Assessment of plot-scale sediment transport on young moraines in the Swiss Alps using a fluorescent sand tracer

Glacial retreat uncovers large bodies of unconsolidated sediment that are prone to erosion. However, our knowledge of overland flow (OF) generation and sediment transport on moraines that have recently become ice-free is still limited. To investigate how the surface characteristics of young moraines affect OF and sediment transport, we installed five bounded runoff plots on two moraines of different ages in a proglacial area of the Swiss Alps. On each plot we conducted three sprinkling experiments to determine OF characteristics (i.e., total OF and peak OF flow rate) and measured sediment transport (turbidity, sediment concentrations, and total sediment yield). To determine and visualize where sediment transport takes place, we used a fluorescent sand tracer with an afterglow as well as ultraviolet (UV) and light-emitting diode (LED) lamps and a high-resolution camera. The results highlight the ability of this field setup to detect sand movement, even for individual fluorescent sand particles (300–500 µm grain size), and to distinguish between the two main mechanisms of sediment transport: OF-driven erosion and splash erosion. The higher rock cover on the younger moraine resulted in longer sediment transport distances and a higher sediment yield. In contrast, the higher vegetation cover on the older moraine promoted infiltration and reduced the length of the sediment transport pathways. Thus, this study demonstrates the potential of the use of fluorescent sand with an afterglow to determine sediment transport pathways as well as the fact that these observations can help to improve our understanding of OF and sediment transport processes on complex natural hillslopes

The CrowdWater game: A playful way to improve the accuracy of crowdsourced water level class data

Data quality control is important for any data collection program, especially in citizen science projects, where it is more likely that errors occur due to the human factor. Ideally, data quality control in citizen science projects is also crowdsourced so that it can handle large amounts of data. Here we present the CrowdWater game as a gamified method to check crowdsourced water level class data that are submitted by citizen scientists through the CrowdWater app. The app uses a virtual staff gauge approach, which means that a digital scale is added to the first picture taken at a site and this scale is used for water level class observations at different times. In the game, participants classify water levels based on the comparison of the new picture with the picture containing the virtual staff gauge. By March 2019, 153 people had played the CrowdWater game and 841 pictures were classified. The average water level for the game votes for the classified pictures was compared to the water level class submitted through the app to determine whether the game can improve the quality of the data submitted through the app. For about 70% of the classified pictures, the water level class was the same for the CrowdWater app and game. For a quarter of the classified pictures, there was disagreement between the value submitted through the app and the average game vote. Expert judgement suggests that for three quarters of these cases, the game based average value was correct. The initial results indicate that the CrowdWater game helps to identify erroneous water level class observations from the CrowdWater app and provides a useful approach for crowdsourced data quality control. This study thus demonstrates the potential of gamified approaches for data quality control in citizen science projects

Shallow-groundwater-level time series and a groundwater chemistry survey from a boreal headwater catchment, Krycklan, Sweden

Shallow groundwater can respond quickly to precipitation and is the main contributor to streamflow in most catchments in humid, temperate climates. Therefore, it is important to have high-spatiotemporal-resolution data on groundwater levels and groundwater chemistry to test spatially distributed hydrological models. However, currently, there are few datasets on groundwater levels with a high spatiotemporal resolution because of the large effort required to collect these data. To better understand shallow groundwater dynamics in a boreal headwater catchment, we installed a network of groundwater wells in two areas in the Krycklan catchment in northern Sweden for a small headwater catchment (3.5 ha; 54 wells) and a hillslope (1 ha; 21 wells). The average well depth was 274 cm (range of 70-581 cm). We recorded the groundwater-level variation at 10-30 min intervals between 18 July 2018-1 November 2020. Manual water-level measurements (0-26 per well) during the summers of 2018 and 2019 were used to confirm and re-calibrate the automatic water-level measurements. The groundwater-level data for each well was carefully processed using six data quality labels. The absolute and relative positions of the wells were measured with a high-precision GPS and terrestrial laser scanner to determine differences in absolute groundwater levels and calculate groundwater gradients. During the summer of 2019, all wells with sufficient water were sampled once and analyzed for electrical conductivity, pH, absorbance, and anion and cation concentrations, as well as the stable isotopes of hydrogen and oxygen. The data are available at https://doi.org/10.5880/fidgeo.2022.020 (Erdbrugger et al., 2022). This combined hydrometric and hydrochemical dataset can be useful for testing models that simulate groundwater dynamics and evaluating metrics that describe subsurface hydrological connectivity

How well can people observe the flow state of temporary streams?

