Gerten, D.

Haddeland, I.

Hagemann, S.

Ludwig, F.

Wiberg, D.

English

Name not available

Definition of socioeconomic scenarios for land surface hydrology simulations of the 21st century

Wageningen Yield 

  
 
 
 
 
 
 
 
Technical Report No. 5 
 
 
DEFINITION OF SOCIOECONOMIC SCENARIOS FOR 
LAND SURFACE HYDROLOGY SIMULATIONS OF 
THE 21ST CENTURY 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Author names: Dieter Gerten, Ingjerd Haddeland, Stefan Hagemann, Fulco Ludwig, David Wiberg, 
Frank Voss 
 
Date: 20 August 2008 
 
 
 
 
Dominant ecosystem classes in 
Africa (GAEZ 2000, FAO/IIASA) 
 Technical Report No. 5 - 2 - 
 
 
WATCH is an Integrated Project Funded by the European Commission under the Sixth Framework 
Programme,  Global Change and Ecosystems Thematic Priority Area (contract number: 036946).  
The WACH project started 01/02/2007 and will continue for 4 years. 
 
 
Title: Definition of socioeconomic scenarios for land surface 
hydrology simulations of the 21st century 
Authors: Dieter Gerten, Ingjerd Haddeland, Stefan Hagemann, 
Fulco Ludwig, David Wiberg, Frank Voss 
 
Organisations: PIK, MPI-M, WUR, IIASA, CESR 
 
Submission date: 20 August 2008 
 
Function: This report is an output from WB 3 (generated together 
with WB 2 and WB 6), Task 3.3.1 
 
Deliverable WATCH deliverable 3.3.1 
 
 
 
This deliverable reports on discussions and progress made to define scenarios for the 21st century that 
reflect regional and global changes in socio-economic conditions (basically land and water use), which 
shall be used to prescribe temporal, and spatially distributed, boundary conditions for the later global 
and regional hydrological sensitivity simulations.  
 
These input databases shall be used for several purposes, a) for specific analyses by individual WATCH 
members and models, and b) for the planned intercomparison of hydrological and land surface models 
for the 21st century. The present, preliminary overview of available data should be regarded as a starting 
point. The final set of scenarios/boundary conditions to be used and the list of models that are to 
participate in the 21st century runs will have to be decided upon by the model intercomparison 
consortium in a later stage of the WATCH project, probably during the General Assembly in November 
2009 in Bratislava.  
 
It will be ensured that the eventually chosen socioeconomic scenarios are consistent with the GCM 
projections of climatic changes that they underlie, i.e. those stemming from the SRES ‘family’, preferably 
the conveniently used A2 and B1 emissions scenarios (or the moderate A1B scenario if only one 
scenario is chosen). For particular (probability-based) applications by single models, a much larger set 
of scenarios can be chosen.  
For WB2, IIASA has produced a suite of historic and SRES-consistent future databases (not yet in 
netCDF format), which are recommended for use in the later hydrological simulations in WATCH (within 
WBs 3, 4, 5, and 6). A link to these global databases and more detailed descriptions are available upon 
request from David Wiberg, wiberg@iiasa.ac.at; in the following only a short description of the data 
sources is provided. 
 Technical Report No. 5 - 3 - 
 
 
a) Historic land use (cropland and pasture area in km2 per grid cell), taken from the HYDE 
database (e.g. Klein Goldewijk 2001) and provided as decadal values for the years 1900 to 
2000 (which can be interpolated linearly to annual values). 
b) Historic population data in the same resolution also taken from HYDE (Klein Goldewijk 2005), 
namely population counts and densities, i.e. number of inhabitants per grid cell (distinguished 
between rural and urban) and inhabitants per km2 per grid cell. 
c) Current land use and land cover including seven major land cover/land use categories at 5 min 
resolution (GAEZ, Fischer et al. 2008), as follows: 1) The GLC2000 land cover database at 30 
min resolution; 2) a global land cover categorization providing 17 land cover classes at 30 min, 
based on IFPRI (2002); 3) The FAO (2001) Global Forest Resources Assessment at 30 min; 4) 
The Digital Global Map of Irrigated Areas (GMIA) version 4.0 at 5 min, providing per grid-cell the 
percentage land area equipped for irrigation (Siebert et al. 2005); 5) IUCN-WCMC protected 
areas inventory at 30 min (http://www.unep-wcmc.org/wdpa/); and 6) a spatial population 
density inventory (30 min) for 2000 developed by FAO-SDRN. These data distinguish between 
fractional coverage by different types of land use. Downscaled data on areas of individual crops 
are being worked on; areas suitable for different crops are already available. 
d) Spatially explicit scenarios of future land use, population, GDP (gross domestic product) and 
energy, describing three alternative demographic-economic development scenarios over the 
period 1990 to 2100 in decadal intervals at 30 min resolution. The three latter products include 
gridded values of 1) population counts, 2) population densities, 3) GDP at market exchange 
rates (US$1990), and 4) densities of the latter (1000 US$1990) (Grübler et al. 2008; data 
accessible at http://www.iiasa.ac.at/Research/GGI/DB/). New SRES-consistent future land use 
datasets are being created, which provide percentage values of land cover at 5 min resolution 
for the following classes: cultivated rainfed land, cultivated irrigated land, total cultivated land, 
forested land, grassland, urban areas, water bodies, and others (sparsely vegetated land). At 
the time of writing this report, one land use scenario (based on the storyline of one of the SRES 
scenarios) is completed, others are expected to be completed within the next months. In 
addition to these data, suitability classes for different agricultural crops and pasture in the 21st 
century can be provided. 
 
