Quantifying postglacial sediment storage and denudation rates in a small alpine catchment of the Făgăraș Mountains (Romania)

Science of the Total Environment 599–600 (2017) 1756–1767

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Quantifying postglacial sediment storage and denudation rates in a small alpine catchment of the Făgăraș Mountains (Romania) Adrian C. Ardelean a,b, Alexandru Onaca a,⁎, Petru Urdea a, Adriana Sărășan a a b

West University of Timișoara, Department of Geography, V. Pârvan, no. 4, Timișoara 300223, Timiș, Romania National Museum of Banat, Department of Archeology, Martin Luther, no. 4, Timișoara 300054, Romania

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• The sediment storage quantification was conducted in an alpine Carpathian valley. • Geomorphological mapping, shallow geophysics and GIS modeling techniques were used. • Sediment volume for the Doamnei Valley was calculated to be 7.08 ± 1.42 106 m3. • The mean annual denudation rates for the entire catchment is 0.2 mm/year. • Improving the understanding of postglacial evolution of Carpathian alpine areas.

a r t i c l e

i n f o

Article history: Received 18 March 2017 Received in revised form 14 May 2017 Accepted 15 May 2017 Available online 19 May 2017 Editor: D. Barcelo Keywords: Sediment storage Sediment budget Postglacial denudation Ground penetrating radar GIS modeling Romanian Carpathians

a b s t r a c t The study of sediment production, transport, storage and discharge in alpine drainage basins is an essential prerequisite for a better understanding of the postglacial evolution of the alpine landscape. To get an overview on sediment production and alpine landscape evolution in Romania, the current study presents the first alpine sediment storage quantification in the Romanian Carpathians. Postglacial denudation was quantified within the small alpine catchment of the Doamnei Valley (3.62 km2), located in the central part of the Făgăraș Mountains. The quantification of sediment volumes was performed through a combined approach consisting of: (i) detailed geomorphological mapping of sediment storage landforms, by means of high accuracy field and remote mapping of sediment storage landforms, (ii) shallow geophysical investigations and (iii) geographic information systems modeling techniques. A total of 64 ground penetrating radar profiles were conducted through the valley for sediment thickness determination of individual landforms. Through parallel profiling, 5 electrical resistivity tomography profiles were also performed for the comparison of bedrock depths in order to determine the overall degree of accuracy of the geophysical investigations applied. In total, 79 sediment storage landforms were identified. Talus sheets were found to be the most dominant landforms within the investigated area, followed by talus cones, moraines and fluvio–torrential deposits. Sediment volume for the Doamnei Valley was calculated to be 7.08 ± 1.42 106 m3, corresponding to a mean sediment thickness of 4.20 m, with the hanging cirques and valleys subsystem storing 48.58% of the total sediment volume, despite covering just 22% of the investigated area. Sediment volume was used in the determination of mean annual denudation rates for the entire catchment (0.20 mm/y ± 0.04 mm/y) as well as for mean annual mass transfer (406.2 ± 31.6 t/km2/y), based on a time span of 13 ka. © 2017 Elsevier B.V. All rights reserved.

⁎ Corresponding author. E-mail addresses: [email protected] (A.C. Ardelean), [email protected] (A. Onaca), [email protected] (P. Urdea), [email protected] (A. Sărășan).

http://dx.doi.org/10.1016/j.scitotenv.2017.05.131 0048-9697/© 2017 Elsevier B.V. All rights reserved.

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1. Introduction High mountain systems are among the most sensitive environments to global climatic changes, reacting rapidly to air temperature rising (Kääb et al., 2005, Beniston and Stoffel, 2014). Approaches dealing with the impact of temperature changes on sediment production, transportation and deposition processes contribute towards a better understanding of the cryosphere, of which the periglacial domain is a major component (French, 2007). The periglacial environment is home to complex geomorphologic processes that govern sediment transfer and landform evolution within the alpine environment. As the latter is thought to be extremely susceptible to changes due to global warming, numerous studies have predicted that global temperature rise will have a major impact on landscape evolution within high-altitude and highlatitude cold environments (Haeberli and Gruber, 2009, Beylich et al., 2011, Schrott et al., 2012, Gobiet et al., 2014, Stoffel et al., 2014). Complex temporal and spatial interactions between climatic and geomorphic processes have led to the current spatial distribution of typical alpine sediment storage landforms, such as: talus slopes, talus cones or rock glaciers. To get an insight into the postglacial evolution of the alpine environments, the existing knowledge regarding both the role of sediment storage and the impact of slope processes in sediments redistribution should be enriched (Schrott et al., 2003). Therefore, the study of sediment production, transport, storage and discharge in alpine drainage basins an essential prerequisite for a better understanding of the evolution of the alpine landscape, especially in densely populated mountain areas with a high potential for the occurrence of natural hazards (Taylor and Steven Kite, 2006). The concept of paraglacial landscape response was first introduced by Church and Ryder (1972) to describe postglacial processes which acted in alpine environments, leaving behind the sequence of landforms that compose today's land surface. The processes governing postglacial evolution in alpine environments are complex and variable within different mountain ranges, leading thus to several models of slope evolution (Church and Slaymaker, 1989, Harbor and Warburton, 1993, Ballantyne, 2003, Dadson and Church, 2005). The main idea behind a sediment budget quantification is to account for the sources, movements and sinks of sediment within a given landscape (Slaymaker et al., 2003). The credit for the first attempt to document sediment mobilization and transfer rates within small alpine catchments is commonly attributed to Jäckli (1957) and Rapp (1960), while Leopold et al. (1966) were also considered one of the pioneers of the field. The research conducted by Caine was also of major importance by introducing the idea of a cascading system within sediment transfer in an alpine system (Caine, 1974, 1976). Their work was subsequently extended through the work of Dietrich and Dunne (1978) on the Rock Creek catchment. Other notable contributions to the sediment budget approach include those of Meade and Trimble (Meade and Trimble, 1974, Meade, 1982, Trimble, 1983), which emphasized the role of alluvial storage within the drainage basins of the east and central United States. Swanson et al. (1982) were the first to provide an exhaustive explanation of the sediment budget methodology, whereas Dunne (1994) was credited for having identified this approach as the backbone of the emerging field of hydrogeomorphology, while Reid and Dunne (1996) emphasized that sediment budgets could play a key role in resolving environmental management problems. Nevertheless, according to Ballantyne (2003) the key element for the construction of a paraglacial sediment budget is the quantification of storage volumes. Within the last decades this approach has been widely applied for modeling the sediment thickness distribution within several alpine catchments, based on different quantification techniques, starting from simple estimations to more complex geometric modeling, drilling, coring, dating and detailed geophysical surveys (Warburton, 1990, Kuhlemann et al., 2001, Schrott and Adams, 2002, Schrott et al., 2003, Otto et al., 2009, Tunnicliffe and Church, 2011, Götz et al., 2013, Müller et al., 2014). Since the quantified sediments allow for the

