CGIAR Initiative on Fragility, Conflict, and Migration Technical Report Nature-based Solutions for Human and Environmental Resilience: The Case of Dolo Ado and Bokolmayo Districts, Somali Regional State, Ethiopia Wolde Mekuria, Awdenegest Moges, Rediet Girma, Getahun Yakob, Tirusew Teshale, Alemseged Tamiru Haile and Sandra Ruckstuhl September 2024 Author affiliations Wolde Mekuria, Senior Researcher - Environment and Development, International Water Management Institute (IWMI), Addis Ababa, Ethiopia. (w.bori@cgiar.org) Awdenegest Moges, Associate Professor, Biosystems Engineering, School of Biosystems and Environmental Engineering, Hawassa University, Hawassa, Ethiopia. (awde_moges@yahoo.co.uk) Rediet Girma, Lecturer, Hawassa University, Hawassa, Ethiopia. (red8.girma@gmail.com) Getahun Yakob, Researcher and Deputy Director, Central Ethiopia Agricultural Research Institute, Durame, Ethiopia. (getahunyakob@gmail.com) Tirusew Teshale, Lecturer, Hawassa University, Hawassa, Ethiopia. (tirusew2000@gmail.com) Alemseged Tamiru Haile, Senior Researcher - Hydrology/Hydrological Modeling, IWMI, Addis Ababa, Ethiopia. (a.t.haile@cgiar.org) Sandra Ruckstuhl, Senior Researcher, IWMI, Giza, Egypt. (s.ruckstuhl@cgiar.org) Suggested citation Mekuria, W.; Moges, A.; Girma, R.; Yakob, G.; Teshale, T.; Haile, A. T.; Ruckstuhl, S. 2024. Nature-based solutions for human and environmental resilience: the case of Dolo Ado and Bokolmayo districts, Somali Regional State, Ethiopia. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Fragility, Conflict, and Migration. 40p. Acknowledgements This work was supported by the Norwegian Government under the project titled ‘Learning Support for a Sub-Saharan Africa Multi-Country Climate Resilience Program for Food Security,’ and by the donors who fund the CGIAR Research Initiative on Fragility, Conflict, and Migration (FCM), through their contributions to the CGIAR Trust Fund: https://www.cgiar.org/funders/ The authors thank Darshini Ravindranath (Research Group Leader - Climate Policies, Finance and Processes [CPFP], IWMI, Delhi, India) for feedback and input provided on the initial versions of this publication. Daniel Ocom (Resilience and Livelihood Specialist, World Food Programme [WFP], Dolo Ado, Somali Region, Ethiopia) is also thanked for coordinating all field activities and logistics as well as for the feedback and input provided on the initial versions of this publication. The authors are also grateful to WFP staff (Abdiwahid Ibrahim, Mohamed Mohamud and Asho Gedi) for supporting and facilitating the fieldwork. CGIAR Initiative on Fragility, Conflict, and Migration The CGIAR Initiative on Fragility, Conflict, and Migration 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. Learn more about the initiative here: https://www.cgiar.org/initiative/fragility-conflict-and-migration/ Cover photo: In situ water harvesting structure constructed in agricultural land in Central Ethiopia Regional State (Photo: Wolde Mekuria). Disclaimer This publication has been prepared as an output of the CGIAR Initiative on Fragility, Conflict, and Migration (FCM) and has not been independently peer reviewed. Responsibility for 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, our partner institutions, or donors. mailto:w.bori@cgiar.org mailto:awde_moges@yahoo.co.uk mailto:red8.girma@gmail.com mailto:getahunyakob@gmail.com mailto:tirusew2000@gmail.com mailto:a.t.haile@cgiar.org mailto:s.ruckstuhl@cgiar.org https://www.cgiar.org/funders/ https://www.cgiar.org/initiative/fragility-conflict-and-migration/ Contents List of Figures .....................................................................................................4 List of Tables .......................................................................................................4 List of Boxes ........................................................................................................4 Acronyms and Abbreviations ..........................................................................5 Summary 6 1. Introduction 6 2. Materials and Methods 8 2.1. Study Area....................................................................................................8 2.2. Approaches ..............................................................................................10 2.3. Data Collection and Analysis .................................................................10 2.3.1. Societal challenges and efforts made to address the challenges ..10 2.3.2. Biophysical assessment ...................................................................... 12 2.3.3. Land-Use and Land-Cover analysis ...................................................13 2.3.4. Assessment of the status of land degradation ................................ 13 2.3.5. Flood mapping ..................................................................................... 13 2.3.6. Socioeconomic characterization ......................................................14 2.3.7. Identification of nature-based solutions options and mapping potential areas for implementation ............................................................14 2.3.8. Assessment of the potential environmental benefits of nature-based solutions .........................................................................................................16 2.3.9. Assessment of the economic viability of the nature-based solutions ...........................................................................................................16 2.3.10. Assessment of success and failure factors ...................................... 17 2.3.11. Analysis of dependency ratio ............................................................ 17 2.3.12. Qualitative data analyses ................................................................... 17 3. Results and Discussion 18 3.1. Biophysical Characteristics ....................................................................18 3.2. Socio-economic Characteristics ...........................................................19 3.3. Land-use and Land-cover Changes ......................................................20 3.4. Land Degradation Status ........................................................................22 3.5. Societal Challenges ................................................................................22 3.6. Potential Nature-based Solutions to Address the Challenges ..........26 3.6.1. Experience in using nature-based solutions ....................................26 3.6.2. Identified potential nature-based solutions ...................................27 3.7. ....Ecological and Socioeconomic Benefits of Identified Nature-based Solutions ...........................................................................................................29 3.8. Economic Viability of the Identified Nature-based Solutions ...........31 3.8.1. Input and output variables ..................................................................31 3.8.2. Economic viability of nature-based solutions ...................................31 3.9. Key Success and Failure Factors .............................................................32 3.10. Sources of Financing ..............................................................................33 4. Conclusions and Recommendations 34 References 35 Annex 39Ph o to g ra p hy b y W o ld e M ek ur ia September 2024 | Nature-based Solutions for Human and Environmental Resilience | 3 List of Figures Figure 1. Location map of the study districts and refugee camps. ............................................................................................ 8 Figure 2. Interannual variability of annual rainfall in the study districts. ......................................................................................... 9 Figure 3. Refugee camps and hosted numbers of refugees in the study area. ............................................................................. 10 Figure 4. Group discussions. Left: workshop participants (top) and UN organizations and NGOs participants (bottom). Right: private sectors and cooperative participants (top) and participants from government office sectors (bottom). ........ 11 Figure 5. Solar-based irrigation scheme in Dolo Ado, Somali, Ethiopia ........................................................................................ 11 Figure 6. Community consultation with three irrigation cooperatives. Top: left corner, Labraho (left), Berwako (right), and Hormd irrigation cooperative members (bottom). ......... 12 Figure 7. Biophysical characteristics of the study districts: (a) Mean annual rainfall, (b) altitude, (c) slope, (d) agroecological zones, and (e) major soil types. ................................................. 18 Figure 8. Livestock type and head count in the study area. .. 19 Figure 9. Fruits growing along the Genale River, Papaya and Mango (top) and Banana (below). .............................................20 Figure 10. Land-use and land-cover classes of the study areas for the years 2010 and 2024. ......................................................21 Figure 11. Land degradation status for a period of 14 years (2010–2024): (a) using LP sub-indicator, (b) LC, (c) SOC, and (d) land degradation status using the three indicators in combination. ...............................................................................22 Figure 12. Irrigated farms affected by floods in Melika-Dida, Bokolmayo, Somali, Ethiopia. ...................................................25 Figure 13. Free grazing in irrigated farms in Dolo Ado, Somali, Ethiopia. ........................................................................................25 Figure 14. Flood map of the study area between 2017 and 2023. .............................................................................................26 Figure 15. The spatial distribution of suitable areas to implement identified NbS: (a) water harvesting, (b) agroforestry, (c) riparian plantation, and (d) ecological restoration practices. ET refers to Eyebrow terrace, LB-Level bund, FJ-Fanya-juu, PFM - Participatory Forest management, RM-Rangeland management, RWH-Rooftop water harvesting, SC-Semicircular catchment, TR-Tied ridges, and ZP-Zay pits. ...................................................................................28 Figure 16. The spatial distribution of (a) NDVI values and (b) AGB. ..............................................................................................30 Figure 17. Enabling or favorable conditions to implement NbS to address societal challenges. .................................................32 List of Tables Table 1. Characteristics of consulted irrigation cooperatives. ............................................................................... 12 Table 2. Inclusion and exclusion criteria to map potential areas for nature-based solutions. ............................................. 