Yet, there is still some inconsistency between the (IIASA-based) land use data available for the past 
and those available for the future. If for the hydrological simulations consistency is required, continuous 
databases from 1900 to 2100 may be produced at the cost of significantly reduced data quality. 
 
Data from other groups are likely to be used in addition for particular analyses by individual modelling 
groups in different WBs. These may include, for example, the SRES-consistent land use datasets 
created by the IMAGE group, which would allow for a comparison of the hydrological effects of the 
differences between that product and the IIASA data; or the SRES-consistent population data from 
Bengtsson et al. (2007). In addition, further scenario data will be required for individual studies on future 
water availability and stress, in particular scenario data on water use by different sectors (water use by 
households and industries e.g. as described by Shen et al. (2008), and also water use in irrigation if this 
is not computed directly by the models). 
 
 Technical Report No. 5 - 4 - 
References 
Bengtsson, M., Shen, Y., Oki, T. (2007) A SRES-based gridded global population dataset for 1990–
2100. Population & Environment 28, 113–131. 
FAO (2001) Global Forest Resources Assessment 2000: Main report. FAO Forestry Paper 140, Rome. 
Fischer, G., van Velthuizen, H., Shah, M., Nachtergaele, F. (2002) Global Agro-Ecological Zones 
Assessment for Agriculture in the 21st Century: Methodology and Results. IIASA, Laxenburg, Austria. 
IIASA/FAO. 
Grübler, A. B. O'Neilla, B., Riahia, K., Chirkova, V., Goujona, A., Kolpa, P., Prommera, I., Scherbova,S. 
Slentoe, E. (2008) Regional, national, and spatially explicit scenarios of demographic and economic 
change based on SRES. Technological Forecasting & Social Change 74, 980-1029 
IFPRI (2002) Reinterpretation of global land cover characteristics database (GLCCD v2.0, EROS Data 
Center), unpublished dataset. Washington D.C. 
JRC (2004) Global Land Cover (GLC) 2000 Database, 1st ed. European Commission Joint Research 
Center (JRC) Global Environment Monitoring Unit.  
Klein Goldewijk, K. (2001) Estimating global land use change over the past 300 years: the HYDE 
database. Global Biogeochemical Cycles 15, 417–434. 
Klein Goldewijk, K. (2005) Three centuries of global population growth: A spatial referenced population 
density database for 1700 – 2000, Population & Environment 26, 343–367. 
Shen, Y., Oki, T., Utsumi, N., Kanae, S., Hanasaki, N. (2008) Projection of future world water resources 
under SRES scenarios: water withdrawal. Hydrological Sciences Journal 53, 11–33. 
Siebert, S., Döll, P., Hoogeveen, J., Faurès, J-M., Frenken, K., Feick, S. 2005. Development and 
validation of the global map of irrigation areas. Hydrology and Earth System Sciences 9, 535–547. 
 


A SRES-based gridded global population dataset for

Development and validation of the global map of irrigation areas.

Estimating global land use change over the past 300 years: the HYDE database.

Global Forest Resources Assessment 2000: Main report. FAO Forestry Paper 140,

Projection of future world water resources under SRES scenarios: water withdrawal.

Regional, national, and spatially explicit scenarios of demographic and economic change based on SRES.

Three centuries of global population growth: A spatial referenced population density database for 1700 –

Definition of socioeconomic scenarios for land surface hydrology simulations of the 21st century

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