Loading…

Deriving a dataset for agriculturally relevant soils from the Soil Landscapes of Canada simulations

The Soil and Water Assessment Tool (SWAT) model has been commonly used in Canada for hydrological and water quality simulations. However, preprocessing of critical data such as soils information can be laborious and time-consuming. The objective of this work was to preprocess the Soil Landscapes of...

Full description

Saved in:
Bibliographic Details
Published in:Earth system science data 2018-09, Vol.10 (3), p.1673
Main Authors: Cordeiro, Marcos R. C, Lelyk, Glenn, Krobel, Roland, Legesse, Getahun, Faramarzi, Monireh, Masud, Mohammad Badrul, McAllister, Tim
Format: Article
Language:English
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page
container_issue 3
container_start_page 1673
container_title Earth system science data
container_volume 10
creator Cordeiro, Marcos R. C
Lelyk, Glenn
Krobel, Roland
Legesse, Getahun
Faramarzi, Monireh
Masud, Mohammad Badrul
McAllister, Tim
description The Soil and Water Assessment Tool (SWAT) model has been commonly used in Canada for hydrological and water quality simulations. However, preprocessing of critical data such as soils information can be laborious and time-consuming. The objective of this work was to preprocess the Soil Landscapes of Canada (SLC) database to offer a country-level soils dataset in a format ready to be used in SWAT simulations. A two-level screening process was used to identify critical information required by SWAT and to remove records with information that could not be calculated or estimated. Out of the 14 063 unique soil records in the SLC, 11 838 records with complete information were included in the dataset presented here. Important variables for SWAT simulations that are not reported in the SLC database (e.g., hydrologic soils groups (HSGs) and erodibility factor (K)) were calculated from information contained within the SLC database. These calculations, in fact, represent a major contribution to enabling the present dataset to be used for hydrological simulations in Canada using SWAT and other comparable models. Analysis of those variables indicated that 21.3 %, 24.6 %, 39.0 %, and 15.1 % of the soil records in Canada belong to HSGs 1, 2, 3, and 4, respectively. This suggests that almost two-thirds of the soil records have a high (i.e., HSG 4) or relatively high (i.e., HSG 3) runoff generation potential. A spatial analysis indicated that 20.0 %, 26.8 %, 36.7 %, and 16.5 % of soil records belonged to HSG 1, HSG 2, HSG 3, and HSG 4, respectively. Erosion potential, which is inherently linked to the erodibility factor (K), was associated with runoff potential in important agricultural areas such as southern Ontario and Nova Scotia. However, contrary to initial expectations, low or moderate erosion potential was found in areas with high runoff potential, such as regions in southern Manitoba (e.g., Red River Valley) and British Columbia (e.g., Peace River watershed). This dataset will be a unique resource to a variety of research communities including hydrological, agricultural, and water quality modelers and is publicly available at
format article
fullrecord <record><control><sourceid>gale</sourceid><recordid>TN_cdi_gale_infotracmisc_A554125667</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A554125667</galeid><sourcerecordid>A554125667</sourcerecordid><originalsourceid>FETCH-LOGICAL-g1017-91821f39238da54fe713daffacf0b1b56702f47fc300d6130e8d7f10d77e6d93</originalsourceid><addsrcrecordid>eNptjE1LAzEYhPegYK3-h4AnDyvJZpNsj6V-FQqC7b28Td6skWwiSbbov3dBDxZkDsMMz8xZNWOdlDUXtLuoLnN-p1S2TIlZpe8xuaMLPQFioEDGQmxMBPrk9OjLmMD7L5LQ4xFCITk6n4lNcSDlDcl2imQDwWQNH5hJtGQFAQyQ7IbRQ3Ex5Kvq3ILPeP3r82r3-LBbPdebl6f1armpe0aZqhesa5jli4Z3BkRrUTFuwFrQlh7YQUhFG9sqqzmlRjJOsTPKMmqUQmkWfF7d_Nz24HHvgo0lgR5c1vulEC1rhJRqou7-oSYZHJyOAa2b-pPB7clgYgp-lh7GnPfr7etf9hv7_G55</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Deriving a dataset for