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A homogenized soil data file for global environmental research: A subset of FAO, ISRIC and NRCS profiles (Version 1.0)

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ISRIC
Working Paper and Preprint 95/10b
A HOMOGENIZED SOIL DATA FILE FOR GLOBAL ENVIRONMENTAL
RESEARCH: A SUBSET OF FAO, ISRIC AND NRCS PROFILES
(Version 1.0)
N.H. Batjes (Editor)
July 1995
INTERNATIONAL SOIL REFERENCE AND INFORMATION CENTRE
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or
transmitted in any form or by any means, electronic, mechanical, photocopying or otherwise, without the
prior permission of the copyright owner. Applications for such permission, with a statement of the purpose
and extent of the reproduction, should be addressed to the Director, ISRIC, P.O. Box 353, 6700 AJ
Wageningen, The Netherlands.
Copyright © 1995, International Soil Reference and Information Centre (ISRIC)
Disclaimer
While every effort has been made to ensure that the data are accurate and reliable, ISRIC cannot assume
liability for damages caused by in-accuracies in the data or as a result of the failure of the data to function
on a particular system. ISRIC provides no warranty, expressed or implied, nor does an authorized
distribution of the data set constitute such a warranty. ISRIC reserves the right to modify any information
in this document and related data sets without notice.
Correct citation:
Batjes, N.H. (ed.), 1995. A homogenized soil data file for global environmental research: a subset of FAO, ISRIC
and NRCS profiles (Version 1.0). Working Paper and Preprint 95/10b, International Soil Reference and
Information Centre, Wageningen.
Inquiries:
Director, ISRIC
P.O. Box 353
6700 AJ Wageningen
The Netherlands
Telefax : +31-317-471700
E-mail: soil@isric.nl
Working Paper and Preprint 95/10b
A HOMOGENIZED SOIL DATA FILE FOR GLOBAL ENVIRONMENTAL
RESEARCH: A SUBSET OF FAO, ISRIC AND NRCS PROFILES
(Version 1.0)
Edited by
N.H. Batjes
(July 1995)
INTERNATIONAL SOIL REFERENCE AND INFORMATION CENTRE
TABLE OF CONTENTS
Abstract ...................................................... 1
1. Introduction ............................................... 1
2. Procedures ................................................ 3
2.1 The WISE database ....................................... 3
2.2 List of soil attributes ...................................... 3
2.3 Data sources ............................................ 3
2.4 Criteria for accepting profile data ............................. 5
2.5 Selection of "international" profiles ............................ 5
2.6 Sources of uncertainty ..................................... 6
3. Discussion and conclusions .................................... 7
Acknowledgements .............................................. 7
References .................................................... 7
Appendices .................................................... 9
Index ........................................................ 43
List of Figures
Fig. 1. Main database files of the WISE data handling system (2)
List of Tables
Table 1. List of attribute data held in WISE (4)
Table 2. Summary of number of profiles per broad geographic area (6)
Appendices
Appendix 1. Number of profiles per country in “international”data set (9)
Appendix 2. Soil units represented in "international" data set (10)
Appendix 3. Examples of listings of SDB, ISIS and NRCS profiles (11)
Appendix 4. Brief installation procedure (17)
Appendix 5. Structure and attributes of WISE database files (18)
Appendix 6. WISE 2.1 database coding protocols (25)
Appendix 7. List of country ISO codes (41)
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 1
Abstract
A homogenized, global set of 1,125 soil profiles is presented. These profiles have been
extracted from the database developed at ISRIC for a project on "World Inventory of
Soil Emission Potentials" (WISE), as a contribution to the activities of the Global Soils
Data Task Group of IGBP-DIS. The subset consists of a selection of 665 profiles
originating from digital data files released by the Natural Resources Conservation
Service (NRCS, Lincoln), 250 profiles obtained from the Food and Agriculture
Organization (FAO, Rome), and 210 profiles from the reference collection of the
International Soil Reference and Information Centre (ISRIC, Wageningen). All profiles
are georeferenced and classified in the FAO-Unesco Legend whereby they can be linked
to the edited and digital version of the FAO-Unesco Soil Map of the World. This data
set is being released in the public domain for use by global modellers and other
interested scientists. It is envisaged that the data set will be expanded by ISRIC when
new, uniform soil profile data become available.
Keywords: soil profiles; WISE database
1. Introduction
The compilation and processing of large-scale data sets of the world's environmental
resources, using well-documented procedures and standards, is crucial for many global
modelling activities (e.g., Zuidema et al., 1994). Staff at ISRIC have developed a
uniform methodology for a global database of soil properties within the framework of
WISE, a project on World Inventory of Soil Emission Potentials (Batjes and Bridges,
1994). During this project a wide range of profiles from all regions of the world have
been screened for completeness and incorporated into the WISE data handling system.
The profiles in WISE were compiled from 5 main sources: (a) ISRIC's Soil Information
System, ISIS (Van de Ven and Tempel, 1994); (b) FAO's Soil Database System, SDB
(FAO, 1989); (c) digital soil data set compiled by the Natural Resources Conservation
Service (NRCS, formerly SCS) of the United States of America; (d) profiles obtained
from an international data gathering activity coordinated by WISE project staff, in
which national soil survey organisations were asked to supply descriptions and analyses
of profiles representative of the units of the Soil Map of the World present in their
countries; and, (e) suitable profiles gathered from survey monographs held at ISRIC's
library. Special attention was given to the systematic compilation of data and recording
of the laboratory methods by which the analytical results were obtained. All profiles are
classified in the FAO-Unesco (1974) legend, whereby they can be linked to the spatial
data shown on an edited and digital version of the Soil Map of the World (FAO, 1991).
INTERNATIONAL SOIL PROFILE DATA SET
2ISRIC Work. Pap. 95/10b
SITE data HORIZON data
Code definition
conversion tables
1:M
AREA DATA ATTRIBUTE DATA
SMW soil units
Lab. methods Source
M:1
derived soil
data per
layer
G I S <- - -> W I S E profile data
This report describes a uniform set of 1,125 soil profiles, extracted from the WISE
database, for use by global modellers. The selected profiles correspond with what has
become known as the "international" profiles of the WISE database, and formed an
ISRIC contribution to the activities of the Global Soils Data Task Group of IGBP-DIS
(Scholes et al., 1994). The set includes 665 profiles from the USDA-NRCS, 250 from
the FAO-SDB and 210 from the ISRIC-ISIS databases.
Section 2 of this report describes the procedures for compiling and extracting the data
set, and possible user groups are identified in Section 3. Appendix 1 is a listing of the
countries from which the profiles originate. The FAO-Unesco (1974) classification of
these profiles is listed in Appendix 2. Examples of listings of profiles derived from these
data files are attached as Appendix 3, and the installation procedure is explained in
Appendix 4. Appendix 5 presents the structure and attributes of the WISE database,
Appendix 6 presents the database coding protocols and, finally, the country ISO codes
are given in Appendix 7.
Fig. 1. Main database files of the WISE data handling system (M:1 stands for many to one
relations, and 1:M for one to many relations)
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 3
2. Procedures
2.1 The WISE database
WISE 2.1 is a soil data handling system developed for IBM®-compatible computers.
It includes a collection of over 90 compiled program modules for storing, editing,
selecting and printing soil data. The individual modules for handling the soil profile
data are linked in a user-friendly manner by a unified menu system (Fig. 1) .
All procedures are written in dBASE IV®, as are the structures for the database files
(Batjes, 1995). The full WISE database holds a growing selection of globally
distributed profiles considered to be representative of the soil units shown on a ½E
latitude by ½E longitude version of the corrected and digitized 1:5 M FAO-Unesco Soil
Map of the World.
2.2 List of soil attributes
The profile component of the WISE database includes information on: (a) soil
classification and site data; (b) soil horizon data; (c) source of data; (d) the methods
used for determining the analytical data; and, (e) a series of "code-definition" translation
files (Batjes, 1995). The full complement of data selected for inclusion in the WISE
profile database is listed in Table 1. The attributes shown are similar to those proposed
for the European Soil Analytical Database (Madsen and Jones, 1995) and for a Global
Soils Database to be developed under the aegis of IGBP-DIS (Ingram, 1993). The
central aim of the WISE database is to provide a basic set of uniform soil data for a
wide range of global studies, including assessments of crop production, soil
vulnerability to pollution and soil gaseous emission potentials (Batjes et al., 1995).
2.3 Data sources and description methods
The "international" data set holds profiles released by ISRIC-ISIS, FAO-SDB and
USDA-NRCS. The profiles originating from ISIS have been compiled specifically to
be representative of the map units of the Soil Map of the World, with special emphasis
on the tropics. They have all been described using the Guidelines for Soil Description
(FAO-ISRIC, 1990) and analysed in a uniform manner in the ISRIC laboratory (Van
Reeuwijk, 1992). The profiles derived from the NRCS set originate from the USA and
41 other countries. Soil descriptions in this data set follow the methodology of the Soil
Survey Manual (USDA, 1993), and the analyses have been
INTERNATIONAL SOIL PROFILE DATA SET
4ISRIC Work. Pap. 95/10b
Table 1. List of attribute data held in WISE.
Site Data Horizon Data
WISE_ID (unique identifier of profile)
Soil classification and source
FAO-Unesco classification (1974 legend)
phase
topsoil texture class
FAO-Unesco classification (1990a revised
legend)
phase
USDA subgroup level classification
edition (year) of Soil Taxonomy
National classification
source of data
name of laboratory where analyses were made
soil profile description status
date of description
Location
country
location of soil profile, descriptive
latitude (deg/min/s)
longitude (deg/min/s)
altitude
General site data
major landform
landscape position
aspect
slope
drainage class
groundwater depth
effective soil depth
parent material
Köppen climate classification
land use
natural vegetation
WISE_ID + horizon_NO (unique reference
number for horizon within a profile)
General attributes
horizon designation
depth, top
depth, bottom
matrix colour (dry and moist)
mottling
presence of roots
Chemical attributes*
organic carbon
total N
available P
pH-H2O
pH-KCl
pH-CaCl2
electrical conductivity (EC)
free CaCO3
CaSO4
exchangeable Ca2+
exchangeable Mg2+
exchangeable Na+
exchangeable K+
exchangeable Al3+ + H+ (exchangeable
acidity)
exchangeable Al3+ (exchangeable aluminum)
cation exchange capacity (CEC)
effective CEC (at field pH)
base saturation (as percent of CEC)
Physical attributes*
structure type
particle size distribution:
weight % sand
weight % silt
weight % clay
stone and gravel content
bulk density
volume per cent water held at specified suctions
hydraulic conductivity at specified suctions
WISE, World Inventory of Soil Emission Potentials; * Analytical methods are specified in a
separate key-attribute file.
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 5
made at the Lincoln laboratory (USDA, 1984). These analytical methods compare well
with those used at ISRIC (Kimble and Van Reeuwijk, pers. comm., 1994). Whereas
profiles originating from the SDB database (FAO, 1989) have been described using the
same guidelines which ISRIC used, the chemical and physical analyses have taken place
in different laboratories (FAO-Unesco, 1971-1981). Therefore, it is not always possible
to compare all SDB data sets directly with those of NRCS and ISIS (see Vogel, 1994).
2.4 Criteria for accepting profile data
Strict criteria have been defined for accepting profiles into WISE: (a) completeness and
apparent reliability of data; (b) traceability of source of data; (c) classifiable in the
FAO-Unesco (1974) legend; and (d) geo-referenced within defined limits. Profiles from
the "international" data holders have been off-loaded to WISE using an automated data-
transfer facility (Tempel, 1994). Procedures, called map-files, have been developed for
the transfer of data from the NRCS, SDB and ISIS databases to WISE 2.1
(Zunnenberg, unpublished data, 1994). Following the initial transfer to a WISE-
compatible dBASE® format, the integrity of the transferred data was checked by a
second computer module. It is only after this second operation that the "screened" data
sets were appended to the main WISE database files. Inherently, the use of an
automated transfer facility will encompass some loss of information (Tempel, 1994).
The original reference number of a soil profile is documented in the WISE database
files. In all cases, the source of data and laboratory where the analyses have been
carried out are specified (see Appendix 3). The WISE attribute-definition files which
are provided with the "international" data set should never be tampered with in any
way, because this will affect the integrity of the database.
2.5 Selection of "international" profiles
An extraction module was written for the mechanical extraction of the "international"
profiles stored in the WISE database. The selected profiles are from various regions of
the globe, with few profiles originating from Europe (Table 2). A data set of European
profiles is being compiled in a separate activity by the European Union (Madsen and
Jones, 1995), but so far unresolved copyright matters seem to have hindered its release
to third parties.