14 Table 3. Land-use and land-cover classes of the study area. Values are area in hectare. .........................................................21 Table 4. Societal challenges of refugees, IDPs, and host communities from the perspective of the participants of the inception workshop. ...................................................................23 Table 5. Potential area for implementing the identified nature- based solutions............................................................................27 Table 6. Ecological and socio-economic benefits of identified nature-based solutions...............................................................29 Table 7. Above-ground biomass and carbon stock estimates across different LULC types using satellite data. ....................30 Table 8. Discounted costs and benefits of the identified nature-based solutions (USD, 1 ha model). .............................32 Table 9. Potential financing mechanism for the identified nature-based solutions...............................................................33 List of Boxes Box 1. Efforts made by communities to address the challenges. ..................................................................................26 List of Figures List of Tables List of Boxes 4 | Nature-based Solutions for Human and Environmental Resilience | September 2024 Acronyms and Abbreviations ISRIC .................. International Soil Reference Information Center AGB .............................................................. Aboveground Biomass CBR ........................................................................Cost-Benefit Ratio CHIRPS .........................................Climate Hazards Group InfraRed Precipitation with Station data CPFP ................................Climate Policies, Finance and Processes CV ................................................................. Coefficient of Variation DBE ..................................................Development Bank of Ethiopia DEM ..............................................................Digital Elevation Model DR .........................................................................Dependency Ratio DR0 ........................................................ Old age dependency ratio. FGDs ........................................................ Focus Group Discussions GIS .............................................. Geographic Information Systems GoSR ................................................Government of Somali Region IDPs ...................................................... Internally Displaced People IUCN ....................International Union for Conservation of Nature IWMI ........................... International Water Management Institute KC ..........................................................................Kappa Coefficient LC ......................................................................................Land Cover LP ............................................................................Land Productivity LULC ....................................................... Land-Use and Land-Cover NbS ..............................................................Nature-based Solutions NDVI ..............................Normalized Difference Vegetation Index NGO ...........................................Non-Governmental Organization NIR ..................................................................................Near Infrared NORAD ....... Norwegian Agency for Development Cooperation NPV .........................................................................Net Present Value OA ...........................................................................Overall Accuracy PA ......................................................................... Producer Accuracy PFM...........................................Participatory Forest Management, R ...........................................................................................Red bands RM ..............................................................Rangeland Management ROAM.....Restoration Opportunities Assessment Methodology RWH .......................................................Rooftop Water Harvesting, SDG ............................................... Sustainable Development Goal SEPAL ................................................System for Earth Observation Data Access, Processing and Analysis for Land Monitoring SOC ...................................................................Soil Organic Carbon UA .................................................................................User Accuracy UNCCD ............................................ United Nations Convention to Combat Desertification WFP ..................................................................World Food Program WRI ...........................................................World Resources Institute Ph o to g ra p hy b y W o ld e M ek ur ia SepteSeptember 2024 | Nature-based Solutions for Human and Environmental Resilience | 5 Summary The Somali Region of Ethiopia is prone to climate-induced displacement and hosts the highest number of internally displaced people (IDPs) due to drought nationwide. Addressing the vulnerability of local communities (i.e., refugees, IDPs, and host communities in this study) to natural hazards, such as drought and floods as well as environmental (soil, vegetation) degradation, requires humanitarian and development strategies to reconcile life-saving objectives and environmental safeguarding. With this consideration, implementing nature-based solutions (NbS) could be one option to balance the objectives of life-saving and environmental management activities. Therefore, the present study was conducted in the Dolo Ado and Bokolmayo districts, Somali Region, Ethiopia to: (i) identify NbS to address the vulnerability of refugees, IDPs, and host communities to natural hazards, and (ii) map potential areas for implementing the interventions. It used multiple methods, such as an inception workshop, reconnaissance surveys, focus group discussions (FGDs), Geographic Information Systems (GIS), and remote sensing techniques to collect and analyze data. In addition, it used two frameworks — the IUCN Global Standard for NbS and the Restoration Opportunities Assessment Methodology (ROAM) — to identify, design, and verify NbS. The results suggest that the study area experienced significant landscape alteration in the last 15 years. Specifically, the increase in farmlands at the expense of forestland, grasslands, and shrublands reflects an evolving agricultural landscape that demands attention to sustainable practices. It is also detected that a considerable proportion (28%) of the land area is degraded, suggesting the need for targeted interventions, especially in grasslands and bare lands, to mitigate or at least reduce degradation risks and natural hazards such as drought and floods. This study identified several context-specific NbS options, which can be classified as water harvesting measures, ecological restoration measures, agroforestry practices, and buffer zone management practices. The NbS vary in cost, trajectory, and specific economic and social outcomes. Most of the NbS were found to be economically viable, environmentally friendly, and socially acceptable. Existing favorable policies and frameworks, active participation of stakeholders in humanitarian and resilience-building activities, enormous government interest, and the possibilities of establishing early warning systems in refugees, IDPs, and host communities can be considered as opportunities for wider implementation of NbS. We offered key recommendations for future actions in the areas of coordination and active participation of stakeholders, capacity building and learning, natural resources management, empowerment of local communities, enforcement of existing policies, the use of adaptive management tools and approaches, and financing mechanisms of NbS. Overall, the study underscores the importance of integrated NbS tailored to local environmental conditions and socioeconomic contexts to better address societal challenges, such as drought and flood. 1. Introduction Climate change and land degradation are impacting the life, health, and security of people worldwide; poor communities and displaced populations are particularly at risk (Ahmed et al. 2021). Growing disaster risk — driven in part by largescale environmental degradation and climate change — threatens to exceed the humanitarian sector’s capacity to respond in the coming decades. With over 20 million people a year displaced by climate-related natural hazards over the last decade (Oxfam 2019), there is an urgent need to find new approaches to reduce risk and save lives. Specifically, the living conditions and lack of reliability of essential services among the displaced populations increase their vulnerability to the negative impacts of climate change on their life, health, and security (Barrett et al. 2021). The refugee populations in the settlements are highly exposed to extreme weather conditions, particularly drought and floods (ibid). This high level of exposure, in combination with often limited abilities to cope and adapt, enhances the vulnerability of these already marginalized populations and their host communities and reduces their ability to create sustainable livelihoods. Ethiopia is one of the most vulnerable countries to weather extremes and land degradation due to the high level of poverty as well as its dependence on key sectors most prone to be affected by climate change and land degradation, such as agriculture, water, tourism, and forestry (World Bank Group 2020). For example, the Climate Resilient Green Economic Strategy of Ethiopia (FDRE 2011) estimated that an area of 9 million hectares of forest might be deforested by 2030, aggravating the vulnerability of local communities. Ethiopia is also among the countries most affected by internal displacement, with 4.4 million internally displaced people (IDPs) nationwide (IDMC 2022). Most of them have been displaced because of conflict and violence (3.6 million), but many have also moved because of disasters, including drought (0.8 million). The Somali Region of Ethiopia, the study area, is particularly prone 6 | Nature-based Solutions for Human and Environmental Resilience | September 2024 to climate-induced displacement. As a result, the government of the Somali Region has recognized climate change as one of the main drivers of displacement in this region; further, it has identified people displaced by drought as a target group in its Durable Solutions Strategy for 2022–2025 (GoSR 2022). In the Somali Regional State, persistent poverty and poor coordinated efforts and development are driving unsustainable natural resource use and undermining the resilience of rural communities (Shigute et al. 2022). Major sources of food and water security problems in the study area include soil erosion, deforestation, biodiversity loss, lack of watershed management, and degrading rangelands. These varying problems are further compounded by unemployment and climate change, making marginalized communities even more vulnerable. Addressing the vulnerability of local communities to natural hazards, such as drought and flood, and environmental degradation requires humanitarian and development interventions to reconcile life-saving objectives with environmental safeguarding standards (Laird et al. 2022; Tsegay and Gezahegne 2023; Kang et al. 2023). With this consideration, implementing NbS could be one option to balance the objectives of these two areas of action (Battistelli et al. 2022). According to Cohen-Shacham et al. (2016), “NbS are actions to protect, sustainably manage and restore natural and modified ecosystems in ways that address societal challenges effectively and adaptively, to provide both human well-being and biodiversity benefits”. Cohen-Shacham et al. (2016) further elaborated that NbS is an “umbrella” concept which includes several types of ecosystem-based approaches, such as protection, restoration and sustainable management of natural resources and ecosystems, to address societal challenges such as disasters, human health, and food and water security. They also included natural/green and hybrid (combined natural and engineered/built or ‘grey’) infrastructure. Specifically, NbS in arid and semi-arid regions can be categorized (Simelton et al. 2021) as: { Rainwater harvesting: Collecting and storing rainwater through construction of small-scale water harvesting systems such as rooftop water harvesting, check dams, and percolation pits. { Agroforestry practices: Planting trees and shrubs in agricultural and communal lands to improve soil fertility, reduce soil erosion, and increase water retention capacity of soils. { Soil and water conservation: Implementing measures such as contour bunds, fanya-juu, bench terraces, and mulching to help reduce soil erosion and improve soil moisture. { Ecological restoration: Restoring degraded natural ecosystems such as forests, wetlands, and grasslands through implementing assisted natural regeneration (e.g., exclosures), reforestation/afforestation, and restoration of freshwater ecosystems. Local people accessing water from the Genale river, Somali region, Ethiopia. Photography by Wolde Mekuria September 2024 | Nature-based Solutions for Human and Environmental Resilience | 7 These measures support improving biodiversity, carbon sequestration, and ecosystem services as well as provide opportunities to diversify livelihoods. This study aims to identify and map NbS to address the vulnerability of refugees, IDPs and host communities to natural hazards in the Somali Regional State of Ethiopia. The specific objectives were to (i) identify and analyze the opportunities or potentials for implementing NbS to environmental sustainability, resilience, and disaster risk management, (ii) locate specific areas for each NbS considered as suitable for the study area, (iii) determine the area extent of opportunities for each NbS, (iv) assess the economic feasibility of identified NbS, (v) assess the gain in biodiversity and integrity of ecosystems, and (vi) assess success and failure factors. The assessment is limited to two districts, Dolo Ado and Bokolmayo, of the Somali Regional State. 