Combined sewer overflow mitigation through SUDS - A review on modelling practices, scenario elaboration, and related performances.

Hydrologic-hydraulic modelling of urban catchment is an asset for land managers to simulate Sustainable Urban Drainage Systems (SUDS) implementation to fulfil combined sewer overflow (CSO) regulations. This review aims to assess the current practices in modelling SUDS scenarios at large scale for CSO mitigation encompassing every stage of the modelling process from the choice of the equation to the validation of the initial state of the urban system, right through to the elaboration, modelling, and selection of SUDS scenarios to evaluate their performance on CSO. Through a quantitative and qualitative analysis of 50 published studies, we found a diversity of choices when modelling the status quo of the urban system. Authors generally do not explain the modelling processes of slow components (deep infiltration, groundwater infiltration) and interconnexion between SUDS and the sewer system. In addition, only a few authors explain how CSO structures are modelled. Furthermore, the modelling of SUDS implementation at catchment scale is highlighted in the 50 studies retrieved with three different approaches going from simplified to detailed. SUDS modelling choices seem to be consistent with the objectives: studies focusing on dealing with several objectives at the time typically opt for a complex system configuration that includes the surface processes, network, CSO, SUDS, and often the soil and/or groundwater components. Conversely, authors who have selected a basic configuration generally aim to address a single, straightforward question (e.g., which type of SUDS). However, elaboration and selection of scenarios for CSO mitigation is mainly based on local constraints, which does not allow hydrological performance to be directly optimised. In conclusion, to improve current practices in modelling SUDS scenarios at large scale for CSO mitigation, authors suggest to: (i) improve clear practices of CSO modelling, calibration and validation at the urban catchment scale, (ii) develop methods to optimize the performance of scenarios for CSO mitigation using hydrological drivers, and (iii) improve parsimonious and user-friendly models to simulate SUDS scenarios in a context of data scarcity.

ATP6H, a subunit of vacuolar ATPase involved in metal transport: evaluation in canine copper toxicosis.

Copper toxicosis (CT), resulting in liver disease, occurs commonly in Bedlington terriers. Canine CT is of particular interest because identification of the causative gene may lead to the discovery of another important gene in the copper transport pathway possibly related to human copper diseases not yet identified. Homologs of the copper transporting ATPase ATP7B, defective in Wilson disease, and the copper chaperone ATOX1 were potential candidates, but both have been excluded. The CT locus in Bedlington terriers has been mapped to canine chromosome region CFA10q26, which has a syntenic human chromosome region, HAS2p13-21. The gene ATP6H, for human vacuolar proton-ATPase subunit M9.2, is associated with copper and iron transport in yeast and has been mapped to HAS2p21 and suggested as a candidate gene for CT. We cloned canine ATP6H, which encodes a predicted protein with 99% amino acid sequence identity to the orthologous human protein. Canine ATP6H shows a conserved potential metal binding site, CSVCC, and a glycosylation site, NET. The canine ATP6H is organized into four exons, with a 246-bp open reading frame. Sequence analysis of the coding regions showed no mutations in ATP6H from genomic DNA of an affected dog. We have also identified two, apparently non-transcribed canine ATP6H pseudogenes. Mapping of the true ATP6H gene and a marker closely linked to the CT locus on a canine radiation hybrid panel indicted lack of close physical association. We have therefore excluded canine ATP6H as a candidate gene for canine copper toxicosis, indicating that some other unidentified gene is responsible for this copper storage disease.