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1. Successful adaptation often involves changes to the decision context to enable new ways of thinking and acting on climate change. Using 16 adaptation initiatives the authors were engaged with, we analysed how and why decision contexts changed to identify ways to improve adaptation as a process of collective deliberation and social learning. 2. We used the scope of the adaptation issue and governance arrangements to classify initiatives into four types and scored changes in the decision context using three frameworks: (1) the values, rules and knowledge (VRK) perspective to identify changes to adaptation decision-making; (2) the five dimensions of futures consciousness to identify the building of adaptation capabilities and (3) the social learning cycle to reveal evidence of reflexive learning. 3. Initiatives using novel governance arrangements for discrete problems (‘problem governance’) or complex, systemic issues (‘systems governance’) scored highest for influences of VRK, futures consciousness and the social learning cycle on the decision context. Initiatives using existing management for discrete problems (‘problem management’) scored moderately for change in the decision context, while those using existing management for systemic issues (‘systems management’) scored low because change was often impeded by existing rules. 4. All three frameworks influenced decision contexts in systems governance initiatives. Problem governance initiatives revealed interactions of VRK and futures consciousness but limited influence of VRK on the social learning cycle. Scope and governance arrangements differ with the adaptation issue and initiatives adapt over time: some small-scale ones became more systemic, developed novel governance arrangements and changed the decision context. 5. Our findings do not show that some adaptation initiatives are better or more transformative than others; just that their scope and appropriate governance arrangements are different. This questions the notion that successful adaptation requires building generic transformative adaptation approaches and capabilities. There is a diversity of arrangements that work. What is important is to align the approach to the adaptation problem. We suggest two directions for improving adaptation initiatives: first, by influencing how they can shift between problem and systems focus and between standard management and novel governance, and secondly, by using methods to diagnose and direct change in the decision context.

According to the United Nations (n.d.), climate change is the long-term shift in temperatures and weather patterns due to natural changes, such as the sun’s activity and significant volcanic eruptions, or human activities, such as burning fossil fuels like coal, oil, and gas. The effects of and challenges caused by climate change on farmers’ ability to manage mixed farming systems in sub-Saharan Africa are well documented in the literature. However, the synergies among mixed farming systems’ components and farmers’ innovation demands and responses to climate change impacts remain fragmented. Using a case of mixed crop-livestock-tree (MCLT) systems in northern Ghana, this paper examined farmers’ responses, their innovation needs, and how these innovations can be catalyzed to enable more farmers to adopt similar climate change adaptations. Our findings show that climate change impacts mixed farming systems in several domains, with these impacts being more visible in some domains. Significant productivity declines are observed in crops, livestock, and the whole mixed farming system. Productivity declines lead to decreased incomes, food availability, and household food security. Female farmers’ access to production factors, resource management, and market participation is reduced. Farmers make technical, managerial, and business changes in response to climate change impacts. Such changes are dominated by technical changes, including using highyielding, disease-resistant, and early-maturing crop varieties, crop and animal pest and disease management, agricultural water and land management, and wind and bush fire control. Interconnections between the MCLT system components include cross-component investments, additional income generation, animal feeding and healthcare improvement, nutrition exchanges, and family nutrition improvement. These interconnections generate income and cash flow and support food and nutrition security, enabling farmers’ adaptation. Climate-resilient innovation bundles to enable farmers’ adaptation include good agricultural practices, circular farming techniques, irrigation packages, information services, and value-chain linkages. Scaling climate-resilient innovations in northern Ghana and other sub-Saharan African contexts require multiple pathways, including innovation platforms, innovation bundling, multi-actor partnerships, inclusive finance, and multistakeholder dialogues to support farmers’ adaptation to climate change.

Reservoirs play a significant role in the mobilization of water resources in Burkina Faso, contributing to the management and availability of water for various purposes. Operational management of reservoirs requires accurate and timely water level information, which remote sensing can provide cost-effectively and with limited resources. In this study, the surface area of 20 reservoirs is first determined using a Random Forest classifier and Sentinel-2 images acquired between 2015 and 2022. The accuracy of the classified surface water areas is evaluated by calculating 5 accuracy assessment metrics. The classifications were validated using manually digitized water areas from high-resolution Google Earth images and compared to the Dynamic World (DW) land cover dataset. Afterward, the spatial variation in the areal extent of the reservoirs is analyzed over time. A linear relationship is established between the estimated surface area and the corresponding observed water level of the reservoirs. The results indicate that reservoir surface areas were accurately classified with Sentinel-2 images (Kappa above 90.35%) for all dates. Moreover, validation with high-resolution images provided an R2 of 0.99 and a Normalized Root Mean Square Error (NRMSE) of 3.53%. Smaller reservoirs exhibit significant variations in surface areas over time as compared to larger ones, which are more stable. The relationship between surface area and water level is satisfactory (R2 ranging from 0.76 to 0.97) for 14 of the 20 analyzed reservoirs. The remaining six reservoirs are affected by aquatic plant intrusion which leads to an underestimation of the surface area. The high accuracy and operational feasibility of the proposed approach demonstrate that Sentinel-2 imagery and machine learning techniques can be recommended for reservoir mapping within the framework of water level monitoring in Burkina Faso.

Despite substantial contemporary research and a growing trend in exploring the water-energy-food (WEF) nexus, most research efforts have been invested in macro-level supply-side infrastructure and policies. However, prioritizing demand-side management policies can provide new opportunities and untapped potential for addressing interconnected resource challenges. Demand management inherently encompasses users’ consumption patterns, behaviors, socio-economic conditions, and choices, thereby necessitating active engagement and participation. Understanding household-level demands is fundamental to assess the demand for and consumption of water, energy, and food, as well as to inform policy decisions. In this context, our study investigated household consumption patterns within the interconnected WEF nexus, including daily practices such as cooking and washing, conservation measures, household governance, and their cross-cutting relationships with climate change. As a case study, we conducted our research in the Jabal Al Natheef neighborhood of Amman City, Jordan. Our findings reveal that households can propose and enact climate-friendly decisions. Significant gender-related differences were also observed in decisions made across WEF household practices. Additionally, households’ perspectives highlighted governance issues and revealed gaps in policy implementation along with the need for more inclusive decision-making processes. Our results underscore the importance of understanding household-level WEF nexus dynamics and daily practices in informing environmental policies, particularly those related to climate action. Such policies are best developed from the bottom-up by incorporating household insights, rather than relying solely on top-down, one-size-fits-all solutions.

Study Region: Three major irrigation oases in Uzbekistan (Bukhara, Samarkand and Kashkadarya) Study focus: The study employs remote sensing to develop enhanced methodologies for quantifying water use in Central Asian irrigation oases from 2017 to 2022. By integrating earth observation data into a water balance approach, we quantify variables that are typically challenging to measure, such as groundwater overdraft and non-growing season water use for soil preparation. A key aspect of agricultural water management in the region is utilizing water from reservoirs. Here we introduce a novel approach that combines optical remote sensing with satellite laser altimetry to monitor the availability and use of active water storage in reservoirs. New hydrological insights for the region: Results indicate that water from reservoir storage satisfies up to 14.9 % 2.2 % of the annual demand, but another 11.5 % 5.2 % are groundwater withdrawals. Our analysis indicates a necessary average annual reduction in groundwater extractions by at least 8.0 % 1.6 % for sustainability. Additionally, highly energy-intensive water pumping from Amu Darya River provides more than half of the water resources used in Bukhara and Kashkadarya, resulting in a significant carbon footprint of the region’s agricultural production. The detailed breakdown of water uses and irrigation water consumption by crop type informs efficient, sustainable water management, offering new opportunities for agricultural water accounting in Central Asian irrigation oases.

