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A conundrum of trends
(2022)
This comment is meant to reiterate two warnings: One applies to the uncritical use of ready-made (openly available) program packages, and one to the estimation of trends in serially correlated time series. Both warnings apply to the recent publication of Lischeid et al. about lake-level trends in Germany.
Quantifying the extremeness of heavy precipitation allows for the comparison of events. Conventional quantitative indices, however, typically neglect the spatial extent or the duration, while both are important to understand potential impacts. In 2014, the weather extremity index (WEI) was suggested to quantify the extremeness of an event and to identify the spatial and temporal scale at which the event was most extreme. However, the WEI does not account for the fact that one event can be extreme at various spatial and temporal scales. To better understand and detect the compound nature of precipitation events, we suggest complementing the original WEI with a “cross-scale weather extremity index” (xWEI), which integrates extremeness over relevant scales instead of determining its maximum.
Based on a set of 101 extreme precipitation events in Germany, we outline and demonstrate the computation of both WEI and xWEI. We find that the choice of the index can lead to considerable differences in the assessment of past events but that the most extreme events are ranked consistently, independently of the index. Even then, the xWEI can reveal cross-scale properties which would otherwise remain hidden. This also applies to the disastrous event from July 2021, which clearly outranks all other analyzed events with regard to both WEI and xWEI.
While demonstrating the added value of xWEI, we also identify various methodological challenges along the required computational workflow: these include the parameter estimation for the extreme value distributions, the definition of maximum spatial extent and temporal duration, and the weighting of extremeness at different scales. These challenges, however, also represent opportunities to adjust the retrieval of WEI and xWEI to specific user requirements and application scenarios.
Die Gesellschaft befindet sich längst in einem digitalen Transformationsprozess. Alle gesellschaftlichen Bereiche verändern sich. Man spricht von einer Kultur der Digitalität, die den Leitmedienwechsel vom gedruckten Buch hin zum vernetzten digitalen Endgerät beschreibt. Auch die Institution „Schule“ muss sich diesem Wandel öffnen. Einen wesentlichen Schritt stellt das Strategiepapier der Kultusministerkonferenz „Bildung in der digitalen Welt“ aus dem Jahr 2017 dar. Darin legt sie die wesentlichen Handlungsfelder zu einem digitalen Wandel fest und erweitert den Bildungsauftrag um die „Kompetenzen in der digitalen Welt“.
Das sog. SAMR-Modell stellt dabei ein geeignetes Umsetzungs- und Reflektionswerkzeug für den Einsatz digitaler Medien dar. Es strukturiert den Einsatz auf vier Stufen. Die beiden unteren Stufen (Substitution und Augmentation) schreiben der Art und Weise, wie die digitalen Medien genutzt werden, eine Ersatz- oder Verbesserungsfunktion des analogen Lernwerkzeuges zu. Ziel des Modells ist es aber, mithilfe hinzugewonnener digitaler Möglichkeiten, Lernen neu zu gestalten. Da das Modell aus den USA stammt, weist es weder direkten Bezüge zum Strategiepapier der Kultusministerkonferenz noch zu den Bildungsstandards der Geographie auf.
Diese wissenschaftliche Arbeit stellt diese Bezüge her. Ziel ist es, auf der Grundlage des SAMR-Modells ein Handlungskonzept für Geographielehrkräfte zu entwickeln. Es zeigt auf, wie sie sowohl fachliche Kompetenzen als auch Kompetenzen in der digitalen Welt systematisch bei den Lernenden fördern können.
Climate change is one of the greatest challenges to humanity in this century, and most noticeable consequences are expected to be impacts on the water cycle – in particular the distribution and availability of water, which is fundamental for all life on Earth. In this context, it is essential to better understand where and when water is available and what processes influence variations in water storages. While estimates of the overall terrestrial water storage (TWS) variations are available from the GRACE satellites, these represent the vertically integrated signal over all water stored in ice, snow, soil moisture, groundwater and surface water bodies. Therefore, complementary observational data and hydrological models are still required to determine the partitioning of the measured signal among different water storages and to understand the underlying processes. However, the application of large-scale observational data is limited by their specific uncertainties and the incapacity to measure certain water fluxes and storages. Hydrological models, on the other hand, vary widely in their structure and process-representation, and rarely incorporate additional observational data to minimize uncertainties that arise from their simplified representation of the complex hydrologic cycle.
