Dynamic attribution of global water demand to surface water and groundwater resources: Effects of abstractions and return flows on river discharges

As human water demand is increasing worldwide, pressure on available water resources grows and their sustainable exploitation is at risk. To mimic changes in exploitation intensity and the connecting feedbacks between surface water and groundwater systems, a dynamic attribution of demand to water resources is necessary. However, current global-scale hydrological models lack the ability to do so. This study explores the dynamic attribution of water demand to simulated water availability. It accounts for essential feedbacks, such as return flows of unconsumed water and riverbed infiltration. Results show that abstractions and feedbacks strongly affect water allocation over time, particularly in irrigated areas. Also residence time of water is affected, as shown by changes in low flow magnitude, frequency, and timing. The dynamic representation of abstractions and feedbacks makes the model a suitable tool for assessing spatial and temporal impacts of changing global water demand on hydrology and water resources.

[1]  L. V. Beek,et al.  Water balance of global aquifers revealed by groundwater footprint , 2012, Nature.

[2]  D. V. D. Leur.  Some effects of the unsaturated zone on nonsteady free‐surface groundwater flow as studied in a scaled granular model , 1962 .

[3]  A. Sterl,et al.  The ERA‐40 re‐analysis , 2005 .

[4]  M. Bierkens,et al.  Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources , 2013 .

[5]  Naota Hanasaki,et al.  An estimation of global virtual water flow and sources of water withdrawal for major crops and livestock products using a global hydrological model , 2010 .

[6]  P. Jones,et al.  Representing Twentieth-Century Space-Time Climate Variability. Part II: Development of 1901-96 Monthly Grids of Terrestrial Surface Climate , 2000 .

[7]  Petra Döll,et al.  Validation of a new global 30-min drainage direction map , 2002 .

[8]  P. Döll,et al.  Development and validation of a global database of lakes, reservoirs and wetlands , 2004 .

[9]  W. Lucht,et al.  Agricultural green and blue water consumption and its influence on the global water system , 2008 .

[10]  M. Bierkens,et al.  Global monthly water stress: 1. Water balance and water availability , 2011 .

[11]  Michel Meybeck,et al.  Lithologic composition of the Earth's continental surfaces derived from a new digital map emphasizing riverine material transfer , 2005 .

[12]  B. Scanlon,et al.  Impact of water withdrawals from groundwater and surface water on continental water storage variations , 2012 .

[13]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[14]  S. Postel.  Entering an era of water scarcity: the challenges ahead. , 2000 .

[15]  T. D. Mitchell,et al.  An improved method of constructing a database of monthly climate observations and associated high‐resolution grids , 2005 .

[16]  Diana M. Allen,et al.  Groundwater sustainability strategies , 2010 .

[17]  M. Bierkens,et al.  Global depletion of groundwater resources , 2010 .

[18]  Naota Hanasaki,et al.  Incorporating anthropogenic water regulation modules into a land surface model , 2012 .

[19]  Dennis P. Lettenmaier,et al.  Influence of spatial resolution on simulated streamflow in a macroscale hydrologic model , 2002 .

[20]  Marc F. P. Bierkens,et al.  Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability , 2011 .

[21]  M. Bierkens,et al.  Nonsustainable groundwater sustaining irrigation: A global assessment , 2012 .

[22]  Andreas Schumann,et al.  Global irrigation water demand: Variability and uncertainties arising from agricultural and climate data sets , 2008 .

[23]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[24]  C. Vörösmarty,et al.  Global water resources: vulnerability from climate change and population growth. , 2000, Science.

[25]  M. Hulme,et al.  A high-resolution data set of surface climate over global land areas , 2002 .

[26]  Rolf Weingartner,et al.  Global monthly water stress: 2. Water demand and severity of water stress , 2011 .