2. Materials and Methods 2.1. Study Area The study was conducted in Dolo Ado and Bokolmayo districts, Liben Zone, Somali National Regional State, southeastern Ethiopia (Figure 1). According to the displacement tracking matrix of the International Organization for Migration, close to 1 million forcibly displaced people currently exist in the Somali Regional State, the largest number of displaced people in a single region in the country. Of these, conflict and violence have displaced an estimated 518,000 persons, and the impact of climate change, including drought, seasonal flash floods, and landslides have displaced another 415,000 people. Women, children, and marginalized groups have been the most impacted by displacement induced by conflict and weather extremes, such as drought and floods. Figure 1. Location map of the study districts and refugee camps. Source: Authors’ creation. 8 | Nature-based Solutions for Human and Environmental Resilience | September 2024 The study districts cover an area of 8,133.8 km2. The elevation of the districts ranges from 189 to 974 meters above sea level. Shrublands and grasslands are the two major land-use and land-cover (LULC) types, covering about 75% of the total land area. The long-term (1980–2023) mean annual rainfall of the Dolo Ado district is 238 mm; for Bokolmayo district, it is 308 mm. Dolo Ado and Bokolmayo districts experience significant variations in annual rainfall (Figure 2). For example, in the Dolo Ado district, the coefficient of variation (CV) of the annual rainfall for a period of 42 years was 42%, suggesting high interannual rainfall variability (Asfaw et al. 2018). Similarly, the interannual variability of rainfall was also high (CV of 40%) in the Bokolmayo district. Detailed description of the biophysical profile of the study districts is presented in Section 3.1. A nn ua l R ai nf al l ( m m ) Year Dol Ado Bokolmayo 1980 100 200 300 400 500 600 700 1985 1990 1995 2000 2005 2010 2015 2020 2025 Figure 2. Interannual variability of annual rainfall in the study districts. Source: Authors’ creation. With an estimated 238,987 members of the host community in the Dolo Ado and Bokolmayo districts (UNHCR 2020), the total population, including refugees, is about 453,068. Of the total population of the host communities, 58.2% (138,980) and 41.8% (100,007) were found in the Dolo Ado and Bokolmayo districts, respectively (UNHCR 2020). The average family size in the host communities is estimated to be six (UNHCR 2020). In the study area, five refugee camps were established between 2009 and 2011 (Figure 3, Betts et al. 2019), located adjacent to the small host towns and communities. The houses in the camps were constructed from wooden walls and corrugated iron rooftops and are managed by UNHCR. According to UNHCR (2024) registration data (updated in June 2024), UNHCR provides support to around 216,721 refugees (Figure 3), almost exclusively Somali refugees in semi-arid and isolated border districts. The IDPs, in most cases, are temporary; they stay with host communities during the time they receive assistance from humanitarian organizations. Key societal challenges of refugees, IDPs and host communities are discussed in Section 3.6. September 2024 | Nature-based Solutions for Human and Environmental Resilience | 9 Hosted population (No.) D o lo A d o B o ko lm ay o 20,000 40,000 60,000 80,000 100,000 120,000 Buramino Total Helaweyn Bokolmayo Kobe Melkadida Total 116,199 43,613 39,279 33,307 100,522 48,797 51,725 Figure 3. Refugee camps and hosted numbers of refugees in the study area. Source: Authors’ creation. 2.2. Approaches The study used two frameworks, the IUCN Global Standard for NbS (IUCN 2020) and the Restoration Opportunities Assessment Methodology (ROAM) (IUCN and WRI 2014) to identify, verify and design NbS options for the study location. The IUCN Global standards can be applied to both large-scale and small-scale interventions. The criteria used in the IUCN global standard for NbS (IUCN 2020) provide a framework to assess social challenges, design the solution to respond to the scale of the challenges, assess tradeoffs, use adaptive management approaches, and ensure sustainability. The ROAM framework used in this study (IUCN and WRI 2014; Moges et al. 2023) comprises five steps: need assessment based on national priorities, identification of potential tree-based NbS, assessment of potential areas for each tree-based NbS, and assessment of the economic viability of interventions and enabling environments. 2.3. Data Collection and Analysis The study used an inception workshop, reconnaissance surveys, key informant interviews, FGDs, literature reviews, and GIS and remote sensing techniques to gather data. Data were gathered on (i) societal challenges, (ii) biophysical and socioeconomic characteristics of the study districts, (iii) potential NbS and available areas, (iv) environmental benefits and economic viability of NbS, and (vi) success and failure factors to determine the feasibility of NbS. The quantitative and qualitative data analyses are discussed in the below sections. 2.3.1. Societal challenges and efforts made to address the challenges We used an inception workshop and reconnaissance surveys to collect data on societal challenges. The inception workshop gathered 24 participants together (Figure 4). The participants represented multiple stakeholders: government offices, such as water, agriculture, livestock and disaster risk management (8), non-governmental organizations (1), humanitarian organizations (7), community-based organizations, such as cooperatives (2), private sector (3), and local administrative bodies (3). These participants were organized into three groups: (i) humanitarian organizations and NGOs, (ii) government offices, and (iii) private sector. Each group discussed farm and household characteristics of refugees, IDPs, and host communities, societal challenges, and previous efforts made by the government, NGOs, and the private sector to address challenges. We gathered these diverse groups to understand the societal challenges and efforts made from the perspective of different groups of a community. Following the inception workshop, three days of reconnaissance surveys were conducted. The reconnaissance surveys were guided by the outputs of the inception workshop. Accordingly, we visited two irrigation schemes, one in Bokolmayo and one in Dolo Ado district (Figure 5) and consulted with three irrigation cooperatives (Figure 6). Details on the irrigation cooperatives consulted are summarized in Table 1. 10 | Nature-based Solutions for Human and Environmental Resilience | September 2024 Figure 4. Group discussions. Left: workshop participants (top) and UN organizations and NGOs participants (bottom). Right: private sectors and cooperative participants (top) and participants from government office sectors (bottom). Figure 5. Solar-based irrigation scheme in Dolo Ado, Somali, Ethiopia Ph o to g ra p hy b y W o ld e M ek u ri a Ph o to g ra p hy b y W o ld e M ek u ri a September 2024 | Nature-based Solutions for Human and Environmental Resilience | 11 Figure 6. Community consultation with three irrigation cooperatives. Top: left corner, Labraho (left), Berwako (right), and Hormd irrigation cooperative members (bottom). Table 1. Characteristics of consulted irrigation cooperatives. Name of irrigation cooperative District Kebele Village Irrigated area (ha) households (No) Years since developed Labraho Bokolmayo Melika-Dida Hello Sale 35 70 2 years Berwako Dolo Ado Kobe 47 65 2 years Hormd Dolo Ado Helawyn Gudbukol 50 100 Note: In the Labraho cooperative, 15 out of the 70 households are refugees. In the Berwako cooperative, 30 of the 65 households are refugees. Of the 65 households, 20 are headed by women, while 45 are headed by men. In the Hormd cooperative, 50 of the 100 households are host communities while the remaining 50 households are refugees. Of the 50 households of host communities, 10 are headed by women, while 40 are headed by men. 2.3.2. Biophysical assessment Field visits, GIS and remote sensing methods, and literature reviews were used to characterize the biophysical features of the two districts. The long-term (1985–2023) inter-annual rainfall variability was characterized using data obtained from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) available at https://data.chc.ucsb. edu/products/CHIRPS-2.0/global_annual/tifs/. Topographic features such as altitude, slope steepness, and aspect were characterized using the freely available high-resolution (12.5 m) digital elevation model (DEM) acquired from Alaskan Satellite Facility (https://search.asf.alaska.edu/#/). We used altitude and long-term mean annual rainfall (Hurni et al. 2016) to characterize the agroecological zones. The soils of the study districts were characterized using the latest FAO Harmonized World Soil Database version 2.0 (https://gaez.fao.org/pages/hwsd) and the SoilGrids raster layer at 250 m spatial resolution developed by the International Soil Reference Information Center (ISRIC) (https://soilgrids.org/). The dynamics of the LULC classes were assessed using 30 m resolution Landsat images (Path = Ph o to g ra p hy b y W o ld e M ek u ri a 12 | Nature-based Solutions for Human and Environmental Resilience | September 2024 https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_annual/tifs/ https://data.chc.ucsb.edu/products/CHIRPS-2.0/global_annual/tifs/ https://search.asf.alaska.edu/#/ https://gaez.fao.org/pages/hwsd https://soilgrids.org/ 166 and Raw = 57) for 2010 and 2024, which were mosaiced and retrieved from the System for Earth Observation Data Access, Processing and Analysis for Land Monitoring (SEPAL) open-source portal (https://sepal.io). Specific to estimating the area of irrigated farmlands, we used Google Earth Pro and digitized it manually. The Sentinel-2 multi-spectral at red and near-infrared bands was used to derive values for normalized difference vegetation index (NDVI) (Muhe and Argaw 2022). 2.3.3. Land-Use and Land-Cover analysis This analysis included the following components: { Land-Use and Land-Cover Classification: Prior to LULC classification, image pre-processing and enhancement operations were performed to improve the quality of the raster images. The hybrid classification (unsupervised and supervised classification) approach, which helps to accurately analyze larger areas characterized by diverse biophysical composition, was used for LULC classification (Girma et al. 2022; Moges et al. 2023). { Accuracy Assessment: We evaluated the performance of image classification using accuracy assessment statistics (Dey et al. 2021), such as overall accuracy (OA), user accuracy (UA), producer accuracy (PA), and kappa coefficient. { Land-Use and Land-Cover Dynamics: For each LULC class, the change in area between two years was determined by subtracting the area of a specific class in the first year from the area of the same class in the second year. The annual rate of change per category was determined by dividing the change in area by the number of years between the two datasets (Girma et al. 2022). The transitions from one LULC class to another were determined using the transition matrix in ArcGIS (Zhang et al. 2017). 