will allow the government to identify vulnerable populations, communities, and infrastructure, and to strengthen emergency response plans through simulations. The resulting DEMs will inform hydraulic and hydrologic models that will be strengthened through this Project (linked to those developed under the Transforming Hydro-Meteorological Services Project, P131049). Such improved models can inform: physical works such as the siting and design of dikes, levees, and river defense infrastructure; broadly for design and siting of the built environment; urban planners designing storm water runoff management systems; and transportation engineers in the design of roads; amongst others. 36. Monitoring and evaluation (M&E) of results from the grants will be integrated as part of the quarterly Progress Reporting that the Project Administration and Monitoring Team (PAMT) puts together on a quarterly basis. The Component Coordinators for each grant in each respective ARA will be responsible for the monitoring and evaluation of the project and submit this data to the PAMT as they put together the progress reports. M&E can help guide management and staff in the ARAs as part of their monitoring of whether implementation is on track to achieve the expected outputs and outcomes. M&E procedures are the same as those set up under the other associated World Bank investments (e.g., National Water Resources Development Project, P107350 and the Transforming Hydro-Meteorological Services Project, P131049). The implementing agencies are obliged, in accordance with the grant agreements, to report on results as agreed in the Project’s Results Framework (see Annex 1). The reporting on results is presented in the quarterly Progress Reports that are sent from the PAMT to the Bank. During the World Bank’s bi-annual Supervision Missions, the results will be discussed and reported on in the Bank’s Aide Memoires and Implementation Status Reports. The Bank and the implementing agencies will undertake an implementation completion report upon project closing. 37. As part of the Bank’s implementation support, progress of the project will be captured in the Mission Aide Memoires and Implementation Status and Results Reports (ISRs) and an Implementation Completion and Results Report (ICR) on completion. C. Sustainability 38. Sustainability of the high resolution spatial and topographical data acquired through the use of Lidar and derivative information products will rely on technical skills of key staff, absorption capacity of beneficiary agencies, technical ability for existing models to integrate DEM derived using Lidar, as well as ability to initiate new models/applications. There will be open access and effective accessibility to the data produced from the Lidar surveys in order to enable and maximise results and usefulness of the project investments. 9 V. KEY RISKS AND MITIGATION MEASURES 39. The overall risk rating of the two grants is ‘Low’. The investments of the two grants focus primarily on the acquisition of spatial data through airborne Lidar surveys and subsequent processing of the data into useful information products. The activities are considered straight forward and not too complex to stall implementation. There are no physical investments that would cause negative environmental and social impacts, and as such the overall risk is considered ‘low’. In addition, the two grants will be implemented with the project management and administrative support of the Project Administration and Monitoring Team (PAMT) in the DNA which provides a mitigation measure to project management responsibilities in the areas of procurement, financial management and reporting on progress (harmonised with ongoing World Bank investments outlined in Section IV). The PAMT is familiar with the Bank requirements and has established routines that will be applied to the two grants. 40. Despite the overall risk rating, the following risks and mitigation measures have been identified: 41. There is a risk that seasonal and immediate weather conditions may delay or reschedule the planned Lidar surveys. The surveys are planned to be undertaken between April and October, which is the dry season providing optimal survey conditions. Procurement of the Lidar surveys will be through a competitive bidding for two separate areas of work, one through ARA-Sul and one through ARA-Zambezi. Field work poses operational issues due to scarce logistical support to perform long and continuous flights in the most remote areas but these problems are can be handled by experienced companies with proven experience of working in these environments. 42. There are risks to the sustainability of the datasets and the development of associated applications. Ensuring sustainable management of the resulting datasets (access and availability of data and update by other government agencies) requires strong institutional coordination and trained staff in all partner government agencies (INGC, INAM, DNA and ANE). Training will be provided by Project and institutional arrangements will be strengthened in order to facilitate data sharing. The risk will be mitigated by ongoing efforts by the Government to adopt a Protocol on data sharing amongst key agencies in the areas of hydro-meteorology and disaster risk management. This effort is supported by the World Bank’s Climate Change Development Policy Lending operation and the operationalisation of the said Protocol is partly financed by the Transforming Hydro-Meteorological Services Project (through the implementation of an integrated data management platform). 43. There is a low risk of limited use of the acquired data sets due to potential lack of ‘uptake’ of the data amongst the agencies and associated projects. However, direct applications of data have already been identified, including above-mentioned associated Bank investments. Recipient entities have identified following applications: flood inundation and risk mapping, dam break analyses, environmental flow applications, spatial planning and urban development, flood response and emergency evacuation plans, amongst others. 44. There is a low risk associated with the sensitivity of acquired spatial data. Sensitivity over use of data could mean that relevant authorities would not provide authorisation for required fly- bys. The end benefits can help mitigate these risks. ARA-Sul and ARA-Zambezi have ongoing collaborations with associated authorities within Mozambique and amongst the riparians which will facilitate the coordinating the logistical arrangements and necessary approvals. 10 45. Environmental Category C. The project will not support any on-the-ground physical works and is therefore classified as environmental Category C. A. Risk Ratings Summary Table Stakeholder Risk Risk Rating Mitigation measures Implementing Agency Risk - Capacity Moderate Expert consultations and trainings - Governance Moderate Supervision of procurement processes Project Risk - Design Low Expert consultation and guidance - Social and Environmental Low N/A - Program and Donor Low Coordination with associated projects - Delivery Monitoring and Sustainability Low Follow-up consultations and trainings Overall Implementation Risk Low B. Overall Risk Rating Explanation 46. The overall risk rating is ‘Low’ because the proposed activities have strong operational linkages to associated investments (especially the National Water Resources Development Project, P107350, the Transforming Hydro-Meteorological Services Project, P131049 and the Roads & Bridges Management & Maintenance Programme, P146402). Moreover, the implementing agencies are familiar with the benefits and use of the proposed Project activities as well as with World Bank processing. The fiduciary risks of the proposed Project are considered low and there are no environmental and social safeguards policies triggered under the Project. The risks associated with governance and capacity are, however, rated moderate as the Project Administration and Monitoring Team (PAMT) within the National Directorate for Water experienced delays in proceeding with procurements as planned in the recent year, in part due to the substantial increase in workload due to the floods of January 2013. VI. APPRAISAL SUMMARY A. Economic benefits and costs 47. The economic benefits from acquiring enhanced spatial data in the lower Limpopo and Zambezi River basins, translating into more accurate and timely estimates of flood impact, outweighs the economic costs for procuring the Lidar surveys and developing derivative information products. 48. During preparation, the economic benefits from Lidar-derived flood management in the Zambezi were estimated to amount to US$1.94bn. To estimate the economic benefits, an extreme 1:10,000 years return period flood was first modeled across the lower Zambezi River basin (with a flow of 70,000m3/s at the city of Tete) to estimate the areas of impact using the available 90x90 meters resolution DEM (from the SRTM – shuttle radar topography mission). Then, priority areas were modeled within the lower basin to show where Lidar data could significantly improve 11 flood estimates. The improved flood assessment accuracy increased by 30.8%. To estimate the economic impact of such improved accuracy, a set of measurements were used as proxies for economic statistics for the priority areas: ‘luminosity’ to characterise population, poverty and economic productivity (i.e., nighttime light) 11; downscaled GDP data 12; and population density projections for 2015 13. These proxies for the priority areas estimated a total value of US$6.3bn for the areas and it was assumed that 30.8% improved accuracy in flood assessment could translate into a value of US$1.94bn. 49. The economic value of assets and productivity in the Lidar-survey areas of the Limpopo were also estimated, amounting to US$2.44bn. Contrary to the Zambezi, a hydraulic simulation is not available for the Limpopo and the floodplains already have some Lidar surveys acquired. Proxies for economic activities were applied (using same methodology as for the Zambezi) showing that the value of economic activity and assets amount to approximately US$2.44bn for the priority areas to be surveyed within the lower Limpopo River basin. 50. The value of high-resolution DEMs is high. They represent a permanent data and information asset that will be utilised in the near term while also remaining relevant for repeat use in the longer term in multiple sectors, and of utility to a wide range of physical planning stakeholders. Lidar enables more judicious and targeted planning of development, reducing risks and costs of poorly designed and located infrastructure and of subsequent damage due to flood events. Although it is difficult to define exact economic benefit of using high-resolution digital elevation models, compared to other techniques, the benefit attribution to Lidar also include: time and effort saved on surveying (particularly in difficult terrain), higher precision of maps, flexibility of areas surveyed and reduced environmental footprint. Several sector/application-specific studies estimate high rate of return on investments. For example, Lidar was estimated to give a 17% IRR in economic output for a wind farm in the UK compared to other techniques 14. 51. Though Lidar is expensive 15, ground-based surveys are infeasible for covering areas as large as the basins in question. The DEM option available to do basin-level modeling of floods is the freely and globally available SRTM. However, given that the horizontal resolution of the SRTM is 90x90 meters, it is not useful for the localised flood mitigation or for low-lying floodplain areas. Airborne Lidar surveys are regarded as the most practical and cost-effective method for generating DEMs at a large scale and with required high resolution. The exact cost of the surveys themselves depends on local market conditions, the area to be covered, the data products to be produced, and the degree of difficulty of mobilising an aircraft to the survey location. 52. During project implementation, the Bank’s team will be supporting further economic analysis as a designated activity area of the World Bank team’s implementation supervision. The more detailed economic analysis during implementation will deepen and strengthen the understanding of what value the technical Lidar work has to development outcomes, as well as informing the Government’s resource allocation and investments. The Bank’s team would present the economic analysis as part of project reporting from Missions. 