agriculturally relevant soils from the Soil Landscapes of Canada simulations</title><source>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</source><source>EZB Electronic Journals Library</source><creator>Cordeiro, Marcos R. C ; Lelyk, Glenn ; Krobel, Roland ; Legesse, Getahun ; Faramarzi, Monireh ; Masud, Mohammad Badrul ; McAllister, Tim</creator><creatorcontrib>Cordeiro, Marcos R. C ; Lelyk, Glenn ; Krobel, Roland ; Legesse, Getahun ; Faramarzi, Monireh ; Masud, Mohammad Badrul ; McAllister, Tim</creatorcontrib><description><![CDATA[The Soil and Water Assessment Tool (SWAT) model has been commonly used in Canada for hydrological and water quality simulations. However, preprocessing of critical data such as soils information can be laborious and time-consuming. The objective of this work was to preprocess the Soil Landscapes of Canada (SLC) database to offer a country-level soils dataset in a format ready to be used in SWAT simulations. A two-level screening process was used to identify critical information required by SWAT and to remove records with information that could not be calculated or estimated. Out of the 14&thinsp;063 unique soil records in the SLC, 11&thinsp;838 records with complete information were included in the dataset presented here. Important variables for SWAT simulations that are not reported in the SLC database (e.g., hydrologic soils groups (HSGs) and erodibility factor (K)) were calculated from information contained within the SLC database. These calculations, in fact, represent a major contribution to enabling the present dataset to be used for hydrological simulations in Canada using SWAT and other comparable models. Analysis of those variables indicated that 21.3&thinsp;%, 24.6&thinsp;%, 39.0&thinsp;%, and 15.1&thinsp;% of the soil records in Canada belong to HSGs 1, 2, 3, and 4, respectively. This suggests that almost two-thirds of the soil records have a high (i.e., HSG 4) or relatively high (i.e., HSG 3) runoff generation potential. A spatial analysis indicated that 20.0&thinsp;%, 26.8&thinsp;%, 36.7&thinsp;%, and 16.5&thinsp;% of soil records belonged to HSG 1, HSG 2, HSG 3, and HSG 4, respectively. Erosion potential, which is inherently linked to the erodibility factor (K), was associated with runoff potential in important agricultural areas such as southern Ontario and Nova Scotia. However, contrary to initial expectations, low or moderate erosion potential was found in areas with high runoff potential, such as regions in southern Manitoba (e.g., Red River Valley) and British Columbia (e.g., Peace River watershed). This dataset will be a unique resource to a variety of research communities including hydrological, agricultural, and water quality modelers and is publicly available at]]></description><identifier>ISSN: 1866-3508</identifier><language>eng</language><publisher>Copernicus GmbH</publisher><subject>Agricultural land ; Analysis ; Soil quality ; Soil research</subject><ispartof>Earth system science data, 2018-09, Vol.10 (3), p.1673</ispartof><rights>COPYRIGHT 2018 Copernicus GmbH</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784</link.rule.ids></links><search><creatorcontrib>Cordeiro, Marcos R. C</creatorcontrib><creatorcontrib>Lelyk, Glenn</creatorcontrib><creatorcontrib>Krobel, Roland</creatorcontrib><creatorcontrib>Legesse, Getahun</creatorcontrib><creatorcontrib>Faramarzi, Monireh</creatorcontrib><creatorcontrib>Masud, Mohammad Badrul</creatorcontrib><creatorcontrib>McAllister, Tim</creatorcontrib><title>Deriving a dataset for agriculturally relevant soils from the Soil Landscapes of Canada simulations</title><title>Earth system science data</title><description><![CDATA[The Soil and Water Assessment Tool (SWAT) model has been commonly used in Canada for hydrological and water quality simulations. However, preprocessing of critical data such as soils information can be laborious and time-consuming. The objective of this work was to preprocess the