Evidence of waste management impacting severe diarrhea prevalence more than WASH: An exhaustive analysis with Brazilian municipal-level data.

Adequate housing protects from diarrhea, which is a substantial health concern in low- and middle-income countries. The purpose of this study was to quantify the relationship between severe diarrhea and housing features at the municipal level to help in public health planning. Regression analyses were performed on annual (2000-2012) datasets on Brazilian municipalities (5570) in six household feature categories (e.g., waste management) and four severe diarrhea outcomes (e.g., diarrhea deaths of under-5 children). Household data were not available elsewhere of this magnitude and granularity, highlighting the scientific value-add of this study. Municipalities were clustered prior to regression analysis because of data heterogeneity. The compositional household feature data were also subjected to principal component analysis to diminish feature variable multicollinearity. The highest explanatory power was found for diarrhea deaths of under-5 children (R2 = 10-22 %), while those in the over-5 population were the least best explained (R2 = 0.3-7 %). Household features predicted diarrhea outcomes more accurately in the "advanced" housing municipality cluster (R2 = 16-22 %) than in the "mid-level" (R2 = 7-20 %) and "basic" (R2 = 6-12 %) ones (over-5 diarrhea deaths excluded). Under-5 children's diarrhea death prevalence was three times higher in the "basic" cluster than in the "advanced" cluster. Importantly, the impact of waste management was overall the largest of all household features, even larger than those of WASH, i.e., water supply, sanitation, and household drinking water treatment. This is surprising in the context of existing literature because WASH is generally regarded as the most important household factor affecting gastrointestinal health. In conclusion, public health interventions could benefit from customizing interventions for diarrhea outcomes, municipality types, and household features. Waste management's identified stronger association with diarrhea compared to WASH may have important implications beyond the water field and Brazil.

World's human migration patterns in 2000-2019 unveiled by high-resolution data.

Despite being a topical issue in public debate and on the political agenda for many countries, a global-scale, high-resolution quantification of migration and its major drivers for the recent decades remained missing. We created a global dataset of annual net migration between 2000 and 2019 (~10 km grid, covering the areas of 216 countries or sovereign states), based on reported and downscaled subnational birth (2,555 administrative units) and death (2,067 administrative units) rates. We show that, globally, around 50% of the world's urban population lived in areas where migration accelerated urban population growth, while a third of the global population lived in provinces where rural areas experienced positive net migration. Finally, we show that, globally, socioeconomic factors are more strongly associated with migration patterns than climatic factors. While our method is dependent on census data, incurring notable uncertainties in regions where census data coverage or quality is low, we were able to capture migration patterns not only between but also within countries, as well as by socioeconomic and geophysical zonings. Our results highlight the importance of subnational analysis of migration-a necessity for policy design, international cooperation and shared responsibility for managing internal and international migration.

Increased probability of hot and dry weather extremes during the growing season threatens global crop yields.

Although extreme weather events recur periodically everywhere, the impacts of their simultaneous occurrence on crop yields are globally unknown. In this study, we estimate the impacts of combined hot and dry extremes as well as cold and wet extremes on maize, rice, soybean, and wheat yields using gridded weather data and reported crop yield data at the global scale for 1980-2009. Our results show that co-occurring extremely hot and dry events have globally consistent negative effects on the yields of all inspected crop types. Extremely cold and wet conditions were observed to reduce crop yields globally too, although to a lesser extent and the impacts being more uncertain and inconsistent. Critically, we found that over the study period, the probability of co-occurring extreme hot and dry events during the growing season increased across all inspected crop types; wheat showing the largest, up to a six-fold, increase. Hence, our study highlights the potentially detrimental impacts that increasing climate variability can have on global food production.

Local and non-local drivers of consumption-based water use in China during 2007-2015: Perspective of metacoupling.

