River Restoration Units: Riverscape Units for European Freshwater Ecosystem Management

Abstract

Freshwater habitats and biota are among the most threatened worldwide. In Europe, significant efforts are being taken to counteract detrimental human impacts on nature. In line with these efforts, the MERLIN project funded by the H2020 program focuses on mainstreaming ecosystem restoration for freshwater-related environments at the landscape scale. Additionally, the Dammed Fish project focuses on one of the main threats affecting European Networks—artificial fragmentation of the river. Meeting the objectives of both projects to work on a large, pan-European scale, we developed a novel spatial database for river units. These spatial units, named River Restoration Units (R2Us), abide by river network functioning while creating the possibility of aggregating multiple data sources with varying resolutions to size-wise comparable units. To create the R2U, we set a methodological framework that departs from the Catchment Characterization and Modelling—River and Catchment Database v2.1 (CCM2)—together with the capabilities of the River Network Toolkit (v2) software (RivTool) to implement a seven-step methodological procedure. This enabled the creation of 11,557 R2U units in European sea outlet river basins along with their attributes. Procedure outputs were associated with spatial layers and then reorganized to create a relational database with normalized data. Under the MERLIN project, R2Us have been used as the spatial analysis unit for a large-scale analysis using multiple input datasets (e.g., ecosystem services, climate, and European Directive reporting data). This database will be valuable for river management and conservation planning, being particularly well suited for large-scale restoration planning in accordance with European Nature legislation.

Dataset: https://zenodo.org/records/15015513 (DOI: 10.5281/zenodo.10753899).

Dataset License: CC-BY-4.0.

1. Summary

Freshwater ecosystems are among the most threatened systems globally [1] and need effective management and restoration. Understanding the intricate relationship between landscapes and rivers, as well as the impact of human activities, land use, and land cover on watercourses, is essential [2]. Thus, riverscape approaches [3] across large spatial scales can aid in identifying priority areas for conservation and restoration. Strategies geared toward management and conservation focused on freshwater environments must account for the river network’s structure and characteristics to be successful [4]. Various key characteristics like directionality, hierarchy, dendriticity, nestedness, and connectedness influence river dynamics, morphology, ecological integrity [5], and biodiversity [6].

Composed of a river network and its drainage area, sea outlet basins are crucial spatial units for freshwater conservation and management due to their insular nature. Their functioning is naturally independent of neighboring basins, thus essential for managing and understanding freshwater-related biodiversity patterns and ecosystem processes [7]. However, understanding spatial patterns at multiple scales and across multiple basins is decisive for monitoring, conservation, and restoration implementation plans [8] and investigating ecological processes [3]. River networks can be separated into discrete nested sub-networks made from their elementary components, i.e., river segments and drainage areas [9]. Thus, breaking sea outlet basins into meaningful smaller spatial units is possible.

Acknowledging and adopting a riverscape approach is important for research projects targeting freshwater environments. The MERLIN project (H2020-LC-GD-2020) focuses on freshwater-related ecosystems, and one of the main goals is to upscale and mainstream ecosystem restoration at the landscape scale. Specifically, the project aims to “identify landscapes with high potential and priority for transformative restoration, particularly focusing on essential ecosystem services, biodiversity targets, and climate change mitigation and adaptation” (https://project-merlin.eu/, accessed on 14 March 2025). To achieve this, a European-wide analysis was conducted using multiple information sources such as environmental-related EU Directives (e.g., Habitats Directive, Water Framework Directive), freshwater ecosystem typologies, hydrological alterations (e.g., river barriers), climate projections, and ecosystem services. Considering this, defining spatial units within each sea outlet basin was necessary to enable a comprehensive analysis incorporating multiple data inputs toward the ’project’s objectives. Spatial aggregation that facilitates river network connectivity at large spatial extents while allowing for multi-resolution analyses was also necessary under the Dammed Fish project (Impact of structural and functional river network connectivity losses on fish biodiversity—Optimising management solutions). Dammed Fish aims to evaluate and propose solutions and tools to inform river network connectivity management, improve fish biodiversity, and enhance the biotic quality of European rivers. Hence, we created the River Restoration Units (R2Us) along with respective characterizing attributes.