Soil Landscapes of Canada (SLC) database to offer a country-level soils dataset in a format ready to be used in SWAT simulations. A two-level screening process was used to identify critical information required by SWAT and to remove records with information that could not be calculated or estimated. Out of the 14&thinsp;063 unique soil records in the SLC, 11&thinsp;838 records with complete information were included in the dataset presented here. Important variables for SWAT simulations that are not reported in the SLC database (e.g., hydrologic soils groups (HSGs) and erodibility factor (K)) were calculated from information contained within the SLC database. These calculations, in fact, represent a major contribution to enabling the present dataset to be used for hydrological simulations in Canada using SWAT and other comparable models. Analysis of those variables indicated that 21.3&thinsp;%, 24.6&thinsp;%, 39.0&thinsp;%, and 15.1&thinsp;% of the soil records in Canada belong to HSGs 1, 2, 3, and 4, respectively. This suggests that almost two-thirds of the soil records have a high (i.e., HSG 4) or relatively high (i.e., HSG 3) runoff generation potential. A spatial analysis indicated that 20.0&thinsp;%, 26.8&thinsp;%, 36.7&thinsp;%, and 16.5&thinsp;% of soil records belonged to HSG 1, HSG 2, HSG 3, and HSG 4, respectively. Erosion potential, which is inherently linked to the erodibility factor (K), was associated with runoff potential in important agricultural areas such as southern Ontario and Nova Scotia. However, contrary to initial expectations, low or moderate erosion potential was found in areas with high runoff potential, such as regions in southern Manitoba (e.g., Red River Valley) and British Columbia (e.g., Peace River watershed). This dataset will be a unique resource to a variety of research communities including hydrological, agricultural, and water quality modelers and is publicly available at]]></description><subject>Agricultural land</subject><subject>Analysis</subject><subject>Soil quality</subject><subject>Soil research</subject><issn>1866-3508</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNptjE1LAzEYhPegYK3-h4AnDyvJZpNsj6V-FQqC7b28Td6skWwiSbbov3dBDxZkDsMMz8xZNWOdlDUXtLuoLnN-p1S2TIlZpe8xuaMLPQFioEDGQmxMBPrk9OjLmMD7L5LQ4xFCITk6n4lNcSDlDcl2imQDwWQNH5hJtGQFAQyQ7IbRQ3Ex5Kvq3ILPeP3r82r3-LBbPdebl6f1armpe0aZqhesa5jli4Z3BkRrUTFuwFrQlh7YQUhFG9sqqzmlRjJOsTPKMmqUQmkWfF7d_Nz24HHvgo0lgR5c1vulEC1rhJRqou7-oSYZHJyOAa2b-pPB7clgYgp-lh7GnPfr7etf9hv7_G55</recordid><startdate>20180913</startdate><enddate>20180913</enddate><creator>Cordeiro, Marcos R. C</creator><creator>Lelyk, Glenn</creator><creator>Krobel, Roland</creator><creator>Legesse, Getahun</creator><creator>Faramarzi, Monireh</creator><creator>Masud, Mohammad Badrul</creator><creator>McAllister, Tim</creator><general>Copernicus GmbH</general><scope>ISR</scope></search><sort><creationdate>20180913</creationdate><title>Deriving a dataset for agriculturally relevant soils from the Soil Landscapes of Canada simulations</title><author>Cordeiro, Marcos R. C ; Lelyk, Glenn ; Krobel, Roland ; Legesse, Getahun ; Faramarzi, Monireh ; Masud, Mohammad Badrul ; McAllister, Tim</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-g1017-91821f39238da54fe713daffacf0b1b56702f47fc300d6130e8d7f10d77e6d93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Agricultural land</topic><topic>Analysis</topic><topic>Soil quality</topic><topic>Soil research</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cordeiro, Marcos R. C</creatorcontrib><creatorcontrib>Lelyk, Glenn</creatorcontrib><creatorcontrib>Krobel, Roland</creatorcontrib><creatorcontrib>Legesse, Getahun</creatorcontrib><creatorcontrib>Faramarzi, Monireh</creatorcontrib><creatorcontrib>Masud, Mohammad Badrul</creatorcontrib><creatorcontrib>McAllister, Tim</creatorcontrib><collection>Gale in Context: Science</collection><jtitle>Earth system science data</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cordeiro, Marcos