Bedload response to dam removal: Results from a 6-year particle tracking survey in the Leitzaran River (Basque Country)

Bedload response to dam removal: Results from a 6-year particle tracking survey in the Leitzaran River (Basque Country) A. Ibisate a,* , H. García b,c,d , D. V´ azquez-Tarrío e , I. S´ anchez-Pinto a , X. Herrero a , A. S´ aenz de Olazagoitia a , A. Ollero f a Department of Geography, Prehistory and Archaeology, University of the Basque Country (UPV/EHU), Vitoria-Gasteiz, Spain b Department of Geography, University of Santiago de Compostela, Santiago de Compostela, Spain c AMBIOSOL Research Group d CISPAC – Interuniversity Research Centre for Atlantic Cultural Landscapes, Spain e Department of Geo-Hazards & Climate Change, IGME, CSIC, Madrid, Spain f Department of Geography and Land Management, University of Zaragoza, Zaragoza, Spain ARTICLE INFO Keywords: Bedload transport Sediment connectivity RFID tracking River restoration Gravel-bed river ABSTRACT Dams, weirs and transverse barriers to rivers interrupt sediment continuity and reduce sediment supply downstream. In this regard, dam removal is an increasingly used river restoration measure to recover longitudinal connectivity of sediment, among many other river processes. In this work we present a 6-year (from 2016 to 2022) monitoring of bedload transport before, during and after the removal of the 7-meters high Olloki dam in the Leitzaran River (Basque Country). The removal process started in 2018 with the upper 3 m and was completed in 2019 with the remaining 4 m of the dam. To monitor bedload transport, we seeded RFID-tagged stones in three reaches: a control reach unaffected by the dam, a reach immediately upstream of the dam, and a reach downstream of the dam. We deployed 300 tagged stones each year (100 by reach), i.e., 1800 in total. We measured important mobilization and displacement of tracer stones (with maximum travel distances of ~8.8 km of tracers seeded upstream the Olloki dam) during an active hydrological year following the complete removal of the dam, with some tagged particles even travelling across a downstream weir. We also reported changes in the progression of tagged stones in the dam-affected reaches (upstream and downstream) with the removal, with further and faster dispersal of sediments once the dam was removed. In addition, in these reaches we estimated larger volumes of mobilized bedload in the three years following removal than in the previous years, especially in the upstream reach. In this regard, the relationship between bedload and cumulated energy suggests that less energy was expended in the upstream reach for mobilizing bedload once the removal of the dam was completed. Conversely, in the control reach no major changes were observed before and after the removal of the dam; this reach showed only an increase in sediment mobilization during the last hydrological year, which was the most hydrologically active of the whole monitoring period. In summary, our tracer observations document that travel distances and mobilization volumes are considerably increased with dam removal, especially once the dam was completely removed. 1. Introduction The geomorphic dynamics of rivers depends on complex interactions between water flow, sediment fluxes and valley configuration, among other controls. In this regard, human activities can alter water and sediment flows and limit the space available for the river to freely flow during floods; thus representing a major disturbance to the geomorphic functioning of rivers in the “Anthropocene” (García et al., 2021). The 20th century has seen a wide variety of human impacts on rivers worldwide, but dams may have had the most significant impact in terms of the geomorphic dynamics of rivers. In fact, these human infrastructures constitute a barrier interrupting the longitudinal continuity of sediment fluxes (mainly in the case of the coarse bedload) and a modification of the flow regime. This is particularly noticeable for larger reservoirs (Brandt, 2000; Graf, 2005; Rollet et al., 2014; Major et al., 2017), but also applies to weirs depending on their height and the * Corresponding author. E-mail address: [email protected] (A. Ibisate). Contents lists available at ScienceDirect Geomorphology journal homepage: www.journals.elsevier.com/geomorphology https://doi.org/10.1016/j.geomorph.2024.109542 Received 28 March 2024; Received in revised form 24 November 2024; Accepted 29 November 2024 Geomorphology 470 (2025) 109542 Available online 2 December 2024 0169-555X/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/bync-nd/4.0/ ). specific geomorphic setting (Sindelar et al., 2017; Peeters et al., 2020). More than 53 % of the global land-to-ocean sediment flux is potentially trapped in reservoirs, with an estimated 4–5 Mt. trapped in about 28 % of the world’s catchments (V¨ or¨ osmarty et al., 2003; Syvitski et al., 2022). This trapping of sediment in reservoirs means a loss of storage capacity, functionality and a reduction of life-span for these infrastructures (Randle