A nitrogen model for European catchments: INCA, new model structure and equations

International audienceA new version of the Integrated Nitrogen in Catchments model (INCA) was developed and tested using flow and streamwater nitrate concentration data collected from the River Kennet during 1998. INCA is a process-based model of the nitrogen cycle in the plant/soil and in-stream systems. The model simulates the nitrogen export from different land-use types within a river system, and the in-stream nitrate and ammonium concentrations at a daily time-step. The structure of the new version differs from the original, in that soil-water retention volumes have been added and the interface adapted to permit multiple crop and vegetation growth periods and fertiliser applications. The process equations are now written in terms of loads rather than concentrations allowing a more robust tracking of mass conservation when using numerical integration. The new version is able to reproduce the seasonal dynamics observed in the streamwater nitrogen concentration data, and the loads associated with plant/soil system nitrogen processes reported in the literature. As such, the model results suggest that the new structure is appropriate for the simulation of nitrogen in the River Kennet and an improvement on the original model. The utility of the INCA model is discussed in terms of improving scientific understanding and catchment management. Keywords: modelling, water quality, nitrogen, nitrate, River Kennet, River Thames</p

COVID-19 pandemic: Impact caused by school closure and national lockdown on pediatric visits and admissions for viral and non-viral infections, a time series analysis.

A time series analysis of 871,543 pediatric emergency visits revealed that the COVID-19 lockdown and school closure were associated with a significant decrease in infectious diseases disseminated through airborne or fecal-oral transmissions: common cold, gastro-enteritis, bronchiolitis, acute otitis. No change was found for urinary tract infections

Evaluating the Impact of Nature-Based Solutions: A Handbook for Practitioners

The Handbook aims to provide decision-makers with a comprehensive NBS impact assessment framework, and a robust set of indicators and methodologies to assess impacts of nature-based solutions across 12 societal challenge areas: Climate Resilience; Water Management; Natural and Climate Hazards; Green Space Management; Biodiversity; Air Quality; Place Regeneration; Knowledge and Social Capacity Building for Sustainable Urban Transformation; Participatory Planning and Governance; Social Justice and Social Cohesion; Health and Well-being; New Economic Opportunities and Green Jobs. Indicators have been developed collaboratively by representatives of 17 individual EU-funded NBS projects and collaborating institutions such as the EEA and JRC, as part of the European Taskforce for NBS Impact Assessment, with the four-fold objective of: serving as a reference for relevant EU policies and activities; orient urban practitioners in developing robust impact evaluation frameworks for nature-based solutions at different scales; expand upon the pioneering work of the EKLIPSE framework by providing a comprehensive set of indicators and methodologies; and build the European evidence base regarding NBS impacts. They reflect the state of the art in current scientific research on impacts of nature-based solutions and valid and standardized methods of assessment, as well as the state of play in urban implementation of evaluation frameworks

Combining farmers' decision rules and landscape stochastic regularities for landscape modelling