INTERNATIONAL SOIL PROFILE DATA SET
6ISRIC Work. Pap. 95/10b
Table 2. Summary of number of profiles per broad geographic area (total= 1,125)
WISE area Total
Africa 315
Australia and Pacific Islands 56
China, India, Indonesia & Philippines 280
Europe 7
North America 158
South America and Caribbean 241
South west and Northern Asia (Siberia) 68
Appendix 1 lists the countries from where the soil profiles originate. The classification
of these soils is presented in Appendix 2. All profiles from the NRCS data set have
been classified at ISRIC into the original (FAO-Unesco, 1974) and revised (FAO,
1990a) legend (see Spaargaren and Batjes, 1995). About 94 % of the 1,125 profiles are
classified in the Revised Legend (FAO, 1990a) and about 88 % according to Soil
Taxonomy (Soil Survey Staff, 1994 and earlier versions).
2.6 Sources of uncertainty
Initial printouts obtained from the NRCS, SDB and ISIS data sets after transfer into
WISE sometimes contained distorted soil horizon designations and duplicate horizon
depths. This was partly associated with the fact that soil horizon and sample depths
were not always defined unambiguously in the source data files. Whenever possible,
these "data issues" have been remedied manually with reference to the original data sets.
Differences in versions of USDA Soil Taxonomy used in the NRCS source files formed
a difficulty when classifying profiles according to the FAO Legend. Similarly, different
horizon designations are used in the various "international" data sets.
In some cases, profiles held in the source data files differed from those published
elsewhere for the same profiles. This was the case for some NRCS profiles from Brazil,
Korea and Zambia (see Spaargaren and Batjes, 1995), some SDB profiles from
Botswana (see FAO, 1990b), and some ISIS profiles. This aspect illustrates the
difficulty in preserving data integrity in digital files since their contents can easily be
corrupted. In most cases, data sets obtained from NRCS, SDB and ISIS were taken at
"face value" in view of the fact that they have been officially released for inclusion in
the WISE database. Nonetheless, all transferred data sets have been submitted to
WISE's computerized and rigorous data-checking scheme leading to rejection of some
of the profiles (see Section 2.4).
In case of missing latitude-longitude references, approximate coordinates have been
derived from the Times Atlas (1993), using general information on location (e.g.,
Machakos, Kenya).
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 7
3. Discussion and conclusions
Version 1.0 of the "international" data set is being released with the implicit
understanding that the source will be acknowledged in all publications arising from use
of the data. The "international" data set is particularly meant for those scientists who
wish to study "primary" soil data. Files are presented in dBASE® IV format using the
WISE database structure and coding conventions (see Batjes, 1995).
The "international" data sets held in WISE have been proposed to serve as the nucleus
for a global profile data set to be developed by the Global Soil Data Task Group of
IGBP-DIS (Scholes et al., 1994). The data set discussed in this paper, with a selection
of soil profiles from three major international holders of soil data — NRCS, FAO and
ISRIC —, is to provide the initial soil profile data for this collaborative activity.
It is anticipated that new releases of the "international" data set will be prepared as new
profile data are being added to the WISE database, notably about 400 profiles from
ISRIC's project on National Soil Reference and Database Collections (NASREC).
The WISE database proper, which currently contains over 4,300 profiles, is being used
by ISRIC to generate a series of uniform data sets of derived soil properties, linked to
a ½E longitude by ½E latitude version of the edited and digital Soil Map of the World
(FAO, 1991), for subsequent use by global modellers.
Acknowledgements
As with any collaborative activity, the WISE project has been carried out with the help of
many people. The data held in the current "international" data set have been obtained from
various organisations including: (a) the Natural Resources Conservation Service (USDA-
NRCS, formerly SCS) at Lincoln, and J.M. Kimble in particular; (b) FAO's Land and Water
Development Division (AGL), notably F.O. Nachtergaele; and (c) ISRIC, particularly J.H.
Kauffman co-ordinator of the NASREC/ISIS project. Crucial, auxiliary software for the
digital transfer of data obtained from these organisations to the WISE database structure was
developed and tested at ISRIC by P. Tempel. The accompanying "map files" were elaborated
by W. Zunnenberg. All profiles transferred from the NRCS data tape have been checked and
classified in the FAO-Unesco system by O.C. Spaargaren under a subcontract with IGBP-DIS.
All profiles derived from ISIS were manually checked by E.M. Bridges. Constructive
comments on creating the "international" data set were received from W.V.P. van Engelen
and L.R. Oldeman. The contributions of ISRIC's staff in the WISE project activities, and those
of E.M. Bridges in particular, are gratefully acknowledged.
The WISE data handling system has been developed at ISRIC for a project on the
Geographic Quantification of Soil Factors and Processes that Control Fluxes of Greenhouse
Gases —known as World Inventory of Soil Emission Potentials (WISE)— with sponsorship
from the Netherlands National Research Programme on Global Air Pollution and Climate
Change (Project 851039).
References
Batjes, N. H., 1995. World Inventory of Soil Emission Potentials: WISE 2.1 - Profile
Database User Manual and Coding Protocols. Technical Paper 26, ISRIC, Wageningen.
INTERNATIONAL SOIL PROFILE DATA SET
8ISRIC Work. Pap. 95/10b
Batjes, N. H. and E. M. Bridges, 1994. Potential Emissions of Radiatively Active Gases from
Soil to Atmosphere with Special Reference to Methane: Development of a Global Database
(WISE). J. Geophys. Res. 99(D8): 16,479-16,489.
Batjes, N. H., E. M. Bridges and F. O. Nachtergaele, 1995. World Inventory of Soil Emission
Potentials: Development of a Global Soil Database of Process Controlling Factors. In:
Climate Change and Rice (Editors S. Peng et al. ), Springer-Verlag, Heidelberg, pp. 102-
115.
FAO, 1989. FAO-ISRIC Soil Database — SDB. World Soil Resources Report 60 (Reprinted),
FAO, Rome.
FAO, 1991. Digitized Soil Map of the World. World Soil Resources Report 67, FAO, Rome.
FAO-Unesco, 1974. Soil Map of the World. Volume I: Legend. Unesco, Paris.
FAO, 1990a. FAO-Unesco Soil Map of the World: Revised Legend. World Soil Resources
Report 60, FAO, Rome [Reprinted as Technical Paper 20, ISRIC, Wageningen, 1994].
FAO, 1990b. Explanatory note on the Soil Map of the Republic of Botswana. AG-
BOT/85/011, FAO, UNDP and Republic of Botswana, Gaborone.
FAO-ISRIC, 1990. Guidelines for Soil Description. FAO, Rome.
Ingram, J. S. I. (ed.), 1993. IGBP-DIS & GCTE Global Soils Database Workshop. Meeting
held at the Soil Survey and Land Research Centre, Silsoe (8-9 October 1992), IGBP-DIS
Working Paper 7, Paris.
Madsen, H. B. and R.J.A. Jones, 1995. The establishment of a soil profile analytical database
for the European Union. In European Land Information Systems for Agro-environmental
Monitoring (Editors D. King, R.J.A. Jones and A.J. Thomasson), Office for Official
Publications of the European Communities, Luxembourg, pp. 55-63.
Scholes, R. J., D. Skole and J. S. Ingram, 1994. A Global Database of Soil Properties:
Proposal for Implementation. IGBP-DIS Working Paper 10, International Geosphere
Biosphere Program, Data and Information System, Paris.
Soil Survey Staff, 1993. Soil Survey Manual (revised and enlarged edition). United States
Department of Agriculture, Handbook No. 18, Washington D.C.
Soil Survey Staff, 1994. Keys to Soil Taxonomy (Sixth Edition). United States Department of
Agriculture, Soil Conservation Service, Washington D.C.
Spaargaren, O.C. and N.H. Batjes, 1995. Report on the classification into FAO-Unesco Soil
Units of Profiles Selected from the NRCS Pedon Database for IGBP-DIS. Working Paper
and Preprint 95/01, ISRIC, Wageningen.
Tempel, P., 1994. Data Transfer Facility between Disparate Soil Databases. Working Paper
and Preprint 94/08, International Soil Reference and Information Centre, Wageningen.
Times Atlas, 1993. The Times Atlas of the World. Times Books, Harper Collins Publ.,
London.
Van de Ven, T. and P. Tempel, 1994. ISIS 4.0 - ISRIC Soil Information System: User
Manual. Technical Paper 15 (rev. ed.), International Soil Reference and Information
Centre, Wageningen.
Van Reeuwijk, L. P., 1992. Procedures for Soil Analysis (Third ed.). Technical Paper 19,
International Soil Reference and Information Centre, Wageningen.
Zuidema, G., G.J. van den Born, J. Alcamo and G.J.J. Kreileman, 1994. Simulation of global
land cover changes as affected by economic factors and climate. Water, Air and Soil
Pollution, 76: 163-198.
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 9
Appendices
Appendix 1. Number of profiles per country in “international”data set.
Country Total
AR - Argentina 5
AU - Australia 15
BD - Bangladesh 3
BE - Belgium 1
BF - Burkina Faso 1
BI - Burundi 12
BR - Brazil 69
BW - Botswana 33
CA - Canada 2
CI - Cote d'Ivoire 12
CK - Cook Islands 1
CL - Chile 6
CM - Cameroon 34
CN - China 50
CO - Colombia 27
CR - Costa Rica 28
CU - Cuba 21
DE - Germany, Fed. Rep. of 1
DZ - Algeria 4
EC - Ecuador 16
FI - Finland 1
GN - Guinea 1
GT - Guatemala 11
GY - Guyana 3
HN - Honduras 8
ID - Indonesia 58
IN - India 49
IT - Italy 1
JO - Jordan 14
JP - Japan 4
KE - Kenya 32
KR - Korea, Republic of 15
LB - Lebanon 2
LS - Lesotho 15
MA - Morocco 5
Country Total
ML - Mali 14
MX - Mexico 4
MY - Malaysia 2
MZ - Mozambique 1
NC - New Caledonia 1
NE - Niger 11
NG - Nigeria 1
NI - Nicaragua 21
NP - Nepal 5
NZ - New Zealand 5
PA - Panama 14
PG - Papua New Guinea 16
PH - Philippines 42
PK - Pakistan 37
PR - Puerto Rico 1
RO - Romania 1
RW - Rwanda 6
SB - Solomon Islands 1
SD - Sudan 46
SL - Sierra Leone 1
SN - Senegal 2
SV - El Salvador 5
SY - Syrian Arab Republic 6
TH - Thailand 35
TN - Tunisia 15
TO - Tonga 2
TW - Taiwan 0
UG - Uganda 12
US - United States 154
VE - Venezuela 6
WS - Samoa 14
YE - Yemen 26
ZA - South Africa 4
ZM - Zambia 37
ZW - Zimbabwe 16
INTERNATIONAL SOIL PROFILE DATA SET
10 ISRIC Work. Pap. 95/10b
Appendix 2. Soil units represented in "international" data set
(FAO-Unesco, 1974).
A: Acrisols
Af= 53 Ag= 12 Ah= 34 Ao= 25 Ap= 15
B: Cambisols
Bc= 11 Bd= 25 Be= 36 Bf= 31 Bg= 7 Bh= 15 Bk= 32 Bv= 12 Bx= 0
C: Chernozems
Cg= 0 Ch= 1 Ck= 5 Cl= 0
D: Podzoluvisols
Dd= 1 De= 2 Dg= 0
E: Rendzinas
E = 3
F: Ferralsols
Fa= 10 Fh= 31 Fo= 25 Fp= 3 Fr= 16 Fx= 18
G: Gleysols
Gc= 1 Gd= 11 Ge= 25 Gh= 3 Gm= 10 Gp= 2 Gx= 4
H: Phaeozems
Hc= 10 Hg= 9 Hh= 47 Hl= 21
I: Lithosols
I = 0
J: Fluvisols
Jc= 14 Jd= 6 Je= 14 Jt= 7
K: Kastanozems
Kh= 1 Kk= 1 Kl= 0
L: Luvisols
La= 4 Lc= 33 Lf= 44 Lg= 7 Lk= 5 Lo= 38 Lp= 5 Lv= 3
M: Greyzems
Mg= 0 Mo= 1
N: Nitosols
Nd= 6 Ne= 15 Nh= 1
O: Histosols
Od= 3 Oe= 0 Ox= 0
P: Podzols
Pf= 0 Pg= 1 Ph= 6 Pl= 2 Po= 4 Pp= 4
Q: Arenosols
Qa= 3 Qc= 9 Qf= 3 Ql= 3
R: Regosols
Rc= 8 Rd= 6 Re= 16 Rx= 0
S: Solonetz
Sg= 4 Sm= 0 So= 20
T: Andosols
Th= 43 Tm= 14 To= 3 Tv= 20
U: Rankers
U = 0
V: Vertisols
Vc= 66 Vp= 38
W: Planosols
Wd= 0 We= 3 Wh= 0 Wm= 1 Ws= 7 Wx= 0
X: Xerosols
Xh= 7 Xk= 8 Xl= 11 Xy= 5
Y: Yermosols
Yh= 5 Yk= 4 Yl= 9 Yt= 0 Yy= 4
Z: Solonchaks
Zg= 1 Zm= 1 Zo= 11 Zt= 1
* For abbreviations see FAO-Unesco (1974), e.g. Af stands for Ferric
Acrisols.