In this context, this thesis aims to contribute to improving the understanding of global water storage variability by combining simple hydrological models with a variety of complementary Earth observation-based data. To this end, a model-data integration approach is developed, in which the parameters of a parsimonious hydrological model are calibrated against several observational constraints, inducing GRACE TWS, simultaneously, while taking into account each data’s specific strengths and uncertainties. This approach is used to investigate 3 specific aspects that are relevant for modelling and understanding the composition of large-scale TWS variations.
The first study focusses on Northern latitudes, where snow and cold-region processes define the hydrological cycle. While the study confirms previous findings that seasonal dynamics of TWS are dominated by the cyclic accumulation and melt of snow, it reveals that inter-annual TWS variations on the contrary, are determined by variations in liquid water storages. Additionally, it is found to be important to consider the impact of compensatory effects of spatially heterogeneous hydrological variables when aggregating the contribution of different storage components over large areas. Hence, the determinants of TWS variations are scale-dependent and underlying driving mechanism cannot be simply transferred between spatial and temporal scales. These findings are supported by the second study for the global land areas beyond the Northern latitudes as well.
This second study further identifies the considerable impact of how vegetation is represented in hydrological models on the partitioning of TWS variations. Using spatio-temporal varying fields of Earth observation-based data to parameterize vegetation activity not only significantly improves model performance, but also reduces parameter equifinality and process uncertainties. Moreover, the representation of vegetation drastically changes the contribution of different water storages to overall TWS variability, emphasizing the key role of vegetation for water allocation, especially between sub-surface and delayed water storages. However, the study also identifies parameter equifinality regarding the decay of sub-surface and delayed water storages by either evapotranspiration or runoff, and thus emphasizes the need for further constraints hereof.
The third study focuses on the role of river water storage, in particular whether it is necessary to include computationally expensive river routing for model calibration and validation against the integrated GRACE TWS. The results suggest that river routing is not required for model calibration in such a global model-data integration approach, due to the larger influence other observational constraints, and the determinability of certain model parameters and associated processes are identified as issues of greater relevance. In contrast to model calibration, considering river water storage derived from routing schemes can already significantly improve modelled TWS compared to GRACE observations, and thus should be considered for model evaluation against GRACE data.
Beyond these specific findings that contribute to improved understanding and modelling of large-scale TWS variations, this thesis demonstrates the potential of combining simple modeling approaches with diverse Earth observational data to improve model simulations, overcome inconsistencies of different observational data sets, and identify areas that require further research. These findings encourage future efforts to take advantage of the increasing number of diverse global observational data.
The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021–2050) and far-term period (2071–2100) with reference to 1976–2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50% during 2021–2050 and between +131 and +388% during 2071–2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.
Quantifying the extremeness of heavy precipitation allows for the comparison of events. Conventional quantitative indices, however, typically neglect the spatial extent or the duration, while both are important to understand potential impacts. In 2014, the weather extremity index (WEI) was suggested to quantify the extremeness of an event and to identify the spatial and temporal scale at which the event was most extreme. However, the WEI does not account for the fact that one event can be extreme at various spatial and temporal scales. To better understand and detect the compound nature of precipitation events, we suggest complementing the original WEI with a “cross-scale weather extremity index” (xWEI), which integrates extremeness over relevant scales instead of determining its maximum.
Based on a set of 101 extreme precipitation events in Germany, we outline and demonstrate the computation of both WEI and xWEI. We find that the choice of the index can lead to considerable differences in the assessment of past events but that the most extreme events are ranked consistently, independently of the index. Even then, the xWEI can reveal cross-scale properties which would otherwise remain hidden. This also applies to the disastrous event from July 2021, which clearly outranks all other analyzed events with regard to both WEI and xWEI.
While demonstrating the added value of xWEI, we also identify various methodological challenges along the required computational workflow: these include the parameter estimation for the extreme value distributions, the definition of maximum spatial extent and temporal duration, and the weighting of extremeness at different scales. These challenges, however, also represent opportunities to adjust the retrieval of WEI and xWEI to specific user requirements and application scenarios.