Climate change induces high variability in drought patterns and extreme precipitation indices in rainfed cocoa farming, impacting cocoa production. This study evaluated water stress, meteorological and agricultural drought conditions, and critical extreme precipitation indices in the worldapos;s two largest cocoa-producing nations from 1981 to 2022. The results revealed a significant reduction in total annual precipitation (PRCPTOT), in the last three decades, with the greatest decline in the 1991–2000 and 2011–2022 periods. Ghana experienced the most significant reduction up to 15% (200mm/year) in the last decade, attributed to a substantial decrease in wet days number (RR1) up to 25days per year, a reduction in maximum consecutive wet days (CWD) up to 6days per year, and an increase in maximum consecutive dry days (CDD) up to 15days per year. Moreover, there was a notable decline in the Simple Daily Intensity Index (SDII), with reductions of up to 4mm/day in certain areas, contributing to increased drought frequency, severity, and duration. In the most recent decade (2011–2022), particularly during the extremely dry years of 2013 and 2015, cocoa-growing regions in Ghana (GHA) and eastern Cte dapos;Ivoire (CIV) experienced prolonged agricultural drought expressed by soil moisture deficit, typically extending from May to September. Additionally, large portions of central and eastern Ghana, as well as northeastern Cte dapos;Ivoire experienced sustained water stress, with over three consecutive months of total monthly precipitation falling below 100mm, negatively impacting cocoa productivity. The decrease in the yield in the range of 2.5% to 37% was noted in the dry years and the following years, varying according to the country depending on the severity of the drought. Sensitivity analysis highlights cocoa yieldapos;s responsiveness to drought and water stress, particularly in specific years when water stress occurred, such as 1984,1985, 1989, 1995, 1999, 2000, and 2008. Considering the observed trends in precipitation patterns and their impact on cocoa production, it is crucial to acknowledge the inherent uncertainty of future precipitation patterns due to climate change. To address this challenge effectively, our study underscores the importance of identifying and closely monitoring regions currently facing water stress, as determined by precipitation and drought indicators. Over the analysed period (1981–2022), we have noted shifts in the distribution of water-stressed areas, highlighting the dynamic nature of this issue. Consequently, we advocate for a targeted approach to implement cocoa supplementary irrigation in consistently water-stressed regions.

Study region: Volta Basin Study focus: Water management in transboundary basins is challenging due to the interaction of natural and human factors across political borders. The Volta River Basin, shared by six West African countries, exemplifies this with variable water distribution and socio-economic pressures. This study presents a comprehensive multi-scale water accounting of the basin, assessing water flows and usage at basin-wide, sub-basin, and riparian country scales from 2003 to 2021. New hydrological insights for the region: The results reveal average basin closure is 55 % with room for additional water allocation given that utilizable water in the basin is 20 km3 /year and almost 25 % of the basin’s exploitable water is non-recoverable water (wastewater). Sub-basin analysis showed variations in average annual rainfall, ranging from 940 to 1250 mm/year, and groundwater recharge rates (18–64 mm/year), with southern sub-basins receiving more rainfall and having higher recharge rates. Similarly at the country level, variability in rainfall (630–1220 mm/ year) and recharge rates (20–280 mm/year) were noted, with downstream countries benefiting from higher rainfall and significant inflows from upstream countries. The analysis underscored the interconnectedness of water use across the basin’s riparian countries. The study’s findings give insights for the strategic management of water resources and the crucial need for enhanced cooperation among riparian countries to address shared challenges and opportunities in the Volta Basin.

The interaction between climate change and agricultural intensification contributes to biodiversity loss, while widespread degradation of land and water undermine food system productivity. Agroecological principles aim to guide food systems transformation but rarely refer to water or aquatic foods, which are critical elements of nutritious, sustainable and equitable food systems. Here we examine the principles and frameworks presented in agroecological literature and suggest rephrasing of six of the principles to incorporate water, aquatic foods and land- to seascapes. We recommend three cross-sectoral actions that leverage aquatic features in agroecosystems to facilitate more effective transition pathways towards sustainable food systems.

Migration and social transformation are major drivers of socio-economic development. Yet, the linkages between social transformation and migration in Ghana are poorly understood. This article seeks to shed light on how social transformation affects or is affected by migration, using mixed methods with transformationalist and social change theoretical lenses. At the same time, there have been retrogressive transformations in the economic conditions, technology and demography have improved and increased, respectively, and political and cultural factors have remained relatively the same over the past decade. Although there is a perceived bi-directional relationship between social transformation and migration, social transformation exerts greater influence on migration than migration has on social transformation except for higher educational attainment and improved household income. Therefore, the relationship between social transformation and migration is not balanced in our study area as the former influences more than the latter.

Sri Lanka Government’s ambitious decision to ban synthetic agrochemicals, including chemical fertilizers (and pesticides), in April 2021 made it the first nation in the world to embark on a full-scale transition to – as the Government called it—organic farming, and address concerns about human health and the environment. Previous policies had envisioned a gradual shift, but the sudden ban caught agriculture off guard. Declining foreign exchange reserves to import chemical fertilizers and coinciding peak fertilizer prices appeared to support the timing of the move. However, the ensuing rush for organic fertilizers failed to meet the national demand, resulting in severe losses in rice and export-oriented plantation crops. Facing decreasing yields and food insecurity, the government lifted the ban in November 2021. The events raised critical questions about the necessity and feasibility of such a drastic transition and alternative ways. To explore the general feasibility of transitioning toward organic fertilizers, this study considered the actual and potential availability of biomass to “replace” chemical fertilizers at the national scale as was envisioned by the Government. The analysis focused on the four main national crops and showed that in none of the selected scenarios, Sri Lanka’s actual and potentially available organic fertilizer could supply rice- and plantation-based agrosystems with sufficient nitrogen, not to mention other crops or nutrients. The Government will in every scenario, including one that assumes a stepwise transition, remain compelled to spend significantly on importing organic fertilizer to maintain the required crop yields, which would cost the Government more foreign currency than purchasing chemical fertilizer. Even more costly is purchasing rice to close the national production gap, as Sri Lanka eventually did at the end of its nationwide experiment, which resulted in major food security concerns.

Climate change is projected to notably impact water requirements and crop yield; therefore, it is imperative to quantify climate risk and devise climate-resilient field management practices. This study applied the AquaCrop model to Tulsipur, a sub-metropolitan city located in Western Nepal. The model was calibrated and validated on a field scale, and various scenarios were analysed for baseline (2010–2020) and future (2021–2100) periods to formulate workable management strategies for irrigation and fertilizer applications. Results showed that a deficit irrigation strategy could lead to 81% fewer requirements for irrigation in rice and 24% in wheat at the cost of a minimal (~1%) reduction in yield. Water requirement is projected to decrease and crop yield to increase for both crops for all future scenarios, except wheat water requirement, where water requirement is projected to increase by up to 13% in the future. Rainfed irrigation leads to extremely high variance in crop yields. Deficit irrigation under the nationally recommended fertilizer dose is recommended as a better option to develop climate resiliency in cereal yield in the study area.

1. As climate change impacts intensify, water-related problems and the vulnerability of small-scale agricultural producers are expected to increase, suggesting the need for an inclusive and integrated management of water resources. This requires understanding the system and mapping the stakeholders, among other things. 2. This study was conducted in the Borkena and Mille catchments of the Awash River basin, Ethiopia. It aimed to improve the understanding of how to improve the effectiveness of agricultural water management practices and water resource planning to address the vulnerability of small-scale agricultural producers and draw implications for future stakeholder participation. 3. Data were collected through key informant interviews, focus group discussions, literature reviews, and observation. The Driver-Pressure-State-Impact-Response framework was used to assess the systemapos;s state and its implications for the vulnerability of small-scale agricultural producers. Stakeholder analyses involved mapping the stakeholders, examining their power and power resources, and evaluating their interest, influence, participation, trust levels, and dynamics of exclusion and empowerment. 4. The results suggested that the natural and agricultural systems in both catchments are degrading, though multiple responses are implemented regarding agricultural water management practices. 5. Diverse groups of stakeholders, such as development organizations, academic and research organizations, local administrative bodies, subregional policy and decision-makers, communities and community-based organizations, civil society organizations, donors, and nongovernmental organizations, participate in the planning, design, and implementation of agricultural water management practices. 6. The stakeholder indicated multiple strategies such as promoting community participation and participatory decision-making, aligning plans with communitiesapos; priorities and interests, improving collaboration and integration, improving access to resources, providing targeted capacity building and continuous awareness raising, and improving the implementation of policies and strategies to improve the effectiveness of interventions and address the vulnerability of small-scale agricultural producers. 7. Stakeholders have perceived strong legitimacy, but most of them have very little or no access and control over resources and connections with other stakeholder groups. Furthermore, stakeholders showed similarities in strategic options, differences in degree of influence, and demonstrated moderate to considerable trust in others. The alliance or relationship of most stakeholder groups in terms of coordinated action and coproduction using common resources was found to be weak, and most of the stakeholders lack competencies (that is, basic skills to plan, design, and implement interventions). 8. We argue that a relatively weak relationship or alliance in terms of coordinated action and co-produ