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calculation of average postglacial denudation rates, overcoming temporal variations, the sediment budget approach is often applied in the quantification of postglacial denudation in alpine environments by relating the sediments stored within landforms and sinks to their contributing source areas within a given temporal scale. In this context, sediment budget derived denudation rates and rockwall retreat rates have been widely applied within numerous alpine catchments (Andre, 1997, Hinderer, 2001, Hoffmann and Schrott, 2002, Curry and Morris, 2004, Cossart and Fort, 2008, Delmas et al., 2009, Otto et al., 2009, Götz et al., 2013). Despite the significant number of studies approaching the quantification of postglacial denudation rates derived by sediment budgets, only a few focus solely on investigating the internal structure of sediment storage landforms by means of shallow geophysical methods and GIS based modeling techniques (Hoffmann and Schrott, 2002, Schrott et al., 2002, Schrott et al., 2003, Otto et al., 2009). These small scale sediment budget studies, located within closed sedimentary systems, are more dependent on the specific topography imposed by glacial erosion, characterized by typical over deepened basins which act as sediment traps, successfully retaining sediments since deglaciation. Therefore, they are less prone to uncertainties generated by the volume of sediments evacuated since the last glaciation, the initial quantity of till deposits stored beneath the present-day sediment storage landforms and the absolute timing of deglaciation (Götz et al., 2013). Within small catchments, sediment budget approaches offer a better understanding of postglacial landscape evolution in alpine environments. The Doamnei Valley contains an outstanding assemblage of periglacial, glacial and fluvial landforms. This catchment was selected based on the pattern of sediment storage landforms, which was regarded as representative for a wider area of the Carpathian alpine range, as the analyzed catchment reveals similarities in landscape, lithology and tectonics, climate characteristics, hydrological regime and ecological conditions with the entire alpine area of the Făgăraș Mountains. Moreover, the existing surface exposure datings of several moraines within this valley (Kuhlemann et al., 2013) has allowed the precise reconstruction of the last deglaciation and the determination of denudation rates. The current approach presents a detailed and comprehensive mapping of sediment thickness, within a small alpine catchment, by means of high density ground penetrating radar (GPR) (64 individual measurements) and electrical resistivity tomography (ERT) profiles. As, previously conducted sediment budget quantification studies didn't pay a special emphasis on estimations of the overall degree of uncertainty (Otto et al., 2009, Götz et al., 2013) regarding the geophysically derived bedrock depths, we propose a quantitative analysis of estimating the overall error of the geophysical methods utilized by applying a cross-validation procedure between parallel GPR and ERT profiles. Therefore, the first alpine sediment storage quantification from the Romanian Carpathians is presented. The quantification of sediment volumes was performed for different high alpine sediment storage landforms located in the Doamnei Valley (Southern Carpathians), using a combination of high accuracy geomorphological mapping, shallow geophysical surveys and subsequent GIS modeling techniques. The aims of this approach are to (i) examine the spatial distribution of sediment storage landforms within the study area, (ii) to assess sediment thickness and volume and (iii) to offer a quantitative approach regarding postglacial evolution of the Doamnei Valley by determining denudation rates and mass transfer volumes based on the sediment budget approach. 2. Material and methods 2.1. Characteristics of the investigated area The study was conducted in the alpine area of the Doamnei Valley located in the central part of the Făgăraș Mountains (45°33′ N, 25°06′ E) (Fig. 1). This north-facing catchment reaches elevations of 2400 m

