The impact of different rainfall products on landscape modelling simulations

Rainfall products can contain significantly different spatiotemporal estimates, depending on their underlying data and final constructed resolution. Commonly used products, such as rain gauges, rain gauge networks, and weather radar, differ in their information content regarding intensities, spatial...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Earth surface processes and landforms 2020-09, Vol.45 (11), p.2512-2523
Hauptverfasser: Skinner, Christopher J., Peleg, Nadav, Quinn, Niall, Coulthard, Tom J., Molnar, Peter, Freer, Jim
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 2523
container_issue 11
container_start_page 2512
container_title Earth surface processes and landforms
container_volume 45
creator Skinner, Christopher J.
Peleg, Nadav
Quinn, Niall
Coulthard, Tom J.
Molnar, Peter
Freer, Jim
description Rainfall products can contain significantly different spatiotemporal estimates, depending on their underlying data and final constructed resolution. Commonly used products, such as rain gauges, rain gauge networks, and weather radar, differ in their information content regarding intensities, spatial variability, and natural climatic variability, therefore producing different estimates. Landscape evolution models (LEMs) simulate the geomorphic changes in landscapes, and current models can simulate timeframes from event level to millions of years and some use rainfall inputs to drive them. However, the impact of different rainfall products on LEM outputs has never been considered. This study uses the STREAP rainfall generator, calibrated using commonly used rainfall observation products, to produce longer rainfall records than the observations to drive the CAESAR‐Lisflood LEM to examine how differences in rainfall products affect simulated landscapes. The results show that the simulation of changes to basin geomorphology is sensitive to the differences between rainfall products, with these differences expressed linearly in discharges but non‐linearly in sediment yields. Furthermore, when applied over a 1500‐year period, large differences in the simulated long profiles were observed, with the simulations producing greater sediment yields showing erosion extending further downstream. This suggests that the choice of rainfall product to drive LEMs has a large impact on the final simulated landscapes. The combination of rainfall generator model and LEMs represents a potentially powerful method for assessing the impacts of rainfall product differences on landscapes and their short‐ and long‐term evolution. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd A weather generator was used to produce rainfall data to drive a landscape evolution model, and calibrated using different observation products. The simulated sediment yields and patterns of landscape change were sensitive to the differences in the observation products. The combination of weather generators and landscape evolution models presents a useful tool for assessing landscape changes due to climate change.
doi_str_mv 10.1002/esp.4894
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2443149866</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2443149866</sourcerecordid><originalsourceid>FETCH-LOGICAL-a3504-a88a85f692b7dc89e1031c0973854cfbfe1c5723b7120df54cf57f85d73da09e3</originalsourceid><addsrcrecordid>eNp10MtKAzEUBuAgCtYq-AgBN26mJpPMJFlKqRcoKFjXIc1FU2aSMZlB-vam1q2rA4fvXPgBuMZogRGq72weFpQLegJmGIm2EpywUzBDWLBKEMLOwUXOO4QwLmoG1ptPC30_KD3C6KDxztlkwwiT8sGproNDimbSY4YxwE4Fk7UaLOyjsV3nwwfMvp86NfoY8iU4KyPZXv3VOXh_WG2WT9X65fF5eb-uFGkQrRTnijeuFfWWGc2FxYhgjQQjvKHabZ3FumE12TJcI-MOvYY53hhGjELCkjm4Oe4tv31NNo9yF6cUyklZU0owFbxti7o9Kp1izsk6OSTfq7SXGMlDVrJkJQ9ZFVod6bfv7P5fJ1dvr7_-B2pkavQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2443149866</pqid></control><display><type>article</type><title>The impact of different rainfall products on landscape modelling simulations</title><source>Access via Wiley Online Library</source><creator>Skinner, Christopher J. ; Peleg, Nadav ; Quinn, Niall ; Coulthard, Tom J. ; Molnar, Peter ; Freer, Jim</creator><creatorcontrib>Skinner, Christopher J. ; Peleg, Nadav ; Quinn, Niall ; Coulthard, Tom J. ; Molnar, Peter ; Freer, Jim</creatorcontrib><description>Rainfall products can contain significantly different spatiotemporal estimates, depending on their underlying data and final constructed resolution. Commonly used products, such as rain gauges, rain gauge networks, and weather radar, differ in their information content regarding intensities, spatial variability, and natural climatic variability, therefore producing different estimates. Landscape evolution models (LEMs) simulate the geomorphic changes in landscapes, and current models can simulate timeframes from event level to millions of years and some use rainfall inputs to drive them. However, the impact of different rainfall products on LEM outputs has never been considered. This study uses the STREAP rainfall generator, calibrated using commonly used rainfall observation products, to produce longer rainfall records than the observations to drive the CAESAR‐Lisflood LEM to examine how differences in rainfall products affect simulated landscapes. The results show that the simulation of changes to basin geomorphology is sensitive to the differences between rainfall products, with these differences expressed linearly in discharges but non‐linearly in sediment yields. Furthermore, when applied over a 1500‐year period, large differences in the simulated long profiles were observed, with the simulations producing greater sediment yields showing erosion extending further downstream. This suggests that the choice of rainfall product to drive LEMs has a large impact on the final simulated landscapes. The combination of rainfall generator model and LEMs represents a potentially powerful method for assessing the impacts of rainfall product differences on landscapes and their short‐ and long‐term evolution. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley &amp; Sons Ltd A weather generator was used to produce rainfall data to drive a landscape evolution model, and calibrated using different observation products. The simulated sediment yields and patterns of landscape change were sensitive to the differences in the observation products. The combination of weather generators and landscape evolution models presents a useful tool for assessing landscape changes due to climate change.</description><identifier>ISSN: 0197-9337</identifier><identifier>EISSN: 1096-9837</identifier><identifier>DOI: 10.1002/esp.4894</identifier><language>eng</language><publisher>Bognor Regis: Wiley Subscription Services, Inc</publisher><subject>Climate variability ; Computer simulation ; Earth surface ; Evolution ; Gauges ; Geomorphology ; Landforms ; Landscape ; landscape evolution ; Meteorological radar ; numerical modelling ; Profiles ; Radar ; Rain ; Rain gauges ; Rainfall ; Rainfall impact ; Rainfall simulators ; Sediment ; Spatial variability ; Spatial variations ; uncertainty ; Variability ; Weather ; weather generator ; Weather radar</subject><ispartof>Earth surface processes and landforms, 2020-09, Vol.45 (11), p.2512-2523</ispartof><rights>2020 The Authors. Earth Surface Processes and Landforms published by John Wiley &amp; Sons Ltd</rights><rights>2020. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3504-a88a85f692b7dc89e1031c0973854cfbfe1c5723b7120df54cf57f85d73da09e3</citedby><cites>FETCH-LOGICAL-a3504-a88a85f692b7dc89e1031c0973854cfbfe1c5723b7120df54cf57f85d73da09e3</cites><orcidid>0000-0001-8853-9606 ; 0000-0002-8164-0442</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fesp.4894$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fesp.4894$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Skinner, Christopher J.</creatorcontrib><creatorcontrib>Peleg, Nadav</creatorcontrib><creatorcontrib>Quinn, Niall</creatorcontrib><creatorcontrib>Coulthard, Tom J.</creatorcontrib><creatorcontrib>Molnar, Peter</creatorcontrib><creatorcontrib>Freer, Jim</creatorcontrib><title>The impact of different rainfall products on landscape modelling simulations</title><title>Earth surface processes and landforms</title><description>Rainfall products can contain significantly different spatiotemporal estimates, depending on their underlying data and final constructed resolution. Commonly used products, such as rain gauges, rain gauge networks, and weather radar, differ in their information content regarding intensities, spatial variability, and natural climatic variability, therefore producing different estimates. Landscape evolution models (LEMs) simulate the geomorphic changes in landscapes, and current models can simulate timeframes from event level to millions of years and some use rainfall inputs to drive them. However, the impact of different rainfall products on LEM outputs has never been considered. This study uses the STREAP rainfall generator, calibrated using commonly used rainfall observation products, to