Suspended sediments impact stream water quality by increasing the turbidity and acting as a vector for strongly sorbing pollutants. Understanding their sources is of great importance to developing appropriate river management strategies. In this study, we present an integrated sediment transport model composed of a catchment-scale hydrological model to predict river discharge, a river-hydraulics model to obtain shear stresses in the channel, a sediment-generating model, and a river sediment-transport model. We use this framework to investigate the sediment contributions from catchment and in-stream processes in the Ammer catchment close to Tübingen in southwestern Germany. The model is calibrated to stream flow and suspended-sediment concentrations. We use the monthly mean suspended-sediment load to analyze seasonal variations of different processes. The contributions of catchment and in-stream processes to the total loads are demonstrated by model simulations under different flow conditions. The evaluation of shear stresses by the river-hydraulics model allows the identification of hotspots and hot moments of bed erosion for the main stem of the Ammer River. The results suggest that the contributions of suspended-sediment loads from urban areas and in-stream processes are higher in the summer months, while deposition has small variations with a slight increase in summer months. The sediment input from agricultural land and urban areas as well as bed and bank erosion increase with an increase in flow rates. Bed and bank erosion are negligible when flow is smaller than the corresponding thresholds of 1.5 and 2.5 times the mean discharge, respectively. The bed-erosion rate is higher during the summer months and varies along the main stem. Over the simulated time period, net sediment trapping is observed in the Ammer River. The present work is the basis to study particle-facilitated transport of pollutants in the system, helping to understand the fate and transport of sediments and sediment-bound pollutants.
Suspended sediments are comprised of fine particulate matter (Bilotta and Brazier, 2008), which is an important component of the aquatic environment (Grabowski et al., 2011). Sediment transport plays significant roles in geomorphology, e.g., floodplain formation (Kaase and Kupfer, 2016), and transport of nutrients, such as particulate phosphorus and nitrogen (Haygarth et al., 2006; Slaets et al., 2014; Scanlon et al., 2004). Fine sediments are important for creating habitats for aquatic organisms (Amalfitano et al., 2017; Zhang et al., 2016). Conversely, high suspended-sediment concentrations can have negative impacts on water quality, especially, by facilitating transport of sediment-associated contaminants, such as heavy metals (Mukherjee, 2014; Peraza-Castro et al., 2016; Quinton and Catt, 2007) and hydrophobic organic pollutants such as polycyclic aromatic hydrocarbons (PAHs) (Rügner et al., 2014; Schwientek et al., 2013b; Dong et al., 2015, 2016), polychlorinated biphenyls (PCBs), and other persistent organic pollutants (Meyer and Wania, 2008; Quesada et al., 2014). Without understanding the transport of particulate matter, stream transport of strongly sorbing pollutants cannot be understood.
An efficient approach to estimate suspended-sediment loads is by rating curves, relating concentrations of suspended sediments to discharge. By this empirical approach, however, we cannot gain any information on the sources of suspended sediments, which is important for the assessment of particle-bound pollutants. Therefore, a model considering the various processes leading to the transport of suspended sediments in streams is needed. Numerous sediment-transport models have been developed during the past decades, including empirical and physically based models. Commonly used empirical models include the Universal Soil Loss Equation (USLE) (Wischmeier and Smith, 1978) and the Sediment Delivery Distributed (SEDD) model (Ferro and Porto, 2000). The USLE was designed to estimate soil loss on the plot scale. It is incapable to deal with heterogeneities along the transport pathways of soil particles and thus cannot be applied to entire subcatchments. The SEDD model considers morphological effects at annual and event scales. The two models cannot distinguish different in-stream processes. Among the models simulating physical processes, the Water Erosion Prediction Project (WEPP) (Flanagan and Nearing, 1995), the EUROpean Soil Erosion Model (EUROSEM) (Morgan et al., 1998), the Soil and Water Assessment Tool (SWAT) (Neitsch et al., 2011), the Storm Water Management Model (SWMM) (Rossman and Huber, 2016), the Hydrological Simulation Program Fortran (HSPF) model (Bicknell et al., 2001), and the Hydrologic Engineering Center's River Analysis System (HEC–RAS) (Brunner, 2016) are widely used. WEPP and EUROSEM are applied to simulate soil erosion from hillslopes on the timescale of single storm events. The two models do not have the capability of estimating urban particles. SWAT uses a modified USLE method to calculate soil erosion from catchments. SWMM aims at simulating runoff quantity and quality from primarily urban areas, including particle accumulation and wash-off in urban areas. HSPF considers pervious and impervious land surfaces. All of these models estimate sediment productions from the catchment and model the transport in the river channel with simplified descriptions of in-stream processes by simplifying the shape of cross sections. Various sediment-transport models for river channels exist that rely on detailed river hydraulics, particularly the bottom shear stress, which controls the onset of erosion and the transport capacity of a stream for a given grain diameter (Zhang and Yu, 2017; Siddiqui and Robert, 2010). HEC–RAS solves the full one-dimensional Saint Venant equation for any type of cross section, including cases with changes in the flow regime, which is beneficial to obtaining detailed information on river hydraulics.