et al., 2021), but above all a deprivation of sediment necessary for a natural geomorphic and ecological functioning of the river downstream of the dam. This has consequences such as planform and bedform changes (Brandt, 2000), narrowing (Kondolf and Wolman, 1993; Kondolf, 1997; Downs and Pi´ egay, 2019) or loss of habitats for some species (Walling, 2006). Sediment starvation and ‘hungry waters’ below dams (sensu Kondolf, 1997) can also trigger bed incision downstream, which has become the main ‘disease’ in many rivers reaches around the world, causing imbalances that endanger the infrastructure located in the channel and the land uses on the floodplain (due to the lowering of the water table). Incisions of up to 10 m have been reported in some reaches of the Bernesga, G´ allego, Cervo or Secchia rivers (Ferrer-Boix et al., 2023), for instance. Sediment trapped in reservoirs can therefore be considered ‘misplaced resources’ (in the words of Kondolf et al., 2014), as these same sediments are unfortunately needed downstream of reservoirs to maintain river morphology and ecology and to replenish critical shoreline land. In this context, there is an increasing societal awareness and demand to rehabilitate or improve bedload dynamics below dams to improve hydraulic conditions, river morphology, habitat complexity or spawning areas. In Europe, for example, the Water Framework Directive from 2000, calls for river restoration as a strategy to improve river functioning, explicitly mentioning the need to maintain river water, sediment and species continuity. In addition, the EU target is to restore 25,000 km of free-flowing rivers by 2030 (European Commission, 2020; Belletti et al., 2020), and the global Freshwater Challenge is to restore 300,000 km of degraded rivers by 2030 as part of the UN Decade of Ecosystems Restoration. Spanish national river strategy is also aligned with this purpose. Several practices have been implemented aiming at increasing sediment availability below reservoirs, such as gravel augmentation (P´ erez et al., 2015; Arnaud et al., 2017; Brousse et al., 2019; Brousse et al., 2021; Chardon et al., 2021; Van Looy and Kurstjens, 2022; V´ azquez-Tarrío et al., 2023), sediment release from reservoirs (Wohl and Cenderelli, 2000; Kondolf et al., 2014), or weir or dam removal (Graf, 2003; Wilcox, 2014; Ibisate et al., 2016; Ritchie et al., 2018). In the last years many dam removals practices have been done worldwide. According to Dam Removal Information Portal, 1796 dams have been removed in US by 2023 (https://data.usgs.gov/drip-dashboard/) and other 6223 dams dismantled in Europe as per Dam Removal Europe (htt ps://damremoval.eu/). Most of the removed dams are low-height barriers (Habel et al., 2020), and few of them higher than 30 m as is the case of dams removed in the rivers S´ elune (Vezins dam), Elwha (Elwha and Glines Canyon dams), White Salmon (Condit dam) and Carmel river (San Clemente dam), with relevant monitoring programs (Wilcox et al., 2014; East et al., 2015; Randle et al., 2015; Warrick et al., 2015; Major et al., 2017; Fovet et al., 2023; East et al., 2023). Overall, experiences with dam removal have demonstrated their potential to improve geomorphic conditions (in terms of reactivating sediment transport downstream dam, mitigating river incision, increasing channel’s morphological diversity…) if implemented thoughtfully and in conjunction with comprehensive river management strategies. However, carefully considering of site-specific factors (Foley et al., 2017a) and potential environmental impacts is crucial to ensure the success and sustainability of such projects. This requires ambitious and sustained monitoring programs to assess the effects and/or success of the rehabilitation/restoration actions. In this regard, field monitoring of the geomorphic and sediment-transport response to dam removal provides precious and indispensable data for other complementary analysis on the topic such as flume experiments (Lisle et al., 1997, 2001; Cui et al., 2003; Ferrer-Boix et al., 2014, 2015) and numerical studies (Cantelli et al., 2004, 2007; Cui and Wilcox, 2008; Woodward et al., 2008; Downs et al., 2009; Cui et al., 2019). Field monitoring of river response to dam removal is typically based on topographic surveys, geomorphic change detection or particle tracking (Major et al., 2012; Ollero et al., 2014; East et al., 2015; Magirl et al., 2015; Ritchie et al., 2018; Gilet et al., 2021; Fovet et al., 2023; M¨ ortl et al., 2023). According to Pizzuto (2002) and Graf (2005), time scales of river response to dam removal are uncertain, but they might be on the order of decades. However, most of the monitoring studies are much shorter and many do not have information on pre-removal conditions (Bellmore et al., 2017; Foley et al., 2017b), limiting our ability to completely understand river adjustments due to dam removal. Major et al. (2017) recommended that a successful monitoring program of dam removal should collect information of pre-removal conditions, reservoir sediment volume and