Increasingly growing consumption-based water use (WU) combined with climate change have exacerbated water stress globally and regionally, yet little is known about how the WU change is affected by metacoupled processes which involve human-nature interactions across space; within and across adjacent and distant places. This study aims to unveil the spatio-temporal pattern of China's WUs during 2007-2015 and its underlying local and non-local drivers. Results show that China's total WU exhibited an upward trend from 386.7 billion m³; in 2007 to 431.2 billion m³ in 2012 but dropped to 412.6 billion m³ by 2015. Widespread and continuous water use efficiency improvement contributed most to offsetting the increase in WU driven by the rising affluence and growing population in the context of rapid urbanization and industrialization. Economic structure drove a relatively large WU reduction (responsible for -23.7% of the WU change during 2007-2015), in line with China's ongoing transform from a capital investment-driven economy to a consumption-driven one and decoupling economic growth from environmental pressure. The population share representing the non-local factor of migration effect was large enough to be seen clearly in the changing WUs across China: the WUs of coastal areas ascended while inland areas descended, which was in accordance with migration patterns. Our findings could make a valuable contribution to decision-making in identifying hotspot areas, charting systematic courses for sustainable water use, and combining demand-oriented and supply-oriented measures.

Large net forest loss in Cambodia's Tonle Sap Lake protected areas during 1992-2019.

Historical land-use practices have caused forest loss in Cambodia's Tonle Sap Lake area (TSLA), the largest freshwater lake in Southeast Asia. However, it remains unclear if this deforestation trend had continued since 2001 when the land was designated as protected areas. Using satellite imagery, we investigated forest conversion flows and fragmentation patterns in the TSLA for 1992-2001, 2001-2010, and 2010-2019, respectively. Results show substantial forest losses and fragmentations occurring at the lower floodplain where the protected areas are located until 2010, with some forest regain during 2010-2019. The land conversions indicated that forest clearing and agricultural farming were the primary causes for observed extensive forest loss during 1992-2010. Hence, despite the creating of protected areas in 2001, our findings reveal the persistence of alarming forest loss in the TSLA until 2010. On the other hand, while net forest loss has stopped after 2010, forest regain during 2010-2019 is way too small to restore the region's total forest area to even the level when the protected areas were established. Thus, more effective planning and implementations of forest management and restoration policies are needed for the TSLA.

Making Waves: Joining forces for better doctoral education in water research.

We argue that doctoral education in water needs an elevated focus towards educating game changers who can drive innovation and change towards more sustainable futures across academic and non-academic settings. Today's doctoral graduates in water are increasingly employed outside academia, and challenged to understand complex and interconnected systems, to integrate and synthesize information from different disciplines and to lead the way toward increasingly creative, resilient, robust, and socially sustainable solutions. Supervisors are challenged by interdisciplinary research topics and by growing diversity of objectives, too often at the cost of their wellbeing. The need to keep up with the rapid scientific and technological development and floods of big data is pressing. We synthesize key insights from higher education literature and doctoral programs in water research to identify priority actions targeted at four key actor groups: supervisors and supervisees, research group, university, and industry. The actions contribute to appropriate resourcing, enabling an environment for enhanced teamwork practices, and systematic structures for progress. Establishing supporting structures will leverage the much-needed communities of practice involved in co-creating and transforming supervision and education of doctoral students in interdisciplinary water research.

Climate change risks pushing one-third of global food production outside the safe climatic space.

Food production on our planet is dominantly based on agricultural practices developed during stable Holocene climatic conditions. Although it is widely accepted that climate change perturbs these conditions, no systematic understanding exists on where and how the major risks for entering unprecedented conditions may occur. Here, we address this gap by introducing the concept of safe climatic space (SCS), which incorporates the decisive climatic factors of agricultural production: precipitation, temperature, and aridity. We show that a rapid and unhalted growth of greenhouse gas emissions (SSP5-8.5) could force 31% of the global food crop and 34% of livestock production beyond the SCS by 2081-2100. The most vulnerable areas are South and Southeast Asia and Africa's Sudano-Sahelian Zone, which have low resilience to cope with these changes. Our results underpin the importance of committing to a low-emissions scenario (SSP1-2.6), whereupon the extent of food production facing unprecedented conditions would be a fraction.