In this study, we present a numerical modeling framework to understand the combined contributions from catchment and in-stream processes to suspended-sediment transport. The main objectives of this study were (i) to develop an integrated sediment-transport model taking sediment-generating processes (e.g., particle accumulation and particle wash-off), and river sediment-transport processes (e.g., bed erosion and bank erosion) into consideration, (ii) to understand annual load and seasonal variations of suspended sediments from different processes, (iii) to investigate how the contributions of suspended sediments from catchment and in-stream processes change under different flow conditions, and (iv) to identify hotspots and hot moments of bed erosion. The model is applied to a specific catchment introduced in the next section, implying that model components that control the behavior of suspended sediments in this catchment are given specific attention, whereas processes of less relevance are simplified in the model formulation. All model components are made available in the Supplement to facilitate modifications that may be needed when applying the framework to catchments with different controls.
We applied the integrated sediment transport model to the Ammer catchment,
located in southwestern Germany (Fig. 1). The River Ammer is a tributary to the
River Neckar within the Rhine basin. It covers approximately 130 km
With the exception of a small stripe at the northeastern boundary of the
study domain, highlighted by the forest land use in Fig. 1, the topography of
the catchment is only slightly hilly (with mean slope of 4.2
Based on the digital elevation model (DEM) of the Ammer catchment, we delineated 14 subcatchments using the watershed delineation tool of the Better Assessment Science Integrating point & Nonpoint Sources (BASINS) model (see Fig. 1). Table 1 shows the proportions of different land-use types and the areas of each subcatchment.
Location of the Ammer catchment and its subcatchments, rivers, and land uses. The numbers show identifiers of 14 subcatchments that are characterized in more detail in Table 1. Two red regular pentagons represent two WWTPs in the study domain. The red triangular indicates the gauge at the catchment outlet.
Properties of the Ammer subcatchments.
Hourly precipitation and air-temperature data are the driving forces of the hydrological model. We use hourly precipitation data of the weather station Herrenberg, operated by the German weather service DWD (CDC, 2017), whereas air temperatures are taken from the weather station Bondorf of the agrometeorological service Baden-Württemberg (BwAm, 2016). The generation and transport of sediments behave differently for different land uses and topography. We use the digital elevation model with 10 m resolution and land-use map of the state topographic service of Baden-Württemberg and Federal Agency for Cartography and Geodesy (BKG, 2009; LGRB, 2011; UBA, 2009). The river-hydraulics model requires bathymetric profiles of the River Ammer and its main tributaries. We use 230 profiles at 100 m spacing, obtained from the environmental protection agency of Baden-Württemberg (LUBW, 2010).
Only one gauging station is installed in the main channel of the Ammer River
at the outlet of the studied catchment in Pfäffingen (red triangle in
Fig. 1); here, hourly discharge and turbidity measurements are available,
which we used for model calibration and validation. The water levels and
turbidity data were measured by online probes (UIT GmbH, Dresden, Germany).