characteristics, background sediment flux, reservoir erosion rates, downstream sediment transport, downstream channel morphological changes and long-term geomorphic adjustment. In addition to improving knowledge of geomorphological adjustments and sediment budgets, these measurements can provide data for numerical models designed to predict geomorphic responses to dam removal (Major et al., 2017). Among the various techniques available for measuring sediment transport, perhaps one of the most potentially applicable in the context of dam removal is particle tracking, i.e., the use of tagged stones to trace the displacements of individual sediment particles over time. This technique has been largely used in fluvial geomorphology to understand links between sediment transport and channel morphology (e.g. Hassan and Bradley, 2017; V´ azquez-Tarrío et al., 2019). This procedure allows tracking the displacement and dispersion of a sediment plume over time, which makes it particularly suitable for tracking the remobilization of the sediment pile stocked in a reservoir following dam removal. There are several experiences of gravel mobility tracking using tagged stones as tracers to assess gravel augmentation response (Arnaud et al., 2017; Chardon et al., 2021; V´ azquez-Tarrío et al., 2023; Liebault et al., 2024) or dam removal (Gilet et al., 2021), but data are still scarce and there are no many long-term tracer studies available within the frame of assessing how gravel-bed rivers react to dam removal. Following this argument, we present the results of a 6-year field survey (2016–2022) for the monitoring of the Olloki dam removal using particle tracking in the Leitzaran gravel-bed river. This sediment transport monitoring is part of a broader geomorphic monitoring of two dam removals in the Leitzaran River (Basque Country, Spain) and accomplished between 2013 and 2022. Our study provides data about the effect on sediment transport after the removal of the Olloki dam, and data of a long particle tracking survey (covering upstream, impounded and downstream reaches) and before, during and after dam removal, that helps to understand sediment dynamics during several years after the setting of a new base level. We detected a change in hydraulic response and sediment dispersal after dam removal, with different sediment transport responses in different reaches. 2. Study area The Olloki dam is located on the Leitzaran River (Basque Country), a 42 km-tributary of Oria River that drains a 124 km 2 basin and flows into Cantabrian Sea in the northern Iberian Peninsula. The river in the study area flows across a narrow valley carved into Paleozoic outcrops. The channel is steep with a meandering pattern, and the bed morphology alternates between straight, plane-bed reaches and sequences of riffles and pools with alternate lateral and point bars. The area is forested with deciduous but also forest plantations with clearings practices (Fig. 1). The mean discharge of the Leitzaran River at the study site is 4.73 m 3 /s, its mean unit stream power 19.7 W/m 2 , bankfull discharge 67.8 m 3 /s and its 2-yr, 5-yr and 10-yr return period discharges are 85.0, 126 and 153 m 3 /s, respectively. Its bed material is mainly cobble and the median A. Ibisate et al. Geomorphology 470 (2025) 109542 2 bed grain size has evolved over the studied period, ranging between 64 and 126 mm. Two dams have already been removed in the framework of two European projects, a European Regional Development Fund (ERDF) project and a LIFE project that seek the recovery of longitudinal connectivity to improve Atlantic salmon habitats together with river geomorphology. These dams are: Inturia dam (12.5 m high), removed between 2013 and 2016 (Ibisate et al., 2016) and Otita (Truchas Erreka) (5 m high) in 2015, both downstream of Olloki dam. Inturia dam was constructed in 1913 for water regulation of a hydroelectrical station located downstream aimed to provide electricity to the tramway of San Sebasti´ an city. Truchas Erreka was initially aimed for hydroelectrical production (from 1913 to 1977), and since 1977 it was used for supplying a fish farm. Nevertheless, there remain some transverse barriers (weirs) in the Leitzaran river, four upstream of Olloki dam and four others downstream of Olloki: Bertxin weir, of 5.8 m-hight, Olaberria weir, of 5.5 m-hight and two more near the confluence with the Oria River. Bertxin weir is filled with sediment (Ibisate et al., 2016). The Leitzaran River has had since 1994 a gauging station that measures discharge every 10 min, located in the lower part of the river, near its confluence with the mainstream Oria River (the gauge station covers 110.01 km 2 of drainage area). Additionally, there is a weir upstream of the study area that derives water to a hydroelectric station located at the tail of the reservoir of Olaberria weir, located downstream (Fig. 1). This bypass has a maximum of only 3 m 3 /s, which is not enough to affect the sediment transport capacity, less alone during flood events when sediment transport is expected