How can expert knowledge increase the realism of conceptual hydrological models? : a case study based on the concept of dominant runoff process in the Swiss Pre-Alps

Both modellers and experimentalists agree that using expert knowledge can improve the realism of conceptual hydrological models. However, their use of expert knowledge differs for each step in the modelling procedure, which involves hydrologically mapping the dominant runoff processes (DRPs) occurring on a given catchment, parameterising these processes within a model, and allocating its parameters. Modellers generally use very simplified mapping approaches, applying their knowledge in constraining the model by defining parameter and process relational rules. In contrast, experimentalists usually prefer to invest all their detailed and qualitative knowledge about processes in obtaining as realistic spatial distribution of DRPs as possible, and in defining narrow value ranges for each model parameter. Runoff simulations are affected by equifinality and numerous other uncertainty sources, which challenge the assumption that the more expert knowledge is used, the better will be the results obtained. To test for the extent to which expert knowledge can improve simulation results under uncertainty, we therefore applied a total of 60 modelling chain combinations forced by five rainfall datasets of increasing accuracy to four nested catchments in the Swiss Pre-Alps. These datasets include hourly precipitation data from automatic stations interpolated with Thiessen polygons and with the inverse distance weighting (IDW) method, as well as different spatial aggregations of Combiprecip, a combination between ground measurements and radar quantitative estimations of precipitation. To map the spatial distribution of the DRPs, three mapping approaches with different levels of involvement of expert knowledge were used to derive so-called process maps. Finally, both a typical modellers' top-down set-up relying on parameter and process constraints and an experimentalists' set-up based on bottom-up thinking and on field expertise were implemented using a newly developed process-based runoff generation module (RGM-PRO). To quantify the uncertainty originating from forcing data, process maps, model parameterisation, and parameter allocation strategy, an analysis of variance (ANOVA) was performed. The simulation results showed that (i) the modelling chains based on the most complex process maps performed slightly better than those based on less expert knowledge; (ii) the bottom-up set-up performed better than the top-down one when simulating short-duration events, but similarly to the top-down set-up when simulating long-duration events; (iii) the differences in performance arising from the different forcing data were due to compensation effects; and (iv) the bottom-up set-up can help identify uncertainty sources, but is prone to overconfidence problems, whereas the top-down set-up seems to accommodate uncertainties in the input data best. Overall, modellers' and experimentalists' concept of model realism differ. This means that the level of detail a model should have to accurately reproduce the DRPs expected must be agreed in advance

Drohnen-gestützte und terrestrische Wärmebilder zur Beurteilung der Fliessgewässer-Temperatur

Terrestrische und drohnen-gestützte Messungen mit thermischem Infrarot (TIR) sind effektiv zur zeitlich-räumlich hochaufgelösten Quantifizierung von Längs- und Quertemperaturunterschieden in gut durchmischten Fliessgewässern. Bei der TIR-Erfassung und -Analyse müssen allerdings verschiedene atmosphärische und andere Umwelteinflüsse berücksichtigt sowie die TIR-Anwendung zur genauen Bestimmung der absoluten Temperatur kritisch betrachtet werden

Mapping dominant runoff processes : an evaluation of different approaches using similarity measures and synthetic runoff simulations

The identification of landscapes with similar hydrological behaviour is useful for runoff and flood predictions in small ungauged catchments. An established method for landscape classification is based on the concept of dominant runoff process (DRP). The various DRP-mapping approaches differ with respect to the time and data required for mapping. Manual approaches based on expert knowledge are reliable but time-consuming, whereas automatic GIS-based approaches are easier to implement but rely on simplifications which restrict their application range. To what extent these simplifications are applicable in other catchments is unclear. More information is also needed on how the different complexities of automatic DRP-mapping approaches affect hydrological simulations. In this paper, three automatic approaches were used to map two catchments on the Swiss Plateau. The resulting maps were compared to reference maps obtained with manual mapping. Measures of agreement and association, a class comparison, and a deviation map were derived. The automatically derived DRP maps were used in synthetic runoff simulations with an adapted version of the PREVAH hydrological model, and simulation results compared with those from simulations using the reference maps. The DRP maps derived with the automatic approach with highest complexity and data requirement were the most similar to the reference maps, while those derived with simplified approaches without original soil information differed significantly in terms of both extent and distribution of the DRPs. The runoff simulations derived from the simpler DRP maps were more uncertain due to inaccuracies in the input data and their coarse resolution, but problems were also linked with the use of topography as a proxy for the storage capacity of soils. The perception of the intensity of the DRP classes also seems to vary among the different authors, and a standardised definition of DRPs is still lacking. Furthermore, we argue not to use expert knowledge for only model building and constraining, but also in the phase of landscape classification

Adaptive management and restoration of a complex floodplain system using artificial flooding (Sarine floodplain, Western Switzerland)

Artificial floods are becoming more common as operational measures to restore impacted hydrological and ecomorphological dynamics in floodplains downstream of dams. Major challenges arise in dimensioning of artificial floods regarding their magnitude, duration and frequency of flood releases for general applicability and implementation. Here we use in situ ecomorphological measurements, supported by remote sensing and hydraulic modelling to monitor, evaluate, predict, and plan the ecomorphological effects of artificial floods in a residual flow section of a complex floodplain. This approach supports the dimensioning and implementation of artificial flood programs for restoration according to an adaptive management plan