The hydrograph was converted to discharge time series by rating curves,
whereas the suspended sediment concentrations are derived from continuous
turbidity measurements (Rügner et al., 2013). The linear relationship
between suspended-sediment concentrations and turbidity with a conversion
factor of 2.02 (mg L
The simulation period covers the years 2013–2016. In this time, the maximum
discharge reflected an event with a 2–10-year return period according to the
long-time statistics of the gauging station (LUBW,
The integrated sediment-transport model consists of a catchment-scale hydrological model, a river-hydraulics model, a catchment sediment-generating model and a river sediment-transport model (Fig. 2). The catchment-scale hydrological model is used to estimate river discharge along the entire stream. The river-hydraulics model uses the discharge of the hydrological model and the river bathymetry to compute the river stage, cross-sectional area, velocity, and bottom shear stress, which are needed for the river-transport model. In this study we use HEC–RAS in quasi-steady-state mode. The catchment sediment-generating model is used for simulating particle accumulation in urban areas during dry weather periods, particle wash-off during storms, and erosion from rural areas during rain periods. The river sediment-transport model is used to simulate in-stream processes (advection, dispersion, and deposition, as well as bank and bed erosion). Wastewater treatment plants are treated as point inputs with constant discharge and sediment concentration during dry weather periods. Under low-flow conditions, when no soil erosion and urban particle wash-off occur and the suspended sediment concentrations in the streams are relatively small, we use a constant concentration to represent the sediment input under these conditions. Based on our prior knowledge of the Ammer catchment, soil erosion is very limited (the information supporting this statement will be discussed in Sect. 4.2), and thus a well-known approach and a simplified method are used to simulate particles from urban and rural areas, respectively. Mobilization of particles from different sources depends on different processes; e.g., input of urban particles depends on the build-up and wash-off processes and rural particles rely on soil erosion, whereas bed and bank erosion are substantially affected by river hydraulics. Considering these processes enables us to diagnose the importance of different sediment sources well.
Integrated sediment transport model, consisting of a catchment-scale hydrological model, a river-hydraulic model, a sediment-generating model, and a river sediment-transport model.
The catchment-scale hydrological model is based on the HBV model (Hydrologiska Byråns Vattenbalansavdelning) (Lindström et al., 1997). However, we have added a quick recharge component and an urban surface runoff component to explain the special behavior of discharge in the Ammer catchment (see Sect. 2.1). The main Ammer springs are fed by groundwater from the karstified middle-Triassic Muschelkalk formation. The measured hydrograph indicates a rapid increase of base flow in sporadic events. We explain this behavior with a model that contains three storages of water in the subsurface: soil moisture in the top soils, a subsurface storage in the deeper unsaturated zone, and groundwater in the karstic aquifer. In our conceptual model, we assume water storage in the deep unsaturated zone, which spills over when a threshold value is reached, causing quick groundwater recharge to occur that then leads to a rapid increase of base flow. An urban surface runoff component is used to obtain surface runoff depths in urban areas in order to simulate particle wash-off from urban land surface. Details of the hydrological model are given in Appendix A. The temporal resolution of the hydrological model is 1 h. We use the catchment-scale hydrological model to simulate discharge contributions from the 14 subcatchments shown in Fig. 1 (detailed information see Sect. 2.1).
In order to better understand in-stream processes, we feed the discharge data of the hydrological model into the river-hydraulics model HEC–RAS (Brunner, 2016), which solves the one-dimensional Saint Venant equations. The HEC–RAS model simulates hourly quasi-steady flow using the hourly discharge of the 14 subcatchments simulated by the hydrological model as change-of-discharge input. The locations where the discharge from 14 subcatchments enters into the main channel are set to the corresponding cross sections. The upstream boundary condition was set to time series of flow and the downstream one to normal depth. We have 258 measured cross sections and we used the built-in interpolation algorithm in HEC-RAS to obtain the additional cross sections, which results in totally 385 cross sections for the entire river network. The distances between computed cross sections range from 10 to 100 m depending on the changes of river bathymetry. The model requires river profiles in cross sections along the river channel and yields the water-filled cross-sectional area, the water depth, flow velocity, and shear stress, among other factors, as model output, which are needed in the river sediment-transport model. The detailed settings of HEC–RAS can be found in the Supplement.
The land use is classified into urban and rural areas as well as forested areas. Impervious surfaces such as roads and roofs are regarded as urban areas, while rural areas consist of pervious surfaces such as gardens, parks, and agricultural land. The sediment-generating processes are different for the two types of land use. Sediment generation in forested areas is considered to be negligible. The sediment-generating model is used to obtain hourly sediments of urban and rural particles from the 14 subcatchments.