to occur. In this work, we focus on Olloki dam removal. This 7 m-height dam was built in 1762 for a forge and the definitive height of the dam was attained in 1929, when the Olloki hydropower plant was built (Cabez´ on, 2023). Therefore, the dam has almost a century of impoundment with its last height, but even 150 years more with a lower one. The reservoir upstream of the dam was 600 m long, ~25 m wide and filled (Fig. 2) with approximately 90,000 m 3 of sediment, mainly cobbles covered by a couple of meters of sand with few silts and clay (Ikerlur., 2015). The dam completely interrupted bedload transport, and only fine sediments travel across the dam during floods, which were the sediments that filled Inturia reservoir (Ibisate et al., 2016). Olloki dam was removed in two stages, by removing horizontal slats covering half width of the dam, as it can be seen in Fig. 2. The first 3 m slat was removed in September 2018 Fig. 1. Location of the studied area in Leitzaran River. A. Ibisate et al. Geomorphology 470 (2025) 109542 3 and the second 4 m slat in September 2019 (Fig. 2). 3. Methodology 3.1. Experimental design To understand how the Leitzaran river would react to the removal of the Olloki dam, we decided to set up a ‘Before-After-Control-Impact’ (BACI) experimental design and we monitored two impact reaches (upstream and downstream of the Olloki dam) and one control reach (upstream of the dam), both before and after dam removal. This kind of experimental designs are commonly applied in ecological monitoring studies for the quantification of environmental impacts (Underwood and Bennett, 1992; Roni et al., 2013; Smokorowski and Randall, 2017) and are becoming increasingly used in fluvial geomorphology (e.g., Marteau et al., 2022). After an initial field campaign in 2016 to characterize the study reaches and deploy the first tracers in the seeding sites, field monitoring extended from 2017 to 2022 and consisted in six fieldwork campaigns (one per year): two campaigns before starting the removal (summer 2017 and 2018); one in between the two removal phases (summer 2019); and three more once the removal was completed (summer 2020, 2021 and 2022). We deployed RFID-tagged stones at three seeding sites, one in an unaffected reach of the river (by the dam) and the other two upstream and downstream of the dam (Fig. 3). The three seeding sites exhibited differences in bed slope and average grain size at the beginning of this research (Table 1). Control seeding site presented a generally natural hydrogeomorphological condition, without relevant alterations, so it could be under optimal conditions in terms of morpho-sedimentary dynamics. Conversely, upstream seeding site corresponds to the tail of the reservoir, and the downstream seeding site is located downstream of the dam, so geomorphic conditions in both reaches are affected by the dam. From one seeding site to the next downstream, we defined a ‘study reach’. We therefore defined three study reaches, hereafter referred to as ‘control’, ‘upstream’ and ‘downstream’, according to their location in relation to the Olloki dam (Fig. 3). That is being said, the ‘control’ reach starts in the most upstream seeding site and extends until the tail of the reservoir, where the upstream-dam seeding site was located. Then, the ‘upstream’ reach extends from the upstream-dam to the downstreamdam seeding site and includes the whole reservoir of the former dam. Finally, the ‘downstream’ reach starts at the downstream-dam seeding site and finishes in the Olaberria weir, where we found the lowermost travelling tagged stones. The control reach is located ~2 km upstream the Olloki dam. It is a narrow (49-m-wide) riffle-pool reach, with a 0.0084 m/m bed slope. The upstream-impact reach is a 1.5-km length reach, located 450 m upstream the dam, but in the area influenced by backwater effects of the dam. It is a 41-m width reach with a ~ 0.08 % bed slope. The downstream-impact reach is located ~600 m downstream of the dam. It is a 30-m width riffle-pool reach, with a mean bed slope around 0.077 m/m. Table 1 summarizes the main characteristics of the three reaches. A particle tracking field campaign was done on the three reaches using RFID technology and PIT-tags for 7 hydrological years, from the summer of 2016 (first seeding) to the summer of 2022 (last search of tracers). Fig. 2. Images showing the Olloki dam (photos taken from downstream to upstream) and the river immediately upstream (photos taken from upstream to downstream) and downstream the dam, before the removal (July 2017), partial removed (September 2018) and completely removed (July 2020) (photos taken from downstream to upstream). A. Ibisate et al. Geomorphology 470 (2025) 109542 4 3.2. Grain-size and topographic measurements We characterized the grain size distribution of each reach using the Wolman pebble count method (Wolman, 1954) and an aluminum template (after Hey and Thorne, 1983) to measure particle diameter. Each year from 2016 to 2021, one Wolman sample (180 counted grains) was collected along “forced” sediment bars in each simple point. The width, depth and the average bed slope of the cross-section where tracer stones were seeded at each of the three study reaches were measured using Leica TS02 and Leica TC-307 total stations. These measurements were repeated each year over the study period aiming at identifying possible geomorphic changes during the monitoring period. 