DYNAMO – Events as DYNAmic drivers of pollutant transport, turnover and export in catchments – from monitoring to MOdels
The second PhD college of the Thematic Area Water Resources and Environment
Managing our freshwater resources to mitigate adverse effects of diffuse pollution, for example, by nutrients or agrochemicals is a challenging problem. To develop robust management strategies for water quality, it is imperative to understand the key drivers that control transport and turnover of these pollutants and their subsequent export. Catchments are complex, dynamic systems consisting of interconnected compartments, such as the unsaturated zone, groundwater, lakes and the river network, which transport, process (e.g. by reactive turnover) and eventually export pollutant inputs from diffuse and point sources. These compartments can be conceptualized as a sequence of reactors, each characterized by distinct transport and reaction rates (see figure below), which exchange water and solutes to produce an integrated pollutant output signal at the catchment outlet.
Compartmental transport and reaction rates are driven by the dynamics of hydro-meteorological events. The frequency and sequence of hydrological events, in particular extreme events such as heavy rainfall, floods, droughts or heat waves have a major, often long-lasting, impact on pollutant export. Recent hydrological extreme events such as the national-scale drought in 2018 or the Elbe flood in 2013 and future changes in event frequency call for concepts and tools to address the impact of such high-magnitude events on pollutant turnover and export at catchment-scale. In view of the increase in the frequency and intensity of extreme events associated with climate change, it is vital to understand how sequences of extreme events alter or disrupt seasonal and long-term patterns of reaction and transport time scales and the corresponding output signals.
In view of these knowledge gaps, we will address the following key challenges within DYNAMO:
- Incorporation of robust estimates of transit times and reaction times for water and solutes in the compartments of catchments
- Improved understanding of the role and significance of events in solute export from catchments
The structure of DYNAMO fosters exchange and joint research activities between PhD projects as well as with the PhD college inSTREAM and the Helmholtz International Research School TRACER. Moreover, the DYNAMO-cohort will be fully embedded in the HIGRADE curriculum and each PhD will attend basic courses such as statistics, scientific writing, soft skills and disciplinary training.
Research context and knowledge gaps
It is not well understood how flow paths and source areas of water change between average flow conditions and extreme events. Consequently, it is unclear to what extent the sequence and magnitude of extreme events may impact the transport and reactivity and, therefore, the short- and long-term fate of pollutants in catchments. A powerful method to study these knowledge gaps is the use of environmental tracer data (e.g., stable water isotopes) to constrain transit time distributions (TTDs), which specify the time that water spends within catchments between its time of entry (via precipitation) and its time of exit at the catchment outlet. In this project, baseflow and event stable water isotope data measured in multiple contrasting sub-catchments of the Bode region will be used to derive dynamic TTDs.
Key questions / hypothesis to be tested
- Event TTDs increase during drought conditions and decrease during floods.
- Pre-event conditions (e.g., soil moisture conditions) and event characteristics (e.g., duration, intensity) govern event TTDs in contrasting sub-catchments.
- Sub-daily isotope samples are needed to accurately constrain event TTDs.
Expected outcomes
- Provision of an extensive high-resolution isotope dataset as well as a modelling tool to incorporate event isotope data.
- Development of a guideline for event isotope sampling in precipitation and streamflow.
- Characterisation of event TTDs in terms of their spatial and temporal variation and response to event characteristics.
PhD student
Advisory team
Research context and knowledge gaps
Water quality models often fail to account for the differing responses of water flow and solute transport to dynamic conditions in catchments. This hinders our ability to accurately simulate the time scales of solute transport and reactivity in catchments, which is crucial to describe, for example, long groundwater transit times and associated legacy contamination (i.e., retention of pollutants in the subsurface long after their release into the catchment). This PhD project therefore aims at better representing the dynamics of flow, solute transport and turnover in a mechanistic water quality model, particularly under extreme event conditions. A key method will be the use of dynamic transit time distributions (TTDs), which will be validated and constrained using existing stable water isotope data from various sub-catchments in the Bode region.
Key questions / hypothesis to be tested
- Stable water isotope data are essential for validating and constraining TTDs in spatially distributed models.
