DC ElementWertSprache
dc.contributor.advisorUwe, Schneider-
dc.contributor.authorFajardo Puente, Andrea Catalina-
dc.date.accessioned2022-05-31T13:25:28Z-
dc.date.available2022-05-31T13:25:28Z-
dc.date.issued2021-
dc.identifier.urihttps://ediss.sub.uni-hamburg.de/handle/ediss/9540-
dc.description.abstractAgriculture is a sector that is highly sensitive to climate. Heatwave events in Germany, like in 2018, show us the relevance of having crop production systems focusing on climate mitigation and adaptation to produce more stable yields in the future. Crop models like the Environmental Policy Integrated Climate (EPIC) allow testing management strategies and their potential effects on yields, nitrogen emissions, and total organic carbon in the long term under three CO2 emissions scenarios that include the Representative Concentration Pathways (RCP) of 2.6, 4.5, and 8.5. This research uses a version of the EPIC model that includes an automatic irrigation option based on a specific field capacity fraction that allows a more realistic irrigation scheme in the model. These values range from no irrigation (0%) to 100% (full irrigation). This option allows a more realistic irrigation scheme in the model. The co-benefit with modified crop calendars and the inclusion of soybeans were also assessed. Lastly, it was analyzed the correlation strength between crop yields and temperature and precipitation indicators. This exploratory assessment helps explain the reason for the increase of crop yield penalties in the future. Although this study was conducted in a small area in northern Germany, the results are still relevant for regions with similar climatic conditions. They may apply similar adaptation strategies in the future to cope with climate change.en
dc.language.isoende_DE
dc.publisherStaats- und Universitätsbibliothek Hamburg Carl von Ossietzkyde
dc.rightshttp://purl.org/coar/access_right/c_abf2de_DE
dc.subject.ddc550: Geowissenschaftende_DE
dc.titleClimate Adaptation Strategies Assessment on the Northern-German Agriculture System: A Crop Model Studyen
dc.typedoctoralThesisen
dcterms.dateAccepted2022-03-08-
dc.rights.cchttps://creativecommons.org/licenses/by/4.0/de_DE
dc.rights.rshttp://rightsstatements.org/vocab/InC/1.0/-
dc.subject.bcl83.66: Agrarwirtschaftde_DE
dc.subject.gndSustainable agriculturede_DE
dc.subject.gndGründüngungde_DE
dc.subject.gndGlobal Climate Observing Systemde_DE
dc.subject.gndKlimade_DE
dc.subject.gndLandwirtschaftde_DE
dc.type.casraiDissertation-
dc.type.dinidoctoralThesis-
dc.type.driverdoctoralThesis-
dc.type.statusinfo:eu-repo/semantics/publishedVersionde_DE
dc.type.thesisdoctoralThesisde_DE
tuhh.type.opusDissertation-
thesis.grantor.departmentGeowissenschaftende_DE
thesis.grantor.placeHamburg-
thesis.grantor.universityOrInstitutionUniversität Hamburgde_DE
dcterms.DCMITypeText-
dc.identifier.urnurn:nbn:de:gbv:18-ediss-99611-
item.advisorGNDUwe, Schneider-
item.grantfulltextopen-
item.languageiso639-1other-
item.fulltextWith Fulltext-
item.creatorOrcidFajardo Puente, Andrea Catalina-
item.creatorGNDFajardo Puente, Andrea Catalina-
Enthalten in den Sammlungen:Elektronische Dissertationen und Habilitationen
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Dissertation.pdfDissertation_Fajardoc12e3fe6317e75ddbff8ea5c46ac562412.04 MBAdobe PDFÖffnen/Anzeigen
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