R2Us were created in each sea outlet basin in past and present European Union Member states. Taking advantage of the nested nature of river networks, the methodological procedure derived homogeneous units concerning drainage and river length while maintaining abidance by the hierarchical, dendritic, and directional nature of river networks. This facilitates management by reducing potential negative feedback from unmanaged units and potentiating positive feedback along the river networks of managed units. Additionally, R2Us facilitate relating freshwater ecosystems with multiple data sources, at distinct resolutions and for large spatial extents. This dataset became the backbone for European-wide analyses targeted by the MERLIN project (H2020-LC-GD-2020), and it was also used for some analysis in their case studies. Here, it was important to identify restoration needs and potentials in similar-sized areas to facilitate management scenario design. Beyond the MERLIN project [10], this dataset has already been used to discuss the challenges of restoration targeting free-flowing rivers under the Nature Restoration Law [11]. We believe this database can be useful for other studies focusing on freshwater-related environments, particularly when requiring inner-basin sub-divisions where the maintenance of the network properties of rivers is paramount, e.g., for river connectivity assessments, such as those being carried out by the Dammed Fish project.

2. Data Description

The dataset encompasses all sea outlet basins containing at least a river segment of Strahler stream order 3 within the Member States of the European Union (EU MS) and the former Member State the United Kingdom (Figure 1). The spatial layers of the Catchment Characterization and Modeling—River and Catchment Database v2.1 (CCM2) [12] were used as input data.

The dataset was streamlined into a PostgreSQL database to facilitate usage and dissemination. The database entity-relation diagram (Figure 2) portrays three tables related to spatial layers: (1) Basins_EU, (2) R2U_ID_drainage_areas, and (3) R2U_Watercourses. The first layer was taken from the CCM2 database and represents the polygons of the sea outlet basins in the study area. The second and third layers represent, respectively, the polygons and lines of the drainage areas and watercourses for each R2U created. The database includes four other exclusively tabular elements: one table containing the attributes of the R2Us and three other supporting tables that codify attributes created to achieve data normalization.

Table 1. Table detailing all the attributes included in the database (DB) elements created for the River Restoration Units. The field “Database Element” refers to the DB entity, and the field “Attribute” refers to the attribute that will be detailed in the field “Description”.

Database Element	Attribute	Description
Basins_EU/R2U_features	WSO_ID	Basin unique identifier code (number) used in CCM2
Basins_EU	Basin_Area_sqkm	Basin area (Km2)
Basins_EU	Basin_Strahler	Maximum Strahler stream order number of a given basin
Present in 4 elements	R2U_ID	River restoration unit (R2U) code
R2U_ID_drainage_areas	R2U_Area_sqkm	Drainage area of an R2U (km2)
R2U_Watercourses	R2U_river_length_km	River length of an R2U (km)
R2U_features	Nextdown_R2U_ID	Identifier code of the downstream R2U unit
R2U_features	R2U_Strahler	Maximum segment Strahler stream order number in the R2U
R2U_features	R2U_Hack	Minimum Hack stream order number of an R2U
R2U_features	Drain_dens	Ratio between river length (m) in an R2U and its drainage area (m2)
R2U_features	Num_segments	Number of river segments included in an R2U
R2U_features/Unit_typology	Id_Unit_code	Unit typology unique code
Unit_typology	Unit_Acronym	Unite Typology Acronym
Unit_typology	Unit_type_descr	Description of River Restoration ‘Units’ typology (LRU—Large River Unit; SRU—Small River Unit) and LRU sub-groups (LRHU—Large River Head Unit; SRSO—Small River Sea Outlet)
R2U_to_MS	Id_R2U_MS	Unique identifier code for the R2U_to_MS table
R2U_to_MS/MS_coding	MS_ID	Member States identifier code (using the countries ISO 3166 international standard numeric code)
MS_coding	Id_ms_coding	Unique identifier code for the MS_coding table
MS_coding	MS_acronym	Member States identifier code (using the countries ISO 3166 international standard alpha-3 code)
MS_coding	MS_name	Member States English country name

describes all attributes from database elements, including the units when adequate, enabling a correct interpretation and articulation of the dataset. To enhance usability, both spatial layers and tabular data are made available in the geodatabase and geopackage formats. Complementary spatial layers are also made available in shapefile format.

