@phdthesis{Schmidt2024,
  author    = {Schmidt, Lena Katharina},
  title     = {Altered hydrological and sediment dynamics in high-alpine areas - Exploring the potential of machine-learning for estimating past and future changes},
  doi       = {10.25932/publishup-62330},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-623302},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxi, 129},
  year      = {2024},
  abstract  = {Climate change fundamentally transforms glaciated high-alpine regions, with well-known cryospheric and hydrological implications, such as accelerating glacier retreat, transiently increased runoff, longer snow-free periods and more frequent and intense summer rainstorms. These changes affect the availability and transport of sediments in high alpine areas by altering the interaction and intensity of different erosion processes and catchment properties. Gaining insight into the future alterations in suspended sediment transport by high alpine streams is crucial, given its wide-ranging implications, e.g. for flood damage potential, flood hazard in downstream river reaches, hydropower production, riverine ecology and water quality. However, the current understanding of how climate change will impact suspended sediment dynamics in these high alpine regions is limited. For one, this is due to the scarcity of measurement time series that are long enough to e.g. infer trends. On the other hand, it is difficult - if not impossible - to develop process-based models, due to the complexity and multitude of processes involved in high alpine sediment dynamics. Therefore, knowledge has so far been confined to conceptual models (which do not facilitate deriving concrete timings or magnitudes for individual catchments) or qualitative estimates ('higher export in warmer years') that may not be able to capture decreases in sediment export. Recently, machine-learning approaches have gained in popularity for modeling sediment dynamics, since their black box nature tailors them to the problem at hand, i.e. relatively well-understood input and output data, linked by very complex processes. Therefore, the overarching aim of this thesis is to estimate sediment export from the high alpine {\"O}tztal valley in Tyrol, Austria, over decadal timescales in the past and future - i.e. timescales relevant to anthropogenic climate change. This is achieved by informing, extending, evaluating and applying a quantile regression forest (QRF) approach, i.e. a nonparametric, multivariate machine-learning technique based on random forest. The first study included in this thesis aimed to understand present sediment dynamics, i.e. in the period with available measurements (up to 15 years). To inform the modeling setup for the two subsequent studies, this study identified the most important predictors, areas within the catchments and time periods. To that end, water and sediment yields from three nested gauges in the upper {\"O}tztal, Vent, S{\"o}lden and Tumpen (98 to almost 800 km² catchment area, 930 to 3772 m a.s.l.) were analyzed for their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. The findings suggest that the areas situated above 2500 m a.s.l., containing glacier tongues and recently deglaciated areas, play a pivotal role in sediment generation across all sub-catchments. In contrast, precipitation events were relatively unimportant (on average, 21 \% of annual sediment yield was associated to precipitation events). Thus, the second and third study focused on the Vent catchment and its sub-catchment above gauge Vernagt (11.4 and 98 km², 1891 to 3772 m a.s.l.), due to their higher share of areas above 2500 m. Additionally, they included discharge, precipitation and air temperature (as well as their antecedent conditions) as predictors. The second study aimed to estimate sediment export since the 1960s/70s at gauges Vent and Vernagt. This was facilitated by the availability of long records of the predictors, discharge, precipitation and air temperature, and shorter records (four and 15 years) of turbidity-derived sediment concentrations at the two gauges. The third study aimed to estimate future sediment export until 2100, by applying the QRF models developed in the second study to pre-existing precipitation and temperature projections (EURO-CORDEX) and discharge projections (physically-based hydroclimatological and snow model AMUNDSEN) for the three representative concentration pathways RCP2.6, RCP4.5 and RCP8.5. The combined results of the second and third study show overall increasing sediment export in the past and decreasing export in the future. This suggests that peak sediment is underway or has already passed - unless precipitation changes unfold differently than represented in the projections or changes in the catchment erodibility prevail and override these trends. Despite the overall future decrease, very high sediment export is possible in response to precipitation events. This two-fold development has important implications for managing sediment, flood hazard and riverine ecology. This thesis shows that QRF can be a very useful tool to model sediment export in high-alpine areas. Several validations in the second study showed good performance of QRF and its superiority to traditional sediment rating curves - especially in periods that contained high sediment export events, which points to its ability to deal with threshold effects. A technical limitation of QRF is the inability to extrapolate beyond the range of values represented in the training data. We assessed the number and severity of such out-of-observation-range (OOOR) days in both studies, which showed that there were few OOOR days in the second study and that uncertainties associated with OOOR days were small before 2070 in the third study. As the pre-processed data and model code have been made publically available, future studies can easily test further approaches or apply QRF to further catchments.},
