January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 0 Food and water security, early warning, early action and response in Western Province, Zambia Retrospective analysis of the 2018-2020 humanitarian food and water crisis in Western Province, Zambia July 2024 CGIAR Initiative on Fragility, Conflict, and Migration Technical Report January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 1 Executive Summary The food and water crisis that affected Zambia due to prolonged dry spells between 2018 and 2020 is an example of how natural, socioeconomic, and political drivers can produce compounding impacts with long-lasting implications for development. This retrospective disaster analysis explores the risk interactions and early warning early action functioning before and during the event, to draw lessons for anticipation and response to future crises of a similar nature. Combined, the findings feed into the understanding of risk and impacts, which is crucial for improving impact-focused early warning and implementation of early actions. The Government of Zambia’s Disaster Management and Mitigation Unity (DMMU) and Zambia Red Cross Society (ZRCS), key stakeholders in the research, indicated a gap in knowledge of the drivers and impacts of the food and water crisis in Western Province and EWEA functioning at the time, especially the more remote border areas located near the border with Angola and Namibia. No retrospective analysis of the 2018-2020 crisis event has so far included a review of the functioning of the EWEA components at the time at the national and local levels. Therefore, this analysis focuses on Western Province of Zambia, specifically the Sioma, Sesheke and Shang’ombo border districts. The research provides an in-depth perspective on one of the most recent food security crises in Zambia to inform localization and strengthen early warning and early action efforts at the national and community levels. The 2023 drought event in Zambia underscores the critical need for enhanced preparedness for similar crises. This research complements ongoing initiatives for early warning for drought (e.g. through the AWARE project) and efforts within the National Technical Working Group for Forecast-Based Financing, chaired by DMMU, on drought trigger and early action protocol development. This research's focus on hazard and vulnerability interactions aligns with the move to multi-hazard contingency planning in Zambia, led by DMMU. The mixed-methods forensic analysis builds on key informant interviews, focus group discussions, peer-reviewed literature, publicly accessible data and geospatial analysis to consider compounding and cascading risk interactions in 2018–2020 in Zambia, their attendant impacts and risk drivers, and available warnings as well as the communication and early actions associated with them. Complementing ongoing initiatives to strengthen EWEA activities in Zambia for food- and water-related impacts, this study provides contextual information that can support improved targeting, early action selection, warning system design and coordination. Findings: Between 2018 and 2020, multiple hazards and risk factors converged, leading to severe food insecurity and water access challenges in Western Province, Zambia. While the main trigger for food insecurity was prolonged dry spells in the 2018/2019 rainy season, this was compounded by the impacts of COVID-19, inflation, and various crop and livestock pests. While local rainfall dynamics were the main driver of the food insecurity, low river flows and diminished water access in 2019, the crisis was deepened and elongated due to local occurrence of fall armyworms, locusts, wildlife damage of crops and later in 2020, the onset of COVID-19. In particular, the unsafe working conditions for migrants seeking employment elsewhere and wildlife attacks near water sources and crop fields were significant local impacts. The findings also highlight the variation in the onset and experience of impacts: where across Western Province, the 2018/2019 rainy season resulted in loss of harvests. In the case study area at the border of Western Province, the rainy season of 2019/2020 was considered more challenging, which resulted in prolonged impacts on food security. At the end of this second failed season, the onset of COVID-19 further influenced food security and coping mechanisms, such as migration for piecework. This highlights the need for further localization of the national early warning systems, accounting for micro-climatic variation and socio-economic and biological influences on food production and security. This study concludes that early action to address impacts on food and water access was possible based on available early warnings, yet this opportunity was missed. Despite the first early warning signals indicating a potential below-average rainy season in August 2018, and the Zambia Meteorological Department (ZMD) confirming this in their 2018/2019 seasonal outlook in September 2018, the national response by the government and humanitarian actors only began in December 2019. Although Zambia has a comprehensive Disaster Risk Management (DRM) framework, the primary challenge to early action at the national level was the mobilization of financial resources, with limited options for scaling awareness and farmer support before a disaster declaration. The lack of pre-agreed financing led to a reliance on humanitarian appeals. At the community level in the case study area, there were practical and cultural barriers to accessing early warning information and agricultural advice from ZMD and the Ministry of Agriculture. Structural barriers included poor road access, limited coverage of telecommunication and radio networks, and distance from markets. However, communities did recognize traditional early warning signs of potential drought conditions through ecological and meteorological indicators. Despite these warnings, limited knowledge of early action options and resource constraints meant communities could do little to mitigate the negative impacts on harvests during the 2018/2019 and 2019/2020 rainy seasons. While Early Warning Early Action (EWEA) would not have entirely prevented the crisis, given the large- scale food insecurity, it could have alleviated the impacts for the most vulnerable households in a more timely and dignified manner, reducing reliance on food aid. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 2 Recommendations: A robust Disaster Risk Management (DRM) framework is necessary for averting crises and effectively handling residual risks by proactively anticipating and responding to emergencies, especially when long-term investments in resilience are constrained. The event studied in this retrospective study is an example of other socioeconomic and biological crises compounding food and water-related impacts triggered by dry spells. Encouragingly, the government has recently demonstrated progress through initiatives such as multi-hazard contingency planning, fortification of local DRM committees, and bolstering response structures. Additionally, the Technical Working Group on Forecast-based Financing, under the leadership of DMMU, has been instrumental in advancing early warning and action strategies for droughts in Zambia following the studied event. The government could consider the recommendations below in advancing national early warning systems, annual contingency planning and coordination of local capacity for DRM, as well as data collection and analysis during and after future crisis events. The recommendations can also be integrated into the ongoing work on drought anticipatory action for humanitarian partners to the Zambia government. 1. Improve national-level analysis of local food insecurity and water access risks through enhanced monitoring and evaluation before, during, and after crises. The study underscores the importance of considering factors beyond hydro-meteorological hazards, such as micro-climatic conditions, food prices, exposure to wildlife, access to agricultural inputs, and mobility, as significant determinants of food insecurity. The findings also highlight a gap in data availability regarding the impacts of the crisis on rural water access, malnutrition, and other health concerns before, during, and after the crisis. Furthermore, the findings explore the connection between microclimates, food insecurity outcomes, and indigenous knowledge for early warning systems. These factors should be considered for risk assessments that inform annual contingency planning for government and humanitarian response plans. Improved risk information can inform more impact-based early warning and better targeted early action. 2. Focus on the last mile in early warning dissemination and communication by expanding dissemination channels and localizing warning messages based on forecast impact information and feasible early actions. Diversifying communication methods such as cross-border radio channels, free SMS messages, or the local chief system would be beneficial, especially in remote areas like Mbao and Imusho, which rely on extension worker visits for advisories. For future dry spell events, more cross-sectoral early warning communication is recommended – bringing together agriculture, health and water resource management departments to develop communications. Actionability of advisories should be improved in dialogue with at-risk communities, identifying viable alternative varieties to plant, strategies to protect from wildlife damage and health impacts, and recommendations for timing of activities – integrating trusted traditional early warning signals. 3. Promote and support Early Action at household, community and national scale. Early action by the government and humanitarian/development partners could have made a difference for communities in the window between the first warnings and the start of the response through livelihood support, rehabilitation of water services, sensitization to potential health risks and active monitoring of vulnerable groups for health issues (between August-December 2019), and this should be strengthened in future crises (for suggested early actions, see Figure 1). To enable early action at scale, this will need to be embedded in the standard operating procedures of DMMU and other DRM actors, ideally with a common national-level trigger for early action responsive to different types of drivers of food and water-related impacts. 4. Strengthen Mechanisms for Pre-Crisis Funding Access: Enhance efforts to access funds before crisis impacts occur. There is a need to enable early action in the Zambian disaster funding structure. Expanding access to trigger- based pre-agreed financing, coordinated through DMMU with support from the broader government, can support more proactive early action in the window between forecasts and peak impacts. Furthermore, the extensive social protection system in Zambia has the potential to offer support to farmers ahead of harvest failure, as some pilots are already underway, which could be further scaled up if accessibility, timeliness and affordability issues are addressed. 5. To effectively address the impacts of future events and reduce long-term risks, measures must also target the root causes of vulnerability and exposure. Disaster Risk Management (DRM) and Climate Change Adaptation (CCA) initiatives should address underlying vulnerabilities related to poverty, education, livelihoods, and accessibility. Communities often struggle to access the essential resources and information needed to implement early actions based on warnings, such as agricultural tools and knowledge of drought-tolerant crops like sorghum and cassava. Limited telecommunication and media coverage restrict access to vital information, while poor road conditions impede access to essential services and markets. Therefore, improving early warning systems at both national and local levels must be coupled with early action-focused support to achieve a lasting positive impact. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 3 Figure 1. Overview of potential windows of opportunity for early action in the case of similar events in the future, focusing on food insecurity impacts. In conclusion, tackling the diverse challenges of food insecurity and water access in Zambia's Western Province requires, across timescales, the involvement of local communities. Recognizing the interconnected nature of risks is key to effective disaster risk management. The retrospective analysis of the 2018-2020 food insecurity crisis in Zambia demonstrates how early warning systems can be designed to be more impactful, how community participation can be made effective, and how multi-risk strategies should be implemented. Strengthening capacity, ensuring that funding reaches local communities, and addressing the underlying causes of vulnerability are crucial for building resilience and preventing future crises. Cooperation among government entities, humanitarian organizations, research institutions, and donors is crucial to executing these recommendations and securing food and water resources in Zambia's Western Province. For an interactive visual summary of the research, please see the online StoryMap accessible through this link: https://arcg.is/1aP4vb0 January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 4 About the Institutions CGIAR is the largest agriculture innovation network with a research portfolio of US $900 million, over 3000 partners and clients in 70+ countries focused on enhancing food and nutrition security through a science-based approach to emerging development issues. The main scientific areas of focus include supporting food systems transformation, driving sustainable land and water use, supporting resilient agri-food systems, and creating genetic innovation through crop breeding and seed systems for adaptation of food and farms to meet goals for poverty reduction, gender equality, nutrition, climate, and the environment. Its research is carried out by 13 CGIAR Centers/Alliances in close collaboration with hundreds of partners, including national and regional research institutes, civil society organisations, academia, development organisations, and the private sector. The International Water Management Institute (IWMI) is an international, research-for-development organization that works with governments, civil society and the private sector to solve water problems in developing countries and scale up solutions. Through partnership, IWMI combines research on the sustainable use of water and land resources, knowledge services and products with capacity strengthening, dialogue and policy analysis to support implementation of water management solutions for agriculture, ecosystems, climate change and inclusive economic growth. Headquartered in Colombo, Sri Lanka, IWMI is a CGIAR Research Center with offices in 16 countries and a global network of scientists operating in more than 55 countries. The Red Cross Red Crescent Climate Centre (RCCC) is a technical reference centre that supports the Red Cross Red Crescent Movement and its partners in reducing the impacts of climate change and extreme weather on vulnerable people, working at the intersection of science, policy and practice. Hosted by the Netherlands Red Cross in The Hague, the Climate Centre operates with a mostly virtual team spanning more than 30 countries, as well as affiliations with universities, foundations, UN agencies, and professional associations. A core objective is to make the best global scientific insights operable at local level. Key elements include support for awareness-raising and capacity-building, especially in developing countries where people are especially vulnerable to climate change. Our focus areas include anticipatory action, heat, the intersection between climate and conflict, climate-smart disaster risk reduction, health, and social protection. Authors RCCC || Tesse de Boer, Technical Advisor IWMI || Munyaradzi Mutenje, Researcher IWMI || Ngowenani Nohayi, Senior Researcher Officer IWMI || Winnie Kasoma-Pele, Research Associate RCCC || Camila Arretche, Junior Researcher RCCC || Catalina Jaime, Manager Climate and Conflict Publication Editor Nehemiah Bridget Ncube Contributors The authors of this report would like to extend their gratitude to all the stakeholders who contributed to this retrospective analysis of the 2018-2020 food and water crisis in Zambia. Contributors to this report include: Dr. Sandra Ruckstuhl, Dr. Juan Carlos January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 5 Sanchez (IWMI), Greenwell Matchaya (IWMI), Cornelia Schulz (RCCC), Dorothy Heinrich (RCCC), Rebeka Ryvola de Kremer (RCCC), Dr. Emmanuel Poan (RCCC), Dr. Faith Mitheu (RCCC), Margret Azuma (RCCC) and Dr. Evan Easton-Calabria (RCCC). We are grateful for review support from Prof. Elizabeth Stephens, Irene Amuron and Dr. Erin Coughlan de Perez. Data collection in Western Province was carried out by IWMI Zambia, and interviews at national level by RCCC. The team wishes to thank all organizations and individuals in Zambia who shared their experiences and contributed to the report. Gratitude goes out to national partners such as the Disaster Management and Mitigation Unit (DMMU), Zambia Red Cross Society (ZRCS), extension department of the Ministry of Agriculture and the Imusho and Mbao communities for the valuable and interactive discussions. Artwork in the report and storymap was created by Rebeka Ryvola de Kremer. Acknowledgement This report was commissioned by CGIAR and co-led between the Red Cross Red Crescent Climate Centre (RCCC) and the International Water Management Institute, with financial support CGIAR Initiative on Fragility, Conflict, and Migration. CGIAR is a global research partnership for a food-secure future, dedicated to transforming food, land, and water systems in a climate crisis. We would like to thank all funders who supported this research through their contributions to the CGIAR Trust Fund: https://www.cgiar.org/funders/. The report is informed by the collaboration between the CGIAR Initiative on Fragility, Conflict, and Migration (FCM). The CGIAR Research Initiative on FCM aims to enhance the resilience of food, land, and water systems in fragile and conflict-affected settings, where migration-related challenges are prevalent. By taking a systems approach and working in partnership with local stakeholders, the Initiative seeks to generate evidence to inform effective policies and programs that promote social and gender equity, climate resilience, conflict mitigation, and peace building in these settings. More information can be found at https://www.cgiar.org/initiative/fragility-conflict-and-migration/ Citation: de Boer, T.; Mutenje, M.; Nohayi, N.; Kasoma-Pele, W.; Arretche, C.; Jaime, C. 2024. Food and water security, early warning, early action and response in Western Province, Zambia: retrospective analysis of the 2018-2020 humanitarian food and water crisis in Western Province, Zambia. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Fragility, Conflict, and Migration. 73p. Disclaimer: This publication has been prepared as an output of the CGIAR Initiative on Fragility, Conflict, and Migration and has not been independently peer reviewed. Responsibility for editing, proofreading, and layout, opinions expressed and any possible errors lies with the authors and not the institutions involved. The boundaries and names shown and the designations used on maps do not imply official endorsement or acceptance by IWMI, CGIAR, Zambia Red Cross, Climate Centre, IFRC or ICRC, our partner institutions, or donors. https://www.cgiar.org/funders/ https://www.cgiar.org/initiative/fragility-conflict-and-migration/ January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 6 Foreword Our changing climate poses unprecedented threats to humanity, not only due to the increasing frequency and intensity of hazards but also because of deeply rooted vulnerabilities that make certain populations particularly susceptible to these dangers. In Zambia, these vulnerabilities are exacerbated by factors such as poverty, fragile infrastructure, and unsustainable use of natural resources, creating conditions where the compounding effects of climate change can have devastating impacts on communities. The 2018-2020 food and water crisis in Zambia's Western Province serves as a distressing example of how multiple hazards can converge, leading to significant human suffering, economic hardship, and instability. This report, produced through the collaboration between the International Water Management Institute (IWMI), the Red Cross Red Crescent Climate Centre (RCCC), and the Disaster Management and Mitigation Unit (DMMU) of Zambia, provides critical insights into the underlying drivers of the 2018-2020 crisis. It highlights the importance of learning from past events to enhance our preparedness and mitigate the impacts of similar future crises. At DMMU, we firmly believe that a comprehensive, systems- based approach is essential to address the interlinked factors contributing to such complex situations. Understanding the root causes and interactions between various risk factors allows us to build a more resilient disaster management system. At the core of this partnership, lies the shared belief that anticipatory action—taking proactive steps to address risks before they fully manifest,- can be a powerful tool for mitigating the impacts of disasters and protecting vulnerable populations. By focusing on early identification of risks and implementing targeted interventions, we have the opportunity to break the cycle of crisis and response that has often characterized traditional disaster management. This report's findings and recommendations emphasize how investing in anticipatory measures, such as early warning systems and community-based risk assessments, can significantly reduce the impact of crises and build resilience at both community and national levels. The lessons from the Western Province’s experience highlight the need to enhance local early warning dissemination, fortify response structures, and address financial barriers that delay timely interventions. By integrating scientific data with traditional knowledge and encouraging community participation, we can ensure that early warning systems are effective and accessible to those who need them most. The adoption of anticipatory action strategies in Western Province, a region historically at the epicenter of food and water crises, could be particularly transformative, helping us to protect lives, improve livelihoods, and reduce reliance on emergency aid. Moving forward, our collective efforts must focus on co-creating context-specific, scalable, and sustainable solutions. Collaboration among government entities, humanitarian organizations, academic institutions, and local communities is vital to driving climate resilience and proactive disaster risk management. This report is a step towards a more resilient Zambia, offering a roadmap for how anticipatory action can be integrated into broader efforts to address the challenges of climate change and fragility. We hope that the findings presented here will inspire stakeholders at all levels to take action, ensuring that together, we can move beyond reactive responses and build a more resilient, just, and equitable future for all. Dr. Sandra Ruckstuhl Fragility, Conflict and Migration Initiative, Co-Lead IWMI, Senior Researcher – Climate Policies, Finance and Processes January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 7 Contents Executive Summary ........................................................................................ 1 About the Institutions ..................................................................................... 4 Authors............................................................................................................. 