Even though more than half of the global river network does not have continuous flow, temporary (i.e., non-perennial) streams are poorly represented in traditional monitoring networks. Therefore, new approaches are needed to monitor these streams. Citizen science provides an interesting opportunity as people, equipped with smartphones, can observe the flow state of temporary streams. Such observations can go beyond a simple classification of flow vs. no flow and include ecologically important states, such as standing water, isolated pools, or wet streambeds. However, the quality of citizen science data for temporary streams has so far not been thoroughly assessed. Therefore, we asked more than 1,200 people during 23 field days to visually determine the flow state of eight temporary streams based on six classes ranging from a dry streambed to flowing water. Participants could most clearly distinguish a flowing stream from a non-flowing stream. The overall agreement between participants was 66%; 83% of the selected flow states were within one class of the most frequently selected flow state. The agreement with the expert was lower (56% chose the same class, and 79% chose a state within one class). Inconsistencies between the selected flow state and answers to specific yes-no statements about the temporary stream were largest for the dry streambed and damp/wet streambed states. These discrepancies were partly caused by participants looking at different parts of the stream (i.e., participants considered the flow state for a location further upstream or downstream). To ensure that all participants determine the flow state comparably, we recommend clear definitions of the flow state classes, detailed information on the exact location for which the flow state needs to be determined, as well as more training

How can we model subsurface stormflow at the catchment scale if we cannot measure it?

Subsurface stormflow (SSF) can be a dominant run‐off generation process in humid mountainous catchments (e.g., Bachmair & Weiler, 2011; Blume & van Meerveld, 2015; Chifflard, Didszun, & Zepp, 2008). Generally, SSF develops in structured soils where bedrock or a less permeable soil layer is overlaid by a more permeable soil layer and vertically percolating water is deflected, at least partially, in a lateral downslope direction due to the slope inclination. SSF can also occur when groundwater levels rise into more permeable soil layers and water flows laterally through the more permeable layers to the stream (“transmissivity feedback mechanism”; Bishop, Grip, & O'Neill, 1990). The different existing terms for SSF in the hydrological literature such as shallow subsurface run‐off, interflow, lateral flow, or soil water flow reflects the different underlying process concepts developed in various experimental studies in different environments by using different experimental approaches at different spatial and temporal scales (Weiler, McDonnell, Tromp‐van Meerveld, & Uchida, 2005). Intersite comparisons and the extraction of general rules for SSF generation and its controlling factors are still lacking, which hampers the development of appropriate approaches for modelling SSF. But appropriate prediction of SSF is essential due to its clear influence on run‐off generation at the catchment scale (e.g., Chifflard et al., 2010; Zillgens, Merz, Kirnbauer, & Tilch, 2005), on the formation of floods (e.g., Markart et al., 2013, 2015) and on the transport of nutrients or pollutants from the hillslopes into surface water bodies (Zhao, Tang, Zhao, Wang, & Tang, 2013). However, a precise simulation of SSF in models requires an accurate process understanding including, knowledge about water pathways, residence times, magnitude of water fluxes, or the spatial origin of SSF within a given catchment because such factors determine the transport of subsurface water and solutes to the stream. But due to its occurrence in the subsurface and its spatial and temporal variability, determining and quantifying the processes generating SSF is a challenging task as they cannot be observed directly. Therefore, it is logical to ask whether we can really model SSF correctly if we cannot measure it well enough on the scale of interest (Figure 1). This commentary reflects critically on whether current experimental concepts and modelling approaches are sufficient to predict the contribution of SSF to the run‐off at the catchment scale. This applies in particular to the underlying processes, controlling factors, modelling approaches, research gaps, and innovative strategies to trace SSF across different scales

Dung beetles as hydrological engineers: effects of tunnelling on soil infiltration