We use the urban-area algorithm of SWMM, which performs well on particle build-up and wash-off for urban land use (Wicke et al., 2012; Gong et al., 2016), to describe sediment generation from urban areas. The corresponding processes are described below.
In contrast to urban areas, the supply of suspended sediments from rural
areas can be seen as “infinite” because they mainly originate from eroded
soils. Soil erosion is assumed to linearly depend on shear stress, provided
that the shear stress generated by surface runoff is larger than a critical
shear stress. The sediment generation from rural areas is based on the study
of Patil et al. (2012).
We consider two types of sediment: suspended sediment in the aqueous phase (mobile component) and bed sediment (immobile component). Figure 3 shows a schematic of the river sediment-transport model, which considers advection, dispersion, deposition, bank erosion, bed erosion, and lateral input of suspended sediments. We use this model to calculate the average concentration of the mobile component and the mass of the immobile component for every computation cell (formed by two cross sections) every hour.
In-stream processes of the river suspended-sediment transport
model considering deposition, bed erosion, bank erosion, and input from the
catchment. XS1 and XS2 are the two cross sections bounding a cell in a
finite-volume scheme.
This model component requires the sediment concentrations in the lateral
inputs (tributaries and WWTPs) as well as in the Ammer spring as boundary
conditions. The lateral inputs are computed by the sediment-generating model.
For the sediment input by the Ammer spring, we consider the turbidity of
Deposition The deposition rate Bed erosion We consider two types of bed erosion, namely particle erosion and mass
erosion, which correspond to two thresholds of the bottom shear stress. The
bed erosion rate Bank erosion In our model, the bank erosion rate
For the estimation of parameters, we used the well-known Nash–Sutcliffe
efficiency (NSE) as model performance criterion:
The hydrological model was applied to 14 subcatchments. Each subcatchment
has three types of land use: agricultural areas, forest, and urban areas. We
used daily average discharge data of 2013–2014 and 2015–2016 for
calibration and validation, respectively. We generated 1000 realizations of
the 14 parameters by Latin hypercube sampling (LHS) and calculated the
corresponding NSE value for each parameter set. If NSE was
For the calibration and validation of the sediment-generating and the river sediment-transport models, we performed a literature survey to identify a reference range of each parameter. We performed a manual calibration of the corresponding parameters within the given range, fitting the modeled and measured suspended sediment concentrations at the river gauge. Subsequently, we used the identified parameter set as base values in a local sensitivity analysis, the details of which are given in Table S1 of the Supplement. Within the given parameter variations, the manually calibrated parameter sets were confirmed as optimal. The parameters of the sediment-generating model and the river sediment-transport models are listed in Tables 2 and 3, respectively.
Parameters of the sediment-generating model.
Parameters of the river sediment-transport model.
The best-fit parameter set of the hydrological model resulted in NSE values
of 0.63 and 0.59 for calibration and validation, respectively. Figure 4 shows
the measured and simulated hydrographs for the calibration and validation
periods with 90 % confidence intervals. It can be seen that the discharge
was reproduced quite well, both in the general trend and the dynamics. The
measured discharge data almost all fall within the 90 % confidence
interval of the simulation. The NSE value for high flows (greater than the
mean discharge, 1 m
Calibration (left, year 2013–2014) and validation (right, year 2015–2016) of hydrological model,
Figure 5 depicts measured suspended-sediment concentrations and the simulation results of the sediment-transport model during the calibration (year 2014) and validation (year 2016) periods. The corresponding NSE values are 0.46 and 0.32, respectively, which indicates an acceptable fit, albeit not as good as for the hydrograph. The integrated sediment transport model can capture the dynamics of the suspended sediment concentrations. In particular, the model captures the concentration peaks well. However, two events, one in the calibration and the other in the validation period, were not well fitted. These are events which were also not captured by the hydrological model, occurring in the summer months and due to thunderstorms.
Modeled and measured suspended sediment concentrations used for calibration (year 2014) and validation (year 2016) of the sediment transport model. A data gap exists for the year 2015.
After calibration and validation, the model results can be used to analyze
the importance of different sediment sources. Figure 6 displays the modeled
annual suspended-sediment loads from catchment and in-stream processes for
the entire Ammer River network. The annual suspended-sediment load at the
gauge ranges between 410 and 550 t yr
In the Ammer catchment, urban particles (266–337 t yr
Annual suspended sediment loads from different processes.