3.3. Particle tracking Each year, 100 clasts per reach were collected and drilled. Then, 23mm RFID tags were inserted, and the hole was sealed with resin. We measured the three axes (a, b and c) of each particle, and we noted each tag identifying code. Finally, we painted the clasts with different colors for each site and year to facilitate their search in the field (Arnaud et al., 2017; Liebault et al., 2024). This workflow was repeated for the three selected reaches and for each study year from 2016 to 2021, i.e., 1800 tagged stones were seeded in total, 600 for each reach, that is, 100 per year and reach. Tracer sizes were selected based on the median size of the bed sediment measured that year at each site. Then, tracer stones were selected to belong to the size class corresponding to the semi-phi interval including the median size, following the Wentworth scale, (Wentworth, 1922), and in the semi-phi size class above the median (Table 2). Due to the small size of the interval below the D50 (45.3 ≥Ø <64) in the control and upstream reaches (compared to the PIT-tag size, 23 mm) we decided to discard these intervals, as well as the lower interval of downstream reach, to be consistent and follow the same conditions in the three study reaches. Fig. 3. Studied river reaches and seeding sites (1: Control, 2: Upstream, 3: Downstream). Table 1 Characteristics of the studied reaches. Distance to the dam from seeding site, 0 represents the dam, negative distances correspond to upstream distance to the dam, whereas positive distances represent downstream distances to the dam. Reaches Length between seeding sites (m) Cumulated lengths (m) Bankfull width (m) Distance to the dam from each seeding site (m) Median grain size (mm) Slope (m/ m) Drainage basin (km 2 ) Control 1938 1938 49 −2224 64 ≥Ø <90.5 0.0084 80.19 Upstream 1044 2980 41 −452 64 ≥Ø <90.5 0.0008 81.91 Downstream 8020 11,002 30 595 90.5 ≥Ø <128 0.077 91.23 Table 2 Grain size intervals of each sample point. In black, the grain size intervals used for tagged stones in each river reach; in grey, those discarded. ID Wentworth interval Below D50 D50 Above D50 Control 45.3 ≥Ø <64 64 ≥Ø <90.5 90.5 ≥Ø <128 Upstream 45.3 ≥Ø <64 64 ≥Ø <90.5 90.5 ≥Ø <128 Downstream 64 ≥Ø <90.5 90.5 ≥Ø <128 128 ≥Ø <256 A. Ibisate et al. Geomorphology 470 (2025) 109542 5 Tracers were deployed in each study reach forming a square over the surface of gravel bars and close to the bar-water boundary. Every year tracers were seeded in the same place (Fig. 4) at the beginning of each hydrological year (two broke and were lost when locating them on the seeding site). The tracer seeding position was geolocated with a GPS. Every summer, starting in 2017 and finishing in 2022, we searched and geolocated the found tracers helped with an Oregon RFID and Biomark tag readers. Two or three operators participated in each survey and the prospected area covered a channel surface defined by the control reach as upstream point, down to a lowermost boundary 500 m downstream of the last tracer found in each campaign. This surveying strategy was followed in all surveys except in the first one (2017), where the prospection was poorer due to limited time available for fieldwork and the surveyed area was up to ~250 m from the downstream seeding site. During the field work, the exact location of each of the tracers found was measured with a trekking GPS during the three first years, and afterwards with the GPS integrated in the Biomark tag reader. Later, data were analyzed using GIS to obtain the spatial distribution of tracers along the river after each field campaign. Our GPS had planimetric errors close to 40 m at some points, due to the dense, tall tree cover and the steepness of the valley. We considered ~50 m as the precision of the tracer position to apply a palliative and conservative measure. Therefore, tracer positions were assigned to 50 m bins along the longitudinal channel profile. For this purpose, GIS software was used to draw a buffer polygon zone from the central axis of the Leitzaran riverbed, allowing a distance of 40 m on either side (i.e. a buffer of 80 m wide and 50 m long). Then, individual travel distances were computed with an error of ±25 m. The central axis of the channel in the study section was drawn at a scale of 1/1000 from the latest available orthoimagery. 