The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021-2050) and far-term period (2071-2100) with reference to 1976-2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50% during 2021-2050 and between +131 and +388% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.
Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available.
Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available.
The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021–2050) and far-term period (2071–2100) with reference to 1976–2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50% during 2021–2050 and between +131 and +388% during 2071–2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.
Die Arbeit gibt einen Einblick in die Verständigungspraxen bei Stadtführungen mit (ehemaligen) Obdachlosen, die in ihrem Selbstverständnis auf die Herstellung von Verständnis, Toleranz und Anerkennung für von Obdachlosigkeit betroffene Personen zielen. Zunächst wird in den Diskurs des Slumtourismus eingeführt und, angesichts der Vielfalt der damit verbundenen Erscheinungsformen, Slumming als organisierte Begegnung mit sozialer Ungleichheit definiert. Die zentralen Diskurslinien und die darin eingewobenen moralischen Positionen werden nachvollzogen und im Rahmen der eigenommenen wissenssoziologischen Perspektive als Ausdruck einer per se polykontexturalen Praxis re-interpretiert. Slumming erscheint dann als eine organisierte Begegnung von Lebensformen, die sich in einer Weise fremd sind, als dass ein unmittelbares Verstehen unwahrscheinlich erscheint und genau aus diesem Grund auf der Basis von gängigen Interpretationen des Common Sense ausgehandelt werden muss. Vor diesem Hintergrund untersucht die vorliegende Arbeit, wie sich Teilnehmer und Stadtführer über die Erfahrung der Obdachlosigkeit praktisch verständigen und welcher Art das hierüber erzeugte Verständnis für die im öffentlichen Diskurs mit vielfältigen stigmatisierenden Zuschreibungen versehenen Obdachlosen ist. Dabei interessiert besonders, in Bezug auf welche Aspekte der Erfahrung von Obdachlosigkeit ein gemeinsames Verständnis möglich wird und an welchen Stellen dieses an Grenzen gerät. Dazu wurden die Gesprächsverläufe auf neun Stadtführungen mit (ehemaligen) obdachlosen Stadtführern unterschiedlicher Anbieter im deutschsprachigen Raum verschriftlicht und mit dem Verfahren der Dokumentarischen Methode ausgewertet. Die vergleichende Betrachtung der Verständigungspraxen eröffnet nicht zuletzt eine differenzierte Perspektive auf die in den Prozessen der Verständigung immer schon eingewobenen Anerkennungspraktiken. Mit Blick auf die moralische Debatte um organisierte Begegnungen mit sozialer Ungleichheit wird dadurch eine ethische Perspektive angeregt, in deren Zentrum Fragen zur Vermittlungsarbeit stehen.
Increasing arctic coastal erosion rates imply a greater release of sediments and organic matter into the coastal zone. With 213 sediment samples taken around Herschel Island-Qikiqtaruk, Canadian Beaufort Sea, we aimed to gain new insights on sediment dynamics and geochemical properties of a shallow arctic nearshore zone. Spatial characteristics of nearshore sediment texture (moderately to poorly sorted silt) are dictated by hydrodynamic processes, but ice-related processes also play a role. We determined organic matter (OM) distribution and inferred the origin and quality of organic carbon by C/N ratios and stable carbon isotopes delta C-13. The carbon content was higher offshore and in sheltered areas (mean: 1.0 wt.%., S.D.: 0.9) and the C/N ratios also showed a similar spatial pattern (mean: 11.1, S.D.: 3.1), while the delta C-13 (mean: -26.4 parts per thousand VPDB, S.D.: 0.4) distribution was more complex. We compared the geochemical parameters of our study with terrestrial and marine samples from other studies using a bootstrap approach. Sediments of the current study contained 6.5 times and 1.8 times less total organic carbon than undisturbed and disturbed terrestrial sediments, respectively. Therefore, degradation of OM and separation of carbon pools take place on land and continue in the nearshore zone, where OM is leached, mineralized, or transported beyond the study area.