2.3.4. Assessment of the status of land degradation The assessment and monitoring of land degradation status was carried out based on the Good Practice Guidance prepared for the Sustainable Development Goal (SDG15) (Sims et al. 2019). Specifically, the analysis employed indicator 15.3.1 developed by the United Nations Convention to Combat Desertification (UNCCD) (Schillaci et al. 2023). Based on the SDG 15.3.1 framework, the analysis considered three sub-indicators: land productivity (LP), land cover (LC), and soil organic carbon (SOC). In this study, we used 2010 as the base year and 2024 as the target year. The QGIS3.36 Trends.Earth plugin and Google Earth engine were used to assess land degradation status. Land Productivity sub-indicator: The LP sub-indicator (kg ha-1yr-1) was determined from a time series of the annual NDVI dataset. The dataset is provided by the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices (MOD13Q1). We used the 2010 and 2024 datasets to detect the changes in LP over a period of 15 years. To consider the effects of the availability of water on LP, we used the Water Use Efficiency correlation method (Trends.Earth 2022). Land Cover sub-indicator: To assess the LC sub-indicator, the 2010 and 2024 custom LULC data were used and reclassified to forestlands, grasslands, croplands, wetlands, artificial areas, bare land, and waterbodies using the UNCCD reporting and the Intergovernmental Panel on Climate Change land classification. Afterward, the LC transition matrix between 2010 and 2024 was analyzed to detect the dynamics of LULC changes. Then, to compute LC indicator values, land degradation typologies were created using experts’ knowledge and experience. This was done to identify areas corresponding to degradation, improvement, or no change. Finally, Trends.Earth computed the values of LC degradation between 2010 and 2024 by combining the information from the LULC analyses and degradation typologies. Soil organic carbon sub-indicator: The relative change in SOC (t ha-1) was determined using a combined LC change per year and SOC approach in Trends.Earth. Changes in SOC stock due to LULC changes were determined using the approach outlined by Schillaci et al. (2023). Areas experiencing a loss of > 10% of SOC during the reporting period were considered potentially degraded, and areas experiencing a gain of > 10% of SOC were considered potentially improved. Finally, the three sub-indicators were integrated into a final SDG 15.3.1 indicator map using the ‘one-out all-out’ rule (Schillaci et al. 2023; Trends.Earth 2022). An area was considered potentially degraded if it was identified as potentially degraded by any of the three sub-indicators. Otherwise, if at least one indicator showed a positive trend and none showed a negative trend (or neutral), it was considered as improved. Only when all indicators remained unchanged was the indicator considered stable for reporting purposes (Schillaci et al. 2023). 2.3.5. Flood mapping The main input data for flood mapping were remote sensing images from multiple satellites — which were optical images from Sentinel-2 (10 m resolution) and Landsat (30 m resolution) and synthetic aperture radar images from Sentinel-1 satellites. In addition, community consultation was conducted to identify the maximum flood extent in the study area and to provide ground truthing data for training the remote sensing algorithm for flood detection. This was followed by a transect walk to validate the information from the community. The images were atmospherically corrected prior to application for flood detection. After comparing multiple indices for the study area, the Enhanced vegetation index and the Root of Normalized Image Difference were found to perform flood detection using optical and radar September 2024 | Nature-based Solutions for Human and Environmental Resilience | 13 https://sepal.io/ images, respectively. Hence, these indices were used to generate the maximum flood extent of the two districts for the period extending from 2017 to 2023. 2.3.6. Socioeconomic characterization We used an inception workshop, reconnaissance surveys, market observations, literature reviews, and national databases to characterize the socioeconomic profile of the study districts in terms of (i) major livelihood mechanisms of local communities (i.e., refugees and host communities), (ii) demography, (iii) land holdings and tenure systems, and (iv) policies, strategies, rules, regulations, bylaws, and practices in relation to the use and management of natural resource. Information on major livelihood mechanisms of local communities was largely gathered through an inception workshop, reconnaissance surveys, and literature reviews. Data on demography was obtained from the latest available population and housing census of Ethiopia (CSA 2007) and grey literature (e.g., UNHCR annual reports). A literature review was mainly used to gather data on land holdings and tenure systems, policies and strategies, and socio-ecological practices in relation to the use and management of natural resources. 2.3.7. Identification of nature-based solutions options and mapping potential areas for implementation We used literature reviews (both published and grey), reconnaissance surveys, key informant interviews and field observations to identify potential NbS suitable for the study districts. While reviewing potential NbS, similarities 1 NbS supporting the protection, restoration, and sustainably managing the ecosystem. 2 Contributions of NbS to addressing natural disasters due to weather extremes and food and water insecurity. 3 Contributions of NbS to enhance biodiversity and human well-being by leveraging ecosystem services. in climate, tree cover, land-use and topography were considered. Furthermore, the criteria outlined by Albert et al. (2021) were used to identify potential NbS. These include contributions to (i) protection and restore1, (ii) address societal challenges2, (iii) improve biodiversity and well- being3, and (iv) the sustainable management of both natural and modified ecosystems. To map potential areas for the identified NbS, inclusion and exclusion criteria were developed by the team of experts (Table 2). The inclusion and exclusion criteria were mainly based on LULC, slope, rainfall, agricultural systems, and management. Key limiting factors to implement a given NbS option were also considered. For example, rooftop water harvesting can also be implemented in towns and settlement areas with corrugated iron rooftops (inclusion criterion, Table 2). In other words, we exclude rural areas with grass- thatched houses (Table 2). Similarly, for some of the in-situ water harvesting structures, we decided the maximum limit for rainfall amount because high rainfall areas need to be excluded (Table 2). Once such inclusion and exclusion criteria were set and upper and lower limits for each variable decided, ArcGIS spatial analysis tools and techniques were used to identify suitable areas for each NbS. While mapping such potential areas for the identified NbS, we carried out activities outlined by Khahro et al. (2019), such as (i) delineating buffer zones of freshwater ecosystems, roads, and wetlands, (ii) overlay analysis to identify areas that meet multiple criteria simultaneously, (iii) selection based on a specific attribute (i.e., using inclusion or exclusion criteria), and (iv) Boolean logic (and, or) to combine multiple mappings of suitable areas. Table 2. Inclusion and exclusion criteria to map potential areas for nature-based solutions. Nature based solution category/practices Cases for inclusion Cases for exclusion 1. Rainwater harvesting 1.1. Rooftop water harvesting Towns and settlement areas with corrugated iron roof tops. Grass thatched houses in rural areas. 1.2. In-situ water harvesting Tied ridges (Biazin and Stroosnijder 2012) Cultivated land with rainfall ranging from 280 to 680 mm; Level to slightly slopy areas. High rainfall areas and steep slopes. Pits, Zay Cultivated land with annual crops; rainfall 350–600 mm; slope < 5%. Areas with low rainfall and slope range greater than 5% Level bunds and fanya-juu Cultivated land; slope 3–50%; rainfall 300–600 mm. Slope > 50%; areas covered with shrubs and grasses. Continued > 14 | Nature-based Solutions for Human and Environmental Resilience | September 2024 Nature based solution category/practices Cases for inclusion Cases for exclusion Eyebrow terrace Tree and shrublands; rainfall 200–600 mm; slope 1–50%. Cultivated areas. Semicircular catchments Rainfall > 300 mm; slope 0.5–5%; run-on runoff area 4:1 to 8:1. Tree and shrublands. Meskata Rainfall 200–400 mm; slope 2–15%; run on: runoff area 2:1. Annual crop producing areas; steep slopes; slopes > 15%. The annual crop producing areas are excluded because they are mainly used for fruit and olive trees. Negarimb Area covered with fruit trees; rainfall 150–600 mm; slope 1–5%; run-on runoff area 3:1 to 25:1. Annual crop producing areas; slope > 5%. Mainly used for growing trees and afforestation/reforestation purpose. Flood water harvesting- within the stream bed Cultivated land for crops and fruit production. Areas that do not generate enough runoff. Jessour -terraced wadi Rainfall 150–200 mm; slope > 5%; dry stream bed. Flat slope areas; areas less than 0.2 ha. 1.3. Flood water diversion Presence of seasonal river; rainfall 150–200 mm; slope 5–30%. Permanent water course; abundant rainfall 1.4. Storage structure Ponds Clay soils with low permeability; topographic position/landscape suitable for installing pond and has sufficient catchment area for runoff generation. High permeability; no catchment. Underground reservoirs- sand dams Seasonal rivers; sufficient flood for recharge; rainfall > 200 mm; riverbed slope 0–5%; width 5–25 m; stream order 1–3 and catchment size 0.15–366 km2 (Yifru et al. 2021). Dry riverbeds. 