Peter Reichert's research while affiliated with Eawag: Das Wasserforschungs-Institut des ETH-Bereichs and other places
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Publications (170)
Identifying sublethal pesticide effects on aquatic organisms is a challenge for environmental risk assessment. Long-term population experiments can help assessing chronic toxicity. However, population experiments are subject to stochasticity (demographic, environmental, and genetic). Therefore, identifying sublethal chronic effects from “noisy” dat...
The traditional description of a hydrological system with a deterministic, conceptual model and a lumped output error term does not explicitly consider the main mechanisms of uncertainty generation due to approximate process representation, unobserved variability in processes and influence factors, and input uncertainty. In this study, we test the...
Small streams in catchments with agricultural land use are at high risk of diffuse pollution by herbicides. Fast transport processes can cause concentration peaks that exceed regulatory requirements. These processes have a high spatio‐temporal variability and data characterizing their occurrence is often sparse. For this reason, such systems show a...
A wide knowledge base regarding the ecological preferences of benthic macroinvertebrates is synthesized in public databases. This knowledge can assist in disentangling the influence of multiple environmental factors on the probability of occurrence of macroinvertebrates and in identifying anthropogenic impacts on the macroinvertebrate assemblage. W...
Key decisions in the design of biomonitoring programs include taxonomic resolution, geographic extent, and site selection, each of which can affect our ability to infer human impacts on biodiversity from biomonitoring data. These decisions are constrained by monitoring goals and budget limitations, which may require trade-offs between them. In this...
Herbicide pollution in headwater streams due to agricultural practices is a major environmental concern and is characterized by episodic peak concentrations from fast transport paths. We rely on previous experimental studies in a small (1.2 km2) agricultural catchment in the Swiss Plateau, to model dynamic diffuse herbicide pollution with emphasis...
Species distribution models (SDMs) are often criticised for lacking explicit linkage to ecological concepts. We aim to improve the ecological basis of SDMs by integrating prior knowledge about ecological preferences of organisms. Additionally, we aim to support a systematic, data-driven review of such prior knowledge by confronting it with independ...
Uncertainty quantification is very important in environmental management to allow decision makers to consider the reliability of predictions of the consequences of decision alternatives and relate them to their risk attitudes and the uncertainty about their preferences. Nevertheless, uncertainty quantification in environmental decision support is o...
Despite the large literature about non-additive value aggregation techniques, in the large majority of applied decision support processes, additive value aggregation functions are used. The main reasons for this may be the simplicity of the approach, minimum elicitation requirements, software availability, and the appeal of the underlying preferenc...
Decision-making in environmental management requires eliciting preferences of stakeholders and predicting outcomes of decision alternatives. Usually, preferences and predictions are both uncertain. Uncertainty of predictions can be tackled by multi-attribute utility theory, but the uncertainty of preferences remains a challenge. We demonstrate an a...
As in many fields of dynamic modeling, the long runtime of hydrological models hinders Bayesian inference of model parameters from data. By replacing a model with an approximation of its output as a function of input and/or parameters, emulation allows us to complete this task by trading-off accuracy for speed. We combine (i) the use of a mechanist...
Aim
Species distribution models (SDMs) are widely used to study geographic distributions of taxa in response to natural and anthropogenic environmental conditions. For a community, common approaches include fitting individual SDMs (iSDMs) to all taxa or directly modelling community properties such as richness. However, the parameters of iSDMs are d...
![Figure 1. Example of skewed Student's t distributions with E[D Q ] = Q...](publication/332763305/figure/fig1/AS:753444667289600@1556646615168/Example-of-skewed-Students-t-distributions-with-ED-Q-Q-det-t-25-mm-h-1-and_Q320.jpg)
The widespread application of deterministic hydrological models in research and practice calls for suitable methods to describe their uncertainty. The errors of those models are often heteroscedastic, non-Gaussian and correlated due to the memory effect of errors in state variables. Still, residual error models are usually highly simplified, often...
The AQUACROSS project was an unprecedented effort to unify policy concepts, knowledge, and management of freshwater, coastal, and marine ecosystems to support the cost-effective achievement of the targets set by the EU Biodiversity Strategy to 2020. AQUACROSS aimed to support EU efforts to enhance the resilience and stop the loss of biodiversity of...
Freshwater ecosystems are increasingly under threat as they are confronted with multiple anthropogenic impairments. This calls for comprehensive management strategies to counteract, or even prevent, long-term impacts on habitats and their biodiversity, as well as on their ecological functions and services. The basis for the efficient management and...
The widespread application of deterministic hydrological models in research and practise calls for suitable methods to describe their uncertainty. The errors of those models are often heteroscedastic, non-Gaussian and correlated due to the memory effect of errors in state variables. Still, the residual error models used to describe them are usually...