This study aimed to assess the impact of urbanization on land use dynamics and its consequences on the local climate of the town of Bingerville for the period from 1990 to 2020. Land cover classification was based on Landsat data for the years 1990, 2000, 2015, and 2020 in order to perform a diachronic analysis of surface conditions. Precipitation and temperature data were used to assess local climate trends. A number of extreme precipitation indices (PRCPTOT, RR1, SDII, CWD, CDD, R95p, and R99p) and temperature indices (TN10p, TN90p, TX10p, TX90p, and WSDI) were calculated. The results show a sharp increase in the built-up area from 1990 to 2020, with 32.11 km² (29.68% per year), compared with forest or crops, i.e., 19.09 km² (0.62% per year), and scrubland or fallow land, i.e., 13.21 km²(1.39% per year). However, extreme precipitation indices such as annual precipitation (PRCPTOT), rainy days (RR1), consecutive rainy days (CWD), and extremely rainy days (R99p) have increased from 2011 to 2020. In addition, buildings are correlated with RR1 and CWD. This could be one of the key factors contributing to the occurrence of flooding in the town of Bingerville, which is probably linked to urbanization. As for extreme temperature indices, most show a statistically insignificant trend, except for cold days (TX10p) and hot days (TX90p), which have a statistically significant trend of 0.004 and 0.018, respectively. This means that there have been changes in these two indices. Consecutive hot days (WSDI) and TX90p increased from 2010 to 2016, and buildings also correlated with these two indices. Consequently, changes in land use could have an influence on local temperature through the urban heat island (UHI) phenomenon. However, uncontrolled urbanization has an impact on the local climate. The town authorities need to be aware of this, and be rigorous in this area, to avoid future disasters in Bingerville.

Study Region: Shilansha is a watershed located in the Upper Bilate River of the Rift Valley Lake Basin in southern Ethiopia. The region experiences extreme soil water-erosion among the greatest rates globally at 498 tons ha- 1 yr- 1 leading to large quantities of sediment accumulation in Lake Abaya. Study Focus: Surface runoff, soil water-erosion, and sediment loads in the region vary with agricultural seasons and rainfall intensities but are often poorly quantified in modeling studies. This study assessed these effects using the event-based physically based distributed open-source Limburg Soil Water Erosion Model (OpenLISEM), incorporating local field data and multi-sensor satellite data processed with machine learning techniques. New Hydrological Insights: During the fallow season, simulated surface runoff and total soil loss were 9.7 % and 47 % larger than the growing season and 0.9 % and 42 % larger than the harvest season, respectively. Compared to moderate intensity, an 87 % increase in high rainfall intensity increased surface runoff by 159 % and soil loss by 295 %, while a 45 % decrease in low rainfall intensity reduced surface runoff by 49 % and soil loss by 85 %. High rainfall intensity had a greater impact when combined with fallow season land cover, while effects were smallest when low rainfall intensity combined with growing season land cover. A calibrated model parameter set for a particular season resulted in deteriorated model performance when applied to other seasons. These findings offer insights on the importance of considering seasonal changes in land cover and rainfall intensity when developing soil and water conservation strategies.

Since its introduction at the 2015 UN Convention to Combat Desertification Conference, the concept of land degradation neutrality (LDN) has guided countries’ efforts to restore land for sustainable socio-economic and environmental benefits. LDN aims to balance reductions in land quality with initiatives to rehabilitate degraded land. However, due to budget constraints, it is not feasible to address all degraded land, necessitating strategic decisions about where to invest resources. This study, using Ethiopia as a case study, aimed to: (i) assess the long-term (1995 - 2024) land degradation trends, (ii) identify areas of net land loss or gain, (iii) prioritize regions and actions for addressing LDN, and (iv) evaluate the impact of Ethiopia’s landscape management initiatives on LDN. The analysis of LULC changes and the observed landscape transformation across diverse agroecological zones yielded mixed results. While some areas, such as the dry Kolla and dry Weyna Dega regions, showed improvement, others, including the dry Dega and der Berha zones, experienced continued degradation. These variations affected the three main objectives of LDN: healthy ecosystems, food security, and human well-being. The ongoing landscape transformation, driven by LULC changes, underscores the need for more comprehensive strategies to mitigate further degradation and restore affected lands. Our findings regarding LDN trajectories, such as a 6 % reduction in degraded land between 2010 and 2024, suggest that national LDN implementation, through diverse Sustainable Land Management (SLM) practices, is essential for achieving the country’s LDN goals. However, LDN outcomes varied across Ethiopia’s agroecological zones, influenced by differences in environmental conditions, land use practices, and socio-economic factors. This highlights the necessity for tailored solutions, an understanding of varying restoration potentials, targeted resource allocations, and a focus on prioritizing the most vulnerable areas. Additionally, documenting both the successes and challenges of Ethiopia’s restoration efforts, enhancing the effectiveness of its landscape management initiatives, and ensuring the long-term sustainability of its SLM practices are critical for achieving LDN.

The Middle East and North Africa (MENA) region, with its arid and semi-arid climate, faces profound challenges in managing limited water resources. These challenges are further intensified by political tensions and socioeconomic inequalities, often resulting in water being an essential element in conflicts and tensions. Particularly during the last decade, the number of conflicts involving water has increased dramatically in MENA. This research explores the dynamics of water’s role in conflicts, actors and scales of conflict across five fragile MENA countries, where it serves as a weapon, a catalyst, and a casualty. The analysis revealed a significant increase in the number of water-related incidents during the last two decades in these countries, with devastating implications on multiple social, economic, and security dimensions. The study suggests a concentric circle transformation (CCT) framework with three tiers of strategies: foundational, supportive, and expansive to help move from water-conflict to water-peace in MENA. These strategies, with examples of interventions, support transformation to water-peace by integrating soft interventions like empowering local communities, raising awareness, with hard interventions such as building resilient infrastructures and leveraging the power of innovative technological solutions. The framework offers scalable and adaptable solutions for regions facing similar challenges globally.

Despite a growing literature highlighting the benefits of agroecology in Africa, policy makers, donors, and scientists are still debating the “viability” of agroecological practices. However, assessing the viability of agroecological practices poses challenges, and so far, no studies have clearly documented them and options for addressing them. The aim of this paper is to describe the main methodological challenges we faced in assessing the viability of agroecology in 11 case studies in Africa so that others planning assessments can benefit from what we learned. Seven methodological challenges discussed are (i) defining an object of study through a list of practices or agroecological principles, (ii) having a practice-based assessment versus a systemic assessment at field or farm scales, (iii) having a subjective assessment of the viability of agroecological practices based on farmers’ perspective or an “objective” assessment, (iv) having a qualitative or quantitative assessment, (v) having a diachronic versus synchronic assessment, (vi) having a multisite approach versus a single-site study, and (vii) having a context-specific assessment method or a unitary assessment method. We conclude that the assessment of the viability of agroecological practices needs to be multicriteria, systemic, and based on farmers’ perspectives and not practice-based using a single simple metric. This is a change from the conventional way such systems are evaluated based on quantitative metrics. We recommend using a mixture of quantitative and qualitative assessments that highlight farmers’ perceptions of practices embedded into their farming systems, using transversal and context-specific data.

The transformation of gender roles and responsibilities have implications for how men and women and other social groups are impacted by and cope differently with the changing climate. However, such dynamics are often not considered in formulating and implementing climate resilience interventions. Through a case study in rural communities of the northwestern part of Ghana, Africa, using a mixed-methods approach, this paper investigates the gendered nature of transformations and the implications for climate resilience building. The study found that compared to ten years ago, women have increase access to farmland, participate more in agricultural development decision-making, better access to credit, and more diverse livelihood pathways. Nevertheless, women’s ability to adapt to climate change impacts like droughts is worsening because of cultural norms that restrict women’s control over land resources and their limited adaptive capacities. To achieve positive gendered transformation outcomes while minimising negative social transformation trade-offs, policy makers must rethink the strategies for building climate resilience. There is the need to focus on strategies that support the formulation and implementation of well-funded and targeted interventions with a perspective on gender realities and dynamics that provide women with real resources and agency, enabling institutional support and transformative opportunities.