Hydrogeological information about an aquifer is difficult and costly to obtain, yet essential for the efficient management of groundwater resources. Transferring information from sampled sites to a specific site of interest can provide information when site-specific data is lacking. Central to this approach is the notion of site similarity, which is necessary for determining relevant sites to include in the data transfer process. In this paper, we present a data-driven method for defining site similarity. We apply this method to selecting groups of similar sites from which to derive prior distributions for the Bayesian estimation of hydraulic conductivity measurements at sites of interest. We conclude that there is now a unique opportunity to combine hydrogeological expertise with data-driven methods to improve the predictive ability of stochastic hydrogeological models.
How fast the Northern Hemisphere (NH) forest biome tracks strongly warming climates is largely unknown. Regional studies reveal lags between decades and millennia. Here we report a conundrum: Deglacial forest expansion in the NH extra-tropics occurs approximately 4000 years earlier in a transient MPI-ESM1.2 simulation than shown by pollen-based biome reconstructions. Shortcomings in the model and the reconstructions could both contribute to this mismatch, leaving the underlying causes unresolved. The simulated vegetation responds within decades to simulated climate changes, which agree with pollen-independent reconstructions. Thus, we can exclude climate biases as main driver for differences. Instead, the mismatch points at a multi-millennial disequilibrium of the NH forest biome to the climate signal. Therefore, the evaluation of time-slice simulations in strongly changing climates with pollen records should be critically reassessed. Our results imply that NH forests may be responding much slower to ongoing climate changes than Earth System Models predict. <br /> Deglacial forest expansion in the Northern Hemisphere poses a conundrum: Model results agree with the climate signal but are several millennia ahead of reconstructed forest dynamics. The underlying causes remain unsolved.
High-mountain regions provide valuable ecosystem services, including food, water, and energy production, to more than 900 million people worldwide. Projections hold, that this population number will rapidly increase in the next decades, accompanied by a continued urbanisation of cities located in mountain valleys. One of the manifestations of this ongoing socio-economic change of mountain societies is a rise in settlement areas and transportation infrastructure while an increased power need fuels the construction of hydropower plants along rivers in the high-mountain regions of the world. However, physical processes governing the cryosphere of these regions are highly sensitive to changes in climate and a global warming will likely alter the conditions in the headwaters of high-mountain rivers. One of the potential implications of this change is an increase in frequency and magnitude of outburst floods – highly dynamic flows capable of carrying large amounts of water and sediments. Sudden outbursts from lakes formed behind natural dams are complex geomorphological processes and are often part of a hazard cascade. In contrast to other types of natural hazards in high-alpine areas, for example landslides or avalanches, outburst floods are highly infrequent. Therefore, observations and data describing for example the mode of outburst or the hydraulic properties of the downstream propagating flow are very limited, which is a major challenge in contemporary (glacial) lake outburst flood research. Although glacial lake outburst floods (GLOFs) and landslide-dammed lake outburst floods (LLOFs) are rare, a number of documented events caused high fatality counts and damage. The highest documented losses due to outburst floods since the start of the 20th century were induced by only a few high-discharge events. Thus, outburst floods can be a significant hazard to downvalley communities and infrastructure in high-mountain regions worldwide.
This thesis focuses on the Greater Himalayan region, a vast mountain belt stretching across 0.89 million km2. Although potentially hundreds of outburst floods have occurred there since the beginning of the 20th century, data on these events is still scarce. Projections of cryospheric change, including glacier-mass wastage and permafrost degradation, will likely result in an overall increase of the water volume stored in meltwater lakes as well as the destabilisation of mountain slopes in the Greater Himalayan region. Thus, the potential for outburst floods to affect the increasingly more densely populated valleys of this mountain belt is also likely to increase in the future. A prime example of one of these valleys is the Pokhara valley in Nepal, which is drained by the Seti Khola, a river crossing one of the steepest topographic gradients in the Himalayas. This valley is also home to Nepal’s second largest, rapidly growing city, Pokhara, which currently has a population of more than half a million people – some of which live in informal settlements within the floodplain of the Seti Khola. Although there is ample evidence for past outburst floods along this river in recent and historic times, these events have hardly been quantified.
