Latest journal articles

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.

Geospatial sciences (GS) include a wide range of applications, from environmental monitoring to infrastructure development, as well as location-based analysis and services. Notably, graph theory algorithms have emerged as indispensable tools in GS because of their capability to model and analyse spatial relationships efficiently. This article underscores the critical role of graph theory applications in addressing real-world geospatial challenges, emphasising their significance and potential for future innovations in advanced spatial analytics, including the digital twin concept. The analysis shows that researchers from 58 countries have contributed to exploring graph theory and its application over 37 years through more than 700 research articles. A comprehensive collection of case studies has been showcased to provide an overview of graph theory’s diverse and impactful applications in advanced geospatial research across various disciplines (transportation, urban planning, environmental management, ecology, disaster studies and many more) and their linkages to the United Nations Sustainable Development Goals (UN SDGs). Thus, the interdisciplinary nature of graph theory can foster an understanding of the association among different scientific domains for sustainable resource management and planning.

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, population growth, rapid urbanization, shifting dietary patterns, and economic development pose significant challenges to food security, particularly in the Global South. Addressing these challenges involves efforts aimed at sustainable agricultural intensification (SAI), especially for smallholder farmers in marginalized regions. However, knowledge gaps persist regarding smallholder farmers’ access to water for SAI, particularly in arid and semi-arid agroecological zones. This study investigates smallholder farmers’ access to water for SAI in the Guinea and Sudan Savannah Agroecological Zones (SSAZ) of Ghana. Data were collected from 698 smallholder farmers across 25 communities using a structured questionnaire and geospatial techniques. The analysis employed cost distance analysis, factor analysis, and multinomial-ordered logistic regression. Findings indicate that the average distance travelled to access water from a dam or a river was 11 km and 9 km, respectively. Most respondents reported low to moderate water access for SAI. Key factors influencing water access included soil type, vegetation, and the distances to dams and rivers. To improve water access, it is recommended that smallholder farmers be educated on effective soil and water conservation techniques. Additionally, both government and non-governmental organizations should focus on building community-level dams to increase water availability for sustainable agricultural intensification.

In the search for promising pathways for equitable and transformative climate adaptation in low-income rural areas, the present study focuses on resilience to more variable and less predictable availability of precipitation and water resources. Equitable water governance is conceptualized as formal and informal polycentric decision-making that narrows infrastructure inequities and ensures equitable water resources allocation. Focusing on recognitional and procedural equity, vulnerable women’s and men’s community-based water tenure is starting point. Partnering with government in Zambia and with the Water Integrity Network in Kenya, field research in three communities in rural Zambia and in rural communities and a small town sharing several schemes in Kenya is conducted. These studies recognized horizontal polycentricity of community-based water tenure by identifying common features: communities’ age-old drought resilience coping strategies to meet daily domestic water needs and daily or seasonal small-scale productive water needs, by tapping water from surface- and groundwater sources through multi-purpose infrastructure, both self-financed and publicly supported, and by ‘sharing’ water ‘in’ within the community and ‘sharing out’ with neighbouring communities and powerful third parties. Procedural equity implies inclusive, locally-led planning, design and implementation in polycentric vertical governance with governments and other support agencies from local to national level and vice versa. The four interventions studied were the installation of a a solar-powered borehole for multiple uses and local government’s institutional framework for potential replication in Zambia, and post-construction support of small water systems and a planned megadam in Kenya. Further research on similar transformative approaches elsewhere is recommended.

To achieve their normative health, environmental and social objectives, water and sanitation services must be safely managed, inclusive and climate resilient. Meeting these imperatives presents a need and opportunity for innovative thinking about water and sanitation service systems. Circular economy concepts are being applied across a multitude of product and service sectors with the aim to facilitate regenerative flows of resources. Given the dependence on water resources, associated climate risks, and the generation of reusable waste products in water and sanitation service delivery, circular economy concepts can be usefully leveraged to drive sustainability outcomes. This article contributes a heuristic in the form of a conceptual framework for applying circular economy concepts in the design and delivery of water and sanitation services in diverse Global South contexts. The framework seeks to drive multiple outcomes relevant to water and sanitation initiatives: safely managed services, social inclusion, and climate resilience. Co-developed by an international research team applying a theoretical multiplicity approach and collaborative sensemaking, the heuristic takes the form of a suite of eight adapted circular economy ‘R strategies’ for water and sanitation. The R strategies were selected and articulated to reflect theory-based principles of circular economy, climate resilience and inclusion. They are intended to prompt thinking and action in pursuit of safely managed, climate resilient, inclusive water and sanitation services that align with the broader sustainability directions that circular economy narratives aspire to. The heuristic offers a conceptually rigorous, practical tool that can support collaborative, deliberative processes to realise the potential benefits of circularity in water and sanitation service systems.

This study compares the performance of satellite precipitation products (SPPs) and soil moisture-based rainfall products (SM2RPPs) in capturing rainfall patterns in Burkina Faso, West Africa. The findings indicate that SPPs outperform SM2RPPs at daily to annual timescales. The decomposition of total bias reveals that hit bias are dominant, but are larger in magnitude in SM2RPPs. Systematic errors are the major component of hit biases, suggesting they could be further treated through bias-correction. Wavelet analysis indicates that SPPs and SM2RPPs well capture seasonal and annual rainfall variability. All products struggle to accurately represent the most extreme rainfall indices, with SPPs performing better than SM2RPPs. For meteorological droughts, RFE2 and CHIRPS show the strongest correlations with observed SPI values across 1- to 12-month timescales. Although SM2RPPs perform less than SPPs in Burkina Faso, they appear mature for hydrometeorological applications and could further benefit from bias-correction to attain similar or better performance than SPPs.

This study evaluates flood susceptibility and risk on Bulk Supply Points in the Greater Accra region (GAR) using a Frequency Ratio model based on 15 flood conditioning factors. The model explores the influence of natural, meteorological and anthropogenic factors on flooding occurrences under the Shared Socioeconomic Pathway (SSP) scenarios and assesses flood risks at Bulk Supply Points (BSPs). Flood susceptibility mapping was conducted for both current and future periods under various SSP scenarios. Results reveal that elevation, slope, soil type, distance from urban areas, and SPI are the most influential factors contributing to flooding susceptibility in the region. The current flood map, about 37% of the total area of GAR categorized under the moderate flood-susceptible zone category followed by about 30% categorized under the low flood-vulnerable zone. However, about 16% was categorized under the very high flood-vulnerable zone. The study projects increasing flood susceptibility under the SSP scenarios with intensification under SSP2 and SSP3 scenarios. For instance, the areas categorized as high and very high flood susceptibility zones are projected to expand to approximately 32% and 26% each by 2055 under SSP3. The study also assesses flood risks at Bulk Supply Points (BSPs), highlighting the escalating susceptibility of power assets to flooding under different scenarios. For instance, in the very high scenario, flooding is estimated to reach 640 h in 2045 and exceed 800 h in 2055—more than double the 2020 baseline. The analysis shows the bulk supply points face increasing flood susceptibility, with risks escalating most sharply under the severe climate change SSP3 and SSP5 scenarios. Over 75% of BSPs are expected to fall in the low- to medium-risk categories across SSPs while more than 50% of BSPs are within medium- to high-risk categories in all scenarios except SSP1, reflecting the impact of climate change. SSP3 and SSP5 stand out with over 60% of BSPs facing high or very high flooding risks by 2055. It indicates moderate resilience with proper adaptation but highlights potential disruptions in critical infrastructure, such as BSPs, during persistent flooding. The findings of the study are expected to inform Ghana’s contributions towards addressing Sustainable Development Goals (SDGs) 7, 11 and 13 in Ghana.

