AlpWISE : ALPine Water, Ice, Sediment and Ecology

ALTROCLIMA is a three-year project funded jointly by the Swiss National Science Foundation and the Autonomous Province of the South Tyrol (Italy). It will support two PhD students based at the University of Lausanne, Switzerland, and a research assistant and a post-doctoral researcher at the Free University of Bozen-Bolzano, Italy (Professor Francesco Comiti, and involves a number of project partners in Switzerland and Italy.

Project aims and objectives

Alpine landscapes are experiencing climate warming at rates higher than other regions of the world. Globally, impacts of warming on the cryosphere are evident in all mountain regions including permafrost degradation; rates of mass movement (rockfalls, debris flows, landslides) at higher altitudes; river flows; and terrestrial/ aquatic ecosystems. Predictions of changing snow/ice cover are available to the end of the 21^st century and there are attempts to couple climate change to river flow in Alpine landscapes including correct treatment of the cryosphere. How bedload transport will evolve under these drivers is much less well-established despite the important environmental significance of bedload for the ecological functioning of Alpine streams and for its potential hazard to Alpine communities. There are only a few decadal-scale records of bedload transport in mountain basins and almost no studies coupling such records to changing river basin function, historically or in terms of predictions. Such analysis must consider the balance between climate-driven changes in bedload supply (S) and bedload transport capacity (C); but also the feedbacks that follow when SC, such as sediment sorting processes when S<C. It is challenging because bedload transport is exceptionally difficult to measure and globally, unlike other measures of environmental change, we have very few instrumented sites worldwide for bedload transport monitoring extending to more than a decade of observations.

Aims and objectives:  The core aim of this project is to understand and to predict how rapid climate warming has and will impact bedload transport in Alpine environments at the centennial timescale. The objectives are;  O1 to provide the first reliable, multi-site quantification in Alpine environments of how bedload transport is changing under warming; O2 to determine the relative role of landscape-scale processes in driving estimated bedload export in the analyzed basins; O3 to establish an appropriate modelling framework for predicting glacier and hillslope bedload supply to the river network using evidence from O1 and O2; O4 to calibrate and to validate of a predictive model for representing bedload flux through the drainage network supported by data from O3; and O5 to provide the first predictions of Alpine bedload transport under future climate considering changes in both supply and capacity.

Methods: Using an innovative method for analyzing the bedload flushing records provided by high altitude Alpine water intakes we will reconstruct bedload export for more than 60 Alpine basins with varying glacier cover for the Swiss Alps and South Tyrol (O1). We will combine these within-basin reconstructed erosion and deposition patterns and connectivity analyses to explain the changes found in O1 (O2). Using results from O2 we will identify and test against O1 the relative merits of stochastic and physically-based models of subglacial and hillslope bedload delivery to the river network (O3). We will integrate these models to generate network-scale predictions of bedload transport under climate change with relative uncertainty (O4).

Expected results and impact: The research will produce the first decadal-scale multi-site quantification of how bedload transport has changed in Alpine environments due to climate warming and why. It will provide the first predictions with uncertainty of how Alpine bedload transport might evolve under 21^st century climate change. The associated understanding and predictions will not only be of academic value but also of importance for water resource managers (including hydropower companies and national/local flood mitigation agencies) in Alpine regions.

AlpWISE is a partner in a new MCSA doctoral training network, EnvSeis. Details of the network are available here. This is part of the EU Horizon 2020 programme. Switzerland is currently excluded from the programme but has adopted transitional measures, including direct Swiss government funding, to allow Swiss scientists to collaborate. So, we have a new grant starting. We will be leading on the project concerned with Seismic sensing of subglacial to proglacial marginal sediment flux and also collaborating on many of the other projects. We are particularly keen to look at subglacial seismic sediment transport monitoring. The grant will allow us to hire a PhD student.

Part 1 : Model invalidation is a good thing. It means that we are forced to reconsider either model structures or the available data more closely, that is to challenge our fundamental understanding of the problem at hand. It is not easy, however, to decide when a model should be invalidated, when we expect that the sources of uncertainty in environmental modelling will often be epistemic rather than simply aleatory in nature. In particular, epistemic errors in model inputs may well exert a very strong control over how accurate we might expect model predictions to be when compared against evaluation data that might also be subject to epistemic uncertainties. We suggest that both modellers and referees should treat model validation as a form of Turing-like Test, whilst being more explicit about how the uncertainties in observed data and their impacts are assessed. Eight principles in formulating such tests are presented. Being explicit about the decisions made in framing an analysis is one important way to facilitate communication with users of model outputs, especially when it is intended to use a model simulator as a ‘model of everywhere’ or ‘digital twin’ of a catchment system. An example application of the concepts is provided in Part 2.