The main motivation of my thesis is to address the data scarcity on past and potential future outburst floods in the Greater Himalayan region, both at a regional and at a local scale. For the former, I compiled an inventory of >3,000 moraine-dammed lakes, of which about 1% had a documented sudden failure in the past four decades. I used this data to test whether a number of predictors that have been widely applied in previous GLOF assessments are statistically relevant when estimating past GLOF susceptibility. For this, I set up four Bayesian multi-level logistic regression models, in which I explored the credibility of the predictors lake area, lake-area dynamics, lake elevation, parent-glacier-mass balance, and monsoonality. By using a hierarchical approach consisting of two levels, this probabilistic framework also allowed for spatial variability on GLOF susceptibility across the vast study area, which until now had not been considered in studies of this scale. The model results suggest that in the Nyainqentanglha and Eastern Himalayas – regions with strong negative glacier-mass balances – lakes have been more prone to release GLOFs than in regions with less negative or even stable glacier-mass balances. Similarly, larger lakes in larger catchments had, on average, a higher probability to have had a GLOF in the past four decades. Yet, monsoonality, lake elevation, and lake-area dynamics were more ambiguous. This challenges the credibility of a lake’s rapid growth in surface area as an indicator of a pending outburst; a metric that has been applied to regional GLOF assessments worldwide.
At a local scale, my thesis aims to overcome data scarcity concerning the flow characteristics of the catastrophic May 2012 flood along the Seti Khola, which caused 72 fatalities, as well as potentially much larger predecessors, which deposited >1 km³ of sediment in the Pokhara valley between the 12th and 14th century CE. To reconstruct peak discharges, flow depths, and flow velocities of the 2012 flood, I mapped the extents of flood sediments from RapidEye satellite imagery and used these as a proxy for inundation limits. To constrain the latter for the Mediaeval events, I utilised outcrops of slackwater deposits in the fills of tributary valleys. Using steady-state hydrodynamic modelling for a wide range of plausible scenarios, from meteorological (1,000 m³ s-1) to cataclysmic outburst floods (600,000 m³ s-1), I assessed the likely initial discharges of the recent and the Mediaeval floods based on the lowest mismatch between sedimentary evidence and simulated flood limits. One-dimensional HEC-RAS simulations suggest, that the 2012 flood most likely had a peak discharge of 3,700 m³ s-1 in the upper Seti Khola and attenuated to 500 m³ s-1 when arriving in Pokhara’s suburbs some 15 km downstream.
Simulations of flow in two-dimensions with orders of magnitude higher peak discharges in ANUGA show extensive backwater effects in the main tributary valleys. These backwater effects match the locations of slackwater deposits and, hence, attest for the flood character of Mediaeval sediment pulses. This thesis provides first quantitative proof for the hypothesis, that the latter were linked to earthquake-triggered outbursts of large former lakes in the headwaters of the Seti Khola – producing floods with peak discharges of >50,000 m³ s-1.
Building on this improved understanding of past floods along the Seti Khola, my thesis continues with an analysis of the impacts of potential future outburst floods on land cover, including built-up areas and infrastructure mapped from high-resolution satellite and OpenStreetMap data. HEC-RAS simulations of ten flood scenarios, with peak discharges ranging from 1,000 to 10,000 m³ s-1, show that the relative inundation hazard is highest in Pokhara’s north-western suburbs. There, the potential effects of hydraulic ponding upstream of narrow gorges might locally sustain higher flow depths. Yet, along this reach, informal settlements and gravel mining activities are close to the active channel. By tracing the construction dynamics in two of these potentially affected informal settlements on multi-temporal RapidEye, PlanetScope, and Google Earth imagery, I found that exposure increased locally between three- to twentyfold in just over a decade (2008 to 2021).
In conclusion, this thesis provides new quantitative insights into the past controls on the susceptibility of glacial lakes to sudden outburst at a regional scale and the flow dynamics of propagating flood waves released by past events at a local scale, which can aid future hazard assessments on transient scales in the Greater Himalayan region. My subsequent exploration of the impacts of potential future outburst floods to exposed infrastructure and (informal) settlements might provide valuable inputs to anticipatory assessments of multiple risks in the Pokhara valley.