11 Measurements of luminosity at high resolution of 1km has shown high correlation with GDP. Data from the US Department of Defense Satellites, 2012. 12 Data from the G-Econ project. http://geocon.yale.edu 13 NASA Socioeconomic Data and Application Center (SEDAC) 14 Sgurr Energy, 2012. 15 Approximately US$240/km2. 12 B. Key financial management, procurement and safeguards issues 53. Procurement & Financial Management. The implementing agencies have agreed that the Project Administration and Management Team (PAMT) in DNA will manage the overall fiduciary tasks as they already have specialists in financial management and procurement, and the proposed set up creates more streamlined and integrated procedures. 54. Within the DNA, the PAMT was set up under the National Water Resources Development Project (P107350) in 2012. The PAMT includes a Project Manager, Procurement Specialist, Financial Management Specialist, a Monitoring & Evaluation Officer and administrative support staff. The PAMT will provide the same functions, in terms of ensuring procurement, financial management and regular reporting requirements. 55. A Financial Management Assessment of the DNA was carried out in accordance with the Financial Management Manual for World Bank-Financed Investment Operations issued by the Financial Management Sector Board on March 01, 2010. The objective of the assessment was to determine whether the implementing agency has acceptable financial management arrangements, which will ensure that: (i) the funds are used only for the intended purposes in an efficient and economical way, (ii) accurate, reliable and timely periodic financial reports are prepared, and (iii) the agency assets are safeguarded. The overall conclusion of the Financial Management Assessment is that the project’s financial management arrangements satisfy the World Bank’s minimum requirements under OP/BP 10.00. The project financial management arrangements have an overall residual risk rating of Moderate. 56. Procurement will be carried out in accordance with the World Bank's "Guidelines: Procurement of Goods, Works and Non-consulting Services under IBRD Loans and IDA Credits and Grants by World Bank Borrowers" published by the World Bank in January 2011 ("Procurement Guidelines"), in the case of goods, works and non-consulting services; and "Guidelines: Selection and Employment of Consultants under IBRD Loans and IDA Credits and Grants by World Bank Borrowers" published by the World Bank in January 2011 ("Consultant Guidelines") in the case of consultants' services, and the provisions stipulated in the Grant Agreement. Further, the “Guidelines on Preventing and Combating Fraud and Corruption in Projects Financed by IBRD Loans and IDA Credits and Grants”, dated October 15, 2006, and revised in January 2011 will apply. 57. The capacity of the PAMT to manage the additional procurement activities under the grants has been reviewed and it is recommended that the procurement function of the PAMT be enhanced through a recruitment of a junior procurement officer 16, to support the existing procurement officer, for a period of 12 months, in view of the additional workload. 58. The existing procurement procedures and Manual under the National Water Resources Development Project (P107350/ P146098) will be used for the Project. However, the Manual will be updated to reflect the particular features of the project. 59. The coordination between the PAMT and the beneficiary institutions will be critical in ensuring timely implementation of agreed activities. 16 The additional procurement staff will be trained by UGEA-unit in DNA and supported by the Strategic Technical Assistance contracted by DNA under the NWRDP P107350. 13 60. A procurement plan has been prepared under the coordination of DNA and will be updated at least annually (or as required) to reflect project implementation needs. 61. Safeguards. The activities planned under the two grants do not trigger the World Bank’s ten Operational and Bank ‘Safeguard’ Policies related to any social and environmental impacts and management of mitigation measures. 14 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project ANNEX 1: RESULTS FRAMEWORK AND MONITORING Cumulative Target Values Data Collection and reporting WB Core Baseline (2014) Unit Results Indicators Data Responsibility FY16/Q4 Description (indicator FY15/Q2 FY15/Q4 FY16/Q2 (project end) FY17/Q2 Freq. Source/ for Data definition) Method Collection Project Development Objective (PDO): To increase the capacity of Mozambique to prepare for and manage flood events in the Limpopo and Zambezi River basins. PDO level indicators Flood preparedness Areas of improved through Low Improved Improved Input contingency Contingency updated & utilised resolution Information needed contingency plan contingency. plan from INGC Contingency Plan and planning plans updated Semi- Contingency Plan led Text limits to improve planning utilised in DRM utilised in DRM INGC to ARA-Zambezi scenario analysis needing with acquired Annual by INGC in the contingency collected routines and routines and decision Progress & ARA-Sul updated improvement information Zambezi and planning decision making making Reports identified Limpopo Flood risk identificatio improved through Atlas maps for INGC creation of probabilisti Semi- Progress basins 17. Flood plains Y/N N N N Y Y Y ARA-Zambezi flood risk hazard maps Annual report for relevant return & ARA-Sul for the Limpopo & periods mapped Zambezi survey areas Lidar data Agencies Flood risk reduced accessible for DEMs, etc. inform involved in System set up for System set up Example/evidence of through use of new key Surveys/ water resources works Lack of public infrastructure for infrastructure Lidar data used in Semi- ARA-Zambezi geospatial data to Text infrastructure Progress under P146098; other spatial data infrastructure agencies to demand agencies to infrastructure Annual & ARA-Sul ‘build-back-better’ planning and report sectors include informed of data demand data Planning and analysis infrastructure 18 feasibility transport Lidar surveys analysis Improved accuracy of % progress in verifying areas & pop. at risk of ARAs, INGC new flood hazard map 100-year flood in the Semi- Progress % 0% 0% 0% 30% 50% 100% and Statistics overlaid with Limpopo and Annual report Institute population maps Zambezi with compared to 2014 19 improvement to EWS 17 See Zambezi and Limpopo Atlas for Disaster Preparedness in the basins: http://edmc1.dwaf.gov.za/library/limpopo/ 18 Indicator will track Project’s ability to deliver relevant spatial information in efforts to improve infrastructure resilience in the Limpopo and Zambezi. 19 The baseline ‘pop. % at risk’ is being estimated as part of NASA’s assignment. The Lidar data will improve this number by %. Population data will be gender disaggregated as feasible 15 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project Cumulative Target Values Data Collection and reporting WB Core Baseline (2014) Unit Results Indicators Data Responsibility FY16/Q4 Description (indicator FY15/Q2 FY15/Q4 FY16/Q2 (project end) FY17/Q2 Freq. Source/ for Data definition) Method Collection Number of people INGC, ARA- Direct project Progress living in the flood plain # 0 0 0 100,000 320,800 320,800 21 Annual Zambezi & beneficiaries (number) report in both the Zambezi ARA-Sul and Limpopo basin Direct female project Populations consist beneficiaries (% of Progress ARA-Zambezi roughly of 60% # 0 0 0 120,000 192,480 192,480 Annual total direct project report & ARA-Sul females in rural beneficiaries) Mozambique Intermediate Results Indicators (Component A): Limpopo high-resolution mapping surveys & model development Acquisition of new high resolution Airborne survey data Pre- and post- Limited Lidar Mission specs. Airborne surveys Semi- Progress elevation data and collected for the Text - processing of - ARA-Sul data available developed flown annual reports aerial photography Limpopo data complete through airborne survey Survey contractor has Data transferred from Semi- Progress transferred data and contractor to client for Y/N N N N Y Y Y ARA-Sul annual reports intermediate products the Limpopo as agreed to the GoM Horizontal resolution Grid resolution DEM Semi- Progress of DEMs used for cm 9000 9000 9000 500 500 500 ARA-Sul at 90x90m available annual reports Limpopo 2014 Plan for data Data backed up Data backed up and Geospatial data stored No storage & storage & mgmt. ICT investments and incorporated Data available Data utilised through incorporated into file Semi- Progress and managed for the Text mgmt. system created & identified into file sharing through network network across ARA-Sul sharing network [e.g. annual reports Limpopo in place agreed network across across agencies agencies Integrated Information agencies Platform P131049] New geospatial Data available via web Semi- Progress Limpopo data Y/N N N N Y Y Y ARA-Sul or FTP for download to annual reports available for public public Hydraulic & Free 2D Free 2D Hydraulic Free 2D Hydraulic Capacity to simulate hydrological Hydraulic & Hydraulic & Free 2D Hydraulic & modeling & hydrological Semi- Progress the flow of water modeling capacity Text n/a hydrological hydrological hydrological model ARA-Sul capacity modeling software annual reports across the surface of increased for the model model operational limited installed/updated the earth Limpopo operational operational Multi-sector ‘uptake’ ARA-Sul, Update and Semi- Progress of Limpopo Lidar Y/N N N N Y Y Y DNA, INGC Applications to annual reports data for applications Other Gov identified and surveyed 20 Direct project beneficiaries (including % of which are female) is a mandatory CORE indicator. 21 Approximately 164,200 in the Limpopo and 156,600 in the Zambezi. 16 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project Cumulative Target Values Data Collection and reporting WB Core Baseline (2014) Unit Results Indicators Data Responsibility FY16/Q4 Description (indicator FY15/Q2 FY15/Q4 FY16/Q2 (project end) FY17/Q2 Freq. Source/ for Data definition) Method Collection other than WRM and agencies during implementation DRM Staff trained in Lidar ARA-Sul, Semi- Progress Cumulative number of processing and data # 0 0 10 20 25 25 INGC, DNA annual reports staff trained management* and others ARA-Sul, Number of which are Semi- Progress Cumulative number of # 0 0 6 8 11 11 INGC, DNA women annual reports women staff trained and others Staff trained in ARA-Sul, hydraulic and Semi- Progress Cumulative number of # 0 0 20 20 30 30 INGC, DNA hydrological annual reports staff trained and others modeling* ARA-Sul, Number of which are Semi- Progress Cumulative number of # 0 0 12 12 15 15 INGC, DNA women annual reports women staff trained and others Intermediate Results Indicators (Component B): Zambezi high-resolution mapping surveys & model development Acquisition of new high resolution Airborne survey data Pre- and post- No Lidar data Mission specs. Airborne surveys Semi- Progress elevation data and collected for the Text - processing of - ARA-Zambezi available developed flown annual reports aerial photography Zambezi data complete through airborne survey Survey contractor has Data transferred from Semi- Progress transferred data and contractor to client for Y/N N N N Y Y Y ARA-Zambezi annual reports intermediate products the Zambezi as agreed to the GoM Horizontal resolution Grid resolution DEM Semi- Progress of DEMs used for cm 9000 9000 9000 500 500 500 ARA-Zambezi at 90x90m available annual reports Zambezi 2014 Data backed up and Plan for data Data backed up incorporated into file Geospatial data stored No storage & storage & mgmt. ICT investments and incorporated Data available Data utilised through Semi- Progress sharing network and managed for the Text mgmt. system created & identified into file sharing through network network across ARA-Zambezi annual reports [especially Integrated Zambezi in place agreed network across across agencies agencies Information Platform agencies under P131049] New geospatial Data available via Semi- Progress Zambezi data Y/N N N N Y Y Y ARA-Zambezi web or FTP for annual reports available for public download to public Hydraulic & Hydraulic Free 2D Hydraulic Free 2D Free 2D Free 2D Hydraulic & Semi- Progress Capacity to simulate Text n/a ARA-Zambezi hydrological modeling & hydrological Hydraulic & Hydraulic & hydrological model annual reports the flow of water 17 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project