Quantifying biodiversity using eDNA from water bodies: General principles and recommendations for sampling designs

Reliable and comparable estimates of biodiversity are the foundation for understanding ecological systems and informing policy and decision‐making, especially in an era of massive anthropogenic impacts on biodiversity. Environmental DNA (eDNA) metabarcoding is at the forefront of technological advances in biodiversity monitoring, and the last few years have seen major progress and solutions to technical challenges from the laboratory to bioinformatics. Water eDNA has been shown to allow the fast and efficient recovery of biodiversity signals, but the rapid pace of technological development has meant that some important principles regarding sampling design, which are well established in traditional biodiversity inventories, have been neglected. Using a spatially explicit river flow model, we illustrate how sampling must be adjusted to the size of the watercourse to increase the quality of the biodiversity signal recovered. We additionally investigate the effect of sampling parameters (volume, number of sites, sequencing depth) on detection probability in an empirical data set. Based on traditional sampling principles, we propose that aquatic eDNA sampling replication and volume must be scaled to match the organisms' and ecosystems' properties to provide reliable biodiversity estimates. We present a generalizable conceptual equation describing sampling features as a function of the size of the ecosystem monitored, the abundance of target organisms, and the properties of the sequencing procedure. The aim of this formalization is to enhance the standardization of critical steps in the design of biodiversity inventory studies using eDNA. More robust sampling standards will generate more comparable biodiversity data from eDNA, which is necessary for the method's long‐term plausibility and comparability

Integrating two‐dimensional water temperature simulations into a fish habitat model to improve hydro‐ and thermopeaking impact assessment

Storage hydropower plants, which are an important component of energy production in Switzerland, can lead to hydro- and thermopeaking, affecting river habitats and organisms. In this study, we developed an approach for integrating water temperature simulations into a habitat model to assess the impact of both hydro- and thermopeaking on the availability of suitable fish habitats. We focused on the habitat requirements of juvenile brown trout (Salmo trutta) in a semi-natural braided floodplain along the Moesa River (Southern Switzerland) in early summer. First, we defined different scenarios (with and without hydropeaking) based on the local hydrological and meteorological conditions. Second, we used a two-dimensional depth-averaged hydro- and thermodynamic model to simulate the spatial distributions of water depth, flow velocity, and water temperature. Third, we applied generalized preference curves for juvenile brown trout to identify hydraulically suitable habitats, and developed a new index to assess the availability of thermally suitable habitats. Finally, we quantified the extent to which hydraulically and thermally suitable habitats overlap in space and time. During both base and peak flow phases, most of the hydraulically and thermally suitable habitats are located in the side channels. High flow conditions combined with strong cold-thermopeaking lead to a higher thermal heterogeneity. However, disconnected habitats originate in the dewatering zone, increasing the risk of stranding as well as thermal stress. By helping to better understand the effects of thermopeaking on the availability of fish habitats, our approach could contribute to the design and evaluation of ecological restoration in hydropeaking rivers

Quantifying biodiversity using eDNA from water bodies : general principles and recommendations for sampling designs

Reliable and comparable estimates of biodiversity are the foundation for understanding ecological systems and informing policy and decision-making, especially in an era of massive anthropogenic impacts on biodiversity. Environmental DNA (eDNA) metabarcoding is at the forefront of technological advances in biodiversity monitoring, and the last few years have seen major progress and solutions to technical challenges from the laboratory to bioinformatics. Water eDNA has been shown to allow the fast and efficient recovery of biodiversity signals, but the rapid pace of technological development has meant that some important principles regarding sampling design, which are well established in traditional biodiversity inventories, have been neglected. Using a spatially explicit river flow model, we illustrate how sampling must be adjusted to the size of the watercourse to increase the quality of the biodiversity signal recovered. We additionally investigate the effect of sampling parameters (volume, number of sites, sequencing depth) on detection probability in an empirical data set. Based on traditional sampling principles, we propose that aquatic eDNA sampling replication and volume must be scaled to match the organisms' and ecosystems' properties to provide reliable biodiversity estimates. We present a generalizable conceptual equation describing sampling features as a function of the size of the ecosystem monitored, the abundance of target organisms, and the properties of the sequencing procedure. The aim of this formalization is to enhance the standardization of critical steps in the design of biodiversity inventory studies using eDNA. More robust sampling standards will generate more comparable biodiversity data from eDNA, which is necessary for the method's long-term plausibility and comparability

Sensing river and floodplain biodiversity : developing a prototype

Freshwaters, such as rivers and floodplains, are among the world’s most diverse ecosystems, but they are losing biodiversity faster than any other ecosystem, mainly due to human activities. A major problem is the low awareness of biodiversity loss. Triggering emotions and amazement may increase people’s biodiversity perception in a more holistic way. Therefore, with an immersive audio visual VR-simulation prototype based on 3D point clouds and sound recordings above and below water developed in the Unity game engine, we want to allow for sensing river biodiversity. Feedback from a user study demonstrates that the prototype can promote laypersons’ awareness of biodiversity loss and provides insights for its further enhancement

Abstracts from the 20th International Symposium on Signal Transduction at the Blood-Brain Barriers

https://deepblue.lib.umich.edu/bitstream/2027.42/138963/1/12987_2017_Article_71.pd