3.4. Metrics for analyzing tracer data Two different metrics were used to characterize the displacement of each single i-tracer: i. the distance travelled between two consecutive surveys (d j ); and ii. the cumulative distance travelled from the initial seeding location (L j ). Then, for each tracer survey, we estimated the mean value of these two metrics: <d>and <L>: 〈d〉Sj=∑ i=nrf i=1 Xi,Sj−Xi,Sj−1 nrf 〈L〉Sj=∑ i=ninf i=1 Li,Sj ninf where S j and S j-1 refer to two successive field surveys; n rf is the number of tracers found in both surveys, and n inf is the number of tracers for which its position is known (or is inferred) for a given survey; X i,Sj -X i, Sj-1 is the difference in longitudinal tracer positions between S j and S j-1 along the channel centerline; and L i is the travel distance measured from initial tracer seeding position. The first metric provides information of each tracer found in both two successive surveys and gives an idea of the average displacements of sediment particles during the survey period, while <L >informs of all tracers found in each survey and provides insight on the progression of the centroid of the tracer plume (Arnaud et al., 2017). For the estimation of Li and <L>, following the recommendations of MacVicar and Papangelakis (2022), we included ‘inferred’ tracers into the analysis of our data, i.e., tracer stones missing in a survey but re-found close to their Fig. 4. On the left shows seeding sites control, upstream, and downstream. On the right shows a tracer searching and a boulder and bedrock difficult to track reach downstream Bertxin weir. A. Ibisate et al. Geomorphology 470 (2025) 109542 6 previous position in a later prospection, so we could infer that they were immobile. To characterize the hydraulic forcing, we used the cumulative excess energy or time-integrated excess (specific) stream power, based on previous literature documenting that mean travel distances of coarse sediment are well correlated with this parameter (Haschenburger, 2013; Papangelakis and Hassan, 2016; Papangelakis et al., 2022). Timeintegrated excess (specific) stream power was calculated as: ∫( ω − ω c)dt = ρ gS w∫tf t0 (Qt−Qc)dt where ρ (kg/m 3 in SI units) is the density of water, g (m/s 2 in SI units) is the acceleration of gravity, S (m/m in SI units) is the bed slope at the beginning of each hydrological year, Q t (m 3 /s in SI units) is the water discharge at an instant t, Q c (m 3 /s in SI units) is the critical discharge, w is the bankfull channel width at the beginning of each hydrological year (m in SI units), and t 0 and t f are the start and end of the mobilizing event. To further assess the links between hydraulic forcing and tracer displacements, we also estimated the ‘Energy Expenditure Index’ (EEI) proposed by V´ azquez-Tarrío et al. (2019) and V´ azquez-Tarrío and Batalla (2019): EEI =∫( ω − ω c)dt 〈d〉 where ω is the specific stream power and ω c is the critical value of ω for incipient sediment motion. This parameter is somehow related to the ‘transport efficiency’ concept of Bagnold and is in some way a proxy of the amount of energy needed to displace tracers per unit length (i.e., 1 m), which in a way quantifies the cross-sectional average energy required to displace the tracers. 3.5. Estimates of bulk bedload volumes Several approaches have been proposed to estimate bedload volumes from particle tracking data (e.g., Haschenburger and Church, 1998; Li´ ebault and Laronne, 2008; Mao et al., 2017). Here, bulk bedload volumes were estimated from the results of tracer experiments using the following expression proposed by Haschenburger and Church (1998): ib= 〈d〉 /t⋅w⋅h⋅(1−p)⋅ ρ •fm where <d>is the mean travel distance of tracers, t the time duration of the competent flow, w is the pre-removal bankfull width at the beginning of the hydrological year, h is the depth of the active layer (mobile sediment), p is the sediment porosity, ρ the mineral grain density (here assumed to be 2650 kg m −3 ) and f m is the mobile fraction of bed sediment. The depth of the active layer was defined depending on the general bed mobility conditions of each year. When bedload transport was dominated by partial mobility (percent of mobile tracers <90 %), we took the D 50 as mean depth of the active layer. For those periods where full mobility conditions were achieved (percent of mobile tracers >90 %), we estimated the depth of the active layer based on the equation for the scour depth proposed by Recking et al. (2023): h=1.4wS Concerning the time duration of the competent flow, we consider the cumulated time above critical flow discharge for each study period. In this regard, during December 2017, 2017–2018 hydrological year, we observed in the field some very small movements, ±1 m or 1.5 m, and rearrangements of the tracers given between October and December 2017 in the control reach. Then, the peak discharge preceding this observation (~25–30 m 3 /s) was assumed in this work as the critical discharge. Finally, the mobile fraction of bed sediment was estimated from tracer data as the ratio n mob /n rec , where n rec is the number of the recovered tracers and n mob are the number of moved tracers. This bedload volume estimation was done for each year based only on the retrieved tracers that were introduced the year immediately before. 