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 11
Appendix 3. Examples of listings of SDB, ISIS and NRCS profiles.
BR054 W I S E S O I L P R O F I L E D A T A S H E E T 21/06/95
====================================================
SOIL CLASSIFICATION:
FAO-Unesco Legend (1974): Ferric Luvisol (Lf) Phase: -- (-) Topsoil texture: coarse (C)
FAO-Unesco Legend (1990): Ferric Luvisol (LVf) Phase: -- (-)
USDA Soil Taxonomy (19--): -
Local Classification System: -
SOURCES:
Source_ID: FAO/SDB Ref. page: FAO-SDB profile: 021011
Lab_ID: XX01 Descr. status: routine description (2)
Desc. (MM/YY): 01/66
SITE DATA:
Location: 9 Km SW Marilia, Sao Paulo state (Brazil)
Coordinates: Lat.: S 22 deg. 19 min. -- sec. Lon.: W 050 deg. 00 min. -- sec.
Altitude: 620 m
Landform: -- (-)
Position: -- (-)
Aspect: -
Slope: - %
Drainage class: moderately well drained (M)
Groundwater: -1 to -1 (cm)
Eff. soil depth > -1 (cm)
Parent material: sandstone, greywacke, arkose (SC2) (Remarks: -)
Koppen climate: Equat. humid with dry season in low-sun season (driest month <60;Tcm > 18C) (Aw)
Land use (LU): -- (-)
Main crop: coffee (CF)
Vegetation (VE): -- (-)
Remarks on LU/VE: -
HORIZON DATA:
---------------------------------------------------------------------------------------------------------------------------
Horiz. Depth Org. Tot. Av. pH ECx CACO GYPS Exch. bases and acidity CEC ECEC BS
C N P -------------- 3 UM -------------------------------- ----------
Desig. (cm) (%) (%) H2O KCl CaCl2 (%) (%) Ca Mg K Na Ac Al (meq/100g) (%)
---------------------------------------------------------------------------------------------------------------------------
Ap 0- 20 0.40 0.05 2.3 6.3 -1.0 5.5 -1.00 -1.0 -1.0 3.0 0.2 0.1 0.0 -1.0 -1.0 4.0 -1.0 83
E 20- 42 0.10 0.02 2.3 6.6 -1.0 5.6 -1.00 -1.0 -1.0 1.8 0.2 0.0 0.0 -1.0 -1.0 2.5 -1.0 80
B1 42- 77 0.20 0.06 2.3 6.4 -1.0 5.3 -1.00 -1.0 -1.0 4.3 1.0 0.1 0.0 -1.0 -1.0 6.0 -1.0 90
B2 77- 97 0.20 0.02 2.3 6.2 -1.0 5.2 -1.00 -1.0 -1.0 3.5 0.9 0.1 0.0 -1.0 -1.0 5.4 -1.0 83
BC 97-209 0.10 0.02 2.3 6.4 -1.0 5.8 -1.00 -1.0 -1.0 2.6 0.7 0.1 0.0 -1.0 -1.0 4.4 -1.0 80
---------------------------------------------------------------------------------------------------------------------------
---------------------------------------------------------------------------------------------------------------------------
Horiz. Colour M R ST Sand Silt Clay GR Bd % vol/vol moisture held at a pF of AWC HCs HCu
-------------- (%) (%) (%) (%) ------------------------------------------- (%v/v) (cm/hr)
Desig. Dry Moist 0.0 1.0 1.5 1.7 2.0 2.3 2.5 2.7 3.4 3.7 4.2
---------------------------------------------------------------------------------------------------------------------------
Ap - 5YR3/3 - M - 91 3 6 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
E - 5YR4/3 - M - 94 2 4 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
B1 - 2.5YR4/4 C M SB 73 2 25 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
B2 - 2.5YR3/6 F F - 74 2 24 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
BC - 5YR4/6 - F - 80 2 18 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
---------------------------------------------------------------------------------------------------------------------------
Abbr.: Av. P as mg P2O5/kg soil; ECx= electrical conductivity in dS/m; Ac= exchangeable (H + Al) in meq/100g;
BS= base saturation (% of CEC); M= mottles; R= roots; ST= structure; GR = % > 2mm size; Bd= bulk density
(g/cm3); HC= hydr. conduct., saturated (HCs) resp. unsat. (HCu) in cm/hr; AWC= av. moisture in v/v %; -1
stands for missing numeric values and - for missing alphanumeric values.
REMARKS:
SDB-profile= BR011.
REFERENCES:
a) Source of profile data [FAO/SDB-2]:
Various authors (see relevant FAO reports), 1994. Selected soils from FAO's Soil Data Base
(SDB; May 94); transfer map-files prepared by W. Zunnenberg. Data from FAO, Rome.
INTERNATIONAL SOIL PROFILE DATA SET
12 ISRIC Work. Pap. 95/10b
b) Laboratory name and methods [XX01]:
General methods as described in FAO-Unesco Soil Map of the World.
-------------------------------------------------------------------------------------------------------------------
Analytical method Code and description
-------------------------------------------------------------------------------------------------------------------
Organic Carbon: OC01: Method of Walkley-Black (Org. matter = Org. C x 1.72)
Total Nitrogen: TN01: Method of Kjeldahl
Available P: TP99: Method not defined
pH-H2O: PH02: pH 1:2.5 soil/water solution
pH-KCl: PK02: pH in 1:2.5 soil/ M KCl solution
pH-CaCl2: PC02: pH in 1:2.5 soil/1 M CaCl2 solution
Electr. conductivity: EL04: Elec. conductivity in saturated paste (ECe)
CaCO3 content: CA04: Calcimeter method (volumetric after adition of dilute acid)
Gypsum content: GY01: Dissolved in water and precipitated by acetone
Exch. Ca, Mg, Na and K: EX01: Various methods with no apparent differences in results
Exch. acidity and aluminum: EA--: Not measured
CEC soil: CS01: CEC in 1M NH4OAc buffered at pH 7
Effective CEC: CE--: Not measured
Base saturation: BS01: Sum of bases as percentage of CEC (method specified above)
Particle size analysis: TE01: Pipette method, with appropriate dispersion treatment (c< 0.002 <si< 0.05 <sa< 2mm)
Bulkdensity: BD--: Not measured
Soil moisture content: MC--: Not measured
Hydraulic conductivity: HC--: Not measured
------------------------------------------------------------------------------------------------------------------
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 13
BR069 W I S E S O I L P R O F I L E D A T A S H E E T 21/06/95
====================================================
SOIL CLASSIFICATION:
FAO-Unesco Legend (1974): Ferric Luvisol (Lf) Phase: -- (-) Topsoil texture: coarse (C)
FAO-Unesco Legend (1990): Haplic Lixisol (LXh) Phase: -- (-)
USDA Soil Taxonomy (1992): Typic Kanhaplustalf
Local Classification System: Podzolico vermelho
SOURCES:
Source_ID: ISIS-0994 Ref. page: ISIS4 [BR001]
Lab_ID: NL01 Descr. status: reference pedon (1)
Desc. (MM/YY): 10/84
SITE DATA:
ocation: Rio de Janeiro, Itaguai (Brazil)
Coordinates: Lat.: S 22 deg. 45 min. 0 sec. Lon.: W 43 deg. 41 min. 0 sec.
Atitude: 45 m
Landform: plain (slope 0-8 %; relief int. < 100 m/km) (LP)
osition: lower slope (LS)
Aspect: -
Slope: 20 %
Drainage class: -- (-)
Groundwater: -1 to -1 (cm)
Eff. soil depth > 180 (cm)
Parent material: metamorphic rocks (M) (Remarks: Weathered rock)
Koppen climate: Equat. humid with dry season in low-sun season (driest month <60;Tcm > 18C) (Aw)
Land use (LU): extensive grazing (HE)
Main crop: -- (-)
Vegetation (VE): herbaceous (H)
Remarks on LU/VE: occ. subsistence farming
HORIZON DATA:
---------------------------------------------------------------------------------------------------------------------------
Horiz. Depth Org. Tot. Av. pH ECx CACO GYPS Exch. bases and acidity CEC ECEC BS
C N P -------------- 3 UM -------------------------------- ----------
Desig. (cm) (%) (%) H2O KCl CaCl2 (%) (%) Ca Mg K Na Ac Al (meq/100g) (%)
---------------------------------------------------------------------------------------------------------------------------
Ap 0- 14 0.95 0.09 -1.0 4.5 4.1 -1.0 0.20 0.0 0.0 1.0 0.5 0.2 0.1 -1.0 -1.0 3.7 1.8 49
E1 14- 30 0.42 -1.00 -1.0 4.7 3.9 -1.0 0.05 0.0 0.0 1.0 0.3 0.0 0.1 -1.0 -1.0 2.1 1.4 67
E2 30- 38 0.38 -1.00 -1.0 4.9 3.9 -1.0 0.04 0.0 0.0 0.8 0.4 0.0 0.1 -1.0 -1.0 2.6 1.3 50
Bt1 38- 50 0.27 -1.00 -1.0 6.5 5.4 -1.0 0.02 0.0 0.0 0.8 2.3 0.1 0.1 -1.0 -1.0 3.9 3.3 85
Bt2 50- 80 0.34 -1.00 -1.0 5.8 4.4 -1.0 0.02 0.0 0.0 1.4 0.9 0.1 0.1 -1.0 -1.0 3.5 2.5 71
Bt3 80-100 0.18 -1.00 -1.0 5.8 4.2 -1.0 0.02 0.0 0.0 1.2 1.0 0.0 0.2 -1.0 -1.0 4.4 2.4 55
CB 100-157 0.13 -1.00 -1.0 5.6 3.9 -1.0 0.02 0.0 0.0 0.6 1.5 0.0 0.2 -1.0 -1.0 5.0 2.3 46
C 157-180 -1.00 -1.00 -1.0 5.5 3.4 -1.0 0.02 0.0 0.0 0.8 2.0 0.1 -1.0 -1.0 -1.0 7.7 2.9 38
---------------------------------------------------------------------------------------------------------------------------
---------------------------------------------------------------------------------------------------------------------------
Horiz. Colour M R ST Sand Silt Clay GR Bd % vol/vol moisture held at a pF of AWC HCs HCu
-------------- (%) (%) (%) (%) ------------------------------------------- (%v/v) (cm/hr)
Desig. Dry Moist 0.0 1.0 1.5 1.7 2.0 2.3 2.5 2.7 3.4 3.7 4.2
---------------------------------------------------------------------------------------------------------------------------
Ap 10YR6/2 10YR4/2 N MV SB 69 16 15 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
E1 10YR6/3 10YR5/4 N CV MA 64 15 21 -1 1.57 36 35 29 -1 23 21 -1 18 15 -1 14 15 -1.0 -1.0
E2 10YR6/3 10YR5/4 N VV MA 61 13 26 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
Bt1 5YR6/6 2.5YR4/6 N VV SB 28 12 60 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
Bt2 2.5YR6/6 2.5YR4/6 N VV SB 35 16 49 -1 1.43 43 41 38 -1 35 33 -1 32 30 -1 27 11 -1.0 -1.0
Bt3 5YR6/6 4YR4/6 N - SB 38 20 42 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
CB 7.5YR6/6 5YR4/6 N - MA 45 26 29 -1 1.54 41 40 38 -1 34 32 -1 30 24 -1 21 17 -1.0 -1.0
C - - - - - 55 26 19 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1.0 -1.0
---------------------------------------------------------------------------------------------------------------------------
Abbr.: Av. P as mg P2O5/kg soil; ECx= electrical conductivity in dS/m; Ac= exchangeable (H + Al) in meq/100g;
BS= base saturation (% of CEC); M= mottles; R= roots; ST= structure; GR = % > 2mm size; Bd= bulk density
(g/cm3); HC= hydr. conduct., saturated (HCs) resp. unsat. (HCu) in cm/hr; AWC= av. moisture in v/v %; -1
stands for missing numeric values and - for missing alphanumeric values.