Part 2 :

Part 1 of this study discussed the concept of using a form of Turing-like Test for model evaluation, together with eight principles for implementing such an approach. In this part, the framing of fitness-for-purpose as a Turing-like Test is discussed, together with an example application of trying to assess whether a rainfall-runoff model might be an adequate representation of the discharge response in a catchment for predicting future natural flood management scenarios. It is shown that the variation between event runoff coefficients in the record can be used to create some limits of acceptability that implicitly take some account of the epistemic uncertainties arising from lack of knowledge about errors in rainfall and discharge observations. In the case study it is demonstrated that the model used cannot be validated in this way across all the range of observed discharges, but that behavioural models can be found for the peak flows that are the subject of interest in the application. Thinking in terms of the Turing-like Test focusses attention on the critical observations needed to test whether streamflow is being produced in the right way so that a model is considered as fit-for-purpose in predicting the impacts of future change scenarios. As is the case for uncertainty estimation in general, it is argued that the assumptions made in setting
behavioural limits of acceptability should be stated explicitly to leave an audit trail in any application that can be reviewed by users of the model outputs.

A copy of Part 1 can be obtained here and Part 2 here

Substantial uncertainties in bedload transport predictions in steep streams have encouraged intensive efforts towards the development of surrogate monitoring technologies. One such system, the Swiss plate geophone (SPG), has been deployed and calibrated in numerous steep channels, mainly in the Alps. Calibration relationships linking the signal recorded by the SPG system to the intensity and characteristics of transported bedload can vary substantially between different monitoring stations, likely due to site-specific factors such as flow velocity and bed roughness. Furthermore, recent flume experiments on the SPG system have shown that site-specific calibration relationships can be biased by elastic waves resulting from impacts occurring outside the plate boundaries. Motivated by these findings, we present a hybrid calibration procedure derived from flume experiments and an extensive dataset of 308 direct field measurements at four different SPG monitoring stations. Our main goal is to investigate the feasibility of a general, site-independent calibration procedure for inferring fractional bedload transport from the SPG signal. First, we use flume experiments to show that sediment size classes can be distinguished more accurately using a combination of vibrational frequency and amplitude information than by using amplitude information alone. Second, we apply this amplitude–frequency method to field measurements to derive general calibration coefficients for 10 different grain-size fractions. The amplitude– frequency method results in more homogeneous signal responses across all sites and significantly improves the accuracy of fractional sediment flux and grain-size estimates. We attribute the remaining site-to-site discrepancies to large differences in flow velocity and discuss further factors that may influence the accuracy of these bedload estimates. A copy of the paper is freely available here.

Loess landform variability across large spatial extents needs to be analyzed to understand the formation and evolution of loess landscapes. This is becoming increasingly possible via the automated analysis of remotely-sensed data. Here, we quantify loess landforms using an object-based image analysis (OBIA) method and use this classification to describe the spatial variability of loess landforms. Quantitative indicators are used to drive the spatial variability analysis of loess landforms and explain their spatio-temporal evolution. Moreover, the hypsometric integral (HI) and topographic interpolation are employed to investigate soil erosion and development patterns of loess landscape. Results show that the OBIA method classified loess landforms to an accuracy of 88.7 %. The derived metrics in terms of the area, slope and complexity of landform shape allow the determination of the spatial structure of the loess landscapes. The HI value of the entire basin is 0.486, representing the mature stage of landform development, with relatively severe surface erosion. Correlation analysis of HI values and related indicators in the sub-basins shows that HI is poorly correlated with the area proportion  of loess landform types and the total erosion volume in the basin but shows a relatively strong correlation with the volume of erosion per unit area. A link to the paper is here.

Glacier shrinkage opens new proglacial terrain with pronounced environmental gradients along longitudinal and lateral chronosequences. Despite the environmental harshness of the streams that drain glacier forelands, their benthic biofilms can harbor astonishing biodiversity spanning all domains of life. Here, we studied the spatial dynamics of prokaryotic and eukaryotic photoautotroph diversity within braided glacier-fed streams and tributaries draining lateral terraces predominantly fed by groundwater and snowmelt across three proglacial floodplains in the Swiss Alps. Along the lateral chronosequence, we found that benthic biofilms in tributaries develop higher biomass than those in glacier-fed streams, and that their respective diversity and community composition differed markedly. We also found spatial turnover of bacterial communities in the glacier-fed streams along the longitudinal chronosequence. These patterns along the two chronosequences seem unexpected given the close spatial proximity and connectivity of the various streams, suggesting environmental filtering as an underlying mechanism. Furthermore, our results suggest that photoautotrophic communities shape bacterial communities across the various streams, which is understandable given that algae are the major source of organic matter in proglacial streams. Overall, our findings shed new light on benthic biofilms in proglacial streams now changing at rapid pace owing to climate-induced glacier shrinkage. A copy of the paper is freely available here.