Africa’s diverse climates and sparse hydro-meteorological networks create significant challenges in accurately estimating river discharge. Discharge data are crucial for managing water resources and predicting extremes. Our review assesses the data gap, existing methods, and technologies for river discharge estimation in Africa. Limited gauging networks on rivers, including in 63 transboundary basins, hinder accurate discharge modelling, affecting resource management and disaster response. Despite the potential of remote sensing, Geographic Information System (GIS), satellite imagery, and machine learning, their large-scale application for river discharge monitoring in Africa is limited. We propose the use of a monitoring system involving local communities in data collection and decision making, supported by global data centres, enhanced regional data sharing, and strengthened transboundary cooperation. For example, incorporating water data products, including discharge data, in data cubes, such as Digital Earth Africa, could improve monitoring. Strategic investments in hydro-meteorological instrumentation are crucial for strengthening climate resilience.

This study examines the experiences of local government councilors between 2013–2020 in four provinces of Pakistan. The study addresses three key questions: Firstly, it investigates the differences and commonalities in the local government structures across provinces and explores the potential for synchronization to enhance the implementation of Sustainable Development Goals (SDGs) at the local level. Secondly, it examines the main challenges local councilors face in effectively delivering basic services, including water, sanitation, health, education, waste management, and transport, within both rural and urban contexts. Lastly, the study analyses the necessary changes or reforms at the provincial level within the existing local government system in rural and urban areas to ensure the delivery of basic services in alignment with SDGs. The findings reveal that a powerful bureaucracy and political influence at the intermediate to upper levels of the government hierarchy exert significant control over administrative, fiscal, and political.

Global demand for sustainable agri-food products creates opportunities for smallholder farmers. But on-farm verification of sustainable practices is costly, making third-party certification inaccessible to many poor farmers. Digital technologies for tracing agri-food products from farm to fork could help: novel traceability systems, based on blockchain technology, can make data about on-farm practices transparently available to downstream stakeholders, enabling them to verify sustainability claims without external audits. There is limited understanding, however, of how such digital tracing systems fit local needs and capacities in smallholder contexts. Through a grounded theory approach, we explore the potential of digital traceability for sustainability monitoring in a case study in the Ucayali region of Peru. Based on interviews with local cocoa sector stakeholders, we identify two major challenges: first, setting up digital traceability systems requires investments that do not seem justified by corresponding increases in income. And second, relying on farmer-supplied data creates the risk of inaccurate information due to insufficient capacity as well as incentives for providing distorted data. Our findings suggest that strong cooperation along the supply chain is needed to ensure adequate return on farmer-side costs and investments. Focusing on sustainability metrics at the community level, in addition to the farm level, may be promising, as these metrics can be reliably collected by external stakeholders and add value beyond existing third-party certification standards. Our case study provides recommendations for local policy makers and supply chain stakeholders to develop inclusive digital sustainability tracing systems with smallholder farmers.

The study reviewed the applications of the water–energy–food (WEF) nexus for knowledge generation and decision-making in the Global South. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol identified 336 studies from the Web of Science and Scopus datasets. One hundred eighty-five articles applied WEF nexus tools to improve the understanding of WEF nexus interactions and to show the potential of nexus applications. The other articles (151) focused on nexus applications to guide planning and decision support for resource allocation and policy formulation. Environment, climate, ecosystems, land, and socioeconomics were other popular nexus dimensions, while waste and economy were considered to a lesser extent. Limitations associated with nexus applications included unavailability of data, uncertainties from data sources, scale mismatch and bias. The inability of nexus tools to capture the complex realities of WEF interactions is hindering adoption, especially for policy formulations and investment planning. Data limitations could be solved using a sound scientific basis to correct uncertainties and substitute unavailable data. Data gaps can be bridged by engaging stakeholders, who can provide local and indigenous knowledge. Despite the limitations, applying nexus tools could be useful in guiding resource management. Limitations associated with nexus applications included – investment planning. Plausible pathways for operationalising the WEF nexus are discussed.

Hydrological Ecosystem Services (HES) are crucial components of environmental sustainability and provide indispensable benefits. The present study identifies critical hot and cold spots areas of HES in the Aglar watershed of the Indian Himalayan Region using six HES descriptors, namely water yield (WYLD), crop yield factor (CYF), sediment yield (SYLD), base flow (LATQ), surface runoff (SURFQ), and total water retention (TWR). The analysis was conducted using weightage-based approaches under two methods: (1) evaluating six HES descriptors individually and (2) grouping them into broad ecosystem service categories. Furthermore, the study assessed pixel-level uncertainties that arose because of the distinctive methods used in the identification of hot and cold spots. The associated synergies and trade-offs among HES descriptors were examined too. From method 1, 0.26% area of the watershed was classified as cold spots and 3.18% as hot spots, whereas method 2 classified 2.42% area as cold spots and 2.36% as hot spots. Pixel-level uncertainties showed that 0.57 km2 and 6.86 km2 of the watershed were consistently under cold and hot spots, respectively, using method 1, whereas method 2 identified 2.30 km2 and 6.97 km2 as cold spots and hot spots, respectively. The spatial analysis of hot spots showed consistent patterns in certain parts of the watershed, primarily in the south to southwest region, while cold spots were mainly found on the eastern side. Upon analyzing HES descriptors within broad ecosystem service categories, hot spots were mainly in the southern part, and cold spots were scattered throughout the watershed, especially in agricultural and scrubland areas. The significant synergistic relation between LATQ and WYLD, and sediment retention and WYLD and trade-offs between SURFQ and HES descriptors like WYLD, LATQ, sediment retention, and TWR was attributed to varying factors such as land use and topography impacting the water balance components in the watershed. The findings underscore the critical need for targeted conservation efforts to maintain the ecologically sensitive regions at watershed scale.

Soil erosion poses a significant challenge in the sub-humid Ethiopian highlands, yet research on the long-term effectiveness of soil and water conservation (SWC) practices in this region using pre- and post-conservation approaches remains limited. This study addresses this knowledge gap by evaluating the impact of SWC practices on water balance and soil erosion in the Debre Mawi watershed. The study covers two-period analyses: pre-conservation (2010–2014) and post-conservation (2015–2022) using the Soil and Water Assessment Tool (SWAT) to simulate hydrological water balance. Hydrological changes were assessed with the Indicators of Hydrological Alteration (IHA) software. Spatial and weekly sediment distribution were also computed. Results showed the SWAT effectively simulated stream flow, though sediment yield estimation was less accurate. The data demonstrated a reduction in surface runoff by 18% and a decrease in sediment yield by 75%. Conversely, evapotranspiration and groundwater storage experienced increases of 13% and 34%, respectively. The decrease in runoff and sediment can be attributed to the implementation of SWC structures with infiltration furrows, which are presently filled with sediment. Moreover, the expansion of eucalyptus tree acreage may deplete soil water during dry periods, thereby prolonging the time needed for the soil to become saturated and produce runoff, but the impact has yet to be quantified. The IHA analysis confirmed a decrease in mean annual flow from 0.06 m3 /s to 0.02 m3 /s, and sediment concentration decreased from 831.2 mg/l to 285 mg/l between the pre-and post-conservation periods. The study detected that soil erosion is higher than the allowable limits recommended for Ethiopia even after implementing SWCPs. Additionally, sediment transport reduced after the first three weeks due to improved ground cover and soil stability, although significant amounts were recorded until the end of the rainy season, primarily from gullies. The study found significant hydrological alterations in flow and sediment dynamics following the implementation of SWC practices, particularly pronounced in the early years post-conservation (2015–2018). However, the effectiveness of SWC practices diminished over time, with conditions beginning to revert to pre-conservation levels after 10 years. This suggests that these techniques (infiltration furrows) may be unsuitable for sub-humid watersheds, or that they require improved design and major maintenance beyond the third year. This study offers valuable insights into the dynamics of SWC interventions, underscoring the importance of integrating agronomic practices with SWC efforts to sustain long-term soil and water conservation in Ethiopia’s sub-humid highlands. Future research should explore the hydrological effects of eucalyptus expansion and refine SWC practices suited to these unique conditions.