REMARKS:
A deep, moderately well drained, red clay soil derived from gneiss; having a yellowish brown,
porous, sandy (clay) loam topsoil. The B horizons show coating of illuvial clay and limited
permeability.
REFERENCES:
a) Source of profile data [ISIS-0994]:
Various authors (see relevant ISRIC Country Reports), 1994. ISIS data set of September 1994
(J.H. Kauffman); transfer map-file produced by W. Zunnenberg. See: Van de Ven, T. and P. Tempel, 1994.
ISIS 4 - User Manual. Technical Paper 15, ISRIC, Wageningen.
INTERNATIONAL SOIL PROFILE DATA SET
14 ISRIC Work. Pap. 95/10b
b) Laboratory name and methods [NL01]:
International Soil Reference and Information Centre (ISRIC) laboratory, Wageningen, The Netherlands.
-------------------------------------------------------------------------------------------------------------------
Analytical method Code and description
-------------------------------------------------------------------------------------------------------------------
Organic Carbon: OC01: Method of Walkley-Black (Org. matter = Org. C x 1.72)
Total Nitrogen: TN01: Method of Kjeldahl
Available P: TP18: Bray-I (acid soils) resp. Olsen (other soils)
pH-H2O: PH02: pH 1:2.5 soil/water solution
pH-KCl: PK02: pH in 1:2.5 soil/ M KCl solution
pH-CaCl2: PC--: Not measured
Electr. conductivity: EL04: Elec. conductivity in saturated paste (ECe)
CaCO3 content: CA03: Method of Piper
Gypsum content: GY01: Dissolved in water and precipitated by acetone
Exch. Ca, Mg, Na and K: EX01: Various methods with no apparent differences in results
Exch. acidity and aluminum: EA01: Exchangeable acidity (H+Al) in 1 M KCl
CEC soil: CS01: CEC in 1M NH4OAc buffered at pH 7
Effective CEC: CE01: Sum of exch. Ca, Mg, K and Na, plus exchangeable aluminium (in 1M KCl)
Base saturation: BS01: Sum of bases as percentage of CEC (method specified above)
Particle size analysis: TE01: Pipette method, with appropriate dispersion treatment (c< 0.002 <si< 0.05 <sa< 2mm)
Bulkdensity: BD01: Core sampling (pF rings)
Soil moisture content: MC01: sand/silt baths and porous plates, undisturbed samples (pF rings)
Hydraulic conductivity: HC--: Not measured
-----------------------------------------------------------------------------------------------------------------
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 15
BR097 W I S E S O I L P R O F I L E D A T A S H E E T 21/06/95
====================================================
SOIL CLASSIFICATION:
FAO-Unesco Legend (1974): Humic Acrisol (Ah) Phase: -- (-) Topsoil texture: fine (F)
FAO-Unesco Legend (1990): Haplic Ferralsol (FRh) Phase: -- (-)
USDA Soil Taxonomy (1994): Humic Kandiudox
Local Classification System: [USDA-code: audparh]
SOURCES:
Source_ID: NRCS-USDA Ref. page: SCS profile code 8500725 (Brazil 7)
Lab_ID: US01 Descr. status: reference pedon (1)
Desc. (MM/YY): 04/85
SITE DATA:
Location: Highway SP127, Piracicaba-Rio Claro (Brazil)
Coordinates: Lat.: S 22 deg. 34 min. -- sec. Lon.: W 047 deg. 35 min. -- sec.
Altitude: 630 m
Landform: -- (-)
Position: middle slope (MS)
Aspect: -
Slope: 008 %
Drainage class: well drained (W)
Groundwater: -1 to -1 (cm)
Eff. soil depth > -1 (cm)
Parent material: slate, phyllite (peliticrocks) (MB1) (Remarks: Reworked pelitic colluvium from argillites/shales)
Koppen climate: Humid subtrop. with dry period in low-sun season (Tcm > 0C; Twm > 22C) (Caw)
Land use (LU): perennial field cropping (AP)
Main crop: sugarcane (SC)
Vegetation (VE): evergreen forest (FE)
Remarks on LU/VE: -
HORIZON DATA:
---------------------------------------------------------------------------------------------------------------------------
Horiz. Depth Org. Tot. Av. pH ECx CACO GYPS Exch. bases and acidity CEC ECEC BS
C N P -------------- 3 UM -------------------------------- ----------
Desig. (cm) (%) (%) H2O KCl CaCl2 (%) (%) Ca Mg K Na Ac Al (meq/100g) (%)
---------------------------------------------------------------------------------------------------------------------------
Ap1 0- 11 4.54 0.35 -1.0 6.1 5.0 6.0 -1.00 -1.0 -1.0 18.1 2.3 1.0 -1.0 10.6 0.1 17.7 -1.0 -1
Ap2 11- 19 2.01 0.15 -1.0 5.3 4.7 5.1 -1.00 -1.0 -1.0 6.8 1.4 0.5 0.1 11.4 -1.0 11.6 -1.0 76
Bto1 19- 43 1.15 0.08 -1.0 4.6 4.3 4.4 -1.00 -1.0 -1.0 2.1 0.8 0.1 -1.0 11.2 1.1 7.4 -1.0 41
Bto2 43- 78 0.82 -1.00 -1.0 4.5 4.3 4.3 -1.00 -1.0 -1.0 0.9 0.4 -1.0 -1.0 10.9 1.2 6.8 -1.0 21
Bo1 78-190 0.47 0.04 -1.0 5.2 4.5 4.5 -1.00 -1.0 -1.0 0.2 0.2 -1.0 -1.0 10.1 0.4 5.9 -1.0 9
Bo2 190-290 0.25 -1.00 -1.0 5.3 4.4 4.4 -1.00 -1.0 -1.0 0.2 0.1 -1.0 -1.0 7.9 0.7 5.7 -1.0 7
BC 290-320 0.18 0.02 -1.0 5.2 4.0 4.2 -1.00 -1.0 -1.0 -1.0 0.2 -1.0 -1.0 8.8 2.6 6.8 -1.0 3
---------------------------------------------------------------------------------------------------------------------------
---------------------------------------------------------------------------------------------------------------------------
Horiz. Colour M R ST Sand Silt Clay GR Bd % vol/vol moisture held at a pF of AWC HCs HCu
-------------- (%) (%) (%) (%) ------------------------------------------- (%v/v) (cm/hr)
Desig. Dry Moist 0.0 1.0 1.5 1.7 2.0 2.3 2.5 2.7 3.4 3.7 4.2
---------------------------------------------------------------------------------------------------------------------------
Ap1 5YR3/3 5YR3/3 - CM GR 18 21 61 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 22 -1 -1.0 -1.0
Ap2 5YR4/4 2.5YE3/6 - CM SB 17 16 67 -1 1.48 -1 -1 -1 -1 30 -1 29 -1 -1 -1 21 9 -1.0 -1.0
Bto1 2.5YR5/6 2.5YR3/6 - CM SB 11 12 77 -1 1.39 -1 -1 -1 -1 33 -1 32 -1 -1 -1 25 8 -1.0 -1.0
Bto2 2.5YR5/6 2.5YR4/6 - CM SB 11 13 76 -1 1.16 -1 -1 -1 -1 36 -1 34 -1 -1 -1 26 10 -1.0 -1.0
Bo1 2.5YR4/6 2.5YR4/6 - F GR 12 15 73 -1 1.22 -1 -1 -1 -1 36 -1 33 -1 -1 -1 26 10 -1.0 -1.0
Bo2 2.5YR5/6 10R4/6 - F - 15 23 62 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 26 -1 -1.0 -1.0
BC 10YR5/6 10R5/6 - F - 14 34 52 -1 -1.0 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 27 -1 -1.0 -1.0
---------------------------------------------------------------------------------------------------------------------------
Abbr.: Av. P as mg P2O5/kg soil; ECx= electrical conductivity in dS/m; Ac= exchangeable (H + Al) in meq/100g;
BS= base saturation (% of CEC); M= mottles; R= roots; ST= structure; GR = % > 2mm size; Bd= bulk density
(g/cm3); HC= hydr. conduct., saturated (HCs) resp. unsat. (HCu) in cm/hr; AWC= av. moisture in v/v %; -1
stands for missing numeric values and - for missing alphanumeric values.
REMARKS:
None.
REFERENCES:
a) Source of profile data [NRCS-USDA]:
Soil Survey Staff (Dr J.M. Kimble; FAO class. by Dr O.C. Spaargaren), 1994. Collection of profiles
derived from data-tape provided by SCS laboratory (now NRCS) at Lincoln, NE. Soil Taxonomy
('75, '90, '94)
INTERNATIONAL SOIL PROFILE DATA SET
16 ISRIC Work. Pap. 95/10b
b) Laboratory name and methods [US01]:
Soil Conservation Service (now NRCS), Lincoln, Nebraska
-------------------------------------------------------------------------------------------------------------------
Analytical method Code and description
--------------------------------------------------------------------------------------------------------------------
Organic Carbon: OC01: Method of Walkley-Black (Org. matter = Org. C x 1.72)
Total Nitrogen: TN01: Method of Kjeldahl
Available P: TP18: Bray-I (acid soils) resp. Olsen (other soils)
pH-H2O: PH02: pH 1:2.5 soil/water solution
pH-KCl: PK02: pH in 1:2.5 soil/ M KCl solution
pH-CaCl2: PC--: Not measured
Electr. conductivity: EL04: Elec. conductivity in saturated paste (ECe)
CaCO3 content: CA03: Method of Piper
Gypsum content: GY01: Dissolved in water and precipitated by acetone
Exch. Ca, Mg, Na and K: EX01: Various methods with no apparent differences in results
Exch. acidity and aluminum: EA01: Exchangeable acidity (H+Al) in 1 M KCl
CEC soil: CS01: CEC in 1M NH4OAc buffered at pH 7
Effective CEC: CE01: Sum of exch. Ca, Mg, K and Na, plus exchangeable aluminium (in 1M KCl) *
Base saturation: BS01: Sum of bases as percentage of CEC (method specified above)
Particle size analysis: TE01: Pipette method, with appropriate dispersion treatment (c< 0.002 <si< 0.05 <sa< 2mm)
Bulkdensity: BD01: Core sampling (pF rings)
Soil moisture content: MC01: sand/silt baths and porous plates, undisturbed samples (pF rings)
Hydraulic conductivity: HC--: Not measured
--------------------------------------------------------------------------------------------------------------------
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 17
Appendix 4. Brief installation procedure
Installing WISE
The “international profile data set” is distributed mainly as “e-mail attachments”. The
WISE 2.1 data handling system and "international profile data set" can be installed on
IBM-compatible PC's (386 and up). The installation procedure must start from within
the directory to which the installation files were transferred initially as e-mail
attachments. The relevant files are WISSETUP.BAT and WISSETUP.ZIP. A
shareware copy of PKZIP#, which is necessary to decompress WISSETUP.ZIP, is
attached also.
To install the data set and data handling system from the DOS prompt (or with RUN
option under WINDOWS) simply start in the directory where your e-mail files arrive
(e.g. C:\E_MAIL):
C:\E_MAIL> WISSETUP
WISSETUP.BAT first creates C:\WISE, with appropriate subdirectories, to which the
various program, system and data files will be copied. In order to access the data a
copy of the proprietary dBASE IV language, version 1.5 and up, is needed. The
datafiles proper however, being dbf-files, can be accessed with a range of software.
Prior to accessing the data set, a PATH must be set to the directory where dBASE IV
resides on the C-drive (C:\DB4), as well as a path to C:\WISE, by adding the following
statements to the AUTOEXEC.BAT file on the C-drive, e.g.:
PATH C:\; C:\DOS; .....; C:\DB4; C:\WISE; ..
The WISE data handling system was developed using dBASE IV, version 1.5. Please
note that if version 2.0 of dBASE IV is used, the file C:\DB4\CONFIG.DB must be
edited to include the following line:
LDCHECK = OFF
Once the above operations have been performed, the system must be re-booted so that
the new path-configuration becomes operational.
At this stage the WISE 2.1 data handling system and "international profile data set" can
be accessed by entering:
WISE
Full data base structure definitions, indexing conventions, and coding conventions may
be found in Appendix 5 to 7 (from Batjes, 1995).
