System Analysis of Wildfire-Water Supply Risk in Colorado, USA with Monte Carlo Wildfire and Rainfall Simulation.

Water supply impairment from increased contaminant mobilization and transport after wildfire is a major concern for communities that rely on surface water from fire-prone watersheds. In this article we present a Monte Carlo simulation method to quantify the likelihood of wildfire impairing water supplies by combining stochastic representations of annual wildfire and rainfall activity. Water quality impairment was evaluated in terms of turbidity limits for treatment by modeling wildfire burn severity, postfire erosion, sediment transport, and suspended sediment dilution in receiving waterbodies. Water supply disruption was analyzed at the system level based on the impairment status of water supply components and their contributions to system performance. We used this approach to assess wildfire-water supply impairment and disruption risks for a system of water supply reservoirs and diversions in the Front Range Mountains of Colorado, USA. Our results indicate that wildfire may impair water quality in a concerning 15.7-19.4% of years for diversions from large watersheds. Reservoir impairment should be rare for off-network reservoirs-ranging from at most 0.01% of years for large reservoirs to nearly 2% of years for small reservoirs. System redundancy meaningfully reduced disruption risk for alternative conveyance routes (4.3-25.0% reduction) and almost eliminated disruption risk for a pair of substitutable terminal sources (99.9% reduction). In contrast, dependency among reservoirs on a conveyance route nearly doubled risk of disruption. Our results highlight the importance of considering water system characteristics when evaluating wildfire-water supply risks.

PEMIP: Post-fire erosion model inter-comparison project.

Land managers often need to predict watershed-scale erosion rates after disturbance or other land cover changes. This study compared commonly used hillslope erosion models to simulate post-fire sediment yields (SY) at both hillslope and watershed scales within the High Park Fire, Colorado, U.S.A. At hillslope scale, simulated SY from four models- RUSLE, AGWA/KINEROS2, WEPP, and a site-specific regression model-were compared to observed SY at 29 hillslopes. At the watershed scale, RUSLE, AGWA/KINEROS2, and WEPP were applied to simulate spatial patterns of SY for two 14-16 km2 watersheds using different scales (0.5-25 ha) of hillslope discretization. Simulated spatial patterns were compared between models and to densities of channel heads across the watersheds. Three additional erosion algorithms were implemented within a land surface model to evaluate effects of parameter uncertainty. At the hillslope scale, SY was only significantly correlated to observed SY for the empirical model, but at the watershed scale, sediment loads were significantly correlated to observed channel head densities for all models. Watershed sediment load increased with the size of the hillslope sub-units due to the nonlinear effects of hillslope length on simulated erosion. SY's were closest in magnitude to expected watershed-scale SY when models were divided into the smallest hillslopes. These findings demonstrate that current erosion models are fairly consistent at identifying areas with low and high erosion potential, but the wide range of predicted SY and poor fit to observed SY highlight the need for better field observations and model calibration to obtain more accurate simulations.

Bringing Greater Accuracy to Europe's Healthcare Systems: The Unexploited Potential of Biomarker Testing in Oncology.

Rapid and continuing advances in biomarker testing are not being matched by take-up in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. This paper sets out the potential of biomarker testing, the unfolding precision and range of possible diagnosis and prediction, and the many obstacles to adoption. It offers case studies of biomarker testing in breast, ovarian, prostate, lung, thyroid and colon cancers, and derives specific lessons as to the potential and actual use of each of them. It also draws lessons about how to improve access and alignment, and to remedy the data deficiencies that impede development. And it suggests solutions to outstanding issues - notably including funding and the tangled web of obtaining reimbursement or equivalent coverage that Europe's fragmented health system implies. It urges a European evolution towards an initial minimum testing scenario, which would guarantee universal access to a suite of biomarker tests for the currently most common conditions, and, further into the future, to an optimum testing scenario in which a much wider range of biomarker tests would be introduced and become part of a more sophisticated health system articulated around personalised medicine. For exploiting genomics to the full, it argues the need for a new policy framework for Europe. Biomarker testing is not an issue that can be treated in isolation, since the purpose of testing is to improve health. Its use is therefore always closely linked to specific health challenges and needs to be viewed in the broader policy context in the EU and more widely. The paper is the result of extensive engagement with experts and decision makers to develop the framework, and consequently represents a wide consensus of views on how healthcare systems should respond from push and pull factors at local, national and cross-border and EU level. It contains strong views and clear recommendations springing from the convictions of patients, clinicians, academics, medicines authorities, HTA bodies, payers, the diagnostic, pharmaceutical and ICT industries, and national policy makers.