Cumulative Target Values Data Collection and reporting WB Core Baseline (2014) Unit Results Indicators Data Responsibility FY16/Q4 Description (indicator FY15/Q2 FY15/Q4 FY16/Q2 (project end) FY17/Q2 Freq. Source/ for Data definition) Method Collection modeling capacity capacity modeling software hydrological hydrological operational across the surface of increased for the limited installed/updated model model the earth Zambezi operational operational Update and Multi-sector ‘uptake’ ARA-Zambezi, Applications to of Zambezi Lidar data Semi- Progress DNA, INGC N/Y N N N Y Y Y identified and for applications other annual reports Other Gov surveyed during than WRM and DRM agencies implementation Staff trained in Lidar ARA-Zambezi, Semi- Progress Cumulative number processing and data # 0 0 5 5 10 10 INGC, DNA annual reports of staff trained management* and others ARA-Zambezi, Cumulative number Number of which are Semi- Progress # 0 0 2 2 4 4 INGC, DNA of women staff women annual reports and others trained Staff trained in ARA-Zambezi, hydraulic and Semi- Progress Cumulative number # 0 0 5 5 10 10 INGC, DNA hydrological annual reports of staff trained and others modeling* ARA-Zambezi, Cumulative number Number of which are Semi- Progress # 0 0 2 2 10 10 INGC, DNA of women staff women annual reports and others trained *Please indicate whether the indicator is a Core Sector Indicator (see further http://coreindicators) **Target values should be entered for the years data will be available, not necessarily annually 18 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project ANNEX 2: DETAILED PROJECT DESCRIPTION A. Overview and background 1. In response to exposure and vulnerability of Mozambique to extreme water and weather events, the Government of Mozambique has identified a series of measures to provide an integrated, multi-institutional response to the recurrent floods and droughts. These measures are intended to improve the response to existing conditions and build climate resilience. 2. Strengthening Mozambique’s ability to respond to and prepare for flood events is a priority of the World Bank’s Country Partnership Strategy with Mozambique (CPS, FY12-15). The CPS focuses on building resilience, particularly to natural disasters and climate change, and commits to support that reduces the country’s vulnerability to disasters. The proposed project forms an important part of a comprehensive range of World Bank financed interventions around water resources, climate change, and disaster risk reduction and recovery. 3. As part of the response to the floods in early 2013, the United Kingdom’s Department for International Development (DfID) identified an opportunity and identified the funds to scale up existing efforts to improve the underlying spatial data to enhance the management of floods. The funds from DfID have been made available through the multi-donor trust fund, the Global Facility on Disaster Reduction and Recovery (GFDRR) administered by the World Bank. 4. Available topographical maps and data for vulnerable areas of the Limpopo and Zambezi River basins are inadequate for modern hydraulic modeling, flood risk assessments and risk zoning. The lack of adequate maps and digital elevation models (DEMs) hinders management of shared waters amongst the riparians in the Limpopo (Botswana, South Africa and Zimbabwe) and the Zambezi (Angola, Botswana, Malawi, Namibia, Tanzania, Zambia and Zimbabwe). 5. The proposed project will support the acquisition of high-resolution spatial data through Lidar 22 (Light detection and ranging) and associated creation of DEMs, aerial photography, and related derivative information products of priority areas of the Limpopo and Zambezi River basins. Understanding the dynamics of high-magnitude floods through computer simulations is critical to flood preparedness and planning. High-resolution DEMs are necessary inputs to hydraulic models that simulate the flow of water across the surface of the earth. As a result, modelers can see where floodwaters will go, their approximate depth, the forces they could exert, and residence time. When combined with historical river discharge records, hydrologists can then estimate the frequency with which floods of a given magnitude will occur. The resulting information is used to improve long-term planning, infrastructure siting and design, emergency response measures, and other proactive management activities. 6. Aerial photography is often used to create land cover classification maps, which can be used to estimate runoff and infiltration. Aerial photography complements DEMs by allowing accurate identification of specific features, such as road, surface water bodies, and other features. 22 Light Detection and Ranging, Lidar, is a remote sensing technology that measures distance by bouncing a laser off a target and analysing the reflected light. When flown in an airborne survey, Lidar can be used to scan large swaths of terrain and create three dimensional models of the terrain surface. 19 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project B. Project Components 7. The proposed project consists of two components representing the two separate small recipient executed grants. 8. Component A. Limpopo River basin high-resolution Lidar survey (ARA-Sul, EUR3.58 million, GFDRR). Component A will be implemented by ARA-Sul in close collaboration with DNA and INGC, as well as key stakeholder agencies. The objective of Component A is to enhance the availability and accuracy of spatial data for priority areas in the lower Limpopo River basin; data that can translate into improved flood risk management amongst other sectors. 9. Component A includes the following activities: A1) Technical Assistance for implementation of the Limpopo Lidar assignment. The activity will include hiring Technical Assistance (TA) to support the implementing agencies with quality control and strategic guidance of the Limpopo Lidar survey. The tasks of the TA will include, amongst others: strategic guidance for implementation of Component A under a comparatively short timeframe, coordination with multiple government agencies, quality control of Lidar data and deliverables, facilitate integration of data into the applications and decision support, alignment with existing Lidar surveys, assistance with the procurement process, and ensuring continuity in capacity building. A2) Determination of priority Survey Areas of the Limpopo. The Lidar surveys to be done in the lower Limpopo river basin will need to consider priority areas required to undertake effective flood modeling, disaster risk management and risk zoning, key infrastructures (such as hydraulic infrastructures, settlement and roads/bridges) as well as alignment with areas that have already been surveyed with Lidar in the lower Limpopo. Planning for acquisition of Lidar data begins with good definition of application needs and requirements. These can be distilled into the specific technical, cost and schedule requirements forming the basis for the technical specifications for the airborne survey contractor. Pre-identified priority areas identified to date include: the Elephants river sub- basin (where the Massingir Dam is a major hydraulic structure regulating the Elephants tributary to the main stem); additional areas along the upper and middle Limpopo main stem (upstream of Chokwé to Elephants River confluence, including the Macarretane Barrage); the middle Limpopo in vicinity of Chokwé (any areas not covered by earlier lidar surveys); right bank upstream of Chokwé with important volumes of water moving across to the Changane tributary flat areas near Chibuto; and, sections of the Changane tributary with its large basin extending far to northern Gaza and Inhambane Provinces (which depending of rain-patterns can contribute with important volumes to the Limpopo floods causing problems down to Xai- Xai). Section C below outlines more detail on priority areas for the Limpopo. A3) Acquisition and completion of Limpopo Lidar Survey. Activity A3 will finance the acquisition of the Lidar survey in the Limpopo River basin. The activity will need to follow global best practice standards of Lidar surveys, in tasks ranging from planning and implementing, the aerial and field operations (including all logistics and flight permits) through to the collection. The bidding documents will detail the requirements of each Lidar surveys (outlined in detail in Section E below). 20 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project A4) Processing and quality assurance review of acquired Lidar point data for open access, long-term use and all possible applications. Activity A4 involves the pre- and post- processing of Lidar data and aerial photography to meet the needs for water resources, disaster risk management, infrastructure planning, amongst others for the Limpopo River basin. The processed data will need to be quality controlled and deliverables should include: Lidar data point cloud, digital elevation/ surface/ terrain models, photos and digital orthophotos and cartographic vector mapping in the metadata files. In order for the processed Lidar data to be useful to the subsequent analysis and production of derivative information products, the survey-firms will be obligated to deliver the data in a format that can be used in, amended and adapted for subsequent applications of analysis. A5) Integration of Lidar data into existing models and decision support systems, and establishment of new ones for the Limpopo. The activity will finance tasks to bridge the gap from processed spatial data from the Lidar surveys into applications for the Limpopo River basin. These applications may include including mapping and zoning, hydrological and hydraulic modeling, disaster risk tools (such as the existing FLOMA managed by INGC). Particular emphasis will be put on developing and updating existing hydrological and hydraulic modeling done by ARA-Sul and other relevant agencies to ensure that DEMs are integrated and seamlessly merged (also called ‘hydrological conditioning’) for the purpose of modeling and understanding flows across the river basin and flood plain 23. Emphasis will be put on ensuring the DEMs are compatible with and support the strategic and cost-efficient development of hydrological and hydraulic modeling across the ARAs (this activity may therefore include targeted analysis and training on selection of hydrological/hydraulic modeling across ARAs). Equally important, will be developing and updating existing tools for disaster risk management such as decision support tools used in contingency planning and early warning systems of INGC, including an exercise to verify population presence data. In addition, the processed Lidar data will need resources to ensure adequate calibration of data sets, and efforts to creating and updating land cover and land classification maps currently available within INE and CENACARTA, as well as mapping tools used for statistics, infrastructure and transport. A6) Long-term training and capacity building for technical staff in ARA-Sul, DNA, INGC and associated agencies working in the Limpopo River basin. Lessons learnt from other Lidar surveys show that training and capacity building of technical staff is critical for the long-term and diverse use of Lidar data and derivative products. Activity A6 will finance a set of training events on processing Lidar data for staff mandated to manage the data, as well as training on facilitating the integration of processed Lidar data into existing and new applications (contracts for Activity A5 will include targeted training elements whereas Activity A6 will focus on the understanding and longer-term management of Lidar data). A7) Effective data management systems and solutions to ensure Lidar data and derivative projects from the Limpopo River basin are easily and openly accessible. To secure the development outcomes of Component A, Activity A7 will finance the necessary 23 Tasks under A5 will be mutually reinforcing with the investments of the Transforming Hydro-Meteorological Services Project that will finance improved modeling capacity of DNA and the ARAs (with current limited use of HYDSTRA, HECRAS and MIKE11),as well as the Flood Response Additional Financing which will finance river basin flood mitigation studies. 