Monthly mean suspended-sediment load from different processes,
calculated using the model results of 2014–2016.
The suspended sediments of the Ammer River are strongly contaminated by polycyclic aromatic hydrocarbons and other persistent organic pollutants (Schwientek et al., 2013b). Table S2 and Eqs. (S1)–(S7) of the Supplement present an end-member-mixing analysis indicating a fraction of rural particles amounting to only 3 %.
The state geological survey of the state of Baden-Württemberg has developed a soil-erosion risk map shown Fig. S1, putting most of Ammer catchment into the class of lowest soil-erosion risk. This is so because the surface runoff from agricultural areas is small due to a comparably flat topography. The same agency associates most of the catchment with deep infiltration as the main discharge mechanism.
Schwientek et al. (2013a) found a lacking connection between soils and streams
in the Ammer catchment. The catchment has a large water storage capacity due
to the karst and the slopes of this catchment are mild. During the simulation
period, the precipitation intensity was not large enough to exceed the
maximum infiltration rates or to reach storage capacity of the subsurface.
Compared with literature values of maximum infiltration rates (10–20 and 5–10 mm h
The comparably flat topography can be explained by the geological formation. The Muschelkalk limestone is a carbonate platform that is partially overlain by mudstones of the upper Triassic. Along the Ammer main stem, there is only a small stretch where the river is incised somewhat deeper into the limestone rock. The river lost its former headwater catchment in the early Pleistocene to river Nagold so that the currently existing small river has a too-wide valley given its discharge.
Relationship between simulated hourly mean flow and hourly
suspended-sediment loads from the catchment
As discussed above, we used a simplified approach to simulate the average sediment delivery from rural areas in our study because the contribution of rural areas to sediment delivery was so small. In particular, we did not distinguish between different crop types and seasons and estimated the average sediment load that reaches the streams instead. In other catchments, where the rural contributions to the sediment load are considerably higher, the description of soil erosion processes would require more differentiations.
To identify seasonal variations of suspended sediment loads originating from different processes, we used the model results of 2014–2016 to analyze the monthly mean suspended sediment loads from the urban areas, rural areas, the karst system, bed erosion, bank erosion, and deposition (Fig. 7). More suspended-sediment loads from urban areas and at the gauge can be observed in June and July (summer months). In summer months events with high rain intensity are more common than in winter months, which results in higher discharge peaks, more sediments generated in urban areas, and higher suspended-sediment loads at the gauge. Monthly suspended-sediment loads at the gauge have similar dynamics as the monthly urban particle contributions. The suspended-sediment load from the karst system is higher in winter months because the subsurface flow in the Ammer catchment is higher in winter months. Rural particles contribute to the overall particle flux only during a few months because annual precipitation and rainfall intensity were relatively small, so that surface runoff generated from rural areas was also low.
Simulated suspended sediment load from bed erosion, bank erosion, the karst system, rural areas, and urban areas (including suspended sediment from WWTPs) under different flow regimes, the suspended sediment loads are the mean values for the specific flow regimes.
In the model simulation period, the seasonal patterns of bed erosion and
bank erosion are obvious. High bed erosion and bank erosion occur from June
to August due to increased bed shear occurring during big events. The area
above the line of
Summary of suspended-sediment sources under different flow conditions.
The distribution of the annual mean deposition, bed erosion, net sediment trapping, net sediment erosion, and channel slope along the main channel of the Ammer River (flow direction from right to left). The blue and red dash–dotted lines highlight net sediment trapping and net erosion, respectively.
Figure 8 shows the relationship between hourly mean discharge and the simulated
hourly suspended sediment loads from the catchment, bed erosion, and bank
erosion. The hourly suspended-sediment load from the catchment monotonically
increases with increasing hourly mean discharge by a power-law relationship
(Fig. 8a), which is consistent with the particle wash-off rate being a
power-law function of discharge. Bed erosion requires that the bed shear
stress exceeds a critical value, so that bed erosion is almost 0 when hourly
mean flow is smaller than 1.5 m
Figure 9 shows the suspended sediment loads from in-stream (bed erosion and
bank erosion) and catchment processes (input from the karst system, urban areas,
and rural areas) under different flow regimes. The fractions of
suspended-sediment contributions from different processes change with flow
regimes. The contributions of in-stream processes are negligible in the flow
regime of discharge smaller than 5 m
Monthly mean bed erosion along the channel of the Ammer River upstream of the gauge (flow direction from right to left).