Enhancing water and land efficiency in agricultural production and trade between Central Asia and China.

Besides posing soaring pressure on water and land resources, the ever-intensifying agricultural production redistributes these pressures trough increasingly intensive trade. Environmental consequences are complicated and unprecedented, and postulate thorough scrutiny. Little attention is paid to developing regions which are small nodes in terms of trade volume in global trade however of visible gaps in water and land productivities. Five Central Asian nations (CANs) have close trade activities with their neighbour China, but their agricultural production efficiency is strikingly low and the ecological environment is severely degraded. Here we evaluate, among CANs and China, the water and land footprints, virtual water and land trades, as well as potentials in enhancing water and land efficiency related to sixteen primary crop products, four primary animal products, and twelve derivative products production and trade over the period 2000-2014. We find that the blue water footprint and land footprint per unit product in CANs were up to 61- and 17-times higher than in China. Through enhancing water and land efficiency without further intervention in water and land endowments, the scenario for CANs shows an additional food supply for feeding 387 million people or half the starving population in the world.

Quantifying economic-social-environmental trade-offs and synergies of water-supply constraints: An application to the capital region of China.

Sustainable water management is one of the sustainable development goals (SDGs) and is characterized by a high level of interdependencies with other SDGs from regional to global scales. Many water assessment studies are restricted to silo thinking, mostly focusing on water-related consequences, while lacking a quantification of trade-offs and synergies of economic, social, and environmental dimensions. To fill this knowledge gap, we propose a "nexus" approach that integrates a water supply constrained multi-regional input-output (mixed MRIO) model, scenario analysis, and multi-criteria decision analysis (MCDA) to quantify the trade-offs and synergies at the sectoral level for the capital region of China, i.e. the Beijing-Tianjin-Hebei urban agglomeration. A total of 120 industrial transition scenarios including nine major industries with high water-intensities and water consumption under current development pathways were developed to facilitate the trade-off and synergy analysis between economic loss, social goals (here, the number of jobs) and environmental protection (with grey water footprint representing water pollution) triggered by water conservation measures. Our simulation results show that an imposition of a tolerable water constraint (a necessary water consumption reduction for regional water stress level to move from severe to moderate) in the region would result in an average economic loss of 68.4 (± 16.0) billion Yuan (1 yuan ≈ 0.158 USD$ in 2012), or 1.3 % of regional GDP, a loss of 1.94 (± 0.18) million jobs (i.e. 3.5 % of the work force) and a reduction of 1.27 (± 0.40) billion m3 or about 2.2% of the regional grey water footprint. A tolerable water rationing in water-intensive sectors such as Agriculture, Food and tobacco processing, Electricity and heating power production and Chemicals would result in the lowest economic and job losses and the largest environmental benefits. Based on MCDA, we selected the 10 best scenarios with regard to their economic, social and environmental performances as references for guiding future water management and suggested industrial transition policies. This integrated approach could be a powerful policy support tool for 1) assessing trade-offs and synergies among multiple criteria and across multiple region-sectors under resource constraints; 2) quantifying the short-term supply-chain effects of different containment measures, and 3) facilitating more insightful evaluation of SDGs at the regional level so as to determine priorities for local governments and practitioners to achieve SDGs.

The Planet's Stressed River Basins: Too Much Pressure or Too Little Adaptive Capacity?

Freshwater is one of the most critical elements for sustainable development of ecosystems and societies. River basins, concomitant with administrative zones, form a common unit for freshwater management. So far, no comprehensive, global analysis exists that would link the ecological challenges of the planet's river basins to the capacity of the societies to cope with them. We address this gap by performing a geospatial resilience analysis for a global set of 541 river basins. We use the social-ecological systems approach by relating three ecological vulnerability factors (human footprint, natural hazards, and water scarcity) with three adaptive capacity factors (governance, economy, and human development), based on temporal trajectories from 1990 to 2015. Additionally, we examine resilience by subtracting ecological vulnerability from adaptive capacity. The most striking result is the fundamentally different patterns of controlling factors of the resilience in different developing regions, particularly those of Africa and Asia. Their root causes are particularly low adaptive capacity in Africa and high ecological vulnerability in Asia. Alarmingly, the difference between those continents grew within the study period. Finally, this study highlights the rapid dynamics of adaptive capacity in comparison to ecological vulnerability, the latter having more inertia. Their fragile balance is of our interest; they can either support or counteract each other depending on the geographic location.

