Harmonised Principles for Public Participation in Quality Assurance of Integrated Water Resources Modelling

The main purpose of public participation in integrated water resources modelling is to improve decision-making by ensuring that decisions are soundly based on shared knowledge, experience and scientific evidence. The present paper describes stakeholder involvement in the modelling process. The point of departure is the guidelines for quality assurance for `scientific` water resources modelling developed under the EU research project HarmoniQuA, which has developed a computer based Modelling Support Tool (MoST) to provide a user-friendly guidance and a quality assurance framework that aim for enhancing the credibility of river basin modelling. MoST prescribes interaction, which is a form of participation above consultation but below engagement of stakeholders and the public in the early phases of the modelling cycle and under review tasks throughout the process. MoST is a flexible tool which supports different types of users and facilitates interaction between modeller, manager and stakeholders. The perspective of using MoST for engagement of stakeholders e.g. higher level participation throughout the modelling process as part of integrated water resource management is evaluate

Quality Assurance of the modelling process

The present paper briefly describes a new modelling support tool (MoST) aimed at facilitating better quality assurance of the modelling process. MoST comprises a Knowledge Base with guidelines on good modelling practise for seven scientific domains. It supports multi-domain modelling and working in teams of different user types (water managers, modellers, auditors/reviewers, stakeholders and members of the public). The key functionality of MoST is to: (a) Guide to ensure that a model has been properly applied; (b) Monitor to record decisions, methods and data used in the modelling work and in this way enable transparency and reproducibility of the modelling process; (c) Report to provide suitable reports on what has been done by the various actors. MoST has been developed under the HarmoniQuA project (www.HarmoniQuA.org

Meta-analysis of type 2 Diabetes in African Americans Consortium

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR)  = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.Peer reviewe

How might climate change affect river flows across the Thames Basin?: an area-wide analysis using the UKCP09 Regional Climate Model ensemble

The Thames Basin drains an area of over 10,000km2 through London to the North Sea. It encompasses both rural and heavily urbanised areas overlying a spatially-varied and complex geology. Historically, the lower Thames has proved resilient to climate variability, and careful river management in recent years has helped protect the region from flooding. However, recent climate projections for the region indicate that over the next century winter rainfall might increase by 10-15%, potentially leading to higher flows than the Thames can accommodate. This study uses a distributed hydrological model, the Grid-to-Grid (G2G), to assess future changes in peak river flows for a range of catchments across the Thames Basin. The G2G model has used as input an ensemble from the UK Climate Projections (UKCP09) Regional Climate Model (RCM), under the A1B emissions scenario, to analyse changes in flood frequency between two 30-year time-slices (Oct 1960-Sep 1990 and Oct 2069-Sep 2099). The RCM ensemble uses a perturbed-parameter approach to address uncertainty in climate projections. Results indicate considerable spatial variation in projected changes in peak flows. Towards the downstream end of the fluvial Thames, the average estimated change in modelled 20-year return period flood peaks by the 2080s is 36% with a range of -11% to +68%, which is broadly in line with recent government guidance for the Thames Basin. A key question that arises is whether these estimated changes fall within the range of natural variability and would therefore be indistinguishable from the effects of typical weather patterns in the current climate. Comparison of the modelled changes in flood frequency with an RCM-based estimate of current natural variability shows that, whilst for some rivers (or parts of rivers) there are few changes outside the range of current natural variability, for other rivers there are more changes outside of this range. The latter locations could be considered as sites where further monitoring/modelling may provide early warning of statistically significant changes in observed flows, due to climate change