From above observations, we can see that the sources of suspended sediments differ under different flow conditions in the following way (Table 4):
The annual mean rates of bed erosion and deposition (mass per unit length per
year) along the main channel can be used to identify hotspots of bed erosion
and net sediment trapping (Fig. 10). The rates of deposition and bed erosion
vary substantially along the main stem, ranging from essentially zero to a
maximum of 8.6 and 8.0 kg m yr
Figure 11 shows monthly means of the bed erosion rates along the Ammer main stem, computed for the simulated years 2014 to 2016. Bed erosion is stronger in the summer months, especially in July, which is consistent with the monthly load of suspended sediments discussed in Sect. 4.2. The hot moments of bed erosion are the extreme events caused by summer thunderstorms. The downstream river segments close to the gauge show higher bed erosion rates than the sections further upstream because flow rates and thus bed shear stresses are higher even with identical channel slope.
Suspended sediment transport is of great importance for river morphology, water quality, and aquatic ecology. In this study, we have presented an integrated sediment-transport model, combining a conceptual hydrological model with a river-hydraulics model, a model of sediment generation, and a shear-stress-dependent sediment-transport model within the river, which enables us to investigate the major contributors to the suspended-sediment loads in different river sections under different flow conditions.
In the dominantly groundwater-fed Ammer catchment, annual suspended-sediment
load is dominated by the contributions of urban particles and sediment input
from the karst system. The contribution from rural areas is small because the
topography is comparably flat and the infiltration capacity of the soils is
high in this region, resulting in a very weak surface runoff from rural areas,
and thus very few rural particles are generated and transported to the river
channel. In-stream processes, i.e., bed erosion and bank erosion, play
significant roles in high-flow conditions (
The model and results of this study are useful and essential for further research on the fate and sediment-facilitated transport of hydrophobic pollutants like PAHs, and for the design of optimal sampling regimes to capture the different processes that drive particle dynamics. In addition, the analysis of deposition and bed erosion in the Ammer main stem provides information on the distribution of net sediment trapping within the channel, which would be a good indicator that channel dredging improves water quality.
The full code, as well as the supporting information related to this article, is provided in the Supplement.
The hydrological model in the integrated sediment transport model is composed of three storage zones in vertical direction with a quick recharge component and an urban surface runoff component. Detailed processes are shown below.
We applied this model to 14 subcatchments of the study domain. Each subcatchment includes three different land uses: urban area, agriculture, and forest. For urban areas, we consider effective urban areas such as roads and roofs and ineffective urban areas such as parks and gardens. We use the same parameters of agriculture for ineffective urban area.
The effective urban area is used for surface runoff component, the ratio is
calculated by the following:
The effective precipitation to the subsurface storage for agriculture,
forest, and ineffective urban area is calculated below:
We use long-term monthly mean evapotranspiration to calculate the actual
evapotranspiration with a temperature adjustment.
The top storage layer, soil moisture, is calculated by the following:
The surface runoff in the effective urban area, overflow and interflow are
calculated by the following:
The two equations below are used to calculate percolation and quick
recharge.
The subsurface storage and groundwater storage are calculated by:
The hydrological model for the Ammer catchment with three storage zones (soil moisture, subsurface storage, and groundwater storage), a quick groundwater recharge and an urban surface runoff component.
The supplement related to this article is available online at:
YL, CZ, NBB, and OAC conceptualized the study. YL wrote the code with the help of OAC. MS provided and preprocessed the data of discharge and turbidity. YL prepared the paper and all co-authors were involved in reviewing the paper.
The authors declare that they have no conflict of interest.
This study was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) within the Research Training Group “Integrated Hydrosystem Modeling” (grant GRK 1829). Additional funding is granted by the Collaborative Research Center SFB 1253 “CAMPOS – Catchments as Reactors”, and by the EU FP7 Collaborative Project GLOBAQUA (grant agreement no. 603629). Edited by: Christian Stamm Reviewed by: two anonymous referees