21 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project installation of data management systems that will faciliate easy and open access of the raw Lidar data and key derivative products. This will involve early distribution of the data from ARA-Sul to other key stakholders as well as the integration of the spatial data into existing and future tools for data sharing (e.g., the future Integrated Information Platform financed by Transforming Hydro-Meteorological Services Project, and the web/cloud-based GeoNode managed by INGC). A8) Investments into Information Management Systems (IMS) will be financed by Activity A8 to ensure long-term accessibility and use of the Lidar data and derivative products. The activity will focus on the necessary reinforcement of IT infrastructure and internet access of ARA-Sul and the key stakeholders. Particular emphasis will be on efficient web-based accessibility. 10. Component A will be supported through the provision of: i) consultant services and technical assistance; ii) goods, equipment and non-consulting services, including equipment for purposes such as monitoring, mapping, computers, and office equipment; iii) works; iv) operating costs, v) training and capacity building; and vi) audits. 11. Component B. Zambezi River basin high-resolution Lidar surveys (ARA-Zambezi, EUR2.96 million, GFDRR). Component B will be implemented by ARA-Zambezi in close collaboration with DNA, INGC and other stakeholder agencies. The objective of Component B is to enhance the availability and accuracy of spatial data for priority areas in the lower Zambezi River basin; data that can translate into improved flood risk management amongst other sectors. 12. Component B includes the following activities: B1) Technical Assistance for implementation of Zambezi Lidar assignment. The activity will include hiring Technical Assistance (TA) to support the implementing agencies with quality control and strategic guidance of the Zambezi Lidar survey. The tasks of the TA will include, amongst others: strategic guidance for implementation of Component B under a comparatively short timeframe, coordination with multiple government agencies, quality control of Lidar data and deliverables, facilitate integration of data into the applications and decision support, alignment with existing Lidar surveys, assistance with the procurement process, and ensuring continuity in capacity building. B2) Determination of priority Survey Areas of the Zambezi. The activity will identify, rank and select the pioritised areas that need to be surveyed in the lower Zambezi River basin. Identification of areas to be ultimately selected, will need to consider the extent and compatibility of existing and adjacent elevation surveys (e.g., the orthophotographic survey in the lower Shire River), the contribution of surveyed areas to improved hydrological and hydraulic modelling, key infrastructures, populations at risk and the Zambezi River Delta. The floodplains of the Zambezi are approximately 12,000km2. Of this vast area, a first order identification of sub-region reaches of the river were identified during preparation with respect to: contributions hydrological and hydraulic modelling, improvements to DEM, populations at risk and economic activity. At the onset of implementation, further correlation with priorities related to disaster risk management, infrastructure and planning will be made to the first order identification of areas for the lower Zambezi River basin. Section D below outlines further details on priority areas. 22 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project B3) Acquisition and completion of Zambezi Lidar Survey. Activity B3 will finance the acquisition of the Lidar survey in the Zambezi River basin. The activity will need to follow global best practice standards of Lidar surveys, in tasks ranging from planning and implementing, the aerial and field operations (including all logistics and flight permits) through to the collection. The bidding documents will detail the requirements of each Lidar surveys (outlined in detail in Section E below). B4) Processing and quality assurance review of acquired Lidar point data for open access, long-term use and all possible applications. Activity B4 involves the pre- processing of Lidar data and aerial photography to meet the needs for water resources, disaster risk management, infrastructure planning, amongst others, for the Zambezi River basin. The activity also includes post-processing of resulting data for final delivery to ARA- Zambezi and the key agencies benefitting from the surveys. The processed data will need to be quality controlled and deliverables include: Lidar data point cloud, digital elevation/ surface/ terrain models, photos and digital orthophotos and cartographic vector mapping in the metadata files. In order for the processed Lidar data to be useful to the subsequent analysis and production of derivative information products, the survey-firms will be obligated to deliver the data in a format that can be used in, amended and adapted for subsequent applications of analysis. B5) Integration of Lidar data into existing models and decision support systems, and establishment of new ones for the Zambezi. The activity will finance tasks to bridge the gap from processed spatial data from the Lidar surveys into applications for the Zambezi River basin. These applications may include including mapping and zoning, hydrological and hydraulic modeling, and disaster risk management tools. Particular emphasis will be put on developing and updating existing hydrological and hydraulic modeling done by ARA- Zambezi and other relevant agencies to ensure that DEMs are integrated and seamlessly merged (also called ‘hydrological conditioning’) for the purpose of modeling and understanding flows across the river basin and flood plain 24. Equally important, will be developing and updating existing tools for disaster risk management such as decision support tools used in contingency planning and early warning systems of INGC, including an exercise to verify population presence data. Furthermore, the mapping products from the Lidar surveys can facilitate the work of the Zambezi River Valley Authority (ZRVA) as well as infrastructure planning in industrially active regions of Tete and in areas further downstream. In addition, the processed Lidar data will need resources to ensure adequate calibration of data sets, and efforts to creating and updating land cover and land classification maps currently available within INE and CENACARTA, as well as mapping tools used for statistics, infrastructure and transport. B6) Long-term training and capacity building for technical staff in ARA-Zambezi, DNA, INGC, ZRVA and associated agencies working in the Zambezi River basin. Lessons learnt from other Lidar surveys show that training and capacity building of technical staff is critical 24 Tasks under B5 will be mutually reinforcing with the investments of the Transforming Hydro-Meteorological Services Project that will finance improved modeling capacity of DNA and the ARAs (with current limited use of HYDSTRA, HECRAS and MIKE11), future support to the ZAMCOM to facilitate the sharing and integration of basin wide Digital Elevation Models, as well as linking DEMs of the lower Zambezi River with topographical surveys done of the lower Shire tributary as part of the Malawi Shire River Basin Management Project (P117617). 23 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project for the long-term and diverse use of Lidar data and derivative products. Activity B6 will finance a set of training events on processing of Lidar data for staff mandated to manage the Lidar data, as well as training on facilitating the integration of processed Lidar data into existing and new applications (contracts for Activity B5 will include targeted training elements whereas Activity B6 will focus on the understanding and longer-term management of Lidar data). B7) Effective data management systems and solutions to ensure Lidar data and derivative projects from the Zambezi River basin are easily and openly accessible. To secure the development outcomes of Component B, Activity B7 will finance the necessary installation of data management systems that will faciliate easy and open access of the raw Lidar data and key derivative products. This will involve early distribution of the data from ARA-Zambezi to other key stakholders as well as the integration of the spatial data into existing and future tools for data sharing (e.g., the future Integrated Information Platform financed by Transforming Hydro-Meteorological Services Project, and the web/cloud-based GeoNode managed by INGC). B8) Investments into Information Management Systems (IMS) will be financed by Activity B8 to ensure long-term accessibility and use of the Lidar data and derivative products. The activity will focus on the necessary reinforcement of IT infrastructure and internet access of the ARA-Zambezi and the key stakeholders. Particular emphasis will be on efficient web-based accessibility. 13. Component B will be supported through the provision of: i) consultant services and technical assistance; ii) goods, equipment and non-consulting services, including equipment for purposes such as monitoring, mapping, computers, and office equipment; iii) works; iv) operating costs, v) training and capacity building; and vi) audits. C. Prioritisation of survey areas in the Limpopo River basin 14. The lower Limpopo River basin within Mozambique is characterised by expansive floodsplains of flat and lowlying topography of roughly 79,800km2 (20% of the total basin size). The headwaters of the Limpopo River start at 1,000 meters above sea level (masl) in South Africa. Before crossing into Mozambique, the elevation of the river drops sharply to 200masl and then again to approximately 100masl at Pafuir. Across the last 400km of the river, within Mozambique, it flows across flat floodplains and its final 175km (between Chokwé and the river’s mouth) are at elevation of less than 7masl. The Rio dos Elifantes tributary (called Olifants in South Africa) contributes with the largest flow and is half the length of Limpopo main stem 25. The other main tributary within Mozambique is the Changane River flowing from northwest and joining the main stem near Chibuto. 15. The proposed Lidar survey in the Limpopo will be defined according to three main criteria. First, to not duplicate already surveyed areas. Second, areas to be surveyed must qualify for priotised needs for topographical data. And third, fall within the resource envelope of the grant financing of Component A’s Lidar survey and associated activities. 25 The Olifantes/Elifants tributary makes a steeper drop than the main stem – from 1,500 masl at Witbank dam in South Africa to 80 masl at the Massingir dam in Mozamibuqe. 24 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project 16. In the lower Limpopo, certain areas have recently been surveyd using Lidar. Under the GFDRR supported Programmatic Support to Disaster Risk Management Project (P124755), two sets of areas have been surveyed as indicated in the map below in figure 2 (i.e., 1,800km2 and 835km2) 26. The map below also indicates estimated additional areas that would make critical contributions to assessment of flood impact from hydrological and hydraulic modelling (equating to a minimum of 3,000km2 upstream to of Chokwé and some 1,500km2 towards Chibuto and the Changane tributary), as well as additional prelimiary sites of key infrastructures, roads and settlements to be defined in implementation. Figure 2. Priority areas in the lower Limpopo River basin (estimated) 17. To estimate the potential extent of floods at different time return periods, the LISFLOOD-FP flood model 27 was run with 1:5, 1:100 and 1:1,000 year return flows estimated from regional growth curves (flood frequency distribution rescaled by the mean annual maximum flow) based on the Global Runoff Data Centre (GRDC). The extent of a 1:1,000 year return period flood is 26 Deliverables included: Digital Vector Maps at 1:2000 scale, land use and occupation maps, aerial photography and orthophoto GSD 30m and data made available on physical hard disks to key agencies. 27 Modelling of flood extents were done at the courtesy of models developed by SSBN University of Bristol. 