The dataset includes 11,557 R2Us (Figure 3a), 7.7% Large River Units (LRUs) (889), 92.3% Small River Units (SRUs) (10,668), and an SRU-to-LRU ratio of 12.0. In the SRU category, 15.7% are sea outlet SRUs (1674) and 4.9% are Large River Head Unit SRUs (524). On average, R2Us have between 65 to 66 segments, 153.0 km of river length, and 432.7 km² of drainage area. Figure 3b portrays the different typologies of R2Us, including the SRU sub-groups, in the study area. LRUs emphasize the main stem watercourses of each river basin. Figure 3c depicts the watercourses associated per R2U per maximum Strahler stream order, exposing an attribute from the database that can illustrate the hierarchy of each basin.

3. Methods

3.1. Methodological Procedure

To create the R2U dataset, we aggregated the segments and respective direct drainage areas provided in the CCM2 database [12], as these are the fundamental building blocks of river networks [9]. CCM2 is a homogeneous and integrated hierarchical representation of rivers and their drainage catchments across Europe that includes layers of sea outlet basins (drainage area of a river network flowing into the sea), river segments (river stretches between confluences), and corresponding drainage catchments (area draining directly to a river segment) [14]. A new function, named “River Restoration Units”, was implemented in the River Network software (RivTool v2) [15] to enable the computation of R2U tabular data, subsequently spatially implemented using ArcGIS^® 3.4.2 tools. This aggregation complies with the nested nature of rivers systematized by Hack’s Stream order [16] and uses thresholds based on the Strahler stream order [17], upstream drainage area (UDA), and upstream river length (URL) defined as follows:

1

Strahler value = 3—this establishes a level of network complexity. Strahler values express branching, hierarchy, and morphology [17,18,19,20,21], and values around 3 have been identified as thresholds of difference in terms of freshwater species richness and diversity.

2

UDA = 1000 km²—defined conservatively to maintain area-wise homogeneous units. This is relevant due to the species–area relationship [22] and its explanatory power for large-scale biodiversity [23,24]. Also, the Water Framework Directive defines large rivers as those with UDAs above 10,000 km² [25] and riverscape units with areas between 1000 km² and 10,000 km², which have been linked to regional biodiversity [26].

3

URL = 1000 km—defined to maintain lengthwise homogeneous units and to control exceptions where river length is not correlated with the drainage area. A watercourse over 1000 km has been termed a large river [27] or even a very long river in connectivity impairment studies [28].

The procedure to establish the R2U is fully described in the following procedure steps and depicted in Figure 4:

1

Identify the source segment of the main stem watercourse of the basin, and afterward, all the Hack pathways and respective mouth segments for the sea outlet basin. Exclude basins with overall maximum Strahler values below 3 (Figure 4—Step 1).

2

For the mouth segments of Hack n (where n is a discrete number starting at 1 and incremental for every procedure iteration) not abiding by all thresholds, their full UDA and URL are considered part of one single SRU. If this is the first iteration, where Hack = 1, then all segments in the basin are now identified with one SRU, an R2U comprising the entire basin, and the entire procedure ends (Basin B in Figure 4—Step 2). If this step does not apply, head to step 3 (Figure 4—Step 2).

3

For those abiding by the thresholds, an LRU will be established from the mouth segment until the most upstream Hack n segment where Strahler order is 4 inclusively (Basin A in Figure 4—Step 3). Upstream of this segment, hack n and respective UDA and URL segments will become part of an SRU (orange segments in Step 3).

4

Identify the Hack n + 1 mouth segments having a Strahler order lower than 3. These, along with respective UDA and URL, will be included in the large river unit established for the previous hack n segments (red segments and respective UDAs in Figure 4—Step 4).

5

Identify the Hack n + 1 mouth segments having Strahler order ≥ 3 but not abiding by the other thresholds. Each one with its respective upstream segments, UDA, and URL will constitute an individual SRU (green segments in Figure 4—Step 5).

6

Identify the Hack n + 1 mouth segments abiding by all the thresholds established for LRUs; these will be part of a new large river unit to be established in the river basin. Establishing a new LRU starting in a Hack n + 1 mouth segment leads to a confluence between LRUs. To maintain the network’s dendritic and hierarchical nature, the previously established LRU in the Hack n segments will be split at this confluence (red segments in Figure 4—Step 6).