Contaminated vegetables grown and consumed in cities of the global South have adverse public health consequences. Through interviews with farmers, traders, consumers and institutional representatives, this article explores why stakeholders in the irrigated vegetable value chain in Accra continue unsafe practices. The multi-stakeholder data are analysed by combining a behavioural model with a framework of complex stakeholder interactions. Arguably, a systemic approach would help meet stakeholders’ opportunity, capability and motivation needs and actualise current efforts to promote safe practices. Findings indicate the need for all stakeholders to develop a shared understanding of each other’s practices and co-design flexible arrangements that better integrate their diverse rationales, knowledge and constraints. Improving hygiene and food safety from farm to fork requires political commitment that accounts for land tenure insecurity and the high cost of safe water.

A major challenge for agricultural water management (AWM) in the 21st century is to feed a growing population in the face of increasing intersectoral resource competition, evolving diets, degradation, pandemics, geopolitical conflicts and climate change. This has to be achieved within the planetary boundaries and without compromising the livelihood and environmental (ecosystem) objectives linked to water, including provisioning, supporting and regulating services. This paper uses a systems and nexus lens to unravel the centrality and complexities in AWM, with particular emphasis on the interconnected dimensions and objectives of AWM, as well as its practices and technologies. AWM exists beyond water and food with linkages to human and environmental well-being. AWM needs to catalyse transformation and integrate approaches across systems, users and scales to meet its objectives in a changing climate. It must provide perspectives beyond productivity, managing water risks and safeguarding food security – as important as these are – and integrate our understanding of the interconnected climate, land, water, food and ecosystems to address planetary health outcomes. By doing so, AWM could catalyse contextualised, equitable, innovative solutions that acknowledge local socio-economic and institutional structures and limitations while catalysing sustainable development and climate resilience.

Increased frequency and magnitude of flooding pose a significant natural hazard to urban areas worldwide. Mapping flood hazard areas are crucial for mitigating potential damage to human life and property. However, conventional hydrodynamic approaches are hindered by their extensive data requirements and computational expenses. As an alternative solution, this paper explores the use of machine learning (ML) techniques to map flood hazards based on readily available geo-environmental variables. We employed various ML classifiers, including decision tree (DT), random forest (RF), XGBoost (XGB), and k-nearest neighbor (kNN), to assess their performance in flood hazard mapping. Model evaluation was conducted using the area under the receiver operating characteristic curve (AUC) and root mean square error (RMSE). Our results demonstrated promising outcomes, with AUC values of 93% (DT), 97% (RF), 98% (XGB), and 91% (kNN) for the validation dataset. RF and XGB have slightly higher performance than DT and kNN and distance to river was the most important factor. The study highlights the potential of ML for urban flood modeling, offering reasonable accuracy and supporting early warning systems. By leveraging available geoenvironmental variables, ML techniques provide valuable insights into flood hazard mapping, aiding in effective urban planning and disaster management strategies.

Water quality is deteriorating in the worldapos;s freshwater bodies, and Lake Tana in Ethiopia is becoming unpleasant to biodiversity. The objective of this study is to retrieve non-optical water quality data, specifically total nitrogen (TN) and total phosphorus (TP) concentrations, in Lake Tana using Machine Learning (ML) techniques applied to Landsat 8 OLI imagery. The ML methods employed include Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest Regression (RF), XGBoost Regression (XGB), AdaBoost Regression (AB), and Gradient Boosting Regression (GB). The XGB algorithm provided the best result for TN retrieval, with determination coefficient (R2), mean absolute error (MARE), relative mean square error (RMSE) and Nash Sutcliff (NS) values of 0.80, 0.043, 0.52, and 0.81 mg/L, respectively. The RF algorithm was most effective for TP retrieval, with R2 of 0.73, MARE of 0.076, RMSE of 0.17 mg/L, and NS index of 0.74. These methods accurately predicted TN and TP spatial concentrations, identifying hotspots along river inlets and northeasters. The temporal patterns of TN, TP, and their ratios were also accurately represented by combining in-situ, RS and ML-based models. Our findings suggest that this approach can significantly improve the accuracy of water quality retrieval in large inland lakes and lead to the development of potential water quality digital services.

Expectations for agricultural landscapes in subtropical and tropical regions are high, aiming for conservation and development amid climate change, unfair trade, poverty, and environmental degradation. Landscape approaches (LAs) are gaining momentum as means to reconcile expectations, although they face multiple challenges, including unclear distinctions among LAs and stakeholder involvement. We studied 380 LAs from three continents via questionnaires with landscape managers (2012–2015 and 2021) and identified three LA types through cluster analysis: an ‘‘integrated’’ type with longer-term, multisectoral goals involving various stakeholders early in the design and two shorter-term types focused on sectoral priorities of preservation or production. Better-performing LAs are associated with longevity, inclusivity, and diversified investments across goals, notably those enabling social justice. International stakeholder analysis shows broad support for LAs but identifies gaps between support and LAs’ needs. The growing interest in LAs is promising. Yet, underpinning effective and lasting LAs that reconcile multiple expectations requires better support.

Gully erosion can be combatted in severely affected regions like sub-Saharan Africa using various low-cost interventions that are accessible to affected farmers. For successful implementation, however, biophysical evidence of intervention effectiveness needs to be validated against the interests and priorities of local communities. Working with farmers in a watershed in southern Ethiopia, we investigated (a) the effectiveness of low-cost gully rehabilitation measures to reduce soil loss and upward expansion of gully heads; (b) how farmers and communities view gully interventions; and (c) whether involving farmers in on-farm field trials to demonstrate gully interventions improves uptake, knowledge, and perceptions of their capacity to act. On-farm field experiments, key-informant interviews, focus group discussions, and household surveys were used to collect and analyse data. Three gully treatments were explored, all with riprap, one with grass planting, and one with grass planting and check-dam integration. Over a period of 26 months, these low-cost practices ceased measurable gully head expansion, whereas untreated gullies had a mean upward expansion of 671 cm, resulting in a calculated soil loss of 11.0 t. Farmers had a positive view of all gully rehabilitation measures explored. Ongoing rehabilitation activities and on-farm trials influenced the knowledge and understanding of similar gully treatments among survey respondents. On-farm experiments and field day demonstrations empowered farmers to act, addressing pessimism from some respondents about their capacity to do so.

Water security remains a critical global development challenge, compounded by persistent public funding shortfalls. Society urgently needs to identify opportunities for innovative private sector engagement in water security solutions. To identify feasible and impactful solutions, quantitative tools are needed to delineate complex environmental and socioeconomic water challenges and prioritize private sector investment opportunity spaces to address these challenges. We introduce the first global and regional-scale maps showing where threats to water security coincide with private sector opportunities to address them. The successful deployment of water solutions is contingent upon the societal and governance landscape that underpins a nation’s capacity to support sustainable water threat interventions and water-related business activities. By delineating areas with substantial pressures on water resources and assessing nations’ enabling environments to support private sector investments, we find nearly two-thirds of the world’s population could benefit from private sector interventions today, with middle income countries realizing the greatest benefits. In the face of global economic development and climate change, such solutions will become increasingly essential in future decades.