25 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project represented in figure 3 below along with an overlay of the floods of January 2013 (derived from the Dartmouth Flood Observation MODIS 28). D. Prioritisation of survey areas in the Zambezi River basin 18. Roughly 12.8% of the Zambezi River basin lies within Mozambique (i.e., 196,250km2 of 1,570,000km2). The last 650km of the Zambezi River is considered the lower Zambezi River; from the outlet of the Cahora Bassa Dam (built in 1974 with 2,075 MW capcity) to the river’s mouth in the Indian Ocean. As the river enters the broad valley of the lower Zambezi, the river is shallow, wide and flowing through main streams (between 5-8km in places); apart from a narrowing at Lupata Gorge where the river width is 200m (320km from the river mouth). The major tributary of the Shire River (flowing from Lake Malawi/Nyasa/Niassa) enters from Malawi into the main stem roughly 160km from the sea. As the river enters the delta with a discharge of approximately 130km3/year, it splits into shallow channels overflowing its sandbars in the rainy season. 19. Land cover in the mapping area includes wetlands with low-lying to medium tall vegetation, agricultural regions, grasslands and structures. The topography is primarily flat although steeply sloped banks with significant hydraulic implications exist in some regions, particularly in the delta area. The proposed Lidar survey in the lower Zambezi River basin will be, like the Limpopo, defined according to three main criteria. First, to not duplicate adjacent surveyed areas in the Shire River. Second, areas to be surveyed must qualify for priotised needs for topographical data. And third, fall within the resource envelope of the grant financing of Component B’s Lidar survey and associated activities. 20. Within Malawi, a orthophotographic survey has been done on the lower Shire River that will contribute to basin-wide hydraulic and hydrological modelling. Understanding the contribution of the lower Shire to the main stem is important to estimate floods at the confluence and within Mozambique. An early assessment of the survey and DEM of the lower Shire River indicate that the proposed new Lidar survey and DEM of the main stem of the Zambezi could be merged (‘hydrologically conditioned’) to improve the DEM for the lower basin to the benefit of both countries. 21. In order to ensure that early estimated priority areas for flood modelling were identified capturing inundation of the natural floodplain (in the absence of detailed topographical data), the model simulations were run with a flow on the Zambezi River of 70,000 m3/s at Tete. The latter is an unrealistically high flow with a likely return period (i.e., frequency of occurrence) orders of magnitude higher than 1:10,000 years. From the model, discrete individual sub-sections of the lower Zambezi River were identified that could contribute significantly to improved hydrological and hydraulic modelling 29. The sub-sections are presented in the map of figure 3. According to the current best available stream network data set, this equates to a distance along the stream 28 http://csdms.colorado.edu/pub/flood_observatory/MODISlance/030e020s/ 29 An individual reach may be defined hydrologically as a section of river where no significant lateral inflows are happening according to the DEM used for hydrologic conditioning (in this case the Hydrosheds version of the SRTM DEM). In terms of first order river hydraulics, the assumption can be made that within a given sub-reach a kinematic flow approximation is sufficiently accurate; in other words a linear gradient between the upstream and downstream sections of that sub-reach is representative of the operating flow process. 26 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project centerline chainage of about 400km, although this number is expected to be much larger when using accurate Lidar data to generate correct stream network topology. 22. The sub-regions encompass between 8,000km2 to 12,000km2 (the latter including the floodplain). The reaches were subsequently ranked based on level of contribution to improved modelling, exposure of populations at risk of flooding, and risks of economic loss in the case of floods. High ranking priority areas equate to approximately 7,500km2, where roughly 156,600 people live and an average of US$1.94bn in economic assets and activity take place. 23. In addition to areas that may contribute to modelling and will reduce the risks to populations and economic assets and activity, the prioritised areas of the Lidar surveys will consider the need for better data on the important delta wetlands (additional minimum 800km2 of southwestern part of Delta), important infrastructures and key river embankments. Figure 3. Priority areas in the lower Zambezi River basin (estimated) E. Lidar technology and Digital Elevation Models (DEM) 24. Lidar, otherwise referred to as Light Detection and Ranging, is a remote sensing technology that measures distance by bouncing a laser off a target and analysing the reflected light. When flown in an airborne survey, Lidar can be used to scan large swaths of terrain and create three dimensional models of the terrain surface. The raw data, which is in the form of a point cloud, is then transformed into a digital elevation model (DEM) at high resolution. With high-resolution Lidar-derived DEMs as an input, hydraulic models are expected to improve in accuracy by a minimum of 20% and in some areas, such as the on the Zambezi River delta which is particularly 27 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project flat. Classification of river embankment areas is expected to improve by a minimum of 70%. The accuracy improvements are based on baselines estimates that use global DEMs at a 90x90 meter resolution. The collection of Lidar-derived DEMs will enable the creation of accurate hydraulic models for use in planning and investment scenarios. 25. Conceptually, raw Lidar return data looks like a cloud of points, with each point representing a point where the laser reflected off of a surface. This data is then processed to remove errors and to distinguish between the ground itself and structures or foliage that sit above ground level. In situations where trees or other structures are present, it is often possible to create a separate data layer that provides a three dimensional model of the structures or foliage. Additionally, during processing, other geographic features such as stream centerlines, road boundaries and crowns, and river embankments may be identified and translated into vector data layers for further use in GIS or modeling. Ultimately, a high resolution DEM and a number of other derivative data products are created. These are used as inputs to hydraulic and hydrologic modeling. 26. Often, large swathes of terrain is surveyed from an airborne platform such as an airplane or a helicopter and when these surveys are flown additional instrumentation can be added at little cost. Thus, Lidar data is often provided in conjunction with aerial photography. 27. The specifications for the acquisition of the Lidar survey are spelt out in the contract details and Statement of Work. These contractual documents will elaborate the following information: - Project Area size and shape of project area - Digital Surface Type bare earth, surface including structures and vegetation, etc. - Model Type point cloud, grid, contour lines, surface - Source Lidar - Accuracy vertical and horizontal - Surface Treatment classification of areas such as buildings, vegetation, etc. - Datum reference earth surface for vertical and horizontal measurement such as WGS 84 - Coordinate Systems UTM, geographic (Latitude / Longitude), or local defined coordinates - Units metric or English units, also specify number of decimal places - Format data file type needed by user, such as shapefile (*.shp) or ASCII text (*.txt) - File Size desired size in terms of memory (MBs) or spatial extent (e.g. km2) - Metadata any required ancillary data, e.g.US Federal Geographic Data Committee (FGDC) standard - Delivery Schedule desired need dates for deliverable items - Budget/contract type fixed price, cost reimbursement with not-to exceed budget 28 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project - The Statement of Work (SOW) will serve as the common point of reference between the project manager and the vendor. 30 28. The raw data and applications generated by the Lidar surveys will be made available through public domain platforms to ensure access and availability to a range of stakeholders and encourage further refinement of tools. 29. Digital elevation models are representations of the surface of the earth in three dimensions. Digital Elevation Models (DEMs) are most frequently created through airborne Lidar survey. The uses of DEMs are numerous and include applications in forestry, construction, ecology, transportation, and urban planning. 30. Acquisition of Lidar data and simultaneous orthophotos over areas in Mozambique could allow building a high resolution, high fidelity 1D-2D hydraulic model of targeted local regions of interest for, for example: i) establishing a detailed understanding of local to regional water storage and fluxes (including wetlands) and timing of flood waves and exact flood wave routing for better flood forecasting; ii) advanced flood hazard/risk mapping for agricultural and urban areas; iii) ecological/environmental flow modeling in key wetland areas; iv) plant and animal habitat protection from flooding; v) orthophotos allow detailed classification and verification of water, land cover and plant type, which are all crucial for improved hydrodynamic modeling at high resolution; and vi) water quality and health indicators related to flood water parameters (length of inundation time and amount of water volume in floodplain) can be derived. F. Lidar Applications and Sector Benefits 31. Acquisition of high-resolution topographical data from Lidar can provide the underlying visual image of the basin and give the tools needed to inform efficient decision making. These are a prerequisite for advanced data collection and presentation and will be used for map production, photogrammetry, image production and GIS services. 32. The primary application of the Lidar-derived DEMs will be to the water resources management sector where DEMs are mainly used for hydrologic and hydraulic modeling and for disaster risk management and the emergency preparation and response work of the Government of Mozambique (in particular, the INGC). 33. Hydraulic models simulate the flow of water across a land surface and therefore an elevation (surface) model is a critical input to the modeling process. Software packages are used to create hydraulic models, which also incorporate the physical characteristics of the landscape such as infiltration capacity and roughness. With a robust hydraulic model, modelers can simulate the flow of different magnitude floods across the surface of the earth. These models can be as simple as one-dimensional cross sections indicating the elevation of the river surface at various points along the river or as complex as two-dimensional maps that estimate parameters such as the force, direction, and residence time of flows across a given area. 34. Existing or new hydraulic models used in Mozambique, can benefit from improved estimates of how water flows across the flood plains in a range of return periods. Flood hazard maps can identify, for example, the expected boundary floods of both different magnitudes and different 30 This is an extremely important document requiring diligence by the project manager. It must be kept in mind that a vendor is only responsible for what is contained in the Statement of Works (SoW). If the project manager should decide to alter or add to the vendor’s requirements after a SoW agreement is established, there is significant risk of a price increase or slip in schedule. 29 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project probabilities of flood occurrence. At the most basic level, flood hazard maps will help individuals and policy makers identify areas at risk of flooding, both in terms of magnitude and probability (building on the example of the FLOMA decision support system established in INGC as part of GFDRR project P124755). Decision makers can then overlay the hazard maps with road, infrastructure, and population layers to identify vulnerable populations, estimate the economic value of infrastructure at risk, and better plan emergency response efforts through the simulation of flood conditions. Flood hazard maps can further be taken up by the insurance industry and by local landuse planning authorities, who may, for example, enact zoning regulations to better prepare for future floods. 