4. Results 4.1. Hydrology of the study period From 2016 to 2022 there have been 22 floods whose peak discharges were above the critical flow rate (Fig. 5). The maximum recorded peak was 143.9 m 3 /s and occurred between the 25th of November and 12th of December of 2021 (Table 3). The total number of days during which critical discharge has been exceeded at least once was 35 from 2016 to 2022. The survey 2021/22 was the most ‘active’ year from a hydrological point of view, with the highest recorded floods (99.7 m 3 /s maximum mean daily flow and 143.8 m 3 /s peak flow – 7.9 yr return period–) during the whole monitoring period and more days above the critical flow (Table 3). Conversely, year 2020/21 was the ‘quietest’, with the lowest recorded peak discharge (39.1 m 3 /s) and only 2 days with discharges above the critical threshold. 4.2. Grain size data Table 4 shows the results of annual grain size measurements in the reaches. We observe a progressive fining of the grain size in the three reaches during the six years of the study. This fining was greater in the downstream reach. In general, downstream reach had the highest grain size values, while the upstream had the lowest values during all the campaigns, except for the last one, once the dam was completely removed, when the control reach had the highest values. 4.3. Tracer surveys: raw data We recovered a remarkable number of the seeded tracers, but recoveries were variable depending on the year. Out of a total of 1798 tracers introduced in the three study reaches, we recovered 474 in 2022 at the end of the 6 years of field survey (Table 5). Many of the tagged stones were recovered several times during the different field campaigns. The data presented in Table 5 document variable recovery rates, ranging from a relatively high recovery ratio of 51.3 % in 2018 to lower recoveries (26.4 %) in 2022. If we consider only the tracers that were found among those that were introduced in the previous year, the recovery ratios are higher in all field campaigns (Table 5). This may be because tracers did not have enough time to become buried and wellmixed in the riverbed, or to travel further down of the prospected area. Recovery ratios in general decreased as field campaigns progressed. The last survey period is the one in which we report a greater decrease in the number of tracers recovered (26.4 % of the total introduced). With all the surveyed years considered, the recovery in control reach was of 989 tracers, 363 in upstream reach and 977 in downstream reach (Table 5). The highest recovery rates were in control reach, considering that 8 tracers found in upstream reach were seeded in control reach and 328 of those tracers recovered in downstream reach migrated from upstream reach, and even 3 other tracers migrated from control reach. Some of the tracers were found in reaches other than the ones where they were seeded. The lowest recovery rates were in general in the upstream reach. Besides that, we never found 545 of the total seeded tracers. The painting of the particles was lost in many of the cases, so few of them were identified by their color. The recovery rate of tracers in summer 2017 was very low compared to the other years (32 %). In addition, the measured displacements that year are limited to a very short reach and close to each seeding site A. Ibisate et al. Geomorphology 470 (2025) 109542 7 (Fig. 6). This is probably a bias resulting from the survey strategy followed during the tracer search, so the prospected area was probably shorter than the travel distance covered by the real movement of tracers. This could likely introduce noise in the interpretation and analysis of the data, so data from this first survey were therefore excluded from further analyses presented in this manuscript. Fig. 6 shows the locations where tracers were retrieved during the different field campaigns. These locations already suggest an important mobilization of sediment during the 2017–2022 monitoring period. The distances and locations of the tracers evidence that some of them crossed weirs, as some particles appeared downstream of Bertxin in 2021 and 2022. In 2021 only one was identified downstream Bertxin weir, 5625 m downstream of the upstream seeding site where it was seeded in 2016. In 2022, we detected 5 tracers downstream Bertxin weir: at 8525 m downstream from its seeding site (seeded in 2019 in upstream site), at 7675 m (seeded in 2021-upstream), at 7425 m (seeded in 2016 in upstream site), at 4675 m (seeded in 2016 downstream) and at 5475 m (seeded in 2016 upstream) each of them. Three more arrived even to the reservoir of Olaberria (2 seeded in upstream reach in 2018–8925 m downstream the seeding siteand the third located at 8825 m from the upstream reach where it was seeded in 2021). 