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Master's Thesis in Geography Physical Geography Mesoscale Modelling of Periglacial Landforms in the Circumpolar Arctic Tommi K

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Master's Thesis in Geography Physical Geography Mesoscale Modelling of Periglacial Landforms in the Circumpolar Arctic Tommi K Master’s thesis in Geography Physical Geography Mesoscale modelling of periglacial landforms in the circumpolar Arctic Tommi Kukkonen 2020 Supervisor: Miska Luoto Master’s Programme in Geography University of Helsinki Faculty of Science Department of geosciences and geography P. O. Box 64 (Gustaf Hällströmin katu 2) 00014 University of Helsinki Tiedekunta – Fakultet – Faculty Koulutusohjelma – Utbildningsprogram – Degree programme Faculty of Science Master's Programme in Geography Opintosuunta – Studieinrikting – Study track Physical Geography Tekijä – Författare – Author Tommi Kukkonen Työn nimi – Arbetets titel – Title Mesoscale modelling of periglacial landforms in the circumpolar Arctic Työn laji – Arbetets art – Level Aika – Datum – Month and year Sivumäärä – Sidoantal – Number of pages Master's thesis May 2020 86 pages Tiivistelmä – Referat – Abstract The Arctic is warming with an increased pace, and it can affect ecosystems, infrastructure and communities. By studying periglacial landforms and processes, and using improved methods, more knowledge on these changing environmental conditions and their impacts can be obtained. The aim of this thesis is to map studied landforms and predict their probability of occurrence in the circumpolar region utilizing different modelling methods. Periglacial environments occur in high latitudes and other cold regions. These environments host permafrost, which is frozen ground and responds effectively to climate warming, and underlays areas that host many landform types. Therefore, landform monitoring and modelling in permafrost regions under changing climate can provide information about the ongoing changes in the Arctic and landform distributions. Here four landform/process types were mapped and studied: patterned ground, pingos, thermokarst activity and solifluction. The study consisted of 10 study areas across the circumpolar arctic that were mapped for their landforms. The study utilized GLM, GAM and GBM analyses in determining landform occurrences in the arctic based on environmental variables. Model calibration utilized logit link function, and evaluation explained the deviance value. Data was sampled to evaluation and calibration sets to assess prediction abilities. The predictive accuracy of the models was assessed using ROC/AUC values. Thermokarst activity proved to be most abundant in studied areas, whereas solifluction activity was most scarce. Pingos were discovered evenly throughout studied areas, and patterned ground activity was absent in some areas but rich in others. Climate variables and mean annual ground temperature had the biggest influence in explaining landform occurrence throughout the circumpolar region. GBM proved to be the most accurate and had the best predictive performance. The results show that mapping and modelling in mesoscale is possible, and in the future, similar studies could be utilized in monitoring efforts regarding global change and in studying environmental and periglacial landform/process interactions. Avainsanat – Nyckelord – Keywords periglacial landforms, logistic regression, Arctic, modelling Säilytyspaikka – Förvaringställe – Where deposited HELDA, an open access repository of the University of Helsinki Muita tietoja – Övriga uppgifter – Additional information Tiedekunta – Fakultet – Faculty Koulutusohjelma – Utbildningsprogram – Degree programme Matemaattis-Luonnontieteellinen tiedekunta Maantieteen maisteriohjelma Opintosuunta – Studieinrikting – Study track Luonnonmaantiede Tekijä – Författare – Author Tommi Kukkonen Työn nimi – Arbetets titel – Title Periglasiaalisten muodostumien mesoskaalainen mallinnus sirkumpolaarisella Arktiksella Työn laji – Arbetets art – Level Aika – Datum – Month and year Sivumäärä – Sidoantal – Number of pages Kirjallinen tutkielma Toukokuu 2020 86 sivua Tiivistelmä – Referat – Abstract Arktinen alue lämpenee kiihtyvällä tahdilla, ja sillä voi olla merkittäviä vaikutuksia ekosysteemeihin, infrastruktuuriin ja alueen yhteisöihin. Tutkimalla periglasiaalisia muodostumia ja prosesseja, sekä hyödyntämällä paranneltuja menetelmiä on mahdollista saada lisätietoa muuttuvista ympäristöolosuhteista ja niiden vaikutuksista. Tämän opinnäytetyön tarkoituksena on kartoittaa tutkimuksen kohteena olevia muodostumia/prosesseja ja pyrkiä ennustamaan niiden esiintymisen todennäköisyys sirkumpolaarisella vyöhykkeellä hyödyntäen eri mallinnusmenetelmiä. Periglasiaalisia ympäristöjä esiintyy korkeilla leveysasteilla ja muilla kylmillä alueilla. Tavallisesti näissä ympäristöissä esiintyy myös ikiroutaa, joka on jäätynyttä maata ja joka reagoi tehokkaasti ilmaston