Local- and Regional-Scale Forcing of Glacier Mass Balance Changes in the Swiss Alps

Glacier mass variations are climate indicators. Therefore, it is essential to examine both winter and summer mass balance variability over a long period of time to address climate-related ice mass fluctuations. In this study, we analyze glacier mass balance components and hypsometric characteristics with respect to their interactions with local meteorological variables and remote large-scale atmospheric and oceanic patterns. The results show that all selected glaciers have lost their equilibrium condition in recent decades, with persistent negative annual mass balance trends and decreasing accumulation area ratios (AARs), accompanied by increasing air temperatures of +0.45 C decade 1. The controlling factor of annual mass balance is mainly attributed to summer mass losses, which are correlated with (warming) June to September air temperatures. In addition, the interannual variability of summer and winter mass balances is primarily associated to the Atlantic Multidecadal Oscillation (AMO), Greenland Blocking Index (GBI), and East Atlantic (EA) teleconnections. Although climate parameters are playing a significant role in determining the glacier mass balance in the region, the observed correlations and mass balance trends are in agreement with the hypsometric distribution and morphology of the glaciers. The analysis of decadal frontal retreat using Landsat images from 1984 to 2014 also supports the findings of this research, highlighting the impact of lake formation at terminus areas on rapid glacier retreat and mass loss in the Swiss Alps

Evolution of Glacial and High-Altitude Lakes in the Sikkim, Eastern Himalaya Over the Past Four Decades (1975–2017)

Global climate change is significantly triggering the dynamic evolution of high-mountain lakes which may pose a serious threat to downstream areas, warranting their systematic and regular monitoring. This study presents the first temporal inventory of glacial and high-altitude lakes in the Sikkim, Eastern Himalaya for four points in time i.e., 1975, 1991, 2000, and 2017 using Hexagon, TM, ETM+, and OLI images, respectively. First, a baseline data was generated for the year 2000 and then the multi-temporal lake changes were assessed. The annual mapping of SGLs was also performed for four consecutive years (2014–2017) to analyze their nature and occurrence pattern. The results show an existence of 463 glacial and high-altitude lakes (> 0.003 km2) in 2000 which were grouped into four classes: supraglacial (SGL; 50) pro/peri glacial lake in contact with glacier (PGLC; 35), pro/peri glacial lake away from glacier (PGLA; 112) and other lakes (OL; 266). The mean size of lakes is 0.06 km2 and about 87% lakes have area < 0.1 km2. The number of lakes increased (by 9%) from 425 in 1975 to 466 in 2017, accompanied by a rapid areal expansion from 25.17 ± 1.90 to 31.24 ± 2.36 km2 (24%). The maximum expansion in number (106%) and area (138%) was observed in SGLs, followed by PGLCs (number: 34%; area: 90%). Contrarily no significant change was found in other lakes. The annual SGL mapping reveals that their number (area) increased from 81 (543,153 m2) to 96 (840,973 m2) between 2014 and 2017. Occurrence pattern of SGLs shows that maximum number of lakes (> 80%) are persistent in nature, followed by drain-out (15–20%) and recurring type lakes (7–8%). The new-formed lakes (9–17%) were consistently noticed in all the years (2014–2017). The results of this study underline that regional climate is accelerating the cryosphere thawing and if the current trend continues, further glacier melting will likely occur. Therefore, formation of new lakes and expansion of existing lakes is expected in the study area leading to increase in potential of glacial lake outburst floods. Thereby, persistent attention should be paid to the influences of climatic change in the region

Dynamic changes at tidewater glacier termini in central west Greenland

The Greenland Ice Sheet rapidly lost mass over the last two decades, in part due to increases in ice loss from termini of large tidewater glaciers. Terminus melting and calving can drive glacier retreat and the pattern of ice sheet mass loss through reductions in resistive stresses near the glacier front and, in turn, increases in ice flow to the ocean. Despite their importance to ice sheet mass balance, factors controlling terminus positions are poorly constrained in ice sheet models, which fundamentally obscures sea level rise predictions. In this dissertation, I use a suite of novel observations and techniques to quantify controls on frontal ablation and terminus positions at tidewater glaciers in central west Greenland. Until recently, frontal ablation processes were obscured due to limited observations of submarine termini. Here, I use observations from multibeam echo sonar to show the morphological complexity of the submarine terminus face and identify previously unrecognized melting and calving processes. The terminus features numerous secondary subglacial plume outlets outside of the main subglacial channel system that drive and disperse large submarine melt rates across the glacier front. Submarine melting drives steep, localized terminus undercutting that can trigger calving by connecting to finely-spaced surface crevasses. In turn, large calving events cause the terminus face to become anomalously overcut. Incorporating observed outlet geometries in a numerical plume model, I estimate small subglacial discharge fluxes feeding secondary plume outlets that are reminiscent of a distributed subglacial network. Regional remote-sensing observations reveal that, for most glaciers in central west Greenland, seasonal terminus positions are more sensitive to glacial runoff than ice mélange or ocean thermal forcing. Shallow, serac-failing tidewater glaciers are most sensitive, where subglacial plumes melt the terminus and locally enhance retreat. Glaciers with large ice fluxes and deep termini retreat sporadically through full ice-thickness calving events less dependent on runoff. Together, these results provide process-oriented constraints on the shape of the submarine terminus face, the geometry of subglacial discharge and submarine melting, the influence of environmental forcing mechanisms and the impact that these variables have on terminus positions and dynamics in a warming climate.Geological Science

Patterns of tree establishment and vegetation composition in relation to climate and topography of a subalpine meadow landscape, Jefferson Park, Oregon, USA