Comprehensive flood risk assessment is often constrained by a lack of appropriate data in high-altitude watersheds, particularly in developing countries like Nepal, where institutional capacities are limited for mapping and monitoring flood-prone communities. This study, one of the first of its kind, produced spatial multi-criteria-based flood susceptibility, vulnerability, and risk index maps for the Kathmandu Valley (KV) watershed in Nepal using an Analytical Hierarchy Process (AHP) approach and Geographical Information System (GIS). The result shows that most parts of the KV (around 80%) have moderate to low flood susceptibility around the watershed but susceptibility is prominent in southern areas. Highly flood-susceptible regions (about 14%) are found mainly along the riverbanks. Flood vulnerability, primarily influenced by population density and literacy rate, is moderate to low in most areas of the watershed (around 86%), predominantly higher in the central urban areas, and gradually lower towards the edge of the watershed. Flood risks in the major portion of the watershed (around 72%), mainly in the southern and eastern parts, are estimated as moderate to low risk, whereas higher risk zones are found in the central urban areas. The high contrast in flood vulnerability scores across the watershed has mainly contributed to the variation of flood risk zones, as flood susceptibility scores are fairly distributed over the watershed. The study findings will help policymakers develop location-specific sustainable flood risk management strategies for the flood-vulnerable communities in the KV watershed.

This study examines the barriers faced by irrigation technology and service suppliers in Ethiopia, and their influence on business effectiveness. Data were collected from 42 firm owners and managers across 21 enterprises through online surveys, phone calls, and in-person interviews in August 2020. Additional insights were provided by 35 key informants. The study utilized a qualitative analysis of survey responses by employing narrative and triangulating information gathered from several actors in the irrigation technology supply chain. The results indicate that a range of barrier categories, including difficulties linked to business enablement, technology user behavior, and business capacity, significantly impede the development and success of small-scale irrigation technology enterprises in Ethiopia. More specifically, barriers include the increasing diffusion of substandard irrigation technology products, such as water lifting devices, and a scarcity of genuine spare parts, which present major obstacles for small-scale irrigation technology suppliers in Ethiopia. Insufficient user awareness regarding the importance of maintenance and repair services has led to frequent equipment failures, eroding consumer trust and demand for irrigation technologies. Additionally, limited access to market information and financial constraints, including foreign currency shortages, further hindered suppliers’ ambitions to increase the scale of their operations. More importantly, lengthy import processes and inefficient tax exemption systems increase equipment costs, impeding the adoption and dissemination of technologies, such as solar-powered irrigation pumps. Addressing these challenges is critical for improving the supply and effectiveness of irrigation technology in Ethiopia.

In contexts where conventional environmental monitoring has historically been limited, citizen science (CS) for monitoring efforts can be an effective approach for decentralized data generation that also raises scientific literacy and environmental awareness. To that end, the United Nations Environmental Program (UNEP) is considering citizen science (CS) as a mechanism for producing ambient water quality data to track progress on Sustainable Development Goal (SDG) indicator 6.3.2: quot;proportion of bodies of water with good ambient water qualityquot;. However, the alignment of SDG 6.3.2 monitoring requirements with citizen science capacity and results in low- or middle-income countries has not been assessed. Through a systematic literature review of 49 journal publications, complemented by 15 key informant interviews, this article examines the methods and outputs of CS programs in resource-constrained settings. We explore the potential of these programs to contribute to tracking SDG 6.3.2. Using the Citizen Science Impact Assessment Framework (CSIAF), we evaluate broader outcomes of CS programs across 5 domains: society, economy, environment, governance, and science and technology. Despite large variability in scope, CS programs were consistently found to generate useful data for national-level reporting on physicochemical and ecological parameters; however, data quality is a concern for CS measurement of microbiological parameters. The focus in literature to-date is predominantly on scientific data production which falls only within the apos;science and technologyapos; outcome domain. Societal, governance, economic, and environmental outcomes are infrequently evaluated. Of the studies reviewed in this article, 75% identified some form of pollution but only 22% of them reported follow-up actions such as reporting to authorities. While CS has important potential, work is still needed towards the apos;formalizationapos; of CS, particularly if intended for more vulnerable contexts.

Gender and social dimensions of access to and use of water resources are often overlooked in policy and programming despite their importance in shaping water security. This study examines factors affecting water security in urban Pakistan through a gender lens. We surveyed 560 men and women in two towns in Islamabad and Rawalpindi facing water and sanitation challenges. Through a binary logit model and marginal effects analysis, we analyzed the relationship between water security and multiple variables, including gender, education, age, employment status, payment for water, urban wealth quintile, drinking water source, individual water concern level, water satisfaction, and water quality perception. While more than 50 percent of both genders experience water insecurity, the prevalence of water insecurity is notably higher among women. Men in the surveyed population had higher levels of employment, wealth, and education levels compared to women. The regression analysis across both genders reveals that paying for drinking water negatively and significantly impacts water security, while concern about future water issues, satisfaction with drinking water, and water quality significantly and positively impact water security levels. For women specifically, access to improved drinking water sources, higher education levels, and employment significantly improve their water security level, underscoring the importance of promoting women’s education and economic empowerment. For men, age and wealth levels emerged as significant factors impacting their water security, with older men more vulnerable to water insecurity than younger men and women. These findings underscore the complex interplay of individual, social, and structural dynamics shaping water security experiences, emphasizing the need for gender-responsive and intersectional approaches to water interventions in urban Pakistan and beyond. Equitable water policies and programs necessitate the collection of more disaggregated data. This study marks the first application of the Individual Water Insecurity Experiences (IWISE) Scale used in Pakistan’s urban context, with recommendations for its broader implementation to improve decision-making that can lead to sustainable water solutions across diverse gender and social groups.

As the world’s population increases, the growing demand for food intensifies the generation of agricultural waste, leading to several environmental issues. Intensive research indicates black soldier fly (BSF) larvae Hermetia illucens (Linnaeus, 1758) as efficient converters of organic waste into nutrient-rich biomass suitable for animal feed. Using a structured questionnaire and volunteer farmers (N = 595), we investigated the potential for adoption of BSF larvae composting technology for sustainable agricultural waste management in Greater Ahafo-Ano. Almost all surveyed farmers declared they generated a significant amount of biowaste on their farms and were willing to learn how to use the BSF-based technology to transform it into value-added products. The waste generated was mainly disposed of in pits at Ahafo-Ano South-East (56.2%), by composting at AhafoAno South-West (34.9%) and by sale at Ahafo-Ano North (34.4%). Across the three districts, awareness of the BSF was very low – 14.5% in Ahafo-Ano South-East, 14.1% in Ahafo-Ano South-West and 0.5% in Ahafo-Ano North. However, high acceptance of the technology was recorded. It was found that about 8% of farmers surveyed in Ahafo-Ano South-East had already tried BSF farming on a small scale. Indicating this district as a good entry point to introduce the technology into Greater Ahafo-Ano.

5-Hydroxymethylfurfural (5-HMF) holds substantial importance as a foundational chemical that can be potentially transformed into biofuels and various additional high-value products. Fructose is gaining popularity as one of the raw materials for the facile formation of 5-HMF. However, it is not as abundant in nature as glucose, the primary product derived from biomass breakdown and the most abundant monosaccharide globally. Producing fructose through glucose isomerization is an economical approach in this context. This study investigates several types of novel, facile, and reusable hydrogel catalysts for the isomerization of glucose into fructose and dehydration of fructose into 5-HMF in green solvent media. This study marks the first application of both amine and amide functional groups within a single catalyst (PEGDA-DMAPMA) for glucose isomerization. The results of glucose isomerization using Brnsted-base PEGDA-DMAPMA hydrogel catalysts reveal a 45% glucose conversion rate and a 27% fructose yield, with a 61% selectivity at 110 C, within a 2 h reaction time. Brnsted-acid PEGDA-3SMP-H gave a fructose conversion rate of 93%, yielding 65% 5-HMF at 120 C after 6 h. A significant observation was made for PEGDA-3SMP-H, indicating an increase in the catalytic ability with regeneration cycles. The synthesized catalysts PEGDA-DMAPMA and PEGDA-3SMP-H exhibited stability up to 120 C despite an increase in swelling ratio at higher temperatures and times. Furthermore, PEGDA-3SMP-Cu2+ demonstrated a considerable yield of fructose compared to other metal ion-modified Brnsted-acid catalysts. Additionally, an efficient heating method for this process was identified. In conclusion, the prepared hydrogel catalysts are preferred for industrial applications in carbohydrate conversion.

