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dc.creatorMasselink, Rens Heines_ES
dc.creatorTemme, A. J. A. M.es_ES
dc.creatorGiménez Díaz, Rafaeles_ES
dc.creatorCasalí Sarasíbar, Javieres_ES
dc.creatorKeesstra, S. D.es_ES
dc.identifier.issn0211-6820 (Print)
dc.identifier.issn1697-9540 (Electronic)
dc.description.abstractSoil erosion from agricultural areas is a large problem because of off-site effects like the rapid filling of reservoirs. To mitigate the problem of sediments from agricultural areas reaching the channel, reservoirs and other surface areas it is important to understand hillslope-channel connectivity and catchment connectivity. To determine the functioning of hillslope-channel connectivity and the continuation of transport of these sediments in the channel, it is necessary to obtain data on sediment transport from the hillslopes to the channels. Simultaneously, the factors that influence sediment export out of the catchment need to be studied. For measuring hillslope-channel sediment connectivity, rare-earth oxide (REO) tracers were applied to a hillslope in an agricultural catchment in Navarre, Spain, preceding the winter of 2014-2015. The results showed that during the winter no sediment transport from the hillslope to the channel was detected. To test the implication of the REO results at the catchment scale, two contrasting conceptual models for sediment connectivity were assessed using a random forest (RF) machine learning method. The RF method was applied using a 15-year period of measured sediment output at the catchment scale. One model proposes that small events provide sediment for large events, while the other proposes that only large events cause sediment detachment and small events subsequently remove these sediments from near and in the channel. For sediment yield prediction of small events, variables related to large preceding events were the most important. The model for large events underperformed and, therefore, we could not draw any immediate conclusions whether small events influence the amount of sediment exported during large events. Both REO tracers and RF method showed that low intensity events do not contribute any sediments from the hillslopes to the channel in Latxaga catchment. Sediment dynamics are dominated by sediment mobilization during large (high intensity) events. Sediments are for a large part exported during those events, but the system shows a memory of the occurrence of these large events, suggesting that large amounts of sediments are deposited in and near the channel after these events. These sediments are gradually removed by small events. To better understand the delivery if sediments to the channel and how large and small events influence each other, more field data on hillslope-channel connectivity and within-channel sediment dynamics is necessary.en
dc.description.sponsorshipThis study was funded by the Dutch Organization for Scientific Research (NWO), grant number 822.01.004, The Spanish Ministry of Science and Innovation, project CGL2015-64284-C2-1-R (MINECO-FEDER) and COST action ES 1306.en
dc.format.extent21 p.
dc.publisherUniversidad de la Riojaen
dc.relation.ispartofCuadernos de Investigación Geográfica 2017, nº 43 (1), pp. 19-39en
dc.rights© Universidad de La Rioja. Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)en
dc.subjectTrazadores de sedimentoses_ES
dc.subjectSelvas aleatoriases_ES
dc.subjectConectividad ladera-caucees_ES
dc.subjectSediment tracingen
dc.subjectRandom forestsen
dc.subjectHillslope-channel connectivityen
dc.titleAssessing hillslope-channel connectivity in an agricultural catchment using rare-earth oxide tracers and random forests modelsen
dc.title.alternativeValorando la conectividad ladera-cauce en una cuenca agrícola utilizando óxidos de tierras raras como trazadores y modelos de selvas aleatoriases_ES
dc.typeArtículo / Artikuluaes
dc.contributor.departmentUniversidad Pública de Navarra. Departamento de Proyectos e Ingeniería Rurales_ES
dc.contributor.departmentNafarroako Unibertsitate Publikoa. Landa Ingeniaritza eta Proiektuak Sailaeu
dc.contributor.departmentUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa. ISFOOD - Institute for Innovation and Sustainable Development in Food Chaines_ES
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.type.versionVersión publicada / Argitaratu den bertsioaes

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© Universidad de La Rioja. Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)
Except where otherwise noted, this item's license is described as © Universidad de La Rioja. Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)