A global empirical typology of anthropogenic drivers of environmental change in deltas.

It is broadly recognized that river delta systems around the world are under threat from a range of anthropogenic activities. These activities occur at the local delta scale, at the regional river and watershed scale, and at the global scale. Tools are needed to support generalization of results from case studies in specific deltas. Here, we present a methodology for quantitatively constructing an empirical typology of anthropogenic change in global deltas. Utilizing a database of environmental change indicators, each associated with increased relative sea-level rise and coastal wetland loss, a clustering analysis of 48 global deltas provides a quantitative assessment of systems experiencing similar or dissimilar sources and degrees of anthropogenic stress. By identifying quantitatively similar systems, we hope to improve the transferability of scientific results across systems, and increase the effectiveness of delta management best practices. Both K-Means and Affinity Propagation clustering algorithms find similar clusters, with relative stability across small changes in K-Means cluster number. High-latitude deltas appear similar, in terms of anthropogenic environmental stress, to several low-population, low-latitude systems, including the Amazon delta, despite substantially different climatic regimes. Highly urbanized deltas in Southeast Asia form a distinct cluster. By providing a quantitative boundary between groups of delta systems, this approach may also be useful for assessing future delta change and sustainability given projected population growth, urbanization, and economic development trends.

Multisectoral climate impact hotspots in a warming world.

The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.

Global water resources affected by human interventions and climate change.

Humans directly change the dynamics of the water cycle through dams constructed for water storage, and through water withdrawals for industrial, agricultural, or domestic purposes. Climate change is expected to additionally affect water supply and demand. Here, analyses of climate change and direct human impacts on the terrestrial water cycle are presented and compared using a multimodel approach. Seven global hydrological models have been forced with multiple climate projections, and with and without taking into account impacts of human interventions such as dams and water withdrawals on the hydrological cycle. Model results are analyzed for different levels of global warming, allowing for analyses in line with temperature targets for climate change mitigation. The results indicate that direct human impacts on the water cycle in some regions, e.g., parts of Asia and in the western United States, are of the same order of magnitude, or even exceed impacts to be expected for moderate levels of global warming (+2 K). Despite some spread in model projections, irrigation water consumption is generally projected to increase with higher global mean temperatures. Irrigation water scarcity is particularly large in parts of southern and eastern Asia, and is expected to become even larger in the future.