INTERNATIONAL SOIL PROFILE DATA SET
18 ISRIC Work. Pap. 95/10b
Appendix 5. Structure and attributes of WISE database files
A) WISE database files
Structure for database: WISESITE.DBF
Field Name Type Width Dec Description
WISE_ID Character 5Unique profile reference number
LAB_ID Character 4Unique laboratory reference number
SOURCE_ID Character 10 Unique reference number for source of profile data
REFPAG Character 50 Profile/page reference in source
HORNUM Numeric 1Number of horizons described for pit (Y/N,
control variable)
FAO_74 Character 2FAO-Unesco (1974), classification as code
PHA_74 Character 2As above, but code for (main) phase
TOP_74 Character 1As above, but code for topsoil textural class
FAO_90 Character 3FAO-Unesco (1990), classification as code
PHA_90 Character 2As above, but code for (main) phase
USCL Character 50 USDA Soil Taxonomy classification, descriptive
USYR Character 2Year (version of Soil Taxonomy, e.g., 75, 94)
LOCAL Character 50 Local classification, descriptive
DESCR Character 1Profile description status, code
DATE Character 5Date profile was first described
COUN Character 2ISO code for country of origin
LOCAT Character 50 Location of profile, descriptive
LATIT Character 1Latitude of profile (N/S)
LATDEG Character 2 degrees
LATMIN Character 2 minutes
LATSEC Character 2 seconds
LONGI Character 1Longitude of profile (E/W)
LONDEG Character 3 degrees
LONMIN Character 2 minutes
LONSEC Character 2 seconds
ALTIT Numeric 4Elevation (m)
LFORM Character 2Landform, code
POSIT Character 2Position, code
ASPECT Character 3Aspect, code
SLOPE Character 3Slope at profile site (%)
DRAIN Character 2Drainage condition, code
GRWHI Numeric 4Average, highest groundwater level (cm)
GRWLO Numeric 4Average, lowest groundwater level (cm)
SOLDEP Numeric 4Average, soil depth to a physically limiting layer (cm)
PARMAT Character 3Parent material, code
PARREM Character 50 Remarks on parent material, descriptive
KOPPEN Character 3Köppen climate classification, code
LANDUS Character 3Land use, code
CROPS Character 2Crops, code
VEGCOD Character 2Vegetation, code
VEGREM Character 100 Remarks on either land use or vegetation, descriptive
REMARKS Character 5Data entry source code
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 19
Structure for database: WISEHOR.DBF
Field Name Type Width Dec Description
WISE_ID Character 5 Unique soil profile number
HORIZ Character 1Unique horizon number (in combination with WISE_ID)
DESIG Character 8Horizon designation, coded acc. to local system
TOPDEP Numeric 3Upper depth of horizon (cm)
BOTDEP Numeric 3Lower depth of horizon (cm)
DCOLOR Character 8Dry matrix colour, Munsell code
MCOLOR Character 8Moist matrix colour, Munsell code
MOTTLE Character 1Mottling, code
ROOTS Character 2Roots abundance/size, code
ORGC Numeric 5 2 Org. carbon (%, for method see keymethod.dbf)
TOTN Numeric 5 2 Total Nitrogen (%)
PTOT Numeric 5 1 Available phosphorus (mg P2O5 kg-1)
CACO3 Numeric 4 1 Calcium carbonate content (%)
GYPSUM Numeric 4 1Gypsum content (%)
PHH2O Numeric 4 1 pH measured in water
PHKCL Numeric 4 1 pH measured in KCl solution
PHCACL2 Numeric 4 1 pH measured in CaCl2 solution
ECE Numeric 5 2 Electrical conductivity (dS m-1 or mmho cm-1)
EXCA Numeric 5 1 Exchangeable calcium (cmol(+) kg-1)
EXMG Numeric 5 1 Exchangeable magnesium
EXNA Numeric 5 1 Exchangeable sodium
EXK Numeric 5 1 Exchangeable potassium
EXACID Numeric 5 1 Exchangeable acidity
EXALUM Numeric 5 1Exchangeable aluminum
CECSOIL Numeric 5 1 Cation exchange capacity (cmol(+) kg-1)
ECEC Numeric 5 1 Effective CEC (cmol(+) kg-1; 1 M KCl)
BSAT Numeric 3Base saturation, expressed as % of CEC
SAND Numeric 2Sand content (w/w%)
SILT Numeric 2Silt content (w/w%)
CLAY Numeric 2 Clay content (w/w%)
GRAVEL Numeric 2Gravel content (v/v %)
STRUCT Character 2Soil structure, code
BULKDENS Numeric 5 2 Bulk density (g cm-3)
PF Character 1Soil moisture content (Y/N, control variable)
PF00 Numeric 2Soil moisture content (% v/v) held at pF 0
PF10 Numeric 2As above, but at pF1.0
PF15 Numeric 2 As above, but at pF1.5
PF17 Numeric 2As above, but at pF1.7
PF20 Numeric 2As above, but at pF2.0
PF23 Numeric 2As above, but at pF2.3
PF25 Numeric 2As above, but at pF2.5
PF27 Numeric 2As above, but at pF2.7
PF34 Numeric 2As above, but at pF3.4
PF37 Numeric 2As above, but at pF3.7
PF42 Numeric 2As above, but at pF4.2
AWC Numeric 2Available water capacity
HC Character 1Hydraulic conductivity (control variable)
CONDSAT Numeric 4 1 Saturated conductivity (cm hr-1)
CONDUNSAT Numeric 4 1 Unsaturated conductivity (cm hr-1)
INTERNATIONAL SOIL PROFILE DATA SET
20 ISRIC Work. Pap. 95/10b
Structure for database: WISEANAD.DBF
Field Name Type Width Dec Description
WISE_ID Character 5Unique profile number
ADD Character 254 Remarks on profile, descriptive
Structure for database: WISESOUR.DBF
Field Name Type Width Dec Description
SOURCE_ID Character 10 Unique reference number for source of profile data
AUTHOR Character 70 Author name and initials
AUTYR Numeric 2Year of publication
REFTIT Character 100 Title of monograph/database, descriptive
REFPUB Character 100 Series/publisher/year, descriptive
Structure for database: WISELAB.DBF
Field Name Type Width Dec Description
LAB_ID Character 4Unique laboratory code
LABNAM Character 150 Reference to laboratory, descriptive
Structure for database: WISEATRIB.DBF
Field Name Type Width Dec Description
LAB_ID Character 4Unique laboratory code
ORGC Character 2Number-code of analytical method ( KEYMETHO.DBF)
TOTN Character 2As above, but for total nitrogen
PTOT Character 2As above, but for 'available' phosphorus
CACO3 Character 2As above, but for calcium carbonate content
GYPSUM Character 2As above, but for gypsum content
PHH2O Character 2As above, but for pH-water
PHKCL Character 2As above, but for pH-KCl
PHCACL2 Character 2As above, but for pH-CaCl2
ELECON Character 2As above, but for electrical conductivity
EXBAS Character 2As above, but for exchangeable Ca, Mg, K and Na
EXACID Character 2As above, but for exchangeable acidity
CECSOIL Character 2 As above, but for CEC
ECEC Character 2As above, but for ECEC
BSAT Character 2As above, but for base saturation
TEXTURE Character 2As above, but for texture (definition of esd-sizes + method)
BULKDENS Character 2As above, but for bulk density
MOISTCON Character 2As above, but for moisture content (pF measurements)
HYDROCON Character 2As above, but for hydraulic conductivity
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 21
B) Key-description conversion files
Structure for database: KEYAREA.DBF
Field Name Type Width Dec Description
KEY Character 2Unique identifier for broad geographic area
(e.g., AF for Africa)
REGION Character 150 Description of broad geographic area
Structure for database: KEYCOUN.DBF
Field Name Type Width Dec Description
ISO Character 2Country ISO code
COUNTRY Character 20 Country name, descriptive
REGION Character 2Unique identifier for broad geographic area
Structure for database: KEYCROPS.DBF
Field Name Type Width Dec Description
KEY Character 2Arable crops, code
CROPS Character 25 As above, but descriptive
Structure for database: KEYDRAIN.DBF
Field Name Type Width Dec Description
KEY Character 2Soil drainage class, code
DRAIN Character 40 As above, but descriptive
Structure for database: KEYFAO.DBF
Field Name Type Width Dec Description
KEYFAO90 Character 3FAO-Unesco (1990) Revised Legend, code
FAOUNIT90 Character 20 FAO-Unesco (1974) Legend, code
KEYFAO74 Character 2FAO-Unesco (1990) classification, descriptive
FAOUNIT74 Character 20 FAO-Unesco (1974) classification, descriptive
INTERNATIONAL SOIL PROFILE DATA SET
22 ISRIC Work. Pap. 95/10b
Structure for databases: C:\WISE\KEYFAO_1
Field Name Type Width Dec Description
KEYFAO74 Character 2FAO-Unesco (1974) Legend, 1st level codes only
FAOUNIT74 Character 20 FAO-Unesco (1974) Legend, descriptive
Structure for database: KEYKOPPE.DBF
Field Name Type Width Dec Description
KEY Character 4Unique identifier for Köppen climate code (e.g., Aw)
KOPPEN Character 115 Summary description of Köppen climate
Structure for database: KEYLANDF.DBF
Field Name Type Width Dec Description
KEY Character 2Landform, code
LFORM Character 90 As above, but descriptive
Structure for database: KEYLUS.DBF
Field Name Type Width Dec Description
KEY Character 3Land use, code
LANDUS Character 45 As above, but descriptive
Structure for database: KEYMETHOD.DBF
Field Name Type Width Dec Description
KEY Character 4Unique identifier code (such as "OC"+"01")
LABMETHOD Character 175 Summary description of laboratory method
Structure for database: KEYMOTTL.DBF
Field Name Type Width Dec Description
KEY Character 1Soil mottling, code
MOTTLE Character 20 As above, but descriptive
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 23
Structure for database: KEYPAREN.DBF
Field Name Type Width Dec Description
KEY Character 3Parent material, code
PARMAT Character 50 As above, but descriptive
Structure for database: KEYPH74.DBF
Field Name Type Width Dec Description
KEY Character 2Code for FAO-Unesco (1974) phase
PHA_74 Character 15 As above, but descriptive
Structure for database: KEYPH90.DBF
Field Name Type Width Dec Description
KEY Character 2Code for FAO-Unesco (1990) phase
PHA_90 Character 15 As above, but descriptive
Structure for database: KEYPOSIT.DBF
Field Name Type Width Dec Description
KEY Character 2Site position, code
POSITI Character 25 As above, but descriptive
Structure for database: KEYREGION.DBF
Field Name Type Width Dec Description
ISO Character 2Country ISO code
COUN Character 20 Country name, descriptive
REGION Character 2Code for broad region (see KEYAREA.DBF)
Structure for database: KEYROOTS.DBF
Field Name Type Width Dec Description
KEY Character 2Roots abundance and size, code
ROOTS Character 40 As above, but descriptive
INTERNATIONAL SOIL PROFILE DATA SET
24 ISRIC Work. Pap. 95/10b
Structure for database: KEYSTATU.DBF
Field Name Type Width Dec Description
KEY Character 1Profile description status, code
DESCR Character 25 As above, but descriptive
Structure for database: KEYSTRUC.DBF
Field Name Type Width Dec Description
KEY Character 2Soil structure, code
STRUCT Character 30 As above, but descriptive
Structure for database: KEYTEXT.DBF
Field Name Type Width Dec Description
KEY Character 1FAO-Unesco (1974) topsoil texture class, code
TOP_74 Character 15 As above, but descriptive
Structure for database: KEYVEGET.DBF
Field Name Type Width Dec Description
KEY Character 2Vegetation classification, code
VEGCOD Character 30 As above, but descriptive
Structure for database: WIS_EXTE.DBF
Field Name Type Width Dec Description
FIELD_NAME Character 10 Name of field
FIELD_TYPE Character 1Type of field (C, N, L)
FIELD_LEN Numeric 3Length of field
FIELD_DEC Numeric 3Decimal places
FIELD_IDX Character 1Index
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 25
Appendix 6. WISE 2.1 database coding protocols
A -- SITE ATTRIBUTES
WISE_ID:
Unique reference number for the soil profile in question, which consists of the country's ISO-
3166 code (see Appendix 7) followed by 3 numbers (Example: BR022).
FAO-Unesco classification (1974):
Classification of profile according the 1 or 2 letter codes used in the Key to Soil Units (FAO-
Unesco, 1974 p. 43-53), for example E for a Rendzina and Ge for an Eutric Gleysol. A
thorough classification is crucial, because the code provides the main "key" for linking the
profile data to the spatial database.
FAO-Unesco phase (1974, p. 5-7):
The main phase, specified using the codes presented below:
CodeDescription
ST stony
PE petric
MK petrocalcic
LI lithic
MY petrogypsic
PH phreatic
Xfragipan
MQ duripan
Zsaline
SO sodic
CE cerrado
MS petroferric
Topsoil texture class:
Textural class of the upper 30 cm of the mineral soil (FAO-Unesco, 1974 p. 4-5), specified
according to the codes below:
CodeDescription Range in % clay and sand
Ccoarse < 15% clay* and > 65% sand
Mmedium < 35% clay and < 70% sand or
# 85% clay if clay $ 15%
Ffine > 35% clay
* Clay, silt and sand-size minerals as used in FAO-ISRIC (1990).