In river basins with strong seasonal river fluctuation, water storage of various types is required to meet water demands. Water is stored in man-made reservoirs, groundwater aquifers, the soil, natural lakes and wetlands. Ideally, to meet any water demand, these water storage options could be used in an integrated manner. However, integrating suites of water storage options in the management for water, food, energy, and the environment is limited in practice. One of the reasons for this is the lack of knowledge on the volume and temporal dynamics of the different storage types. This study therefore assessed water storage in different storage types and their temporal dynamics using remote sensing and secondary data in the Tana-Beles sub-basin of Ethiopia. The results show that the active total storage volume in the sub-basin varies from 7.3 BCM to 16.2 BCM in dry and wet months, respectively. Lake Tana storage is the largest with 50% of total storage while built reservoirs only account for 2% of the same. Given different competing needs and constraints from each storage options not all the water in the storages can be utilized. Optimizing natural and built storage options in an integrated system can maximize water security gains.

Understanding current and future crop water demand is crucial for improving agricultural productivity and managing long-term water resources in a changing climate. This study aimed to estimate how the crop water demand will change under different water management practices and climate change scenarios. The field experiment using irrigation decision-making tools was carried out in 2016 and 2017 in Lemo, Ethiopia. Crop and water management data were collected on cabbage and carrot production. The field data were used to estimate the crop coefficient (Kc), and the results were compared with the simulated Kc with the Agricultural Policy Environmental eXtender (APEX) model. Predicted future climate data were used in APEX to evaluate the effect of climate change on future crop water requirements and Kc. The field data analysis indicated that, on average, farmer traditional practice (FTP) treatments used more water than wetting front detector (WFD) treatments. Using the soil water balance method, the average of the two treatments’ Kc values at the initial, mid, and late stages was 0.71, 1.21, and 0.8 for cabbage and 0.69, 1.27, and 0.86 for carrot, respectively. The APEXsimulated Kc has captured the FAO Kc pattern very well with the coefficient of determination (R-square) ranging between 0.5 and 0.74. The APEX simulation and the soil water balance estimated Kc also indicated a strong association with R-square ranging between 0.5 and 0.75 for cabbage and 0.66 and 0.96 for carrot. The projected climate change analysis indicated that the crop water demand is expected to increase in the future due to increasing temperatures. Under climate change scenarios, the growing season potential evapotranspiration will increase by 2.5, 5.1, and 6.0% in 2025, 2055, and 2085 compared to the baseline period, respectively. The simulated Kc indicated a higher coefficient of variation in 2085 with 19% for cabbage and 24% for carrot, while the 2025 period simulated Kc indicated the least coefficient of variation (16 and 21% for cabbage and carrot, respectively). The study shows that current irrigation planning with the available water resources should take into account higher crop water requirements in the region to reduce water scarcity risks.

The accuracy of flood susceptibility prediction (FSP) could be affected by inadequate representation of flood conditioning factors (FCFs) and the approaches used to identify the most relevant FCFs. This study analyzed twenty-eight FCFs derived from open-access earth observation datasets to develop FSP model for a highly urbanized Akaki catchment, which hosts and surrounds the capital city of Ethiopia, Addis Ababa. In the study, relevant FCFs were first identified using different collinearity-based and model-integrated feature selection methods, and sequentially introduced into a machine learning model. Simulated FSPs were compared against a reference flood inventory dataset to determine the most effective selection method. Findings show that: (i) using extreme rainfall indices improved the accuracy of FSP, (ii) Mean Decrease Impurity (MDI) was found to be the most effective feature selection method, (iii) geomorphological and physiographic FCFs showed the highest and the lowest predictive power, respectively, and (iv) the quantile method outperformed other approaches in classifying the flood susceptibility map. Findings indicate that an area of 217 km2 , 43000 buildings, 163 km of paved roads and 0.54 million inhabitants are highly susceptible to flooding in the catchment. In particular, Addis Ababa contains almost 75 % of the estimated susceptible elements in only one-third of the catchment area. The results of this study provide valuable insights for urban planning and flood management, helping to reduce the socio-economic impacts of flooding and enhance urban resilience.

The Akaki River, in Ethiopia, becomes a source of antimicrobial-resistant (AMR) pathogens and genes that are spreading to receiving water. Water quality monitoring (WQM) is limited in Akaki, and the available evidence is based on short-term monitoring of inconsistent sampling sites and water quality parameters. Therefore, we designed a suitable WQM plan for the Big Akaki River receiving wastewater from rural, urban, and peri-urban areas. WQM plan was designed by employing multiple approaches including literature review, field observations, spatial analysis, and pollutant “hotspot” identification. Information was extracted through a systematic review of 48 articles, selected through a screening process, to guide the selection of suitable monitoring sites. Field observation was used to inspect previously sampled sites and identify pollution sources and exposure routes to antibiotic-resistant bacteria and zoonotic pathogens. For validation, water samples were collected from 40 sites identified from the literature review and field observation, and results were refined during a stakeholder consultation workshop. Hotspots were identified based on chemical oxygen demand, dissolved oxygen, ammonia, and extended-spectrum eta-lactamase (ESL)-producing Escherichia coli and Salmonella enteritidis/Shigella flexneri data. Cluster analysis of the water quality data categorized the 40 sites into three groups, and the number of sites for future monitoring to 20, including possible pollutant hotspots, reference sites, known pollution sources, exposure routes, and availability of river discharge data. The WQM plan will help AMR and zoonotic pathogens monitoring and mitigation in the study sites. Our approach can be replicated to design WQM plans for other rivers.

The study explores the evolving land use patterns and their implications for sustainable development in Ghana and neighboring megacities. Using 15 years of historical Land Use and Land Cover (LULC) data combined with Land-Use Harmonization datasets, the study applies the Future Land Use Simulation (FLUS) model to project future LULC dynamics under Shared Socioeconomic Pathway (SSP) scenarios in the densely urbanized Greater Accra Region (GAR) of West Africa. Analyzing historical and current land use dynamics in the GAR revealed notable shifts, notably a decrease in Rangeland and an increase in Built-up areas. Future projections of LULC under SSP scenarios show continuous expansion of Built-up areas, particularly under SSP245 (middle of the road scenario) and SSP370 (Regional Rivalry scenario). This is consistent with results from the urban growth analysis using Urban Expansion Intensity Index (UEII), indicating high-speed expansion in baseline periods and shifts towards medium to high-speed expansion under SSP245 and SSP370 with low-speed expansion under the SSP126 (Sustainability scenario). Shannon entropy analysis shows dispersed urban sprawl, especially under SSP245 and SSP370, with rapid increases in Built-up areas and declines in green areas. For instance, the analysis of the landscape metrics reveal that built-up and green areas are projected to increase and decrease up to 87% and 12% respectively, under these scenarios. The decline in urban green areas was significantly influenced by proximity to the central business district (CBD), with green spaces diminishing more as distance to the CBD decreased. Therefore, relevant local legislation, such as the 2016 Land Use and Spatial Planning Act (Act 925) must be enforced, along with integrating urban initiatives and policies that promote green areas, is essential for ensuring the sustainability of urban ecosystems for the well-being of both humans and the environment. This enables West Africa to achieve its Global commitments as reflected in the UN SDGs, towards the New Urban Agenda (NUA) and the Africa Urban Agenda 2063.

There is an urgent need to expand wastewater treatment on the African continent. To help choose appropriate technologies for this task, we evaluated the efficiency, energy and chemical demands, and costs of four wastewater treatment plants (WWTPs). These plants represent the main wastewater treatment technologies operated by the Addis Ababa Water and Sewerage Authority (AAWSA): waste stabilization pond (WSP), anaerobic baffled reactor (ABR), up-flow anaerobic sludge blanket with trickling filter (UASB-TF), and membrane bioreactor (MBR) technologies. Principal component analysis revealed that season significantly impacts the raw and treated wastewater quality (ANOSIM, R ¼ 0.3126, p ¼ 0.001), while the type of treatment plant did not significantly affect the measured effluent characteristics (ANOSIM, R ¼ 0.1235, p ¼ 0.2000). In contrast, construction and operational costs, as well as energy and chemical demands per m3 of treated wastewater, varied starkly between the WWTPs. Total costs of wastewater treatment in 2022 ranged from $0.045 to 0.546 per m3 of wastewater treated, being 6–12 times higher for MBR compared with the other WWTP technologies. Real-world performance data as reported in this study are essential for choosing appropriate technologies that meet Africa’s wastewater treatment needs.