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(Paltinu Peak, 2401 m), whereas the lowest alpine areas are located below 1500 m. The investigated area covers 3.62 km2, having a specific lithology dominated by an alternation of amphibolites and mica schist and limestone-dolomite formations (Pană, 1990). The Făgăraș Mountains are currently free of ice, but during the last glacial phase of the Pleistocene the highest catchments supported small glaciers that did not reach the foreland. The lowest preserved moraines on this valley are at 1390 m, but the end moraine was probably completely eroded since the typical U shaped morphology of the valley and the occurrence of the erratic boulders suggest that the Doamnei paleo-glacier terminated around 1200 m. The end moraine probably belongs to the oldest glacial advance - locally termed Lolaia (Urdea, 2004) - and was not dated yet in the Southern Carpathians. According to 10Be exposure dating of moraines in the Doamnei Valley (Kuhlemann et al., 2013) the alpine sector of the investigated area, located above 1600 m, was deglaciated around 13 ka. The most prominent lateral and latero-terminal moraine complexes (Ștevia phase) within this valley occur between 1800 and 1900 m, in the vicinity of the Doamnei glacial lake. Based on the glacially defined general morphology the alpine sector of the Doamnei Valley can be roughly subdivided into two different subsystems, forming a typical landform assemblage of a sediment cascade system. The two different subsystems are: (i) the two hanging glacial cirques (Căldărușa cu Iarbă and Căldarea Pietroasă) – subsystem I, and (ii) the outer Doamnei glacial cirque with the corresponding glacial valley sector – subsystem II (Fig. 1). Typical periglacial landforms can be found above 1500 m, including scree slopes, talus debris, solifluction lobes, ploughing blocks, patterned ground, rock streams and one rock glacier within the Căldarea Pietroasă hanging cirque. The occurrence of permafrost within the Pietroasa rock glacier was recently confirmed by geophysical investigations and ground surface temperature monitoring (Onaca et al., 2013). The dominant present-day geomorphological processes are represented by rockfall, debris flows, solifluction and snow avalanches (Onaca et al., 2016). Under the influence of local regulators (e.g. slope angle and length) these processes play a major role within the local sediment flux system, ensuring debris accumulation and transfer as well as the connection between the two subsystems of the investigated area. According to the climatic data from the nearby Bâlea meteorological station (2038 m.a.s.l., period 1979–2009), the mean annual air temperature (MAAT) is 0.4 °C, whereas the mean air temperature of the winter

months is −7.1 °C. The calculated 0° C isotherm lies between 2050 and 2100 m, whereas at 2400 m the extrapolated MAAT is − 1.9° C. The mean annual precipitation is 1220 mm/y, with the highest precipitations occurring during June (146 mm/y). During the winter season (November–April) the mean temperatures are below freezing and the precipitations falls primarily as snow. At the Bâlea meteorological station the ground is covered by snow around 240–250 days/year. The quantification of sediment volumes within the alpine sector of the Doamnei Valley consists of a combination of different methods adapted to the specific morphology of the investigated area. A high-resolution digital elevation model (DEM) and aerial images were used for detailed geomorphological mapping, whereas ground penetrating radar (GPR) and electrical resistivity tomography (ERT) were used for subsequent GIS modeling of sediment thickness and volumes. The vast number of GPR profiles offered a comprehensive set of high accuracy data regarding bedrock depth at several sediment storage landforms. The information obtained has been successfully utilized in a GIS-based interpolation of sediment thickness as well as for further quantification of sediment storage volumes. Based on the overall sediment volume the mean annual denudation rate and the mass transfer were determined for the entire area and for the two individual subsystems. Fig. 2 presents an overview of the applied methodology, whereas the most important aspects will be described in detail in the following schema. 2.2. Geomorphological mapping The concept of geomorphological mapping is widely accepted as being a key tool in geomorphological system analysis as well as for offering a basis for understanding local catchment configuration (Otto and Dikau, 2004, Messenzehl et al., 2014). Recent advances in remote sensing along with the ever increasing availability of high resolution aerial and satellite imagery offer the possibility of generating automatically derived geomorphological maps based solely on specific GIS analysis (Siart et al., 2009, Seijmonsbergen et al., 2011). Due to the complex topography of the investigated area the delineation of sediment storage landforms was performed via a combined approach of both direct field and remote GIS mapping techniques. Field mapping of individual sediment storage landforms was performed in the summer of 2013 and 2014 using a submetric Trimble GeoExplorer 6000 DGPS. Landform distribution within inaccessible areas (e.g. steep slopes, rock walls) was

Fig. 1. Location of the study area.

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Fig. 2. Schematic representation of the methodology applied in the sediment budget quantification within the Doamnei Valley.

latter digitized using two distinct aerial images of 0.25 and 0.5 m resolution as well as a 0.5 m resolution DEM. All the spatial data were processed using specific GIS software (ArcMap 10) in order to generate the geomorphological map covering the 3.62 km2 of the investigated area. The final database includes information on both quantitative and qualitative information of each individual sediment storage landform. Based on these the investigated area was classified into six distinct categories, according to Ballantyne and Harris (1994): (i) talus sheets, (ii) talus cones, (iii) moraine deposits, (iv) rock glaciers, (v) fluvio-torrential deposits and (vi) superficial deposits. The remaining areas which were not included in the current classification consist of bedrock outcrops and rock walls. 2.3. Geophysical investigations 2.3.1. GPR The use of GPR for subsurface investigations has increased during recent years. The most common applications in alpine geomorphology involve permafrost detection (Angelopoulos et al., 2013, Stiegler et al., 2014, Onaca et al., 2015) and internal structure characterization of talus slopes (Sass, 2006, 2007, Sass and Krautblatter, 2007, Onaca et al., 2016). The technique is based on transmitting high frequency electromagnetic (EM) pulses into the ground (Reynolds, 1997, Hauck and Kneisel, 2008, Jol, 2009). When the transmitted signal encounters a single object or a continuous contact between two layers of different relative dielectric constant, the signal changes its path, thus part of it is reflected back to the receiver and part of it is redirected further in the substratum (Telford et al., 1990, Bristow and Jol, 2003, Milsom, 2003). In fact, this technique reveals the pulse signal travel time from the transmitter to the encountered object and back to the receiver. Thus, by knowing the velocity of the EM signal, the two-way traveltime (m/ns) can be converted to depth (m) of the investigated environment (Kearey et al., 2002, Milsom, 2003). A total of 64 GPR profiles (Fig. 3), ranging between 60 and 300 m in length, were performed in the summers of 2013, 2014 and 2015. The investigations were carried out using a RAMAC GPR system from MalåGeoSciences, equipped with a 50 MHz center frequency rough terrain antenna (RTA). The survey design was based on the previously determined geomorphological context, the large number of profiles offering a complete picture regarding the internal structure of individual sediment storage landforms. The continuous measurement technique was applied during data acquisition, with a sampling interval of 0.4 s, using a sample frequency of 500 MHz, while the auto-stacking option provided by the manufacturer was used for trace stacking. The use of compact RTA antennas did not allow for Common Midpoint (CMP) or Wide Angle Reflection and Refraction (WARR) measurements, thus a mean value of 0.10 m/ns was used for the depth conversion of radar signal (Sass and Wollny, 2001, Otto, 2006, Sass, 2007, Sass and Krautblatter, 2007). Processing of GPR data was performed using Reflexw 6.0 dedicated software. The processing sequence applied was based on previous investigations in similar environments (Degenhardt, 2009, Onaca et al., 2015). Thus, the processing sequence involved several steps: (i) running average filter for noise reduction, (ii) dewow filter for signal