Pokhara (ca. 850 m a.s.l.), Nepal's second-largest city, lies at the foot of the Higher Himalayas and has more than tripled its population in the past 3 decades. Construction materials are in high demand in rapidly expanding built-up areas, and several informal settlements cater to unregulated sand and gravel mining in the Pokhara Valley's main river, the Seti Khola. This river is fed by the Sabche glacier below Annapurna III (7555 m a.s.l.), some 35 km upstream of the city, and traverses one of the steepest topographic gradients in the Himalayas. In May 2012 a sudden flood caused >70 fatalities and intense damage along this river and rekindled concerns about flood risk management. We estimate the flow dynamics and inundation depths of flood scenarios using the hydrodynamic model HEC-RAS (Hydrologic Engineering Center’s River Analysis System). We simulate the potential impacts of peak discharges from 1000 to 10 000 m3 s−1 on land cover based on high-resolution Maxar satellite imagery and OpenStreetMap data (buildings and road network). We also trace the dynamics of two informal settlements near Kaseri and Yamdi with high potential flood impact from RapidEye, PlanetScope, and Google Earth imagery of the past 2 decades. Our hydrodynamic simulations highlight several sites of potential hydraulic ponding that would largely affect these informal settlements and sites of sand and gravel mining. These built-up areas grew between 3- and 20-fold, thus likely raising local flood exposure well beyond changes in flood hazard. Besides these drastic local changes, about 1 % of Pokhara's built-up urban area and essential rural road network is in the highest-hazard zones highlighted by our flood simulations. Our results stress the need to adapt early-warning strategies for locally differing hydrological and geomorphic conditions in this rapidly growing urban watershed.
In-depth understanding of the potential implications of climate change is required to guide decision- and policy-makers when developing adaptation strategies and designing infrastructure suitable for future conditions. Impact models that translate potential future climate conditions into variables of interest are needed to create the causal connection between a changing climate and its impact for different sectors. Recent surveys suggest that the primary strategy for validating such models (and hence for justifying their use) heavily relies on assessing the accuracy of model simulations by comparing them against historical observations. We argue that such a comparison is necessary and valuable, but not sufficient to achieve a comprehensive evaluation of climate change impact models. We believe that a complementary, largely observation-independent, step of model evaluation is needed to ensure more transparency of model behavior and greater robustness of scenario-based analyses. This step should address the following four questions: (1) Do modeled dominant process controls match our system perception? (2) Is my model's sensitivity to changing forcing as expected? (3) Do modeled decision levers show adequate influence? (4) Can we attribute uncertainty sources throughout the projection horizon? We believe that global sensitivity analysis, with its ability to investigate a model's response to joint variations of multiple inputs in a structured way, offers a coherent approach to address all four questions comprehensively. Such additional model evaluation would strengthen stakeholder confidence in model projections and, therefore, into the adaptation strategies derived with the help of impact models. This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change
Pokhara (ca. 850 m a.s.l.), Nepal's second-largest city, lies at the foot of the Higher Himalayas and has more than tripled its population in the past 3 decades. Construction materials are in high demand in rapidly expanding built-up areas, and several informal settlements cater to unregulated sand and gravel mining in the Pokhara Valley's main river, the Seti Khola. This river is fed by the Sabche glacier below Annapurna III (7555 m a.s.l.), some 35 km upstream of the city, and traverses one of the steepest topographic gradients in the Himalayas. In May 2012 a sudden flood caused >70 fatalities and intense damage along this river and rekindled concerns about flood risk management. We estimate the flow dynamics and inundation depths of flood scenarios using the hydrodynamic model HEC-RAS (Hydrologic Engineering Center’s River Analysis System). We simulate the potential impacts of peak discharges from 1000 to 10 000 m3 s−1 on land cover based on high-resolution Maxar satellite imagery and OpenStreetMap data (buildings and road network). We also trace the dynamics of two informal settlements near Kaseri and Yamdi with high potential flood impact from RapidEye, PlanetScope, and Google Earth imagery of the past 2 decades. Our hydrodynamic simulations highlight several sites of potential hydraulic ponding that would largely affect these informal settlements and sites of sand and gravel mining. These built-up areas grew between 3- and 20-fold, thus likely raising local flood exposure well beyond changes in flood hazard. Besides these drastic local changes, about 1 % of Pokhara's built-up urban area and essential rural road network is in the highest-hazard zones highlighted by our flood simulations. Our results stress the need to adapt early-warning strategies for locally differing hydrological and geomorphic conditions in this rapidly growing urban watershed.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.