Adoption of improved seed varieties (ISV) is considered one of the key ingredients to sustainably increase crop yields and incomes and reducing hunger. Previous research has extensively demonstrated that there is a positive link between adoption of ISV and several agricultural and health outcomes. However, most prior research focused on a single crop only, particularly maize, yet most smallholder farmers grow multiple crops simultaneously. Additionally, most of the existing studies are largely case studies using cross-sectional data, where controlling for possible unobserved confounding factors is difficult. We attempt to address these caveats by testing the hypothesis that adoption of ISV improves crop productivity and income, dietary diversity, and short-term child nutrition outcomes. To do so, we use a decade (2010–2020) of nationally representative panel data from Malawi. Our panel data regression results show that adoption of ISV is positively correlated with value of crop production, dietary diversity, and weight for age z-scores. Our findings suggest that intensifying development and promoting use of nutrition-sensitive ISV among smallholder farming households could be key to sustainably address food insecurity and child malnutrition.

Advancing food security requires multi-level and inclusive approaches. This article presents a novel framework to (E) evaluate the social inclusiveness of policies and interventions (PIs) towards (V) vulnerable social groups in (A) agricultural value chains. The EVA-framework is applicable to any value chain, geography and vulnerable group. We apply it to the irrigated vegetable value chain of Mali, analyzing the social inclusiveness of weighted PIs towards women and youth. We find that respective PI formulation in Mali is largely not inclusive. Only few PIs set specific targets, quotas or a financial budget for women and youth inclusion. To be inclusive PIs need to consult targeted social groups, include clear targets, budgets, and accountability mechanisms, and be monitored and evaluated.

The water–energy–food–ecosystems (WEFE) provide vital resources that are essential to human existence. Exploring synergies and trade-offs in these systems has been of interest in recent years to increase economic gain while sustaining the environment. The Tana-Beles Sub-basin of Ethiopia is challenged by population density, climate change, and ecosystem degradation that requires a WEFE Nexus thinking. To understand the current WEFE nexus interactions in the basin, a systematic review of 102 scientific research articles published from 1991 to 2021 was undertaken. Additionally, the systematic review is complemented by spatial data analysis to identify synergies and trade-offs among the WEFE nexus indicators. The analysis revealed the dominance of food–water–ecosystem interdependencies in WEFE nexus research for the Tana-Beles Sub-basin. This dominance is driven by extensive food production activities, which lead to substantial water abstraction and hydrological alterations to meet the intensive water demands of crop cultivation. Simultaneously, the energy-ecosystem interactions are critical due to excessive biomass utilization that exceeds the biomass production potential of the area. Furthermore, the available vegetation cover of the area is very limited to supplement the growing fuel wood demands, which is exerting extreme land degradation and threatening the ecosystem in the sub-basin. This study identifies gaps in WEFE understanding, highlights specific challenges and opportunities within the basin, and calls for coordinated stakeholder action for sustainable resource management through a Nexus approach.

Study region: The Shashe catchment, Limpopo River Basin, Botswana, and Zimbabwe. Study focus: The Shashe catchment is the third largest flow contributor to the Limpopo River Basin. Water availability in the Shashe catchment is highly seasonal due to high seasonal rainfall variability. The seasonality and inter-annual variability cause shortfalls (demand exceeds the average water availability) in certain months and years. Storage is needed to bridge the seasonal water availability “gap” and mitigate the deficits in drought years, i.e., inter-annual variability. While the need for water storage through grey infrastructure such as dams has long been known, there is growing recognition of the need for approaches to water storage that capitalize on all storage types. However, the current capacity to plan in ways that utilize all storage types is limited. The analyses conducted for this paper assessed the volume and spatial and temporal variability of different storage options – large and small dams, sand dams, soil moisture, and aquifers – in the Shashe catchment of the Limpopo River Basin. An integrated SWAT-MODFLOW model and remote sensing approach were developed for 2015–2020. New hydrological insights for the region: The total annual water storage in the Shashe catchment is approximately 44,000 Mm3 , dominated by groundwater. The annual storage is about 42,000 Mm3 in aquifers, 1500 Mm3 in soil, 700 Mm3 in large dam reservoirs, 45 Mm3 in small dams/ponds, and 0.13 Mm3 in sand dams. There is high seasonality in water storage availability. Soil moisture storage is at its maximum from January to March and lowest from July to September. Dam storage is at its maximum from March to May, and the water storage is relatively stable throughout the year. Aquifer storage is relatively stable during the dry seasons compared to other storage options. Optimizing water use considering the seasonal variation in different storage types could improve water availability and climate resilience.

Vendors in traditional urban food markets in West Africa offer locally produced vegetables. These may be unsafe, carrying pathogens and posing potential risks to consumers’ health; or safe, being free from pathogens. Safe produce is rarely differentiated from unsafe produce through certification or price differentiation. Consequently, there is no market data on consumers’ actual payments for certified safe vegetables. Therefore, we aimed to find out whether there is a demand for certified safe vegetables and whether such safety certification is profitable for small-scale farmers. Previous studies have used experiments to elicit price premia consumers’ state to be willing to pay. In contrast, we offered pathogen-free cabbage certified as safe on traditional food markets in Tamale, Ghana, and observed what consumers actually paid. We noted consumer’s actual purchases, who – at the same market stalls – chose between ordinary cabbage of unknown safety status and certified safe cabbage, which carried a price premium to be paid in addition to the price of ordinary cabbage. Our results show that 176 consumers purchased certified safe cabbage and 123 bought ordinary cabbage during the test sales. Consumers’ probability to buy certified safe cabbage is explained by the size of the price premium charged, households’ characteristics and perceptions of local production modes. Estimating customers’ demand function for certified safe cabbage revealed that a pioneer farmer should charge a monopolistic price premium of GHS 1.48 (+46 % on top of the average price for ordinary cabbage valid during the test sales) to maximise the profits from introducing certified safe cabbage into the market. We find that the most promising certification option is for groups of geographically concentrated farmers to jointly apply for safe vegetable certification.

Simulation models are useful decision-support tools for designing and analyzing subsurface drainage systems in irrigated lands. However, the challenge is determining the soil hydraulic data inputs required by models to achieve reliable and accurate simulation of water table depths (WTDs) and drainage discharges (DDs) at various drain depths and spacing combinations. This is particularly important for data-scarce areas, such as middle- and low-income countries (MLICs), that lack facilities to determine in-situ soil hydraulic properties. We evaluated the performance of WaSim and DRAINMOD models to simulate WTDs and DDs at a field scale in KwaZulu-Natal, South Africa. Saturated hydraulic conductivity (Ksat) and soil water retention ( (h)) values were determined using the in-situ pumping test and a pressure plate apparatus. Pedotransfer functions (PTFs) in the Rosetta computer program also estimated these soil parameters. The DRAINMOD and WaSim models were calibrated using the in-situ measured Ksat and laboratory-measured (h) data, while the validation exercise used the PTFs-estimated Ksat and (h) data as soil hydraulic inputs. The models’ performance in simulating WTDs and DDs was assessed using Nash-Sutcliffe Model Efficiency (NSE), Modified Index of Agreement (d), Coefficient of Determination (R2 ), and Mean Absolute Error (MAE). During validation, DRAINMOD simulated WTDs with NSE, d, R2 , and MAE of 0.86, 0.81, 0.89, and 5.3 cm, respectively, whereas, for DDs, the model registered NSE, d, R2 , and MPE of 0.81, 0.79, 0.83, and 0.17 mm.day-1, respectively. During the validation period, the WaSim model simulated WTDs with NSE, d, R2 , and MAE of 0.76, 0.74, 0.78, and 9.0 cm, respectively. For the same validation period, the WaSim model simulated DDs with NSE, d, R2 , and MAE of 0.74, 0.73, 0.77, and 0.2 mm.day-1, respectively. The results suggest that both models, with either in-situ measured and laboratory-measured soil data or PTFs-estimated soil data, can be used to design and analyze drainage systems in data-scarce environments with a reasonably high confidence level. Designers of subsurface drainage systems in Pongola, South Africa, can use any of the two drainage models as decision support tools. We recommend using DRAINMOD and WaSim models with PTFs-estimated hydraulic soil data based on soil textural information, soil particle size data, bulk density, and (h) data at field capacity and permanent wilting point.