saturation, (iii) energy decay gain to compensate for rapid attenuation of radar signal with depth, (iv) 0 time correction for first time arrival correction, (vi) background removal for horizontal de-striping, (vii) bandpass frequency filter to remove artificial traces and (viii) topographic correction for an accurate interpretation of the resulting radargrams. 2.3.2. ERT It is well known that the GPR investigation technique offers a higher data acquisition rate and a higher resolution than the ERT method and that a combination of at least two geophysical methods is recommended for a good interpretation of subsurface conditions (Otto and Sass, 2006, Sass, 2006). Based on the above statements the first was used as an exhaustive investigation method of the entire area, whereas the latter was utilized to compare bedrock depth at five sites, through parallel profiling (Fig. 3). The obtained results were evaluated in order to determine the overall accuracy of the geophysical investigations applied in detecting the talus body - bedrock contact. Three ERT profiles, previously conducted by Onaca et al. (2013) on the surface of the Pietroasa rock glacier, were also used to generate the model of sediment thickness distribution. The ERT investigation method relies on measured differences between voltage intensity transmitted towards the substratum. Based on the obtained intensity of the direct current injected and on the geometry of the four electrodes the resulting apparent resistivity can be determined (Hauck and Kneisel, 2008). The geoelectrical profiles were conducted using a GeoTom MK8E1000 high-resolution multielectrode system in the summer of 2014. All the profiles were performed using the Werner electrode array, with an electrode spacing of 4 m and a total length of 192 m, allowing a maximum penetration depth of 30 m. Using appropriate tomographic inversion schemes for data processing, true resistivity was determined (Degroot-Hedlin and Constable, 1990) by applying a nonlinear robust least-squares inversion technique in Res2DINV software (Loke and Barker, 1996).

Fig. 3. Location ERT and GPR profiles used in the cross validation process.

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Fig. 4. Land surface classification of the Doamnei Valley.

2.4. Quantification of sediment volume

2.5. Determination of denudation rates and mass transfer

The sediment quantification was based on a point feature dataset, using several sources as input for bedrock surface interpolation. The first step consisted in integrating the geophysically derived bedrock depths. In the case of the GPR data, bedrock depth was manually determined based on EM signal amplitudes, at a 10 m interval, whereas in the case of the ERT data in order to determine the apparent resistivity of the underlying bedrock several profiles were conducted having bedrock outcrops or rock walls as starting point (Otto, 2006). In the second phase the DGPS derived bedrock outcrops were integrated, along with information regarding superficial deposits covering the main valley (subsystem II) slopes. The latter were determined based on in situ observation (gully erosion on the valley slopes, bedrock outcrops, digging), thus a mean overall thickness of 0.5 m was found to be representative. Finally, the local hydrological network, which carves its way on the bedrock surface, as well as the surface of the rock walls, located within the hanging valleys, were included within the sediment thickness model as constraining factors. The interpolation of sediment thickness was computed using the TopoToRaster function implemented in ArcGIS 10 software. The current interpolation method was chosen because it offers both the possibility to generate a continuous surface based on both point and vector data, as well as for allowing the use of constraint factors. It relies on an iterative finite difference interpolation technique, being optimized to have the computational efficiency of local interpolation methods, as Inverse Distance Weighted (IDW) without affecting the surface continuity of global interpolation methods, as Kriging and Spline (Childs, 2004). Sediment volumes were calculated based on the result of the interpolation algorithm and the real surface areas in GIS, on a pixel basis analysis. In order to determine the overall degree of accuracy of the model a cross-validation was applied, thus the initial point cloud of 1005 points was divided in two subsets, 80% of the data being used for the final interpolation, while 20% was utilized for the validation of the model. The difference between measured and predicted root mean square (RMS) error values along with the results of the cross-validation between GPR and ERT data served as a basis to determine the overall degree of accuracy of the final model.

The quantification of denudation rates (DR) was based on previously determined sediment volumes, using the following equation (Otto et al., 2009): DR ¼ SV

Pb P s Ad T

ð1Þ

where: SV represents sediment volume, expressed as km3, Pb and Ps are the dry bulk density of bedrock and sediment, expressed as g/cm3, Ad defines the denudation area, expressed as km2, while the time period is termed T, expressed in years (y). According to similar studies (Clark, 1966, Otto et al., 2009, Norton et al., 2010, Müller et al., 2014) a mean value of 2.7 g/cm3 was considered optimum for the quartzitic-schists and dolomites bedrock density. There are several factors determining sediment density, among which the most important are the consolidation processes of landform types. Glacial and fluvio-torrential deposits will have higher density values, while talus deposits, composed mainly of loose deposits, will have lower values. Thus, based on sediment density values ranging between 1.5 and 2.6 g/cm3, derived in similar

Table 1 Landform distribution and mean sediment thickness within the Doamnei Valley. Landform type

Nr. Surface area (km2)

% of total area

Mean surface (ha)

Elevation (m) Min

Max

TS TC MD RG FTD SD Total Other: BD Total

33 21 19 1 9 – 79

0.77 0.30 0.28 0.09 0.10 1.74 3.28

21 8 8 2 3 48 90 (42a)

2.32 1.45 1.15 9.10 0.88 –

1555 1549 1539 2074 1520 1521

2317 2309 2186 2221 2198 2441

0.34 3.62

10 100

a

Without superficial deposits.