4 Editors .............................................................................................................. 4 Contributors .................................................................................................... 4 Acknowledgement ......................................................................................... 5 Foreword ......................................................................................................... 6 List of Acronyms .............................................................................................. 8 List of Figures ................................................................................................ 10 List of Tables .................................................................................................. 11 Chapter 1: Introduction ...................................................................... 12 Chapter 2: Methodology .................................................................... 14 2.1 Desk-based review ................................................................................. 14 2.2 Data collection .................................................................................... 14 2.3 Data analysis ........................................................................................... 15 2.4 Study limitations .................................................................................... 16 Chapter 3: Event evolution and risk drivers ....................................... 17 3.1 Crisis impacts .......................................................................................... 17 3.2 Drivers of Risk ......................................................................................... 26 3.3 Root causes ............................................................................................. 33 Chapter 4: Early Warning Early Action during 2018-2020 ................ 37 4.1 Understanding risk ................................................................................. 37 4.2 Forecast availability and monitoring .................................................... 38 4.3 Warning dissemination and communication ....................................... 40 4.4 Early action planning and implementation .......................................... 41 4.5 Financing ................................................................................................. 44 Chapter 5: Conclusion and Recommendations .................................. 47 5.1 Summary .................................................................................................. 47 5.2 Recommendations ................................................................................. 48 Annexes: ............................................................................................. 51 Annex 1. Context profile: Physical and socio-economic and governance context of Western Province, Zambia ......................................................... 51 1.1 Zambia Context ...................................................................................... 51 1.2 Disaster Risk Management (DRM) ........................................................ 52 1.3 Case study area ...................................................................................... 53 January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 8 Annex 2: Terminology .................................................................................. 56 Annex 3: Overview of climatology and forecast analysis ......................... 57 Annex 4: Overview of relevant early actions .............................................. 61 Annex 5: Geospatial analysis and supporting materials ........................... 62 References .......................................................................................... 65 List of Acronyms AA Anticipatory Action ADBG African Development Bank Group AML African Migratory Locust CERF Central Emergency Response Fund DMMU Disaster Management and Mitigation Unit DRM Disaster Risk Management DRR Disaster Risk Reduction ENSO El Nino Southern Oscillation EWEA Early Warning Early Action EWS Early Warning System FAO Food and Agriculture Organization of the UN FAW Fall Army Worm FCAS Fragile and Conflict-Affected Settings FCM Fragility, Conflict, and Migration FCV Fragility, Conflict, and Violence FGD Focus Group Discussion FLWS Food, Land, and Water Systems FMD Foot and Mouth Disease FMECD Federal Ministry for Economic Cooperation and Development Zambia GBV Gender Based Violence GRZ Government of the Republic of Zambia IOD Indian Ocean Dipole IFRC International Federation of Red Cross and Red Crescent Societies IPC Integrated Food Security Phase Classification IWMI International Water Management Institute MOA Ministry of Agriculture MTENR Ministry of Tourism, Environment & Natural Resources NGO Non-governmental organization NOAA National Oceanic and Atmospheric Administration OCHA Office for the Coordination of Human Affairs PIN People in Need RCCC Red Cross Red Crescent Climate Centre January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 9 SADC Southern Africa Development Community SADRI Southern Africa Drought Resilience Initiative SARCOF Southern Africa Regional Climate Outlook Forum SASSCAL Southern African Science Service Centre for Climate Change and Adaptive Land Management SMS Short message service UN United Nations USAID United States Agency for International Development WBG World Bank Group WARMA Water Resources Management Authority WFP World Food Programme WPA Western Province Provincial Administration WWF World Wildlife Fund ZMD Zambia Meteorological Department ZRCS Zambia Red Cross Society ZSA Zambia Statistics Agency ZVAC Zambia Vulnerability Assessment Committee January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 10 List of Figures Figure 1. Analyzed districts within the Western Province. ..................................................................................................................... 13 Figure 2. Methodology overview............................................................................................................................................................. 16 Figure 3. Overview of impact evolution over time, summarizing findings from desk review, interviews (across Western Province), focus group discussions (in the villages of Mbao and Imusho specifically) and data analysis, focusing on Western Province. Figure 3 summarizes the main findings described in 4.1-4.3. .............................................................................................................. 17 Figure 4. Food insecurity in Zambia, showing the percentage of surveyed population in IPC food security classification 3 or higher, indicating severe food insecurity, in the districts Sioma, Sesheke and Shang’ombo in Western Province. Note that seasons marked with an * are projected data by the IPC 2019, 2020, not actual observations. ....................................................... 18 Figure 5. Overview of cascading impacts from food insecurity during 2018-2020 reported in Western Province. Background image credit (edited transparency): Will Roberts CC-BY-SA-4.0, Via Wikimedia Commons. ............................................................ 21 Figure 6. Satellite imagery of western province of Zambia on 15.3.2017 (top left) and 5.3.2019 (right). The comparison highlights the extent of dried-up areas around the Zambezi River after the extremely low rainfalls during rainy season November 2018 to March. Imagery Source: Terra MODIS – NASA WorldView 2023. ...................................................................... 22 Figure 7. Satellite imagery of Imusho and Mbao. The comparison highlights the extent of the progressively dried-up areas around both communities between 2018 - 2020. Imagery Source: Google Earth Satellite Data. ................................................... 23 Figure 8. Deforestation in Imusho is reflected by comparing satellite imagery from 2017 (above) and 2020 (below) .................. 25 Figure 9. Fire Occurrences during dry seasons (Apr-Oct) 2017 & 2019. Red: low fire occurrences in 2017 and high occurrences in 2019. Orange: high fire occurrences in 2017 and low occurrences in 2019. Brown: high fire occurrences in 2017 and high occurrences in 2019. Brown: high fire occurrences in 2017 and high occurrences in 2019. Own diagram, data source: FIRMS- MODIS 2017-2019. Type: 0 = presumed vegetation fire; Confidence: >75%. .................................................................................. 25 Figure 10. Reduced food security during 2018-2020 in Zambia, cognitive map in the Western Province. Background image credit (edited transparency): Florence Devouard, CC-BY-SA-4.0, Via Wikimedia Commons. .......................................................... 26 Figure 11. Reduced surface water availability cognitive map, summarizing the main drivers and impacts. Background image credit (edited transparency): Google Earth Satellite Imagery. ............................................................................................................. 27 Figure 12. Geospatial overlay of the physical and biological drivers of risk, including the most affected areas for the following layers: 18/19 dry spells, 2019 floods, 2019 foot- and mouth disease outbreaks, January 2020 floods, COVID-19, 2020 African Migratory Locusts outbreaks. Areas with darker red colour indicate the highest number of events experienced. This figure shows geospatial co-occurrence, and some impacts are spatially disconnected, as explored in the section below. Annex 3 includes the individual maps of the identified drivers. .......................................................................................................................... 27 Figure 13. Annual precipitation anomalies for Jul. 2018-Jun 2019 (left) and Jul. 2019-Jun 2020 (right). Anomalies are computed in terms of percentage with respect to the 1991-2020 climatology as estimated by CHIRPS. Red colours depict below-average values. Data source: FEWS-NET .............................................................................................................................................................. 28 Figure 14. Satellite-observed rainfall totals timeseries (daily) for 2018/2019 and 2019/2020 rainy seasons in Sesheke, Zambia. Data source: ZMD. .................................................................................................................................................................................... 29 Figure 15. Satellite-observed rainfall monthly totals for 2018/2019 and 2019/2020 rainy seasons in Sesheke, Zambia. Data source: ZMD. ............................................................................................................................................................................................. 29 Figure 16. First row: Surface Soil Moisture (DEKAD) for 21-31 March 2018-2020 (Data source: NASA 2018-2020); Second row: Vegetation Health Index (DEKAD) for 21-31 March 2018-2020 (Data source: FAO 2018-2020). ..................................................... 30 Figure 17. Zoomed in the March 2020 Vegetation Health Index (VHI) map for Sesheke, Sioma and Shangombo districts in Western Province, Zambia (pink lined). Red areas indicate diminished VHI. Data source: FAO, 2023. ........................................... 30 Figure 18. Average prices for different varieties of Maize in the Western Province across seasons (2018-2021). Zambia has three seasons namely cool dry (May to July), hot dry (August to October) and wet rainy (November to April). Districts analysed include: Kaoma, Mongu, Nalolo, Kalabo, Lukulu, Sesheke, and Shang’ombo. (FAOSTAT, 2024). ................................................... 33 Figure 19. Average prices for different varieties of Maize in the Western Province in Shang’ombo and Sesheke (2018-2021) (FAOSTAT, 2024). ..................................................................................................................................................................................... 