As in many fields of dynamic modeling, the long runtime of hydrological models hinders Bayesian inference of model parameters from data. By replacing a model with an approximation of its output as a function of input and/or parameters, emulation allows us to complete this task by trading-off accuracy for speed. We combine (i) the use of a mechanist...
Multi-criteria decision analysis (MCDA) requires an accurate representation of the preferences of decision-makers, for instance in the form of a multi-attribute value function. Typically, additivity or other stringent assumptions about the preferences are made to facilitate elicitation by assuming a simple parametric form. When relaxing such assump...
This study considers Bayesian calibration of hydrological models using streamflow signatures and its implementation using Approximate Bayesian Computation (ABC). If the modeling objective is to predict streamflow time series and associated uncertainty, a probabilistic model of streamflow must be specified but the inference equations must be develop...
This study investigates Bayesian signature‐domain inference of hydrological models using Approximate Bayesian Computation (ABC) algorithms, and compares it to “traditional” time‐domain inference. Our focus is on the quantification of predictive uncertainty in the streamflow time series and on understanding the information content of particular comb...
• Habitat destruction, biological invasions and water quality deterioration are serious threats to native communities and can lead to modifications in community composition and structure, and in ecosystem function.
• To predict the consequences of river restoration, biological invasions and water quality change in the taxonomic composition of macro...
Parameter estimation for agent-based and individual-based models (ABMs/IBMs) is often performed by manual tuning and model uncertainty assessment is often ignored. Bayesian inference can jointly address these issues. However, due to high computational requirements of these models and technical difficulties in applying Bayesian inference to stochast...
While the number of river restoration projects is increasing, studies on their success or failure relative to expectations are still rare. Only a few decision support methodologies and integrative methods for evaluating the ecological status of rivers are used in river restoration projects, thereby limiting informed management decisions in restorat...
Gaussian process (GP) emulation is a data-driven method that substitutes a slow simulator with a stochastic approximation. It is then typically orders of magnitude faster than the simulator at the costs of introducing interpolation errors. Our approach, the mechanism-based GP emulator, uses knowledge of the simulator mechanisms in addition to the i...
Rainfall input uncertainty is one of the major concerns in hydrological modeling. Unfortunately, during inference, input errors are usually neglected, which can lead to biased parameters and implausible predictions. Rainfall multipliers can reduce this problem but still fail when the observed input (precipitation) has a different temporal pattern f...
The AQUACROSS concept introduced in this deliverable aims to make ecosystem-based management (EBM) an ecosystem-service and resilience-oriented concept that can be made fully operational in the context of the management of aquatic ecosystems (inland, coastal and marine). The AQUACROSS Assessment Framework (AF) will, for the first time, generate con...
Modelling community dynamics of aquatic invertebrates is an important but challenging task, in particular in ecotoxicological risk assessment. Systematic parameter estimation and rigorous assessment of model uncertainty are often lacking in such applications. We applied the mechanistic food web model Streambugs to investigated the temporal developm...
Many simulation-intensive tasks in the applied sciences, such as sensitivity analysis, parameter inference or real time control, are hampered by slow simulators. Emulators provide the opportunity of speeding up simulations at the cost of introducing some inaccuracy. An emulator is a fast approximation to a simulator that interpolates between design...
The community assembly of macroinvertebrates in streams depends on the regional taxon pool, dispersal limitations, local habitat conditions and biotic interactions. By integrating existing knowledge about these processes from theoretical ecology in a mechanistic model, we can test our mechanistic understanding and disentangle multiple stressor effe...
Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how soci...
We present a novel approach for practically tackling uncertainty in preference elicitation and predictive modeling to support complex multi-criteria decisions based on multi-attribute utility theory (MAUT). A simplified two-step elicitation procedure consisting of an online survey and face-to-face interviews is followed by an extensive uncertainty...
With its source in the Alps and its mouth close to the Rhine falls, the Thur once was a dynamic braided river flowing through the Swiss Plateau. However, to gain arable land and decrease the impacts of floods, most parts of the river were constrained in a straight, unique channel and surrounded by high levees at the end of the 19th century. Since t...
Environmental modeling often requires combining prior knowledge with information obtained from data. The robust Bayesian approach makes it possible to consider ambiguity in this prior knowledge. Describing such ambiguity using sets of probability distributions defined by the Density Ratio Class has important conceptual advantages over alternative r...
To quantify the contribution of hyporheic community respiration to whole running-water ecosystem respiration in a cultural
landscape setting, we studied the vertical hydraulic exchange in riffle–pool sequences of the River Lahn (Germany). We used
flow through curves from four tracer experiments to estimate flow velocities in the surface and subsurf...
We use a Gaussian stochastic process emulator to interpolate the posterior probability density of a computationally demanding application of the biogeochemical-ecological lake model BELAMO to accelerate statistical inference of deterministic model and error model parameters. The deterministic model consists of a mechanistic description of key proce...