INTERNATIONAL SOIL PROFILE DATA SET
26 ISRIC Work. Pap. 95/10b
FAO-Unesco classification (1990):
These are to be encoded using the 3-letter codes of the Key to Major Soil Groupings and Soil
Units (FAO-Unesco, 1990 p. 74-88), for example, HSf for a Fibric Histosol and ACp for a
Plinthic Acrisol.
FAO-Unesco phase (1990, p. 68):
The main phase, specified using the codes presented below:
CodeDescription Code Description
AN anthraquic PF petroferric
DU duripan PH phreatic
FR fragipan PL placic
GE gelundic SO sodic
GI gilgai RU rudic
IN inundic SA salic
SK skeletic TK takyric
YR yermic LI Lithic
USDA Soil Taxonomy:
The classification is to be specified at the subgroup level, as a text string with a maximum
length of 50 characters (see Soil Survey Staff, 1994; abbreviate if necessary).
Version of USDA Soil Taxonomy:
Two characters indicating the version/year of USDA Soil Taxonomy (e.g., 75, 87, 90, 94).
Local soil classification:
The classification according to the National System, up to a maximum of 50 characters
(abbreviate if necessary).
SOURCE_ID:
The unique SOURCE_ID provides an alphanumeric reference to the source from which the
soil profile data were derived, for example a soil monograph or digital database. The format
is free, provided the total length is less than 10 characters (e.g., AF5/34.1 for a source from
the ISRIC library).
Ref. in source:
The page and number of the profile in the source represented by SOURCE_ID.
LAB_ID:
This unique code provides an alphanumeric reference to the laboratory where the
measurements have been made. The LAB_ID consists of the country's ISO-code, followed by
two numbers (Example: IN02). Further information on the analytical procedures that have
been used to measure a certain attribute can be described on Form C, using the coding system
held in the KEYMETHO.DBF database file.
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 27
Soil profile description status:
This code refers to the completeness of the soil descriptions and analytical data for the
specified profile. The description status is determined after screening of the original profile
description and the analytical data for possible inconsistencies. It may be seen as an indicator
of the (likely) accuracy and reliability of the data shown. The following distinctions are made
(modified after FAO-ISRIC, 1990).
Code Description
1 ISIS or other Reference Pedon Description (additional information is provided under the heading
SOURCE_ID).
2 Routine profile description in which no essential data are lacking from the description, sampling or
analysis. The data give a good indication of the nature of the soil in the FAO-Unesco (1974) Legend.
3 Incomplete description in which certain relevant elements are missing from the description, an
insufficient number of samples collected, or the reliability of the analytical data do not permit a complete
characterization of the soil. The description is however useful for specific purposes and provides a
satisfactory indication of the nature of the soil in the FAO-Unesco (1974) Legend.
4 Other descriptions in which essential elements are lacking from the description, preventing a satisfactory
soil characterization and classification*.
*Generally not accepted for inclusion in WISE database unless soil unit is grossly under represented in
global data set.
Date of description:
The date on which the profile was described, specified as month and year (MM/YY).
Country:
The country where the profile was described, specified according to the ISO-3166 codes
(Example: NE for Niger, see Appendix 7).
Location:
Description of general location of profile (e.g., town, province), as text string of maximum
50 characters.
Coordinates of soil profile:
The full coordinates of the soil profile given as degrees, minutes and seconds latitude (N or
S) and longitude (E or W). The coordinates can be derived from an appropriately detailed
topographical map, and must be accurate to at least 25 km in view of their application in a
½E by ½E spatial database (A ½E by ½E degree grid corresponds approximately with 55 x 55
km at the equator). [Note: if only deg. min. is given in the database, this indicates the profile
coordinates are approximative and derived from the Times Atlas (1993)].
INTERNATIONAL SOIL PROFILE DATA SET
28 ISRIC Work. Pap. 95/10b
Altitude:
The altitude of the soil profile relative to mean sea level, specified in meters. This information
can be derived from a suitably detailed topographical map. (Note: 1 foot = 0.3048 m).
Landform:
This refers to the major landforms, which are described principally by their morphology and
not by their genetic origin, or processes responsible for their shape. The first differentiating
criterion is the dominant slope, followed by relief intensity as used in the SOTER manual
(Van Engelen and Wen, 1993 p. 24-25):
Code Landform Description
LLevel land Land with characteristic slopes of 0-8 %, and a relief intensity of less than 100 m
per km.
SSloping land Land with characteristic slopes of 8-30 % and a relief intensity of more than 50 m
per slope unit. Areas with a limited relief intensity (< 50 m per slope unit) but
slopes in excess of 8% are included, as are isolated mountains (relief intensity
> 600 m) with slopes of 8-30 %.
TSteep land Land with characteristic slopes of over 30 % and a relief intensity of mostly more than
600 m per 2 km.
CLand with com- Land made up of steep elements together with sloping or level land, or sloping land
posite landforms with level land, in which at least 20 % of the area consists of land with the lesser slope.
Codes for second level major landforms are used in the WISE database. The initial breakdown
of major landforms is made according to the procedures of the SOTER Manual:
First level Second level Gradient Relief intensity
LLevel land LP plain
LL plateau
LD depression
LF low-gradient footslope
LV valley floor
0-8%
0-8%
0-8%
0-8%
0-8%
< 100 m/km
< 100 m/km
< 100 m/km
< 100 m/km
< 100 m/km
SSloping land SM medium-gradient mountain
SH medium-gradient hills
SE med.-gradient escarpment zone
SR ridges
SU mountainous highland
SP dissected plain
15-30%
8-30%
15-30%
8-30%
8-30%
8-30%
> 600 m/2km
> 50 m/s.u.
< 600 m/2km
> 50 m/s.u.
> 600 m/2km
> 50 m/s.u.
TSteep land TM high-gradient mountain
TH high-gradient hill
TE high-grad. escarpment zone
TV high gradient valleys
> 30%
> 30%
> 30%
> 30%
> 600 m/2km
< 600 m/2km
> 600 m/2km
variable
CLand with composite CV valley
CL narrow plateau
CD major depression
> 8%
> 8%
> 8%
variable
variable
variable
Note: s.u. stands for slope unit. Where this is not clear from the gradient or relief intensity, the distinction between
the various second level major landforms follows from the description.
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 29
Landscape position:
The physiographic position of the site where the profile is located, specified according to the
following system (FAO-ISRIC, 1990 p. 7).
Code Description
Position in undulating to mountainous terrain
CR Crest/top
UP Upper slope
MS Middle slope
LS Lower slope
BO Bottom (flat)
Position in flat or almost flat terrain
HI Higher part
IN Intermediate part
LO Lower part
BO Bottom (drainage line)
Aspect:
The aspect of the site coded using the following format: N, NNE, NE, ENE, E, ..., NNW. In
case of flat or almost level land, the aspect is indicated as O (letter) .
N
NNW NNE
NW NE
WNW ENE
W O E
WSW ESE
SW SE
SSW SSE
S
Slope gradient:
The slope refers to the inclination of the land immediately surrounding the site. The measured
or estimated slope angle is specified to the nearest per cent.
Drainage class:
The internal drainage class is coded according to the conventions of FAO-ISRIC (1990 p. 20).
In WISE, intergrades of two neighbouring drainage classes may be indicated by a combination
of two codes. For instance "VP", represents a soil with very poor to poor internal drainage.
Code Description
Vvery poorly drained
Ppoorly drained
Isomewhat poorly (imperfectly) drained
Mmoderately well drained
Wwell drained
Ssomewhat excessively drained
Eexcessively drained
INTERNATIONAL SOIL PROFILE DATA SET
30 ISRIC Work. Pap. 95/10b
Depth of groundwater table:
The measured or estimated depth to the groundwater table, if present/known, indicating both
the mean highest and mean lowest values during the year. Depths are specified in centimetres
from the surface. If the water-table always occurs at a great depth, this can by entering similar
values for the both the mean high and low values (e.g., 200 cm).
Soil depth to rock:
The average measured or estimated depth, in cm, from the surface to a layer that physically
precludes the development of most roots. Limitations of a chemical nature, such as high levels
of salt/alkali, are not considered under this heading as they are often of a transient nature,
being prone to change with agricultural practices.
Parent material/lithology:
The main parent rock/material over which the soil has been formed is coded using the
categories considered in the SOTER manual and FAO-ISRIC (1990, p. 14). Additional codes,
introduced in the context of the WISE project, and are indicated by an asterisk:
Major class Group Type
IIgneous rocks IA acid igneous IA1 granite
IA2 grano-diorite
IA3 quartz-diorite
IA4 rhyolite
II intermediate igneous II1 andesite, trachyte,
phonolite
II2 diorite-syenite
IB basic igneous IB1 gabbro
IB2 basalt
IB3 dolerite
IU ultrabasic igneous IU1 peridotite
IU2 pyroxenite
IU3 ilmenite, magnetite,
ironstone, serpentine
MMetamorphic rocks MA acid metamorphic MA1 quartzite
MA2 gneiss, migmatite
MA3*slate, phyllite
MA4*schists
MB basic metamorphic MB1 slate, phyllite (pelitic
rocks)
MB2 schist
MB3 gneiss rich in ferro-magn.
min.
MB4 metamorphic limestone
(marble)
SSedimentary rocks SC clastic sediments SC1 conglomerate, breccia
SC2 sandstone, greywacke,
arkose
SC3 siltstone, mudstone,
claystone
SC4 shale
SO organic SO1 limestone, other carb. rocks
SO2 marl and other mixtures
SO3 coals, bitumen and rel.
rocks
SE evaporites SE1 anhydrite, gypsum
SE2 halite
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 31
(Parent material/lithology cont.)
Major class Group Type
UUnconsolidated UF fluvial
UL lacustrine
UM marine
UC colluvial
UE eolian
UG glacial
UP pyroclastic
UO organic
UX*soft laterite and
ferruginous materials
UY*hardened laterite and
ferruginous materials
* Additional, tentative codes
Remarks on parent material/lithology:
When necessary, additional remarks about the parent material can be specified as text on the
proforma, with a maximum length of 50 characters.
Köppen climate classification:
The climate at the site is classified according to the Köppen system which considers
precipitation effectiveness for plant growth as the major classification factor, and uses the
appropriate seasonal values of temperature and precipitation to determine the limits of
climatic groupings. The Köppen system figures a shorthand code of letters designating major
climate groups, subgroups within these major groups, with further subdivisions to distinguish
particular seasonal characteristics of temperature and precipitation (adapted from Strahler,
1969 p. 224; Times Atlas, 1993).
a) Major climate groups
The following major climate groups are considered:
Code Classification and description
A Tropical (rainy) climates: Average temperature of every month is above 18 oC. These climates have
no winter season. Annual rainfall is large and exceeds annual evaporation.
B Dry: Potential evaporation exceeds precipitation on the average throughout the year. No water surplus;
hence no permanent streams originate in B climate zones.
C Warm temperate (mesothermal) climates: Coldest month has an average temperature under 18 oC, but
above -3 oC. The C climates thus have both a summer and a winter season.
D Snow (microthermal) climates: Coldest month average temperature under -3 oC. Average temperature
of the warmest month above 10 oC, that isotherm corresponding approximately with pole-ward limit
of forest growth.
E Ice climates: A polar climate type with average temperature in no month averaging over 10 oC. These
climates have no true summer
H Mountain/Highland climates
INTERNATIONAL SOIL PROFILE DATA SET
32 ISRIC Work. Pap. 95/10b
b) Subgroups
Subgroups within the major climate groups are designated by a second letter according to the
following code:
Code Description
S*Steppe climate, a semiarid climate with about 380 to 760 mm of rainfall annually
at low latitudes.
W Desert climate. Arid climate. Most regions included have less than 250 mm of
rainfall annually.
f Moist. Adequate precipitation in all months. No dry season. This modifier is
applied to major climate types A, C and D.
w Dry season in winter of the respective hemisphere (low-sun season)
s Dry season in summer of the respective hemisphere (high-sun season)
m Rainforest climate despite a short dry season in monsoon type of precipitation
cycle. Applies only to A climates.
*The letters S and W are applied only to the dry climates (i.e., BS and BW).