The forest alpine tundra ecotone (FTE, also known as alpine treeline or subalpine parkland), is a conspicuous feature of mountain landscapes throughout the world. Climate change-driven increases in temperature are believed to result in FTE movement and tree invasion of subalpine meadows, which have been documented throughout the Northern Hemisphere across a wide range of geographic locations, climatic regimes, forest types, land use histories, and disturbance regimes. Climate-driven FTE movement may have numerous ecological effects such as: positive temperature feedbacks, increased net primary productivity and carbon storage, and declines of plant populations and species. The magnitude of these ecological effects is highly uncertain, but will be largely determined by the rates and spatial extent of FTE movement and meadow invasion. FTE movement and meadow invasion are often considered at global or regional spatial scales in relation to climate, yet they are fundamentally driven by tree regeneration processes that are influenced by a variety of climatic and biophysical factors at micro site, landscape, and regional scales. Much of the research on the FTE has not taken a landscape approach incorporating multi-scale processes. For example, species distribution models used to project climate change effects on future species distributions and plant biodiversity in mountainous landscapes rely on species distribution data that is often sparse and incomplete across FTE landscapes. This dissertation attempts to overcome many of the limitations in FTE research by taking a landscape approach to develop a greater understanding of past spatiotemporal patterns of tree invasion, current spatial patterns of vegetation composition and structure, and potential future patterns of climate-driven tree invasion in the FTE. The setting for this research is Jefferson Park, a 260 ha subalpine parkland landscape in the Oregon High Cascades, USA. This study uses field plots, remotely sensed imagery, airborne Light Detection and Ranging (LiDAR), and simulation modeling to: 1) predictively map current fine-scale species distributions, vegetation structure, and tree ages; 2) reconstruct patterns of tree invasion over the last fifty years in subalpine meadows in relation to climatic conditions, landforms, microtopography, and seed dispersal limitations; and 3) develop a statistical model that projects future patterns of tree invasion into subalpine meadows under different climate scenarios in Jefferson Park. In chapter two, I generated fine-scale spatially-explicit predictions of current vegetation composition, structure, and tree ages in the Jefferson Park study area. Objectives of this chapter were threefold: 1) to characterize spatial patterns of tree ages, vegetation composition, and vegetation structure in a FTE landscape in the Oregon Cascades using predictive mapping; 2) determine how vegetation composition and structure were associated with gradients of environmental factors derived from multispectral satellite imagery and Light Detection and Ranging (LiDAR) data; and 3) determine if predictive mapping characterizations of tree age, vegetation composition, and vegetation structure were improved by the inclusion of LiDAR data. Predictive mapping of vegetation attributes was accomplished using gradient analysis with nearest neighbor imputation; integrating field plots, multispectral SPOT 5 satellite imagery, and LiDAR data. Vegetation composition was best described by SPOT 5 imagery and LiDAR-derived topography, while vegetation structure was best described by LiDAR-derived vegetation heights. Predictions of species occurrence were most accurate for tree species, moderate for shrub species and vegetation groups, and highly variable for graminoid species. Tree age, which was the most accurately predicted vegetation structure variable, indicates the study area was largely un-forested in 1600, gradually invaded by trees from 1600 to the 1920's, and rapidly invaded from the 1920's to 1980. Predictive mapping of vegetation structure variables such as basal area and stand density were subject to large amounts of error, possibly resulting from scale incompatibilities between vegetation patterns and plot size, and/or heterogeneous FTE landscapes where forest structure does not develop along consistent trajectories with stand age. This study suggests integrating multispectral satellite imagery, LiDAR data, and field plots can accurately predict fine-scale spatial characterizations of species distributions and tree invasion in the FTE. This study also indicates that sample design can influence spatial patterns of model uncertainty, which needs to be considered if predictive mapping of vegetation and sensitive ecosystems is a component of inventory and monitoring programs. In chapter three, I focused on quantifying spatiotemporal patterns of subalpine parkland tree invasion in Jefferson Park over the past five decades in relation multi-scale climatic and biophysical controls. LiDAR data provided previously unavailable fine-scale spatial characterizations of microtopography and vegetation structure. I utilized LiDAR, georeferenced field plots, and tree establishment reconstructions to quantify spatiotemporal patterns of tree invasion in relation to late season snow persistence, landform types, fine-scale topographic variability, distances from potential seed sources, and climate variation within 130 ha of the subalpine parkland landscape of Jefferson Park. Tree occurrence (i.e. tree presence in 2 m plots and grid cells) occurred in 7.75% of study area meadows in 1950 and increased to 34.7% in 2007. Landform types and finer-scale patterns of topography and vegetation structure influenced summer snow depth, which influenced temporal and spatial patterns of tree establishment. Tree invasion rates were higher on debris flow landforms, which had lower summer snow depth than glacial landforms, suggesting potentially rapid treeline responses to disturbance events. Tree invasion rates were strongly associated with reduced annual snow fall on glacial landforms, but not on debris flows. Tree establishment was spatially constrained to micro sites with high topographic positions and close proximity to overstory canopy, site conditions associated with low summer snow depth. Seed source limitations placed an additional species-specific spatial constraint on where trees invaded meadows. Climate and topography had an interactive effect, with trees establishing on higher topographic positions during both high snow/low temperature and low snow/high temperature periods, but had greater than expected establishment on lower topographic positions during low snow/high temperature periods. Within the context of larger landform types, topography and proximity to overstory trees constrained where trees established in the meadows, even during climate periods with higher temperatures and lower snowfall. Results of this study suggest large scale climate-driven models of vegetation change may overestimate treeline movement and meadow invasion, because they do not account for biophysical controls limiting tree establishment at multiple spatial scales. In chapter four, I used field data and analyses from chapter 3 to parameterize a spatially and temporally explicit statistical model of fine-scale tree invasion within 130 ha of the Jefferson Park study area. The model incorporated both the climatic and biophysical controls found in chapter 3 to influence tree invasion. The model was used in two ways: (1) to spatially project patterns of tree invasion from 1950 to 2007 in response to historical climate; and (2) to project future tree invasion of the study area from 2007 to 2064 under six different annual snowfall scenarios. Modeling addressed the following questions: (1) Can fine-scale (2 m pixel size) patterns of historical tree invasion be accurately predicted? (2) How sensitive is future tree invasion (and therefore meadow persistence) to different future snowfall scenarios? (3) Are non-climatic factors such as landforms and biotic interactions associated with different spatial patterns of tree invasion? From 1950 to 2007, simulated historical meadow area declined from 82% to 65% of the study area. Model outputs of historical area, spatial distributions, and spatial clustering of tree invasion generally agreed with independent validation, and suggest biotic interactions due to young tree establishment facilitation are important on glacial landforms but not debris flows. Simulations of future scenarios indicated meadow declined to 36 to 43% of the study area by 2064. Projected meadow area declined with reduced annual snow fall, but not under prolonged high and low snow fall periods. Meadows persisted under all future scenarios in 2064. This model suggests subalpine meadows may significantly decline under climate warming, but will still persist in 2064. Micro sites and recruitment limitation may be equally or more important factors than climate change in influencing subalpine landscape change, suggesting local high-elevation persistence of subalpine meadows under future climate warming