Historically, Ethiopia has experienced recurrent droughts and floods, which may intensify due to climate change. This study has evaluated the performance of 45 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating ten extreme precipitation indices against corresponding indices from the Enhancing National Climate Services (ENACTS) during short rainy (February–May, FMAM) and main rainy (June–September, JJAS) seasons for the period 1981–2014 over Ethiopia. Ensemble mean of the top-ranking models are also evaluated against ENACTS in reproducing extreme indices over five Agro-ecological zones (AEZs) of the country. The Taylor Skill Score (TSS) was used to rank the performance of the individual CMIP6 models for JJAS and FMAM seasons with respect to ENACTS while Comprehensive Rating Metrics (RM) were used to compute the overall ranks of the models. Our results show that most CMIP6 models reasonably captured the spatial distribution of the seasonal extreme precipitation indices even though they could not reproduce the magnitude of indices, especially in the highland and high rainfall areas of the country such as Northwest and west parts of the country. However, the biases in lowland and low rainfall regions, such as the eastern and northeastern parts of the country, are smaller compared to other areas. More than 30 CMIP6 models underestimated the extreme indices with the exception of consecutive wet days which is grossly overestimated in the highland and high rainfall areas specifically in western parts of the country. Additionally, EnseMean in the tropical and desert AEZs performs particularly better in simulating extreme indices compared to other AEZs. The ensemble mean of the top-ranking models (EnseMean) generally outperformed both individual models and ensemble of all models in the representation of observed extreme indices across all metrics and seasons. Moreover, the performance of individual models is subject to variation based on the season, and the selected extreme indices. It is also noteworthy that their performance is relatively less influenced by horizontal resolution. Further evaluation, focusing on teleconnections such as ENSO and IOD, is a crucial next step for evaluating models and creating a sub-ensemble.

Groundwater is one of the most vital natural resources worldwide. However, shallow aquifers are prone to contamination, posing significant risks to human health, livestock, agricultural productivity, and economic growth. Identifying appropriate land management strategies is critical for mitigating groundwater vulnerability to pollution. This study evaluates groundwater vulnerability to pollution under various land management scenarios using the modified DRASTIC model in Bahir Dar City, Ethiopia. The analysis incorporates multiple parameters within the ArcGIS environment, including depth to water table, net recharge, aquifer characteristics, soil properties, topography, vadose zone, hydraulic conductivity, and land use/land cover (LULC). In this study, LULC was added as an additional parameter to enhance the DRASTIC model. Groundwater vulnerability to pollution was evaluated under four distinct land management scenarios: baseline, agricultural expansion, urbanization, and reforestation. A single-parameter sensitivity analysis and a map removal sensitivity analysis were performed to identify the most influential parameters affecting groundwater vulnerability under the baseline LULC conditions. The result revealed that groundwater vulnerability in Bahir Dar City under baseline conditions is primarily influenced by LULC and net recharge. The areal average groundwater vulnerability to pollution index at the baseline scenario was 184. Agricultural expansion and urbanization increased the areal average groundwater vulnerability to pollution by 4.9 % and 1.6 %, respectively, while the reforestation scenario reduced it by 1.6 %. These findings highlight the critical role of effective land management practices, such as reforestation, in mitigating groundwater susceptibility to pollution. The results also indicate that groundwater vulnerability to pollution varies across different geological formations. Therefore, given the influence of geological variability on groundwater vulnerability, incorporating geological considerations into urban expansion planning is essential for minimizing the risk of groundwater contamination.

Irrigation plays a crucial role in enhancing food production, increasing land productivity, and improving the livelihoods of smallholder farmers in Sub-Saharan Africa (SSA). Solar pumps and water harvesting ponds have emerged as promising technologies for sustainable agriculture for smallholders in SSA and beyond. The socio-economic impacts of these systems are less studied in the existing literature. This study examined the agricultural productivity of solar pump and water harvesting irrigation technologies and their impacts on income and food security among smallholder farmers in the Central Rift Valley, Lake Hawassa, and Upper Awash sub-basin areas in Ethiopia. Data were collected from 161 farming households that were selected randomly from woredas where solar pump and water harvesting pond irrigation systems had been implemented. The sample size was determined using the power calculation method. Bio-physical observation and measurements were also conducted at field levels. The benefit–cost ratio (BCR) and net water value (NWV) from the use of solar pump and water harvesting pond irrigations were analyzed to assess the viability of these systems. The household food consumption score (HFCS) and household dietary diversity score (HDDS) were calculated to measure food security, while the revenue from crop production was used to measure crop income. An endogenous switching regression model was applied to address the endogeneity nature of the adoption of the irrigation technologies. The counterfactual analysis, specifically the Average Treatment Effect on the Treated (ATT), was used to evaluate the impacts of the irrigation technologies on income and food security. Results indicate that the ATT of crop income, HFCS, and HDDS are positive and statistically significant, illustrating the role of these irrigation systems in enhancing smallholder farmers’ welfare. Moreover, smallholder farmers’ solar pump irrigation systems were found to be economically viable for few crops, with a BCR greater than 1.0 and an NWV ranging from 0.21 to 1.53 USD/m³. It was also found that bundling agricultural technologies with solar pump irrigation systems leads to enhanced agricultural outputs and welfare. The sustainable adoption and scale-up of these irrigation systems demand addressing technical and financial constraints, as well as input and output market challenges.

The global drought community and policy representatives gathered at the United Nations Convention to Combat Desertification’s 16th Conference of the Parties (UNCCD COP16) in Riyadh in December 2024 to discuss the urgent need for improvements in assessing and quantifying drought risks, in developing and implementing transformative solutions, and in boosting policy actions and investments. Only through unprecedented global cooperation can we facilitate pathways towards drought-resilient futures.

Small reservoirs are increasingly common across Africa. They provide decentralised access to water and support farmer-led irrigation, in addition to contributing towards mitigating the impacts of climate change. Water quality monitoring is essential to ensure the safe use of water and to understand the impact of the environment and land use on water quality. However, water quality in small reservoirs is often not monitored continuously, with the interlinkages between weather, land, and water remaining unknown. Turbidity is a prime indicator of water quality that can be assessed with remote sensing techniques. Here we modelled turbidity in 34 small reservoirs in central Kenya with Sentinel-2 data from 2017 to 2023 and predicted turbidity outcomes using primary and secondary Earth observation data, and machine learning. We found distinct monthly turbidity patterns. Random forest and gradient boosting models showed that annual turbidity outcomes depend on meteorological variables, topography, and land cover (R2 = 0.46 and 0.43 respectively), while longer-term turbidity was influenced more strongly by land management and land cover (R2 = 0.88 and 0.72 respectively). Our results suggest that shortand longer-term turbidity prediction can inform reservoir siting and management. However, inter-annual variability prediction could benefit from more knowledge of additional factors that may not be fully captured in commonly available geospatial data. This study contributes to the relatively small body of remote sensing-based research on water quality in small reservoirs and supports improved small-scale water management.

This paper introduces and applies iGain4Gains, an Excel-based model, to reveal how changes to water conservation and allocation, and irrigation technology, can produce four nexus gains. These gains are; reduced aggregate water consumption, sustained crop production, lower carbon emissions, and enhanced water availability for nature. We developed the model with limited data and hypothetical future scenarios from the Amman–Zarqa basin in Jordan. Given its significant irrigation and urban water demands and difficult decisions regarding future water allocation and nexus choices, this basin is a highly appropriate case study. The paper’s primary aim is to demonstrate the iGains4Gains nexus model rather than to build an accurate hydrological model of the basin’s water resources. The model addresses two critical questions regarding increased irrigation efficiency. First, can irrigation efficiency and other factors, such as irrigated area, be applied to achieve real water savings while maintaining crop production, ensuring greenhouse gas emission reductions, and ‘freeing’ water for nature? Second, with the insight that water conservation is a distributive/allocative act, we ask who between four paracommoners (the proprietor irrigation system, neighbouring irrigation systems, society, and nature) benefits hydrologically from changes in irrigation efficiency? Recognising nexus gains are not always linear, positive and predictable, the model reveals that achieving all four gains simultaneously is difficult, likely leading to trade-offs such as water consumption rebounds or increased carbon emissions. Demonstrated by its use at a workshop in Jordan in February 2024, iGains4Gains can be used by students, scientists and decision-makers, to explore and understand nexus trade-offs connected to changes in irrigation management. The paper concludes with recommendations for governing water and irrigated agriculture in basins where large volumes of water are withdrawn and depleted by irrigation.