4.4. Analysis of tracer displacements Globally, for the whole study reach, the analysis of the mean tracer displacements (d i ) shows: i. a progressive increase in the mean tracer displacements from the survey year 2017/2018 (before dam removal) to 2018/2019 (1st partial dam removal); ii. large tracer displacements were recorded once the dam was removed (survey year 2019/2020); iii. mean tracer displacements (298.6 m) are moderate during the year 2020/2021; and iv. large mean tracer displacements (1055.9 m) are recorded during the last monitoring year (2021/2022). Focusing on the behavior of the tracers introduced in each reach, the downstream reach records the longest displacements in all monitoring years, as well as the highest displacements in the most hydrologically active years (Table 6). The shortest displacements are reported in either the control or in upstream reach, depending on the year. In 2017/2018, before the start of dam removal, the upstream reach had the lowest displacements, but after the 1st dam removal and after its completion, larger displacements were found in the upstream reach, higher than in the control reach. The last monitored year, 2021/2022 (3 years after dam removal was completed), recorded the largest displacements in the upstream and downstream reaches, while 2017/2018 was the year with the largest mean travel distances in the control reach. We have also analyzed the potential influence of grain size on travel Fig. 5. Mean daily flow hydrograph of the whole monitoring period. Grey columns indicate the tracer tracking periods each year and the vertical dotted lines the beginning of each hydrological year (1-Oct to 30-Sep). Partial (3 m removal) and complete dam removal (4 m removal) moments are indicated. Table 3 Hydrology data: days above critical flow and peak flows for each hydrological year. Hydrological year Days above critical discharge Hours above critical discharge Q max (m 3 /s) Dam removal phase 2016/17 4 120.9 110.2 Before removal 2017/18 7 267.5 109.9 Before removal First slat removal (3 m). Partial removal 2018/19 7 251.3 70.6 3 m partial removal Second slat removal (4 m). Complete removal 2019/20 3 101 69.9 Complete removal 2020/21 2 85.2 39.1 Complete removal 2021/22 12 404.3 143.9 Complete removal Table 4 Grain size characteristics of each reach in each fieldwork campaign, in mm. Reach Decile 2016 2017 2018 2019 2020 2021 Control D16 27 45 33 22 24 17 D50 82 92 63 74 58 54 D84 180 180 110 190 120 110 Upstream D16 36 49 20 28 12 19 D50 68 79 39 58 34 44 D84 110 120 71 110 99 80 Downstream D16 48 47 35 27 21 26 D50 97 110 70 86 43 49 D84 210 210 160 180 82 85 A. Ibisate et al. Geomorphology 470 (2025) 109542 8 distances. For this purpose, it is not sufficient to plot distances against particle size, as this type of plot will be co-founded by the hydraulic effects associated with differences in hydraulic forcing in the data set. Therefore, it is first necessary to isolate the pure size effects from those due to different hydraulic conditions. In this respect, Church and Hassan (1992) proposed an approach to analyze the effects of grain size on travel distance, isolating them from the effects of hydraulics and particle arrangements. To do so, Church and Hassan (1992) suggested that observed tracer travel distances should be scaled with the mean travel distance of the bed median grain size (L* =L J /L JD50 )) and plotted against the ratio of the tracer size over the bed median grain size (D* = D j /D Jd50 ). To estimate L J D 50 , we only used tracers from the semi-phi interval of the bed median size. Additionally, Church and Hassan (1992) used the median of the subsurface grain size distribution to estimate D*. Here the grain size data were scaled by the surface D50 area following Wilcock (1997) rather than the subsurface, so to fit the original form of the relationship found by Church and Hassan, the grain size was multiplied by a factor of 2.2, which is an average value for armour ratio in gravel-bed rivers (V´ azquez-Tarrío et al., 2020). In Fig. 7, we have accomplished this analysis with our data. We do not observe any clear trend between particle travel distances and grain size, nor did we observe any difference before and after dam removal. Indeed, our tracer population was selected in a very narrow range of sizes and around the D50, so probably this is masking any potential trend. Table 5 Recovery data by reach, identifying the seeding origin for each field campaign (in grey the number of tracers found just from those introduced the year before). Seeding year Seeding site Locaon of found tracers 2017 2018 2019 2020 2021 2022 2016 CONTROL CONTROL 62 55 46 28 49 43 UP 1 2 DOWN 2 UP UP 21 43 33 19 12 DOWN 15 32 13 DOWN DOWN 13 40 61 19 20 16 2017 CONTROL CONTROL 49 35 40 60 29 UP 1 1 2 2 UP UP 54 20 6 5 DOWN 28 29 13 DOWN DOWN 67 59 12 15 19 2018 CONTROL CONTROL 49 46 62 44 UP 1 UP UP 34 17 10 DOWN 29 27 21 DOWN DOWN 60 27 29 23 2019 CONTROL CONTROL 46 70 43 UP 2 DOWN 1 UP UP 20 10 DOWN 38 40 13 DOWN DOWN 20 26 22 2020 CONTROL CONTROL 10 44 UP 1 UP UP 40 5 DOWN 15 DOWN DOWN 79 7 2021 CONTROL CONTROL 65 UP UP 1 DOWN 15 DOWN DOWN 12 Recovered 96 308 398 412 627 474 % recovered 32.0 51.3 44.3 34.4 41.9 26.4 Recovered only from those seeded the year before 96 170 143 124 129 93 %idem 32.0 56.7 47.8 41.3 43.1 31.0 Seeded 300 600 899 1199 1498 1798 A. Ibisate et al. 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