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

The added value of high-resolution above coarse-resolution remote sensing images in crop yield forecasting: A case study in the Egyptian Nile Delta

Crop growth models play a major role in sustaining the world-wide food security. These models are used to simulate crop growth during the growing season, and the final crop yield at the end of the growing season, given the farmers’ management practices. At a more strategic level, these crop growth models play an important role to decision makers to take timely decisions regarding food import and/or export strategies. The simulation accuracy of crop growth models relies on the quality of the input data. Since crop yield forecasting applications are often applied over large areas that rely on a spatially distributed crop growth model, the uncertainty in the spatial variation of the input data increases. Remote sensing images are often used in crop growth models because remote sensing images provide spatially distributed input data to these models. These images are available in numerous spatial resolutions, where coarse resolution images are often freely available compared to the more expensive high-resolution images. Therefore, the objective of the current study was to evaluate the added value of high-resolution satellite imagery above coarse-resolution satellite imagery in crop yield forecasting

Why increased extreme precipitation under climate change negatively affects water security

An increase in extreme precipitation is projected for many areas worldwide in the coming decades. To assess the impact of increased precipitation intensity on water security, we applied a regional-scale hydrological and soil erosion model, forced with regional climate model projections. We specifically considered the impact of climate change on the distribution of water between soil (green water) and surface water (blue water) compartments. We show that an increase in precipitation intensity leads to a redistribution of water within the catchment, where water storage in soil decreases and reservoir inflow increases. This affects plant water stress and the potential of rainfed versus irrigated agriculture, and increases dependency on reservoir storage, which is potentially threatened by increased soil erosion. This study demonstrates the crucial importance of accounting for the fact that increased precipitation intensity leads to water redistribution between green and blue water, increased soil erosion, and reduced water security. Ultimately, this has implications for design of climate change adaptation measures, which should aim to increase the water holding capacity of the soil (green water) and to maintain the storage capacity of reservoirs (blue water), benefiting rainfed and irrigated agriculture.</p

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