From combinations of the two letter groups, 12 distinct climates emerge as follows:
Code Description
Af Tropical rainforest (also Am a variant of Af)
Aw Tropical savanna
BS Steppe climate
BW Desert climate
Cw Temperate rainy (humid mesothermal) climate with dry winter
Cf Temperate rainy (humid mesothermal) climate moist all seasons
Cs Temperate rainy (humid mesothermal) climate with dry summer
Df Cold snowy forests (humid microthermal) climate moist in all seasons
Dw Cold snowy forest (humid microthermal) climate with dry winter
ET Tundra climate
EF Climates of perpetual frost (ice-caps)
H Mountain/Highland climates (undifferentiated)
c) A third letter may be added to differentiate still more variations. Meanings are as follows:
Code Description
a With hot summer; warmest month over 22 oC (C and D climates)
b With warm summer; warmest month below 22 oC (C and D climates)
c With cool, short summer; fewer than four months over 10 oC (C and D climates)
d With very cold winter; coldest months below - 38 oC (D climates only)
h Dry-hot; mean annual temperature over 18 oC (B climates only)
k Dry-cold; climates annual temperature under 18 oC (B climates only).
The unique, Köppen codes allowed in WISE are listed in file KEYKOPPE.DBF. For example
BWk, which refers to a dry-cold, desert climate.
Current land use:
The current land use at the site is coded using the classes given by FAO-ISRIC (1990 p. 13),
as below:
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 33
Code Description Code Description
SSettlement Industry
SR Residential use
SI Industrial use
ST Transport
SC Recreational use
SX Excavations
ACrop Agriculture
AA Annual field cropping
AA1 Shifting cultivation
AA2 Fallow system cult.
AA3 Ley system cult.
AA4 Rainfed arable cult.
AA5 Wet rice cultivation
AA6 Irrigated cultivation
AP Perennial field cropping
AP1 Non-irrigated cult.
AP2 Irrigated cult.
AT Tree and shrub cropping
AT1 Non-irr. tree crop cult.
AT2 Irrigated tree crop cult.
AT3 Non-irrigated shrub crop
cultivation
AT4 Irrigated shrub crop
cultivation
HAnimal Husbandry
HE Extensive grazing
HE1 Nomadism
HE2 Semi-nomadism
HE3 Ranching
HI Intensive grazing
HI1 Animal Production
HI2 Dairying
FForestry
FN Natural forest and woodland
FN1 Selective felling
FN2 Clear felling
FP Plantation forestry
MMixed farming
MF Agro-forestry
MP Agro-pastoralism (cropping and livestock
systems)
EExtraction and Collection
EV Exploitation of natural vegetation
EH Hunting and fishing
PNature Protection
PN Nature and game reserve
PN1 Reserves
PN2 Parks
PN3 Wildlife management
PD Degradation control
PD1 Without interference
PD2 With interference
UNot Used and Not Managed
Main corp (for arable uses):
The dominant crop is coded using the following list (adapted from FAO-ISRIC, 1990).
Code Crop
BA Barley
BE Beans
CH Cashew
CA Cassava
CO Cocoa
CN Condiments
CC Coconut
CE Cereals (unsp.)
CF Coffee
CT Cotton
CP Cowpea
FB Fibre crops
FD Fodder crops
Code Crop
FR Fruit trees
GR Groundnut
MA Maize
MI Millet
OL Oil/protein crops
OP Oil palm
PE Peas
PO Potato
RI Rice
RB Rice (flooded)
RT Root crops (unsp.)
RU Rice (upland)
RR Rubber
Code Crop
SO Sorghum
SB Soybean
SC Sugar cane
SF Sunflower
SI Sisal
SP Sweet potato
SU Sugar beet
ST Stimulants (unsp.)
TC Tuber crops (unsp.)
TE Tea
TB Tobacco
VE Vegetables
WH Wheat
YA Yams
INTERNATIONAL SOIL PROFILE DATA SET
34 ISRIC Work. Pap. 95/10b
Vegetation:
The natural vegetation at a site is described using the broad classes given by Unesco (1973),
conforming with the coding conventions of SOTER:
Code Description Code Description
FClosed Forest
FE Evergreen forest
FS Semi-deciduous forest
FD Deciduous forest
FX Xeromorphic forest
WWoodland
WE Evergreen woodland
WS Semi-deciduous wood.
WD Deciduous woodl.
WX Xeromorphic woodl.
SScrub
SE Evergreen shrub
SS Semi-deciduous shrub
SD Deciduous shrub
SX Xeromorphic shrub
DDwarf scrub
DE Evergreen dwarf shrub
DS Semi-deciduous dwarf shrub
DD Deciduous dwarf shrub
DX Xeromorphic dwarf shrub
DT Tundra
HHerbaceous
HT Tall grassland
HM Medium grassland
HS Short grassland
HF Forb
HE*Hydromorphic vegetation
* New code
Remarks on land use or vegetation:
Additional remarks, for instance about the crop rotation or felling history, can be entered as
text with a maximum length of 100 characters.
Number of horizons:
This refers to the total number of horizons for which analytical data are available. The
maximum number of horizons that can be accommodated per profile in the database is 9.
However, physically, there is only place for 6 horizons on each data entry sheet.
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 35
B - HORIZON ATTRIBUTES
Horizon number:
This number is automatically created by the WISE input module. Data for the main horizons
must be entered from the surface downwards. If more than 9 soil horizons are described in
the original source, it may be necessary to ‘regroup’ this information to a smaller number.
This should only be done for the subsoil, for example, by averaging numeric data for similar
horizons such as a Btg1 and Btg2.
Horizon designation:
Whenever possible, the horizon designation should be given according to the terminology of
FAO-ISRIC (1990).
Top (upper) depth:
Upper depth of horizon (cm). In case of a litter layer, use negative numbers (e.g., top depth
of -20 cm to bottom depth of 0 cm). If the original depth of a horizon is given as e.g. 30/40
cm, the horizon depth is entered as (30+40)/2= 35 cm.
Bottom (lower) depth:
Lower depth of horizon (cm). If the lower depth of a profile is not indicated and analytical
data are available for the last horizon, the assumption is that this horizon is 15 cm thick. For
example, 75+ cm would imply a lower depth of 90 cm.
Organic carbon:
Organic carbon (% by weight) is specified with 2 decimal places. The code for the
measurement method is to be specified separately on Form C. [Note: The codes for the
analytical methods are held in KEYMETHO.DBF. The list of codes will grow as new
analytical procedures are encountered during data collection. The most recent list can be
printed with option <6> of the selection menu of WISE (see Section 4.5)].
Total Nitrogen:
Total nitrogen (% by weight) is rounded to 2 decimal places. The code for the measurement
method is to be specified separately on Form C (see KEYMETHO.DBF).
Available P:
Available (extractable) P content, by weight, in mg P2O5 kg-1 soil. The code for the
measurement method is to be specified separately on Form C (see KEYMETHO.DBF).
pH-H2O:
Measured in water at a soil:water ratio which is to be specified in the ‘analytical methods’
key-file. One decimal is adequate.
INTERNATIONAL SOIL PROFILE DATA SET
36 ISRIC Work. Pap. 95/10b
pH-KCL:
Measured in 1 M KCl solution at the soil:solution ratio specified with the data. The code for
the measurement method is to be specified separately on Form C (see KEYMETHO.DBF).
pH-CaCl2:
Measured in 1 M CaCl2 solution at the soil:solution ratio specified with the data. The code for
the measurement method is to be specified separately on Form C (see KEYMETHO.DBF).
Electrical conductivity (EC):
Specify the EC for the horizon, indicating the soil:water ratio. The unit used is mS cm-1 or dS
m-1, originally mmho cm-1, at 25 oC. The code for the measurement method is to be specified
separately on Form C (see KEYMETHO.DBF).
CaCO3:
Total CaCO3 content (% by weight) is rounded off to the nearest integer. The code for the
measurement method is to be specified separately on Form C (see KEYMETHO.DBF).
CaSO4:
Total gypsum (CaSO4.2H2O) content, by weight %, is rounded off to the nearest integer. The
code for the measurement method is to be specified separately on Form C (see
KEYMETHO.DBF).
Exchangeable bases (Ca2+, Mg2+, K+ and Na+):
To be specified in cmol(+) kg-1, using 1 decimal. The code for the measurement method is to
be specified separately on Form C (see KEYMETHO.DBF).
Exchangeable acidity (Al3+ and H+):
Obtained with a percolation of a soil sample with a 1 M KCl solution. Exchangeable acidity
is measured by titration of the percolate, and exchangeable aluminum is determined separately
in the percolate. Exchangeable acidity is specified in cmol(+) kg-1, using 1 decimal. [Note:
Values for exchangeable acidity, determined in 1 M KCl percolate, and extractable acidity,
equilibrated with a BaCl2-TEA buffer at pH 8.2, refer to different measurement methods!]
Exchangeable aluminum (Al3+):
Exchangeable aluminum, in cmol(+) kg-1, as determined separately in the percolate described
above.
Cation exchange capacity (CEC):
CEC is given in cmol(+) kg-1, using 1 decimal, according to the method specified on Form
C.
Effective cation exchange capacity (ECEC):
ECEC is determined by summation of exchangeable bases and exchangeable acidity, and
expressed in cmol(+) kg-1 using 1 decimal (i.e., ECEC= Exch[Ca2+ + Mg2+ + K+ + Na+] +
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 37
Exch[H+ + Al3+]). [Note: The above definition is used in the WISE database to conform with
the definition of the ISRIC laboratory (Van Reeuwijk, 1990, p. 11.1)].
Base saturation (BS):
Specified as nearest integer, and calculated as sum of exchangeable cation bases (Ca2+, Mg2+,
K+ and Na+) divided by the CEC, measured with the specified CEC method, times 100%.
Matrix colour, dry:
The dry colour is specified using the Munsell Colour Charts. Colour codes have the general
form: hue, value, chroma (e.g., 5YR5/3). All "complex" Munsell codes must be rounded off.
For example, 10YR3.5/1 would become 10YR4/1.
Matrix colour, moist:
The moist colour is specified using the Munsell Colour Charts (e.g., 5YR3/2).
Mottling:
Mottling in a horizon is characterized by its abundance (after FAO-ISRIC, 1990 p. 42).
Code Description % of occurrence
N none positive statement
V very few 0-2 %
F few 2-5 %
C common 5-15 %
M many 15-40 %
A abundant > 40 %
Roots:
The presence of roots is described using a two character code (FAO-ISRIC, 1990 p. 63). The
first letter of this code refers to the overall size of the roots, and the second letter to their
abundance (e.g., MC stands for many coarse roots).
- Abundance of roots (expressed as number of roots per square decimeter):
Code Quantity Description
O no roots 0
Vvery few 1-20
Ffew 20-50
C common 50-200
MMany > 200
INTERNATIONAL SOIL PROFILE DATA SET
38 ISRIC Work. Pap. 95/10b
- Description of root sizes:
Code Description Diameter (mm)
Vvery fine < 0.5 mm
Ffine 0.5-2 mm
Mmedium 2-5 mm
Ccoarse > 5 mm
Xall very fine roots to coarse
Soil structure:
The type of soil structure is described according to the classes of FAO-ISRIC (1990 p. 51):
Code Description of class
SG single grain
MA massive
CR crumb
GR granular
PR prismatic
PS subangular prismatic
CO columnar
AB angular blocky
SB subangular blocky
Code Description
AS angular and subangular blocky
SA subangular and angular blocky
SN nutty subangular blocky
AW angular blocky wedge-shaped
AP angular blocky parallelepiped
PL platy
RS rock structure
SS stratified structure
Particle size distribution:
The particle size distribution refers to the fine earth fraction only (< 2 mm). The weight
percentages of sand-, silt- and clay-size materials are given as integers. The analytical
procedure and ‘esd’ or equivalent spherical diameter for the clay-, silt-, and sand-size
fractions must be documented on Form C. For example: pipette method, full dispersion; esd:
<2 µm, < 50 µm and < 2 mm.
Stone and gravel content:
Give a visual estimate of the percentage of large rock and mineral fragments with a diameter
larger than 2 mm, rounded off to the nearest 5 per cent.
Bulk density:
Bulk density (oven dry sample) is given as g cm-3, using two decimals.
Soil water retention:
The volume percentage of water (MC) in the soil horizon, at the considered pF-values (i.e.,
0.0, 1.0, 1.5, 1.7, 2.0, 2.3, 2.5, 2.7, 4.3, 3.7 and 4.2; see WISEHOR.DBF p. 27), is to be
specified as an integer. The moisture content is expressed on a percent by volume basis:
MC (% by volume v/v) = MC (% by weight w/w) x bulk density (kg m-3)
Selected pF-values or suctions, at which the soil water retention measurements were made,
can be entered on the data entry sheet. (Indicate which pF values are considered to correspond
with the Field Capacity and the Permanent Wilting Point so that the Available Water
Capacity (AWC) can be calculated). [Note: pF is the log10 [head(cm of water)], i.e. a head of
100 cm of water corresponds with a pF of 2.0. (1 bar = 1017 cm of water = 100 kPa = 0.987
atmosphere)]
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 39
Hydraulic conductivity:
Hydraulic conductivity or permeability (cm hr-1) varies with soil moisture conditions (pF
values). Two values can be entered: (a) saturated hydraulic conductivity, and (b) non-saturated
hydraulic conductivity.