35. DEMs are also used to estimate slope, runoff, and routing parameters. DEMs are particularly useful when combined with landcover and landuse data that provide infiltration and roughness parameters. In the most basic sense, hydrologic models describe the relationship between precipitation and discharge over a given catchment and a robust hydrologic model will enable discharge forecasting across a variety of time horizons depending on the time horizon of the precipitation data with which it is driven. Furthermore, but enabling the development of robust hydrologic models, this data will set the basis for monitoring for long-term environmental changes induced by climate change. 36. Thus, when used in a modeling context, DEMs inform planning and investment decisions in the private and public sector. Individuals may, for example, base decisions about where to build a house or start a business on the updated flood risk information. Local policy makers may change zoning regulations and building codes to reduce the vulnerability of the built environment to floods. Urban planners may use elevation models to better manage urban stormwater. Land use planners and natural resource managers may use the information to develop resource management plans. Engineers can use the information to design infrastructure such as bridges to withstand appropriate floods. Transportation planners can use elevation models to route roads optimally with respect to slope, aspect, and avoidance of flood-prone areas. The insurance industry may use the data to reduce uncertainty and as a result, open new insurance markets. Engineers and architects may use elevation models to design and site buildings and infrastructure. Hydrologists can use the models to plan and design flood management infrastructure such as dikes, levees, and river defense systems. 37. Lidar can be used for many of the following applications: • Disaster management: DEMs are typically useful in disaster scenarios to assess flood extent and risk, the intactness of road infrastructure, etc. However, Lidar also is useful in most scenarios where 3D, terrain information is required to assess damage. For example: Building damage assessment: There is evidence that Lidar, after rigorous analysis, can be used to assess building damage in cases where the structure’s damages exhibits as “crumpled” facets. A normal vector (a line that originates from the center of a facet and is perfectly perpendicular to that facet’s plane) can be calculated for each building facet. In the case of an intact roof, all vectors will be aligned along a uniform direction. But in the case of a crumpled roof, normal vectors will have much more variability in their directional quality. This approach does not, however, work well for “pancaked” buildings, i.e., buildings that looks intact from above but collapsed along all building floors. 30 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project • Ecological: Lidar can be used to assess detailed vegetation structure. These structural assessments are not limited to the canopy height, but also within-canopy structures (e.g., gaps). Examples of ecological applications include: Habitat assessment: Many species require specific types of vegetation structures, such as tree heights, canopy closure (no canopy gaps), specific leaf biomass (measured as “leaf area index”), or even defined height, slope, or aspect (direction of the ground surface slope) ranges. As such Lidar is particularly useful for defining species habitat ranges. The biggest drawback is that Lidar often is not flown for large regions, and such habitat modeling efforts may be limited to smaller areas. • Line-of-sight mapping: This is also called “viewshed analysis”, i.e., “what can and can I not see from a particular point in a 3D landscape?” This kind of analysis can benefit, for example, commercial operations that require direct line-of-sight (e.g., cell tower placement, communications, real estate development, etc). • Landscape or urban planning: Lidar is often used to assess the 3D terrain to plan new buildings, golf courses, roadways and other infrastructure. The benefit is accurate and dense (high spatial resolution) 3D products. • Vegetation volume assessment: Forest companies are investing in new ways to assess growing stock. Lumber, pulp, firewood farms need to know how much timber stock they have. This is true of companies that diversify their portfolios to include a stable investment like forestry. Lidar is used to measure tree height, crown widths, and even tree density (stems/hectare), all of which can be used to predict tree or forest stand volume and biomass. • Right-of-way mapping: Many companies need to assess the structures that infringe on their investments. The most notable example is utility companies which spend large sums on managing vegetation near power lines. Lidar is more frequently being used to map power line corridors to optimise field operations that curb vegetation growth and limit risks. • Insurance industry: Insurance companies are often interested not only in potential damage to property but also need to establish baseline or truth data for insurance purposes. For example, the need to assess building footprints, roof area etc. to make insurance premium adjustments. • Tax purposes: Finally, government institutions can use Lidar to assess property and assets, especially in terms of building structures and crop extent. While this application is not commonplace, it has been discussed as a potential technology to use for tax assessments. G. Project Cost and Financing 38. Two recipient exectued grants of EUR3.58million and EUR2.96 million have been allocated for Lidar surveys, applications and capacity building activities in the Limpopo and Zambezi River basin, respectively. The funds will be allocated to survey the areas of highest marginal value in terms of their contribution to model accuracy and hydraulic significance. An indicative cost breakdown across activities is presented in table 2 below. 31 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project Table 2: Detailed financing estimates (EUR million) Program Component GoM GFDRR Total A. Limpopo River Lidar Survey and Applications in-kind 3.58 3.58 A1. Techn. Assistance –Implementation and Quality Assurance for Limpopo 0.35 0.35 A2. Determination of priority Survey Areas 0.03 0.03 A3. Acquisition and delivery of Limpopo Lidar Survey (incl. logistics) 1.42 1.42 A4. Processing of Lidar data for key application and long-term use/access 0.30 0.30 A5. Integration/Establ. of Lidar applications (focus sectors: WRM and DRM) 0.44 0.44 A6. Training & Capacity building for ARA-Sul, DNA, INGC and associated agencies 0.44 0.44 A7. Management and dissemination of Lidar data, with GIS 0.30 0.30 A8. Data and Information Management System, including IT infrastructure 0.30 0.30 B. Zambezi River Lidar Survey and Applications in-kind 2.96 2.96 B1. Techn. Assistance –Implementation and Quality Assurance for Zambezi 0.15 0.15 B2. Determination of priority Survey Areas 0.03 0.03 B3. Acquisition and delivery of Zambezi Lidar Survey (incl. logistics) 2.2 2.2 B4. Processing of Lidar data for key application and long-term use/access 0.07 0.07 B5. Integration/Establ. of Lidar applications (focus sectors: WRM and DRM) 0.14 0.14 B6. Training & Capacity building for ARA-Zambezi, DNA, INGC and associated agencies 0.07 0.07 B7. Management and dissemination of Lidar data, with GIS 0.1 0.1 B8. Data and Information Management System, including IT infrastructure 0.2 0.2 Total Baseline Costs 6.54 6.54 Total Program Contribution 6.54 6.54 32 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project ANNEX 3: IMPLEMENTATION ARRANGEMENTS A. Project Institutional and Implementation Arrangements 1. The two recipient executed small grants from the GFDRR will be implemented by the two Regional Water Authorities, ARA-Sul and ARA-Zambezi. The ARAs were established in 1992 by an addendum to the Water Law (No. 16/August 03, 1991), and the first to be set up was ARA-Sul (Administração Regional de Águas do Sul). The ARAs are semi- autonomous and report to the Ministry for Public Works and Housing (MoPH, Ministério das Obras Públicas e Habitação) and receive strategic and management guidance from the National Directorate for Water (DNA, Direcção Nacional de Águas). The ARAs operate under the tutelage of DNA, and are responsible to guide the planning of basin development, monitoring and modelling of water resources, administration of public water, register and organise tariffs to cover water use costs, licensing and concessions, and operating and approval of hydraulic works. 2. The addendum of the Water Law in 1992 and the establishment of the ARAs signaled a shift of the National Directorate for Water (DNA) from operation to strategic focus. With the guidance of the 2007 Water Policy and the Ministerial Decree 142/2012 (specifying organisational responsibilities of DNA), the responsibilities of DNA were further articulated (Article 1). These are: the sustainable development of water resources; the delivery of water supply and sanitation; defining policy, strategies and legislation on water; and the strategic management of hydro-meteorological networks, flood warning systems, and coordination. 3. Component Coordinators within both ARA-Sul and ARA-Zambezi will be responsible for the technical management and delivery of each component and activities. There is strong alignment of the Lidar surveys with the activities under the National Water Resources Development Project (P107350), the Emergency Flood Response Additional Financing (P146098) and the Transforming Hydro-Meteorological Services Project (P131049), where the outputs will be mutually beneficial. Responsibilities for ongoing activities under the associated projects are already established. Therefore, the new activities under the proposed small grants will be harmonised with existing staff resources to the extent possible (also because the ARAs, DNA and INGC experience constraints in staff capacity and availability). The technical work related to the development of the technical content of the bidding documents for the Lidar surveys and the prioritisation of the areas to be surveyed will be completed by staff within ARA- Sul and ARA-Zambezi, respectively, with support provided by DNA, INGC and other government agencies (Technical Assistance will also provide support during implementation). 4. The Project Administration and Monitoring Team (PAMT) in DNA will be responsible for procurement, financial management and coordinating progress reporting. In 2012, the PAMT was set up with funds from the National Water Resources Development Project within DNA. The PAMT includes a Project Manager, Procurement Specialist, Financial Management Specialist, a Monitoring & Evaluation Officer, and administrative support staff. The PAMT will extend its support to provide the same services and functions for the new proposed grants. Their core tasks will include: supervising and managing procurements, financial management and reporting, and coordinating reporting on progress of implementation and results. 5. The airborne Lidar surveys will be flown by a specialised contractor(s). The firms providing the non-consultancy service of Lidar surveys, will be contracted through a competitive 33 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project bidding process in adherence with the World Bank’s Procurement Policies and Guidelines of January 2011. 