2. Agroforestry Live fencing Homesteads; tree cover < 30%; average annual rainfall > 250 mm. Farmlands far from homesteads; tree cover > 30%; annual rainfall < 250 mm. Shelterbelts Areas affected by wind erosion; tree cover < 30%; Average annual rainfall > 250 mm. Less wind erosion affected areas; tree cover greater than 30%; annual rainfall < 250 mm. Boundary planting Farmlands and homesteads; tree cover < 30%; average annual rainfall > 250 mm. Mechanized and large-scale farming; tree cover > 30%; annual rainfall < 250 mm. Scattered trees on farmlands Smallholder farmlands with tree cover < 30% or < 24 trees/ha; average annual rainfall > 250 mm. Mechanized and large-scale farming; tree cover > 30% or > 24 trees/ha; annual rainfall < 250 mm. 3. Riparian buffers/ plantations Date palm tree (Phoenix dactylifera L.) plantation along the major riverbanks Buffer zones of major rivers (up to 50 meters from the rivers). Farmlands with rainfed agriculture; tree cover > 30%. Banana plantation Buffer zone of major rivers (up to 50 meters from the rivers). Farmlands with rainfed agriculture; tree covers > 30%. Fodder bank (e.g., trees such as Sesbania Sesban and elephant grass) Buffer zone of major rivers (up to 50 meters from the rivers). Farmlands with rainfed agriculture; tree covers > 30%. Continued > September 2024 | Nature-based Solutions for Human and Environmental Resilience | 15 Nature based solution category/practices Cases for inclusion Cases for exclusion 4. Ecological restoration Exclosure Bare land and degraded shrub/bush lands; tree cover of < 30%. Water bodies and farmlands; altitude > 3700 m and < 500 m. Rangeland management Area of land that is occupied by native herbaceous or shrubby vegetation with tree cover < 30%. Water bodies and farmlands; altitude > 3700 m and < 500 m. Participatory forest management Area of land that is occupied by shrub and forest with tree cover > 30%. Farmlands, bare land, and degraded shrub/ bush lands; tree cover of < 30%. Notes: a The meskat micro-catchment system consists of a catchment area called “meskat”, of about 500 m2 in size, and a cropping area called “manka” of about 250 m2. The ratio between catchment and cropping area is 2:1. The entire meskat system is surrounded by a 20 cm high bund equipped with spillways to let excess runoff. The system is mainly used to crop fruit trees. b Negarims are diamond-shaped micro-basins surrounded by low earth bunds. The distance between the most distant points is 5–30 m. They are mainly used for growing fruit trees, fodder bushes, and reforestation. Most suitable in flat areas with slopes not greater than 5%. Negarims are constructed by handwork, so the labor demand is relatively high. 2.3.8. Assessment of the potential environmental benefits of nature-based solutions The quantitative assessment of the expected environmental benefits of the identified NbS was limited to estimating carbon accumulation due to the implementation of NbS categorized under ecological restoration (Table 2). The aboveground biomass (AGB) was estimated using a biomass function that considered NDVI as an independent variable using Equation 1 (Fantahun et al. 2022). log10AGB = 0.812 + 1.762(NDVI) .......... (Eq.1) Where NDVI is the Normalized Difference Vegetation Index calculated as NDVI = .......... (Eq.2) NIR-R NIR+R Where NIR and R represent the Near Infrared and Red bands. Following the estimation of above-ground biomass, above- ground carbon was estimated using Equation 3 (Eggleston et al. 2006). Carbon Content (t C ha-1) = 0.5 × AGB (t) .......... (Eq.3) Where t C ha-1 is tons of carbon per hectare, AGB is aboveground biomass. Carbon stock is traded as CO2 units (Höhne et al. 2003); therefore, the CO2 equivalent (t CO2 ha-1) was estimated by multiplying the carbon stock (t C ha-1) by the molar conversion factor of 3.67 (Olschewski and Benitez 2005) as shown in Equation 4. CO2(t CO2eq ha-1) = Carbon content (t C ha-1) * 3.67 .......... (Eq.4) Other ecological benefits due to the implementation of NbS were assessed using literature reviews, key informant interviews, and FGDs. 2.3.9. Assessment of the economic viability of the nature-based solutions The evaluation of the economic viability of NbS requires quantifying the output and input variables. We used market analysis (observation), and secondary data (government reports) to gather data and quantify input and output variables for each identified NbS. The monetary value of the physical quantities of input and output variables was estimated using local market prices. To quantify the maintenance cost of different fixed infrastructures needed to implement the NbS, such as fences for ecological restoration and different soil and water conservation structures, 10% of the investment cost was used. We used two criteria to determine the expected economic viability of the identified NbS. These were the cost–benefit ratio (CBR) and net present value (NPV) (Australia 2006). The CBR evaluates an investment’s net return per dollar of expense and was computed using Equation 5 (Australia 2006). The NPV of a project, defined as the present value of expected future returns minus the present value of expected future costs, with costs and revenues discounted at the appropriate social discount rate, was computed using Equation 6 (Australia 2006). We used the discount rate of 12% in this study, a rate usually used by the Development Bank of Ethiopia for long-term loans for agricultural investment (DBE 2017). In this context, the phrase “appropriate social discount rate” refers to a discount rate that considers factors such as inflation, opportunity cost, and the time value of money and is contextualized to the study area as well as used by the Development Bank of Ethiopia. 16 | Nature-based Solutions for Human and Environmental Resilience | September 2024 CBR = .......... (Eq.5) ∑T t=0 Bt (1+d )t ∑T t=0 Ct (1+d )t NPV = = .......... (Eq.6) St (1+d )t∑ T t=0 ∑ T t=0 Bt - Ct (1+d )t Where Bt is benefits (cash-flows) in year t, Ct is costs (cash- flows) in year t, St is the net-benefit of a given restoration option at time t, t is the year in which the cash flow occurs, d is the discount rate, and T is the period (the last year of the intervention or rotation age). Values of CBR > 1 indicate the economic viability of an option; the higher the CBR, the greater the benefit in proportion to the costs. However, the CBR is insensitive to the magnitude of net benefits and, therefore, may favor projects with smaller benefits and costs over those with higher net benefits. As a result, it is mostly used to show the value of a single project rather than for comparison between projects (Anandajayasekeram et al. 2004). In contrast, the NPV is a better criterion for selecting from different alternatives (Anandajayasekeram et al. 2004). Values of NPV > 0 suggest the economic viability of an option. If there are multiple investments (interventions), the project alternative that can generate greater NPV is the most desirable. In this study, therefore, the identified NbS were ranked based on their NPVs. 2.3.10. Assessment of success and failure factors Data on the success and failure factors of implementing the identified NbS were collected using literature reviews (mainly national and regional government policies and strategies), inception workshop, and reconnaissance surveys. The collection of data on success and failure factors was focused on four areas: motivation of key actors, enabling conditions, capacity of actors, and resources. The motivation of key actors was assessed using indicators, such as the benefits of NbS, awareness, and legal requirements. The existence of enabling conditions was assessed using indicators, such as market access for purchasing inputs and selling products, focusing on existing policies and strategies, as well as the availability of incentives to implement NbS. The capacity of actors and resources required to implement the identified NbS were assessed using indicators such as capability in leadership, technical knowledge, finance and incentives, and feedback mechanisms for learning and adaptive management. 2.3.11. Analysis of dependency ratio Data on the demography of the study districts aggregated by age — used for the analyses of dependency ratio — was obtained from the latest available population and housing census data of Ethiopia (CSA 2007). The active labor force in the study districts was analyzed using a dependency ratio (Clark and Spengler 1980; Bartram and Roe 2005), a ratio which shows the burden of economically inactive people over economically active people using three criteria: youth dependency ratio, old-age dependency ratio and total dependency ratio. The total dependency ratio (DRt) combines the two dependency ratios (Equation 7, Clark and Spengler 1980). The youth (Equation 8) and old-age (Equation 9) dependency ratio considers the burden on economically active people due to people younger than 15 years as well as retired people, respectively (Clark and Spengler 1980). DRt = ( )× 100 .......... (Eq.7) People < 15 + People ≥ 65 years People between 15 and 64 DRy = ( )× 100 .......... (Eq.8) People < 15 years People between 15 and 64 DR0 = ( )× 100 .......... (Eq.9) People ≥ 65 years People between 15 and 64 Where: DRt is total dependency ratio; DRy is youth dependency ratio and DR0 is old age dependency ratio. 2.3.12. Qualitative data analyses The qualitative data gathered through key informant interviews, an inception workshop and reconnaissance surveys were analyzed using deductive, coding approach by using the questions as a guide for the analysis. Prior to conducting the qualitative data analyses, all data gathered through the different qualitative data collection methods described above were organized to produce a single dataset for analyses. Then, the data is processed through manual topic coding and building categories, which involves repeated readings of transcribed data. After repeated readings, themes such as societal challenges, cause of livelihood vulnerability, consequences, efforts to address vulnerability, drivers of natural resources degradation, and pressures of environmental degradation were identified and then key words and phrases representing each theme were manually categorized or summarized. Finally, each response was tagged with all the themes and subthemes presented in the dataset and analyzed. September 2024 | Nature-based Solutions for Human and Environmental Resilience | 17 3. Results and Discussion 3.1. Biophysical Characteristics The long-term (42 years) mean annual rainfall for Bokolmayo district varied between 229 and 382 mm, while it ranged from 215 to 306 mm in Dolo Ado. In the entire study area, the mean annual rainfall range was 215–382 mm (Figure 7a). The spatial distribution of the mean annual rainfall revealed that the highest rainfall occurs in the northwest and central part of the study area and declines toward the northeast and southeast (Figure 7a). The altitude ranges from 167 to 974 meters above sea level (Figure 7b). Most of the study area (87%) exhibited very gentle to gentle slopes, whereas 13% of the study area showed moderately steep to very steep slopes (> 15%). Most of the steep slopes were in the southwestern and central part of the study area (Figure 7c). According to the traditional agroecological classification of Ethiopia using rainfall and altitude (MoA 2016), the study area falls under two agroecological zones: Dry Berha (areas receiving less than 900 mm annual rainfall and found below 500 m above sea level) and Dry Kolla (less than 900 mm annual rainfall and found between 500 and 1500 m above sea level) (Figure 7d). Most (62%) of the Bokolmayo district classified as Dry Kolla agroecological zone, while 94% of the Dolo Ado district is categorized as Dry Berha agroecological zone. Overall, over 60% of the study area is classified as Dry Berha. Based on the FAO soil classification system (FAO 2023), four and five major soil types were identified in Bokolmayo and Dolo Ado respectively (Figure 7e). More than 80% of the Bokolmayo district is covered by two major soil types, Leptosols (51%) and Gypsisols (33%). On the other hand, 80% of the soil in the Dolo Ado district is characterized as Gypsisols. Soils along the rivers with irrigation investment are saline (Figure 7e), suggesting the need to reclaim the soils and reduce the accumulation of salts in the topsoil through improved agricultural water management. Figure 7. Biophysical characteristics of the study districts: (a) Mean annual rainfall, (b) altitude, (c) slope, (d) agroecological zones, and (e) major soil types. Source: Authors’ creation. 18 | Nature-based Solutions for Human and Environmental Resilience | September 2024 3.2. Socio-economic Characteristics The average total dependency ratio in the study districts was about 113%, suggesting that on average, around 113 persons are economically dependent on 100 economically active persons. Of the 113 economically dependent individuals, 109 represent the youth dependency ratio, while about 4 represent aged dependency ratio. This suggests that the majority (96.5%) of economically inactive persons are individuals with age less than 15 years. Most host communities live from subsistence farming and their own livestock; they are heavily dependent on natural resources. In addition, for most refugees and host community members, the economy is based mainly on two inter-related elements: humanitarian aid and the cross- border economy. As most of the people are pastoralists and agropastoral, livestock plays a central role in their livelihood activity. Shoat (sheep and goat) is the dominant reared type of livestock by the pastoralist and agropastoral communities (Figure 8). For most households, however, camel ownership is also a livelihood activity, as well as a symbol of status (Betts et. al. 2019). Betts et al. (2019) indicated that around 55% of refugee households have livestock. Furthermore, local communities cultivate crops, such as maize, sorghum, watermelon, maize, and sesame using irrigated and rainfed agriculture. In recent years, irrigated agriculture along the Genale and Dawa rivers is expanding, and communities are growing fruits such as mango, lemon, papaya, banana, and onion (Figure 9). In addition to the household chores, rural women in the study districts take part in agricultural activities, as per Gurmu (2018). Specifically, they largely participate in the production of small ruminants. In the study districts, the role of women in crop production appeared to be minimal due to the cultural outlook that posits women to be weaker than men (Gurmu 2018). Li ve st o ck h ea d c o un t (N o .) 