Vegetation Dynamics Revealed by Remote Sensing and Its Feedback to Regional and Global Climate

This book focuses on some significant progress in vegetation dynamics and their response to climate change revealed by remote sensing data. The development of satellite remote sensing and its derived products offer fantastic opportunities to investigate vegetation changes and their feedback to regional and global climate systems. Special attention is given in the book to vegetation changes and their drivers, the effects of extreme climate events on vegetation, land surface albedo associated with vegetation changes, plant fingerprints, and vegetation dynamics in climate modeling

Assessment of climate change and development of data based prediction models of sediment yields in Upper Indus Basin

Hohe Raten von Sedimentflüssen und ihre Schätzungen in Flusseinzugsgebieten erfordern die Auswahl effizienter Quantifizierungsansätze mit einem besseren Verständnis der dominierten Faktoren, die den Erosionsprozess auf zeitlicher und räumlicher Ebene steuern. Die vorherige Bewertung von Einflussfaktoren wie Abflussvariation, Klima, Landschaft und Fließprozess ist hilfreich, um den geeigneten Modellierungsansatz zur Quantifizierung der Sedimenterträge zu entwickeln. Einer der schwächsten Aspekte bei der Quantifizierung der Sedimentfracht ist die Verwendung traditioneller Beziehung zwischen Strömungsgeschwindigkeit und Bodensatzlöschung (SRC), bei denen die hydrometeorologischen Schwankungen, Abflusserzeugungsprozesse wie Schneedecke, Schneeschmelzen, Eisschmelzen usw. nicht berücksichtigt werden können. In vielen Fällen führt die empirische Q-SSC Beziehung daher zu ungenauen Prognosen. Heute können datenbasierte Modelle mit künstlicher Intelligenz die Sedimentfracht präziser abschätzen. Die datenbasierten Modelle lernen aus den eingespeisten Datensätzen, indem sie bei komplexen Phänomenen wie dem Sedimenttransport die geeignete funktionale Beziehung zwischen dem Output und seinen Input-Variablen herstellen. In diesem Zusammenhang wurden die datenbasierten Modellierungsalgorithmen in der vorliegenden Forschungsarbeit am Lehrstuhl für Wasser- und Flussgebietsmanagement des Karlsruher Instituts für Technologie in Karlsruhe entwickelt, die zur Vorhersage von Sedimenten in oberen unteren Einzugsgebieten des oberen Indusbeckens von Pakistan (UIB) verwendet wurden. Die dieser Arbeit zugrunde liegende Methodik gliedert sich in vier Bearbeitungsschritte: (1) Vergleichende Bewertung der räumlichen Variabilität und der Trends von Abflüssen und Sedimentfrachten unter dem Einfluss des Klimawandels im oberen Indus-Becken (2) Anwendung von Soft-Computing-Modellen mit Eingabevektoren der schneedeckten Fläche zusätzlich zu hydro-klimatischen Daten zur Vorhersage der Sedimentfracht (3) Vorhersage der Sedimentfracht unter Verwendung der NDVI-Datensätze (Hydroclimate and Normalized Difference Vegetation Index) mit Soft-Computing-Modellen (4) Klimasignalisierung bei suspendierten Sedimentausträge aus Gletscher und Schnee dominierten Teileinzugsgebeiten im oberen Indus-Becken (UIB). Diese im UIB durchgeführte Analyse hat es ermöglicht, die dominiertenden Parameter wie Schneedecke und hydrologischen Prozesses besser zu und in eine verbesserte Prognose der Sedimentfrachten einfließen zu lassen. Die Analyse der Bewertung des Klimawandels von Flüssen und Sedimenten in schnee- und gletscherdominierten UIB von 13 Messstationen zeigt, dass sich die jährlichen Flüsse und suspendierten Sedimente am Hauptindus in Besham Qila stromaufwärts des Tarbela-Reservoirs im ausgeglichenen Zustand befinden. Jedoch, die jährlichen Konzentrationen suspendierter Sedimente (SSC) wurden signifikant gesenkt und lagen zwischen 18,56% und 28,20% pro Jahrzehnt in Gilgit an der Alam Bridge (von Schnee und Gletschern dominiertes Becken), Indus in Kachura und Brandu in Daggar (von weniger Niederschlag dominiertes Becken). Während der Sommerperiode war der SSC signifikant reduziert und lag zwischen 18,63% und 27,79% pro Jahrzehnt, zusammen mit den Flüssen in den Regionen Hindukush und West-Karakorum aufgrund von Anomalien des Klimawandels und im unteren Unterbecken mit Regen aufgrund der Niederschlagsreduzierung. Die SSC während der Wintersaison waren jedoch aufgrund der signifikanten Erwärmung der durchschnittlichen Lufttemperatur signifikant erhöht und lagen zwischen 20,08% und 40,72% pro Jahrzehnt. Die datenbasierte Modellierung im schnee und gletscherdominierten Gilgit Teilbecken unter Verwendung eines künstlichen neuronalen Netzwerks (ANN), eines adaptiven Neuro-Fuzzy-Logik-Inferenzsystems mit Gitterpartition (ANFIS-GP) und eines adaptiven Neuro-Fuzzy-Logik-Inferenzsystems mit subtraktivem Clustering (ANFIS) -SC), ein adaptives Neuro-Fuzzy-Logik- Inferenzsystem mit Fuzzy-C-Mittel-Clustering, multiplen adaptiven Regressionssplines (MARS) und Sedimentbewertungskurven (SRC) durchgeführt. Die Ergebnisse von Algorithmen für maschinelles Lernen zeigen, dass die Eingabekombination aus täglichen Abflüssen (Qt), Schneedeckenfläche (SCAt), Temperatur (Tt-1) und Evapotranspiration (Evapt-1) die Leistung der Sedimentvorhersagemodelle verbesserne. Nach dem Vergleich der Gesamtleistung der Modelle schnitt das ANN-Modell besser ab als die übrigen Modelle. Bei der Vorhersage der Sedimentfrachten in Spitzenzeiten lag die Vorhersage der ANN-, ANIS-FCM- und MARS-Modelle näher an den gemessenen Sedimentbelastungen. Das ANIS-FCM-Modell mit einem absoluten Gesamtfehler von 81,31% schnitt bei der Vorhersage der Spitzensedimente besser ab als ANN und MARS mit einem absoluten Gesamtfehler von 80,17% bzw. 80,16%. Die datenbasierte Modellierung der Sedimentfrachten im von Regen dominierten Brandu-Teilbecken wurde unter Verwendung von Datensätzen für Hydroklima und biophysikalische Eingaben durchgeführt, die aus Strömungen, Niederschlag, mittlerer Lufttemperatur und normalisiertem Differenzvegetationsindex (NDVI) bestehen. Die Ergebnisse von vier ANNs (Artificial Neural Networks) und drei ANFIS-Algorithmen (Adaptive Neuro-Fuzzy Logic Inference System) für das Brandu Teilnbecken haben gezeigt, dass der mittels Fernerkundung bestimmte NDVI als biophysikalische Parameter zusätzlich zu den Hydroklima-Parametern die Leistung das Modell nicht verbessert. Der ANFIS-GP schnitt in der Testphase besser ab als andere Modelle mit einer Eingangskombination aus Durchfluss und Niederschlag. ANN, eingebettet in Levenberg-Marquardt (ANN-LM) für den Zeitraum 1981-2010, schnitt jedoch am besten mit Eingabekombinationen aus Strömungen, Niederschlag und mittleren Lufttemperaturen ab. Die Ergebnisgenauigkeit R2 unter Verwendung des ANN-LM-Algorithmus verbesserte sich im Vergleich zur Sedimentbewertungskurve (SRC) um bis zu 28%. Es wurde gezeigt, dass für den unteren Teil der UIB-Flüsse Niederschlag und mittlere Lufttemperatur dominierende Faktoren für die Vorhersage von Sedimenterträgen sind und biophysikalische Parameter (NDVI) eine untergeordnete Rolle spielen. Die Modellierung zur Bewertung der Änderungen des SSC in schnee- und gletschergespeiste Gilgit- und Astore-Teilbecken wurde unter Verwendung des Temp-Index degree day modell durchgeführt. Die Ergebnisse des Mann-Kendall-Trendtests in den Flüssen Gilgit und Astore zeigten, dass der Anstieg des SSC während der Wintersaison auf die Erwärmung der mittleren Lufttemperatur, die Zunahme der Winterniederschläge und die Zunahme der Schneeschmelzen im Winter zurückzuführen ist. Während der Frühjahrssaison haben die Niederschlags- und Schneedeckenanteile im Gilgit-Unterbecken zugenommen, im Gegensatz zu seiner Verringerung im Astore-Unterbecken. Im Gilgit-Unterbecken war der SSC im Sommer aufgrund des kombinierten Effekts der Karakorum-Klimaanomalie und der vergrößerten Schneedecke signifikant reduziert. Die Reduzierung des Sommer-SSC im Gilgit Fluss ist auf die Abkühlung der Sommertemperatur und die Bedeckung der exponierten proglazialen Landschaft zurückzuführen, die auf erhöhten Schnee, verringerte Trümmerflüsse Trümmerflüsse und verringerte Schneeschmelzen von Trümmergletschern zurückzuführen sind. Im Gegensatz zum Gilgit River sind die SSC im Astore River im Sommer erhöht. Der Anstieg des SSC im Astore-Unterbecken ist auf die Verringerung des Frühlingsniederschlags und der Schneedecke, die Erwärmung der mittleren Sommerlufttemperatur und den Anstieg des effektiven Niederschlags zurückzuführen. Die Ergebnisse zeigen ferner eine Verschiebung der Dominanz von Gletscherschmelzen zu Schneeschmelzen im Gilgit-Unterbecken und von Schnee zu Niederschlägen im Astore-Unterbecken bei Sedimenteden Sedimentfrachten in UIB. Die vorliegende Forschungsarbeit zur Bewertung der klimabedingten Veränderungen des SSC und seiner Vorhersage sowohl in den oberen als auch in den unteren Teilbecken des UIB wird nützlich sein, um den Sedimenttransportprozess besser zu verstehen und aufbauen auf dem verbessertenProzessverständnis ein angepasstes Sedimentmanagement und angepasste Planungen der zukünftigen Wasserinfrastrukturen im UIB ableiten zu können