6. Inter-agency coordination is critical for successful results, and will build on existing platforms for coordination on water resources and floods in Mozambique. During preparation, focal points were identified and mandated to support coordination amongst the key agencies of the ARAs, DNA and INGC. This group will continue to collaborate during implementation and extend the engagement to other key agencies through existing platforms for coordination. These include the operative centers for emergency (e.g., CENOE), the inter-agency working group on hydro-meteorological services and the collaborations established under the previous smaller Lidar survey of the lower Limpopo in 2012 (P124755 GFDRR). Other essential partners include: the National Center for Cartography (CENACARTA, Centro Nacional de Cartografia), the National Institute for Statistics (INE, Instituto Nacional de Estatistica) along with the National Operational Emergency Center (CENOE, Centro Nacional Operativo de Emergência), the National Meteorological Institute (INAM, Instituto Nacional de Meteorologia) and the National Roads Administration (ANE, Administração Nacional de Estradas), etc. 7. In particular, close collaboration and involvement of the National Institute for Disaster Management (INGC, Instituto Nacional de Gestão de Calamidades) is critical for the delivery and outcomes of the Lidar surveys. INGC has a strong position and mandate within the Government of Mozambique with respect to preparation, risk reduction and response to emergencies. With a coordination role among government agencies in crisis management, INGC undertakes tasks such as relocation of communities, temporary accommodation, communication, annual contingency planning, and coordination of national to district level groups and drills. For INGC to undertake timely, accurate and relevant work, they depend on information from DNA, the ARAs and INAM on water and rainfall levels and risks related to floods and extreme events. Figure 5. Implementation Arrangements National Directorate for Water (DNA) National Institute for Disaster Project Administration & Monitoring Team (PAMT) Management (INGC) Department for Water Resources & relevant Ministries, incl. INAM - National Inst. for Meteorology MINAG - Ministry for Agriculture MOPH - Ministry of Public Works & Housing Ministry of Transport Regional Water Authority Regional Water Authority of IIAM - Institute for Agrarian Research DNSA - National Directorate for of the South (ARA-Sul) the Zambezi (ARA-Zambezi) Agriculture Extension ANE – Component A Coordinator Component B Coordinator UEM – University of Eduardo Modlane Specialist firms 34 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project 8. Access to Lidar survey data and maps can strengthen basin-level cooperation in the Limpopo River basin and the Zambezi River basin. Mozambique is the most down-stream riparian of both river basins, and is active in the two river basin organisations for each catchment, namely the Limpopo Watercourse Commission (LIMCOM) and the Zambezi Watercourse Commission (ZAMCOM). Both the 2003 Agreement on the Establishment of the Limpopo Watercourse Commission31 (ratified in 2010) and the 2004 Agreement on the Establishment of the Zambezi Watercourse Commission32 (ratified in 2011), emphasise and provide for the sharing of information required for early flood warnings and protection of lives and assets. Under both LIMCOM and ZAMCOM there are also ongoing efforts to strengthen information sharing systems, including harmonisation of hydrological modeling and data. In addition, there are topographical surveys in neighbouring riparian countries, which will facilitate hydrological modeling of floods across the basin once the Digital Elevation Models are merged and harmonised (so called hydrological conditioning). B. Risk Analysis 9. The overall risk rating of the two grants is ‘Low’. The fact that the two grants will be implemented with the project management and administrative support of the Project Administration and Monitoring Team (PAMT) in the DNA is a mitigation measure to overall project management. The PAMT is familiar with Bank requirements on financial management, procurement and progress reporting and has established routines in these areas that will be applied to the two grants. The design of the two grants and the implementation of activities will be aligned with a programme of support in the areas of water resources management, disaster risk management, investments into roads and transport, hydro-meteorological monitoring and forecasting as well as support to enhanced transboundary water management. This provides a mitigation measure for the risk of the two grant activities not linking to associated sectors. 10. Specifically, the following risks and mitigation measures have been identified: 11. There is a risk that seasonal and immediate weather conditions may delay or reschedule the planned Lidar surveys. The surveys are planned to be undertaken between April and October, which is the dry season providing optimal survey conditions. Procurement of the Lidar surveys will be through a competitive bidding for two separate areas of work, one through ARA-Sul and one through ARA-Zambezi. Field work poses operational issues due to scarce logistical support to perform long and continuous flights in the most remote areas but these problems are can be handled by experienced companies with proven experience of working in these environments. 12. There are risks to the sustainability of the datasets and the development of associated applications. Ensuring sustainable management of the resulting datasets (access and availability of data and update by other government agencies) requires strong institutional coordination and trained staff in all partner government agencies (INGC, INAM, DNA and ANE). Training will be provided by Project and institutional arrangements will be strengthened in order to facilitate data sharing. The risk will be mitigated by ongoing efforts by the Government to adopt a Protocol on data sharing amongst key agencies in the areas of hydro-meteorology and disaster risk management. This effort is supported by the World Bank’s Climate Change Development Policy Lending operation and the operationalisation of the said Protocol is partly financed by the 31 http://www.icp-confluence-sadc.org/riverbasin/96 32 http://www.zambezicommission.org/index.php 35 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project Transforming Hydro-Meteorological Services Project (through the implementation of an integrated data management platform). 13. There is a low risk of limited use of the acquired data sets due to potential lack of ‘uptake’ of the data amongst the agencies and associated projects. However, direct applications of data have been identified, including investments under the National Water Resources Development Project; the Limpopo Emergency Flood Response with rehabilitation of dykes/levees, roads and a build-back-better approach to flood management; PPCR funded Transforming Hydro- Meteorological Services Project; and the Zambezi River Development Projects that is enhancing the ZAMWIS. Recipient entities have identified following applications: flood inundation and risk mapping, dam break analyses, environmental flow applications, spatial planning and urban development, flood response and emergency evacuation plans, among others. 14. There is a low risk associated with the sensitivity of acquired spatial data. Sensitivity over use of data could mean that relevant authorities would not provide authorisation for fly-bys required to do the mapping. The clear benefits associated with relevant projects and infrastructures (especially support for cooperation on transboundary waters in the Zambezi) can help mitigate the risk. ARA-Sul and ARA-Zambezi have ongoing collaborations with associated authorities within Mozambique and amongst the riparians which will facilitate the coordinating the logistical arrangements and necessary approvals. 15. Environmental Category C. The project will not support any on-the-ground physical works and is therefore classified as environmental Category C. C. Project Beneficiaries 16. The direct project beneficiaries are the two government institutions mandated with water resources management in the Limpopo and Zambezi River basins: the Regional Water Authority for the South (ARA-Sul, Administração Regional de Águas do Sul) and the Regional Water Authority for the Zambezi (ARA-Zambezi, Administração Regional de Águas do Zambezi) respectively. These two institutions will serve as the immediate custodians of the project. The two ARAs will be responsible for managing the acquisition and outputs of the detailed high- resolution spatial and topographical surveys, including the management and processing of resulting data, as well as making the raw data and developed derivative information products available and useable to other agencies. Involvement and close collaboration will be necessary with the National Directorate for Water (DNA, Direcção Nacional de Águas), National Institute for Disaster Management (INGC, Instituto Nacional de Gestão de Calamidades), the National Center for Cartography (CENACARTA, Centro Nacional de Cartografia), the National Institute for Statistics (INE, Instituto Nacional de Estatistica) along with the National Operational Emergency Center (CENOE, Centro Nacional Operativo de Emergência), the National Meteorological Institute (INAM, Instituto Nacional de Meteorologia) and the National Roads Administration (ANE, Administração Nacional de Estradas), amongst others. 17. The indirect project beneficiaries are people, communities, and businesses at risk of water and weather related hazards. Improved information about flood-related hazards can both lower the exposure to risks and increase productivity. This includes approximately 450,000 people living in the middle and lower Limpopo River basin and 313,000 in the lower Zambezi River basin in Mozambique. The target area in the Limpopo is one of the more populated areas of Gaza, Inhambane and Maputo Provinces. It comprises around 253 small villages and important 36 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project settlements such as the provincial capital Xai-Xai (115,752 inhabitants), and district capitals Chibuto (63,184 inhabitants), Chokwé (53,062 inhabitants) and Guijá (28,492 inhabitants). 18. During preparation, a set of preliminary priority survey areas were identified in the two basins. Population estimates for the Lidar survey areas are 164,200 in the Limpopo and 156,600 in the Zambezi 33. The people who live in these areas can benefit through increased information about the immediate and long-run risks of water and weather related hazards. Indirectly, a number of private sectors will benefit: from commercial farmers and power utilities, to telecommunication and construction companies. These minimum estimates of direct beneficiary may increase as survey areas are refined. 19. A gendered dimension exists among beneficiaries in part because Mozambique is experiencing an increasing feminisation of both vulnerability and small-scale farming 34. Analysis of the social impact from climate change conducted in Mozambique emphasise that women and girls will be more affected in drought-prone areas, for example, because of the increase in time spent on activities such as water collection. 20. Indirectly, other sectors will also benefit; private sector agencies and investors including enterprises such as farming for commercial purposes, telecommunication, forestry, maritime transport and extractive industries. Beneficiary media agencies could include: the National News Agency (AIM – Agência de Informação de Moçambique), Rádio Moçambique, and local community radio stations, the newspaper Notícias, Television of Mozambique (TVM – Televisão de Moçambique), Socio TV, TV Miramar, Radio Miramar and Radio FM99. 21. Beyond the beneficiaries listed above, freely available spatial data from Lidar surveys can have the following positive outcome: - Businesses may use the information to inform investment decisions and optimise activities for increased productivity (e.g., commercial farming or forestry). - The Zambezi River Valley Authority mandated to facilitate inter-agency collaboration and development in the lower Zambezi River basin. - Government agencies of Mozambique involved with land use and infrastructure planning, and natural resources and environmental management, including the Ministries of Agriculture, Planning, Infrastructure, Transportation, and the Water Supply Investment and Assets Fund (FIPAG). - The research community, such as hydrologists at national and regional universities but internationally. - The governments of the upstream riparians. D. Financial Management, Disbursements and Procurement 22. The implementing agencies have agreed that the Project Administration and Management Team (PAMT) in DNA will manage the overall fiduciary tasks as they already have specialists in financial management and procurement, and the proposed set up creates more streamlined and integrated procedures. 33 Source of population data: NASA SEDAC. 34 In Chibuto District southern Mozambique, for example, male migration results in women representing 57% of total population. Africa Climate Change Resilience Alliance Understanding adaptive capacity at the local level in Mozambique (2012). 