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...
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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. |
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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 & 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 & 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 & 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 & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & 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 & 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> |
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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 |
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