From processes to predictions in hydrological modelling of glacierized basins

Glacierized mountain headwaters act as water towers, providing critical water resources to downstream environments when other sources are unavailable. These headwaters are currently witnessing a shift in their coupled hydrological and glaciological systems. This shift is reducing glacier volume, extent and elevation range, in addition to changing the snow dynamics across both glacierized and non-glacierized areas. These interconnected changes occur simultaneously, driven by complex physical feedbacks, and they impact streamflow generation processes. To properly characterize this transition period and predict future hydrological behaviour in these glacierized basins, physically based glacio-hydrological models representing the full range of both glacier and basin hydrological processes are needed. However, obtaining the data to apply such modelling approaches is complicated by the scarce data availability in mountain regions. New approaches to collect the required data and parametrize these complex processes need to be developed in parallel with increased process representations in glacio-hydrological models. This thesis aims to assess the impact of future climate and glacier change on glacierized basin hydrological processes and streamflow generation. Its specific objectives are to (1) develop and apply innovative approaches to characterize hydro-glaciological processes in glacierized basins, (2) diagnose hydrological and glaciological processes resulting in streamflow generation and variability and (3) assess the coupled impacts of climate and landscape change on the hydrological processes and streamflow generation in a glacierized basin. Field-based investigations of streamflow measurement uncertainty, sub-debris melt and surface energy balance were conducted and used to guide new and revised algorithms for the Cold Region Hydrological Modelling (CRHM) platform. Using CRHM with the newly added process representations for katabatic wind turbulent transfer, hourly energy balance and sub-debris melt, a physically based glacio-hydrological model was developed and tested in the Peyto Glacier Research Basin, a 53% glacierized headwater basin (as of 2013) located in the Canadian Rockies. This glacio-hydrological model was used to investigate the recent past and current (1990-2020) hydrology of the basin using in-situ weather observations. Over the 32 years, strong inter-annual variability in the meteorological forcings caused highly variable streamflow in this cold alpine basin. Snowmelt always provided the largest fraction of annual streamflow (44 to 89%), with lower snowmelt contributions occurring in high streamflow years. Ice melt provided between 10 to 45% of total streamflow, with a higher contribution associated with high flow years. Both rainfall-runoff and firn melt contributed less than 13% of annual streamflow. Years with high streamflow were on average 1.43˚C warmer than low streamflow years, and high streamflow years had lower winter snow accumulation, earlier snowmelt and higher summer rain than years with low streamflow. The glacier hydrology of current (2000-2015) and future periods (2085-2100) was compared, using bias-corrected, dynamically downscaled, convection-permitting high-resolution atmospheric model outputs. The simulations show that the end-of-century increase in precipitation, mainly expressed as an increase in rainfall at the expense of snowfall, will nearly compensate for the decreased ice melt associated with almost complete deglaciation, resulting in a decrease of 7% in annual streamflow. However, the timing of streamflow will advance substantially, with the timing of peak flow shifting from July to June, and August streamflow dropping by 68%. To examine the sensitivity of future hydrology to possible future post-glacial landscapes, the end-of-century simulations were run under a range of boundary conditions and were most sensitive to initial ice volume and surface water storage. This research provides better modelling techniques to represent the complex systems of headwater glacierized basins, as well as robust estimates of future glacier contributions to streamflow in reference basins of the Canadian Rockies and should be useful for water availability studies and water management mitigation strategies

Applicazione di tecniche remote sensing per lo studio dell'evoluzione e della dinamica criosferica in aree remote e di alta quota