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Fig. 5. Thickness of sediment storage landforms derived from GPR measurements. (TS – talus slopes, TC – talus cones, MD – moraine deposits, FTD – fluvio–torrential deposits).

environments (Einsele, 2000, Hinderer, 2001, Sass and Wollny, 2001, Embleton-Hamann and Slaymaker, 2006, Schrott et al., 2006, Morche et al., 2008, Beylich et al., 2009, Otto et al., 2009, Krautblatter et al., 2012), as well as on the fact that the current study focuses on quantifying different genetic types of sediment, a mean value of 2 g/cm3 was applied as mean sediment density within the Doamnei Valley. Denudation rates were calculated both as overall values (for the entire area and the two subsystems) as well as individual landform values, for landforms with clearly distinguishable source areas (talus sheets and cones).

In a previous work (Kuhlemann et al., 2013) the exposure age of two moraines located at 1670 and 2065 m in the Doamnei Valley was calculated using 10Be measurements. The analyzed samples yielded exposure ages of 13.1 and 13 ka, despite that one of the investigated boulders was located within the Căldărușa cu Iarbă hanging cirque and the other one 400 m downslope near the talveg of the main valley. Therefore, a mean value of 13 ka was applied for the entire area. In order to assess the amount of sediment that is remobilized within the investigated area the total mass transfer (MT) depicted as the

Fig. 6. Radargram of a talus cone from the lower sector of the Doamnei Valley depicting the bedrock – talus interface.

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Fig. 7. ERT profile performed near the Doamnei Lake.

volume of material in tons per area and time (t/km2/y) was determined based on the following equation:

MT ¼ SV

Pb Ad T

ð2Þ

where: SV represents sediment volume, expressed as km3, Pb the dry bulk density of bedrock, expressed as g/cm3, Ad defines the denudation area, expressed as km2 and the time period is termed T, expressed in years (y). The term mass transfer is similar to the sediment yield (SY) of a given catchment, but while the SY is regarded as an indicator of erosion and sediment delivery, describing the amount of sediment that is discharged from a given drainage basin (Schiefer et al., 2001) mass transfer describes the amount of material that has been remobilized within a given timespan, but has not left the denudation area (Otto, 2006).

3. Results 3.1. Spatial distribution of sediment storage landforms The results of the geomorphological mapping based on field investigations and remote sensing data are depicted in Fig. 4. The dominant landforms in the Doamnei Valley are talus sheets followed by talus cones, moraines and fluvio–torrential deposits, whereas the Pietroasa rock glacier occupies almost the entire floor of the Căldarea Pietroasă hanging glacial cirque. As the main valley has a rather uniform N–S orientation, slope deposits are developed along the main axis, with talus sheets better represented on the east facing slopes, whereas talus cones are more common on the west facing ones. Moraines are concentrated mainly in the median part of the valley, next to the Doamnei Lake. In total, 79 sediment storage landforms were identified, covering about 42% of the investigated area, whereas the remaining parts were considered superficial deposits (48%), solid rock walls (7%) and bedrock outcrops (3%) (Table 1). Based on the topological relationship between the existing landforms several downslope successions of landform types or toposequences can be distinguished. The most frequently observed toposequence type is the coupling between rock walls and underlying slope deposits (talus sheets and cones). Other toposequences found within the investigated area are: rock walls – slope deposits – rock glacier, rock walls – slope deposits – moraine deposits and rock walls – slope deposits – fluvio – torrential deposits.

3.2. Sediment thickness derived from geophysical investigation The GPR method proved to be an efficient solution for detecting bedrock contact within the complex topography of the investigated area. The bedrock boundary was clearly identified via a two case scenario: (i) as a sharp continuous surface at the base of the investigated deposits or (ii) as a specific fading of reflections due to a low dielectric contrast between the talus deposits and the underlying bedrock (Sass, 2007). Bedrock depths range from under 1 m on steep slopes and near bedrock outcrops to more than 15 m in the median part of the Doamnei Valley, where a former glacial basin was filled by fluvio–torrential deposits, whereas mean sediment thickness values range between 3.3 and 8.8 m (Fig. 5). In order to illustrate bedrock detection using the GPR method, as a basis for sediment thickness evaluation, a profile is presented in detail (Fig. 6). Fig. 6 reveals the results of a longitudinal profile conducted on a talus cone within the lower sector of the Doamnei Valley. The 160 m long profile has a W–E general orientation ranging between 1653 and 1550 m. The talus – bedrock interface is clearly identified as a sharp continuous boundary at the base of the debris body (Otto, 2006). The bedrock depth varies from 1 m, in the upper part, to over 9 m at 100 m on horizontal distance. Near the lower end of the profile sediment thickness decreases to less than 5 m. The internal structure of the talus body reveals a series of internal reflections stretching over the entire length of the radargram. This dense pattern of mostly parallel reflections is thought to reveal an alteration of fine grained and coarse grained deposits (Otto and Sass, 2006, Sass, 2006, Stiegler et al., 2014). Five two–dimensional electrical resistivity soundings were conducted in the upper part of the Doamnei Valley (Fig. 3) on talus deposits, moraines and fluvio–torrential deposits. Due to the specific physical characteristics of the investigated area, consisting of heterogeneous

Table 2 Comparison between the two geophysical methods applied (ERT vs GPR). Name of ERT/GPR

Landform type

Mean thickness (m) ERT/GPR

Mean difference (m)

ERT 1 ERT 2 ERT 3 ERT 4 ERT 5

TS TC MD MD MD

7.5 10.7 8.2 12.7 5.3

1.2 1 0.8 1 0.8

GPR 35 GPR 43 GPR 7 GPR 50 GPR 52

8.7 9.7 9 13.7 4.5

TS – talus slope, TC– talus cone, MD – moraine deposits.