In this paper we study the case of contract farming for exports with farmers in remote hilly areas of Nepal. The prospect for contract farming in such areas with accessibility issues owing to underdeveloped markets and lack of amenities is ambiguous. On the one hand, contractors find it difficult to build links in these cases particularly when final consumers have quality and safety requirements. On the other hand however, remoteness makes the contracts more sustainable. The latter happens if there are product specific quality advantages because of agro-ecology and more importantly due to lack of side selling opportunities. At the same time concerns remain about monopsonistic powers of the buyers when remotely located small farmers do not have outside options. This study hence quantifies the benefits of contract farming on remotely located farmers’ income and compliance with food safety measures. Results show that contract farming is significantly more profitable (58% greater net income) than independent production, the main pathway being higher price realization along with training on practices and provision of quality seeds.

At a rhetorical level, the SDGs provide a unified global agenda, and their targets and indicators are believed to drive action for social and environmental transformation. However, what if the SDGs (and their specific goals and indicators) are more of a problem than a solution? What if they create the illusion of action through a depoliticised and technical approach that fails to address fundamental dilemmas of politics and power? What if this illusion continues to reproduce poverty, inequality, and environmental degradation? This paper addresses these questions through a focus on SDG 6.5.1 – the implementation of integrated water resources management (IWRM), measured on a 0-100 scale through a composite indicator. The paper presents an empirical analysis of SDG 6.5.1 reporting in Colombia, Ethiopia, India, Malaysia, and the UK, drawing on research from the Water Security and Sustainable Development Hub.1 An evidence review and series of expert interviews are used to interrogate the local politics of IWRM measurement, specifically three dilemmas of global composite indicator construction: (1) reductive quantification of normative and contested processes; (2) weak analysis of actually existing institutional capability, politics, and power; and (3) distracting performativity dynamics in reporting. The paper concludes that SDG 6.5.1 is an example of a apos;fantasy artefactapos;, and that in all countries in this study, IWRM institutions are failing to address fundamental and apos;wickedapos; problems in water resources management. We find little evidence that these numbers, or the survey that gives rise to them, drive meaningful reflection on the aims or outcomes of IWRM. Instead, they tend to hide the actually-existing political and institutional dynamics that sit behind the complexity of the global water crisis.

Climate change significantly challenges the sustainability of forest ecosystems, with broad socio-ecological impacts insufficiently assessed. This study examines one such critical system, the Globally Important Agricultural Heritage Systems (GIAHS), focusing on preserving the Argan tree in the Ait Souab-Ait Mansour region of southern Morocco. The region, including the Massa and Tamanart river basins, is crucial for Argan tree conservation, yet there is limited information on how climate change will affect the tree. This study aims to analyze climate variability trends and potential impacts on Argan tree distribution using observed (1983–2022) and projected rainfall and temperature data up to 2080. The MaxEnt model projected Argan tree distribution for 2041–2060 and 2061–2080 under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). Findings reveal significant climatic disparities, with warming of 0.4 C between 1983 and 2022 and future temperatures reaching up to 4 C between 2041 and 2080. Rainfall shows considerable variability, with a decrease of approximately 2.5 mm per decade during the rainy season. Projections indicate a decline in annual precipitation, impacting seasonality and increasing the frequency of extreme events during the argan fruit production season. Suitable areas for Argan trees are expected to decline, particularly in the Tamanart and Massa River basins. The study highlights a 47–65% reduction in highly adapted zones in the med term (2041–2060), and 49–81% in the long term (2061–2080), emphasizing the need for proactive adaptation measures in effort to conserve and increase Argan tree’s survival and productivity.

Climate change leading to Climate extremes in the twenty-first century is more evident in megacities across the world, especially in West Africa. The Greater Accra region is one of the most populated regions in West Africa. As a result, the region has become more susceptible to climate extremes such as floods, heatwaves, and droughts. The study employed the Coupled Model Intercomparison Project 6 models in simulating climate extreme indices under the Shared Socioeconomic Pathway scenarios (SSPs) over West Africa between 1979 and 2059 as exemplified by the Greater Accra region. The study observed a generally weak drought in the historical period and expected to intensify especially under SSP585 in Greater Accra. For instance, continuous dry days (CDD) reveal an increasing trend under the SSPs. Similarly, the overall projected trend of CDD over West Africa reveals an increase signifying a more frequent and longer drought in the future. The flood indices revealed a surge in the intensity and duration of extreme precipitation events under the SSPs in the region. For instance, R99pTOT and Rx5days are expected to significantly increase under the SSPs with intensification under the SSP245, SSP370, and SSP585. A similar trend has been projected across West Africa, especially along the Guinean coast. The study foresees a gradual and intensifying rise in heatwave indices over the Greater Accra region. The warming and cooling indices reveal an increasing and decreasing trend respectively in the historical period as well as under the SSPs particularly within urban centers like Accra and Tema. Most West African countries are projected to observe more frequent warm days and nights with cold nights and days becoming less frequent. Expected effects of future climate extreme indices pose potential threats to the water, food, and energy systems as well as trigger recurrent floods and droughts over Greater Accra. The findings of the study are expected to inform climate policies and the nationally determined contribution of the Paris Agreement as well as address the sustainable development goal 11 (Sustainable cities) and 13 (Climate action) in West Africa.

The reliance on rainfed agriculture exposes southern Africa to low agricultural productivity and food and nutritional insecurity; yet, the region is endowed with vast irrigation potential. Extreme weather events including drought, floods, and heatwaves exacerbate the existing challenges, underscoring the need to improve agricultural water management as a climate change adaptation strategy. This mixed-methods review followed the Search, Appraisal, Synthesis, and Analysis (SALSA) framework to explore the irrigation opportunities and challenges in southern Africa by critically analysing the drivers and constraints of irrigation systems in southern Africa. The premise is to understand the reasons behind the abandonment of some of the areas equipped for irrigation. In cases where irrigation systems are present, the study assesses whether such technologies are effectively being used to generate the expected agricultural productivity gains, and what factors, in cases where that is not the case, constrain farmers from fully using the existing infrastructure. The review further discusses the enabling environment supporting irrigated agriculture and the role of gender in irrigation development. An assessment of the role of women in agriculture on the share of land equipped for irrigation to total cultivated land area, as well as on the proportion of the area equipped for irrigation versus the area that is actually irrigated is conducted. The review found a divergence between countries’ land areas equipped for irrigation and actually irrigated areas. Specific to irrigation expansion, the review rebuts the notion that increasing the irrigated area increases crop production and ensures food security. This may not always be true as irrigation development needs to consider the impacts on other closely linked water and energy sectors through transformative approaches like the water–energy–food (WEF) nexus and scenario planning. If well-planned and implemented, sustainable irrigated agriculture could be catalytic to transforming southern Africa’s food system to be inclusive, equitable, socially just, and resilient, benefiting people and the planet.