From food insufficiency towards trade dependency: a historical analysis of global food availability.

Achieving global food security is one of the major challenges of the coming decades. In order to tackle future food security challenges we must understand the past. This study presents a historical analysis of global food availability, one of the key elements of food security. By calculating national level dietary energy supply and production for nine time steps during 1965-2005 we classify countries based on their food availability, food self-sufficiency and food trade. We also look at how diets have changed during this period with regard to supply of animal based calories. Our results show that food availability has increased substantially both in absolute and relative terms. The percentage of population living in countries with sufficient food supply (>2500 kcal/cap/d) has almost doubled from 33% in 1965 to 61% in 2005. The population living with critically low food supply (<2000 kcal/cap/d) has dropped from 52% to 3%. Largest improvements are seen in the MENA region, Latin America, China and Southeast Asia. Besides, the composition of diets has changed considerably within the study period: the world population living with high supply of animal source food (>15% of dietary energy supply) increased from 33% to over 50%. While food supply has increased globally, food self-sufficiency (domestic production>2500 kcal/cap/d) has not changed remarkably. In the beginning of the study period insufficient domestic production meant insufficient food supply, but in recent years the deficit has been increasingly compensated by rising food imports. This highlights the growing importance of food trade, either for food supply in importing countries or as a source of income for exporters. Our results provide a basis for understanding past global food system dynamics which, in turn, can benefit research on future food security.

Using global datasets to create environmental profiles for data-poor regions: a case from the Irrawaddy and Salween River Basins.

The increasing availability of spatial data inspires the exploration of previously less-studied, yet regionally and nationally important areas, such as the Irrawaddy and Salween River Basins in Southeast Asia. This article documents our experience using global datasets to create environmental basin profiles in these two basins. Our approach draws on the concepts of freshwater vulnerability assessments that guided the selection of indicators. Data on land use, population distribution and fertilizer load were used. The unit of analysis was chosen to distinguish areas with similar bio-geographical characteristics, such as the critical delta areas. Results were further discussed for sub-areas that experience relatively the most pressure in terms of examined indicators within the studied area. The river mouths of both rivers had the most intensive land use and high population density. They are also home to important ecosystems and are sensitive to changes in upstream areas. Our study presents a concise and spatially distributed view of the environmental basin profiles of the Irrawaddy and Salween River Basins. The analysis also provides some interesting methodological insights about the potential of public macro-scale datasets for environmental assessment. The spatial approach allowed the analysis of different indicators, providing a platform for data integration as well as a visually powerful overview of the study area. Yet, the use of macro-scale datasets entails challenges. Despite improvements, the assessment process tends to be driven by the availability and quality of data, rather than by the actual research and management needs. The greatest utility of macro-scale datasets lies-at least in data-poor areas-in larger scale comparative analyses between the basins and their different sub-areas.

Bayesian networks in environmental and resource management.

This overview article for the special series, "Bayesian Networks in Environmental and Resource Management," reviews 7 case study articles with the aim to compare Bayesian network (BN) applications to different environmental and resource management problems from around the world. The article discusses advances in the last decade in the use of BNs as applied to environmental and resource management. We highlight progress in computational methods, best-practices for model design and model communication. We review several research challenges to the use of BNs in environmental and resource management that we think may find a solution in the near future with further research attention.

Fully connected Bayesian belief networks: a modeling procedure with a case study of the Ganges river basin.