Flooding has emerged as a significant concern in the Akaki catchment area of Ethiopia, affecting settlements and properties. Early warning systems (EWSs) are implemented to reduce flood risks, but power dynamics among at-risk communities and stakeholders have raised concerns about the reliable accessibility of warning information. We integrated a citizen science approach into existing flood EWSs to promote inclusivity, local perspectives, and equitable expertise distribution in flood early warning. It draws on primary data collected through diverse methods, alongside an extensive review of documents from the years 2021 to 2022. The analysis of qualitative data indicates the integration of citizen science into a flood EWSs delivers dependable early warning information and encourages the establishment of networks. This approach reduces dependence on external entities, enhances local decision-making capabilities, and promotes a sense of ownership, empowerment, and trust. This can transform the dynamics and responsibilities linked to flood management. However, the longer-term participation of citizen scientists in flood EWSs is challenging due to the disparity between commitment levels and benefits, lack of legal frameworks, and insufficient recognition of community diversity within policy frameworks. The research herein emphasizes the significance of understanding power dynamics and institutional capacities in integrating citizen science into flood EWSs. It offers valuable perspectives for policymakers, practitioners, and communities on participatory governance, social equity, and the resilience of communities in the face of environmental challenges.

The Limpopo River Basin (LRB), a transboundary river basin extending over Botswana, Mozambique, South Africa, and Zimbabwe, is highly vulnerable to drought. This manuscript analyzes drought conditions in the LRB using Earth Observation (EO) datasets and key drought indices such as the Standardized Precipitation Index (SPI) and Vegetation Condition Index (VCI). The year 2023, marked by the El Nio phenomenon, exacerbated dry conditions, resulting in prolonged water shortages and reduced agricultural output. Approximately 37% of the basin has been experiencing drought since the 2023–2024 cropping season, impacting ecosystems and crop yields. The present manuscript presents a comprehensive analysis of drought conditions in the LRB and applications of the Digital Twin platform for the LRB to support resource allocation for agricultural planning. Integrating multiple near real-time datasets, the platform enables policymakers to visualize and analyze drought conditions, enhancing decision-making for sustainable resource management and food security in the basin.

Early warning systems (EWS) inform decision making and planning in response to climate shocks and catastrophic disasters. However, the current disaster response mechanism falls short due to the fragmented warning, action, and finance systems, coupled with inadequate institutional collaboration, coordination and inclusive engagement for effective anticipatory action. This study addresses this challenge by introducing an Early Warning, Action and Finance (AWARE) platform to promote anticipatory action through multistakeholder engagement. Data from literature re views, expert surveys, and stakeholder workshops in Senegal, Zambia and Sri Lanka helped identify the platform’s needs and priorities. The study draws upon theories of technological frames, interpretative flexibility, boundary objects, social learning, collaborative governance and adaptive co-management to conceptualize a framework for AWARE. Results demonstrate the potential of AWARE as a boundary object that fosters social engagement, active involvement, open communication, collaboration, and shared commitment to safeguarding lives and liveli hoods. Analysis of technological frames and interpretative flexibility underscores the role of social learning in shaping the design and user features that promote multiscale institutional responses to disasters. AWARE aligns with the priorities of the Sendai Framework and emphasizes system thinking, co-production of knowledge, and the need for context-specific solutions to enhance anticipatory action. Recognizing the limitations of one-size-fits-all EWS, the AWARE framework acknowledges contextual factors as barriers to implementation. The study underscores the importance of integrated EWS and collaborative efforts to overcome implementation barriers and improve anticipatory action outcomes.

The world faces multiple water crises, including overextraction, flooding, ecosystem degradation and inequitable safe water access. Insufficient funding and ineffective implementation impede progress in water access, while, in part, a misdiagnosis of the causes has prioritized some responses over others (for example, hard over soft infrastructure). We reframe the responses to mitigating the world’s water crises using a ‘beyond growth’ framing and compare it to mainstream thinking. Beyond growth is systems thinking that prioritizes the most disadvantaged. It seeks to decouple economic growth from environmental degradation by overcoming policy capture and inertia and by fostering place-based and justice-principled institutional changes.

Conventional rice production through puddled transplanted rice-PTR is tillage, water, energy, and capital intensive. Furthermore, it is a major contributor to greenhouse gas (GHG) emissions. In this regard, Direct seeded rice-DSR can be a potential alternative to PTR. DSR can reduce input use and GHGs emissions, while sustaining yields. However, depending upon agroclimatic situation, DSR impact analysis on GHGs emission and yield resulted inconsistent findings, questioning whether it is better over PTR or not. To bridge this knowledge gap, we performed a meta-analysis synthesizing 876 paired measurements from 54-peer-reviewed studies to understand how DSR impacts N2O and CH4 emissions, GWP (heat-trapping potential of greenhouse gases compared to CO2), yield and C-footprint-CFP (environmental impact in CO2 eq. due to concerned activity). Compared to PTR, DSR decreased CH4 emissions by 70%, GWP by 37% and CFP by 34%, despite 85% increase in N2O emissions. However, this shift comes with a trade-off, with 11% decrease in yield. To decipher the primary factors driving these outcomes, we conducted subgroup analyses by taking assorted environmental conditions and management practices as moderators. Low to medium pH soils, zero tillage, puddled soil (wet DSR), conventional flooding, and high nitrogen rates (gt;200kg/ha) are found to be favourable for DSR with comparable yields but posing a discrepancy with environmental sustainability. Therefore, further research to evaluate DSR across agro-ecologies, management practices, are needed, to optimize yields with lower GWP and CFP.

Financial inclusion is recognized as a vital driver of sustainable development and serves as a fundamental pillar of climate action. It is crucial to enhance the climate resilience of smallholder farmers in the face of severe and unpredictable climate shocks, which disproportionately affect them. However, the level of financial inclusion in Ethiopia remains low, and its impact on the climate resilience of smallholder farmers has not been thoroughly examined using rigorous model and comprehensive dataset. This study investigates the impact of financial inclusion on the climate resilience of rural households, using a large data set from the Ethiopian Socio-Economic Survey. The principal component analysis was applied to construct a climate resilience index. The financial inclusion was measured using an index that encompasses three dimensions: penetration, availability, and usage. In order to address the endogenous nature of financial inclusion, an instrumental variable approach was employed, using the distance to the nearest financial institution and religion as instrumental variables. The results demonstrated a positive and significant impact of financial inclusion on the climate resilience of rural households. Therefore, the government should strengthen the provision of essential financial and related infrastructures in rural Ethiopia to improve access to financial products and services. Furthermore, it is essential for policymakers to initiate and implement financial sector reforms that ensure the availability of affordable and tailored financial services. These reforms should also prioritize the development of climate-resilient agricultural finance, thereby contributing to the achievement of climate action goal of sustainable development.

Greenhouse gas (GHG) emission from tropical large hydropower reservoirs (LHRs) is the highest among all climatic zones due to the combinatory effect of elevated content of flooded organic matter and high temperatures. Traditional methods for GHG emission estimation involve extensive fieldwork, topographic surveys, hydrological analyses, and environmental assessments with high-end instrument requirements. In a country like India, where the hydropower sector is mushrooming rapidly, implementing these techniques on such a large scale is challenging. Alternatively, cloud-based tools like Google Earth Engine (GEE), G-res, and Earth Observation (EO) data related to biophysical and climatic conditions with in-situ reservoir water levels provide an opportunity to quantify GHG emissions from LHRs efficiently. In the present study, Maithon, one of the oldest LHRs in India, situated in a tropical climatic zone, has been studied by integrating site-specific parameters to estimate GHG emissions. The results from this study, which show that at the mean operating level (146.31 m) of the reservoir, net GHG emission is 1,024 - 1,271 gCO2e/m2/yr (with a 95% confidence interval), are of significant importance. This study highlights the GHG emissions varying greatly between the full reservoir level (786 gCO2e/m2/yr) and near the dead storage level (3,855 gCO2e/m2/yr), indicating the role of reservoir operating level in mitigating GHG emissions to achieve global goals like net zero emissions. There has been limited work globally using the G-res tool, and this is the first comprehensive study of initial GHG emission estimation of a tropical reservoir using G-res and GEE incorporating updated high-resolution land use land cover and Sentinel-1 images.