Years after the initial settlement, food aid remains an essential component of humanitarian assistance for protracted refugees in managed camps. From data collected among refugee households in three camps in southern Chad and an exogenous variation of time between the latest food distribution and households’ interviews, we draw the time path of household’s consumption. Consistent with the literature on intertemporal choices in high-income countries, refugee households experience an average decline of 1.1 to 1.5 percent per day in their daily caloric intake between distributions. The short-term nutritional status of children under five also responds to the distance from food aid distribution and confirms the existence of food distribution cycles. Our results suggest that households don’t smooth consumption during the interval of time between two distributions, and face regular and frequent cycles of food shortage resulting in detrimental consequences on children’s health.

The sediment transport, involving the movement of the bedload and suspended sediment in the basins, is a critical environmental concern that worsens water scarcity and leads to degradation of land and its ecosystems. Machine learning (ML) algorithms have emerged as powerful tools for predicting sediment yield. However, their use by decision-makers can be attributed to concerns regarding their consistency with the involved physical processes. In light of this issue, this study aims to develop a physics-informed ML approach for predicting sediment yield. To achieve this objective, Gaussian, Center, Regular, and Direct Copulas were employed to generate virtual combinations of physical of the sub-basins and hydrological datasets. These datasets were then utilized to train deep neural network (DNN), conventional neural network (CNN), Extra Tree, and XGBoost (XGB) models. The performance of these models was compared with the modified universal soil loss equation (MUSLE), which serves as a process-based model. The results demonstrated that the ML models outperformed the MUSLE model, exhibiting improvements in Nash–Sutcliffe efficiency (NSE) of approximately 10%, 18%, 32%, and 41% for the DNN, CNN, Extra Tree, and XGB models, respectively. Furthermore, through Sobol sensitivity and Shapley additive explanation–based interpretability analyses, it was revealed that the Extra Tree model displayed greater consistency with the physical processes underlying sediment transport as modeled by MUSLE. The proposed framework provides new insights into enhancing the accuracy and applicability of ML models in forecasting sediment yield while maintaining consistency with natural processes. Consequently, it can prove valuable in simulating process-related strategies aimed at mitigating sediment transport at watershed scales, such as the implementation of best management practices.

In recent years, use of solar-powered irrigation pumps (SIPs) has increased significantly in the agricultural plains (terai) of Nepal. Federal and local governments there have subsidized the pumps in an effort to expand irrigated agriculture using renewable energy. We use data from a cross-sectional survey of 656 farming households in the terai to examine how SIPs affect fossil fuel use and groundwater extraction. We find that most SIP users continued to use their fossil-fuel pumps, as very few completely replaced them with solar pumps. Farmers who received SIPs operated their irrigation pumps more hours than those who did not receive SIPs. Taken together, these findings suggest that groundwater use has increased, as SIP recipients ‘stack’ their pumps. We also find that solar pumps were more likely to be owned by richer households and those with better social networks than those who were poorer and had relative social disadvantage. As Nepal expands the use of solar pumps in agriculture, policy efforts may benefit from managing expectations about the carbon-mitigation potential of this technology, managing groundwater risks as SIP use expands, and making SIPs more inclusive.

Purpose and Methods: Crop identification using remotely sensed imagery provides useful information to make management decisions about land use and crop health. This research used phonecams to acquire the Normalized Difference Vegetation Index (NDVI) of various crops for three crop seasons. NDVI time series from Sentinel (L121-L192) images was also acquired using Google Earth Engine (GEE) for the same period. The resolution of satellite data is low therefore gap filling and smoothening filters were applied to the time series data. The comparison of data from satellite images and phenocam provides useful insight into crop phenology. The results show that NDVI is generally underestimated when compared to phenocam data. The Savitzky-Golay (SG) and some other gap filling and smoothening methods are applied to NDVI time series based on satellite images. The smoothened NDVI curves are statistically compared with daily NDVI series based on phenocam images as a reference.; Results: The SG method has performed better than other methods like moving average. Furthermore, polynomial order has been found to be the most sensitive parameter in applying SG filter in GEE. Sentinel (L121-L192) image was used to identify wheat during the year 2022–2023 in Sargodha district where experimental fields were located. The Random Forest Machine Leaning algorithm was used in GEE as a classifier.; Conclusion: The classification accuracy has been found 97% using this algorithm which suggests its usefulness in applying to other areas with similar agro-climatic characteristics.

Affordable and reliable energy is an important driver for improving access to irrigation in South Asia. Policies for improving electricity access and augmenting supply are likely to impact affordability and equity in irrigation access, especially in regions where agriculture is the mainstay of the economy. In this paper, we focus on the state of Bihar in eastern India to study trade-offs across economic, equity, and political dimensions of energy transition in irrigation. We argue that in the context of the nascent but steadily increasing solar-powered irrigation, a decentralised energy regime is techno-economically and socio-politically distinct from a conventional centralised grid supply. With different economic costs, governance issues, and varied incentives of stakeholders, there are significant trade-offs associated with the two pathways of energisation. We further assess the multidimensional trade-offs associated with the conventional ‘centralised’ and the modern ‘decentralised’ energy supply systems for irrigation to present a comprehensive understanding of the technical systems aiming to address economic development and livelihood security issues. We find that the life cycle costs (LCC) of centralised grid supply are not only higher than that of decentralised solar-powered irrigation (SIP) but also the LCC for grid supply has a high sensitivity to average cost to supply electricity (ACS). We also find that at lower pumping hours or lower average cost to supply (ACS), grid electricity is competitive compared to SIP, but with an increase in pumping hours, ACS or both, there is a considerable increase in the LCC of the grid connected pump, making SIP a more economical option. Furthermore, we augment the analysis using primary data on farmers to examine the economic, equity, and political trade-offs. By highlighting the complexities associated with the diffusion of decentralised energy solutions in irrigation, our findings provide useful insights for public policy related to energy transition in irrigation in India.

In low- and middle-income countries, inadequate sanitation results in faecal contamination of the water used by urban farmers for irrigation. Consumers of raw contaminated vegetables run the risk of developing diarrhoeal diseases and helminth infections, which are a leading cause of under-five mortality and impact the well-being and productivity of millions of adults. This review identifies the evidence base for assessing which factors determine the success and/or failure of interventions that aim to manage the risk of faecal contamination in the urban irrigated vegetable value chain. We carried out a systematic search of the literature from the perspective of the COM-B behaviour framework (Capability þ Opportunity þ Motivation ¼ Behaviour). Our results reveal that most interventions address stakeholders’ opportunity or capability to adopt safe practices without adequately considering their motivation. Interventions often focus on one sector rather than on the whole value chain (sanitation, agriculture, trade, consumption). To effectively change hygiene and food safety practices in the urban irrigated vegetable value chain, stakeholders’ intrinsic motivations need to be identified. Where WHO’s multi-barrier approach is the best option, we recommend building on local multistakeholder platforms and adopting a behaviour change framework to support the largely technical change from farm to fork.

Unsafe water reuse in the informal irrigation sector dominates in the Global South and requires more attention to protect food safety and public health. Promoting formal wastewater use in conjunction with (usually constrained) investment in treatment capacities is not sufficient in LMIC. New approaches and indicators are needed across the formal and informal reuse sectors to increase food safety and monitor progress on safe reuse. Current reuse guidelines need to be updated with greater attention to policy, regulations, investments, and behavior change for a higher implementation potential.

The Intergovernmental Panel on Climate Change (IPCC) has been producing influential reports for over 35 years. As the IPCC’s Seventh Assessment Report (AR7) cycle begins, we offer our perspective as former members of the IPCC Technical Support Units from Working Groups I, II amp; III, and the Synthesis Report on lessons learned during the Sixth Assessment Report (AR6) cycle. We identify three broad issues that, if addressed, could reinforce and sustain the IPCC in continuing its mission to comprehensively assess the scientific understanding of human-induced climate change. These are the imperative to ensure balanced representation, the importance of author recognition, and the need for improved institutional memory. Our recommendations include addressing skill and training needs, tackling barriers to participation particularly for Global South authors, and ensuring all contributors receive appropriate recognition for their efforts. We focus, in particular, on feasible incremental changes that could be implemented during AR7 without major changes to the underlying procedures that require approval by the 195 member governments that make up the IPCC.