  language  = {en}
}
@phdthesis{Brosinsky2015,
  author    = {Brosinsky, Arlena},
  title     = {Spectral fingerprinting},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-83369},
  school      = {Universit{\"a}t Potsdam},
  pages     = {VI, 117},
  year      = {2015},
  abstract  = {Current research on runoff and erosion processes, as well as an increasing demand for sustainable watershed management emphasize the need for an improved understanding of sediment dynamics. This involves the accurate assessment of erosion rates and sediment transfer, yield and origin. A variety of methods exist to capture these processes at the catchment scale. Among these, sediment fingerprinting, a technique to trace back the origin of sediment, has attracted increasing attention by the scientific community in recent years. It is a two-step procedure, based on the fundamental assumptions that potential sources of sediment can be reliably discriminated based on a set of characteristic 'fingerprint' properties, and that a comparison of source and sediment fingerprints allows to quantify the relative contribution of each source. This thesis aims at further assessing the potential of spectroscopy to assist and improve the sediment fingerprinting technique. Specifically, this work focuses on (1) whether potential sediment sources can be reliably identified based on spectral features ('fingerprints'), whether (2) these spectral fingerprints permit the quantification of relative source contribution, and whether (3) in situ derived source information is sufficient for this purpose. Furthermore, sediment fingerprinting using spectral information is applied in a study catchment to (4) identify major sources and observe how relative source contributions change between and within individual flood events. And finally, (5) spectral fingerprinting results are compared and combined with simultaneous sediment flux measurements to study sediment origin, transport and storage behaviour. For the sediment fingerprinting approach, soil samples were collected from potential sediment sources within the Is{\´a}bena catchment, a meso-scale basin in the central Spanish Pyrenees. Undisturbed samples of the upper soil layer were measured in situ using an ASD spectroradiometer and subsequently sampled for measurements in the laboratory. Suspended sediment was sampled automatically by means of ISCO samplers at the catchment as well as at the five major subcatchment outlets during flood events, and stored fine sediment from the channel bed was collected from 14 cross-sections along the main river. Artificial mixtures of known contributions were produced from source soil samples. Then, all source, sediment and mixture samples were dried and spectrally measured in the laboratory. Subsequently, colour coefficients and physically based features with relation to organic carbon, iron oxide, clay content and carbonate, were calculated from all in situ and laboratory spectra. Spectral parameters passing a number of prerequisite tests were submitted to principal component analyses to study natural clustering of samples, discriminant function analyses to observe source differentiation accuracy, and a mixing model for source contribution assessment. In addition, annual as well as flood event based suspended sediment fluxes from the catchment and its subcatchments were calculated from rainfall, water discharge and suspended sediment concentration measurements using rating curves and Quantile Regression Forests. Results of sediment flux monitoring were interpreted individually with respect to storage behaviour, compared to fingerprinting source ascriptions and combined with fingerprinting to assess their joint explanatory potential. In response to the key questions of this work, (1) three source types (land use) and five spatial sources (subcatchments) could be reliably discriminated based on spectral fingerprints. The artificial mixture experiment revealed that while (2) laboratory parameters permitted source contribution assessment, (3) the use of in situ derived information was insufficient. Apparently, high discrimination accuracy does not necessarily imply good quantification results. When applied to suspended sediment samples of the catchment outlet, the spectral fingerprinting approach was able to (4) quantify the major sediment sources: badlands and the Villacarli subcatchment, respectively, were identified as main contributors, which is consistent with field observations and previous studies. Thereby, source contribution was found to vary both, within and between individual flood events. Also sediment flux was found to vary considerably, annually as well as seasonally and on flood event