Global warming-induced melting and thawing of the cryosphere are severely altering the volume and timing of water supplied from High Mountain Asia, adversely affecting downstream food and energy systems that are relied on by billions of people. The construction of more reservoirs designed to regulate streamflow and produce hydropower is a critical part of strategies for adapting to these changes. However, these projects are vulnerable to a complex set of interacting processes that are destabilizing landscapes throughout the region. Ranging in severity and the pace of change, these processes include glacial retreat and detachments, permafrost thaw and associated landslides, rock–ice avalanches, debris flows and outburst floods from glacial lakes and landslide-dammed lakes. The result is large amounts of sediment being mobilized that can fill up reservoirs, cause dam failure and degrade power turbines. Here we recommend forward-looking design and maintenance measures and sustainable sediment management solutions that can help transition towards climate change-resilient dams and reservoirs in High Mountain Asia, in large part based on improved monitoring and prediction of compound and cascading hazards. A link to the paper is available here.

Microbial biofilms have received great attention in the last few decades from both aquatic ecologists and biogeomorphologists. Most recently, this has focused on mapping biofilms to understand their spatial distributions and ecosystem services. Such studies often involve the use of satellite imagery, which typically provides large temporal and spatial scales and wide-range spectral information. Although satellites have the advantage of multi- and hyper-spectral sensors, images often have low spatial resolution that limits their use in river studies, where both rivers are narrower and stream processes occur at resolutions smaller than the footprint of satellite sensors. Spatial resolution is sensor quality dependent but also controlled by sensor elevation above the ground. Hence, high resolutions can be achieved either by using a very expensive sensor or by decreasing the distance between the target area and the sensor itself. To date, sensor technology has advanced to a point where multi- or even hyper-spectral cameras can be easily carried out by an Uncrewed Aerial Vehicle (UAV) at unprecedented spatial resolutions. Where such sensors have high spectral resolution, they are often prohibitively expensive, especially as their use in extreme environments such as glacial forefields risks UAV damage. In this paper, we test the performance of visible band ratios in mapping biofilms in an Alpine glacier forefield characterized by a well-developed and heterogeneous stream ecosystem but using a low-cost UAV. The paper shows that low-cost and consumer grade UAVs can be easily deployed in such extreme environments, delivering both quality RGB images for photogrammetric (SfM-MVS) processing and sufficient spectral information for benthic biofilm mapping at high temporal and spatial resolution. A copy id freely available here.

The spatio-temporal variability of bedload transport processes poses considerable challenges for bedload monitoring systems. One such system, the Swiss plate geophone (SPG), has been calibrated in several gravel-bed streams using direct sampling techniques. The linear calibration coefficients linking the signal recorded by the SPG system to the transported bedload can vary between different monitoring stations by about a factor of six, for reasons that remain unclear. Recent controlled flume experiments allowed us to identify the grain-size distribution of the transported bedload as a further site-specific factor influencing the signal response of the SPG system, along with the flow velocity and the bed roughness. Additionally, impact tests performed at various field sites suggested that seismic waves generated by impacting particles can propagate over several plates of an SPG array, and thus potentially bias the bedload estimates. To gain an understanding of this phenomenon, we adapted a test flume by installing a partition wall to shield individual sensor plates from impacting particles. We show that the SPG system is sensitive to seismic waves that propagate from particle impacts on neighboring plates or on the concrete bed close to the sensors despite isolating elements. Based on this knowledge, we designed a filter method that uses time-frequency information to identify and eliminate these “apparent” impacts. Finally, we apply the filter to four field calibration datasets and show that it significantly reduces site-to-site differences between calibration coefficients and enables the derivation of a single calibration curve for total bedload at all four sites. A copy is freely available here.

Understanding and predicting bedload transport is an important element of watershed management. Yet, predictions of bedload remain uncertain by up to several order(s) of magnitude. In this contribution, we use a five-year continuous time-series of streamflow and bedload transport monitoring in a 13.4 km2 snow-dominated Alpine watershed in the Western Swiss Alps to investigate hydrological drivers of bedload transport. Following a calibration of the bedload sensors, and a quantification of the hydraulic forcing of streamflow upon bedload, a hydrological analysis is performed to identify daily flow hydrographs influenced by different hydrological drivers: rainfall, snowmelt, and combined rain and snowmelt events. We then quantify their respective contribution to bedload transport. Results emphasize the importance of combined rain and snowmelt events, for both annual bedload volumes (77% on average) and peaks in bedload transport rate. A non-negligible, but smaller, amount of bedload transport may occur during late summer and autumn storms, once the snowmelt contribution and baseflow have significantly decreased (9% of the annual volume on average). Although rainfall-driven changes in flow hydrographs are responsible for a large majority of the annual bedload volumes (86% on average), the identified melt-only events also represent a substantial contribution (14% on average). The results of this study help to improve current predictions of bedload transport through a better understanding of the bedload magnitude-frequency relationship under different hydrological conditions. We further discuss how bedload transport could evolve under a changing climate through its effects on Alpine watershed hydrology. A copy is freely available here.