Southern Africa faces significant impacts of El Nio primarily in the form of droughts. Zambia is not an exception. Standardized Precipitation Index (SPI), rainfall anomaly and Vegetation Condition Index (VCI) are robust indicators for drought studies due to their distinct and complementary roles. Our results reveal severe meteorological drought conditions in Zambia using SPI and rainfall anomaly. VCI values have declined in the cropping season due to vegetation stress induced by water deficit conditions. Low rainfall leads to widespread deterioration of crop production, with approximately 40.46% of the country experiencing drought conditions in 2023–2024. The Central, Eastern, Southern, Lusaka, and Copperbelt provinces showed lower VCI values in March and April 2024, indicating poor crop health and drought-like conditions. On the other hand, low rainfall has substantially influenced hydropower reservoirs. Significant surface water loss is observed in the hydropower reservoirs such as Itezhi Tezhi Dam (117.40 sq. km), Mita Hills Dam (25.72 sq. km) and in parts of Lake Kariba (58.72 sq. km) between December 2023 and April 2024. This loss has disrupted industries relying on water resources and hindered hydropower generation, leaving substantial portions of the population without electricity for extended periods. The present study aims to explore the power of open access Earth Observation data and cloud analytics to evaluate the extent and multi-sectoral impact of the recent drought in Zambia. Results highlight the upcoming challenges the country might face in food and nutrition and the critical need for stakeholder involvement and policy design to mitigate future crises and strengthen vulnerable communities.

Climate change remains a significant threat to farm households, especially in developing countries. It exacerbates their vulnerability to food insecurity by reducing agricultural productivity and raising agricultural production costs. Adoption of climate smart-agricultural (CSA) practices is a promising alternative to build resilient farm households. In this study, we assessed the impacts of adopting CSA practices on climate resilience and vulnerability among farm households in Bale-Eco Region, Ethiopia. A power calculation was used to determine the sample size, and 404 farm households were randomly selected to collect data using structured questionnaire. We estimated household climate resilience index using categorical principal component analysis, and vulnerability index using vulnerability as expected poverty approach. Endogenous switching regression model, which is conditional on the adoption of multiple CSA practices and used to control selection bias and unobserved heterogeneity, was used to assess the impacts of CSA practices on household climate resilience and vulnerability. We employed counterfactual approaches to assess the impacts. The results show that the average treatment effects for most CSA practices are statistically significant and positive for resilience, but negative for vulnerability. This provides empirical support for interventions in climate-smart agriculture, which can help farm households build resilience and reduce vulnerability. We, therefore, suggest that agricultural policies should encourage the adoption of CSA practices and provide incentive packages to farm households that promote this.

Identifying best performing climate models is indispensable for better understanding of the future climate and its impact as well as for planning effective climate change adaptation and mitigation measures. This research aims to identify the best performing Global Climate Models (GCMs) products from the Coupled Model Inter-comparison Project phase 6 (CMIP6) in simulating rainfall and temperature in the Bale Eco-Region (BER), Southern Ethiopia. In this study, evaluations were performed for ten CMIP6 GCMs against observed and reanalysis rainfall and temperature products in terms of how well the GCMs reproduce rainfall, maximum temperature (Tmax) and minimum temperature (Tmin) from daily to annual temporal scales during 1995–2014 period. Performance evaluations were performed using the Comprehensive Rating Index (CRI), which is based on four statistical metrics. The best performing CMIP6 model(s) were bias-corrected by Distribution Mapping (DM) for future climate analysis at different agro-ecological zones (AEZs) and at the eco-region level. The study used projections of climate variables in the near future (2021–2040), mid-century (2041–2060) and late century (2081–2100) periods. Three shared socioeconomic pathways (SSP2-4.5, SSP3-7.0, and SSP5-8.5) were considered as future climate scenarios. The result indicated that BCC-CSM2-MR, CNRM-CM6-1 and MRI-ESM2-0 are relatively better for simulating the rainfall climatology of the BER from the daily to annual temporal scales. EC-Earth3, Ec-Earth3-Veg and MPI-ESM1-2-LR are also comparatively better for simulating Tmax while CNRM-CM6-1, EC-Earth3-Veg and EC-Earth3 outperformed for simulating Tmin in the studied temporal scales. After careful evaluations, climate change analysis was performed using the ensemble mean of BCC-CSM2-MR, CNRM-CM6-1 and MRI-ESM2-0 for rainfall, EC-Earth3 for Tmax and the ensemble mean of CNRM-CM6-1 and EC-Earth3-Veg for Tmin. Accordingly, the annual rainfall is expected to decrease in the near future in the three scenarios in the alpine (2–5%), temperate (11–14%) and sub-tropical (7–9%) AEZs as well as the BER spatial scales (2–5%), but rainfall is expected to increase in the late century period. In contrast, rainfall is expected to increase in the tropical AEZ in both the near future (3–11%) and late century (25–45%) periods. In the mid-century period, rainfall is expected to increase in the tropical AEZ in all the three scenarios, but it exhibits different directions of changes in the remaining AEZs and BER scale at different scenarios. The finding also revealed an expected increase in both Tmax and Tmin in the different AEZs as well as the BER scale, but the projected temperature increase is high in temperate AEZ. The projected increase of rainfall in the near future in tropical AEZ may reduce the frequently occurring droughts mainly in the lowland parts of the BER. Conversely, the reductions of rainfall in the remaining AEZs may introduce challenges for agriculture, water reso

Water plays a crucial role in our food systems and food security. However, the essential role of water for a functioning food system and the impacts of food systems on water availability and quality have not yet been adequately recognized. Due to a lack of coordination among water and food systems actors, there are siloed water, food security, and nutrition strategies. This paper presents the case to make water pivotal in designing food systems, laying out action perspectives for different actors to move toward what we call “water-responsible food systems”. This paper is based on input from many participants during workshops and existing literature. A food systems approach provides an excellent entry point to link food with water considering climate change and energy. Moreover, collective and cross-cutting actions between actors in food systems are essential to make decisive progress, as well as a common language and insight into the trade-offs of the multiple values of water for a clear prioritization of water use and allocation.

Water resources assessments are essential for effective planning in water-scarce regions such as Jordan. Such assessments require sufficient data in space and time. The WaPOR-based Water Accounting Plus (WA +) framework is relevant as it integrates remote sensing data and the Pixel-Based Soil Water Balance model to simulate a basin’s water balance. However, since it relies on remote sensing, this framework only tracks water consumption in irrigated agriculture and does not consider non-irrigation water use and its return flow. This paper modifies the WaPOR-based WA + framework to include non-irrigation manmade consumption and its return flows. The modified framework provides a more comprehensive water budget for the Amman-Zarqa (AZ) basin, presented in a modified WA + resource base sheet for 2018 through 2021. The results show that water availability in the AZ basin is highly responsive to precipitation changes. Average precipitation was approximately 926 Mm3/year between 2018 and 2020, corresponding to an average available water of 485 Mm3/year. However, a reduction in average precipitation by 28% in 2021 corresponded to a reduction in available water to 243 Mm3/year. Nevertheless, substantial groundwater outflows to neighbouring basins may indicate that available water is being overestimated. Manmade consumption increased by 18% from 2018 to 2021, and the total demand exceeded the available supply by 150%. This underscores the pressing need to investigate supply augmentation and conservation methods. Future studies could focus on improving the representation of groundwater dynamics in the modified framework by improving groundwater dynamics in PixSWAB and testing the modified framework with other remote sensing datasets.

This research explores the limitations and opportunities of Water Accounting Plus (WA+) for addressing water management issues in the MENA, focusing on Jordan. A comprehensive literature review and interview-based analysis were conducted to identify prevalent water management issues and evaluate information used in decision-making and strategy appraisals. The findings suggest that WA+ can enhance the spatio-temporal coverage of water resource assessments, refine estimates of irrigation water consumption, and facilitate demand management. Quantifying recharge and surface runoff requires integrating WA+ with hydrological models. Addressing climate change’s impact on future water resources requires integrating climate change projections with WA+.