base. Storage was confirmed to play an important role in the sediment dynamics of the studied catchment, whereas floods with lower total sediment yield tend to deposit and floods with higher yield rather remove material from the channel bed. Finally, a comparison of flux measurements with fingerprinting results highlighted the fact that (5) immediate transport from sources to the catchment outlet cannot be assumed. A combination of the two methods revealed different aspects of sediment dynamics that none of the techniques could have uncovered individually. In summary, spectral properties provide a fast, non-destructive, and cost-efficient means to discriminate and quantify sediment sources, whereas, unfortunately, straight-forward in situ collected source information is insufficient for the approach. Mixture modelling using artificial mixtures permits valuable insights into the capabilities and limitations of the method and similar experiments are strongly recommended to be performed in the future. Furthermore, a combination of techniques such as e.g. (spectral) sediment fingerprinting and sediment flux monitoring can provide comprehensive understanding of sediment dynamics.},
  language  = {en}
}
@phdthesis{Wulf2011,
  author    = {Wulf, Hendrik},
  title     = {Seasonal precipitation, river discharge, and sediment flux in the western Himalaya},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-57905},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Rainfall, snow-, and glacial melt throughout the Himalaya control river discharge, which is vital for maintaining agriculture, drinking water and hydropower generation. However, the spatiotemporal contribution of these discharge components to Himalayan rivers is not well understood, mainly because of the scarcity of ground-based observations. Consequently, there is also little known about the triggers and sources of peak sediment flux events, which account for extensive hydropower reservoir filling and turbine abrasion. We therefore lack basic information on the distribution of water resources and controls of erosion processes. In this thesis, I employ various methods to assess and quantify general characteristics of and links between precipitation, river discharge, and sediment flux in the Sutlej Valley. First, I analyze daily precipitation data (1998-2007) from 80 weather stations in the western Himalaya, to decipher the distribution of rain- and snowfall. Rainfall magnitude frequency analyses indicate that 40\% of the summer rainfall budget is attributed to monsoonal rainstorms, which show higher variability in the orogenic interior than in frontal regions. Combined analysis of rainstorms and sediment flux data of a major Sutlej River tributary indicate that monsoonal rainfall has a first order control on erosion processes in the orogenic interior, despite the dominance of snowfall in this region. Second, I examine the contribution of rainfall, snow and glacial melt to river discharge in the Sutlej Valley (s55,000 km2), based on a distributed hydrological model, which covers the period 2000-2008. To achieve high spatial and daily resolution despite limited ground-based observations the hydrological model is forced by daily remote sensing data, which I adjusted and calibrated with ground station data. The calibration shows that the Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall product systematically overestimates rainfall in semi-arid and arid regions, increasing with aridity. The model results indicate that snowmelt-derived discharge (74\%) is most important during the pre-monsoon season (April to June) whereas rainfall (56\%) and glacial melt (17\%) dominate the monsoon season (July-September). Therefore, climate change most likely causes a reduction in river discharge during the pre-monsoon season, which especially affects the orogenic interior. Third, I investigate the controls on suspended sediment flux in different parts of the Sutlej catchments, based on daily gauging data from the past decade. In conjunction with meteorological data, earthquake records, and rock strength measurements I find that rainstorms are the most frequent trigger of high-discharge events with peaks in suspended sediment concentrations (SSC) that account for the bulk of the suspended sediment flux. The suspended sediment flux increases downstream, mainly due to increases in runoff. Pronounced erosion along the Himalayan Front occurs throughout the monsoon season, whereas efficient erosion of the orogenic interior is confined to single extreme events. The results of this thesis highlight the importance of snow and glacially derived melt waters in the western Himalaya, where extensive regions receive only limited amounts of monsoonal rainfall. These regions are therefore particularly susceptible to global warming with major implications on the hydrological cycle. However, the sediment discharge data show that infrequent monsoonal rainstorms that pass the orographic barrier of the Higher Himalaya are still the primary trigger of the highest-impact erosion events, despite being subordinate to snow and glacially-derived discharge. These findings may help to predict peak sediment flux events and could underpin the strategic development of preventative measures for hydropower infrastructures.},
  language  = {en}
}