International audienceLandscape spatial organization (LSO) strongly impacts many environmental issues. Modelling agricultural landscapes and describing meaningful landscape patterns are thus regarded as key-issues for designing sustainable landscapes. Agricultural landscapes are mostly designed by farmers. Their decisions dealing with crop choices and crop allocation to land can be generic and result in landscape regularities, which determine LSO. This paper comes within the emerging discipline called "landscape agronomy", aiming at studying the organization of farming practices at the landscape scale. We here aim at articulating the farm and the landscape scales for landscape modelling. To do so, we develop an original approach consisting in the combination of two methods used separately so far: the identification of explicit farmer decision rules through on-farm surveys methods and the identification of landscape stochastic regularities through data-mining. We applied this approach to the Niort plain landscape in France. Results show that generic farmer decision rules dealing with sunflower or maize area and location within landscapes are consistent with spatiotemporal regularities identified at the landscape scale. It results in a segmentation of the landscape, based on both its spatial and temporal organization and partly explained by generic farmer decision rules. This consistency between results points out that the two modelling methods aid one another for land-use modelling at landscape scale and for understanding the driving forces of its spatial organization. Despite some remaining challenges, our study in landscape agronomy accounts for both spatial and temporal dimensions of crop allocation: it allows the drawing of new spatial patterns coherent with land-use dynamics at the landscape scale, which improves the links to the scale of ecological processes and therefore contributes to landscape ecology.L'organisation du paysage influe sur les problèmes environnementaux. Modéliser les paysages pour les décrire à l'aide de formes significatives est une étage clé. Les paysages agricoles sont principalement construits par les agriculteurs dont les décision d'assolement peuvent être génériques et déterminer des régularités dans l'organisation du paysage. Cet article contribue à l'agronomie des paysage qui est une discipline émergente. Nous cherchons à articuler les échelles du paysage et de l'exploitation agricole en développant deux méthodes : l'une consiste à identifier les décisions des agriculteurs par le bais d'enquêtes, l'autre consiste à retrouver des régularités stochastiques dans le paysage par le bais de fouille de données. Nous avons appliqué cette approche au paysage de la plaine de Niort en France. Les résultats montrent que les décisions des agriculteurs en matière de tournesol et maïs sont génériques et ont des effets sur le paysages que des méthodes de fouille de données révèlent et quantifient

Hedonic estimates of agricultural landscape values in suburban areas

This paper analyses the relationship between housing prices and suburban agriculture zones endowments using the hedonic price methods. We use spatially referenced housing and land-use date to capture the effect of rural amenities around the house location in the area of Angers (France). Results indicate that put higher value on diversified landscapes rather than on unified ones. The proximity to vegetables, grasslands and vineyards do not have a significant impact on house prices while the proximity to forests has a positive impact. This impact differs following the shape of the forest

Effect on nitrate concentration in stream water of agricultural practices in small catchments in Brittany: II. Temporal variations and mixing processes

In catchments with impervious bedrock, the nitrate concentrations in streamwater often show marked seasonal and small inter-annual variations. The inter-annual trends are usually attributed to changes in nitrogen inputs, due to changes in land use or in nitrogen deposition whereas seasonal patterns are explained in terms of availability of soil nitrate for leaching and of seasonality of nitrogen biotransformations. The companion paper showed that inter-annual variations of nitrogen in streamwater are not directly related to the variations of land use. The aim of this study is to describe nitrate concentration variations in a set of very small adjacent catchments, and to discuss the origin of the inter-annual and seasonal trends. Data from four catchments at the Kerbernez site (South Western Brittany, France) were used in this study. Nitrate concentrations in streamwater were monitored for eight years (1992 to 1999) at the outlet of the catchments. They exhibit contrasting inter-annual and seasonal patterns. An extensive survey of agricultural practices during this period allowed assessment of the amount of nitrogen available for leaching. The discharges measured since 1997 show similar specific fluxes but very different seasonal dynamics between the catchments. A simple, lumped linear store model is proposed as an initial explanation of the differences in discharge and nitrate concentration patterns between the catchments. The base flow at the outlet of each catchment is considered as a mixture of water from two linear reservoirs with different time constants. Each reservoir comprises two water stores, one mobile contributing to discharge, the other, immobile, where nitrate moves only by diffusion. The storm flow, which accounts for less than 10% of the annual flux, is not considered here. Six parameters were adjusted for each catchment to fit the observed data: the proportion of deep losses of water, the proportion of the two reservoirs and the size and initial concentration of the two immobile stores. The model simulates the discharge and nitrate concentration dynamics well. It suggests that the groundwater store plays a very important role in the control of nitrate concentration in streamwater, and that the pattern of the seasonal variation of nitrate concentration may result from the long term evolution of nitrogen losses by leaching. Keywords: nitrate, diffuse pollution, groundwater, seasonal variations, agricultural catchment, simulation model</p