33 Figure 20. Summary of root causes of vulnerability in the Western Province (WIP). .......................................................................... 34 Figure 21. Full cognitive map, combining figure 10, 11 For a fully interactive version, see: https://storymaps.arcgis.com/stories/68abb7c623f7492784ac67d747958502 ................................................................................ 36 January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 11 Figure 22. Overview of potential windows of opportunity for early action in the case of similar dry spell events in the future. For more details, see Annex 4. ....................................................................................................................................................................... 50 Figure 23. Zambia Provinces. ................................................................................................................................................................... 52 Figure 24. Leadership structure in the Barotse Floodplains. ................................................................................................................ 54 Figure 25. Zambia Population Density. ................................................................................................................................................... 56 Figure 27. ENSO index (blue) and standardized precipitation anomalies over western Zambia. Source: CHIRPS and NOAA ..... 59 Figure 28. IOD time series from 2015 to 2020. Source: Bureau of Meteorology Australia, 2020 ..................................................... 59 Figure 29. Monthly precipitation anomalies for the rainy seasons Nov. 2017 - March 2020 (left to right). Anomalies are shown in mm rainfall difference from the long term mean. The long-term average rainfall was calculated from CHIRPS monthly rainfall data 1997 to 2017. Red colors are depicting below average values, blue above average. Source: own diagram, Data source: CHIRPS. ...................................................................................................................................................................................................... 60 Figure 30. Minimum monthly total rainfall (mm) during rainy season 2018-2019. Source: own diagram, Data source: CHIRPS 2018-2019. ................................................................................................................................................................................................. 63 Figure 31. Average prices for different varieties of Maize in the Western Province (2018-2021). Districts analyzed include: Kaoma, Mongu, Nalolo, Kalabo, Lukulu, Sesheke, and Shangombo. Source: FAOSTAT, 2024. ...................................................... 63 Figure 32. Drivers and impacts timeline. ................................................................................................................................................ 64 List of Tables Table 1. Overview of indigenous or traditional signals that warned communities of drought conditions. ...................................... 39 Table 2. Overview of identified potential early actions to address observed impacts on food and water security in Western Province, Zambia. ...................................................................................................................................................................................... 57 Table 3. Overview of available early warning information and abbreviated verification information for Zambia. OND = October, November, December; JFM = January, February, March, DJF = December, January, February etc……………………………….61 Table 4. Overview of identified potential early actions to address observed impacts on food and water security in Western Province, Zambia……………………………………………………………………………………………………………………………….62 January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 12 Chapter 1: Introduction There is growing recognition among emergency responders, policy makers and donors of the value of early action to reduce the humanitarian impacts of disasters in Zambia. An in-depth contextual understanding of risk factors, their root causes, and drivers can support effective strategies to respond to disasters, including government, development, and humanitarian partners' ongoing efforts for early warning and early action (EWEA). Early warning early action, also called Anticipatory Action, is one element of the disaster risk management (DRM) continuum. It refers to actions taken to reduce the humanitarian impacts of a forecast hazard before it occurs or before its most acute impacts are felt. The decision to act is based on a forecast, or collective risk analysis, of when, where and how the event will unfold (IFRC 2020c). However, EWEA is designed to manage residual risk1. Addressing the root causes of vulnerability2 necessitates a broader strategy involving disaster risk reduction, climate adaptation, and other interventions across longer timescales (Wilkinson et al., 2020). Building on successful initiatives in the humanitarian sector, there is now a growing call in the EWEA/AA community to integrate EWEA into both national and local DRM frameworks, led by national governments to ensure sustained implementation and scale (GRC, IFRC, ICRC, 2024; Anticipation Hub, 2022). Between 2018 and 2020, triggered by extensive dry spells, Zambia experienced a food security crisis and diminished water access, primarily affecting the Southern, North-Western and Western regions. Impacts included crop failures, food and water shortages, livestock deaths and reduced GDP, amongst others (IPC, 2019, 2020). As a result, in September 2019, 1.7 million people out of the total 18.4 million inhabitants in Zambia at the time, faced severe food insecurity (IPC class 3+) and a year later, by September 2020, 1.42 million people were still classified as at this level (IPC, 2019, 2020). IPC data shows that Western Province had the highest percentage of the population facing severe food insecurity (IPC class 3 or higher): up to 34% in 2019 and 40% in 2020 (IPC, 2019, 2020). Humanitarian needs were higher across the province than other affected areas (OCHA, 2019). Furthermore, the Government of Zambia’s Disaster Management and Mitigation Unity (DMMU) and Zambia Red Cross Society (ZRCS), key stakeholders in the research, indicated a gap in knowledge of the drivers and impacts of the food and water crisis in Western Province. Given the recurrence of drought conditions in Zambia due to El Nino, addressing drought-related impacts on food and water access is considered a high priority by DMMU and humanitarian partners. Located near the border with Angola and Namibia, the remoteness and diversity in local climatic conditions make this a helpful case study focused on supporting the localization of EWEA and broader DRM approaches. The 2018-2020 event is Zambia's most recent example of a food security crisis. Yet, no retrospective analysis of the event included a review of the functioning of the EWEA components at the time at the national and local levels. Therefore, the focus of this analysis is Western Province of Zambia, specifically the border districts Sioma, Sesheke and Shang’ombo – with specific attention to Sesheke district (Figure 1). While extensive dry spells in the rainy season of 2018/2019 and 2019/2020 were the main triggers for the crisis, a dynamic interplay of connected risks and societal responses converged to produce severe humanitarian impacts. Recognizing the risk interactions that result in disaster impacts, early warning early action systems and broader disaster response frameworks are increasingly trying to address risk interactions (e.g. compounding or cascading relationships). Analysing such events can improve disaster risk management planning and response (GAR, 2022). Integration of compound risk in EWEA is recognized as a challenge, and current EWEA systems typically focus on single natural hazard events. Recent examples from the global pandemic COVID-19 have revealed the inherent complexity and interconnections of risk, preparedness and response, and challenges for early warning, early action systems (de la Poterie et al., 2022; Kruczkiewicz et al., 2021). There is also an increasing recognition of the importance of a shift from hazard- to impact-based forecasting and action (RCCC, 2020; WMO, 2021), which considers economic, political, conflict, violence, migration and other elements of fragility as risk drivers (Jaime et al., 2024). During the 2018-2020 crisis, Zambia lacked a formal system for early action triggers, financing, and implementation, though some EWEA components were operational. Currently, under the leadership of the government, stakeholders are developing such a system. With ongoing initiatives to enhance early warning and action for food and water security, understanding historical risk drivers, interactions, impact pathways, and EWEA capacity is crucial. This study follows a mixed-methods retrospective approach to analyze the food and water crisis event and EWEA functioning during 2018-2020. It combines the methodology of forensic investigation of disaster events (FORIN) (Oliver-Smith et al., 2016) with a focus on cascading and compounding hazards and impacts analysis (Cavallo & Ireland, 2014; de Ruiter et al., 2020; Pescaroli & Alexander, 2016; UNDRR, 2022), and EWEA systems design (GRC et al., 2020). The study combines secondary literature and data analysis with primary interviews and focus group discussion data. We examine the role of EWEA as a key part of the process to address residual risks. Combined, the findings feed into the understanding of risk and impacts, which is crucial 1 Defined by UNDRR as “the disaster risk that remains in unmanaged form, even when effective disaster risk reduction measures are in place, and for which emergency response and recovery capacities must be maintained” (UNDRR, 2022). 2 This study differentiates between root causes of vulnerability and drivers of risk. Drivers of risk are dynamic - specific time-bound events influencing elements of disaster risk over years or decades and are the triggers of disaster events. These include climate, weather (physical drivers), biological and socio-economic (societal drivers) processes. Root causes of vulnerability involve social and economic structures, such as the characteristics of power, wealth and resources distribution, as well as ideologies and historical heritage. Such root causes may change, albeit slowly, and help explain how events result in impacts on specific people (Marchezini & Wisner, 2017). January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 13 for selecting early warning sources and theory of change for potential early actions. It also suggests areas for further strengthening of the EWEA system in Zambia based on a counterfactual approach. The results of the study will inform recommendations for long- and short-term investments in disaster risk management in Zambia, as well as climate change adaptation, including early warning/ early action. These measures aim to support the resilience of the population in the long term, and at the same time aim to support institutions and communities in anticipating unprecedented extreme events that are more likely to occur in our changing climate. The insights from 2018-2020 can be applied to anticipation of and response to future crisis events. The following research questions guide the analysis: 1. What were the underlying drivers of risk that led to the disaster event (including relevant natural, socio-economic, and political factors), and how did the various drivers interact over time in the years before the event? 