The ecological quick scan is the first step in the assessment and can be performed without any input from stakeholders. Global precipitation, geography and land-use data can be used as input for hydro-morphodynamic and water quality models such as Wflow and Delwaq to predict discharge (Figure 1), water depth, sediment transport and water quality parameters. Tools like the Aqua Monitor (Donchyts et al., 2016) and other algorithms in Google Earth Engine can provide information on flooding dynamics and morphological changes (Figure 2).  For what is available via google earth engine, check this document. The global data and tools provide a set of abiotic parameters that are necessary to describe the ecological status or spatial arrangement of species.

At the core of E-Flow assessments is the relation between abiotic fluvial processes and the presence or absence of species or groups of species. The generic approach of REACT suits a trait strategy approach better than a species approach, as trait strategies are tailored to survive certain conditions and are therefore not attributed to a specific species. Still, trait strategies can be translated to species. The use of generic trait strategies allows for a ‘standard’ set of relations between abiotic variables and trait strategies but might be made specific for delineated river zones.

From a trait perspective, abiotic (and also biotic) variables that steer trait strategy composition are called filters: they filter those trait strategies that are suitable to occur under the specified combination of abiotic (and biotic) processes. The filter approach is a helpful approach within the DPSIR method by linking drivers, pressures, states, impacts and results: what are the filters preventing trait strategies to be present or absent? And do those filters change over the longitudinal, lateral and/or temporal dimension? Pinpointing which filters (specific parts of the state of a system) are crucial for presence and absence of trait strategies leads to a generic set of filters – trait strategy relations.

Examples of generic sets of filters – trait strategies can be found for different species groups. For example, Gurnell et al. (2016) developed a conceptual model that linked lateral fluvial processes to the occurrence of plant trait strategies based on the ability to cope with flooding, inundation and sediment dynamics (Figure 3). Within this conceptual model, no zonation approach was used, as the order of processes over the lateral gradient is believed to be fixed and only depends on the level of confinement of the river itself.

Figure 3:  conceptual model of fluvial processes and the circumstances plants must be able to cope with (i.e. trait strategies) (left) and how confinement of the river results in the presence or absence of the different zones (right). Taken from (Gurnell et al., 2016)

Also, for fish there are conceptual models (often backed with field data) available for the connection between abiotic conditions and trait strategies: fish guilds. There are many fish guild approaches, some focusing on using fish composition to deduce abiotic conditions (De Mérona et al., 2005; Macnaughton, 2016), other use abiotic conditions to predict fish composition (Aarts et al., 2004; Baumgartner et al., 2014). The latter is of interest for REACT: based on deduced or predicted abiotic conditions, fish trait strategies can be simulated.

So, in short, the abiotic information resulting from the global tools and models is used as input for the trait strategy analyses: which trait strategies can be present based on those abiotic conditions? Information on the relation between abiotic conditions and trait strategies are derived from literature (e.g. conceptual work Gurnell et al. (2016), fish guilds etc). The combination of abiotic conditions and trait strategies result in a spatially explicit overview of trait strategies. And so, the output of the first step of REACT is the current state of the ecosystem expressed as an arrangement of the distribution of ecological trait strategies within the system, for instance, the relative area of rheophilic fish habitat in a river basin.

Key in the REACT’s approach is by using global data and models, spatiotemporal data in the form of maps and, with some adaptations, graphs and tables are rendered. This spatiotemporal feature is an important aspect of the tool because it:

• Shows the spatiotemporal variety in river dynamics and land cover
• Shows the spatiotemporal variety of drivers and pressures
• Aids the discussion between stakeholders by providing tangible material
• May aid in refining the model because wrongs in the output may trigger stakeholders to share their data and knowledge.

Appendix A gives an elaborate overview of models, tools and global datasets that are available for an ecological quick scan.

Refinement

The low resolution of a first approximation of the climatological simulation can be increased easily for the historical, present-day and scenario runs when data and knowledge are made available through stakeholders.

The present-day situation is, ideally, derived from measured in situ data for discharge, flow velocity, bathymetry and perhaps some water quality parameters. When data is lacking or limited, there are two options to supplement the information:

• Together with stakeholders make educated guesses, perhaps supplemented with some measurements, on water abstractions, dam operations, bathymetry of the river to simulate the current situation.
• Using recent satellite images to further extract knowledge on the river’s flow regime, including the effects of dams and abstractions. This is a long stretch but is the best that can be done when no detailed data and knowledge is available. For ungauged systems some tests are done, and findings are promising to retrieve detailed enough information to calibrate and validate hydrological models (Van der Zalm, 2018).

testen