INTERNATIONAL SOIL PROFILE DATA SET
40 ISRIC Work. Pap. 95/10b
C ——- SOURCE OF DATA
SOURCE_ID:
Unique code for source (e.g., soil monograph or digital database).
Source:
Authors and initials, as text string (For example: Van Waveren, E.J. and Bos, A.B.).
Year:
Year data during which the profile data were collected/described (For example: 1988).
Title:
Title of source in which data are published, as text string (For example: ISRIC Soil
Information System).
Series/publisher/year:
Self-explanatory, as text string (For example: Technical Paper 15, International Soil
Reference and Information Centre, Wageningen).
LAB_ID:
Unique reference code for laboratory where analyses for relevant profile(s) were made (e.g.,
FR01).
Laboratory name:
Name of laboratory where analyses were made, as text string.
Coding system for analytical methods:
-Organic Carbon (OC__)
-Total Nitrogen (TN__)
-Available Phosphorus (TP__)
-pH-water (PH__)
-pH-KCl (PK__)
-pH-CaCl2(PC__)
-Electrical conductivity (EL__)
-Free CaCO3 (CA__)
-Gypsum (GY__)
-Exch. Ca, Mg, K, and Na (EX__)
-Exch. acidity and Aluminum (EA__)
-CEC soil (CS__)
-ECEC soil (CE__)
-Base saturation (BS__)
-Particle size distribution (TE__)
-Bulk density (BD__)
-Moisture content (MC__)
-Hydraulic conductivity (HC__)
Note: All codes, plus a brief description of the corresponding analytical procedures, are
documented in KEYMETHO.DBF, for example "OC01" stands for "Method of Walkley-
Black". This information can be printed with option <6> of the TOOLS menu.
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 41
Appendix 7. List of country ISO codes
AF Afghanistan
AL Albania
DZ Algeria
AS American Samoa
AD Andorra
AO Angola
AI Anguilla
AQ Antarctica
AG Antigua and Barbuda
AR Argentina
AM Armenia
AW Aruba
AU Australia
AT Austria
AZ Azerbaijan
BS Bahamas
BH Bahrain
BD Bangladesh
BB Barbados
BE Belgium
BZ Belize
BJ Benin
BT Bhutan
BO Bolivia
BW Botswana
BV Bouvet Island
BR Brazil
IO Brit. Ind. Ocean Territory
BN Brunei Darussalam
BG Bulgaria
BF Burkina Faso
BU Burma
BI Burundi
BY Belarus
CM Cameroon
CA Canada
CV Cape Verde
KY Cayman Islands
CF Central African Republic
TD Chad
CL Chile
CN China
CX Christmas Island
CC Cocos Islands
CO Colombia
CG Congo
CK Cook Islands
CR Costa Rica
HR Croatia
CU Cuba
CY Cyprus
CS Czechoslovakia
CI Côte d'Ivoire
DK Denmark
DJ Djibouti
DM Dominica
DO Dominican Republic
TP East Timor
EC Ecuador
EG Egypt
SV El Salvador
GQ Equatorial Guinea
EE Estonia
ET Ethiopia
FK Falkland Islands
FO Faroe (Islands)
FJ Fiji
FI Finland
FR France
GF French Guiana
PF French Polynesia
TF French Southern Territories
GA Gabon
GM Gambia
GE Georgia
DE Germany, Fed. Rep. of
GH Ghana
GI Gibraltar
GR Greece
GL Greenland
GD Grenada
GP Guadeloupe
GU Guam
GT Guatemala
GN Guinea
GW Guinea-Bissau
GY Guyana
HT Haiti
HM Heard and McDonald Islands
HN Honduras
HK Hong Kong
HU Hungary
IS Iceland
IN India
ID Indonesia
IR Iran, Islamic Republic of
IQ Iraq
IE Ireland
IL Israel
IT Italy
JM Jamaica
JP Japan
JO Jordan
KH Kampuchea, Democratic
KZ Kazakhstan
KE Kenya
KI Kiribati
KR Korea, Republic of
KP Korea, Dem. Peopl. Rep.
KW Kuwait
KG Kyrgystan
LA Lao, People's Democratic Rep.
LB Lebanon
LS Lesotho
LR Liberia
LY Libyan Arab Jamahiri
LI Liechtenstein
LT Lithuania
LU Luxembourg
MO Macau
MG Madagascar
MW Malawi
MY Malaysia
MV Maldives
ML Mali
MT Malta
MH Marshall Islands
MQ Martinique
MR Mauritania
MU Mauritius
MX Mexico
FM Micronesia
INTERNATIONAL SOIL PROFILE DATA SET
42 ISRIC Work. Pap. 95/10b
MD Moldova, Republic of
MC Monaco
MN Mongolia
MS Montserrat
MA Morocco
MZ Mozambique
NA Namibia
NR Nauru
NP Nepal
NL Netherlands
AN Netherlands Antilles
NT Neutral Zone
NC New Caledonia
NZ New Zealand
NI Nicaragua
NE Niger
NG Nigeria
NU Niue
NF Norfolk Island
MP Northern Mariana Islands
NO Norway
OM Oman
PK Pakistan
PW Palau
PA Panama
PG Papua New Guinea
PY Paraguay
PE Peru
PH Philippines
PN Pitcairn
PL Poland
PT Portugal
PR Puerto Rico
QA Qatar
RE Reunion
RO Romania
RU Russian Federation
RW Rwanda
LC Saint Lucia
WS Samoa
SM San Marino
ST Sao Tome and Principe
SA Saudi Arabia
SN Senegal
SC Seychelles
SL Sierra Leone
SG Singapore
SB Solomon Islands
SO Somalia
ZA South Africa
ES Spain
LK Sri Lanka
SH St. Helena
KN St. Kitts and Nevis
PM St. Pierre and Miquelon
VC St. Vincent and the Grenadines
SD Sudan
SR Suriname
SJ Svalbard and Jan Mayen
SZ Swaziland
SE Sweden
CH Switzerland
SY Syrian Arab Republic
TW Taiwan, Province China
TJ Tajikistan
TZ Tanzania, United Rep. of
TH Thailand
TG Togo
TK Tokelau
TO Tonga
TT Trinidad and Tobago
TN Tunisia
TR Turkey
TM Turkmenistan
TC Turks and Caicos Islands
TV Tuvalu
SU USSR
UG Uganda
UA Ukraine
AE United Arab Emirates
GB United Kingdom
US United States
UY Uruguay
UM US. Minor Outlying Islands
UZ Uzbekistan
VU Vanuatu
VA Vatican City State
VE Venezuela
VN Viet Nam
VG Virgin Islands (U.K.)
VI Virgin Islands (U.S.)
WF Wallis and Futuna Islands
EH Western Sahara
YE Yemen
YD Yemen, Democratic
YU Yugoslavia
ZR Zaire
ZM Zambia
ZW Zimbabwe
INTERNATIONAL SOIL PROFILE DATA SET
ISRIC Work. Pap. 95/10b 43
Index
Coding protocols
Horizon data ...............35
Laboratory methods ..........40
Source of data ..............40
Database structure
KEYAREA.DBF ............21
KEYCOUN.DBF ............21
KEYCROPS.DBF ...........21
KEYDRAIN.DBF ...........21
KEYFAO.DBF .............21
KEYKOPPE.DBF ...........22
KEYLANDF.DBF ...........22
KEYLUS.DBF ..............22
KEYMETHOD.DBF .........22
KEYMOTTL.DBF ...........22
KEYPAREN.DBF ...........23
KEYPH74.DBF .............23
KEYPH90.DBF ............ 23
KEYPOSIT.DBF ........... 23
KEYREGION.DBF ......... 23
KEYROOTS.DBF .......... 23
KEYSTATU.DBF .......... 24
KEYSTRUC.DBF .......... 24
KEYTEXT.DBF ........... 24
KEYVEGET.DBF .......... 24
WIS_EXTE.DBF ........... 24
WISEANAD.DBF .......... 20
WISEATRIB.DBF .......... 20
WISEHOR.DBF ............ 19
WISELAB.DBF ............ 20
WISESITE.DBF ........... 18
WISESOUR.DBF .......... 20
WISE
installation ................ 17
... In the WISE project, a wide range of worldwide soil databases (point and network-based) have been collected to make the data more accurate at regional and global levels. These data are related to the FAO-UNESCO soil map data (Batjes 1995; http://www.isric .org). ...
... Several world soil maps have been prepared to address this problem (FAO-UNESCO 1974;WRB 1998WRB , 2006Zobler 1986;Hengl et al. 2014;Batjes 1995;Wieder et al. 2014). Gijsman et al. (2007) created a set of soil input sets for the DSSAT model using the WISE soil database. ...
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Your article is protected by copyright and all rights are held exclusively by Springer Nature Switzerland AG. This e-offprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com". Abstract Soil information is a vital input for crop models applications in various large area studies including climate change impact and food security. One of the global soil databases that provide full information for crop models is HC27 of IFPRI. The quality of the database has not been assessed for crop modeling so far. A tested crop simulation model (SSM-iCrop2) was used for this purpose that needs soil water related properties (i.e., depth, albedo, curve number for runoff, drainage coefficient, and soil water limits at saturation, drained upper limit and lower limit) for the simulation of crop properties. Actual data of two soil profiles from three different climate zones (locations) were used as model inputs to simulate potential yield, evapotran-spiration (under rainfed conditions) or net irrigation water requirement (under irrigated conditions) of some important plant species (alfalfa, sugar beet, sugar cane, wheat, olive, soybean, apricot and chickpea) under rainfed and irrigated conditions of Iran. Results showed that the application of HC27 soil information in the SSM-iCrop2 model resulted in model output that was not different from the model output with actual soil information with respect to mean, variance, and distribution. No statistically significant difference was found in the simulation of various combinations of soil profiles-plant species-locations. It was concluded that HC27 information can be used in simulation studies with SSM-iCrop2 or other similar simple models for the simulation of potential yield, net irrigation water, or evapotranspiration that are commonly required for food security and climate change studies.
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Danish Journal of Geography 95: 49–58, 1995. In 1985 the European Communities now the European Union published a soil map covering all the Community countries. This map has been digitized, but for modelling purposes it was necessary to compile a Soil Profile Analytical Database connected to the European Communities Soil Map. This compilation commenced in 1992 following a decade of expert group meetings concerning European soil and land data. This account describes the events that led to the decision to develop this database, and how it was compiled.
Article
This paper describes two global models: (1) an Agricultural Demand Model which is used to compute the consumption and demand for commodities that define land use in 13 world regions; and, (2) a Land Cover Model, which simulates changes in land cover on a global terrestrial grid (0.5 latitude by 0.5 longitude) resulting from economic and climatic factors. Both are part of the IMAGE 2.0 model of global climate change. The models have been calibrated and tested with regional data from 1970–1990. The Agricultural Demand Model can approximate the observed trend in commodity consumption and the Land Cover Model simulates the total amount of land converted within 13 world regions during this period. Some degree of the spatial variability of deforestation has also been captured by the simulation. Applying the model to a Conventional Wisdom scenario showed that future trends of land conversions could be strikingly different on different continents even though a consistent scenario (IS92a from the IPCC) was used for assumptions about economic growth and population. Sensitivity analysis indicated that future land cover patterns are especially sensitive to assumed technological improvements in crop yield and computed changes in agricultural demand.
FAO-ISRIC Soil Database -SDB
  • Fao
FAO, 1989. FAO-ISRIC Soil Database -SDB. World Soil Resources Report 60 (Reprinted), FAO, Rome.
Digitized Soil Map of the World Soil Map of the World. Volume I: Legend
FAO, 1991. Digitized Soil Map of the World. World Soil Resources Report 67, FAO, Rome. FAO-Unesco, 1974. Soil Map of the World. Volume I: Legend. Unesco, Paris.
FAO-Unesco Soil Map of the World: Revised Legend
FAO, 1990a. FAO-Unesco Soil Map of the World: Revised Legend. World Soil Resources Report 60, FAO, Rome [Reprinted as Technical Paper 20, ISRIC, Wageningen, 1994].
Explanatory note on the Soil Map of the Republic of Botswana
FAO, 1990b. Explanatory note on the Soil Map of the Republic of Botswana. AGBOT/85/011, FAO, UNDP and Republic of Botswana, Gaborone.