Improved freshwater resource management requires the implementation of widespread, effective, and timely water quality monitoring. Conventional monitoring methods are often inhibited by financial, infrastructural, and human capacity limitations, especially in developing regions. This study aimed to validate the citizen-scientist-operated transparency or clarity tube (hereafter “clarity tube”) for measuring water clarity as a proxy for total suspended solids (TSS) concentration, a critical quality metric in river systems and wastewater treatment works (WWTW) effluent in Southern Africa. Clarity tubes provided a relatively accurate and precise proxy for TSS in riverine lotic systems and WWTW effluent, revealing significant inverse log- linear relationships between clarity and TSS with r 2 = 0.715 and 0.503, respectively. We demonstrate that clarity-derived estimates of TSS concentration (TSScde) can be used to estimate WWTW compliance with WWTW effluent TSS concentration regulations. The measurements can then be used to engage with WWTW management, potentially affecting WWTW performance. Overall, these findings demonstrate the usefulness of clarity tubes as low-cost, accessible, and easy-to-use citizen science tools for high spatial and temporal resolution water quality monitoring, not only in rivers in Southern Africa but also in WWTW effluent for estimating compliance, with strong global relevance to the sustainable development goals (SDGs).

Many wetlands in East Africa are farmed and wetland reservoirs are used for irrigation, livestock, and fishing. Water quality and agriculture have a mutual influence on each other. Turbidity is a principal indicator of water quality and can be used for, otherwise, unmonitored water sources. Low-cost turbidity sensors improve in situ coverage and enable community engagement. The availability of high spatial resolution satellite images from the Sentinel-2 multispectral instrument and of bio-optical models, such as the Case 2 Regional CoastColor (C2RCC) processor, has fostered turbidity modeling. However, these models need local adjustment, and the quality of low-cost sensor measurements is debated. We tested the combination of both technologies to monitor turbidity in small wetland reservoirs in Kenya. We sampled ten reservoirs with low-cost sensors and a turbidimeter during five Sentinel-2 overpasses. Low-cost sensor calibration resulted in an R2 of 0.71. The models using the C2RCC C2X-COMPLEX (C2XC) neural nets with turbidimeter measurements (R2 =0.83) and with low-cost measurements (R2 = 0.62) performed better than the turbidimeter-based C2X model. The C2XC models showed similar patterns for a one-year time series, particularly around the turbidity limit set by Kenyan authorities. This shows that both the data from the commercial turbidimeter and the low-cost sensor setup, despite sensor uncertainties, could be used to validate the applicability of C2RCC in the study area, select the better-performing neural nets, and adapt the model to the study site. We conclude that combined monitoring with low-cost sensors and remote sensing can support wetland and water management while strengthening community-centered approaches.

Central Asia faces substantial water scarcity due to increasing water demand driven by rapid urbanization, population growth, economic development, and inefficiency of irrigated agriculture. These developments are compounded by the effects of climate change, such as rising temperatures, loss of glacier mass and increased frequency of extreme events, including droughts. The region’s escalating water scarcity is causing disputes and straining rural livelihoods. Moreover, these challenges drive migration, creating considerable societal impacts. However, these issues remain underexplored in climate change research, making the region a global blind spot in climate adaptation and migration studies. We advocate for innovative research pathways that scrutinize smallholder adaptation strategies, examine the nexus between climate change, water scarcity, and mobility, and investigate tensions and cooperation over water resources. We conclude by emphasizing that substantial investments in inter- and transdisciplinary collaboration, improved data availability and quality, and strengthening of research and institutional capacities are essential to advance interdisciplinary climate impact research in Central Asia. Such efforts are vital for addressing existing knowledge gaps and enhancing evidence-based policymaking to improve the region’s position in current and future debates on climate change and sustainable development.

To address the growing electricity demand driven by population growth and economic development while mitigating climate change, West and Central African countries are increasingly prioritizing renewable energy as part of their Nationally Determined Contributions (NDCs). This study evaluates the implications of climate change on renewable energy potential using ten downscaled and bias-adjusted CMIP6 models (CDFt method). Key climate variables—temperature, solar radiation, and wind speed—were analyzed and integrated into the Teal-WCA platform to aid in energy resource planning. Projected temperature increases of 0.5–2.7 C (2040–2069) and 0.7–5.2 C (2070–2099) relative to 1985–2014 underscore the need for strategies to manage the rising demand for cooling. Solar radiation reductions (~15 W/m2 ) may lower photovoltaic (PV) efficiency by 1–8.75%, particularly in high-emission scenarios, requiring a focus on system optimization and diversification. Conversely, wind speeds are expected to increase, especially in coastal regions, enhancing wind power potential by 12–50% across most countries and by 25–100% in coastal nations. These findings highlight the necessity of integrating climate-resilient energy policies that leverage wind energy growth while mitigating challenges posed by reduced solar radiation. By providing a nuanced understanding of the renewable energy potential under changing climatic conditions, this study offers actionable insights for sustainable energy planning in West and Central Africa.

Freshwater pollution is, together with climate change, one of today’s most severe and pervasive threats to the global environment. Comprehensive and spatially explicit scenarios covering a wide range of constituents for freshwater quality are currently scarce. In this Global Perspective paper, we propose a novel model-based approach for five water quality constituents relevant for human and ecosystem health (nitrogen, biochemical oxygen demand, anthropogenic chemicals, fecal coliform, and arsenic). To project the driving forces and consequences for emissions and impacts, a set of common data based on the same assumptions was prepared and used in different large-scale water quality models including all relevant demographic, socioeconomic, and cultural changes, as well as threshold concentrations to determine the risk for human and ecosystem health. The analysis portrays the strong links among water quality, socio-economic development, and lifestyle. Internal consistency of assumptions and input data is a prerequisite for constructing comparable scenarios using different models to support targeted policy development.

The major concern of applying citizen science in water resources is the quality of the data. However, there are limited scientific studies addressing this concern and showing the data value. In this study, we established a citizen science program in the Akaki catchment which hosts Addis Ababa, Ethiopia. Citizen scientists monitored river stage at multiple gauging sites for multiple years. We evaluated the quality of citizen science data through a systematic quality control. Reference data was obtained from neighboring stations of the citizen science program and professionals while the evaluation involved graphical inspections and statistical methods. The quality-controlled data were applied to evaluate the spatial and temporal variation of rainfall-runoff relationships. Initially, large numbers of suspicious data were detected using single station data but that was significantly reduced when the data of multiple sites were compared. Further comparison against professional data revealed excellent agreement with high correlation coefficient (r gt;0.95), and low centered root mean square error (RMSE) lt;0.03–0.08 mm. The citizen science data indicated a large difference in rainfall-runoff relationship over the dominantly urban and rural sub-catchments. The citizen science data allowed comparison of runoff coefficient and base flow index for recent and historical periods where recent streamflow data is unavailable from a formal data source. This study illustrates the immense value of (i) multiple data quality assessment steps for building confidence on the quality of citizen science data, and (ii) citizen science for enhancing our understanding of rainfall-runoff relationships and change in a rapidly urbanizing catchment.

An effective flood early warning system is vital to take action to save lives and protect properties in urban areas which are increasingly prone to flooding. Despite substantial progress in flood early warning systems, limited available and accessible data often impede their advancement and reliability. Engaging communities affected by flooding can help address data and information gaps in flood early warning systems, facilitated by appropriate methods. This study developed and evaluated a flood threshold combination method to support a community-based flood early warning system in the Akaki catchment, home to Addis Ababa, the capital city of Ethiopia. Various flood threshold combinations were formulated, calibrated and validated by integrating multiple sources of data: rainfall, antecedent precipitation index estimates, Sentinel-1 Synthetic Aperture Radar satellite time series of flood extent, long-term simulated streamflow, citizen science data, river water level and three days lead-time numerical weather prediction rainfall forecast. During validation, the rainfall and river water level threshold combination outperformed other threshold combinations with probability of detection, false alarm ratio, and critical success index estimates of 0.74, 0.18 and 0.63, respectively. The flood threshold combination showed high detection performance for most flooding conditions. Flood forecasts with a 1-day lead-time exhibited a high likelihood in detecting historical severe flood events. The study provides a tested methodology for selecting suitable flood threshold-combinations, enhance the engagement of citizen scientists in a community–based flood early warning system in urban communities.