R. C</au><au>Lelyk, Glenn</au><au>Krobel, Roland</au><au>Legesse, Getahun</au><au>Faramarzi, Monireh</au><au>Masud, Mohammad Badrul</au><au>McAllister, Tim</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Deriving a dataset for agriculturally relevant soils from the Soil Landscapes of Canada simulations</atitle><jtitle>Earth system science data</jtitle><date>2018-09-13</date><risdate>2018</risdate><volume>10</volume><issue>3</issue><spage>1673</spage><pages>1673-</pages><issn>1866-3508</issn><abstract><![CDATA[The Soil and Water Assessment Tool (SWAT) model has been commonly used in Canada for hydrological and water quality simulations. However, preprocessing of critical data such as soils information can be laborious and time-consuming. The objective of this work was to preprocess the Soil Landscapes of Canada (SLC) database to offer a country-level soils dataset in a format ready to be used in SWAT simulations. A two-level screening process was used to identify critical information required by SWAT and to remove records with information that could not be calculated or estimated. Out of the 14&thinsp;063 unique soil records in the SLC, 11&thinsp;838 records with complete information were included in the dataset presented here. Important variables for SWAT simulations that are not reported in the SLC database (e.g., hydrologic soils groups (HSGs) and erodibility factor (K)) were calculated from information contained within the SLC database. These calculations, in fact, represent a major contribution to enabling the present dataset to be used for hydrological simulations in Canada using SWAT and other comparable models. Analysis of those variables indicated that 21.3&thinsp;%, 24.6&thinsp;%, 39.0&thinsp;%, and 15.1&thinsp;% of the soil records in Canada belong to HSGs 1, 2, 3, and 4, respectively. This suggests that almost two-thirds of the soil records have a high (i.e., HSG 4) or relatively high (i.e., HSG 3) runoff generation potential. A spatial analysis indicated that 20.0&thinsp;%, 26.8&thinsp;%, 36.7&thinsp;%, and 16.5&thinsp;% of soil records belonged to HSG 1, HSG 2, HSG 3, and HSG 4, respectively. Erosion potential, which is inherently linked to the erodibility factor (K), was associated with runoff potential in important agricultural areas such as southern Ontario and Nova Scotia. However, contrary to initial expectations, low or moderate erosion potential was found in areas with high runoff potential, such as regions in southern Manitoba (e.g., Red River Valley) and British Columbia (e.g., Peace River watershed). This dataset will be a unique resource to a variety of research communities including hydrological, agricultural, and water quality modelers and is publicly available at]]></abstract><pub>Copernicus GmbH</pub><tpages>1673</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1866-3508
ispartof Earth system science data, 2018-09, Vol.10 (3), p.1673
issn 1866-3508
language eng
recordid cdi_gale_infotracmisc_A554125667
source Publicly Available Content Database (Proquest) (PQ_SDU_P3); EZB Electronic Journals Library
subjects Agricultural land
Analysis
Soil quality
Soil research
title Deriving a dataset for agriculturally relevant soils from the Soil Landscapes of Canada simulations
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T14%3A17%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Deriving%20a%20dataset%20for%20agriculturally%20relevant%20soils%20from%20the%20Soil%20Landscapes%20of%20Canada%20simulations&rft.jtitle=Earth%20system%20science%20data&rft.au=Cordeiro,%20Marcos%20R.%20C&rft.date=2018-09-13&rft.volume=10&rft.issue=3&rft.spage=1673&rft.pages=1673-&rft.issn=1866-3508&rft_id=info:doi/&rft_dat=%3Cgale%3EA554125667%3C/gale%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-g1017-91821f39238da54fe713daffacf0b1b56702f47fc300d6130e8d7f10d77e6d93%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_galeid=A554125667&rfr_iscdi=true