Context:
Seizures during intoxications with pharmaceuticals are a well-known complication. However, only a few studies report on drugs commonly involved and calculate the seizure potential of these drugs.
Objectives:
To identify the pharmaceutical drugs most commonly associated with seizures after single-agent overdose, the seizure potential of...
Ecological assessment requires the integration of many physical, chemical, and/or biological quality elements. The choice of the aggregation method of such partial assessments into an overall assessment can considerably affect the assessment outcome – an issue that has been controversially discussed within the scientific community for the last deca...
To overcome the difficulties of strategic asset management of water distribution networks, a pipe failure and a rehabilitation model are combined to predict the long-term performance of rehabilitation strategies. Bayesian parameter estimation is performed to calibrate the failure and replacement model based on a prior distribution inferred from thr...
Hydrodynamic models are useful tools for urban water management.
Unfortunately, it is still challenging to obtain accurate results and
plausible uncertainty estimates when using these models. In particular,
with the currently applied statistical techniques, flow predictions are
usually overconfident and biased. In this study, we present a flexible...
Accurate predictions of future conditions of sewer systems are needed for efficient rehabilitation planning. For this purpose, a range of sewer deterioration models has been proposed which can be improved by calibration with observed sewer condition data. However, if datasets lack historical records, calibration requires a combination of deteriorat...
A proper uncertainty assessment of rainfall-runoff predictions has
always been an important objective for modelers. Several sources of
uncertainty have been identified, but their representation was limited
to complicated mechanistic error propagation frameworks only. The
typical statistical error models used in the modeling practice still
build on...
Predictions of the expected number of failures of water distribution network pipes are important to develop an optimal management strategy. A number of probabilistic pipe failure models have been proposed in the literature for this purpose. They have to be calibrated on failure records. However, common data management practices mean that replaced p...
Hydrodynamic models are useful tools for urban water management. Unfortunately, it is still challenging to obtain accurate results and plausible uncertainty estimates when using these models. In particular, with the currently applied statistical techniques, flow predictions are usually overconfident and biased. In this study, we present a flexible...
Climate change impact assessments have become more and more popular in
hydrology since the middle 1980's with another boost after the
publication of the IPCC AR4 report. During hundreds of impact studies a
quasi-standard methodology emerged, which is mainly shaped by the
growing public demand for predicting how water resources management or
flood p...
The presented approach aims to overcome the scarce data problem in service life modeling of water networks by combining subjective expert knowledge and local replacement data. A procedure to elicit imprecise quantile estimates of survival functions from experts, considering common cognitive biases, was developed and applied. The individual expert p...
Predictions of the urban hydrologic response are of paramount importance
to foresee floodings and sewer overflows and hence support sensible
decision making. Due to several error sources models results are
uncertain. Modeling statistically these uncertainties we can estimate
how reliable predictions are. Most hydological studies in urban areas
(e.g...
Formal methods of decision analysis can help to structure a decision making process and to communicate reasons for decisions transparently. Objectives hierarchies and associated value and utility functions are useful instruments for supporting such decision making processes by structuring and quantifying the preferences of decision makers or stakeh...
For the first time, we combine concepts of theoretical food web modeling, the metabolic theory of ecology, and ecological stoichiometry with the use of functional trait databases to predict the coexistence of invertebrate taxa in streams. We developed a mechanistic model that describes growth, death, and respiration of different taxa dependent on v...
1. We investigated photosynthesis±irradiance relationships (P±I curves; P = oxygen production rate due to photosynthesis, I = light irradiance rate at the water surface) and ecosystem respiration in a 9 km long reach of a river that is characterised by light conditions favouring primary production, high ambient nutrient concentrations, a high re-ae...
1. With a modified version of the lake model BELAMO, we were able to describe the essential features of the dynamics of nutrients, dissolved oxygen, phyto- and zooplankton in three lakes of different trophic status over periods of 19–30 years, with essentially the same model parameters for all three lakes. This is remarkable, as the measured nutrie...
Models of environmental systems are simplified representations of the reality. For this reason, their results are affected by systematic errors. This bias makes it difficult to get reliable uncertainty estimates of model parameters and predictions. A relatively simple way of considering this bias when using deterministic models is to add a statisti...
In the absence of model deficiencies, simulation results at the correct parameter values lead to an unbiased description of observed data with remaining deviations due to observation errors only. However, this ideal cannot be reached in the practice of environmental modeling, because the required simplified representation of the complex reality by...
Decisions in environmental management can be challenging, amongst other things, due to two major sources of uncertainty. Predictions of consequences of different management alternatives can be very uncertain. Furthermore, uncertainty exists regarding the subjective preferences of decision makers and stakeholders. For a transparent decision process...