lämpenemiseen. Ikirouta-alueilla esiintyy monia muodostumatyyppejä, joita tutkimalla ja mallintamalla voidaan saada tietoa muuttuvista olosuhteista Arktiksella sekä muodostumien ja prosessien levinneisyyksistä. Tässä tutkimuksessa tarkastelun kohteena oli neljä eri muodostumatyyppiä: kuviomaat, pingot, termokarstiaktiivisuus sekä solifluktio. Tutkimus koostui kymmenestä tutkimusalueesta sirkumpolaarisella Arktiksella, joista kaikista kartoitettiin muodostumia. Tutkimuksessa hyödynnettiin GLM, GAM ja GBM analyyseja, joilla mallinnettiin muodostumien esiintymistä Arktisella alueella perustuen ympäristömuuttujiin. Mallien kalibroinnissa hyödynnettiin logit linkkifunktiota ja evaluoinnissa selitettyä poikkeavuutta. Data jaettiin evaluaatio- ja kalibraatio aineistoihin, jotta ennustekapasiteettia voitiin arvioida. Ennusteiden tarkkuuden määrityksessä hyödynnettiin ROC/AUC arvoja. Termokarstiaktiivisuutta esiintyi eniten tutkituilla alueilla, ja solifluktiota kaikkein vähiten. Pingoja esiintyi tasaisesti kaikilla alueilla. Kuviomaata ei löytynyt tietyiltä alueilta, mutta jollain alueilla sitä esiintyi runsaasti. Ilmastomuuttujat ja maanpinnan keskilämpötila osoittautuivat merkittävimmiksi muuttujiksi selitettäessä muodostumien esiintyvyyttä sirkumpolaarisella alueella. GBM oli mallinnusmenetelmistä tarkin ja sillä oli paras ennustuskyky. Tulokset osoittavat, että kartoitus ja mallinnus mesoskaalassa on mahdollista. Tulevaisuudessa tuloksia voitaisiin hyödyntää Arktisen alueen monitorointi- ja globaalimuutostutkimuksiin, sekä mahdollisesti arvioitaessa periglasiaalisten muodostumien suhdetta alueellisiin ympäristömuuttujiin. Avainsanat – Nyckelord – Keywords periglasiaaliset muodostumat, logistinen regressio, Arktinen alue, mallinnus Säilytyspaikka – Förvaringställe – Where deposited HELDA, Helsingin yliopiston avoin digitaalinen arkisto Muita tietoja – Övriga uppgifter – Additional information Table of contents 1. Introduction .......................................................................................................................... 1 2. Theoretical background ........................................................................................................ 2 2.1 Northern circumpolar region ........................................................................................ 2 2.2 Periglacial environment ................................................................................................ 3 2.3 Global change ............................................................................................................... 6 2.4 Studied periglacial formations ...................................................................................... 7 2.4.1 Patterned ground .................................................................................................. 7 2.4.2 Pingos .................................................................................................................... 9 2.4.3 Thermokarst activity ........................................................................................... 12 2.4.4 Solifluction .......................................................................................................... 14 2.5 Modelling in geomorphological research ................................................................... 17 2.5.1 Nonlinearity ........................................................................................................ 18 3. Study area ........................................................................................................................... 19 3.1 Russia and Northern Asia ............................................................................................ 21 3.2 North America ............................................................................................................. 22 4. Methods .............................................................................................................................. 24 4.1 Methodological background ....................................................................................... 24 4.1.1 Generalized linear models .................................................................................. 24 4.1.2 Generalized additive models .............................................................................. 25 4.1.3 Generalized boosting methods ........................................................................... 25 4.2 Modelling material ...................................................................................................... 26 4.2.1 Model calibration and evaluation ....................................................................... 28 5. Results ................................................................................................................................. 30 5.1 The occurrence of periglacial formations ..................................................................
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