I ghiacciai sono efficaci indicatori climatici poich\ue8 si modificano in risposta ai cambi del clima (es. temperatura e precipitazioni). L'attenzione sui ghiacciai di montagna sta aumentando tra la comunit\ue0 scientifica per via del loro sempre pi\uf9 evidente arretramento a scala globale negli ultimi cinquant'anni. Ci\uf2 \ue8 conseguenza del riscaldamento globale. Comprendere il comportamento dei ghiacciai in risposta al cambio climatico \ue8 di enorme importanza non solo per arricchire la conoscenza scientifica, ma anche per poter meglio gestire in futuro le situazioni di rischio naturale che possono colpire le popolazioni che vivono nelle zone montuose, sia nel breve termine (es. GLOF), sia nel lungo (es. Siccit\ue0). Questa tesi di dottorato analizza differenti aspetti della criosfera (ghiacciai e neve) per descriverne la variabilit\ue0 recente e le relazioni con la dinamica climatica. Inizialmente ci si \ue8 concentrati sul Karakorum. Questa \ue8 un\u2019area particolare per gli studi criosferici, che non segue i trend globali di regresso; infatti, in questa zona il bilancio di massa netto dei ghiacciai nei primi anni del ventunesimo secolo \ue8 stato leggermente positivo, con anche taluni casi di espansione. Questa eccezionale situazione \ue8 riconosciuta con il nome di Anomalia del Karakorum (Karakoram Anomaly). Pi\uf9 precisamente il presente elaborato si focalizza sulla zona del Central Karakoram National Park (CKNP), un'area protetta nel nord del Pakistan, rappresentativa della glaciazione dell'intera catena del Karakorum. In questa regione, i venti occidentali rappresentano il sistema di venti dominante e sono presenti nella stagione invernale, mentre la confinante regione Himalayana \ue8 sotto l'influenza predominante dei monsoni, che sono venti estivi. Il presente lavoro descrive in maniera completa lo stato dei ghiacciai del CKNP e la loro recente evoluzione. Ci\uf2 \ue8 stato possibile a seguito della compilazione del catasto glaciale del parco per gli anni 2001 e 2010, a sua volta descritto nel dettaglio nel presente elaborato. Inoltre \ue8 discussa l'analisi dei cambiamenti climatici poi messa in relazione con quelli glaciali, per poter comprendere le cause dietro l'Anomalia del Karakorum. Il cambiamento areale dei 711 ghiacciai mappati nell'area di studio \ue8 stato -0.4 \ub1 202.9 km2 (su 4605.9 \ub1 86.1 km2 nel 2001), il che evidenzia una generale situazione di stabilit\ue0. Anche l'analisi climatica supporta tale condizione di stabilit\ue0. Durante il periodo 2001\u20132010 si \ue8 osservato grazie ai dati del sensore MODIS un leggero aumento delle aree coperte da neve a fine estate. Allo stesso tempo, dati meteo dalle stazioni disponibili hanno rivelato un aumento delle nevicate e una diminuzione della temperatura media dell'aria in estate fin dal 1980, il che si tradurrebbe in coperture nivali pi\uf9 persistenti durante la stagione ablativa. Questi risultati vanno a favore della preservazione glaciale nelle zone di ablazione dovuta a una copertura di neve pi\uf9 duratura, e un maggiore accumulo a quote pi\uf9 alte, presupponendo bilanci di massa netti tendenti al segno positivo. L'altro principale obiettivo del presente elaborato di tesi \ue8 quello di fornire un modello di semplice utilizzo per quantificare l'ablazione di ghiaccio alla superficie glaciale. Dal momento che una copertura detritica sopraglaciale \ue8 in grado di alterare la fusione del ghiaccio vicino alla superficie in funzione dello spessore, il modello tiene conto di due diversi casi: una parte stima l'ablazione per le aree di ghiaccio scoperto con un metodo definito enhanced T-index; l'altra stima la fusione per le zone coperte da detrito, utilizzando un modello di flusso di calore conduttivo. Per quanto concerne le parti coperte da detrito, \ue8 stata prodotta una mappa degli spessori detritici che \ue8 poi stata usata come input per il modello, assieme alla radiazione solare entrante distribuita. Per le aree scoperte da detrito, sono state derivate la temperatura dell'aria e la radiazione entrante distribuite attraverso i dati delle stazioni meteo automatiche presenti nell'area, in seguito usate come input. L'altro parametro necessario \ue8 un modello di elevazione del terreno. In particolare, la distribuzione degli input meteorologici \ue8 stata validata con dati di altre due stazioni presenti all'interno del CKNP (le stazioni di Urdukas e Concordia). L'ablazione modellata \ue8 risultata essere fortemente concorde con le misurazioni effettuate sul ghiacciaio del Baltoro nel 2011, ghiacciaio rappresentativo di tutto il CKNP. Due campioni dello stesso set di dati di fusione misurati su terreno sono stati usati ciascuno rispettivamente in sede di calibrazione e validazione. La fusione nivale \ue8 stata ignorata dal momento che mancavano dati di neve sistematici nell'area di studio. Il modello \ue8 stato fatto girare durante il picco della stagione ablativa (23 luglio\u20139 agosto 2011), durante il quale l'acqua di fusione deriva primariamente dalla fusione glaciale, mentre quella nivale ha un ruolo decisamente minore in questa regione. Il modello ha calcolato un totale di acqua da fusione glaciale pari a 1.963 km3 (0.109 km3 al giorno in media). Quella derivante dalle parti coperte da detrito ammonta a 0.223 km3 (0.012 km3 al giorno in media; min\u2013max 0.006\u20130.016 km3 al giorno), mentre per le parti a ghiaccio scoperto \ue8 1.740 km3 (0.097 km3 al giorno in media; min\u2013max 0.041\u20130.139 km3 al giorno). Tale quantit\ue0 \ue8 paragonabile al 14% di tutta l'acqua contenuta in una grande diga strategica lungo il fiume Indo, di cui i ghiacciai del CKNP sono tributari. I test di sensitivit\ue0 del modello suggeriscono che un aumento delle superfici coperte da detrito sui ghiacciai (probabile per via dell'aumento di eventi di macrogelivazione e di frane) avr\ue0 un notevole impatto sulla fusione effettiva in funzione dei nuovi spessori detritici, e l'ablazione aumenter\ue0 sensibilmente se la temperatura dell'aria dovesse alzarsi. Successivamente l'attenzione del presente elaborato di tesi \ue8 concentrata sulle Ande Cilene e sulla variabilit\ue0 della copertura nevosa. Un obiettivo principale parallelo della presente ricerca \ue8 stato infatti quello di individuare una metodologia basata sul telerilevamento per studiare la variazione della copertura nevosa ad una risoluzione spazio-temporale accettabile. Il sensore MODIS si \ue8 rivelato il pi\uf9 idoneo allo scopo ed \ue8 stata implementata una metodologia che permettesse di estrarre mappe di copertura di neve in maniera automatica dalle informazioni raccolte dal sensore stesso. In particolare, sono stati studiati diciotto bacini idrografici di montagna delle Ande centrali in Cile durante il periodo 2008\u20132011. La stessa metodologia \ue8 stata esportata e adottata per l'analisi della neve nel CKNP come detto. L'area di studio \ue8 stata divisa in tre sotto-zone (Settentrionale, Centrale, Meridionale), per alleggerire il carico di calcolo dell'analisi. In generale, l'area coperta da neve \ue8 diminuita nel corso dei quattro anni di riferimento. I valori massimi sono stati ritrovati nella zona centrale, mentre fattori topografici e climatici (i.e. quote basse pi\uf9 a sud e un clima pi\uf9 arido nel nord), hanno limitato la deposizione della neve nelle altre zone. La linea della neve \ue8 pi\uf9 alta nella zona settentrionale a causa della presenza dell'altopiano, e si abbassa via via verso la zona merdionale. Nella zona settentrionale i minimi di copertura nivale vengono raggiunti prima che nelle altre zone e durano pi\uf9 a lungo (da novembre a marzo), probabilmente a causa del clima pi\uf9 arido. Durante