200,000 0 400,000 600,000 800,000 Type of Livestock in the study districts Camel Cattle Donkey Poultry Shoat Camel Cattle Donkey Poultry Shoat Bokolmayo Dolo Ado 58,980 28,769 11,432 9,528 613,498 153,417 111,367 13,080 11,777 669,403 Figure 8. Livestock type and head count in the study area. Source: Authors’ creation. September 2024 | Nature-based Solutions for Human and Environmental Resilience | 19 Figure 9. Fruits growing along the Genale River, Papaya and Mango (top) and Banana (below). 3.3. Land-use and Land-cover Changes The overall classification accuracy and kappa analysis were greater than 85 and 84%, respectively, suggesting that the classified maps (Figure 10) can be used for further analyses. In both districts, eight major LULC classes were identified — waterbodies, grasslands, forestlands, farmlands, bare land, settlement/built-up areas, shrublands and wetlands (Table 3). Grasslands and shrublands are the dominant LULC classes in the base year (2010) and in the year 2024 (Table 3). Forestlands are mainly found in the central and northern part of the study area, mainly situated in the Bokolmayo district (Figure 10). Bare land dominates in the south and southeastern parts of the Dolo Ado district (Figure 10). Ph o to g ra p hy b y W o ld e M ek u ri a 20 | Nature-based Solutions for Human and Environmental Resilience | September 2024 Table 3. Land-use and land-cover classes of the study area. Values are area in hectare. LULC class 2010 2024 Area (ha) Total area Area (ha) Total Dolo Ado Bokolmayo ha % Dolo Ado Bokolmayo ha % Waterbodies 418.5 507.4 925.8 0.1 585.6 649.5 1,235.1 0.2 Farmlands 4,985.6 2,899.8 7,885.3 1.0 9,003.0 9,099.3 18,102.3 2.2 Forestlands 5,679.6 1,13,875.2 1,19,554.8 14.7 3,436.2 75,189.6 78,625.8 9.7 Grasslands 1,98,217.2 71,731.9 2,69,949.1 33.2 1,91,426.2 53,765.1 2,45,191.3 30.1 Shrublands 52,116.5 2,37,665.8 2,89,782.2 35.6 75,420.5 2,88,905.0 3,64,325.5 44.8 Bare land 82,942.6 41,233.1 1,24,175.7 15.3 64,175.7 40,004.8 1,04,180.5 12.8 Settlement area 491.2 542.8 1,033.9 0.1 850.2 782.6 1,632.8 0.2 Wetlands 54.7 17.0 71.7 0.01 8.3 76.9 85.2 0.01 Total 3,44,905.7 4,68,472.9 8,13,378.6 100.0 3,44,905.7 4,68,472.8 8,13,378.5 100.00 During the last 14 years (2010–2024), forestlands, grasslands, and bare lands saw a decrease, whereas farmlands, shrublands, and settlement areas increased (Table 3). The expansion of farmlands occurred mainly at the expense of grasslands and shrublands in Dolo Ado and Bokolmayo districts, respectively (Annex). For example, 2,609 ha of grasslands in the Dolo Ado, and 3,576 ha of shrublands in the Bokolmayo district were converted to farmlands over a period of 14 years (Annex). This could partly be attributed to the expansion of irrigated agriculture established in the study area through the support from humanitarian organizations. Most (84%) of the farmlands are rainfed agriculture, while the remaining 16% (2,831.6 ha) are irrigated. Water bodies District boundary LULC Class Rainfed farmlands Irrigated farmlands Forestlands Grasslands Shrublands Bare land Settlement area Wetlands Figure 10. Land-use and land-cover classes of the study areas for the years 2010 and 2024. Source: Authors’ creation. September 2024 | Nature-based Solutions for Human and Environmental Resilience | 21 3.4. Land Degradation Status The analysis of land degradation status using the LP sub- indicator for a period of 14 years (2010–2024) indicated that most (90%) of the study area showed stable LP, 8.6% showed “early sign of decline”, 0.7% “decline” and 0.02% displayed “stressed” conditions (Figure 11a). The results also indicated that the status of land degradation varied with LULC classes. For example, out of the total “stressed” area, 56% and 33% were found in grasslands and bare land, respectively. Similarly, the grasslands contributed the largest share of the “early signs of decline” (67%) and “decline” (47.5%) categories, suggesting that grazing land management should be given priority to address land degradation and to sustain the productivity of livestock because it is the main livelihood mechanism in the study districts. Figure 11. Land degradation status for a period of 14 years (2010–2024): (a) using LP sub-indicator, (b) LC, (c) SOC, and (d) land degradation status using the three indicators in combination. Source: Authors’ creation. The analysis using LC sub-indicator (Figure 11b) suggested that most (66%) of the study area was stable, while 14% showed improvement, and 21% exhibited degraded status. The analysis using SOC sub-indicator (Figure 11c) indicated similar results: 85% displayed stable condition, 6% showed improvement, and 8% exhibited degraded status. The analysis of land degradation status using the combination of the three indicators indicated 28% of the study area to be under degraded status, 59% unchanged, and 13% as showing improvement over a period of 14 years (Figure 11d). Local communities’ perspective on societal challenges including land degradation is discussed in the next section (Section 3.5). 3.5. Societal Challenges Societal challenges from the perspective of participants of inception workshop: The analysis of data gathered through the inception workshop suggested that a considerable proportion (44%) of societal challenges can be categorized as social challenges, whereas the environmental, economic, and social/economic challenges constituted 18.5% each (Table 4). Compared with groups representing government offices and private sector, groups representing humanitarian organizations and NGOs provided exhaustive lists of societal challenges. According to this group, the most important environmental challenges included drought and flood. Water and food insecurity, lack of access to land to establish settlement areas for refugees, lack of basic services, and gender imbalance in accessing land and basic services were mentioned as the social challenges of most significance. This group also noted inflation to be the most important economic challenge (Table 4). 22 | Nature-based Solutions for Human and Environmental Resilience | September 2024 Table 4. Societal challenges of refugees, IDPs, and host communities from the perspective of the participants of the inception workshop. Challenges Categories Identified Remark Group 1 Group 2 Group 3 Floods Environmental ✓ ✓ ✓ This could be from the overflow of rivers and runoff. Drought Environmental ✓ ✓ ✓ Land degradation Environmental ✓ Soil fertility decline Environmental ✓ Mainly caused by water and wind erosion. Deforestation Environmental ✓ Water scarcity/insecurity Social ✓ Human and animal diseases Social/economic ✓ Crop pests and diseases Economic ✓ Lack of access to land for refugees and IDPs Social ✓ Inequality in land resources Social ✓ High poverty rate Social/economic ✓ Food insecurity Social ✓ ✓ Poor agricultural practices Social ✓ Low agricultural productivity Economic ✓ Lack of market access Economic/social ✓ Lack of access to financial services Economic ✓ Inflation Economic ✓ High cost of living Economic ✓ Lack of livelihood opportunities Social/economic ✓ Youth and women unemployment Social ✓ Lack of basic services Social ✓ ✓ Refers to education, health, water supply and other services. Lack of road access Social/economic ✓ Declining interactions among the different groups Social ✓ This refers to inter- and intra- dynamics in the interactions between refugees and host communities, refugees and IDPs and IDPs and host communities. Conflict of interest between informal and formal institutions Social ✓ Gender imbalance in accessing education, resources, and workload Social ✓ Continued > September 2024 | Nature-based Solutions for Human and Environmental Resilience | 23 Challenges Categories Identified Remark Group 1 Group 2 Group 3 Conflict in resource use Social ✓ ✓ The conflicts are mainly associated with use of water resources and grazing lands. Lack of capacity to cope with disasters Social ✓ Note: Group 1 represents UN organizations and NGOs, group 2 represents government sector offices, and group 3 represents private sector and cooperatives. Societal challenges from the perspective of local communities: Data gathered through reconnaissance surveys and discussion with irrigation cooperatives indicated that the most common societal challenges from the perspective of local communities included (i) lack of knowledge and experience in cropping patterns and irrigation water use and management, (ii) floods due to overflow of rivers and runoff, (iii) recurrent drought, (iv) lack of market access, and (v) poor road access. Particularly, the floods that occurred in 2023 caused considerable damage to the irrigated farms, and farmers lost their production (Figure 12). As a result, farmers are currently practicing free grazing and feeding their livestock on irrigated agriculture (Figure 13). This helped to reduce grass and weeds and to prepare the land for the next planting season. Water abstraction from the Genale river using diesel pump,Somali region, Ethiopia. Photography by Wolde Mekuria 24 | Nature-based Solutions for Human and Environmental Resilience | September 2024 Figure 12. Irrigated farms affected by floods in Melika-Dida, Bokolmayo, Somali, Ethiopia. Figure 13. Free grazing in irrigated farms in Dolo Ado, Somali, Ethiopia. Ph o to g ra p hy b y W o ld e M ek u ri a Ph o to g ra p hy b y W o ld e M ek u ri a September 2024 | Nature-based Solutions for Human and Environmental Resilience | 25 The spatial analysis of floods: The spatial analysis shows the areas where irrigated farmers are more likely to be affected by floods (Figure 14). The flood maps from remote sensing images indicated that 3.1% and 1.1% of the Dolo Ado and Bokolmayo districts were affected by floods in 2023, which in turn impacted the displaced people living in those areas, as well as the host communities. Most of the flood was generated by the Genale River, although excess rainfall (pluvial floods) affected relatively densely populated areas, as well. Figure 14. Flood map of the study area between 2017 and 2023. Source: Authors’ creation. Potential solutions to address the challenges: The local communities and participants of the inception workshop suggested multiple options to address the challenges. For example, groups representing government offices suggested that challenges associated with floods can be managed through constructing dams and restoring ecosystems. To focus on drought, the group suggested solutions such as rotational grazing, establishing exclosures, temporary migration, and diverting and harvesting water during rainy seasons. Some of the social challenges can be addressed by expanding schools and providing training to teachers. This group suggested that conflicts over the use of resources can be addressed through awareness campaigns promoting the importance of peace and stability. Similarly, the communities are not simply passive observers of the challenges they face. The responses by communities to such problems are both diverse and specific to their own situations. These are listed in Box 1. Sometimes they can be fully successful in their responses aimed at addressing their challenges, while other times, their responses may fail to overcome the challenges. In both cases, it is crucial to work closely with local communities when planning, designing and implementing options to meet societal challenges. Box 1. Efforts made by communities to address the challenges. { Learn from their own failure. { Using extension services. { Gain knowledge from on-job trainings offered by WFP. { Store nonperishable crops for some time and sell when the market price increases. { Transport products to nearby markets. { Use local knowledge and practice (particularly religious practice), i.e., they take water, pray by putting the holy Kuran on the water, and distribute this water to the farm. { Use traditional storage facilities. { Staying near water sources (rivers). { Changing production patterns, i.e., during drought, they mainly focus on producing livestock feeds to save their main asset, livestock. 