- Spatially explicit representation of TTDs significantly increases the accuracy and reliability of water quality models.
- Successful mitigation of legacy contamination largely depends on the sub-catchment-specific responses to extreme events.
Expected outcomes
- Spatially explicit estimates of water age metrics and TTDs across various study sub-catchments under dynamic hydrologic conditions.
- Reliable representation of water and solute transport in a catchment-scale water quality model through incorporation of dynamic TTDs.
- A modelling framework providing straightforward incorporation of isotope datasets in a spatially explicit catchment model (mHM).
PhD student
Arianna Borriero
Advisory team
Research context and knowledge gaps
Concentration-Discharge (C-Q) relationships of solutes observed at catchment outlets define the export regime and encode the large-scale interplay of compartmental transport and reaction mechanisms (Musolff et al., 2015). Their significant scatter is possibly related to hydrological event conditions occurring at sampling time, which could be used to clarify the displayed variability. Among these conditions, extreme events may trigger lasting changes of solute export regimes. Understanding their role is therefore pivotal for better quantifying export of critical substances such as nitrate and phosphate. The approach developed by Tarasova et al. (2018a, b) to characterize runoff events suggests relevant descriptors of event dynamics that could explain scatter in C-Q relationships, and opens up the opportunity to align hydrological and export regimes. This will build an empirical basis for understanding the dynamic role of runoff events in integrated catchment scale matter export.
Key questions / hypothesis to be tested
- Characteristics of runoff events and their drivers explain observed scatter of C-Q relationships and thus assist in pinpointing sources and reactive transport mechanisms. Scatter effects will be distinguished from network mixing and reaction effects that are assessed in the inSTREAM cohort.
- Magnitude and dominant type of runoff events determine varied degree of responsivity of solute export regimes in diverse river catchments and the persistence of changes.
- Catchment and hydro-meteorological descriptors can be used to rank German river basins in terms of their contribution to overall load of solutes from diffuse sources toward the sea.
Expected outcomes
- Identification of runoff event types and hydro-meteorological conditions which amplify solute export from river catchments. This will serve as a guide for modelling efforts.
- Assessment of the persistence of water quality alterations caused by different runoff event types. This will be instrumental in water quality management during post-event periods.
- Classification of German catchments with respect to solute export and responsivity to events. This will support prioritization of actions to reduce water pollutants.
PhD student
Felipe Saveedra
Advisory team
Research context and knowledge gaps
Standing waters like lakes and reservoirs are integral features of catchments that modulate nutrient fluxes. However, catchment-scale studies of solute export tend to end only where lake assessments start (at the catchment outlet / lake inlet), so coupled lake-catchment dynamics are poorly understood. On a global scale, standing waters play a huge role in C, N, and P retention due to sedimentation, which is disproportionately higher than in rivers and streams. Depending on temporal scales, lake characteristics and environmental factors, standing waters do not simply buffer the input dynamics but can periodically switch between being nutrient sinks or sources (Shatwell and Köhler 2019). Moreover, carbon and nitrogen can enter and leave the aquatic ecosystem as gas through biological and physical processes, which are strongly seasonal. The above studies clearly demonstrate that lakes and reservoirs need to be included in catchment-scale assessments of nutrient retention, but our knowledge of nutrient export dynamics, especially at seasonal and event time-scales, is lacking.
Key questions / hypothesis to be tested
- Standing waters alter solute export patterns from catchments and their representation in catchment models improves the model’s predictive power.
- The relative contribution of standing waters to whole-catchment nutrient retention depends on time scales of transport and reactivity, which are controlled by lake characteristics and hydrological forcing.
- Extreme events lead to major shifts between transport-dominated and reaction-dominated states and therefore strongly modify retention capacities.
- Management strategies to optimize nutrient retention can be developed with coupled models.
Expected outcomes
- Characterization of the emergent behavior of coupled catchment-lake archetypes as a basis to conceptualize lakes in water quality models developed at the UFZ.
- Predictions of nutrient retention efficiencies at the event scale including extreme events.
- Model-based management strategies to optimize nutrient retention in the face of increasing frequency of extreme events.
PhD student
Advisory team