Urban water demand will increase by 80% by 2050, while climate change will alter the timing and distribution of water. Here we quantify the magnitude of these twin challenges to urban water security, combining a dataset of urban water sources of 482 of the world’s largest cities with estimates of future water demand, based on the Intergovernmental Panel on Climate Change (IPCC)’s Fifth Assessment scenarios, and predictions of future water availability, using the WaterGAP3 modelling framework. We project an urban surface-water deficit of 1,386–6,764 million m³.

Urban growth is increasing the demand for freshwater resources, yet surprisingly the water sources of the world’s large cities have never been globally assessed, hampering efforts to assess the distribution and causes of urban water stress. We conducted the first global survey of the large cities’ water sources, and show that previous global hydrologic models that ignored urban water infrastructure significantly overestimated urban water stress.

Delhi with fast-growing rate of urbanisation is the second most water-stressed cities in the world according to this new research published in Global Environmental Change Journal which has mapped 500 large cities to determine how global urbanisation is affecting water supplies. Kolkata (6), Chennai (18), Bangalore (19) and Hyderabad (20) are also listed in this first global survey of the large cities’ water sources.

Nearly 3 billion additional urban dwellers are forecasted by 2050, an unprecedented wave of urban growth. While cities struggle to provide water to these new residents, they will also face equally unprecedented hydrologic changes due to global climate change.

Concern over climate change has led the U.S. to consider a cap-and-trade system to regulate emissions. Here we illustrate the land-use impact to U.S. habitat types of new energy development resulting from different U.S. energy policies. We estimated the total new land area needed by 2030 to produce energy, under current law and under various cap-and-trade policies, and then partitioned the area impacted among habitat types with geospatial data on the feasibility of production.