Decision making in public and political contexts can be complex. Multi-attribute value/utility theory (MAVT/MAUT) can support such decision processes by providing a transparent framework that helps focusing on objectives and corresponding degrees of achievement by different alternatives. Eliciting preferences with MAVT/MAUT can be time consuming an...
As rehabilitation of previously channelized rivers becomes more common worldwide, flexible integrative modeling tools are needed to help predict the morphological, hydraulic, economic, and ecological consequences of the rehabilitation activities. Such predictions can provide the basis for planning and long-term management efforts that attempt to ba...
Despite the vivid scientific debate on the suitability of RCM
predictions for hydrological forecasting, impact studies relying on
climatic input data and hydrological models are still the exclusive
methods to provide some insight into the expected evolution of streams
in the close future. While the climatic uncertainty is usually
considered being d...
The aim of this study is to apply the Bayesian method of identifying optimal experimental designs to a toxicokinetic-toxicodynamic model that describes the response of aquatic organisms to time dependent concentrations of toxicants. As for experimental designs, we restrict ourselves to pulses and constant concentrations. A design of an experiment i...
![Figure 2: Illustration of the density of late summer fry [ind ha −1 ]...](profile/Lukas-Indermaur/publication/235222271/figure/fig2/AS:669440668610564@1536618501469/Illustration-of-the-density-of-late-summer-fry-ind-ha-1-at-the-end-of-the-summer-with_Q320.jpg)
Brown trout (Salmo trutta fario) is an ecologically and economically important
fish species in many Swiss rivers. Since the 1980s, a significant decrease of brown
trout catches was reported across Swiss rivers. To better understand the causes of
this decline, a trout population model was developed a few years ago. It predicted trout
densities at si...
Switzerland provides an example of successful management of water infrastructure and water resources that was accomplished largely without integration across sectors. Limitations in this approach have become apparent; decisions that were formerly based only on technical and economic feasibility must now incorporate broader objectives such as ecolog...
A distributed hydrological model was used to simulate the distribution
of fast runoff formation as a proxy for critical source areas for
herbicide pollution in a small agricultural catchment in Switzerland. We
tested to what degree predictions based on prior knowledge without local
measurements could be improved upon relying on observed discharge....
The probability distributions of uncertain quantities needed for predictive modelling and decision support are frequently elicited from subject matter experts. However, experts are often uncertain about quantifying their beliefs using precise probability distributions. Therefore, it seems natural to describe their uncertain beliefs using sets of pr...
Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistical inference, require a large number of model evaluations to be performed at different input and/or parameter values. This limits the application of these techniques to models that can be implemented in computationally efficient computer codes. Emula...
To evaluate the role of the benthic community within headwater stream ecosystems, it is crucial to understand the mechanisms of the processes dominating their turnover rates and temporal dynamics. To analyze the benthic community dynamics of an intermittent Mediterranean stream (Fuirosos, Spain), we developed a mechanistic model that describes the...
Model-based environmental decision support requires that uncertainty be rigorously evaluated. Whether uncertainty is aleatory or epistemic, we argue that probability is the natural mathematical construct for describing uncertainty in predictions used for decision-making. If expert knowledge is elicited using stated preferences between lotteries, an...
It has been recognized for many decades that the stoichiometry of biological reactions is important for linking ecological and biogeochemical processes. However, only during the past decade has the scientific community become aware that “biological stoichiometry” may also help bridge evolutionary biology and ecosystem ecology. This awareness led to...
Despite more than a decade of research, the magnitude of wastewater leakage from defective sewer systems into groundwater supplies is still largely unknown, partly because reliable measurement methods are lacking. Although recently suggested in-sewer tracer studies present a promising solution, it is unclear how to optimally design such studies in...
Even after careful calibration, the output of deterministic models of environmental systems usually still show systematic deviations from measured data. To analyse possible causes of these discrepancies, we make selected model parameters time variable by treating them as continuous time stochastic processes. This extends an approach that was propos...
A recently developed technique for identifying continuous-time, time-dependent, stochastic model parameters is embedded in a general framework for identifying causes of bias and reducing bias in dynamic models. In contrast to the usual approach of considering bias in model output with an autoregressive error model or a stochastic process, we make t...
The modeling of diagenetic processes in the sediment of deep eutrophic lakes requires a dynamic approach covering seasonal changes to decadal trends. Due to the large base of scientific knowledge, the description of environmental systems is often based on complex simulation models that contain parameterizations of a large number of processes. The p...
Rivers are heterogeneous at various scales. River metabolism estimators based on oxygen time series provide average estimates of net oxygen production at the scale of a river reach. These estimators are derived for homogeneous river reaches. For this reason, they cannot be used to analyze how exactly they average over longitudinal variations in net...