The use of Bayesian Belief Networks (BBNs) in modeling of environmental and natural resources systems has gradually grown, and they have become one of the mainstream approaches in the field. They are typically used in modeling complex systems in which policy or management decisions must be made under high uncertainties. This article documents an approach to constructing large and highly complex BBNs using a matrix representation of the model structure. This approach allows smooth construction of highly complicated models with intricate likelihood structures. A case study of the Ganges river basin, the most populated river basin of the planet, is presented. Four different development scenarios were investigated with the purpose of reaching the Millennium Development Goals and Integrated Water Resources Management goals, both promoted by the United Nations Agencies. The model results warned against the promotion of economic development policies that do not place strong emphasis on social and environmental concerns.

How close do we live to water? A global analysis of population distance to freshwater bodies.

Traditionally, people have inhabited places with ready access to fresh water. Today, over 50% of the global population lives in urban areas, and water can be directed via tens of kilometres of pipelines. Still, however, a large part of the world's population is directly dependent on access to natural freshwater sources. So how are inhabited places related to the location of freshwater bodies today? We present a high-resolution global analysis of how close present-day populations live to surface freshwater. We aim to increase the understanding of the relationship between inhabited places, distance to surface freshwater bodies, and climatic characteristics in different climate zones and administrative regions. Our results show that over 50% of the world's population lives closer than 3 km to a surface freshwater body, and only 10% of the population lives further than 10 km away. There are, however, remarkable differences between administrative regions and climatic zones. Populations in Australia, Asia, and Europe live closest to water. Although populations in arid zones live furthest away from freshwater bodies in absolute terms, relatively speaking they live closest to water considering the limited number of freshwater bodies in those areas. Population distributions in arid zones show statistically significant relationships with a combination of climatic factors and distance to water, whilst in other zones there is no statistically significant relationship with distance to water. Global studies on development and climate adaptation can benefit from an improved understanding of these relationships between human populations and the distance to fresh water.

Mekong at the Crossroads.

The Mekong region is undergoing rapid transitions, socially, economically, and environmentally. Economies are stabilizing after the political turbulence of the last several decades, and development pressures as well as ambitions are vast. Water is related to these social, economic, and environmental changes in many ways and in a very profound manner. This article summarizes the approach and major conclusions of the research project title "Integrated Water Resources Management (IWRM) on the Mekong River." The concept of IWRM is elaborated in the setting of these major transitions, and the roles of academic research and education are highlighted.

Poverty, economic growth, deprivation, and water: the cases of Cambodia and Vietnam.

Poverty reduction decorates all development agendas, but the complexity of the poverty issue is too often hidden behind simplistic indicators and development goals. Here, a closer look is taken at the concepts of "deprivation" and "vulnerability" as outcomes of poverty. Deprivation leads typically to social exclusion and marginalization; such groups are particularly weak in getting themselves out of poverty by "self-help," and economic growth does not trickle down to these people. When looking at the connections between poverty reduction and economic growth, special emphasis should be put on the differences between modern and more traditional sectors: development of the modern sector should not marginalize and exclude those dependent on more traditional livelihoods. Two case studies--The Tonle Sap area, Cambodia, and the Mekong Delta, Vietnam--reveal that investment in education, empowerment of small-scale entrepreneurship and other means of microeconomic environment, along with good governance, infrastructure, and income distribution can ensure that economic growth includes the poorer echelons of society.

Backyard of the rich north: the climate change-related vicious circle of the Arctic zone.

The Arctic zone is full of controversies, unknowns, contrasts, and challenges. The following example is enlightening. Saudi Arabia is a country that has been considered to have almost unlimited possibilities because of its enormous oil earnings. The country has US$60 thousand million purchasing power parity oil income each year for its mere 22 million inhabitants. Astonishingly, the Arctic zone's income from oil, gas, and minerals is at least as large as that of Saudi Arabia, modestly estimated, but the Arctic has less than 4 million people. Most money, however, flows away from the tundra, yet social and environmental problems remain there. A part of the side effect of consuming these resources-largely fossil fuels-returns to the Arctic in the form of greenhouse warming and all its consequences. The Arctic zone now warms at approximately double the rate of the world average.