A.C. Ardelean et al. / Science of the Total Environment 599–600 (2017) 1756–1767 Table 3 Sediment volumes and thickness of different landform types within the two subsystems. Subsystems Area (km2)

% of total area

Sediment volume (106 m3)

% of total area

20% error (106 m3)

Thickness (m) Min Mean Max

Subsystem I TS TC MD RG FTD SD

0.19 0.10 0.04 0.09 0.02 0.09

23.25 11.97 4.49 11.11 2.09 11.45

1.19 0.45 0.76 1.01 0.02 0.01

34.54 13.05 22.02 29.24 0.73 0.42

0.24 0.09 0.15 0.01 0.01 –

0.9 0.5 1.0 3.3 0.3 0.0

4.7 6.2 5.0 13.4 2.0 0.3

14.9 17.8 16.8 28.4 9.2 2.1

Subsystem II TS TC MD FTD SD

0.58 0.21 0.24 0.08 1.64

20.64 7.47 8.54 2.85 58.36

1.57 0.54 0.81 0.09 0.63

43.02 14.72 22.39 2.59 17.28

0.31 0.11 0.16 0.02 0.13

0.4 0.3 0.5 0.0 0.0

3.1 3.2 4.2 2.5 0.5

10.2 13.2 15.8 14.3 6.0

sediment deposits and the underlying crystalline bedrock, high resistivity contrasts allowed for an accurate identification of the sediment deposit – bedrock contact. Mean sediment thickness values range between 5 and 12 m. In the case of shallow deposits located near bedrock outcrops sediment thickness is less than 1 m, while the maximum depth of over 16 m is represented by lake infilling. The resulting ERT profile conducted on the slopes near the Doamnei Lake is displayed in Fig. 7. The tomogram reveals resistivity values ranging between 1 and 15 kΩm. At a horizontal distance of 30 to 120 m a high resistivity upper layer, with values between 7 and 13 kΩm, can be observed. This layer has a variable thickness of 4 to 12 m corresponding to a mixture of dry, porous, fine sediments, cobbles and small

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decametric boulders (Scapozza et al., 2011), representing probable moraine deposits. On the downslope section of the profile, between 120 and 160 m, the resistivity values drop to less than 3 kΩm, confirming the in situ observations of glacial rock basins silting. Resistivity values of the uppermost layer increase considerably in the lower part exceeding 12 kΩm corresponding again to moraines deposits. At greater depths the tomogram reveals a sharp decrease in resistivity over its entire length, interpreted as the bedrock interface (Sass, 2007, Siewert et al., 2012). Table 2 reveals the results of the cross-validation between the GPR and ERT profiles. The bedrock interface was successfully identified in all the profiles conducted for comparison. The mean difference in sediment thickness ranges between 0.8 and 1.2 m, leading to a mean overall difference in bedrock detection of 0.96 m, included in the determination of overall degree of accuracy of the final sediment thickness model. 3.3. Quantification of sediment volumes 3.3.1. Sediment distribution and thickness From the total area of subsystem I (0.81 km2) nearly 78% is covered by debris. Sediment thickness as depicted by the interpolated model reveals a series of variations between the sediment storage landforms (Table 3). Slope deposits exhibit a sediment thickness that ranges from less than 1 m, near the contact with the source areas to 15 m (for talus slopes) and 18 m (for talus cones) in their downslope part (Fig. 8). The difference in maximum thickness between talus sheets and cones is regarded as a testimony of their formative processes. Channeling of debris input from the source area above acts like a limiting factor confining the accumulation area, increasing thus the overall debris thickness of talus cones (Otto et al., 2009). Moraine deposits reveal a mean overall thickness of 5 m, while the maximum values

Fig. 8. Sediment quantification within the Doamnei valley; A: Data point cloud utilized in the generation of the interpolated model; B: Sediment thickness in the investigated area as depicted by the resulting model.

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Table 4 Sediment storage volume and distribution of the Doamnei Valley subsystems. Subsystem

Area (km2)

% of total area

Sediment volume (106 m3)

% of total volume

Sediment volume/area (106m3/km2)

20% error (106 m3)

Thickness (m) Min

Mean

Max

I II Total

0.81 2.81 3.62

22.37 77.63 100

3.44 3.64 7.08

48.58 51.42 100

4.25 1.30 1.96

0.68 0.60 1.42

0.25 0.15 0.15

5.28 4.49 4.20

28.39 15.81 28.39

reach 17 m. The largest sediment thickness values are calculated for the Pietroasa rock glacier, with a maximum depth of over 20 m. The total sediment volume stored within subsystem I is 3.44 ± 0.68 106 m3 (Table 4). Almost 50% of the total sediment volume is stored within slope deposits, followed by the Pietroasa rock glacier with 29%. Moraine deposits hold over 20% of the total amount of sediments, whereas fluvio–torrential and superficial deposits represent only 2% of the total sediment cover (Table 3). Subsystem II occupies a total area of 2.81 km, of which 40% is covered by sediment storage landforms. Despite its larger area the overall sediment thickness values are lower compared to subsystem I (Table 3). According to the interpolated model, debris depths range from less than 1 m to almost 16 m. The largest thickness values are calculated for moraine deposits with a maximum of over 15 m, followed by fluvio-torrential deposits with maximum values exceeding 14 m, representing lake silting. Talus deposits reveal shallower depths compared to subsystem I, with values ranging between under 0.5 m and over 13 m. The mean sediment thickness of superficial deposits is 0.46 m while the highest value is 6 m. The overall sediment volume stored within subsystem II is calculated to be 3.64 ± 0.60 106 m3 (Table 4). According to the model, over 43% of the total sediment volume is stored within talus slopes, followed by moraine deposits with over 22%. Due to their vast area, superficial deposits accumulate up to 17% of the sediments of subsystem II, whereas talus cones store approximately 15% of the total volume (Table 3). Based on the sediment thickness model the total sediment volume stored within the Doamnei Valley is 7.08 ± 1.42 106 m3. Subsystem I stores 48.58% of the total sediment volume, despite covering 22% of the investigated area, while subsystem II stores 51% of the sediment volume. The overall mean sediment thickness of the Doamnei Valley is 4.2 m, with a mean sediment thickness of 5.28 m for subsystem I and 4.45 m for subsystem II (Table 4). 3.4. Postglacial denudation and mass transfer

