Multicompartment Depletion Factors for Water Consumption on a Global Scale.

Balancing human communities' and ecosystems' need for freshwater is one of the major challenges of the 21st century as population growth and improved living conditions put increasing pressure on freshwater resources. While frameworks to assess the environmental impacts of freshwater consumption have been proposed at the regional scale, an operational method to evaluate the consequences of consumption on different compartments of the water system and account for their interdependence is missing at the global scale. Here, we develop depletion factors that simultaneously quantify the effects of water consumption on streamflow, groundwater storage, soil moisture, and evapotranspiration globally. We estimate freshwater availability and water consumption using the output of a global-scale surface water-groundwater model for the period 1960-2000. The resulting depletion factors are provided for 8,664 river basins, representing 93% of the landmass with significant water consumption, i.e., excluding Greenland, Antarctica, deserts, and permanently frozen areas. Our findings show that water consumption leads to the largest water loss in rivers, followed by aquifers and soil, while simultaneously increasing evapotranspiration. Depletion factors vary regionally with ranges of up to four orders of magnitude depending on the annual consumption level, the type of water used, aridity, and water transfers between compartments. Our depletion factors provide valuable insights into the intertwined effects of surface and groundwater consumption on several hydrological variables over a specified period. The developed depletion factors can be integrated into sustainability assessment tools to quantify the ecological impacts of water consumption and help guide sustainable water management strategies, while accounting for the performance limitations of the underlying model.

Advancing water footprint assessments: Combining the impacts of water pollution and scarcity.

Several water footprint indicators have been developed to curb freshwater stress. Volumetric footprints support water allocation decisions and strive to increase water productivity in all sectors. In contrast, impact-oriented footprints are used to minimize the impacts of water use on human health, ecosystems, and freshwater resources. Efforts to combine both perspectives in a harmonized framework have been undertaken, but common challenges remain, such as pollution and ecosystems impacts modelling. To address these knowledge gaps, we build upon a water footprint assessment framework proposed at conceptual level to expand and operationalize relevant features. We propose two regionalized indicators, namely the water biodiversity footprint and the water resource footprint, that aggregate all impacts from toxic chemicals, nutrients, and water scarcity. The first impact indicator represents the impacts on freshwater ecosystems. The second one models the competition for freshwater resources and its consequences on freshwater availability. As part of the framework, we complement the two indicators with a sustainability assessment representing the levels above which ecological and human freshwater needs are no longer sustained. We test our approach assessing the sustainability of water use in the European Union in 2010. Water stress hampers 15 % of domestic, agricultural and industrial water demand, mainly due to irrigation and pesticide emissions in southern Europe. Moreover, damage to the freshwater ecosystems is widespread and mostly resulting from chemical emissions from industry. Approximately 5 % of the area is exceeding the regional sustainability limits for ecosystems and human water requirements altogether. Concerted efforts from all sectors are needed to reduce the impacts of emissions and water consumption under the sustainability limits. These advances are considered an important step toward the harmonization of volumetric and impact-oriented approaches to achieve consistent and holistic water footprinting as well as contributing to strengthen the policy relevance of water footprint assessments.

Global water consumption impacts on riverine fish species richness in Life Cycle Assessment.

Reduced river discharge and flow regulation are significant threats to freshwater biodiversity. An accurate representation of potential damage of water consumption on freshwater biodiversity is required to quantify and compare the environmental impacts of global value chains. The effect of discharge reduction on fish species richness was previously modeled in life cycle impact assessment, but models were limited by the restricted geographical scope of underlying species-discharge relationships and the small number of species data. Here, we propose a model based on a novel regionalized species-discharge relationship (SDR). Our SDR-based model covers 88 % of the global landmass (2320 river basins worldwide excluding deserts and permanently frozen areas) and is based on a global dataset of 11,450 riverine fish species, simulated river discharge, elevation, and climate zones. We performed 10-fold cross-validation to select the best set of predictors and validated the obtained SDRs based on observed discharge data. Our model performed better than previous SDRs employed in life cycle impact assessment (Kling-Gupta efficiency coefficient about 4 times larger). We provide both marginal and average models with their uncertainty ranges for assessing scenarios of small and large-scale water consumption, respectively, and include regional and global species loss. We conducted an illustrative case study to showcase the method's applicability and highlight the differences with the currently used approach. Our models are useful for supporting sustainable water consumption and riverine fish biodiversity conservation decisions. They enable a more specific, reliable, and complete impact assessment by differentiating impacts on regional riverine fish species richness and irreversible global losses, including up-to-date species data, and providing spatially explicit values with high geographical coverage.