The hydrological response of the Ourthe catchment to climate change as modelled by the HBV model

The Meuse is an important river in Western Europe, which is almost exclusively rain-fed. Projected changes in precipitation characteristics due to climate change, therefore, are expected to have a considerable effect on the hydrological regime of the river Meuse. We focus on an important tributary of the Meuse, the Ourthe, measuring about 1600 km2. The well-known hydrological model HBV is forced with three high-resolution (0.088°) regional climate scenarios, each based on one of three different IPCC CO2 emission scenarios: A1B, A2 and B1. To represent the current climate, a reference model run at the same resolution is used. Prior to running the hydrological model, the biases in the climate model output are investigated and corrected for. Different approaches to correct the distributed climate model output using single-site observations are compared. Correcting the spatially averaged temperature and precipitation is found to give the best results, but still large differences exist between observations and simulations. The bias corrected data are then used to force HBV. Results indicate a small increase in overall discharge, especially for the B1 scenario during the beginning of the 21st century. Towards the end of the century, all scenarios show a decrease in summer discharge, partially because of the diminished buffering effect by the snow pack, and an increased discharge in winter. It should be stressed, however, that we used results from only one GCM (the only one available at such a high resolution). It would be interesting to repeat the analysis with multiple model

Effecten van landgebruiksveranderingen op gemiddelde en extreme afvoer in het Rijnstroomgebied

Recentelijk heeft veel onderzoek plaatsgevonden om de invloed van klimaatverandering te kwantificeren. Dit kan op verschillende manieren gebeuren, bijvoorbeeld kan er op basis van gemeten data een extreme-waardenverdeling worden geëxtrapoleerd. Een dergelijke aanpak heeft als nadeel dat de aanpak gebaseerd is op statistische kenmerken van het huidige klimaat, terwijl die juist waarschijnlijk veranderen. Een andere mogelijkheid is daarom het doorberekenen van klimaatscenario's zoals die worden gegenereerd met klimaatmodellen. Het landoppervlaktemodel dat in deze studie is gebruikt, namelijk het Variable Infiltration Capacity (VIC) model maakt gebruik van statistische parameters voor de invloed van verzadigde bodems. Het gebied betreft de substroomgebieden van Ruhr, Lahn, Mosel, Main en Necka

Monitoring and profiling with CESAR Observatory

The climate system is complex. Although it is understood in qualitative terms, there are still many physical processes of which the impact on climate change is far from quantifi able. A well-known example of such a process is the interaction between cloud and rainfall formation, aerosols, radiation and the land-atmosphere energy exchange. It is one of the sources of large uncertainty in climate models

Cytokine responses to repeated, prolonged walking in lean versus overweight/obese individuals.

OBJECTIVES: Obesity is characterized by a pro-inflammatory state, which plays a role in the pathogenesis of metabolic and cardiovascular disease. An exercise bout causes a transient increase in pro-inflammatory cytokines, whilst training has anti-inflammatory effects. No previous study examined whether the exercise-induced increase in pro-inflammatory cytokines is altered with repeated prolonged exercise bouts and whether this response differs between lean and overweight/obese individuals. DESIGN: Lean (n=25, BMI 22.9±1.5kg/m2) and age-/sex-matched overweight/obese (n=25; BMI 27.9±2.4kg/m2) individuals performed walking exercise for 30, 40 or 50km per day on four consecutive days (distances similar between groups). METHODS: Circulating cytokines (IL-6, IL-10, TNF-α, IL-1β and IL-8) were examined at baseline and <30min after the finish of each exercise day. RESULTS: At baseline, no differences in circulating cytokines were present between groups. In response to prolonged exercise, all cytokines increased on day 1 (IL-1β: P=0.02; other cytokines: P<0.001). IL-6 remained significantly elevated during the 4 exercise days, when compared to baseline. IL-10, TNF-α, IL-1β and IL-8 returned to baseline values from exercise day 2 (IL-10, IL-1β, IL-8) or exercise day 3 (TNF-α) onward. No significant differences were found between groups for all cytokines, except IL-8 (Time*Group Interaction P=0.02). CONCLUSIONS: These data suggest the presence of early adaptive mechanisms in response to repeated prolonged walking, demonstrated by attenuated exercise-induced elevations in cytokines on consecutive days that occur similar in lean and overweight/obese individuals

Evolutionary leap in large-scale flood risk assessment needed

Current approaches for assessing large-scale flood risks contravene the fundamental principles of the flood risk system functioning because they largely ignore basic interactions and feedbacks between atmosphere, catchments, river-floodplain systems and socio-economic processes. As a consequence, risk analyses are uncertain and might be biased. However, reliable risk estimates are required for prioritizing national investments in flood risk mitigation or for appraisal and management of insurance portfolios. We review several examples of process interactions and highlight their importance in shaping spatio-temporal risk patterns. We call for a fundamental redesign of the approaches used for large-scale flood risk assessment. They need to be capable to form a basis for large-scale flood risk management and insurance policies worldwide facing the challenge of increasing risks due to climate and global change. In particular, implementation of the European Flood Directive needs to be adjusted for the next round of flood risk mapping and development of flood risk management plans focussing on methods accounting for more process interactions in flood risk systems

Grid box-level evaluation of IMERG over Brazil at various space and time scales

This study evaluates the performance of the Integrated Multi-satellitE Retrievals for GPM (IMERG) Final Run product over Brazil by means of multi-temporal and -spatial analyses. The assessment of the IMERG Final Run product is based on six statistics obtained for the period between January-December 2016 (daily, monthly, and annual basis). The analysis consisted of comparing the satellite-based estimates against a ground-based gridded rainfall product created using daily records from 4,911 rain gauges distributed throughout Brazil. Overall, the results show that the IMERG product can effectively capture the spatial patterns of rainfall across Brazil. However, the IMERG product presents a slight tendency in overestimating the ground-based rainfall at all timescales. Furthermore, the performance of the satellite product varies throughout the region. The higher errors and biases are found in the North and Central-West regions, but the low density of rain gauges in those regions can be a source of large deviations between IMERG estimates and observations. A large underestimation of the IMERG data is evident along the coastal zone of the Northeast region, probably due to the inability of the passive microwave and infrared sensors to detect warm-rain processes over land. This study shows that the IMERG product can be a good source of rainfall data to complement the ground precipitation measurements in most of Brazil, although some uncertainties are found and need to be further studied