2. To what extent were elements of an EWEA system in place and operational during the event? (Including understanding risks, forecast availability and monitoring, warning dissemination and communication, early action planning, and financing) The report first outlines the methodology (Chapter 2) before outlining the findings relating to drivers of risk (Chapter 3) and EWEA functioning during the event (Chapter 4). The discussion further contextualizes the findings (Chapter 5), and the report concludes with recommendations for future EWEA and DRM investments in Zambia (Chapter 5). Figure 2. Analyzed districts within the Western Province. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 14 Chapter 2: Methodology To address the research questions, a longitudinal retrospective disaster analysis of the 2018-2020 food security crisis in Zambia was conducted, specifically focusing on early warning early action. The study explored the triggering event (dry spell occurrence between 2018 and 2020), the risk drivers before, during, and after the main physical triggering event, and how early warning, early action, and response were implemented. The longitudinal retrospective disaster analysis approach builds on the Forensic Investigations of Disasters (FORIN) framework (Oliver-Smith et al., 2016). FORIN is a structured approach to understanding crisis events. It emphasises the importance of understanding the context leading up to a disaster, including the events that acted as risk drivers and the root causes (social, economic, and political conditions) contributing to vulnerability and resilience. However, FORIN does not explicitly cover a systematic and integrated approach to analysing compounding or cascading risks or any early warning or early action. Therefore, this study complements the FORIN historical framing with an in-depth assessment of early warning signals for the dry spell and food insecurity impacts, building on the Forecast-based Financing manual methodology (GRC et al., 2020). The retrospective review of the EWEA functioning at the time is structured along critical elements of the EWEA value chain: understanding risks, forecast availability and monitoring, warning dissemination and communication, early action planning, and financing. The study integrates primary qualitative data from key informant interviews and data from secondary sources (literature, geospatial and time series data), covering both research questions. The methodological framework is summarised in Figure 2 and the definitions of the terminology used are listed in Annex 2. The sections below describe the methods used. 2.1 Desk-based review First, a comprehensive literature review was carried out to identify the events, responses, and impacts that occurred before and during the crises experienced in 2019-2020 in Zambia. This review included peer-reviewed and grey literature sources selected based on their relevance and alignment with the research questions, along with stakeholder suggestions and interviews. Grey literature included humanitarian reports and appeals, research reports, governmental websites, and newspaper articles. Through the literature review, we identified the spatiotemporal occurrence of events and their interactions, and these templates formed the basis for the analysis of the event's evolution. 1. Initial literature review of academic and grey literature to populate an event/impact and EWEA timelines. The first captures the main impacts, the number of people affected, and the timing and locations affected. The second documents early warning signals and early actions and responses. 2. Impact/Driver Interaction Matrix with an overview of linked events, or drivers of risk, mentioned in the literature, which influenced the hazards, exposure or vulnerability during 2018-2020 of the affected population (Tilloy et al., 2019). The relationship between the event (triggers/direct causes; increases exposure/vulnerability; reduces impacts) with each of the impacts from the impacts calendar was noted, along with the locations affected, and short description and sources. 3. For each of the identified drivers, we summarized identified root causes of vulnerability that were highlighted in the literature. For the main physical triggers (dry spells) and impacts (food insecurity, limited water availability) of the event identified through the literature review, we further reviewed available reports and forecast information to inform the forecasts section of the EWEA system overview. For details on the hydro-meteorological forecasts assessed, see Annex 3. The main impacts and drivers of the event were then summarized geospatially, using the GIS weighted overlay approach (RCCC, 2021b), which further showed the geospatial occurrence of the drivers identified in the literature review. For details on data processing for the different layers, please refer to Annex 5. 2.2 Data collection Primary data was collected in November and December 2023 to explore the event and EWEA experience in Western Province more specifically. 1. Four semi-structured focus group discussions (FGD) on the experiences of rural communities in Mbao (2) and Imusho (2) villages, before and during 2018-2020. The FGDs focussed on the impacts during the event, the triggers for the events experienced and the access to timely and reliable early warning information and implementation of action. During the FGDs, note takers captured the information in Lozi and later translated this to English. Community members who directly or indirectly experienced the impacts of the events participated in a discussion on general conditions and context during research on the timeframe and EWEA. They were specifically asked to reflect on access and understanding of information, actions taken, challenges, lived experience of the event, and connected risk drivers. FGD January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 15 were separated by gender (one FGD for women and one for men per community) and constituted of 6-12 people, one facilitator and two note-takers. 2. Fourteen semi-structured key informant interviews with government, NGO, research/academia and humanitarian sector experts in Western Province and Lusaka. Interview questions focused on the same topics as the FGDs. Interviews were conducted in English, both online and in-person. Fourteen key informant interviews were conducted with government, humanitarian, NGO and development key actors at the national and provincial levels. Findings from the research were then shared back with community members in Mbao and Imusho villages, and key informants in Mongu during a validation research visit in March 2024, yielding additional insights and refining conclusions. Findings were also shared with national key informants to validate the findings. 2.3 Data analysis Literature, FGDs and interview data were coded in NVIVO and organized according to the following categories: event evolution and description; disaster impacts; drivers of risk/linked events; exposure and vulnerability; root causes; early action; forecast; warning dissemination; financing; response; recommendations. Interview and FGD data were then added to the impact, EWEA timeline, and impact/driver matrix. Event evolution, risk drivers and root causes of vulnerability This research combines community-based research with various desk-based methods to create an interdisciplinary historical systems perspective on the event. The emphasis is on exploring the interconnectedness of various factors contributing to the crisis at the local, district, provincial and national scales. Risk drivers are typically dynamic and can interact with each other (Wisner et al. 2014; see Annex 2 for a full glossary). To better understand the interactions between various events and processes, the analysis adds to FORIN a specific focus on cascading and compounding hazards and impacts by mapping out risk interactions (Cavallo & Ireland, 2014; de Ruiter et al., 2020; Pescaroli & Alexander, 2016; UNDRR, 2022). Based on the impact/driver interaction matrix (Tilloy et al. 2019), for the event and driver analysis (research question 1), the mixed data sources supported the creation of a timeline, cognitive map and geospatial overlay of key events identified. These were iteratively improved through stakeholder consultations and expert review. The cognitive map served as a visual representation of the interactions between the detected elements identified in the literature and interviews, providing a comprehensive overview of the complex risk dynamics at play (Bakhtavar et al., 2021; Matanó et al., 2022). Risk drivers are dynamic events influencing elements of disaster risk over years or decades and are the triggers of disaster events. These include climate, weather (physical drivers), and biological and socio-economic processes. Root causes of vulnerability involve social and economic structures, such as power characteristics, wealth and resource distribution, ideologies, and historical heritage. Such root causes may change, albeit slowly, and help explain how events result in impacts on specific people (Marchezini & Wisner, 2017). The root causes of vulnerability for each identified driver were summarized in an adapted alluvial diagram. Only linkages supported by the primary data or multiple sources in the literature were included, while other linkages with little evidence were deprioritized. EWEA functioning For the overview of EWEA functioning during the 2018-2020 period in Zambia, an integrative approach was used to synthesize the findings from the desk-based analysis (literature and forecasting data) and primary data collection. This analysis was split up following the core elements of the EWEA value chain: understanding risk, forecast availability and monitoring, warning dissemination and communication, early action planning and implementation, and financing. Based on the coded literature and primary data, the different sections synthesize the functioning of the different core elements during the 2018-2020 crisis. Understanding risk and financing was not covered extensively in the primary data, and therefore, the analysis relied mainly on the literature review for these core elements. The available forecasts and the qualitative re-analysis of timeliness and accuracy of the forecasts were based on the criteria used for early action protocol development for anticipatory action (GRC et al. 2020) and built on the ongoing drought early action protocol scoping conducted in October 2023 by ZRCS supported by the Climate Centre and 510 (ZRCS, forthcoming). For the analysis, the study used the same trigger levels as the EAP to determine whether action would have been triggered hypothetically (as no early warning early action system existed officially). Based on the analysis of available early warning information for the identified drivers of risk that triggered impacts, several windows of opportunity for early action were determined. This hypothetical overview of early warnings and early actions was then compared to information communicated and actions implemented to identify key areas for further improvement. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 16 Figure 3. Methodology overview 2.4 Study limitations This study design and implementation faces various limitations that should be considered when interpreting the findings. First, the literature review has inherent challenges in ensuring information accuracy, especially when incorporating grey literature, such as media articles and humanitarian reports, as verifying the reliability of sources can be difficult. Similarly, while interviews and FGDs provide a unique perspective on the events under analysis, they introduce subjectivity to the narrative and only cover a small sample and geographical area. To mitigate these limitations, we systematically compared information from the literature review with data gathered through stakeholder interviews, FGDs, and time series data analysis. This triangulation of diverse evidence types, aimed to alleviate inherent uncertainties in each research method. In addition, stakeholder interviews and FGDs introduce a potential source of cognitive biases. Individual motivations, personal emotions, and experiences may influence stakeholders' recollections of the period under analysis. At the time of data collection, 5 years had passed since the onset of the event. To overcome these limitations and enhance the quality of elicited information, (Browne & Rogich, 2001) suggest the use of context-dependent questions. In alignment with this, our interview questions were context-specific, focusing on the events within the period under analysis. This approach aimed to minimize cognitive biases and ensure a more accurate understanding of the stakeholders' perspectives. Furthermore, sample selection bias from the literature review and focus group interviews can yield a partial representation of the system under analysis. Recognizing this challenge, we incorporated diverse data from various geospatial and time-series sources to capture various perspectives. We also endeavoured to clarify the spatial scale findings, as some were very localized for the FGDs locations, while others applied more generally to Western Province. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 17 Chapter 3: Event evolution and riskdrivers The following chapter covers the crisis impacts in Zambia from 2018-2020 (section 4.1) and the identified drivers that either directly triggered the event or altered the exposure or vulnerability of populations (4.2). 3.1 Crisis impacts The section below outlines the major humanitarian impacts during 2018-2020 in Western Province, summarized in Figure 3. The period between 2018 and 2020 was characterized by food insecurity for households dependent on subsistence farming and fishing and a severe reduction in water availability and drinking water access in Western Province. Figure 4. Overview of impact evolution over time, summarizing findings from desk review, interviews (across Western Province), focus group discussions (in the villages of Mbao and Imusho specifically) and data analysis, focusing on Western Province. Figure summarizes the main findings described in 4.1-4.3. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 18 Food security impacts Western Province, North-Western, Southern, and Eastern provinces in Zambia saw a rapid deterioration in food security from 2018 onwards. Although the rainy season (November-March) is generally considered the lean season, most of the Western Province recorded a steep increase in food insecurity during the dry season of 2019, reaching a peak of 60% of people in extreme food insecurity (IPC phase 3 or higher) during the 2019 rainy season in some districts (Sioma and Shang’ombo notably) (IPC, 2020; Figure 4). Food insecurity impacts in Sesheke were delayed compared to Sioma and Shang’ombo, peaking in 2020. This aligns with findings from focus group discussions, where communities experienced 2020 as the most problematic year with local variation in dry spell occurrence, availability of food from the market and coping capacity, as will be discussed in the following sections. Figure 5. Food insecurity in Zambia, showing the percentage of surveyed population in IPC food security classification 3 or higher, indicating severe food insecurity, in the districts Sioma, Sesheke and Shang’ombo in Western Province. Note that seasons marked with an * are projected data by the IPC 2019, 2020, not actual observations. “ [During the drought period of 2018-2020, red.] farmers who had planted crops experienced complete crop loss, and at the community level, the impact translated into heightened levels of hunger. This period marked a time when the country recorded significantly elevated hunger levels, accompanied by various other challenges. People became malnourished due to a lack of sufficient food.] KI14 Food production decreased substantially in the 2018-2020 period, affecting food availability for subsistence households and households dependent on the markets. All FGDs highlighted the lack of harvests in 2018/2019 and 2019/2020 and the depletion of food stocks early in the rainy seasons. There were differences in the reported harvests in the two villages where FGDs were conducted, which also deviated from the findings based on the interviews. Across Western Province, interviews and literature underline the high crop losses during the 2018/2019 season due to prolonged dry spells. The 2018/2019 dry spell affected 72% of fields in Western province (Mpundu & Sichilima, 2020). The main staple crop production of maize decreased by 16.3% nationally in 2019 compared to the previous season, reflecting a 31.6% decrease from the 5-year average (2014-2018) (FAO, 2019). Similarly, rice production (paddy) also decreased by 18.7% nationally compared to the previous season (FAO, 2019). FGDs in Mbao indicated that 2018/2019 already came with poor harvests and food shortages, worsening over 2019/2020. In Imusho most impacts were experienced in 2019/2020, considered a worse season, as illustrated by the quote below. Harvests were better for those who could plant earlier, as rains stopped very early in 2018/2019 and January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 19 2019/2020 (KI03). The main reason for the low yields was dry spells3, which affected staple crops in the crucial flowering stages, resulting in high crop losses. Furthermore, according to some women in focus group discussions, remaining crops, such as more drought-resistant sorghum and millet, were eaten by wildlife or affected by locusts. “ No one harvested anything. The only people that had food are those that reserved maize from the previous growing season, and they were selling it at very high price. FGD1 May 2019, the Ministry of Agriculture communicated an overall expectation of reduced production compared to the 2017/2018 season of key staple and cash crops, specifically: season rice (-31%); sorghum (-49%); millet (-23%); maize (-16%) (MoA, 2019). The 2019/2020 season National Food Balance Sheet reported a deficit of 354,930 megatons of maize for human and industrial consumption, mainly due to the decrease in crop production of the 2018/2019 season, according to the Ministry of Finance (2019). Nationally, the improved rainfall conditions in 2019/2020 were reflected in the improvements in production for key staple crops such as maize (+69%), sorghum (+200%), rice (+17%) and millet (+81%) (MoA, 2020). This is at odds with the local experience in Imusho and Mbao, as discussed above. Access to food from the market was also greatly hindered by high food prices, up by 15.9% from February 2019 to February 2020 (IMF, 2019; Open Zambia, 2020), impacting household expenditures. In the Western Province, household cereal stocks had already dwindled over the first three months of the 2019–2020 season, and FGDs also underlined the early onset of hunger (IFRC, 2021b; FGD1-4). Due to the decrease in staple crop production, various affected households were left to turn to the market to access food (OCHA, 2019), as these ran out of their produced stock earlier than normal (ZVAC, 2019). Across Zambia, high household expenditure on food was reported, with 39% of drought-affected households nationally spending over 65% of their income on food (OCHA, 2019). Food prices are further explored in Section 4.2. “There was crop failure due to high temperatures and insufficient moisture, also, due to a few people that managed to harvest, there was the high food price, especially for maize grain ... The prices of maize grain were high just across the country, not really attributable to one geographical location, but it was just at a general level across the country” (KI01). As a result of the low yields and high food prices, high rates of wasting and undernutrition were reported, particularly affecting young children and the elderly (KI04; KI03; ZVAC, 2019). Severe acute malnutrition levels were already increasing in the year before the dry spells – showing a particularly large prevalence of wasting in Western Province (GRZ, 2019). The most recent 2018 Demographic and Health Survey (ZSA, 2020) found stunting in 35% of children below the age of 5, with 4% stunting and 12% underweight nationally. In July 2019, the Zambia Vulnerability Assessment Committee developed an in-depth vulnerability and needs assessment that supported these values as high levels of under-nutrition and stated that Zambia is one of the countries with the highest burden of under-5 malnutrition in Africa (ZVAC, 2019). In the Western Province, the assessment found many districts with a prevalence of wasting above the national average (4%), with a provincial average of 6%. Shang’ombo (33%) and Sioma (29%) were the most affected districts. In 2019, across Western Province, 65,254 children under five were screened, finding 1,539 children aged 6 to 59 months with Severe Acute Malnutrition (SAM) and 1,320 Moderately Acutely Malnourished (MAM) (CERF, 2020). The impacts in Shang’ombo district were also observed by humanitarian actors and similar experiences were recorded for other districts in Western Province: 3 Dry spells are periods of interrupted rainfall within the rainy season, which can have a significant (often disastrous) impact on livelihood activities. In agriculture, for example, a dry spell lasting more than three weeks is commonly regarded as a climatic event with a major impact on the crop cycle. Dry spells can also occur either at the beginning of the season, with the effect of delaying the start-up of agricultural activities, or at the end of the season, with the effect of penalizing the harvest. Consequently, it is important to anticipate these dry spells and to have an efficient system for monitoring the season. Droughts, on the other hand, are measured over a relatively longer period (than dry spells), often from a few months to a few years. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 20 “ 2019 was bad for Shang’ombo district. When we went on the ground, we found people had not eaten for more than a week. They were surviving on a wild tuber called Ndowa. This root if eaten too much, you die in your sleep, if you eat little your feet swell. Many people especially the elderly and young ones had died of hunger. Villages were empty, everyone went to dig the tubers. KI13 Faced with challenges in accessing food from subsistence production or markets, communities resorted to other coping mechanisms. Many focus group discussions mentioned a shift to gathering wild fruits and tubers/roots. However, for communities living in or near national parks, the search for edible roots was restricted in 2020 by the Zambian Wildlife Protection Authority, according to focus group discussion participants. Elderly people were found to have the lowest coping capacity, as they were less mobile and could not venture out to collect food. Some participants recalled instances where elderly people living alone passed away from hunger. While these stories cannot be verified directly, the increased malnutrition rates by official sources, as described above, underline the severity of this issue. Negative coping strategies were also employed, increasing vulnerability over time. Overfishing of the rivers was discussed, which had implications for fish stocks in the subsequent years. Fishing exposed people to detainment by border soldiers along the Cuando River bordering Angola (KI03; KI05). Based on interviews, focus group discussions and reports, school drop-out rates also increased as families could not afford school fees anymore (Rosen et al., 2021; Focus Group Discussions; Bank of Zambia, 2020). Some community and primary schools had to close since students were forced to abandon school in search of other sources of income to alleviate food insecurity (CERF, 2020). “ As a result of food insecurity, young marriages dissolved, people skipped meals for two days, and people gathered wild fruits, tubers, vegetables, and fish for survival. Twenty percent of the schoolchildren dropped out of school. FGD2; FGD4 As a result of the socio-economic impacts of the high food insecurity and lack of livelihood options, various cascading impacts and (negative) coping strategies were mentioned that influence the long-term vulnerability of communities (Figure 5). All focus group discussions mentioned that early marriages became more frequent and that tensions increased between men and women in the household. Some community members mentioned an increase in theft and an increase in teenage pregnancies as well. This aligns with findings from Rosen et al., 2021. Several interviewees mentioned a local increase in gender-based violence (KI01; KI04; KI08). However, these incidents were not reported in focus group discussions. In the border districts of Western Province, such as Sesheke, migration to Namibia and Angola was a commonly reported coping strategy. Estimates of the number of people who moved away range from 75-90% based on focus group discussions and interviews, of which a sizable portion relocated permanently (up to 90% of those who migrated, according to the Mbao focus group discussions). Women (mainly middle-aged) moved to Namibia for piecework. These women faced mistreatment and underpayment and were sometimes detained because they lacked travel documents (FGD1; KI07). The impacts on the village due to the migration of some of its inhabitants were evident from focus group discussions, which emphasized the large number of people who had not yet returned. The departure of the young working population and parents was described as having left the elderly and children more vulnerable to future shocks. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 21 Figure 6. Overview of cascading impacts from food insecurity during 2018-2020 reported in Western Province. Background image credit (edited transparency): Will Roberts CC-BY-SA-4.0, Via Wikimedia Commons. Impacts on water resources Rural communities in Western Province are highly reliant on rivers, streams, wells and boreholes for their own drinking water, water for livestock for fishing and other water-based livelihood strategies such as reed-mat making. Between 2018 and 2020, underground and surface water resources were reduced drastically in the province, leading to water shortages in which most traditional water sources dried up. The Barotse floodplains, for example, which form the main economic water source in the Western Province, were highly affected (see Figure 6 for an illustration). The floodplains provide favourable land for fish breeding, and farmers are also highly dependent on the flooding season for farming (Chihango Kabanda & Mapanza Sikananu, 2021). While the Western Province is among the areas receiving the lowest rainfall per year in Zambia, floods are an annual recurrence due to the proximity to the Zambezi River and tributaries as well as the Cuando River. Floods in the Barotse floodplains are celebrated each year at the start of the rainy season with the Kuomboka ceremony, one of the most famous traditional ceremonies which signals the period when people move from the floodplains to the uplands with their livestock. Several interviews highlighted the importance of floods for the local economy and traditional ceremonies, as floodwaters support the fish population (a significant source of livelihood) and replenish soil moisture. However, in 2019, the ceremony was cancelled due to low river levels, and in 2020 due to COVID-19 (Lusaka Times, 2019b, 2020). “ Perennial rivers dried up, patches in the rivers with water were not healthy for drinking and boreholes dried up by May 2020. Men accompanied women to fetch water 5-10km away to protect women from wildlife (jackals, lions, leopards, elephants, and crocodiles). FGD1 January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 22 Impacts in Western Province, where people are strongly connected to and dependent on the rivers that flow through the province, are not only driven by rainfall dynamics locally. Basin-wide dynamics related to rainfall, evaporation and water abstraction determine river flows, which sometimes have a time lag compared to local rainfall dynamics. Local dry conditions reported for the 2019-2020 rainy season and the following months are supported by satellite imagery of the study sites (Figure 7). While there is limited data for the Cuando River, such information exists for the other major river system passing through Western Province, the Zambezi River. Across the Zambezi basin, the year 2019 (including the tail-end of the 2018/2019 rainy season) was characterized by deficient rainfall, which slightly recovered in 2020, in line with earlier mentioned local observations (Hulsman et al., 2021). According to a press statement released by the Zambezi River Authority, the Zambezi River flows monitored at Victoria Falls were at 800m3/s in March 2019, greatly below the 2,522m3/s long-term average (Zambezi River Authority, 2020). These values continued to decrease, reaching 349m3/s by January 2020 and recovering by the end of March (Idem). Water storage levels were also extremely low in both 2019 and 2020 across the basin, especially at the Kariba dam just downstream of Western Province in Zambia, which was strongly influenced by evaporation and slow recovery from the previous dry year (Hulsman et al., 2021). The low levels in the Kariba dam also resulted in power cuts and electricity shortages across the country, as Zambia´s energy is 85% hydropower (FMECD, 2022). This generated electricity rationing (load shedding), which progressively worsened in 2019, greatly impacting those areas with irrigated agriculture (Kabisa et al., 2019a;KI05). By December 2019, load shedding occurred for a minimum of ten hours (N. Nkhuwa, 2020). This contributed locally to the shift to charcoal-production and selling in Western Province as described in section 4.1 (WWF, 2021b; KI09). A Ministerial Statement issued by the Minister of Energy in February 2020 stated that the Kariba Reservoir was 10% full compared to 43% the previous year (N. Nkhuwa, 2020). Electricity generation in the country remained a significant concern by February 2020, primarily attributed to the low rainfall in the 2018/19 season (N. Nkhuwa, 2020). In March 2020, the Guardian warned that Zambia continued to face severe water and electricity shortages as the rains were insufficient to refill reservoir levels after the prolonged dry spells (Gibbons, 2020). Figure 7. Satellite imagery of Western Province of Zambia on 15.3.2017 (top left) and 5.3.2019 (right). The comparison highlights the extent of dried-up areas around the Zambezi River after the extremely low rainfalls during rainy season November 2018 to March 2019. Imagery Source: Terra MODIS – NASA WorldView 2023. Image (down right): Reference map of above imagery extent (red rectangle). January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 23 Figure 8. Satellite imagery of Imusho and Mbao. The comparison highlights the extent of the progressively dried-up areas around both communities between 2018 - 2020. Imagery Source: Google Earth Satellite Data. In Zambia, around 829,000 people die from diarrhoea annually due to unsafe water (Chihango Kabanda & Mapanza Sikananu, 2021). The Western Province has one of the lowest rates for access to improved water supply in Zambia (49%) (African Development Bank Group, 2014), greatly affecting the vulnerability of these areas to dry spell events as more unreliable sources of water dry up. The reduced surface water availability resulted in issues for humans and animals. During 2018-2020, humanitarian actors reported issues in drinking water access and increased use of poor-quality groundwater for drinking and domestic purposes (Green Climate Fund, 2018b; IFRC, 2021a; OCHA, 2019; ZVAC, 2019). Reports and interviews also mentioned an increase in water-borne diarrheal diseases (IFRC, 2020; KI3; KI4). Of the two villages covered with FGDs, only Imusho village experienced an increase in water-borne diseases, yet epidemiological data on this is missing4. All focus group discussions also highlight the lack of clean drinking water, increases in the time spent to fetch water, and safety issues due to wild animals close to water points (see for example the quote below). 4 Similarly, one interviewee mentioned poor air quality due to dried soils and respiratory issues as a health impact. There were no reports to corroborate this finding. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 24 Furthermore, increased interactions of livestock and wild animals due to sharing dwindling water resources and increased proximity of humans to wildlife while fetching water led to an increase in human-wildlife conflict and attacks close to water sources. This finding was mentioned repeatedly in all focus group discussions, as well as interviews in Western Province. This issue was particularly rife in areas where communities live close to or in national parks and where migration routes of elephants cross through. Attacks from crocodiles (KI07; KI09) and elephants (KI04; KI07; KI14) were mentioned as key issues. “ When the river water levels decrease, animals go to deeper waters, where people also fish, and reports of attacks by hippos, elephants, and crocodiles increase. KI07 Limited surface water and loss of pasture also resulted in negative impacts on livestock health, due to dehydration, lower reproduction rates and increased exposure to diseases (KI08; KI09; Banda et al., 2021; Rosen et al., 2021; ZVAC, 2019; Ministry of Finance, 2019). The sharing of few available water sources between humans and livestock, as well as wildlife, contributed to an increase in livestock disease outbreaks (e.g. foot-and-mouth disease, anthrax) (KI11; OCHA, 2019). The onset of these diseases reduced the ability of affected households to sell their livestock to supplement their income (ZVAC, 2019). Focus group discussions also emphasised the variability of prices of livestock, with some households having to sell at very low prices, resulting in long-term impacts on their livelihoods. Long-term shifts in livelihood strategies were also mentioned by those who would normally depend on fishing and reed-mat- making. As these livelihoods weren’t viable anymore in 2018/2020 due to low water levels, many villages shifted to charcoal- based livelihoods in the province (KI09; KI10). As one interviewee put it: “[…] people opted to sell charcoal in town so that they can return home with a bag of maize to feed their families. In the past, you would find coal in Senanga or Sesheke but today you find it everywhere across Western Province.” (KI09). Positively, findings from the research indicate that conflicts over land and water resources were rare. Most interviewees mentioned that the traditional land governance system, and particularly the interference of local chiefs and traditional courts (described in Annex 1) supported dispute settlement and abated most tensions over land- and water resources (KI04; KI07; KI14). However, some interviews (KI08; KI05) mentioned rare instances where tensions over productive land and water resources between host communities and those moving to find alternative livelihood options emerged, and cases where people moved to areas where aid was distributed. Load shedding due to nationwide energy shortages also contributed to increased charcoal demand and higher selling prices (Mpundu & Sichilima, 2020). This shift to charcoal-based heating and selling of charcoal locally influenced deforestation and fire occurrences (Mpundu & Sichilima, 2020). Analysis of fire occurrence shows pronounced increases in fire occurrences in 2019 compared to 2017 (Figure 9). Wood harvesting to make coal is a significant driver of deforestation in Western Province, usually done by starting a fire (Ngoma et al., 2023; WWF, 2021a). Besides timber harvesting for charcoal production and heating, deforestation and fire occurrence are also driven by field burning for agricultural expansion (Chomba et al., 2012; GRZ, 2023; Masikati et al., 2021). Although not mentioned in the interviews, an agriculture assessment of the Western Province (PIN, 2018a) also reflects that low expected yields due to uncertain seasons in the uplands of the Western Province tend to reduce farmers’ invested labour time and increase less suitable field management practices, like burning fields during clearance and in between seasons. This further enhances the impacts of the dry spells by decreasing the capacity of fields to hold water and shortening their production period (Keddy, 2003)This also compounded impacts on dry spell exposure locally in the long term, as deforested areas typically see more soil moisture loss and higher temperatures. In Imusho and Mbao, deforestation and wildfires were considered significant drivers of the impacts experienced between 2018 and 2020. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 25 Figure 9. Deforestation in Imusho is reflected by comparing satellite imagery from 2017 (above) and 2020 (below) Figure 10. Fire Occurrences during dry seasons (Apr-Oct) 2017 & 2019. Red: low fire occurrences in 2017 and high occurrences in 2019. Orange: high fire occurrences in 2017 and low occurrences in 2019. Brown: high fire occurrences in 2017 and high occurrences in 2019. Brown: high fire occurrences in 2017 and high occurrences in 2019. Own diagram, data source: FIRMS- MODIS 2017-2019. Type: 0 = presumed vegetation fire; Confidence: >75%. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 26 3.2 Drivers of Risk This section further explores the different drivers of risk that contributed to the impacts described in section 4.1, based on the analysis of risk interactions from interviews, FGDs, literature and other secondary data. These drivers are categorized as physical, biological, or socio-economic. The cognitive maps below summarize the findings of the drivers of risk and specific factors determining exposure and vulnerability for 1) food insecurity impacts (Figure 10) and 2) water resource impacts (Figure 11). The full cognitive map is captured in Figure 21. Figure 12 shows the geospatial overlay of the various drivers identified. Figure 11. Reduced food security during 2018-2020 in Zambia, cognitive map in the Western Province. Background image credit (edited transparency): Florence Devouard, CC-BY-SA-4.0, Via Wikimedia Commons. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 27 Figure 12. Reduced surface water availability cognitive map, summarizing the main drivers and impacts. Background image credit (edited transparency): Google Earth Satellite Imagery. Figure 13. Geospatial overlay of the physical and biological drivers of risk, including the most affected areas for the following layers: 18/19 dry spells, 2019 floods, 2019 foot- and mouth disease outbreaks, January 2020 floods, COVID-19, 2020 African Migratory Locusts outbreaks. Areas with darker red colour indicate the highest number of events experienced. This figure shows geospatial co-occurrence, and some impacts are spatially disconnected, as explored in the section below. Annex 3 includes the individual maps of the identified drivers. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 28 Physical risk drivers Drought conditions 2018/2019 and 2019/2020 Interviews, situation reports, and focus group discussions directly link the food and water crisis of 2018 - 2020 to prolonged dry spells during the 2018-2019 and, in some cases, the 2019-2020 rainy seasons, along with non-physical drivers related to food prices and access. However, the definition of the dry conditions behind the 2018-2020 food insecurity crisis is not straightforward due to local differences in climatology and hydrology. Both rainy seasons (2018-2019 and 2019-2020) saw below-average total rainfall in the southern half of Western Province (Figure 13). The rainy season of 2018/2019 was characterized by prolonged dry spells, a late start, early cessation, and below-average total rainfall across the Western, Southern, Lusaka and Central provinces (Figure 13; Giriraj & Niranga, 2022). According to the Zambia Meteorological Department (ZMD), the 2018-2019 rainy season was one of the worst in the southern half of the country since 1981 (OCHA, 2019). Figure 14. Annual precipitation anomalies for Jul. 2018-Jun 2019 (left) and Jul. 2019-Jun 2020 (right). Anomalies are computed in terms of percentage with respect to the 1991-2020 climatology as estimated by CHIRPS. Red colours depict below-average values. Data source: FEWS-NET However, focus group discussions in the Sesheke district (Mbao and Imusho villages) highlighted the 2019/2020 season as having the most drought impact. This crisis experience deviates from the general crisis timeline based on interviews and situation reports (Figure 3). In 2019-2020, total rainfall was slightly better compared to the previous season across the province (Figure 13). However, rainfall data from Sesheke district shows that the 2019-2020 season was characterized by multiple false starts to the rainy season, prolonged periods of little to no rain (albeit fewer compared to 2018-2019) and short periods with very intense rainfall (Figure 14). Although total rainfall was higher in 2019/2020, the rainfall peak arrived considerably late, in Feb-March (Figure 14 and Figure 15). Due to the late start, with multiple “false starts” (December 2019) and relatively early cessation, farmers were unsure when to plant and harvest. However, both the vegetation health index and soil surface moisture index show 2018- 2019 to be the driest season in Western Province, but in 2019-2020, there were still areas facing dry conditions (Figure 16 and Figure 17). Nonetheless, soil moisture and rainfall data do not fully explain the deviation in the experience of dry conditions and failed harvests in 2019-2020, compared to 2018-2020 locally in the focus group discussion locations. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 29 Figure 15. Satellite-observed rainfall totals timeseries (daily) for 2018/2019 and 2019/2020 rainy seasons in Sesheke, Zambia. Data source: ZMD. Figure 16. Satellite-observed rainfall monthly totals for 2018/2019 and 2019/2020 rainy seasons in Sesheke, Zambia. Data source: ZMD. January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 30 Figure 17. First row: Surface Soil Moisture (DEKAD) for 21-31 March 2018-2020 (Data source: NASA 2018-2020); Second row: Vegetation Health Index (DEKAD) for 21-31 March 2018-2020 (Data source: FAO 2018-2020). Figure 18. Zoomed in the March 2020 Vegetation Health Index (VHI) map for Sesheke, Sioma and Shangombo districts in Western Province, Zambia (pink lined). Red areas indicate diminished VHI. Data source: FAO, 2023. Inter-annual variability: ENSO and IOD On an inter-annual timescale, El Ninõ Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) dynamics influence rainfall dynamics strongly across Zambia (Gachigonta & Reason, 2006; Palmer et al., 2023). In 2018-2019 and 2019-2020, rainfall dynamics correlated (negatively) with a positive ENSO phase (El Nino). Positive ENSO is typically linked to rainfall deficits across southern Africa and Zambia, although these episodes were relatively moderate compared with, for example, 2015. The 2018- 2019 season was also marked by a neutral to a slightly negative IOD, which would either have a slightly negative or a neutral effect on precipitation. For more details, see Annex 3. Changes in climatology Changes in climatology can be considered a driver of risk, influencing the hazard occurrence and intensity over the past decades. While the dry spells of 2018-2020 fall within the boundaries of natural variability in Zambia, dry spell occurrences have increased in frequency over the past 60 years and mean annual rainfall has decreased by a rate of 1.9mm per month since January 25 | Food and water security, early warning, early action and response in Western Province, Zambia 31 1960 (SADRI, 2021). Average temperatures have also been increasing, reflected in a 0.7 °C increase for the wet season and a 2.3 °C increase in the dry season between 1982 and 2015, influencing evapotranspiration (Mwongera et al., 2020). The mean annual temperature across Zambia is also expected to increase between 1.9 °C and 2.3 °C between 2050 – 2100 (Mwongera et al., 2020)5. Extreme heat Beyond the dry spells in the rainy seasons of 2018/2019 and 2019/2020, other hydro-meteorological conditions (indirectly) contributed to the observed impacts in Western Province. Participants in focus group discussions and interviewees (KI01, KI02) mentioned that high temperatures towards the end of 2018 and at the start of 2019 contributed to the loss of soil moisture and evapotranspiration, affecting crops and water sources and influencing health outcomes for humans and livestock. One interviewee also mentioned observing issues such as heatstroke in community visits in Western Province, although no data confirmed this. Floods in Northern, Central, Eastern and Southern Provinces In 2019 and 2020, the northern, central, and eastern areas of Zambia were affected by floods and water logging. The floods damaged agricultural production, which was meant for domestic markets. This likely contributed to increased food prices across the country, as the south was simultaneously facing the second consecutive season with prolonged dry spells (European Commission, 2019; IPC, 2020). Biological drivers of risk COVID-19 The global onset of COVID-19 in February/March 2020 compounded the impacts of the prolonged dry spells in Zambia. As of December 2020, Zambia had seen 17,916 cases of COVID-19, with 364 registered deaths (OCHA, 2020). One interviewee mentioned that they lost many people active in agricultural support and dedicated farmers during the pandemic, which influenced the government's ability to support farmers during dry spells (KI14). Furthermore, the measures initiated in response to the pandemic, strongly contributed to food insecurity due to limitations in market access, mobility, and the ability of households to earn income. During interviews and focus group discussions, it was mentioned that in the border districts of Western Province, where the economy is strongly dependent on trade and migration to Namibia and Angola, border closures had a significant impact on communities' livelihoods and ability to buy food (KI01; KI06; FGD2; FGD4). People could not go to markets across the border nor send back remittances (FGD2). Other measures included closing schools and airports, restricting travel to large gatherings, and closing recreational activities (bars, restaurants, etc.) (CERF, 2020). All four focus group discussions touched on the drastic price increase of staple foods in early 2020 due to the dry spells and the co-occurrence of COVID-19. Not only did the COVID-19 crisis directly contribute to food insecurity, but the restrictions and budgetary consequences also negatively impacted the response to the food security crisis in 2020. It was repeatedly mentioned in interviews that school feeding programmes had to stop, and disaster response efforts were slowed down due to lockdown measures (KI07; KI04; KI06). In some cases, ongoing resilience-building activities for farmers were paused, and the COVID-19 response resulted in reduced budgets for NGOs and the government to respond to the impact of food insecurity (KI04; CERF, 2020). Furthermore, the health system was overrun in the first months of the pandemic. While agricultural production improved as rainfall and soil moisture recovered mainly to normal levels in 2020 across Western Province (with local differences), the increase in food prices and impacts of COVID-19 at the national, district and household levels prolonged the crisis and had lasting impacts on coping capacity of communities, extending the food security crisis further into 2020. Fall armyworm Fall armyworm (FAW) outbreaks contributed to crops' destruction across Zambia in the 2018/2019 season (KI01;