Dataset Information

Assessment of future changes in water availability and aridity.

ABSTRACT: Substantial changes in the hydrological cycle are projected for the 21st century, but these projections are subject to major uncertainties. In this context, the "dry gets drier, wet gets wetter" (DDWW) paradigm is often used as a simplifying summary. However, recent studies cast doubt on the validity of the paradigm and also on applying the widely used P - E (precipitation?-?evapotranspiration) metric over global land surfaces. Here we show in a comprehensive CMIP5-based assessment that projected changes in mean annual P - E are generally not significant, except for high-latitude regions showing wetting conditions until the end of the 21st century. Significant increases in aridity do occur in many subtropical and also adjacent humid regions. However, combining both metrics still shows that approximately 70% of all land area will not experience significant changes. Based on these findings, we conclude that the DDWW paradigm is generally not confirmed for projected changes in most land areas.

SUBMITTER: Greve P

PROVIDER: S-EPMC4810427 | biostudies-other | 2015 Jul

REPOSITORIES: biostudies-other

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Assessment of future changes in water availability and aridity.

Greve P P Seneviratne S I SI

Geophysical research letters 20150704 13

Substantial changes in the hydrological cycle are projected for the 21st century, but these projections are subject to major uncertainties. In this context, the "dry gets drier, wet gets wetter" (DDWW) paradigm is often used as a simplifying summary. However, recent studies cast doubt on the validity of the paradigm and also on applying the widely used <i>P</i> - <i>E</i> (precipitation - evapotranspiration) metric over global land surfaces. Here we show in a comprehensive CMIP5-based assessment ...[more]

PMID: 27076690

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Project description:Global warming and anthropogenic changes can result in the heterogeneity of water availability in the spatiotemporal scale, which will further affect the allocation of water resources. A lot of researches have been devoted to examining the responses of water availability to global warming while neglected future anthropogenic changes. What's more, only a few studies have investigated the response of optimal allocation of water resources to the projected climate and anthropogenic changes. In this study, a cascade model chain is developed to evaluate the impacts of projected climate change and human activities on optimal allocation of water resources. Firstly, a large set of global climate models (GCMs) associated with the Daily Bias Correction (DBC) method are employed to project future climate scenarios, while the Cellular Automaton-Markov (CA-Markov) model is used to project future Land Use/Cover Change (LUCC) scenarios. Then the runoff simulation is based on the Soil and Water Assessment Tool (SWAT) hydrological model with necessary inputs under the future conditions. Finally, the optimal water resources allocation model is established based on the evaluation of water supply and water demand. The Han River basin in China was selected as a case study. The results show that: (1) the annual runoff indicates an increasing trend in the future in contrast with the base period, while the ascending rate of the basin under RCP 4.5 is 4.47%; (2) a nonlinear relationship has been identified between the optimal allocation of water resources and water availability, while a linear association exists between the former and water demand; (3) increased water supply are needed in the water donor area, the middle and lower reaches should be supplemented with 4.495 billion m3 water in 2030. This study provides an example of a management template for guiding the allocation of water resources, and improves understandings of the assessments of water availability and demand at a regional or national scale.

Dataset Information

Assessment of future changes in water availability and aridity.

Publications

Assessment of future changes in water availability and aridity.

Similar Datasets

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