produce longer rainfall records than the observations to drive the CAESAR‐Lisflood LEM to examine how differences in rainfall products affect simulated landscapes. The results show that the simulation of changes to basin geomorphology is sensitive to the differences between rainfall products, with these differences expressed linearly in discharges but non‐linearly in sediment yields. Furthermore, when applied over a 1500‐year period, large differences in the simulated long profiles were observed, with the simulations producing greater sediment yields showing erosion extending further downstream. This suggests that the choice of rainfall product to drive LEMs has a large impact on the final simulated landscapes. The combination of rainfall generator model and LEMs represents a potentially powerful method for assessing the impacts of rainfall product differences on landscapes and their short‐ and long‐term evolution. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley &amp; Sons Ltd A weather generator was used to produce rainfall data to drive a landscape evolution model, and calibrated using different observation products. The simulated sediment yields and patterns of landscape change were sensitive to the differences in the observation products. The combination of weather generators and landscape evolution models presents a useful tool for assessing landscape changes due to climate change.</description><subject>Climate variability</subject><subject>Computer simulation</subject><subject>Earth surface</subject><subject>Evolution</subject><subject>Gauges</subject><subject>Geomorphology</subject><subject>Landforms</subject><subject>Landscape</subject><subject>landscape evolution</subject><subject>Meteorological radar</subject><subject>numerical modelling</subject><subject>Profiles</subject><subject>Radar</subject><subject>Rain</subject><subject>Rain gauges</subject><subject>Rainfall</subject><subject>Rainfall impact</subject><subject>Rainfall simulators</subject><subject>Sediment</subject><subject>Spatial variability</subject><subject>Spatial variations</subject><subject>uncertainty</subject><subject>Variability</subject><subject>Weather</subject><subject>weather generator</subject><subject>Weather radar</subject><issn>0197-9337</issn><issn>1096-9837</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp10MtKAzEUBuAgCtYq-AgBN26mJpPMJFlKqRcoKFjXIc1FU2aSMZlB-vam1q2rA4fvXPgBuMZogRGq72weFpQLegJmGIm2EpywUzBDWLBKEMLOwUXOO4QwLmoG1ptPC30_KD3C6KDxztlkwwiT8sGproNDimbSY4YxwE4Fk7UaLOyjsV3nwwfMvp86NfoY8iU4KyPZXv3VOXh_WG2WT9X65fF5eb-uFGkQrRTnijeuFfWWGc2FxYhgjQQjvKHabZ3FumE12TJcI-MOvYY53hhGjELCkjm4Oe4tv31NNo9yF6cUyklZU0owFbxti7o9Kp1izsk6OSTfq7SXGMlDVrJkJQ9ZFVod6bfv7P5fJ1dvr7_-B2pkavQ</recordid><startdate>20200915</startdate><enddate>20200915</enddate><creator>Skinner, Christopher J.</creator><creator>Peleg, Nadav</creator><creator>Quinn, Niall</creator><creator>Coulthard, Tom J.</creator><creator>Molnar, Peter</creator><creator>Freer, Jim</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0001-8853-9606</orcidid><orcidid>https://orcid.org/0000-0002-8164-0442</orcidid></search><sort><creationdate>20200915</creationdate><title>The impact of different rainfall products on landscape modelling simulations</title><author>Skinner, Christopher J. ; Peleg, Nadav ; Quinn, Niall ; Coulthard, Tom J. ; Molnar, Peter ; Freer, Jim</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3504-a88a85f692b7dc89e1031c0973854cfbfe1c5723b7120df54cf57f85d73da09e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Climate variability</topic><topic>Computer simulation</topic><topic>Earth surface</topic><topic>Evolution</topic><topic>Gauges</topic><topic>Geomorphology</topic><topic>Landforms</topic><topic>Landscape</topic><topic>landscape evolution</topic><topic>Meteorological radar</topic><topic>numerical modelling</topic><topic>Profiles</topic><topic>Radar</topic><topic>Rain</topic><topic>Rain gauges</topic><topic>Rainfall</topic><topic>Rainfall impact</topic><topic>Rainfall simulators</topic><topic>Sediment</topic><topic>Spatial variability</topic><topic>Spatial variations</topic><topic>uncertainty</topic><topic>Variability</topic><topic>Weather</topic><topic>weather generator</topic><topic>Weather radar</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Skinner, Christopher J.</creatorcontrib><creatorcontrib>Peleg, Nadav</creatorcontrib><creatorcontrib>Quinn, Niall</creatorcontrib><creatorcontrib>Coulthard, Tom J.