l'intero periodo i valori massimi di copertura nevosa si ritrovano verso ovest. Al termine dell'elaborato e pertinente al tema principale delle applicazioni del telerilevamento allo studio della criosfera, sono presentati alcuni esempi di analisi di ghiacciai di diversa tipologia, dimensione e area geografica. Si tratta di sei casi, fra cui sono presenti tre ghiacciai alpini (Miage, Freney, Aletcsh), ghiacciai equatoriali (i ghiaccia del Kilimajaro), l'Harding Icefield in Alaska e un esempio di ghiacciaio antartico (la Drygalsky ice Tongue).Glaciers are sensitive climate indicators because they adjust their size in response to changes in climate (e.g. temperature and precipitation). The attention paid by the scientists to mountain glacier change is increasing as there are robust evidence of a global glacier shrinkage over the past five decades, which in turn is the consequence of global warming. Understanding the glacier response to climate change is of tremendous importance not only for improving scientific knowledge, but also to predict and manage water resources and natural risks for the people living in mountain areas in the short (e.g. glacier lake outburst floods), and long term (e.g. droughts). In this thesis are analysed different cryospheric elements (mainly glaciers and snow coverage) to describe their recent evolution and to look for relations, if any, with climate trends. Firstly, the focus is put on the Karakoram glaciers. Although a general worldwide retreat of mountain glaciers has been acknowledged by the scientific community, the Karakoram region represents an exception in this sense. Indeed, the net mass balance of the glaciers here in the early twenty-first century was slightly positive, and even some are expanding and thickening. This anomalous behaviour is known as Karakoram Anomaly. More precisely the study area is the Central Karakoram National Park (CKNP), a protected national park in Northern Pakistan representative of the glaciation of the whole Karakoram Range. The westerlies represent the dominant wind system and they occur during winter, while the neighbour Himalayan region is mainly influenced by the summer moonson. A comprehensive description of the state of the CKNP glaciers and of their recent evolution is presented. This was made after the compilation of the glacier inventory of the park for the years 2001 and 2010, which is also presented. Moreover, the analysis of the regional climate change in the recent years is also discussed and related to the actual glacier change, in order to understand the causes behind the Karakoram Anomaly. The glacier area change of the 711 glaciers mapped in the study zone during 2001\u20132010 was only -0.4 \ub1 202.9 km2 (over 4605.9 \ub1 86.1 km2 in 2001), evidencing a general stability. The climate analysis supports glacier stability in the area. A slight increase in late summer snow cover area during 2001\u20132010 was observed from MODIS snow data. At the same time, the available weather stations revealed an increase of snowfall events and a decrease of mean summer air temperatures since 1980, which would translate into more persistent snow cover during the melt season. These results support an enhanced glacier preservation in the ablation areas due to a long-lasting snow cover, and stronger accumulation at higher altitudes, pushing towards positive net balances. The other major aim of the present work is to provide a simple model to evaluate ice melt at the glacier surface. As the supraglacial-debris cover can alter ice ablation close to the glacier surface depending on its thickness, the model was made up of two parts: one which computes the ice melt over the bare ice areas using an enhanced T-index formula; and one for the debris-covered areas using a conductive heat flux module. For the debris-covered parts, the debris thickness map is produced and then provided to the model as input for the computation, other than the distributed shortwave incoming radiation. For the bare ice areas, the modeled air temperature and shortwave incoming radiation are derived from the automatic weather stations present in the CKNP and given to the model. The other model requirement is the digital elevation model. In particular, the meteorological input data were distributed starting from data acquired at Askole automatic weather station, located within the CKNP. The meteorological distribution was validated by comparison with data from other two AWS in the same park limits (Urdukas and Concordia). The modeled ablation data were in strong agreement with measurements collected in the field during 2011 on Baltoro glacier, which is representative of CKNP glaciers. Two sets of the same ablation dataset collected in the field in the CNKP area were used separately for calibration and validation. Snow melt was neglected since snow data in the study area was not systematically available. The model was run against the peak ablation season (23 July\u20139 August 2011), when meltwater mainly comes from ice melt, with snow thaw playing a minor role in this region. The total freshwater from the ablation areas of CKNP glaciers estimated by the model was 1.963 km3 (0.109 km3 d\u20131 on average). The meltwater from the debris-covered parts was 0.223 km3 (0.012 km3 d\u20131 on average; min\u2013max 0.006\u20130.016 km3 d\u20131), and 1.740 km3 (0.097 km3 d\u20131 on average; min\u2013max 0.041\u20130.139 km3 d\u20131) from debris-free sectors. The estimated total freshwater corresponds to 14% of the water contained in a large strategic dam along the Indus River, of which all the CKNP glaciers are tributaries. The sensitivity tests suggest that any increase in the extent of debris coverage (which will likely occur due to augmented macrogelivation processes and rockfall events), will affect melt depending on new debris thickness, and melting will increase largely if summer air temperature increases. The second major focus of this research is put on the snow cover variability of the Chilean Andes. A parallel major aim of this research work is to implement a methodology based on remote sensing to study the snow cover variation on an acceptable spatio-temporal resolution. The MODIS sensor was chosen as the most suitable for this purpose and a methodology for deriving snow maps automatically from it is described and applied for analyzing the SCA variation over 18 watersheds of the central Andes in Chile during 2008\u20132011. The same methodology was then adopted for the climate analysis in the CKNP as mentioned. The study area was divided into three sub-zones (Northern, Central, and Southern), for easing the computation of the snow analysis. Overall, SCA decreased during the four considered years. The maximum SCA was found in the Central Zone, while the topographic and climatic features (i.e. lower altitudes in the South, and a drier climate in the North), limited snow deposition elsewhere. The snow line was found higher in the Northern zone due to the presence of the plateau, while it decreases southwards. In the Northern Zone the minimum SCA was reached sooner than elsewhere, and it lasted for a longer period (November to March), probably because of the drier climate. West aspects showed the maximum of SCA in all zones throughout the study period. Finally, some examples of application of remote sensing to glacier related studies is presented for glaciers of various typology, size, and localization. Six case studies are shown, amongst which there are three alpine glaciers (Miage, Freney, Aletcsh), equatorial glaciers (the Kilimanjaro glaciers), the Harding Icefield in Alaska, and an Antarctic glacier (the Drygalsky Ice Tongue)