7

The procedure to define the extent of the Hack n + 1 LRU and to continue the process can now be taken back from step 2 onward (since a new iteration will start, n will also increase accordingly) (dark blue and orange segments in Figure 4—Step 7).

Applying the R2U methodological procedure creates two types of R2U, Small River Units (SRU) and Large River Units (LRU), for each sea outlet river basin. The LRUs are units associated with the main stem pathways of river basins that serve as connectors between SRUs, which are units of smaller size and complexity on average. Establishing an LRU is preceded by adhering to all the thresholds: Strahler values above 3, UDA above 1,000 km², and URL above 1,000 km. Considering these thresholds, some SRUs may fall within two categories: (1) Small River Sea Outlet (SRSO), an SRU that matches the full sea outlet basin, and (2) Large River Head Unit (LRHU), an SRU that contains the source segment of a contiguous LRU.

3.2. Dataset Validation

The construction of this database departed from the CCM2 database [12], which contains multiple layers and attributes that depict European rivers’ spatial and structural characteristics [14]. By using CCM2 as source data, we took advantage of the set of validations and its spatial correctness, thus avoiding topological errors. This also means that no aggregation inaccuracies arise from the employed method. Nonetheless, the CCM2 original report [1] and later work [4] acknowledge that errors exist for certain regions, meaning that defined R2Us in these areas may also reflect these errors. As soon as those are corrected by the data providers, the method can be applied again to account for the corrections. Adopting the sea outlet basinsbasin identifiers from CCM2 ensures interoperability between databases.

Despite the methodological thresholds to enforce size homogeneity, exceptions may occur associated with mountainous areas where high Strahler values are reached across small drainage areas or, conversely, in flat areas where large drainage areas will have small variations in Strahler stream order values. Other than this, small units associated with main stem watercourses may occur due to step 6 when a main stem segment starts and ends at confluences between Large River Units (please see Figure A1 in Appendix A for further details on the R2U drainage area).

After the implementation and execution of the methodological procedure, the tabular output was verified and linked to spatial data using ArcGIS Pro ^® (version 3.2.2). These outputs were then streamlined into a PostgreSQL relational database, a process that entailed data normalization into a relational model and a validation process. The set of rules and constraints implemented for validation enforces data integrity, accuracy, and reliability while streamlining usage efficiency and effectiveness. The R2U dataset attributes were created to enable the possibility of being useful for network analysis using, for example, ArcGIS Pro^® or RivTool [15]. This possibility was validated using RivTool by creating a fully functional network file (made available via Open Science Framework: https://osf.io/gp7xr/ accessed on 18 March 2025) that allows further river network calculations as connectivity indexes.

4. User Notes (Optional)

River Restoration Units (R2Us) are the result of a novel method for grouping river segments and their corresponding drainage areas across European river networks, aligning with river network functioning. Beyond the MERLIN and Dammed Fish projects [10], this dataset has already been used to discuss the challenges of restoration targeting free-flowing rivers under the Nature Restoration Law [11]. Furthermore, at the sea outlet basin level, the definition of small river units connected by large river units enables a simplification of the river network useful for river connectivity research and management at two different scales: (1) at the local scale, where we can calculate connectivity within R2Us and test local connectivity restoration scenarios; and (2) at the basin-scale, where the inner connectivity of the Small River Units and Large River Units (here acting as within-basin connectors) can be used to assess the overall basin connectivity and test for basin-wide connectivity restoration scenarios. The option offered by river restoration units to work at these two nested scales provides great computational benefits as this simplifies the problem without compromising accuracy. River biodiversity and processes are spatially influenced by the surrounding land patches and conditions [29]. Therefore, R2Us may expedite the integration of data covering multiple aspects such as land use, land cover, soil and geological properties, human social aspects and heritage, climate change, and governance, enabling more holistic approaches. Another example of reusing this dataset would be to rely on the river restoration units as an intermediate scale between river segments and river basins in plans to upscale interventions in river networks (e.g., conservation actions), taking advantage of the nested nature of river networks. By allowing data integration into river management units with similar complexity and size that maintain the basic features of river network functioning, the sub-units created here provide a useful platform for data management at large spatial extents. Moreover, since the aggregation of river building blocks and consequent creation of river restoration units is made per river basin, the dataset preserves the insular nature of river basins, which is crucial for management and conservation purposes.