</creatorcontrib><creatorcontrib>Molnar, Peter</creatorcontrib><creatorcontrib>Freer, Jim</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library (Open Access Collection)</collection><collection>CrossRef</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><jtitle>Earth surface processes and landforms</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Skinner, Christopher J.</au><au>Peleg, Nadav</au><au>Quinn, Niall</au><au>Coulthard, Tom J.</au><au>Molnar, Peter</au><au>Freer, Jim</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The impact of different rainfall products on landscape modelling simulations</atitle><jtitle>Earth surface processes and landforms</jtitle><date>2020-09-15</date><risdate>2020</risdate><volume>45</volume><issue>11</issue><spage>2512</spage><epage>2523</epage><pages>2512-2523</pages><issn>0197-9337</issn><eissn>1096-9837</eissn><abstract>Rainfall products can contain significantly different spatiotemporal estimates, depending on their underlying data and final constructed resolution. Commonly used products, such as rain gauges, rain gauge networks, and weather radar, differ in their information content regarding intensities, spatial variability, and natural climatic variability, therefore producing different estimates. Landscape evolution models (LEMs) simulate the geomorphic changes in landscapes, and current models can simulate timeframes from event level to millions of years and some use rainfall inputs to drive them. However, the impact of different rainfall products on LEM outputs has never been considered. This study uses the STREAP rainfall generator, calibrated using commonly used rainfall observation products, to produce longer rainfall records than the observations to drive the CAESAR‐Lisflood LEM to examine how differences in rainfall products affect simulated landscapes. The results show that the simulation of changes to basin geomorphology is sensitive to the differences between rainfall products, with these differences expressed linearly in discharges but non‐linearly in sediment yields. Furthermore, when applied over a 1500‐year period, large differences in the simulated long profiles were observed, with the simulations producing greater sediment yields showing erosion extending further downstream. This suggests that the choice of rainfall product to drive LEMs has a large impact on the final simulated landscapes. The combination of rainfall generator model and LEMs represents a potentially powerful method for assessing the impacts of rainfall product differences on landscapes and their short‐ and long‐term evolution. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley &amp; Sons Ltd A weather generator was used to produce rainfall data to drive a landscape evolution model, and calibrated using different observation products. The simulated sediment yields and patterns of landscape change were sensitive to the differences in the observation products. The combination of weather generators and landscape evolution models presents a useful tool for assessing landscape changes due to climate change.</abstract><cop>Bognor Regis</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/esp.4894</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-8853-9606</orcidid><orcidid>https://orcid.org/0000-0002-8164-0442</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0197-9337
ispartof Earth surface processes and landforms, 2020-09, Vol.45 (11), p.2512-2523
issn 0197-9337
1096-9837
language eng
recordid cdi_proquest_journals_2443149866
source Access via Wiley Online Library
subjects Climate variability
Computer simulation
Earth surface
Evolution
Gauges
Geomorphology
Landforms
Landscape
landscape evolution
Meteorological radar
numerical modelling
Profiles
Radar
Rain
Rain gauges
Rainfall
Rainfall impact
Rainfall simulators
Sediment
Spatial variability
Spatial variations
uncertainty
Variability
Weather
weather generator
Weather radar
title The impact of different rainfall products on landscape modelling simulations
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T10%3A33%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20impact%20of%20different%20rainfall%20products%20on%20landscape%20modelling%20simulations&rft.jtitle=Earth%20surface%20processes%20and%20landforms&rft.au=Skinner,%20Christopher%20J.&rft.date=2020-09-15&rft.volume=45&rft.issue=11&rft.spage=2512&rft.epage=2523&rft.pages=2512-2523&rft.issn=0197-9337&rft.eissn=1096-9837&rft_id=info:doi/10.1002/esp.4894&rft_dat=%3Cproquest_cross%3E2443149866%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2443149866&rft_id=info:pmid/&rfr_iscdi=true