3.6. Potential Nature-based Solutions to Address the Challenges 3.6.1. Experience in using nature-based solutions In the study districts, the use of NbS to address societal challenges, such as drought, floods, land degradation, and water insecurity is not completely new. For example, NbS, like water harvesting, was mentioned by all participants of the inception workshop, whereas other types of NbS, such as solar-based irrigation and the use of solar pumps to access water, were mentioned by groups representing humanitarian organizations and the private sector. Multiple stakeholders — government organizations, NGOs, humanitarian organizations, the private sector, and communities — are involved in the implementation of NbS to address societal challenges. Government sector offices are mainly involved in implementing interventions, community mobilization, and availing of conducive frameworks and policies. Humanitarian organizations, NGOs, and the private sector provide financial and technical support. Local communities largely contribute unpaid labor and offer locally available materials. Overall, the participants indicated that the implemented activities have been 26 | Nature-based Solutions for Human and Environmental Resilience | September 2024 effective in terms of mitigating drought in the short term and adapting to weather extremes. Local communities have limited experience in restoring landscapes. As part of restoring degraded landscapes, exclosures have been established in a few locations with the support of a local NGO, Save the Environment of Ethiopia. Coping with climate hazards and environmental pressures through implementing NbS is, however, an integral part of agropastoral life, especially in settings that experience a lot of climate variability in the study areas (Seddon et al. 2020; Chee et al. 2021). Some of the tree-based NbS implemented in the study area include: { Exclosure: There are four types of ‘seero’ (exclosure) in the study area — private, government, communal and/or NGO‐ supported, and cooperative. There are two types of private exclosures — “sera” within an existing farm, and “beer” outside the farm (Napier and Desta 2011). { Agroforestry: Live fencing, boundary planting and scattered trees on farmlands. { Reforestation and plantations: Banana plantation. Furthermore, other adaptation strategies already practiced in study areas include trenches and roof water harvesting. 3.6.2. Identified potential nature-based solutions Based on the inclusion and exclusion criteria (see Table 2, Section 2.3.7), based on a literature review and including the IUCN Global Standards, we identified diverse NbS that can address the societal challenges in the study location (Table 5 and Figure 15). Ecological restoration efforts, including exclosures and rangeland management were found to be most suitable; they can be implemented in 44.8% of the total land area of the districts. Water harvesting techniques like eyebrow terraces, Meskat, and Negarim were also found to be most suitable. For example, based on the biophysical and socio-economic characteristics of the study districts, eyebrow terraces or Meskat can be implemented in 15.5% of the total area. Similarly, Meskat or Negarim can be implemented in 22.2% of the total land area. Agroforestry practices like boundary planting or shelterbelts can be implemented in 1.4% of the total area, while riparian buffers and plantations (e.g., date palm tree and banana plantations) can be implemented in 0.3% and 0.6% of the total land area, respectively. Table 5. Potential area for implementing the identified nature-based solutions. Nature-based solution Area (ha) % of total area Bokolmayo Dolo Ado Total Water harvesting Eyebrow terrace 52,297.4 6,620.4 58,917.8 7.2 Eyebrow terrace/Meskat 1,15,984.5 10,048.1 1,26,032.6 15.5 Eyebrow terrace/Meskat/Negarim 83,105.6 5,609 88,714.6 10.9 Eyebrow terrace/Negarim 24,627.7 1,530.5 26,158.2 3.2 Level bund/Fanya-juu 1,621.3 15.2 1,636.5 0.2 Meskat 38,060.7 86,336 1,24,396.7 15.3 Meskat/Negarim 34,663.6 1,45,639.7 1,80,303.3 22.2 Negarim 11,469.8 64,125 75,594.8 9.3 Rooftop water harvesting 731.1 848.1 1,579.2 0.2 Semicircular catchments/Meskat/ Negarim 6,863.8 100.8 6,964.6 0.9 Semicircular catchments/Negarim 1,929.8 25.6 1,955.4 0.2 Tied ridges 1,600.2 213.4 1,813.6 0.2 Tied ridges/Level bunds and Fanya- juu 1,851.5 32.5 1,884 0.2 Tied ridges/Level bunds and Fanya- juu/SC 855.7 12.5 868.2 0.1 Tied ridges/Pits, Zay/Level bunds and fanya-juu/SC 24.3 0 24.3 0.0 Continued > September 2024 | Nature-based Solutions for Human and Environmental Resilience | 27 Nature-based solution Area (ha) % of total area Bokolmayo Dolo Ado Total Agroforestry practice Boundary planting/Shelterbelts/ Scattered trees 9,084.3 2,240.5 11,324.8 1.4 Riparian buffer/plantation Date palm tree plantation 1,077.6 1,690.7 2,768.3 0.3 Banana plantation 425 2,406.6 2,831.6 0.3 Ecological restoration Exclosure 39,961.7 64,145.5 1,04,107.2 12.8 Rangeland management 53,737.3 1,91,414.4 2,45,151.7 30.1 Exclosure/Rangeland management 2,88,811.1 75,319.7 3,64,130.8 44.8 Participatory forest management 75,164.7 3,414.8 78,579.5 9.7 Source: Authors. Figure 15. The spatial distribution of suitable areas to implement identified NbS: (a) water harvesting, (b) agroforestry, (c) riparian plantation, and (d) ecological restoration practices. ET refers to Eyebrow terrace, LB-Level bund, FJ-Fanya-juu, PFM - Participatory Forest management, RM-Rangeland management, RWH- Rooftop water harvesting, SC-Semicircular catchment, TR-Tied ridges, and ZP-Zay pits. Source: Authors’ creation. 28 | Nature-based Solutions for Human and Environmental Resilience | September 2024 3.7. Ecological and Socioeconomic Benefits of Identified Nature-based Solutions NbS have the potential to provide various types of ecological and socio-economic benefits to communities (Table 6). For example, NbS categorized as water harvesting practices can help mitigate storm water runoff, reduce soil erosion, increase water availability in dry seasons, increase agricultural productivity, and ensure water and food security. Similarly, NbS classified as agroforestry practices support to conserve soil, improve biodiversity, and diversify livelihoods (Table 6). NbS classified as ecological restoration practices are key to restoring degraded landscapes, sequester aboveground carbon, improve biodiversity, and mitigate climate change (Table 6). NbS aimed at buffer zone management are also crucial for flood control, diversifying livelihoods and improving livestock productivity (Table 6). Table 6. Ecological and socio-economic benefits of identified nature-based solutions. Categories of NbS Benefits Ecological Socio-economic Water harvesting practices { Conserve water and enable efficient use of available rainwater. { Reduce storm runoff and risks of flooding. { Reduce soil erosion. { Increase water availability in dry seasons. { Increase groundwater recharge. { Enhance household water and food security. { Enhance local communities’ resilience to weather extremes. { Support to increase and diversify agricultural production. { Enables livelihood diversification. Ecological restoration { Restore degraded indigenous trees. { Improve AGB and carbon. { Adapt and mitigate climate change. { Increase productivity of rangelands. { Improve biodiversity. { Improve micro-climatic conditions. { Conserves soil and water. { Reduce desertification. { Increase availability of fuelwood. { Support to diversify livelihood. { Improve agricultural productivity. { Improve livestock productivity. { Increase availability of livestock feed. { Support to ensure water and food security. Agroforestry { Conserves soil. { Enhance soil fertility. { Improve biodiversity. { Improve microclimate. { Protect wind and water erosion. { Reduce desertification. { Provide wood (e.g., timber, construction material) and non-wood products (e.g., fuelwood, fodder, etc.). { Support livelihood diversification. Riparian buffers/ plantations { Modifies microclimate. { Support to control floods due to overflow of rivers. { Reduce desertification. { Support to diversify livelihood. { Improve food and nutrition security. { Improve availability of livestock feed. { Support to diversify livelihood. { Increase income. Source: Authors’ creation. The estimation of AGB using NDVI values (Figure 16) suggested spatial differences across the study districts. The variation in AGB between Bokolmayo and Dolo Ado districts can primarily be attributed to the distribution of forest cover within these districts. Bokolmayo district, which exhibits high amounts of AGB (Figure 16), likely benefits from high forest cover (see Table 3, Section 3.3), which is a significant reservoir of biomass due to the accumulation of plant material. In contrast, Dolo Ado district, characterized by its lower AGB, suggests a sparser forest cover or a landscape dominated by less dense vegetation types, which inherently store less biomass. Our results (Table 7) indicated that forestlands displayed the highest NDVI (0.634) and accumulated 85.0 t ha-1 of AGB. This translates to carbon accumulation of 42.5 t C ha-1, and CO2 equivalent of 155.985 tCO2 eq ha-1. This suggests that ecological restoration practices have a substantial role in adapting to and mitigating climate change. Shrublands September 2024 | Nature-based Solutions for Human and Environmental Resilience | 29 and grasslands also indicated notable biomass and carbon sequestration capacities. In contrast, waterbodies and bare land exhibited the lowest NDVI values, reflecting minimal carbon sequestration potential (Table 7). The results imply that the implementation of the identified NbS, such as exclosures, can increase the climate mitigation potential of ecosystems. Assuming that establishing exclosures in degraded landscapes can convert degraded areas to well-established shrublands within a period of 30 years, exclosures could potentially improve the ecological value of the land and can lead to an increase in AGB from a mere 7.58 t ha-1 to 61.1 t ha-1 and enhance carbon sequestration from 13.9 tCO2 eq ha-1 to 112.0 tCO2 eq ha-1 (Table 7). Such improvements underscore the potential of these interventions to restore ecological functions, mitigate climate change, and improve biodiversity, making them critical strategies for sustainable land management and environmental rehabilitation. In addition, these expected changes due to the implementation of NbS could contribute to reducing flood incidents, improving resource availability and food security, building livelihood assets, and diversifying livelihoods. Figure 16. The spatial distribution of (a) NDVI values and (b) AGB. Source: Authors’ creation. Table 7. Above-ground biomass and carbon stock estimates across different LULC types using satellite data. LULC NDVI AGB (t ha-1) Carbon content (t C ha-1) Carbon sequestration (tCO2 eq ha-1) Waterbodies -0.20 2.88 1.44 5.29 Farmlands 0.39 32.33 16.16 59.32 Forestlands 0.63 85.01 42.50 155.99 Grasslands 0.49 48.40 24.20 88.82 Shrublands 0.55 61.06 30.53 112.04 Bare land 0.03 7.58 3.79 13.90 Settlement area 0.04 7.75 3.87 14.22 Wetlands 0.06 8.20 4.10 15.05 Source: Authors’ creation. 