The Influence of Measurement Scale and Uncertainty on Interpretations of River Migration

Environmental scientists increasingly use remotely-sensed images to measure how rivers develop over time and respond to upstream changes in environmental drivers such as land use, urbanization, deforestation and agricultural practices. These measurements are subject to uncertainty that can bias conclusions. The first step towards accurate interpretation of river channel change is properly quantifying and accounting for uncertainty involved in measuring changes in river morphology. In Chapter 2 we develop a comprehensive framework for quantifying uncertainty in measurements of river change derived from aerial images. The framework builds upon previous uncertainty research by describing best practices and context-specific strategies, comparing each approach and outlining how to best handle measurements that fall below the minimum level of detection. We use this framework in subsequent chapters to reduce the impact of erroneous measurements. Chapter 3 evaluates how the time interval between aerial images influences the rates at which river channels appear to laterally migrate across their floodplains. Multiple lines of evidence indicate that river migration measurements obtained over longer time intervals (20+ years) will underestimate the ‘true’ rate because the river channel is more likely to have reversed the direction of migration, which erases part of the record of gross erosion as seen from aerial images. If the images don’t capture channel reversals and periodic episodes of fast erosion, the river appears to have migrated a shorter distance (which corresponds to a slower rate) than reality. Obtaining multiple measurements over shorter time intervals (\u3c 5 years) and limiting direct comparisons to similar time intervals can reduce bias when inferring how river migration rates may have changed over time. Chapter 4 explores the physical processes governing the relationship between river curvature and the rate of river migration along a series of meander bends. We used fine-scale empirical measurements and geospatial analyses to confirm theory and models indicating that migration and curvature exhibit a monotonic relationship. The results will improve models seeking to emulate river meander migration patterns

Advancing the understanding for hydro-climatic controls on water balance and lake-level variability in the Tibetan Plateau: Hydrological modeling in data-scarce lake basins integrating multi-source data

The contrasting patterns of lake-level changes across the Tibetan Plateau (TP) are indicators of differences in the water balance over the TP. However, little is known about the key hydrological factors controlling this variability. The purpose of this study was to contribute to a more quantitative understanding of these factors for four selected lakes in the southern-central part of the TP: Nam Co and Tangra Yumco (increasing water levels), and Mapam Yumco and Paiku Co (stable or slightly decreasing water levels). Therefore, an integrated approach combining hydrological modeling, atmospheric-model output and remote-sensing data was developed. The J2000g hydrological model was adapted and extended according to the specific characteristics of closed-lake basins on the TP and driven with High Asia Refined analysis (HAR) data at 10 km resolution for the period 2001–2010. Differences in the mean annual water balances among the four basins are primarily related to higher precipitation totals and attributed runoff generation in the Nam Co and Tangra Yumco basins. Precipitation and associated runoff are the main driving forces for inter-annual lake variations. The glacier-meltwater contribution to the total basin runoff volume (between 14 and 30% averaged over the 10-year period) plays a less important role compared to runoff generation from rainfall and snowmelt in non-glacierized land areas. These results highlight the benefits of linking hydrological modeling with atmospheric-model output and satellite-derived data in regions where observation data are scarce, and the developed approach can be readily transferred to other data-scarce closed-lake basins, opening new directions of research