input) talus cones exhibit higher mean sediment depths as well as a greater maximum depth (17.8 m) than talus sheets in both subsystems (Table 3). All the individual sediment storage landforms exhibit greater thicknesses within subsystem I compared to their counterpart situated in subsystem II (Table 3). Similar results were reported for the Turtmann Valley (Swiss Alps), where Otto et al. (2009) concluded that over 60% of the sediment deposited since deglaciation is stored within the hanging valleys. The considerably higher values of sediment volume per area of subsystem I (Table 4), can be explained by: (i) the presence of one rock glacier on the floor of Pietroasa hanging cirque, being well known that rock glaciers store large amounts of sediment within confined areas (Barsch, 1996); (ii) the hanging cirques located at higher elevation are subject to faster rates of physical weathering generating an increase in sediment input and (iii) reduced quantities of material output determined by their typical glacially shaped topography. The latter is also due to the fact that the hanging cirques subsystem is decoupled from the main valley sediment flux (if considering coarse sediment transfer) due to specific local topographic conditions, thus the sediment transfer between the hanging cirques and the main valley is mostly limited to fine grained material, controlled by fluvial discharge. Regarding the relatively large sediment thickness values of the superficial deposits located in subsystem II (Table 3) (0.46 m mean depth and a maximum of 6 m) this overestimation is specific to single, isolated locations, and is due to an over deepening of the interpolation algorithm where superficial deposits are connected to sediment storage landforms of greater thickness. 4.2. Interpretation of denudation rates and sediment flux Because no data is currently available on sediment budget derived denudation rates for the Carpathian Mountains range, the data obtained here were compared with mean annual denudation values from the Alps, which vary between 0.03–6.2 mm/a (Table 6). Despite the fact that all studies chosen for comparison rely on the conversion of

The total mean annual mass transfer in the Doamnei Valley was estimated for the postglacial period of 13 ka (Kuhlemann et al., 2013) using Eq. (2) as 406.2 ± 31.6 t/km2/y (Fig. 9). The mass transfer is double in subsystem I with a corresponding volume of 882.1 ± 153.8 t/km2/y, whereas in the case of subsystem II mass transfer is calculated to be 269.0 ± 50.3 t/km2/y. By applying Eq. (1) the sediment budget approach offers the possibility to determine mean annual denudation rates (MADR) for the investigated area. The calculation of denudation rates is dependent on two important factors: (i) the denudation area and (ii) the time span taken into consideration. The MADR for the entire Doamnei valley is 0.20 ± 0.04 mm/y (Table 5). Denudation values are considerably higher in subsystem I (0.44 mm/y). Regarding individual sediment storage landforms the greatest MADR correspond to talus cones. 4. Discussion 4.1. Sediment storage distribution Sediment thickness and volume distribution were quantified for the alpine sector of the Doamnei Valley, Southern Carpathians. As a direct consequence of their formative processes (channeling of sediment

Fig. 9. Mass transfer within the alpine sector of the Doamnei valley, TS – talus slopes, TC – talus cones, MD – moraine deposits, RG – rock glacier, FTD – fluvio-torrential deposits.

A.C. Ardelean et al. / Science of the Total Environment 599–600 (2017) 1756–1767 Table 5 Mean annual denudation rates within the Doamnei Valley.

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Table 7 Denudation rates for individual sediment storage landform types (various time periods).

Location

Source area (km2)

Total volume (106 m3)

M.A.D.R. (mm/y)

Cirque-valley sector Hanging cirques sector Doamnei Valley (total) Talus sheets Talus cones Rock glacier

2.81 0.81 3.62 1.73 0.69 0.62

3.64 3.44 7.08 2.01 0.71 1.00

0.13 0.44 0.20 0.21 0.22 0.17

M.A.D.R. – mean annual denudation rate.

sediment budget derived volumes into denudation rates they exhibit a large scatter in denudation values which could be put on account of the various spatial and temporal scales of analysis, variable environmental characteristics, as well as on a change in the overall influence of individual process domains within the investigated sites (Caine, 2004). The mean annual denudation rate of the Doamnei Valley (0.20 ± 0.04 mm/y), lies at the lower end of the published data. Nevertheless, it is thought that the widespread construction of dams in Swiss rivers act as large scale sediment traps, playing thus a major impact on present-day derived denudation rates (Otto et al., 2009). With respect to denudation rates for individual sediment storage landform types, within the study area, the average values range between 0.1–0.61 mm/a for talus sheets and 0.1–0.75 mm/a for talus cones (Table 7). MADR of talus sheets reveal a good correlation with values calculated by Sass and Wollny (2001) in the Bavarian Alps. The minimum and maximum values for the same landforms fit well with the values determined by Hoffmann and Schrott (2002) for the Reintal Valley and are well above the rates presented by Rapp (1960) for the Kärkevagge catchment in Sweden. Similar to mean annual denudation rates derived for entire catchments, individual landform rates are also strongly dependent on the factors involved in the quantification method. Thus one should be cautious when comparing values from different study sites, where various time spans and especially different quantification methods applied, could lead to potential overestimations of postglacial sediment storage and consequently denudation rates. The comparison of sediment volumes per process domain is strongly dependent on both the extent of the investigated catchments and the local distribution of sediment storage landforms (Otto, 2006). As no data on sediment flux is available for the Carpathian Mountains range the comparison was again carried out using similar studies conducted on Alpine drainage basins, ranging between 1 and 27 km2 (Rapp, 1960, Caine, 1986, Schrott and Adams, 2002, Schrott et al., 2003, Götz et al., 2013). Within the Doamnei Valley talus specific deposits (talus sheets and cones) play the most important role within the local sediment flux system (Fig. 9). These findings are consistent with the aforementioned studies, where it was outlined that talus related sediment storage act as the main agent within the local sediment flux system, situation which is in good agreement with the paraglacial sediment model proposed by Church and Slaymaker (1989).