30 | Nature-based Solutions for Human and Environmental Resilience | September 2024 3.8. Economic Viability of the Identified Nature-based Solutions 4 To monetize the environmental benefits of the exclosure, a market price of €22 (USD $3.18 per ton of CO2 eq., (which is used in carbon trading at one of REDD+ site in Ethiopia- the Humbo restoration site), is used. Moreover, the carbon stock accumulated in exclosure over 30 years using NDVI is distributed for 20 years by taking the mean carbon stock estimated. 3.8.1. Input and output variables The major input variables required for the implementation of the identified NbS include labor and agricultural inputs, such as fertilizers and planting materials. NbS such as exclosures also necessitate payment for guards as an input for implementing the intervention. The major outputs of the identified NbS include fruits, livestock feed (grass and banana stem) and fuelwood. Outputs such as livestock feed and fuelwood are mainly related to NbS categorized as ecological restoration practices. The results also suggested that assisted management of ecological restoration practices could increase grass production and fuelwood by 22% and 60%, respectively. Some of the NbS, such as water harvesting structures, provide direct benefits, such as increased agricultural production and livestock feed through increasing water availability and access. Studies (e.g., Deribe et al. 2009) indicated that water harvesting structures, such as eyebrow terraces and semi-circular catchments could increase the production of fuelwood by 41% and 77%, respectively. Furthermore, water harvesting structures — fanya-juu, tied ridges, level bund, and ponds — could increase maize and onion production by up to 26% and 41%, respectively (Naba et al. 2020; Jacobsen 2002). 3.8.2. Economic viability of nature-based solutions The results of the economic analyses indicated that the expected discounted total benefit and costs per hectare associated with the identified NbS, excluding the expected environmental benefits and costs, ranged from about USD $715 to $95,187 and USD $153 to $7,215, respectively. The BCR ranged from 1.05 to 49 (Table 8). The results suggest that all assessed NbS appeared to be economically viable (Table 8). River buffer zone management through planting high value crops, such as banana and in-situ water harvesting structures appear to be the most attractive interventions (Table 8), generating a net discounted value of about USD $87,972 and $7,335 per hectare, respectively. Conversely, exclosures (BCR of 1.21); agroforestry (BCR of 1.16), micro and macro water structures (effect measured on the productivity of fodder, shrubs and grass) (BCR of 1.10), and date palm plantation (BCR of 1.05) are the NbS generating the minimum NPV per hectare. Notably, ecological restoration measures (e.g., exclosures), and micro- and macro-water catchment structures could generate intangible goods and services, such as the preservation of ecosystem services, biodiversity, soil health, and carbon sequestration. For instance, if the environmental benefits of the exclosure is considered using the sequestrated CO2 (112.04 tCO2 eq ha-1), it would have an additional environmental discounted benefit of about 646.63 USD ha-1 over a period of 20 years4, provided the presence of an enabling environment to implement carbon financing. In addition, if other unmarketable environmental benefits — contributing to improve microclimate, biodiversity, soil fertility, and erosion — are considered, the benefits of NbS classified as ecological restoration measures could further outweigh the costs. Ph o to g ra p hy b y W o ld e M ek u ri a September 2024 | Nature-based Solutions for Human and Environmental Resilience | 31 Table 8. Discounted costs and benefits of the identified nature-based solutions (USD, 1 ha model). Indicators Nature-based solutions Riparian buffers/ plantations Exclosures Agroforestry Water harvesting structures Banana Date palm tree Micro and Macro catchments In-situ water harvesting Surface water storage (Ponds) Total Benefit 2,54,851.84 9,900.05 4,852.54 3,828.29 1,974.88 20,049.99 5,111.49 Total Cost 15,859.85 5,993.72 2,313.70 3,208.12 910.00 296.13 1,599.94 Net-value 2,38,992.00 3,906.33 2,538.84 620.17 1,064.88 19,753.86 3,511.55 Discounted total Benefit 95,187.01 2,578.79 1,485.01 1,364.61 715.27 7,488.11 1,909.00 Discounted total cost 7,215.04 2,454.55 1,230.85 1,172.06 652.28 153.47 770.88 NPV 87,971.97 124.24 254.16 192.55 62.99 7,334.64 1,138.12 Benefit-Cost Ratio 13.19 1.05 1.21 1.16 1.10 48.79 2.48 Source: Authors’ creation. 3.9. Key Success and Failure Factors The diverse ecological and socio-economic benefits of the identified NbS (Table 6) could motivate local communities and other stakeholders to implement the options. In line with this, studies (IUCN and WRI 2014) demonstrated that the key motivating factors which influence the participation of actors in natural resources management include benefits, awareness, and legal issues. Specific to the study area, restored bushes and grasslands could increase the availability of and access to livestock feed, enhance livestock productivity and improve access to fuelwood. Such benefits support the livelihood of pastoral and agropastoral communities, motivating them to participate in the implementation of NbS. In addition, several enabling conditions can address societal challenges through the implementation of NbS (Figure 17). The enabling conditions can be categorized as favorable policies and frameworks, availability of natural resources, active stakeholders involved in humanitarian and resilience building activities, significant government interest, access to local markets for selling the product of fruit production, and possibilities to establish early warning systems in refugees, IDPs, and host communities. Enabling conditions for NBS Local ecological knowledge Experience in natural resource management Ability to incorporate within carbon markets Access to local markets Natural resources such as water and sunshine Stakeholders involving in development actions Policies and frameworks Government support Figure 17. Enabling or favorable conditions to implement NbS to address societal challenges. Source: Authors’ creation. 32 | Nature-based Solutions for Human and Environmental Resilience | September 2024 In the study area, however, the strong focus of humanitarian and non-governmental organizations on disaster response rather than disaster prevention could constrain the wider implementation of NbS. The harsh climatic conditions and limited water availability could also be hampering factors. Furthermore, the lack of experience of most stakeholders, including refugees, IDPs, and host communities, in the planning, designing, and implementation of NbS may further curb the adoption, wider implementation, and sustainability of the options. Studies conducted in Ethiopia (e.g., Marie et al. 2020) and elsewhere in the world (e.g., Nelson et al. 2020; Seddon et al. 2020; United Nations Environment Programme 2022) also demonstrated that there are diverse socio-economic and governance related constraints for adoption or wider implementation of NbS. For example, Marie et al. (2020) indicated that household characteristics such as age, gender, family size, farm income, and farm size significantly influence the adoption of NbS. This study further elaborated that access to climate information and market access impact adoption. A review by Nelson et al. (2020) identified five categories of NbS adoption challenges: participation and equity, governance, valuation, infrastructure integration, and scale and feedback. This same study also argues that NbS do not entail quick solutions, affecting the adoption of interventions. Seddon et al. (2020) identified three barriers hindering the evidence- based integration of NbS into international, national, and local climate and development policy and practice. According to Seddon et al. (2020), first, challenges in measuring or predicting the effectiveness of NbS lead to high uncertainty about their cost-effectiveness compared with the alternatives. Second, poor financial models and flawed approaches to economic appraisal led to under-investment in NbS. Third, inflexible and highly sectoral forms of governance hinder the uptake of NbS; grey, engineered interventions are still the default approach for many climate adaptation and mitigation barriers. Limited awareness, understanding and agreement around NbS are still barriers to scaling up their use (United Nations Environment Programme 2022). In practice, scaling up of NbS has been restricted by siloed policies and programs, a lack of sufficient and long-term finance, inadequate technical capacity and a lack of confidence in their economic, social, and environmental integrity (United Nations Environment Programme 2022). Furthermore, it is argued that local actions, including local participation and knowledge, are an important element influencing the scaling up of NbS. Overcoming these challenges requires major systemic change in how we conduct and communicate interdisciplinary research, and how we organize and run our institutions. It also argued that the benefits of NbS will not be realized unless they are implemented within a systems-thinking framework that accounts for multiple ecosystem services and recognizes trade-offs among them from the perspectives of different stakeholders (United Nations Environment Programme 2022). 3.10. Sources of Financing The review of relevant literature (e.g., Meselu et al. 2022; Besacier et.al. 2021; Ozment et. al. 2021; Abebaw 2019; OECD 2010) indicated that there are multiple potential sources of financing for NbS (Table 9). These include private investment, co-investments, payment for ecosystem services, safety net programs, and agricultural credits (Table 9). Table 9. Potential financing mechanism for the identified nature-based solutions. Categories of NbS Financing mechanisms Description Riparian/buffer plantation Private investment Managing jointly with a community for commercial purposes. Co-investments (multilateral investment institutions) An investment between government and private investors. The government supplies land for free and the investor plants trees at their cost. Benefits are shared equally. Contract arrangements with private investors Providing technical, technological, and financial support to investors to plant preferred tree species using contract arrangements. Ecological restorations Revolving fund to diversify livelihood Providing revolving capital for farmers to use for livelihood activities. These include integrating livestock fattening within restored areas (exclosures). Payment for ecosystem services Providing capital (making payments) based on the level and intensity of rehabilitated tree species and reappeared wild animals for communities that implement NbS. Continued > September 2024 | Nature-based Solutions for Human and Environmental Resilience | 33 Categories of NbS Financing mechanisms Description Water harvesting Productive safety net program (rural) Engaging people in need in community works of this kind as a regular funding process to enable households to receive payments over multiple years. Agroforestry Private investment Managing privately and jointly with communities for commercial purposes. Agricultural credit Providing land for private investors to enhance the forest combined with apiculture or livestock fattening in adjacent forests on a large scale. Debt-Financing (Green-bond) Engaging investors to participate in natural resource management for the purpose of financing or refinancing projects that contribute positively to the environment and/or climate. Source: Authors’ creation. 4. Conclusions and Recommendations The findings of this study indicate that significant landscape alteration in the last 15 years ha