Precise estimation of irrigated areas is essential for effective water management, increased production, environmental conservation, and conflict resolution. Nonetheless, discrepancies frequently exist between estimated and actual irrigated areas. To address the data gaps in actual irrigation areas within Ethiopia, we utilized high-resolution remote sensing imagery. However, the accuracy of these images under varying climatic and landscape conditions was not fully substantiated. We conducted a comparative analysis between global irrigation map and local irrigated region maps within two distinct watersheds. Field data was gathered to both train and assess by employing random forest supervised classification algorithm. This algorithm was then applied to create accurate irrigation maps using high-resolution Sentinel-1 data for the Bilate and Gumara watersheds. During the irrigation seasons, maps of irrigated regions were produced using time-series imagery. Additionally, we employed maps indicating lands suitable for surface irrigation and applied post-processing techniques to refine the actual irrigated areas. The resulting accuracy was comparably high for both watersheds, with values of 88% and 87%. The kappa coefficients were 0.74 and 0.73, respectively, indicating a very good level of agreement. However, there were significant discrepancies between the global irrigation map and the local irrigated regions map in terms of spatial distribution and the extent of irrigation. This discrepancy necessitates further analysis of both products to decipher the underlying causes of their differences. We recommend for additional studies encompassing diverse watershed characteristics to improve irrigation area mapping via remote sensing. Our findings also validate the effectiveness of post-processing techniques in remote sensing applications.

This study provides a critical assessment of future climate scenarios in the White Volta Basin (WVB), an area heavily reliant on groundwater resources. With monthly model results for two Shared Socioeconomic Pathway Scenarios (SSP2-4.5 and 5–8.5), seven (7) Coupled Model Intercomparison Project Phase 6 (CMIP6) models with spatial resolution ranging from 1.125 × 2.8 were assessed. The study also considered, three 30-year time intervals, 1971–2013 for the Baseline (historical) climate, the 2020s (2020–2040) 2050s (2041–2070), and the 2080s (2071–2075) for the future climate scenarios. The Climate Change for Watershed Modeling (CMhyd) software was used for bias correction of these models, with observational data sourced from the National Centers for Environmental Prediction’s Climate Forecast System Reanalysis (NCEP CFSR) and 12 gridded climate stations. The bias-corrected models validated using R2 , NSE, RMSE, PBIAS, and additional metrics, demonstrated good calibration results compared to observed data. Precipitation ensembles showed 97–99% R2, 94–99% NSE, 70–485 mm RMSE, and -9-5% PBIAS. Maximum and minimum bias corrected temperatures performance varied from 95 to 99% R2, 92–99% NSE, 0.01–0.07 RMSE, and 0.01–0.23 PBIAS, Overall, precipitation levels are expected to decline for SSP2-4.5, while under SSP5-8.5 are expected to increase until the 2080s across all scenarios in comparison to the baseline period. Maximum temperature will be considerably high under SSP5-8.5, with an estimated increase of around 4.3 C/year in comparison to the reference period. The monthly average variation in the maximum temperature ranges from 0.62 to 2.43 0 Cunder the SSP5-8.5 scenario. These findings reveal the potential impacts of climate change on agricultural productivity, groundwater recharge, and crucial information for the development of Ghana’s National Determined Contributions (NDCs) and National Adaptation Plans (NAPs). Thus, emphasizing the need for comprehensive adaptation strategies to mitigate the climate change impact on water resources and ecosystem services.

Flooding, exacerbated by the challenges of climate change, poses a growing threat to communities in the Upper West Region (UWR) of Ghana. This persistent issue, particularly during the rainy seasons has subjected the region to several losses of properties and lives over the years. This has spurred the need for a comprehensive delineation of flood risk terrains (FRTs) and analysis of the rainfall patterns in the region. This study, therefore, started by analysing a digital elevation model (SRTM—DEM) using Jenks Natural Breaks Classification (JNBC) algorithm to delineate potential FRTs map within the region. Further, analysis was performed using Analytical Hierarchy Process Multi-Criteria Decision (AHP-MCD) with the incorporation of six spatial factors (Lineament Density, Elevation, Topographic Wetness Index, Drainage Density, Slope, and Aspect) to generate a comprehensive FRTs map. Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) from 1992 to 2022 were also visualized in a Jupyter Notebook to assess rainfall patterns in the UWR. Historical flood events data were also analysed to understand the trends of flood events impacts. From the findings, both the JNBC and AHP-MCD algorithms categorized the UWR’s total area into five classes, namely; very high, high, moderate, low, and very low FRTs. The JNBC map had area coverages of 4% (856.278 km2), 7% (1466.685 km2), 12% (2418.642 km2), 35% (7014.96 km2), and 42% (8351.496 km2) from very high risk to very low FRTs, respectively. Notably, the very high risk terrains and high risk terrains were predominantly located along the southeastern and eastern regions, particularly along the Kulpawn River and Sisili River in the UWR. The five classes AHP-MCD map also recorded areas as 0.004% (0.707 km2), 21% (3830.02 km2), 69% (12807.31 km2), 10% (1827.011 km2), and 0.062% (11.535 km2) very high risk to very low FRTs, respectively. These findings further revealed a prevalence of high FRTs along stream and river networks. Interestingly, the validation of the AHP-MCD map over the ground truthing points indicated that the UWR is dominated by moderate FRTs (71.76%), underscoring the regionapos;s vulnerability to flooding. The visualization of the spatial rainfall distribution from 1992 to 2022, also highlighted the significance of heavy rainfall years, particularly in 2018, 2019, and 2021, and the month of August as consistent predictors of flood occurrences. A correlation matrix reinforces the strong connection between rainfall and flood-related impacts, such as affected populations, economic costs, and agricultural losses from 2016 to 2021. In light of these findings, UWR residents must prioritize flood-resilient crop cultivation and adhere to flood disaster safety protocols, especially during the critical month of August. These insights hold valuable implications for municipal, district, and community planning policies, offering a foundation for proactive sustainable flood risk mitigation and co

Climate change effects are expected to be profoundly local and region-specific, underlining the urgent need for local-level assessments. This study emphasizes the agriculturally important Zanzan region of northeastern Cte dapos;Ivoire and examines future changes in precipitation, temperature, and resultant drought conditions based on six global climate models (GCMs) from the Coupled Model Intercomparison Project 6 (CMIP6) under shared socioeconomic pathways (SSPs) scenarios - SSP2-4.5 and SSP5-8.5. We integrate data from 12 stations within the Zanzan region, applying CMhyd software to correct model biases. Key statistical metrics confirm the well-calibrated nature of the corrected GCMs vis-a-vis observed data. Projections show a decrease in annual precipitation by an average of 133 mm and 177 mm under SSP2-4.5 and SSP5-8.5 scenarios respectively by 2100. Future precipitation patterns suggest a shift towards the prevalent dry season. Tmax and Tmin are projected to increase by þ3 C and þ4.8 C (SSP2-4.5 and SSP5-8.5) and þ3.3 C (both scenarios) respectively, by the end of the century. These changes suggest an intensification of severe droughts, particularly in the 2050s and 2080s, as assessed by the SPEI. Additionally, extreme temperatures (TX90p) and consecutive dry days (CDD) are projected to intensify, posing imminent threats to food security, water resources, and public health in the Zanzan region. This study bridges a critical gap by offering localized insights into future climate scenarios, thereby enhancing our understanding of the region-specific impacts of climate change. The research also underscores the urgency of adaptation and mitigation strategies tailored to the Zanzan region’s vulnerabilities.