37 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project 23. Within the DNA, the PAMT was set up under the National Water Resources Development Project (P107350) in 2012. The PAMT includes a Project Manager, Procurement Specialist, Financial Management Specialist, a Monitoring & Evaluation Officer and Administrative support staff. The PAMT will provide the same functions to the new Project as they do for existing operations (P107350, P146098 and P131049), in terms of ensuring procurement, financial management and regular reporting requirements. However, a junior procurement officer will be recruited to enhance the performance of the procurement function. 24. Financial Management. A Financial Management Assessment of the DNA was carried out in accordance with the Financial Management Manual for World Bank-Financed Investment Operations issued by the Financial Management Sector Board on March 01, 2010. The objective of the assessment was to determine whether the implementing agency has acceptable financial management arrangements, which will ensure that: (i) the funds are used only for the intended purposes in an efficient and economical way, (ii) accurate, reliable and timely periodic financial reports are prepared, and (iii) the agency assets are safeguarded. The overall conclusion of the Financial Management Assessment is that the project’s financial management arrangements satisfy IDA’s minimum requirements under OP/BP 10.00. The project financial management arrangements have an overall residual risk rating of Moderate. 25. The Recipient may withdraw the proceeds of the grants in accordance to finance eligible expenditures consisting of goods, works, services and operating costs, inclusive of taxes. 26. Procurement. Procurement will be carried out in accordance with the World Bank's "Guidelines: Procurement of Goods, Works and Non-consulting Services under IBRD Loans and IDA Credits and Grants by World Bank Borrowers" published by the World Bank in January 2011 ("Procurement Guidelines"), in the case of goods, works and non-consulting services; and "Guidelines: Selection and Employment of Consultants under IBRD Loans and IDA Credits and Grants by World Bank Borrowers" published by the World Bank in January 2011 ("Consultant Guidelines") in the case of consultants' services, and the provisions stipulated in the Grant Agreement. Further, the “Guidelines on Preventing and Combating Fraud and Corruption in Projects Financed by IBRD Loans and IDA Credits and Grants”, dated October 15, 2006, and revised in January 2011 will apply. 27. The coordination between the PAMT and the beneficiary institutions will be critical in ensuring timely implementation of agreed activities. The Procurement procedures and Manual under the National Water Resources Development Project (P107350/ P146098) will be adopted for the Project. However, the Manual will be updated to incorporate the particular features of the project. A procurement plan has been prepared under the coordination of DNA and will be updated at least annually (or as required) to reflect project implementation needs. E. Role of Partners 28. The proposed Project and two Lidar surveys in the lower Limpopo and Zambezi River basins are part of multi-donor response to recurrent floods and acknowledged need to enhance climate resilience given potential for increasing issues in the face of potential climate change. 29. In the Limpopo River basin, the Lidar surveys will be mutually reinforcing of a number of parallel investments. They include, amongst others: - Limpopo river basin monograph and pilot DRM efforts in Chokwé (GiZ/DfiD) 38 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project - Resilience in the Limpopo River basin, RESILIM (USAid) - Rehabilitation civil works to the Massingir Dam (African Development Bank) - Feasibility design studies of the Mapai Dam (African Development Bank) - Limpopo Irrigation and Climate Resilience Project (African Development Bank, Pilot Programme for Climate Resilience) - Integrated Flood Risk Management Framework (the Government of the Netherlands) - Climate Resilience Infrastructure Development Facility, CRIDF (UK DfID) 30. In the Zambezi River basin, the Lidar surveys will be mutually reinforcing of a number of parallel investments. They include, amongst others: - Zambezi Watercourse Commission technical assistance programme and investments into the Zambezi River Water Information System (Danida and World Bank, Cooperation in International Waters in Africa) - Zambezi River Basin Initiative (International Federation of the Red Cross) 39 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project ANNEX 4: SIMPLIFIED OPERATIONAL RISK ASSESSMENT FRAMEWORK 1. Project Stakeholder Risks Rating Low Description: There is a low risk that the Lidar surveys Risk Management: The information products developed from the detailed topographic surveys being financed by the Project, will not benefit the intended are intended to benefit the people who are threatened by water and weather related hazards within stakeholders due to lack of sharing of information or the Limpopo and Zambezi River basins. Although the Project focus on a critical ‘input’ to cooperation amongst key government agencies. improved information (e.g., early flood warnings), and it is difficult to deliver the entire ‘change- process’ because of uncertainties, the Government has comparatively strong mechanisms for sharing information through the mandate of national council for disaster management (CENOE) that is coordinated by the National Institute for Disaster Management (INGC). There are also further protocols and decrees being developed to facilitate further flow of information across government agencies under parallel Bank investments, including the ongoing Climate Change DPO and the Transforming Hydro-Meteorological Services Project (both financed by the Pilot Programme for Climate Resilience under the Climate Investment Funds) Resp: Client Due Date: Not yet due Status: Preparation 2. Implementing Agency Risks (including fiduciary) Capacity Rating: Moderate Description: There is a low risk of inadequate operational Risk Management: The two grants will be implemented with the project management and capacity for project management and technical administrative support of the Project Administration and Monitoring Team (PAMT) in the DNA. implementation. The PAMT’s support to the grants provides a mitigation measure to overall project management. The PAMT has been in place since 2012 and has a procurement specialist and a financial management specialist, as well as established reporting routines. In 2013, the PAMT experienced delays in key procurements – in part due to the increase in work associated with the floods of January 2013. The technical capacity for DEMs and hydrological analysis/modeling resides with the ARAs. Although number of technical staff is low, their capacity is deemed strong. The proposed Project includes training to address gaps in technical capacity. Resp: Client Due Date: Not yet due Status: Preparation Governance (including Fraud & Corruption) Rating: Moderate Description: There are risks associated with governance Risk Management: The PAMT will manage the governance aspects of the Project, with respect (incl. fraud and corruption) associated with business to financial management, procurement, reporting and annual independent audits. Recent environment and procurement practices noted in challenges with delays experienced in the PAMT’s processing gives the moderate rating. Mozambique that could affect the Project. Resp: Client Due Date: Not yet due Status: Preparation 3. Project Risks Design Rating: Low Description: The airborne surveys should be flown at the Risk Management: The client has been encouraged, following technical discussions during 40 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project end of the dry season (April to October, 2014); therefore, project preparation, to initiate the initial stages of procurement so that the contractor(s) for the there is a low risk that delays in the procurement process surveys can be in place as soon as possible. Procurement documents are being drafted, clearly may result in the survey window closing. identifying the airborne mission requirements to expedite the procurement process. There is a risk that inclement weather may impede or Weather during the dry season is favorable to airborne surveys. delay the airborne survey. The clear benefits associated with relevant projects and infrastructures (especially support for There is a low risk associated with the sensitivity of cooperation on transboundary waters in the Zambezi) can help mitigate the risk. ARA-Sul and acquired spatial data. Sensitivity over use of data could ARA-Zambezi have ongoing collaborations with associated authorities within Mozambique and mean that relevant authorities would not provide amongst the riparians which will facilitate the coordinating the logistical arrangements and authorisation for fly-bys required to do the mapping. necessary approvals. Resp: Client Due Date: Not yet due Status: Preparation Social & Environmental Rating: Low Description: Not applicable as no social and Risk Management: N/A environmental safeguard policies are triggered by the grants. Resp: N/A Due Date: N/A Status: N/A Delivery Monitoring Rating: Low Description: Execution of the airborne surveys, Risk Management: Technical assistance and guidance is being provided to the client during the processing of the survey data, and transfer of that data to procurement, processing, and transfer of the survey data (both as part of the Bank’s preparation the client constitute the first set of outputs. Risks to support and as integral part of project design). Technical assistance will help ensure that delivery include inclement weather and poor performance technically advanced surveys are conducted in accordance with relevant standards and on the part of the survey contractor. The second set of benchmarks and will provide quality control on the delivered survey data. outputs consists of information products to be used in decision making resulting from analysis of the survey data. Technical Assistance part of the grants will facilitate day-to-day implementation and support The risks to delivery include the government’s technical government staff in building necessary technical skills to analyze the survey data. Trainings and capacity to perform the analyses necessary to utilised the workshops will be conducted to strengthen capacity. survey data as well as the government’s capacity to disseminate the data to relevant secondary beneficiaries. The implementation of the proposed RE grants is aligned with a number of Bank supported investments: for example, the input of Lidar surveys will directly benefit flood mitigation studies There is a risk that monitoring of development impact is under the Flood Response Additional Financing (P146098) and data will become more easily made difficult by the fact that the Project is attributable to accessible through the Integrated Information Platform of the Hydro-Meteorological Services collection of topographical survey data and creation of Project (P131049). digital elevation models. Resp: Client, WB Due Date: Not yet due Status: Preparation Other Rating: Description: Not applicable Risk Management: N/A Resp: N/A Due Date: N/A Status: N/A 41 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project 4. Overall Risk Rating Comments: The overall risk rating is low because the proposed activities have strong operational linkages to associated investments (especially the National Water Resources Development Project, P107350 and the Transforming Hydro-Meteorological Services Project, P131049). Moreover, the implementing agencies are familiar with the benefits and use of the proposed Project activities as well as with World Bank processing. The fiduciary risks of the proposed Project are considered low and there are no environmental and social safeguards policies triggered under the Project. The risks associated with governance and capacity are, however, rated moderate as the Project Administration and Monitoring Team (PAMT) within the National Directorate for Water experienced delays in proceeding with procurements as planned in the recent year, in part due to the substantial increase in workload due to the floods of January 2013. 42 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project ANNEX 5: MAPS 43 MOZAMBIQUE Enhancing Spatial Data for Flood Risk Management Project Lower Limpopo and Zambezi River basins: population densities & priority survey areas Maps used in the Project Paper have been cleared by the World Bank Mapping Department (April 30, 2014). 44