Location

M.A.D.R. (mm/an)

Reference

Min

Mean Max

Talus sheets Doamnei Valley (Romania) Bavarian Alps (Germany) Reintal Valley (German Alps) Turtmann Valley (Swiss Alps) Kärkevagge (Sweden)

0.1 0.06 0.1 0.2 0.04

0.21 0.28 – 0.7 –

0.61 0.73 1.0 1.3 0.15

– Sass and Wollny (2001) Hoffmann and Schrott (2002) Otto (2006) Rapp (1960)

Talus cones Doamnei Valley (Romania) Turtmann Valley (Swiss Alps) Lechtaler Alps (Austria) Nanga Parbat (Pakistan)

0.1 0.6 0.5 0.3

0.22 2.2 – 2.5

0.75 3.1 0.8 7.0

– Otto (2006) Sass (2006) Shroder Jr et al. (1999)

Rock glaciers Doamnei Valley (Romania) Swiss Alps (Switzerland) South Tirol (Italy) Turtmann Valley (Swiss Alps)

– 0.5 – 0.12

0.17 2.5 0.5 0.62

– 4.6 – 1.8

– Barsch (1977) Höllermann (1983) Otto (2006)

M.A.D.R. – mean annual denudation rate.

The total mean annual mass transfer within the Doamnei Valley, estimated based on current sediment storage landform volumes over a period of 13 ka is 406.2 ± 31.6 t/km2/y (Fig. 9). The estimated value for reworked sediments is considerably lower than the similar values reported for the Alps, where Otto (2006) calculated mean annual transfer values between 1509 ± 755–1960 ± 998 t/km2/y for the Turtmann Valley, while Hinderer (2001) determined a mean annual sediment yield of 2370 t/km2/y since the Late Glacial Maximum for the Rhone River. In contrast, the values calculated within the current study exhibit important similarities to those reported by Vezzoli (2004) for the western Italian Alps, where although the overall values determined for the 21 small catchments taken into consideration ranged between 19– 1926 t/km2/y, values between 200–600 t/km2/y were determined for six alpine catchments. 5. Conclusions The current study offer the first approach in determining sediment volume, denudation rates and sediment flux within the alpine environment of the Romanian Carpathians, namely the Doamnei Valley (3.62 km2), Făgăraș Mountains. A combined approach consisting of high resolution geomorphological mapping (aerial images and DEM), detailed subsurface data obtained via geophysical investigations (GPR and ERT) and advanced modeling techniques were used in order to achieve the overall aim of the current study. A total of 79 sediment storage landforms were identified, covering about 42% of the investigated area, whereas the remaining parts were considered superficial deposits (48%), solid rock walls (7%) and bedrock

Table 6 Published denudation rates of alpine catchments based on the sediment budget approach. Location

M.A.D.R.(mm/a)

Time period

Reference

Doamnei Valley (Romania) Bündner Rhine (Switzerland) Alps Alps Langental (Italy) Rhone/Port de Scex (Switzerland) Reintal (Germany) Turtmann Valley (Swiss Alps) Hohe Tauern (Swiss Alps)

0.20 0.58 6.2 0.13 1.1 0.15 0.3 0.62–1.87 0.03–0.93

13 (ka) Quaternary Late and Postglacial Present Post-glacial Present day Post-glacial 10 (ka) Post-glacial

– Jäckli (1957) Hinderer (2001) Hinderer (2001) Schrott and Adams (2002) Schlunegger and Hinderer (2003) Hufschmidt (2002) Otto et al. (2009) Götz et al. (2013)

M.A.D.R. – mean annual denudation rate.

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outcrops (3%). The overall sediment volume of the investigated area was calculated to be 7.08 ± 1.42 106 m3, with a corresponding mean sediment thickness of 4.2 m. From the total sediment volume 48.58% is stored within subsystem I, which has an overall surface three times smaller than subsystem II. Sediment volume within the sediment storage landforms of subsystem I is dominated by slope deposits (50%), the Pietroasa rock glacier (29%) and moraine deposits (20%). The situation is similar in subsystem II were slope deposits sum up over 58% of the total sediment, followed by moraine deposits (22%) and superficial deposits (17%). A mean annual denudation rate of 0.20 mm/y ± 0.04 mm/y as well as a total mean annual sediment transfer value of 406.2 ± 31.6 t/km2/y were determined for the investigated area. The current study allowed for the first estimation of denudation rates within the Romanian Carpathians, values which proved to be in good agreement with previous results from other alpine environments. Therefore, this approach stands as a first step towards a better understanding of the magnitude of postglacial landform evolution within Romania, offering a prerequisite towards modeling postglacial evolution of alpine areas at a larger scale (e.g. Southern Carpathian Mountains) by extending the current approach to other small scale alpine catchments. Furthermore, the relation between sediment thickness and the main topographic attributes (e.g., elevation, slope, curvature, aspect etc.) within different types of alpine catchments will be analyzed in the future.

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