1. Soil infiltration capacity determines the partitioning of precipitation into infiltration and overland flow and is therefore an important soil hydrological characteristic. Water infiltration through soil is facilitated by macropores created by roots and soil macrofauna. In clay-rich soils, such as those of the tropical forests of Sabah, Malaysian Borneo, most infiltration occurs via these preferential flow pathways. 2. We evaluated the effects of dung beetle tunnelling on infiltration and macropore creation (depth and width of the flow pathways) in tropical forest soils in Sabah. Using mesocosms, we applied three treatments (i) soil-only, (ii) dung-only, (iii) dung + dung beetles, and measured saturated hydraulic conductivity (i.e., the steady-state infiltration rate) after 0, 5 and 10 days, and assessed depth and width of infiltration pathways by applying a blue dye tracer. 3. The steady-state infiltration rate increased in the presence of dung beetles, though differences among treatments were only statistically significant after 10 days. After 5 days of dung beetle presence, infiltrated water had reached a greater depth than the control mesocosms without beetles. However, there were no differences in the width of infiltration pathways among treatments. 4. These results reveal the important, but under studied roles of dung beetles on soil hydrological functioning, that may have consequences for nutrient cycling and plant productivity. Further, our findings indicate that the novel application of an established hydrological method—blue dye tracer—can provide interesting and reliable results for macrofauna–soil interaction studies.ISSN:0307-6946ISSN:1365-231

Aqua temporaria incognita

Invited commentary

Virtual Staff Gauges for Crowd-Based Stream Level Observations

Hydrological observations are crucial for decision making for a wide range of water resource challenges. Citizen science is a potentially useful approach to complement existing observation networks to obtain this data. Previous projects, such as CrowdHydrology, have demonstrated that it is possible to engage the public in contributing hydrological observations. However, hydrological citizen science projects related to streamflow have, so far, been based on the use of different kinds of instruments or installations; in the case of stream level observations, this is usually a staff gauge. While it may be relatively easy to install a staff gauge at a few river sites, the need for a physical installation makes it difficult to scale this type of citizen science approach to a larger number of sites because these gauges cannot be installed everywhere or by everyone. Here, we present a smartphone app that allows collection of stream level information at any place without any physical installation as an alternative approach. The approach is similar to geocaching, with the difference that instead of finding treasure-hunting sites, hydrological measurement sites can be generated by anyone and at any location and these sites can be found by the initiator or other citizen scientists to add another observation at another time. The app is based on a virtual staff gauge approach, where a picture of a staff gauge is digitally inserted into a photo of a stream bank or a bridge pillar, and the stream level during a subsequent field visit to that site is compared to the staff gauge on the first picture. The first experiences with the use of the app by citizen scientists were largely encouraging but also highlight a few challenges and possible improvements

Dung beetles as hydrological engineers: effects of tunnelling on soil infiltration

Soil infiltration capacity determines the partitioning of precipitation into infiltration and overland flow and is therefore an important soil hydrological characteristic. Water infiltration through soil is facilitated by macropores created by roots and soil macrofauna. In clay-rich soils, such as those of the tropical forests of Sabah, Malaysian Borneo, most infiltration occurs via these preferential flow pathways. We evaluated the effects of dung beetle tunnelling on infiltration and macropore creation (depth and width of the flow pathways) in tropical forest soils in Sabah. Using mesocosms, we applied three treatments (i) soil-only, (ii) dung-only, (iii) dung + dung beetles, and measured saturated hydraulic conductivity (i.e., the steady-state infiltration rate) after 0, 5 and 10 days, and assessed depth and width of infiltration pathways by applying a blue dye tracer. The steady-state infiltration rate increased in the presence of dung beetles, though differences among treatments were only statistically significant after 10 days. After 5 days of dung beetle presence, infiltrated water had reached a greater depth than the control mesocosms without beetles. However, there were no differences in the width of infiltration pathways among treatments. These results reveal the important, but under studied roles of dung beetles on soil hydrological functioning, that may have consequences for nutrient cycling and plant productivity. Further, our findings indicate that the novel application of an established hydrological method—blue dye tracer—can provide interesting and reliable results for macrofauna–soil interaction studies