New Method for Quantifying Uncertainty in Groundwater Models Using Optimization-Based Bound Tightening
Researchers have proposed an Optimization-based Bound Tightening (OBBT) framework to quantify uncertainty in groundwater models that cannot be uniquely solved from available data. Unlike conventional ensemble sampling methods, OBBT directly computes guaranteed outer bounds on uncertain variables by optimizing over a system of physical and observational constraints. The approach addresses a longstanding risk that incomplete sampling in traditional methods can systematically underestimate the true range of plausible subsurface conditions.
Groundwater models are frequently non-identifiable, meaning sparse subsurface measurements leave many combinations of parameters, states, and boundary conditions equally consistent with observed data. Existing uncertainty quantification (UQ) methods rely on sampling a finite set of model realizations, which can miss parts of the solution space and underestimate uncertainty. The proposed OBBT framework instead represents uncertainty as intervals and tightens them by finding extremes of variables subject to constraints encoding Darcy's law and available observations, discretized via a finite-volume scheme. A key technical challenge identified is that McCormick relaxations of the resulting bilinear terms can break the physical coupling between flow direction and hydraulic head gradients, allowing non-physical rotational flow. The authors address this by introducing flow sign prescription and irrotationality constraints, and they validate the framework on three numerical examples spanning 1D steady-state, 2D steady-state, and 2D transient configurations. The method is described as conservative, deterministic, and physically grounded, with connections to null space theory and data assimilation, though computational scalability to large real-world models remains an open question.
What's missing
The study is a preprint and has not yet undergone peer review. The authors acknowledge scalability limitations but do not provide benchmarks against real-world large-scale groundwater models or comparisons with established UQ methods on identical test cases. The practical computational cost relative to ensemble-based approaches at operational scales is not fully characterized.
What different sources said
- arXiv physicsCenter
Bounding the Null Space: Interval-Based Uncertainty Quantification for Non-Identifiable Groundwater Models
Related
Gut Bacteria Enzyme Found to Break Down Heat-Processed Food Compounds, Producing Novel Biogenic Amines
Researchers have discovered that an enzyme in common gut bacteria can degrade N-epsilon-carboxymethyllysine (CML), a compound formed during thermal food processing, producing previously unknown biogenic amines. The enzyme, ornithine decarboxylase SpeC from enterobacteria, acts on CML and related modified lysine derivatives through a low-level 'underground' catalytic activity. This finding suggests a previously unrecognized communication axis between thermally processed dietary compounds and gut microbial physiology, with potential implications for host health.
Full-Length Gene Sequencing Reveals Two Distinct Bacterial Communities in Black-Legged Ticks Expanding Into Canada
Researchers used Oxford Nanopore full-length 16S rRNA gene sequencing to characterize the microbiome of Ixodes scapularis black-legged ticks collected in Nova Scotia, Canada, distinguishing between tick-adapted bacteria and environmentally acquired bacteria. The study comes as I. scapularis — the primary vector of Lyme disease — is rapidly expanding northward into Canada due to climate change. The findings suggest that environmentally derived bacteria in tick microbiomes are not mere contamination, which has implications for how tick microbiome data is collected and interpreted across surveillance studies.
Study Identifies Metabolic Link Between Cell Envelope Stress and Biofilm Formation in Bacteria
Researchers have discovered that the metabolite acetyl-CoA directly inhibits enzymes that degrade the bacterial signaling molecule c-di-GMP, connecting cell envelope biosynthesis stress to biofilm formation in Pseudomonas aeruginosa. The study found that sub-inhibitory concentrations of antibiotics targeting early peptidoglycan biosynthesis — but not other antibiotic classes — elevate c-di-GMP levels by reducing phosphodiesterase activity, with acetyl-CoA competing for the enzyme active site. Because the relevant enzyme domain is broadly conserved across bacterial species, this checkpoint mechanism may be widespread and could have implications for understanding antibiotic-induced biofilm responses.